EcoBalance 2014
The 11th International Conference on EcoBalance

ABSTRACT BOOK
Creating benefit through life cycle thinking
27–30 October 2014, Tsukuba, Japan

Organized by

The Institute ofLife Cycle Assessment, JapanAbstract Book of the 11th International Conference on EcoBalance
Edited by
Yasushi Kondo
Faculty of Political Science and Economics, Waseda University, Japan
Shinsuke Murakami
Graduate School of Engineering, The University of Tokyo, Japan
Yasuhiro Fukushima
Graduate School of Engineering, Tohoku University, Japan
Published on 19 December 2014

This is the collection of abstracts of presentations at EcoBalance 2014, the 11th International Conference on EcoBalance,
held at Tsukuba, Japan, from 27 to 30 October 2014.

This is an Open Access publication licensed under Creative Commons Attribution 4.0 International License.
The details of this license are available at http://creativecommons.org/licenses/by/4.0/.
ISBN 978-4-9907995-0-2
The authors hold the copyright on their own abstracts even though that is not explicitly indicated. The licensee
is The Institute of Life Cycle Assessment, Japan (ILCAJ).
ILCAJ holds the copyright on the other parts of this publication.

©2014 The Institute of Life Cycle Assessment, Japan

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

3

Contents
Organizing Committee �������������������������������������������������������� 4
International Advisory Board ����������������������������������������������� 5
Sponsors ���������������������������������������������������������������������������� 6
Financial Supports �������������������������������������������������������������� 6
Cooperating Government Offices ����������������������������������������� 6
Cooperating Organizations �������������������������������������������������� 6
Exhibitors �������������������������������������������������������������������������� 7
Session List ������������������������������������������������������������������������ 8
Invited Speakers ����������������������������������������������������������������� 9

Program�������������������������������������������������������������������������10
Plenary Sessions������������������������������������������������������� 10
Oral Sessions������������������������������������������������������������� 11
October 28, Tuesday����������������������������������������� 11
October 29, Wednesday������������������������������������ 15
October 30, Thursday��������������������������������������� 20
Poster Session����������������������������������������������������������� 23
Abstracts���������������������������������������������������������������������� 30�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

4

Organizing Committee
Chair
Yasushi Kondo
Waseda University, Japan

Vice-chairs
Yasuhiro Fukushima
Tohoku University, Japan
Shinsuke Murakami
The University of Tokyo, Japan

Members
Ichiro Daigo

The University of Tokyo, Japan

Minako HaraNTT Energy and Environment Systems Laboratories, Japan

Seiji Hashimoto

Ritsumeikan University, Japan

Kiyotada Hayashi

National Agriculture and Food Research Organization (NARO), Japan

Hiroki Hondo

Yokohama National University, Japan

Toshiharu Ikaga

Keio University, Japan

Norihiro Itsubo

Tokyo City University, Japan

Shigemi Kagawa

Kyushu University, Japan

Hideki Kakisawa

The University of Tokyo, Japan

Yuki Kudoh

National Institute of Advanced Industrial Science and Technology (AIST), Japan

Kazuyo Matsubae

Tohoku University, Japan

Yasunari Matsuno

The University of Tokyo, Japan

Shigeyuki Miyamoto

NEC Corporation, Japan

Masaharu Motoshita

National Institute of Advanced Industrial Science and Technology (AIST), Japan

Kenichi Nakajima

National Institute for Environmental Studies (NIES), Japan

Shiro Nakajima

Building Research Institute (BRI), Japan

Michiyasu Nakajima

Kansai University, Japan

Keisuke Nansai

National Institute for Environmental Studies (NIES), Japan

Keiichi Okajima

University of Tsukuba, Japan

Hirokazu Sugiyama

The University of Tokyo, Japan

Yasushi Umeda

The University of Tokyo, Japan

Naoki Yoshikawa

Ritsumeikan University, Japan�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

5

International Advisory Board
Martin Baitz

PE International AG, Germany

Paul H. Brunner

Vienna University of Technology, Austria

Sau Soon Chen

SIRIM Berhad, Malaysia

Mary Ann Curran

BAMAC, Ltd, U.S.A.

Bruno DeBenedetti

DISAT Politecnico di Torino, Italy

James Fava

PE-INTERNATIONAL, U.S.A.

Matthias Finkbeiner

Technical University of Berlin, Germany

Marina Fischer-Kowalski

Institute of Social Ecology Vienna, AAU, Austria

Rolf Frischknecht

treeze Ltd., Switzerland

Shabbir H. Gheewala	The Joint Graduate School of Energy and Environment, King Mongkut's
University of Technology Thonburi, Thailand
Mark Goedkoop

PRé Consultants B.V., The Netherlands

Stefanie Hellweg

ETH Zurich, Switzerland

Edgar Hertwich

Norwegian University of Science and Technology, Norway

Klaus Hubacek

University of Maryland, College Park, U.S.A.

David Hunkeler

AQUA+TECH, Switzerland

Gjalt Huppes

CML, Leiden University, The Netherlands

Tak Hur

Konkuk University, Korea

Walter Klöpffer

LCA Consult & Review, Germany

Michael Kuhndt

Collaborating Centre on Sustainable Consumption and Production, Germany

Kun-mo Lee

Ajou University, Korea

Yuh-Ming Lee

National Taipei University, Taiwan

Manfred Lenzen

The University of Sydney, Australia

Thumrongrut Mungcharoen
	
Kasetsart University and National Science and Technology Development
Agency, Thailand
Shinichiro Nakamura

Waseda University, Japan

Sangwon Suh

University of California, Santa Barbara, U.S.A.

Arnold Tukker

CML, Leiden University, The Netherlands

Sonia Valdivia

UNEP, France

Bo Weidema

Aalborg University, Denmark

Marc-Andree Wolf

maki Consulting, Germany�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

6

Sponsors
Platinum Sponsors:
PE INTERNATIONAL AG
LCA Society of Japan (JLCA)Gold Sponsor:
PRé Consultants
Bronze Sponsors:
TCO2 Co., Ltd.
Pacific Consultants Co., Ltd.
Panasonic Corporation
FUJITSU LIMITEDMITSUBISHI ELECTRIC CORPORATION
Toshiba Corporation
Hitachi, Ltd.
Nissan Motor Co. Ltd.

Financial Supports
City of Tsukuba
The Japan World Exposition 1970 Commemorative Fund, KANSAI OSAKA 21st Century
Association
Tsukuba Tourist and Convention Association
Watanabe Memorial Foundation for the Advancement of New Technology

Cooperating Government Offices
Ministry of Agriculture, Forestry and Fisheries
Ministry of Education, Culture, Sports, Science and Technology
Ministry of Economy, Trade and Industry
Ministry of Land, Infrastructure and Transport
Ministry of the Environment

Cooperating Organizations
Architectural Institute of Japan

Industries Association

Center for Environmental Information Science

Japan Chain Stores Association

Communications and Information network Associationof Japan
Green Purchasing Network (GPN)

Japan Chemical Fibers Association
Japan Chemical Industry Association (JCIA)

Japan Aluminium Association

Japan Electronics and Information Technology
Industries Association

Japan Association for Chemical Innovation

Japan Environment Association

Japan Association for Techno-innovation in
Agriculture, Forestry and Fisheries

Japan Federation of Construction Contractors

Japan Automobile Manufacturers Association, Inc.

Japan LP Gas Association

Japan Business Machine and Information System

Japan Greenhouse Horticulture Association
Japan Packaging Institute�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

7

Japan Petrochemical Industry Association

The Japan Institute of Energy

Japan PVC Environmental Affairs Council

The Japan Institute of Light Metals

Japan Society for Atmospheric Environment

The Japan Institute of Metals and Materials

Japan Society of Civil Engineers

The Japan Iron and Steel Federation

Japan Society of Energy and Resources

The Japan Petroleum InstituteJapan Society of Material Cycles and Waste
Management

The Japan Reinforced Plastics Society

Japan Society of Powder and Powder Metallurgy

The Japan Society for Composite Materials

Japanese Consumers' Co-operative Union
Japanese Society of Agricultural Machinery and FoodEngineers
Japanese Society of Farm Work Research
Japanese Society of Soil Science and Plant Nutrition
JSPS 143rd Committee on Process Systems
Engineering
Manufacturing Science and Technology Center
National Institute for Materials Science
Nippon Association of Consumer Specialists
Pesticide Science Society of Japan
Petroleum Association of Japan
Plastic Waste Management InstituteResearch Institute of Innovative Technology for the
EarthSociety for Environmental Economics and Policy
StudiesSociety of Environmental Science, Japan
SOKEIZAI Center
The Agricultural Society of JapanThe Building Center of JapanThe Ceramic Society of JapanThe Committee for the Promotion of Recycling ofConstruction By-Product
The Engineering Academy of JapanThe High Pressure Gas Safety Institute of JapanThe Institute of Electrical Engineers of JapanThe Iron and Steel Institute of JapanThe Japan Electrical Manufacturers' Association
The Japan Gas Association

The Japan Rubber Manufacturers Association
The Japan Society for Precision Engineering
The Japan Society for Technology of Plasticity
The Japan Society of Industrial Machinery
Manufacturers
The Japan Society of Mechanical Engineers
The Japan Wood Research Society
The Japanese Society for Biomaterials
The Japanese Society for Food Science andTechnology
The Materials Research Society of Japan (MRS-J)
The Mining and Materials Processing Institute ofJapan (MMIJ)The Society for Risk Analysis JapanThe Society of Chemical Engineers, JapanThe Society of Heating, Air-Conditioning and SanitaryEngineers of JapanThe Society of Materials Science, JapanThe Society of Polymer Science, JapanThe Society of Rubber Science and Technology, JapanThe Surface Finishing Society of Japan
Thermal and Nuclear Power Engineering Society
Union of EcoDesigners
Vinyl Environmental Council
Water Reuse Promotion Center
Wood Technological Association of Japan
Ministry of Agriculture, Forestry and Fisheries
Ministry of Education, Culture, Sports, Science andTechnology
Ministry of Economy, Trade and Industry
Ministry of the Environment

Exhibitors
TCO2 Co., Ltd.
PE Asia corporation
ifu Hamburg GmbH�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

8

Session List▲

Plenary Sessions
Opening Plenary
Closing Plenary▲

Special Sessions
Tsukuba Special Session
28B3
Sustainability in the Chemical Industry
28A3–28A4
Global Food Security and Corporate Practices from Life Cycle Perspectives
Global Strategies on Agriculture, Food, and Nutrients
28C3
Evaluating Management Practices
28C4
Resource Management in Agriculture
28C5
Green ICT
28D3–28D4
Sustainability of Materials and Industries
Evaluation of Urban Mining
29F1
State-of-the-Art of Research and Developments in Ecomaterials for Low Carbon Society
29F2
Technologies and Assessments for Recovering Materials from Urban Mining
29F3
The Practical Challenge for Sustainable Industry
Challenges, Experiences and Lessons
29C1
Organizational LCA (O-LCA): Concepts and Methodologies
29C2
Organizational LCA (O-LCA): Lessons from Application Studies
29C3
Sustainable value chain management by MFCA
30C1
Keys for the breakthrough in business
30C2
Sustainable Resource Management
30A1–30A2▲

General Sessions
Estimating the Contribution to Avoided Emissions
Material Flow Analysis
E-wasteDriving innovation
LCA Methodology
Supply Chain Risk Management
City & Building
Behavior & Policy
Policy & Visualization
Agriculture & Foods
EnergyWaste Management & Recycling
Water

28A5
28B4
28B5
28D5
29D1
29D2
29D3
29E1
29E2
29E3
29G1–29G2
30B1–30B2
30D1–30D2�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

9

Invited Speakers
Keynote 1 Values of life cycle thinking
Junko Edahiro (Institute for Studies in Happiness, Economy and Society; Environmental Journalist, Japan)

Keynote 2 Business strategies and environmental visions in the Hitachi
Ryuichi Otsuki (Hitachi, Ltd., Japan)

Keynote 3	Life cycle based sustainability solutions: How successful companies turnsustainability solutions into company benefit and business value
Martin Baitz (PE International AG, Germany)

Closing

EcoBalance+20
Matthias Finkbeiner (Technische Universität Berlin, Germany)
Guido Sonnemann (University of Bordeaux, France)
Kohmei Halada (National Institute for Materials Science, Japan)
Atsushi Inaba (Kogakuin University, Japan)

28A3-1

Decision-support tools for designing sustainable chemical products and processes
Konrad Hungerbühler (ETH Zurich, Switzerland)

28B3-2

Hydrocarbon production from microalgae and its potential commercial use
Makoto M Watanabe (University of Tsukuba, Japan)

28B3-3

Mobility robot technologies in AIST for green innovation
Osamu Matsumoto (National Institute of Advanced Industrial Science and Technology, Japan)

28C3-1

Japanese nitrogen footprint model for the prediction of nitrogen loss to the environment
Hideaki Shibata (Hokkaido University, Japan)

28C3-3

Scientific robustness of including indirect land use change into life cycle assessment
Matthias Finkbeiner (Technische Universität Berlin, Germany)

28C4-2	Environmental impacts of organic rice farming in Thailand by using life cycle
assessment to support policy decision on sustainable agriculture
Rattanawan Mungkung (Kasetsart University, Thailand)

28C4-3

Water footprint assessment of crops cultivation in Kurdistan Region, Iraq
Marlia Mohd Hanafiah (National University of Malaysia, Malaysia)

28C4-4	Life cycle assessment of biogas production in small-scale household digesters in Vietnam
Van Thi Khanh Vu (National Institute of Animal Sciences, Viet Nam)

28D3-1Analyzing the carbon emissions of cloud computing facilities
Kendra Tupper (City of Boulder, U.S.A.)

29C2-1A new direction for LCA: Organizational LCA
Matthias Finkbeiner (Technische Universität Berlin, Germany)
Atsushi Inaba (Kogakuin University, Japan)

29F2-2	
Ultra-high temperature materials for higher-efficiency energy conversion of heat engines
Kyosuke Yoshimi (Tohoku University, Japan)

29F2-3	Advanced green innovation discovered by self-healing ceramics
Wataru Nakao (Yokohama National University, Japan)

29F3-1	Minor rare metals concentration from e-waste by combining novel comminution
and physical separation
Shuji Owada (Waseda University, Japan)

29F3-2

Metal recovery from urban mines by hydrometallurgical methods
Mikiya Tanaka (National Institute of Advanced Industrial Science and Technology, Japan)

30C1-1	Material flow cost accounting: Simple approach, untapped opportunities, upcoming tasks
Bernd Wagner (University of Augsburg, Germany)�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan10

Wed 29 Oct

Tue 28 Oct

Opening Plenary
Opening Ceremony and Keynote Lectures（Main Convention Hall）10:00−12:00 October 28, Tuesday

Chair : Y. Fukushima
Vice-chair of EcoBalance 2014

Opening address

10:00–10:05

Welcome address

10:05–10:10

Keynote 1

10:10–10:50

Yasushi Kondo
Chair of EcoBalance 2014
Kenichi Ichihara
Mayor, City of Tsukuba

Values of life cycle thinking
Junko Edahiro
Institute for Studies in Happiness, Economy and Society; Environmental Journalist, Japan

Keynote 2

10:50–11:30

Business strategies and environmental visions in the Hitachi

Thu 30 Oct

Ryuichi Otsuki
Chief Strategy Officer, Information & Telecommunication Systems Company, Hitachi, Ltd., Japan

Keynote 3

11:30–11:50

Life cycle based sustainability solutions: How successful companies
turn sustainability solutions into company benefit and business value
Martin Baitz
Director Content, PE International, Germany

Closing address

11:50–12:00

Shinsuke Murakami
Vice-chair of EcoBalance 2014

Closing Plenary
Special Panel Discussion and Closing Ceremony（Convention Hall 300）13:30–16:00 October 30, Thursday

Special panel discussion

13:30–15:00
Chair : N. Itsubo

EcoBalance+20
Matthias Finkbeiner
Professor, Department of Environmental Technology, Technical University of Berlin; Chairperson, ISO/TC 207/SC 5
Life Cycle Assessment
Guido Sonnemann
Professor, ISM-CyVi, University of Bordeaux; Co-founder and former Programme Officer, the UNEP/SETAC Life
Cycle Initiative
Kohmei Halada
NIMS Invited Researcher, Research Center for Strategic Materials, National Institute for Materials Science; President,
The Institute of Life Cycle Assessment, Japan
Atsushi Inaba
Professor, Department of Environmental and Energy Chemistry, Kogakuin University; Former President of The
Institute of Life Cycle Assessment, Japan

Closing ceremony

15:00–16:00

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

11

Oral Sessions
28A3（Room 101）13:30−14:50 October 28, Tuesday

Sustainability in the Chemical Industry-1
Chair : H. Sugiyama and M. Yoshikiyo

28A3-1 (invited)
13:30−14:10
Decision-support tools for designing sustainablechemical products and processes

28A3-3

14:10−14:30
Development of the risk-based management systemfor chemicals throughout the supply chain
Fumiaki Shono, Satoshi Tokushige
Japan Chemical Industry Association

Emi Kikuchi-Uehara, Yasunori Kikuchi, Masahiko Hirao
The University of Tokyo
28A4（Room 101）15:10−16:30 October 28, Tuesday

Sustainability in the Chemical Industry-2
Chair : H. Sugiyama and M. Yoshikiyo

28A4-1

15:10−15:30
The use of LCA as a metrics in advancing and scaling
up green chemistry research: The case of black
liquorAmandine Foulet, Hervé Deleuze, Philippe Garrigues,
Guido Sonnemann
University of Bordeaux

28A4-2

15:30−15:50
Sulphur distribution to products in wet biomass
gasification
Kenji Koido, Yutaro Watanabe, Kiyoshi Dowaki
Tokyo University of Science

28A4-3

15:50−16:10
Estimating reduction of environmental load forresource recovery from plastic waste by LCA
methodology and plastic waste processing pathways
Akihiro Izumi, Hajime Munekuni
Plastic Waste Management Institute

28A4-4
16:10−16:30
Applying c-LCA for challenges to global warming at
Asahi Kasei Corp.
Junichi Nakahashi
Asahi Kasei Corporation

28A5-1

16:50−17:10
Guideline on quantifying and reporting the avoided
emissions of products
Motozo Yoshikiyo, Kiyoshi Kasai
Japan Chemical Industry Association

28A5-2

17:10−17:30
Establishment of Kawasaki mechanism, thecertification program of avoided emissions outside
Kawasaki city
Shoichiro Tsuruta1), Masayuki Kanzaki1),
Akikazu Kobayashi2), Toshifumi Takamizawa2),
Ichiro Daigo3)
1)
Japan Environmental Management Association for Industry,)
2)
City of Kawasaki, 3 The University of Tokyo

28A5-3

17:30−17:50
Program for assessing the contribution of businessactivities to avoided emissions in Shiga Prefecture,Japan
Maki Ogura1), Takeshi Matsuda1), Ryota Ii1),
Madoka Kaito2), Kazuomi Okuda2))
1)
Pacific Consultants Co., Ltd., 2 Shiga Prefecture

28A5-4

17:50−18:10
Neutralize CO2 emissions by product contributions
Ryo Yokoyama, Tetsuya Kuwashima, Yasuyuki Fujioka,
Masaru Hirose
TDK Corporation
28B3（Room 102）13:30−14:50 October 28, Tuesday

Tsukuba Special Session
Chair : K. Okajima

28B3-1

13:30−13:40
Introduction: Tsukuba Environmental Style “SMILe”
Tomokazu Ueta
City of Tsukuba

28B3-2 (invited)
13:40−14:10
Hydrocarbon production from microalgae and its
potential commercial use
Makoto M Watanabe
University of Tsukuba

28B3-3 (invited)
14:10−14:40
Mobility robot technologies in AIST for green
innovation
Osamu Matsumoto
National Institute of Advanced Industrial Science and Technology

Discussion



14:40−14:50

��������������������������������������������� ProgramThu 30 Oct

28A3-4
14:30−14:50
Chemicals management for sustainability in small
and medium-sized enterprises

Chair : A. Inaba

Wed 29 Oct

Konrad Hungerbühler, Stavros Papadokonstantakis
ETH Zurich

28A5（Room 101）16:50−18:10 October 28, Tuesday

Estimating the Contribution to Avoided Emissions

Tue 28 Oct▲

October 28, TuesdayEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan12

Thu 30 Oct

Wed 29 Oct

Tue 28 Oct

Oral Sessions
28B4（Room 102）15:10−16:30 October 28, Tuesday

Material Flow Analysis
Chair : W.R. Poganietz

28B4-1

15:10−15:30
Spatial cluster analysis of global metal flows
Shigemi Kagawa1), Keisuke Nansai2), Yasushi Kondo3))
1)
Kyushu University, 2 National Institute for Environmental
3),
Studies Waseda University

28B4-2

15:30−15:50
Impact of resource-use intensity of goods andservices and demand structure on national resource
productivity: Time series analysis for 10 countries
Arata Ito, Seiji Hashimoto
Ritsumeikan University

28B4-3

15:50−16:10
Selection of products for remanufacturing based on
the designs of end of life products
Aditi D Joshi1), Surendra M Gupta1), Tetsuo Yamada2))
1)
Northeastern University, 2 The University of ElectroCommunications

28B4-4
16:10−16:30
Mathematical formulation of urban mines design
problem
Shinsuke Kondoh, Hitoshi Komoto, Keijiro Masui
National Institute of Advanced Industrial Science and Technology
28B5（Room 102）16:50−18:10 October 28, Tuesday

E-wasteChair : G. Sonnemann

28B5-1

16:50−17:10
Sorted collection of used batteries and small home
appliances by municipalities
Atsushi Terazono1), Masahiro Oguchi1), Shigenori Iino2),
Satoshi Mogi3))
1)
National Institute for Environmental Studies, 2 Tokyo
Metropolitan Research Institute for Environmental Protection,
3)
Bureau of Environment, Tokyo Metropolitan Government

28B5-2

17:10−17:30
Life cycle assessment of an automotive lithium-ion
battery in large-scale commercial production
Hyung Chul Kim, Timothy J. Wallington
Ford Motor Company

28B5-3

17:30−17:50
The impact of demographic change in Japan on
supply security footprint of critical metals

28B5-4

17:50−18:10
Material flow analysis of heavy metals incontaminated soil: A case study on the polluted sites
in Taoyuan County, Taiwan
Rong-Hua Lee, Yuh-Ming Lee
National Taipei University
28C3（Room 201）13:30−14:50 October 28, Tuesday

Global Food Security and Corporate Practices from
Life Cycle Perspectives-1
Chair : K. Hayashi

28C3-1 (invited)
13:30−13:50
Japanese nitrogen footprint model for the predictionof nitrogen loss to the environment
Hideaki Shibata1), Lia R Cattaneo2), Allison M Leach2),
James N Galloway2))
1)
Hokkaido University, 2 University of Virginia

28C3-2

13:50−14:10
Aggregation of biodiversity impacts acrossinternational value chains
Jan Paul Lindner1,2), Laura Brethauer1,2), Ulrike Bos1,2),
Rainer Luick3), Michael Jäger2)))
1)
Fraunhofer IBP, 2 University of Stuttgart, 3 University of Applied
Forest Sciences Rottenburg

28C3-3 (invited)
14:10−14:30
Scientific robustness of including indirect land usechange into life cycle assessment
Matthias Finkbeiner
Technische Universität Berlin

28C3-4
14:30−14:50
Future perspectives on LCA in agriculture: Lessons
from the research in Japan
Masanori Saito
Tohoku University
28C4（Room 201）15:10−16:30 October 28, Tuesday

Global Food Security and Corporate Practices from
Life Cycle Perspectives-2
Chair : M. Saito

28C4-1

15:10−15:30
Assessing impacts of land use change andmanagement intensification: A life cycle perspective
on agricultural production
Kiyotada Hayashi
National Agriculture and Food Research Organization

Yosuke Shigetomi1,2,3), Keisuke Nansai2), Susumu Tohno1))
1)
Kyoto University, 2 National Institute for Environmental Studies,3)
JSPS Research Fellow

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

13

Oral Sessions

Rattanawan Mungkung, Patthra Pengthamkeerati,
Ratcha Chaichana, Saranya Watcharothai,
Kittiwan Kitpakornsanti, Supachok Tapananont
Kasetsart University

Marlia Mohd Hanafiah1), Hushiar Raheem Hamarash1),
Muhammad Muaz Aminordin1), Shabbir Gheewala2,3))
1)
National University of Malaysia, 2 The Joint Graduate School ofEnergy and Environment, King Mongkut's University of)Technology Thonburi, 3 Ministry of Education, Thailand

Van Thi Khanh Vu, Quynh Duong Vu, Lars S. Jensen,
Sven G. Sommer, Sander Brunn
National Institute of Animal Sciences, Vietnam
28C5（Room 201）16:50−18:10 October 28, Tuesday

Global Food Security and Corporate Practices from
Life Cycle Perspectives-3
Chair : H.Shibata

28C5-1

16:50−17:10
Resource logistics for sustainable management ofagricultural nutrients
Kazuyo Matsubae1), Kenichi Nakajima2), Keisuke Nansai2),
Tetsuya Nagasaka1))
1)
Tohoku University, 2 National Institute for Environmental
Studies

28C5-2

17:10−17:30
Monetary and physically flow analyses on productsof agriculture
Yuko Oshita1), Yasunori Kikuchi2))
1)
Kobe University, 2 The University of Tokyo

28C5-3

17:30−17:50
Evaluation of environmental improvement byintroduction of eco-feed
Hongqin Yu, Hiroshi Yagita
Nippon Institute of Technology

28C5-4

17:50−18:10
Uncertainty analysis for greenhouse gas impact offeedstuff in Korea
Yoosung Park, Minhyeok Lee, Kunmo Lee
Ajou University

Chair : M. Hara

28D3-1 (invited)
13:30−13:50
Analyzing the carbon emissions of cloud computing
facilities
Kendra Tupper
City of Boulder

28D3-2

13:50−14:10
New key performance indicators for smart
sustainable city
Jiro Nakamura, Minako HaraNTT Energy and Environment Systems Laboratories

28D3-3

14:10−14:30
Social impact assessment of ICT services: Case study
and tool realization
Julien Boisseau1), Tomoko Tanaka1), Ahmed Zeddam1),
Kazue Takahashi2), Takashi Sawada2))
1)
Orange Japan, 2 NTT Energy and Environment Systems
Laboratories

28D3-4
14:30−14:50
Multiple environmental impact assessment methodon biodiversity for industry
Kazue Ichino Takahashi1), Eri Matsunaga1),
Takashi Sawada1), Norihiro Itsubo2), Masaharu Motoshita3),
Kayo Murakami4))
1)
NTT Energy and Environment Systems Laboratories, 2 Tokyo
3)
City University, National Institute of Advanced Industrial)
Science and Technology, 4 Kyoto University
28D4（Room 202）15:10−16:30 October 28, Tuesday

Green ICT-2
Chair : K. Tupper

28D4-1

15:10−15:30
Case study on effect of mechanics development oftelecommunication product on material efficiency
Lauri Smalén1), Elisabeth Dechenaux2), Topi Volkov1),
Timo Galkin1), Timo Junno1), Heikki Karvinen3),
Marc Aubree2)))
1)
Nokia Solutions and Networks, 2 Orange Labs, 3 Aalto University

28D4-2

15:30−15:50
Five IT thoughts from a waste management proofof-concept project
Yukihisa Yonemochi, Takashi Sakairi, Hiroshi Horii,
Tatsuya Ishikawa, Scott Trent, Heather D Achilles
IBM Research

28D4-3

15:50−16:10
Environmental footprint for IT equipment
Takaaki Kumazawa, Osamu Namikawa
Hitachi, Ltd.

��������������������������������������������� ProgramThu 30 Oct

28C4-4 (invited)
16:10−16:30
Life cycle assessment of biogas production in smallscale household digesters in Vietnam

Green ICT-1

Wed 29 Oct

28C4-3 (invited)
15:50−16:10
Water footprint assessment of crops cultivation in
Kurdistan region, Iraq

28D3（Room 202）13:30−14:50 October 28, Tuesday

Tue 28 Oct

28C4-2 (invited)
15:30−15:50
Environmental impacts of organic rice farming in
Thailand by using life cycle assessment to support
policy decision on sustainable agricultureEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan14

Wed 29 Oct

Tue 28 Oct

Oral Sessions
28D4-4
16:10−16:30
Analysis of influence of ICT services including
application-service and network-service on CO2emission
Jiro Nakamura, Tomomi Nagao, Yuichiro Takei,
Atsushi Sakurai, Shinsuke Hannoe, Keiichi Saito
NTT Energy and Environment Systems Laboratories
28D5（Room 202）16:50−18:10 October 28, Tuesday

Driving innovation
Chair : M. Sagisaka

28D5-1

16:50−17:10
Measuring social impacts of products: The Handbookof the Roundtable for Social Metrics

Thu 30 OctJoão Fontes, Mark Goedkoop, Anne Gaasbeek
PRé Consultants B.V.

28D5-2

17:10−17:30
Policies promoting ecodesign for energy andresource efficiency in Europe: Experiences, barriers
and future options
Carl Johan Dalhammar
Lund University

28D5-3

17:30−17:50
Reverse flow of knowledge and the development ofsustainable energy systems
Harald Ernst Otto
Polytechnic University of Marche

28D5-4
Canceled



17:50−18:10

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

15

Oral Sessions
29C1（Room 201）9:00−10:20 October 29, Wednesday

The Practical Challenge for Sustainable Industry-1
Chair : M. Motoshita

29C1-1
Hitachi’s CO2 visualization effort

9:00−9:20

Sachiko Motoike, Hideki Sasaki, Hiroshi Onishi
Panasonic Corporation
29C3（Room 201）13:30−14:50 October 29, Wednesday

The Practical Challenge for Sustainable Industry-3

29C1-2

9:20−9:40
Challenges to biofuel production enhancing foodproduction: A food and beverage alcohol company
perspective
Satoshi Ohara, Akira Sugimoto, Kazutoshi Kitai,
Takaomi Yasuhara
Asahi Group Holdings, Ltd.

Lucia Rigamonti1), Mario Grosso1), Mino Leo Marucci2))
1)
Politecnico di Milano, 2 Reno De Medici S.p.A.

29C1-4
10:00−10:20
Policy options for LCA deployment in automotive
industry
Annekatrin Lehmann1), Matthias Finkbeiner1),
Kirana Wolf 1), Cees ten Broek2))
1)
Technische Universität Berlin, 2 World Steel Association
29C2（Room 201）10:40−12:00 October 29, Wednesday

The Practical Challenge for Sustainable Industry-2
Chair : M. Nakajima

29C2-1 (invited)
10:40−11:00
A new direction for LCA: Organizational LCA
Matthias Finkbeiner1), Julia Martínez-Blanco1),
Atsushi Inaba2))
1)
Technische Universität Berlin, 2 Kogakuin University

29C2-2

11:00−11:20
Guidance on organizational LCA by the UNEP/SETACLife Cycle Initiative
Julia Martínez-Blanco1), Sonia Valdivia2), Ana Quiros3),
Llorenç Milà i Canals5), Atsushi Inaba4),
Matthias Finkbeiner1))
1)
Technische Universität Berlin, 2 World Resources Forum,)
3)
4)
ECOGLOBAL, Kogakuin University, 5 UNEP-SETAC Life
Cycle Initiative

29C2-3

11:20−11:40
Activity to evaluate a positive impact of anorganization
Seiya Yamazaki, Hiroko Ioka, Takafumi Hashitani
Fujitsu limited

29C3-1

13:30−13:50
Estimating multiple changes of GHG emissions on
mitsubishi electric group's supply chain; category11possible variation of GHG during use stage
Chie Uchiyama
Mitsubishi Electric Corporation

29C3-2

13:50−14:10
What allocation method should be taken to provide
the data for SCOPE3 by supplier to customer? An
example of the printing company
Hiromichi Sasaki, Nobuyasu Tanaka
Sun Messe Co., Ltd.

29C3-3

14:10−14:30
Water consumption evaluation along the supply
chain
Junichi Nakahashi
Asahi Kasei Corporation

29C3-4
14:30−14:50
Supply-chain environmental assessment forsustainable procurement
Kenji Ohashi
Shiseido Co., ltd.
29D1（Room 202）9:00−10:20 October 29, Wednesday

LCA Methodology
Chair : Y-M. Lee

29D1-1

9:00−9:20
GreenGDP study based on life cycle impact
assessment of refinery sector in Thailand
Kultida Kunanuntakij1), Viganda Varabuntoonvit1),
Natanee Vorayos2), Thumrongrut Mungcharoen1))
1)
Kasetsart University, 2 ChiangMai University

29D1-2

9:20−9:40
Fast screening of alternative life cycles and system
optimization using flexibly linkable process
subsystems
Bernhard Steubing, Chris Mutel, Florian Suter,
Stefanie Hellweg
ETH Zurich��������������������������������������������� ProgramThu 30 Oct

9:40−10:00

Chair : M. Motoshita

Wed 29 Oct

Tetsuichi Nomiyama, Hitoshi Maekawa
Hitachi, Ltd.

29C1-3Experience of EPD process certification

29C2-4

11:40−12:00
Proposal for a supplementary calculation method for
scope 3 emissions

Tue 28 Oct▲

October 29, WednesdayEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan16

Wed 29 Oct

Tue 28 Oct

Oral Sessions
29D1-3
9:40−10:00
Investigation of the differences between staticand probabilistic LCA/LCC results of different floor
finishes
Gantner Johannes1), William Fawcett2), Matthias Fischer3))
1)
University of Stuttgart, 2 Cambridge Architectural Research Ltd,
3)
Fraunhofer IBP

29D1-4
10:00−10:20
Supporting uncertainty evaluation in prospective
assessment of innovations: A case on ecologicalmethod in shrimp farming
1)

1)

2)

Heng Yi Teah , Yasuhiro Fukushima , Motoharu Onuki)
1)
National Cheng Kung University, 2 The University of Tokyo
29D2（Room 202）10:40−12:00 October 29, Wednesday

Thu 30 Oct

Supply Chain Risk Management
Chair : K. Tahara

29D2-1

10:40−11:00
Development of supply-chain matrix database withIDEA aiming for the application to consequential
LCA
Kiyotaka Tahara1), Masaharu Motoshita1,3),
Kotaro Kawajiri1), Hiroki Hatayama1), Chunyoul Baek1),
Tomohiko Ihara2)
1)
National Institute of Advanced Industrial Science and))Technology, 2 The University of Tokyo, 3 Technische Universität
Berlin29D2-2

11:00−11:20
Resolution of nuclear power plant construction
conflicts: Argument of tsunami issues throughconcept mapping and lifecycle thinking
Ting-Fang Hsieh, Yuh-Ming Lee
National Taipei University

29D2-3

11:20−11:40
LCA system boundary selection using the industrial
clustering analysis
Shunsuke Okamoto
Kyushu University

29D2-4

11:40−12:00
Assessing climate impact of industrial symbioses: A
dynamic approach
François Dumoulin1,2), Tom Wassenaar1),
Jean-Marie Paillat1))
1)
CIRAD, 2 ADEME

29D3（Room 202）13:30−14:50 October 29, Wednesday

City & Building
Chair : T. Ikaga

29D3-1

13:30−13:50
Towards a low-carbon future in China’s rural
residential sector
Rui Xing, Tatsuya Hanaoka, Yuko Kanamori,
Hancheng Dai, Toshihiko Masui
National Institute for Environmental Studies

29D3-2

13:50−14:10
Exploring intersection of product lifecycles: GHG
emissions associated with vehicles and pavement
influenced by pavement maintenance strategies
Yasuhiro Fukushima, Fitria, Shih-Hsien Yang
National Cheng Kung University

29D3-3

14:10−14:30
A cradle-to-cradle assessment framework forgreen building evaluation: Emphases on energy
management and resource recovery
Chia-Lin Hsu, Yuh-Ming Lee
National Taipei University

29D3-4
14:30−14:50
A life cycle assessment of silica sand: Comparing thebeneficiation processes
Anamarija Grbes
Faculty of Mining, Geology and Petroleum Engineering, Zagreb,
Croatia29E1（Room 303）9:00−10:20 October 29, Wednesday

Behavior & Policy
Chair : H. Hondo

29E1-1

9:00−9:20
A life cycle thinking assessment framework for land
reclamation policy in Taiwan
Lih-Ren Liu, Yuh-Ming Lee
National Taipei University

29E1-2

9:20−9:40
Constructing a system thinking model for climate
policy making based on national GHG inventory
Yu-Tsang Lu, Yuh-Ming Lee
National Taipei University

29E1-3
9:40−10:00
Evaluating the change of psychological factors andpro-environmental behaviors through workshop
about life cycle thinking and norms
Eri Aoki, Kiyo Kurisu, Keisuke Hanaki
The University of Tokyo

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

17

Oral Sessions
29E3-2

13:50−14:10
Total material requirement of food production andrelated materials in Japan
Eiji Yamasue1), Kazuyo Matsubae2), Keiichi N Ishihara1))
1)
Kyoto University, 2 Tohoku University

Ai Hiramatsu, Kiyo Kurisu
The University of Tokyo
29E2（Room 303）10:40−12:00 October 29, Wednesday

Chair : K. Nansai

29E2-1

10:40−11:00
Visualizing core structure of international carbon
network associated with household consumption
Yasushi Kondo
Waseda University

Thumrongrut Mungcharoen1,2),
Thumrongrut Mungcharoen1,2)1)National Science and Technology Development Agency,
2)
Kasetsart University

29E2-3

11:20−11:40
Thai CF Pro: A web-based program for evaluating
carbon footprint of product1)

1)

Chantana Yuvaniyama , Wanwisa Thanungkano ,Ruthairat Wisansuwannakorn1), Athiwatr Jirajariyavech1),
Thepchai Supnithi2), Nattapol Kritsuthikul2),
Thumrongrut Mungcharoen3))
1)
National Metal and Materials Technology Center, 2 National
3)
Electronics and Computer Technology Center, National Scienceand Technology Development Agency

29E2-4

11:40−12:00
Visualization of comprehensive environmental
impacts
Yoshinori Kobayashi, Kiyoshi Sanehira
Toshiba Corporation
29E3（Room 303）13:30−14:50 October 29, Wednesday

Agriculture & Foods
Chair : R. Mungkung

29E3-1

13:30−13:50
Life cycle assessment of environmental impacts ofcrop residue management and manure application in
Japanese rice cultivation
Ai Leon, Yasuhito Shirato, Shin-ichi Yoshimatsu,
Seiya Tsushima, Kazuyuki Yagi, Kazunori Kohyama
National Institute for Agro-Environmental Sciences

29E3-4
14:30−14:50
Ecoefficiency analysis of integrated and nonintegrated crop, forestry and livestock production
systems in the Brazilian Cerrado
Marcela Porto Costa1,2), Sueli Aparecida de Oliveira1),
Gerson Araujo de Medeiros2))
1)
FEE- Espaço ECO Foundation- BASF, 2 UNESP- Universidade
Estadual Paulista Julio de Mesquita Filho -Sorocaba
29F1（Room 405）9:00−10:20 October 29, Wednesday

Sustainability of Materials and Industries-1
Chair : Y. Matsuno

29F1-1

9:00−9:20
How much does urban mining reduce theenvironmental burden?
Kohmei Halada
National Institute for Material Science

29F1-2

9:20−9:40
Designing strategic urban mining in Japan for
criticality mitigation
Hiroki Hatayama1), Kiyotaka Tahara1), Ichiro Daigo2)
1)
National Institute of Advanced Industrial Science and)Technology, 2 The University of Tokyo

29F1-3
9:40−10:00
Comparison of end-of-life recycling rates of common
metals in Japan
Ichiro Daigo, Kohei Iwata, Yoshikazu Goto
The University of Tokyo

29F1-4
10:00−10:20
Framework and applications of time-series material
flow and stock analysis
Shotaro Nakanishi, Jun Nakatani, Yuichi Moriguchi
The University of Tokyo��������������������������������������������� ProgramThu 30 Oct

29E2-2

11:00−11:20
Life cycle inventory database and its applications to
support public policy in Thailand

Joana Almeida1), Jeroen Degerickx1), Wouter M J Achten2),
Bart Muys1))
1)
KU Leuven, 2 Universite Libre de Bruxelles

Wed 29 Oct

Policy & Visualization

29E3-3

14:10−14:30
Land use change related CO2 emissions in the LCA of
biofuel-based electrification in Mali

Tue 28 Oct

29E1-4
10:00−10:20
People’s environmental consciousness in daily
activities

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan18

Thu 30 Oct

Wed 29 Oct

Tue 28 Oct

Oral Sessions
29F2（Room 405）10:40−12:00 October 29, Wednesday

Sustainability of Materials and Industries-2
Chair : H. Kakisawa

29F2-1

10:40−11:00
Value added material flow analysis of NdFeB
magnets in Denmark
Komal Habib, Henrik Wenzel
University of Southern Denmark

29F2-2 (invited)
11:00−11:20
Ultra-high temperature materials for higherefficiency energy conversion of heat engines
Kyosuke Yoshimi
Tohoku University

Yasunori Kikuchi1), Masahiko Hirao1),
Hirokazu Sugiyama1,2), Stavros Papadokonstantakis2),
Konrad Hungerbühler2), Takashi Ookubo3),
Akinobu Sasaki3)))
1)
The University of Tokyo, 2 ETH Zurich, 3 Mitsubishi Rayon, Co.,Ltd.
29G1（Room 406）9:00−10:20 October 29, Wednesday

Energy-1
Chair : K. Okajima

29F2-3 (invited)
11:20−11:40
Advanced green innovation discovered by selfhealing ceramics
Wataru Nakao
Yokohama National University

29F2-4

11:40−12:00
Environmental barrier coating on SiC fiber-reinforced
SiC matrix composites for low pressure turbine in jetengineHideki Kakisawa
The University of Tokyo
29F3（Room 405）13:30−14:50 October 29, Wednesday

Sustainability of Materials and Industries-3
Chair : K. Halada

29F3-1 (invited)
13:30−13:50
Minor rare metals concentration from e-waste
by combining novel comminution and physicalseparation
Shuji Owada, Chiharu Tokoro
Waseda University

29F3-2 (invited)
Metal recovery from urban mines byhydrometallurgical methods
1)

29F3-4
14:30−14:50
A recycling system for poly (methyl methacrylate) in
Japan

1)

13:50−14:10

29G1-1

9:00−9:20
Life cycle inventory of energy technologies: Survey
and application to energy scenarios
Andrew John Chapman, Benjamin Craig McLellan,
Tetsuo Tezuka
Kyoto University

29G1-2

9:20−9:40
Network theory integrated life cycle assessment for
an electric power system
Heetae Kim, Petter Holme
Sungkyunkwan University

29G1-3
9:40−10:00
Life cycle greenhouse gas emission and land usechange impact on compressed natural gas asalternative vehicle fuel in Thailand
Worayut Saibuatrong, Viganda Varabuntoonvit,
Thumrongrut Mungcharoen
Kasetsart University

29G1-4
10:00−10:20
Life cycle assessment of biodiesel in Hong Kong
Ya Hong Dong, S. Thomas Ng
The University of Hong Kong
29G2（Room 406）10:40−12:00 October 29, Wednesday

Energy-2
1)

Mikiya Tanaka , Hirokazu Narita , Tetsuo Oishi ,Takeshi Ogata1), Yuiko Tasaki Handa1), Kazuya Koyama1,2)
1)National Institute of Advanced Industrial Science and)Technology, 2 Chiba Institute of Technology

29F3-3

14:10−14:30
Development of new processes for precious metals
recovery using organic aqua regia

Chair : K. Dowaki

29G2-1

10:40−11:00
Ecological effects from operating a biomass power
plant
Akito Murano2), Satoshi Nakano3), Ayu Washizu1)))
1)
Waseda University, 2 Toyo University, 3 The Japan Institute forLabour Policy and Training

Kana Umehara, Akihiro Yoshimura, Yasunari Matsuno
The University of Tokyo

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

19

Oral Sessions

Witold Roger Poganietz1), Yasushi Kondo2),
Hans-Joachim Gehrmann1), Shinichiro Nakamura2))
1)
Karlsruhe Institute of Technology, 2 Waseda University

Rui Ohkubo1), Mitsuo Kameyama2), Yutaro Watanabe1),
Kenji Koido1), Kiyoshi Dowaki1))
1)
Tokyo University of Science, 2 Japan Blue Energy Co.,Ltd.

29G2-4

11:40−12:00
Small hydro power plants: A modular LCA approachfor optimization��������������������������������������������� ProgramThu 30 Oct

Beatrix F. Becker, Liselotte Schebek
Technische Universität Darmstadt

Wed 29 Oct

29G2-3

11:20−11:40
An analysis of LCI and fuel cost due to Blue Tower
process based on the low power purification systemTue 28 Oct

29G2-2

11:00−11:20
Load flexible power plant concepts: A comparative
analysis from a life-cycle perspective

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

20

October 30, Thursday

30A2-3

11:20−11:40
Sustainability and stakeholder interaction in deep
ocean mineral resources▲

Tue 28 Oct

Oral Sessions
30A1（Room 101）9:00−10:20 October 30, Thursday

Sustainable Resource Management-1
Chair : B. McLellan

Wed 29 Oct

30A1-1

9:00−9:20
Global flow of nickel: Identifying its supply chain andimplication for sustainable resource management
Kenichi Nakajima1), Keisuke Nansai1), Hiroya Yamano1),
Kazuyo Matsubae2), Shinsuke MURAKAMI3),
Yuto OHTSUKA2), Yasunori IWATSUKI3),
Tetsuya NAGASAKA2))
1)
National Institute for Environmental Studies, 2 Tohoku
3)
University, The University of TokyoThu 30 Oct

30A1-2

9:20−9:40
Sustainability of rare metal supply chains fromunconventional resources
Glen D Corder1), Saleem Ali1,3), Artem Golev1),
Benjamin C McLellan1,2)))
1)
The University of Queensland, 2 Kyoto University, 3 Universityof Vermont

30A1-3
9:40−10:00
Refinement of a simulation model to analyze theformation of urban mines with demonstrative
experiments
Hitoshi Komoto, Shinsuke Kondoh, Keijiro Masui
National Institute of Advanced Industrial Science and Technology

30A1-4
10:00−10:20
Quality-oriented end-of-life vehicle scrap recycling
aimed at efficient utilization of steel alloying
elements
Hajime Ohno1), Kazuyo Matsubae1), Kenichi Nakajima2),
Yasushi Kondo3), Shinichiro Nakamura3),
Tetsuya Nagasaka1))
1)
Tohoku University, 2 National Institute for Environmental
3)
Studies, Waseda University
30A2（Room 101）10:40−12:00 October 30, Thursday

Sustainable Resource Management-2
Chair : G.D. Corder

30A2-1

10:40−11:00
Measuring supply risk footprints of critical metals
for Japanese goods and services
1)

1)

2)

Keisuke Nansai , Kenichi Nakajima , Shigemi Kagawa ,Yasushi Kondo3))
1)
National Institute for Environmental Studies, 2 Kyushu
3)
University, Waseda University

30A2-2Material flow of cobalt in Taiwan

Benjamin Craig McLellan1,2))
1)
Kyoto University, 2 University of Queensland

30A2-4

11:40−12:00
Indicators for environmental impacts at mine sites-case studies for large-scale underground mines
Shinsuke Murakami1), Tsuyoshi Adachi2),
Yoshihiko Wada3), Satoshi Kojima4)))
1)
The University of Tokyo, 2 Akita University, 3 Doshisha
4)
University, Institute for Global Environmental Strategies
30B1（Room 102）9:00−10:20 October 30, Thursday

Waste Management & Recycling-1
Chair : Y. Oshita

30B1-1

9:00−9:20
Repercussion effects of final consumption on
production and environmental loads using a ChinaJapan waste input-output table
Makiko Tsukui1), Chen Lin2))
1)
Tokyo International University, 2 Shandong University

30B1-2

9:20−9:40
The implementation of financial incentive on singleuse takeout cup source reduction and recycling in
TaiwanWei-Kai Yang, Ying-Hsuan Lin, Chih-Ku Chen
Sustainable Environmental Technology and Management Co.,Ltd.

30B1-3
9:40−10:00
Environmental impacts assessment of plastic wastein Thailand
Unchalee Suwanmanee1), Thanawadee Leejarkpai2),
Shinatiphkorn Pongpinyopap3),
Thumrongrut Mungcharoen3))
1)
Srinakharinwirot University, 2 National Metal and Materials
3)
Technology Center, Kasetsart University

30B1-4
10:00−10:20
Assessing environmental impact of fiber reinforced
plastic table top product mixed with non-metallic
fraction from printed circuit board waste
Sawanya Jareemit1), Suphaphat Kwonpongsagoon1),
Premrudee Kanchanapiya2))
1)
Mahidol University, 2 National Metal and Materials Technology
Center

11:00−11:20

Lu-Yen Chen, Shun-Tian Huang, Yu-Wen Huang
National United University

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

21

Oral Sessions
Waste Management & Recycling-2
Chair : R. Inaba

30B2-1

10:40−11:00
WEEE management in Lombardia region (Italy): An
LCA-based evaluation
Laura Biganzoli, Alida Falbo, Federica Forte,
Lucia Rigamonti, Mario Grosso
Politecnico di Milano

30C2（Room 201）10:40−12:00 October 30, Thursday

30B2-4

11:40−12:00
Climate co-benefit from improving food waste
management: A case of small communities inThailandAmornchai Challcharoenwattana, Chanathip Pharino
Chulalongkorn University
30C1（Room 201）9:00−10:20 October 30, Thursday

The Practical Challenge for Sustainable Industry-4
Chair : M. Nakajima

30C1-1 (invited)
9:00−9:20
Material Flow Cost Accounting: Simple approach,untapped opportunities, upcoming tasks
Bernd Wagner
University of Augsburg

30C1-2

9:20−9:40
Extending raw material input evaluation in the MFCA
framework through implementation of criticality
assessments
Christoph Helbig, Christoph Kolotzek, Andrea Thorenz,
Axel Tuma
University of Augsburg

30C1-3
9:40−10:00
Cost accounting instruments as components in amaterial flow analysis tool-chain
Andreas Moeller1), Martina Prox2))
1)
Leuphana University Lueneburg, 2 ifu Hamburg GmbH

Jeremy Faludi
University of California, Berkeley

30C2-2

11:00−11:20
Product and organisation environmental footprint:
Challenges in theory and practice
Annekatrin Lehmann, Vanessa Bach, Matthias Finkbeiner
Technische Universität Berlin

30C2-3

11:20−11:40,
20 years of LCA development have we understood
the user needs?
Mark Goedkoop
PRé Consultants B.V.

Discussion

11:40-12:00

30D1（Room 202）9:00−10:20 October 30, Thursday

Water-1
Chair : M. Motoshita

30D1-1

9:00−9:20
The significance of land use effects on groundwater
resource availability in Japan
Masaharu Motoshita1,2), Stephan Pfister3), Brad Ridoutt4),
Yuya Ono5), Kiyotaka Tahara1), Atsushi Inaba6)
1)
National Institute of Advanced Industrial Science and)))Technology, 2 Technische Universität Berlin, 3 ETH Zurich, 4 The
Commonwealth Scientific and Industrial Research Organisation,)
5)
Tokyo City University, 6 Kogakuin University

30D1-2

9:20−9:40
Human health impact models from water use:
Comparing to better harmonize
Anne-Marie Boulay1), Masaharu Motoshita2),
Stephan Pfister3), Cecile Bulle1), Manuele Margni1))
1)
CIRAIG, Ecole Polytechnique, 2 National Institute of Advanced)
Industrial Science and Technology, 3 ETH Zurich

30D1-3
9:40−10:00
Functional mapping for sustainable consumption: An
example through drinking water consumption
Sébastien M.R. Dente, Seiji Hashimoto
Ritsumeikan University��������������������������������������������� ProgramThu 30 Oct

11:20−11:40

30C2-1

10:40−11:00
Integrating LCA into a design innovation method

Wed 29 Oct

Chair : M. Finkbeiner

Tamon Maruyama, Jun Nakatani, Yuichi Moriguchi
The University of Tokyo



Michiyasu Nakajima, Asako Kimura
Kansai University

The Practical Challenge for Sustainable Industry-5

30B2-2

11:00−11:20
Evaluation of environmental effects of recycling ofwaste from food supply chains using the integrated
hybrid analysis

30B2-3Canceled

30C1-4
10:00−10:20
New challenge to develop sustainable value chain
management by MFCA information

Tue 28 Oct

30B2（Room 102）10:40−12:00 October 30, Thursday

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan22

Thu 30 Oct

Wed 29 Oct

Tue 28 Oct

Oral Sessions
30D1-4
10:00−10:20
Economic water productivity of polylactic acid (PLA)
production chain in Thailand
Shinatiphkorn Pongpinyopap1), Unchalee Suwanmanee2),
Thumrongrut Mungcharoen1))
1)
Kasetsart University, 2 Srinakharinwirot University
30D2（Room 202）10:40−12:00 October 30, Thursday

Water-2
Chair : A.-M. Boulay

30D2-1

10:40−11:00
Environmental life cycle emissions for vegetable oil
microemulsion-based biofuels
Noulkamol Arpornpong1), Ampira Charoensaeng1),
Virin Kittithammavong1), David A. Sabatini2),
Sutha Khaodhiar1))
1)
Chulalongkorn University, 2 The University of Oklahoma

30D2-2

11:00−11:20
Life cycle assessment of biofuels and the issue ofindirect land use change
Liselotte Schebek, Yalda Cikovani
Technische Universität Darmstadt

30D2-3

11:20−11:40
Evaluation of uncertainty in for- and backgroundsystems: A case study of municipal wastewater
treatment plant
Hiroko Yoshida, Charlotte Schuetz, Thomas H Christensen
Technical University of Denmark

30D2-4

11:40−12:00
Basin-scale multi-objective optimization of water
and wastewater systems considering global andregional impacts
Seiya Maki, Jun Nakatani, Kiyo Kurisu, Keisuke Hanaki
The University of Tokyo

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

23

Poster Sessions
P-001 Life cycle based sustainability solutions:
How successful companies turn sustainability
solutions into company benefit and businessvalue
Martin Baitz1), Masahiro Osumi2), Hatori Yukiyoshi2),
Harald Florin1))
1)
PE International AG, 2 PE Asia Corporation

P-002 Guidance to assess avoided emissions of GHGs
Atsushi Inaba2), Masaharu Motoshita1,3)
1)National Institute of Advanced Industrial Science and))Technology, 2 Kogakuin University, 3 Technische
Universität Berlin

P-003 Life cycle inventory analysis for environmental
footprints: Case study on skin-care and cosmetic
products
Hsin-jui Wu, Yuh-Ming Lee
National Taipei University

P-004 Estimation of the workload of calculating GHG
emissions of scope 3
Hideki Sasaki, Sachiko Motoike, Hiroshi Onishi
Panasonic Corporation

P-006 Application of life cycle assessment andeconomic rationality: A cost survey
1)

2)

Tomohiro Tasaki , Koichi Shobatake ,Ken-ichi Nakajima1), Carl Dalhammar3))
1)
National Institute for Environmental Studies, 2 TCO2
3)
Co. Ltd., Lund University

P-007 SCOPE3 of Kogakuin University
Atsushi Inaba1), Ko Miyata1), Koji Tanaka2))
1)
Kogakuin University, 2 es.feed

P-008 Life-cycle co-benefit of industrial and regional
symbiosis: Environmental input-output analysis
on typical resource dependent city in China
Liang Dong1,2), Tsuyoshi Fujita1), Minoru Fujii1),
Satoshi Ohnishi1), Takuya Togawa1), Huijuan Dong1)
1)
National Institute for Environmental Studies,2)
Nagoya University

P-010 Projection of demand and supply change of first
generation biomass
Yuri Hirako, Kenji Koido, Kiyoshi Dowaki
Tokyo University of Science

P-011 Decision supporting tool for sustainable dairy
cow system
Chun-Youl Baek1), Kiyotaka Tahara1), Kun-Mo Lee2),
Kyu-Hyun Park3)
1)
National Institute of Advanced Industrial Science and))Technology, 2 Ajou University, 3 Kangwon National
University

P-012 Domestic consumption and household stock
storage media in Japan
Junya Yano, Misuzu Asari, Shin-ichi Sakai
Kyoto University

P-013 Eco-efficiency assessment of ICT productsystems: An example of set top box
Jun-Yi Chiang, Yuh-Ming Lee
National Taipei University

P-014 A visualization system for carbon footprint of
products on mobile devices
Peijiang Zhao, Gun Suzuki, Koji Nagano,
Kazuhiko Sato
Muroran Institute of Technology

P-016 Forecasting electricity consumption of theJapanese information and communications
sector toward green of ICT
Yusuke Kishita1), Kohei Kuroda), Yasushi Umeda),
Yohei Yamaguchi), Yoshiyuki Shimoda),
Minako Hara), Hiroki Oka), Jiro Nakamura)))
1)
Osaka University, 2 The University of Tokyo, 3 NTT
Energy and Environment Systems Laboratories

P-017 Testing the FineChem tool
Jan Paul Lindner1,2), Ida Masoomi1,2),
Florian Gehring1,2))
1)
Fraunhofer IBP, 2 University of Stuttgart

P-019 Life cycle assessment of PVC products based onmaterial flow analysis (MFA) in Thailand
Pomthong Malakul, Thanakorn Rodcharoen,
Manit Nithitanakul
Chulalongkorn University

P-020 Sustainability of 3D printing vs. machining: Do
machine type and size matter?
Jeremy Faludi, Rishi Ganeriwala, Brett Kelly,
Toril Rygg, Chi Yang
University of California, Berkeley

P-021 Life cycle-based exergy analysis and its
application to Japanese case
Ryota Ii1), Eiji Yamasue2), Shinsuke Murakami3),
Jun Nakatani3), Takeshi Matsuda1), Ken Horiguchi1),
Yuusuke Kousaka1), Rintarou Terada1), Kei Gomi2),
Makoto Inari4))
1)
Pacific Consultants Co., Ltd., 2 Kyoto University,
3)
4)
The University of Tokyo, Inari Consulting OfficeP-022 Compilation of embodied CO2 emission inventory
using China's input-output tables: Implicationfor environmental public utilities
Qian Zhang, Jun Nakatani, Yuichi Moriguchi
The University of Tokyo��������������������������������������������� ProgramEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

24

Poster Sessions
P-023 Integration of material performance index for
a comprehensive change-oriented LCA: The
biopolymer caseBruno De Benedetti, Pierluigi Freni, Paolo Tecchio,
Sara Rollino
Politecnico di Torino

P-024 Environmental profile of stonepaper
Atsushi Inaba1), Nobuharu Shinozai1),
Takumi Kawashima1), Masaharu Motoshita2,3))
1)
Kogakuin University, 2 National Institute ofAdvanced Industrial Science and Technology,
3)Technische Universität Berlin

P-026 LCA for environmental policy in case of Japanese
local governments
Yasuyoshi Taruta, Yoshiteru Nakamori
Japan Advanced Institute of Science and Technology

P-028 Eco-design of tableware from palm fiber biocomposite
Singh Intrachooto, Rattanawan Mungkung,
Kanokon Hancharoen, Chiravoot Petchyen
Kasetsart University

P-029 Critical material footprint of household
consumption
Stefan Pauliuk
NTNU

P-030 Life cycle assessment (LCA) of the supercriticalproduction of barium titanate nanomaterials
Michael Tsang, Gilles Philippot, Cyril Aymonier,
Guido Sonnemann
University of BordeauxP-031 Integration of geopolitical related criticality
assessment for resources into the life cycle
assessment framework
Eskinder Demisse Gemechu1), Christoph Helbig2),
Guido Sonnemann1), Andrea Thorenz2), Axel Tuma2))
1)
University of Bordeaux, 2 University of Augsburg

P-032 Exploring potentials of a data-intensive
approach for sustainability quantification
Ali Kharrazi, Yarime Masaru
The University of Tokyo

P-033 Toward sustainable energy business using
woody biomass in rural communities
Yusuke Kishita, Noriaki Nakatsuka,
Yukari Fuchigami, Fumiteru Akamatsu
Osaka University

P-034 Combining product lifetime distribution analysis
with multi-regional waste input-output analysis:
A case study of automobiles in Japanese
prefectures
Daisuke Nishijima1), Ryoji Hasegawa2),
Kenichi Nakajima3), Shigemi Kagawa1))
1)
Kyushu University, 2 Osaka International University,
3)
National Institute for Environmental Studies

P-036 System dynamics model for sustainability
assessment of mineral resource consumption
considering both environmental and resource
constraints
Tatsuhiko Kawamoto, Shinsuke Murakami,
Jiro Yamatomi
The University of Tokyo

P-037 Global supply chain analysis for sustainableutilization of nickel
Yuto Ohtsuka1), Hajime Ohno1), Kazuyo Matsubae1),
Kenichi Nakajima2), Keisuke Nansai2),
Tetsuya Nagasaka1))
1)
Tohoku University, 2 National Institute forEnvironmental Studies

P-038 Mining impact on the changes in land use
measured by satellite images analysis
Yasunori Iwatsuki1), Kenichi Nakajima2),
Hiroya Yamano2), Shinsuke Murakami1))
1)
The University of Tokyo, 2 National Institute forEnvironmental Studies

P-039 Potential self supply of local resources towards
regional sustainability: Case study of Shinjo
Village in Okayama Prefecture, Japan
Kazutoshi Tsuda1), Hirokazu Makino2), Keishiro Hara1),
Michinori Uwasu1))
1)
Osaka University, 2 Independent

P-041 Anthropogenic earth movement analysis basedon geomorphological change by digital elevation
model
Keisuke Yoshida, Kenji Sugimoto, Keijiro Okuoka,
Hiroki Tanikawa
Nagoya University

P-042 A review of methodology for critical materials
evaluation
Lu-Yen Chen1), Jia-Huei Huang1), Mei-Chiun Chou2))
1)
National United University, 2 National Taiwan
University

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

25

Poster Sessions
P-043 Modeling climate effects of biogenic carbon
flows from forests and wood products at thenational level1)

1)Bernhard Steubing , Florian Suter ,Stefanie Hellweg1), Esther Thurig2), Golo Stadelmann2))
1)
ETH Zurich, 2 Swiss Federal Institute for Forest

P-044 Material flow analysis of the Swiss waste
management system
Melanie Haupt, Carl Oskar Vadenbo,
Bernhard Steubing, Stefanie Hellweg
ETH Zurich

P-045 Metrics for performance measurement ofadvanced repair-to-order, disassembly-to-orderand refurbishment-to-order
Ammar Yahya Alqahtani1), Surendra M. Gupta2),
Kenichi Nakashima3))
1)
King Abdulaziz University, 2 Northeastern University,
3)
Kanagawa University

P-047 An estimation of ship waste quantities at port:
A case study in Haiphong, Vietnam
Thang Ngoc To, Takaaki KatoThe University of Kitakyushu

P-048 Optimal improvement of waste plastics recycling
system in Tianjin based on environmental
evaluation and GISRichao Cong1), Toru Matsumoto1),
Takamasa Hayashi2), Wenchao Li3))
1)
The University of Kitakyushu, 2 NTT DATA Institute)of Management Consulting, Inc., 3 Nankai University

P-049 Life cycle assessment of reuse system for
surgical gowns
Naoki Yoshikawa1), Nobumitsu Kitanishi2,1),
Koji Amano1), Koji Shimada1))
1)
Ritsumeikan University, 2 Takasago ThermalEngineering Co., Ltd.

P-051 Analysis of contamination of impurities in steel
recycling
Chihiro Murayama, Ichiro Daigo, Yoshikazu Goto
The University of Tokyo

P-052 Evaluation of the recyclability of concrete rubble
using total material requirement index
Keijiro Okuoka, Hiroki Tanikawa
Nagoya University

P-054 Matching reused products with users considering
their satisfaction
Yuki Yamamori, Keisuke Nanjo, Hiroyuki Hiraoka
Chuo University

P-058 Review of excessive packaging restriction
implementation in Taiwan
Chih-Ku Chen1), Hsin-Ying Chuang1), Wei-Kai Yang1),
Chin-Wei Tang1)
1)
Sustainable Environmental Technology and)Management Co., Ltd., 2 International Solid Waste
3),
Association Taiwan Packaging Design Association

P-060 International interdependencies analysis using
detailed Asian international input-output table
Hiroshi Yamaguchi, Hiroshi Yamaguchi,
Norihiro Itsubo
Tokyo City University

P-061 Study on framework of life cycle sustainability
assessment and social life cycle assessment: Asa subject of biorefinery
Tomoko Fuchigami1), Xiao-Zheng Sun2),
Yutaka Genchi2))
1)
The University of Tokyo, 2 National Institute ofAdvanced Industrial Science and Technology

P-062 Global scale fate factor of nitrogen for aquatic
eutrophication using water circulation model
Masahiaru Motoshita2,3), Norihiro Itsubo1))
Tokyo City University, 2 National Institute ofAdvanced Industrial Science and Technology,
3)Technische Universität Berlin
1)P-063 Methodology to assess sustainability of biomass
utilisation in East Asia
Yuki Kudoh1), Masayuki Sagisaka1), Sau Soon Chen2),
Jessie C. Elauria3), Shabbir H. Gheewala4),
Udin Hasanudin5), Jane Romero6), Vinod K. Sharma7),
Xunpeng Shi8)
1)
National Institute of Advanced Industrial Science and))Technology, 2 SIRIM Berhad, 3 University of the4)
Philippines Los Baños, The Joint Graduate School ofEnergy and Environment, King Mongkut's University)of Technology Thonburi, 5 University of Lampung,)
6)
Asian Development Bank, 7 Indira Gandhi Institute of
8)
Development Research, National University ofSingapore

P-064 New version of simple LCA software including acomprehensive inventory database (IDEA)
Kuan Jay Bartel, Kiyotaka Tahara
National Institute of Advanced Industrial Science andTechnology

P-065 Land use, an important midpoint category
indicator in agriculture: How should we deal
with it?
Takahiro Nakashima, Shoko Ishikawa
National Agriculture and Food Research Organization��������������������������������������������� ProgramEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

26

Poster Sessions
P-066 Setting method of the evaluation boundary fromthe viewpoint of uncertainty management in
LCA for transport infrastructure provision
4)

1)

Ryoko Morimoto , Hirokazu Kato ,Naoki Shibahara2), Yuki Masuda3))
1)
Nagoya University, 2 Japan Environmental)
Management Association for Industry, 3 JR-Central
4)Consultants Company, Nagoya University (former)

P-067 Uncertainty analysis for infrastructure LCA
Hirokazu Kato1), Yuki Masuda2), Naoki Shibahara3),
Ryoko Morimoto4), Koh Kanai1))
1)
Nagoya University, 2 JR-Central Consultants
3)
Company, Japan Environmental Management)
Association for Industry, 4 Nagoya University (former)

P-068 Calculation and comparison of weighting factors
based on different approaches in LCIA
Ryosuke Yokoi1), Jun Nakatani1),
Masaharu Motoshita2), Yuichi Moriguchi1))
1)
The University of Tokyo, 2 National Institute ofAdvanced Industrial Science and Technology

P-069 Spatial variation of health damage factors forPM2.5 on a continent level
Longlong Tang1), Tatsuya Nagashima1),
Kouichi Hasegawa2), Toshimasa Ohara1),
Kengo Sudo3), Norihiro Itsubo4)
1)
National Institute for Environmental Studies,))
2)
Chuden CTI Co., Ltd., 3 Nagoya University, 4 Tokyo
City University

P-070 The role of world structural changes on CO2emissions
Kayoko Shironitta, Kayoko Shironitta,
Shunsuke Okamoto, Shigemi Kagawa
Kyushu University

P-071 Pedagogical training for environmental
education based on life cycle thinking forengineers
Hatsuna Tadaka1), Shinya Matsumoto1),
Reiko Tomaru2), Chiake Fukasawa2))
1)
Yokohama National University, 2 Sanden Kankyo
Mirai Zaidan

P-072 Eliminating mottainai product features for oursustainable society
Masatsugu Kitamura, Hidataka Hayashi
EcoDesign Promotion Network

P-073 Environmental performance of biodiesel
productions using waste cooking oil
Shogo Eguchi1), Shigemi Kagawa1), Sangwon Suh2),
Yuki Kudoh3))
1)
Kyushu University, 2 University of California, Santa
3)
Barbara, National Institute of Advanced Industrial
Science and Technology

P-074 Life cycle CO2 emission of wind energy at
optimum locations in the world
Kotaro Kawajiri
National Institute of Advanced Industrial Science andTechnology

P-075 Life cycle environmental impacts of electricity
from renewable sources in Turkey
Burcin Atilgan, Adisa Azapagic
The University of Manchester

P-076 Water-based life cycle assessment of power
generation and supply in Thailand
Tomohiro Okadera1), Shabbir H. Gheewala2,3))
National Institute for Environmental Studies, 2 The
Joint Graduate School of Energy and Environment,
King Mongkut's University of Technology Thonburi,
3)
Ministry of Education, Thailand
1)

P-077 The concept of efficiency in the context ofsustainable energy consumption: Theoreticalconsiderations and legacy
Harald Ernst Otto
Polytechnic University of Marche

P-078 Life cycle energy and environmental assessmentof the production and utilization of compressedbiogas (CBG) in Thailand
Pomthong Malakul1,2), Seksan Papong2),
Thawach Chatchupong3))
1)
Chulalongkorn University, 2 National Metal and)Materials Technology Center, 3 PTT Public Company
Limited

P-081 The concept of efficiency in the context ofsustainable energy consumption: Current
practice and shortcomings
Harald Ernst Otto
Polytechnic University of Marche

P-082 Evaluating the greenhouse gas emissions andthe life cycle cost of thermoelectric generators
for passenger automobiles
Yusuke Kishita, Yuji Ohishi, Michinori Uwasu,
Masashi Kuroda, Hiroyuki Takeda, Keishiro Hara
Osaka University

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

27

Poster Sessions
P-083 A proposal of the eco-efficiency of the fuelcell co-generation system of "Ene-Farm" inconsideration of LCCO2 emission and metal
resources depletion
Yusuke Jinno, Kenji Koido, Kiyoshi Dowki
Tokyo University of Science

P-084 Cost, CO2 emission and energy consumption ofbioethanol production from a lignocellulosic
energy crop, Erianthus sp. by SRB-CaCCO process
Takahiro Orikasa1), Ken Tokuyasu2), Masakazu Ike2),
Rui Zhao2), Mitsuru Gau3), Shoji Koide1),
Takeo Shiina2,4))
1)
Iwate University, 2 National Food Research Institute,
3)
NARO, NARO Kyushu Okinawa Agricultural)
Research Center, 4 Chiba University

P-086 Evaluation of power interchange potential
and supply-demand balance of distributed
generation in Kinki
Daisuke Fukuhara, Naoki Yoshikawa, Koji Amano,
Koji Shimada
Ritsumeikan University

P-087 A framework to assess impacts of grid mix
changes in Japan using input-output tables
Shunichi Hienuki1), Yuki Kudoh1,2), Hiroki Hondo1))
1)
Yokohama National University, 2 National Institute ofAdvanced Industrial Science and Technology

P-088 Analysis of environmental loads and benefits ofa bio-coke production factory: A case study in
Osaka
Yukari Fuchigami1), Keishiro Hara1), Takeo Kita2),
Michinori Uwasu1), Shuji Kurimoto1))
1)
Osaka University, 2 Osaka Prefecture Forest Owners
Association

P-089 Input-output analysis of introducing smart grid
systems in Japan
Satoshi Nakano2), Ayu Washizu1))
1)
Waseda University, 2 The Japan Institute for Labour
Policy and Training

P-090 Benefits of biogas projects from local and global
perspectives
Aya Heiho, Hiroki Hondo, Yue Moriizumi
Yokohama National University

P-091 Carbon footprint labelling certification ofrailway operating service in Korea
Jae-Young Lee1), Woo-Sung Jung1), Cheul-Kyu Lee1),
Hee-Man Kim2))
1)
Korea Railroad Research Institute, 2 Korea Railroad
Corporation

P-092 A review of the life cycle assessment of nearlyzero-energy residential buildings
Markus Weißenberger1), Werner Jensch1),
Werner Lang2))
1)
University of Applied Sciences Munich, 2 Technical
University Munich

P-093 An aggregative assessment of environmental
impacts on reservoir catchments imposed bypublic construction projects: A case study on
Feitsui Reservoir
Yu-An Lin, Yuh-Ming Lee
National Taipei University

P-094 Environmental impacts of portland cement
manufacturing and developed process withalternative technologies in Thailand
Unchalee Suwanmanee1), Suthida Authayanun1),
Worayut Saibuatrong2), Viganda Varabuntoonvit2),
Thumrongrut Mungcharoen2))
1)
Srinakharinwirot University, 2 Kasetsart University

P-095 Eco-benefit analysis of multifunctional building
products
Michael Jäger1), Johannes Gantner1), Sarah Homolka2),
Hannes Krieg1))
1)
University of Stuttgart, 2 Fraunhofer Institute for
Building Physics IBP

P-096 Development of a combined LCA and LCC tool
for refurbishment measures of districts
Rafael Horn2), Johannes Gantner1), Michael Baumann1))
1)
University of Stuttgart, 2 Fraunhofer IBP

P-098 Macro analysis of life cycle CO2 from urban
passenger transport systems in Asian developing
countries
Kei Ito1), Naoki Shibahara2), Hirokazu Kato3),
Koh Kanai3))
1)
Nagoya City Hall, 2 Japan Environmental)
Management Association for Industry, 3 Nagoya
University

P-099 Estimation method of the change in life cycle
CO2 from mass transit system applying microscopic traffic flow simulation
Naoki Shibahara1), Ryoko Morimoto4), Nozomi Kudo2),
Hirokazu Kato3)
1)
Japan Environmental Management Association for)
Industry, 2 National Traffic Safety and Environment))
Laboratory, 3 Nagoya University, 4 Nagoya University(former)��������������������������������������������� ProgramEcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

28

Poster Sessions
P-100 Net CO2 emissions by the change of consumption
in consequential LCA
Kotaro Kawajiri1), Masaharu Motoshita1,2),
Tomohiko Ihara3), Hiroki Hatayama1),
Kiyotaka Tahara1)
1)
National Institute of Advanced Industrial Science and))Technology, 2 Technische Universität Berlin, 3 The
University of Tokyo

P-101 Modeling consumer's choice and its GHG
implication under simultaneous consideration ofavailable income and time
Koji Takase1), Yasushi Kondo2))
Shizuoka University, 2 Waseda University

1)

P-102 Determinants of environment-conscious
behavior in eating habits
Tomohiko Ihara1), Wakana Zaima1),
Hideaki Kurishima2))
1)
The University of Tokyo, 2 Shibaura Institute ofTechnology

P-103 Product differentiation and eco-behavior byusing carbon footprint
Akai Kenju, Haruaki Tamura, Nishino Nariaki
The University of Tokyo

P-104 Analysis of the effects of low-carbon
technologies and individual activity schedule on
carbon dioxide emissions
Chika Ishida1), Hiroyoshi Morita3), Yoshimi Kanaoka2),
Hirokazu Kato1))
1)
Nagoya University, 2 Urban Renaissance Agency,
3)
Nippon Engineering Consultants Company

P-105 Emission metrics for climate policies and theirimplications to life cycle assessment
Katsumasa Tanaka
Institute for Advanced Sustainability Studies (IASS)

P-106 Evaluating the relationship between agricultural
workers and agricultural residues production: A
case study in the Hyogo Prefecture
Tomohiro Tabata, Yukako Sakon
Kobe University

P-107 Land constraints associated with future foodand biofuel demands
Kento Tamura, Naoki Yoshikawa, Koji Amano,
Seji Hashimoto
Ritsumeikan University

P-108 Web-based system development for GHG
emission from livestock sector
Guen-Young Lee1), Sung-Mo Yeon1), Kun-Mo Lee2),
Yoo-Sung Park2))
1)
WECOS, 2 Ajou University

P-109 Greenhouse gas emission of rice production
system in the Philippines based upon life cycle
inventory analysis
Elmer G. Bautista2), Masanori Saito1))
1)
Tohoku University, 2 Philippine Rice ResearchInstituteP-110 A proposal of the CF index of rice inconsideration of consumer’s health condition
Takashi Oi, Kenta Shiokawa, Kenji Koido,
Kiyoshi Dowaki
Tokyo University of Science

P-112 Influence of management practices on life cycle
greenhouse gas emissions from rice production
in Yamagata Prefecture, Japan
Katsushi Yokoyama1), Kiyotada Hayashi2)
1)
Yamagata Integrated Agricultural Research Center,2)
National Agriculture and Food Research Organization

P-113 Potential reductions in life-cycle greenhouse gas
emissions from paddy rice production: Assessing
the influence of puddling, transplanting density,and irrigation depth
Motoko Shimura1), Hidehiro Takahashi1), Chiharu Ito2),
Makoto Shibuya2), Kiyotada Hayashi3),
Kenji Matsumori1)
1)
NARO Western Region Agricultural Research Center,2)
Akita Prefectural Agricultural Experiment Station,
3)
NARO Agricultural Research Center

P-114 Life cycle CO2 emission of konjac production via
an overwintering methodology in Gunma, Japan
Kenji Koido, Yusuke Akaike, Yousuke Isshi,
Keisuke Ide, Shou Ushikubo, Masanori Kou,
Kenta Komiya, Katsuya Shimizu, Takumi Minami,
Kiyoshi Dowaki
Tokyo University of Science

P-116 Life cycle cost analysis of willow production on
small-scale field
Hidetsugu Morimoto1), Shigeru Satoh2),
Kimiharu Ishizawa3), Takeshi Arai1))
1)
Tokyo University of Science, 2 Kyoto Prefectural
3)
University, Miyagi University of Education

Program����������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

29

Poster Sessions
P-117 Life cycle inventory analysis for small scale trawl
fishery in Sendai Bay
Kazuhito Watanabe1), Kiyotaka Tahara2)
Miyagi Prefecture Kesennuma Regional Promotion)
Office, 2 National Institute of Advanced Industrial
Science and Technology
1)

P-118 Improving the environmental efficiency ofwoody biomass utilization: Focusing on the
manufacturing of high value-added products in
Maniwa, Japan
Moon Dami, Kitagawa Naomi, Genchi Yutaka,
Sagisaka Masayuki
National Institute of Advanced Industrial Science andTechnology

P-119 Potential for energy saving of dairy farming
system dependent upon land utilization
Tatsuo Hishinuma
Utsunomiya University

P-120 Substance flow analysis on agricultural nutrients
focusing on nitrogen and phosphorus
Takashi Yamamoto1), Masafumi Mizoguchi1),
Kazuyo Matsubae1), Kenichi Nakajima2),
Keisuke Nansai2), Tetsuya Nagasaka1))
1)
Tohoku University, 2 National Institute forEnvironmental Studies

P-122 Water security and socio-economic metabolism
in China: Toward an integrated assessment
Tao Wang, Seiji Hashimoto
Ritsumeikan University

P-123 Water footprint assessment of machine tool
Jahau Lewis Chen1), Yen-Bou Chen1),
Hua-Chih Huang2))
1)
National Cheng Kung University, 2 ITRI

P-124 Evaluation of water use in paddy-rice production
on the basis of differential water footprint
Susumu Uchida
Ibaraki University

P-125 Development of water footprint inventory
database of Asian countries
Soya Iida, Yuya Ono, Norihiro Itsubo
Tokyo City University��������������������������������������������� Program28A3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

30

Decision-Support Tools for Designing Sustainable Chemical Products and Processes
Konrad Hungerbühler,* Stavros Papadokonstantakis
Swiss Federal Institute of Technology (ETH), Zurich*Corresponding author: konrad.hungerbuehler@chem.ethz.ch

1. Introduction
The design of sustainable processes and products has been
identified as one of the key research and engineering
challenges [1]. In particular, the applicability of sustainability
principles can be more advantageous in earlier phases ofprocess design characterized by more degrees of freedom fordecision making. To this end, both life cycle impact and hazard
assessment affect directly and/or indirectly all three main
pillars of sustainability, (i.e., economic, environmental, andsocial).
One of the rather data intensive methods for promoting
environmental sustainability is the systematic procedure of life
cycle analysis (LCA, ISO-Norm 14040). However, to be able
to assess life cycle impacts at early design stages poses a greatchallenge. On the other hand, safety, health and environmental
hazard assessment extend the analysis from the impacts of thenormal to those of the abnormal process operation. Index-based
methods are particularly popular in industry and academia forhazard assessment in early to basic design stages, mainly due
to their simplicity [2].
In this study we discuss the role of energy related impacts,
the availability of short-cut approaches to overcome data gaps
for the estimation of life cycle inventories and the challenges ofmulti-criteria analysis. This is done on the basis of illustrative
examples for the energy related impacts of chemical production,
evaluating green solvents, and biomass based production.

chemicals.
To this end, a novel approach for basic and fine chemicals
based on fossil resources has already demonstrated thatcomplementary life cycle impact assessment data can beobtained on the basis of molecular structures with satisfactory
accuracy for early to basic design stages [6]. Here, we will alsopresent some first efforts towards short-cut models for
estimating the CED and GWP of biomass based chemical
products based on their molecular structure and minimal
process information.

2. Energy related impacts of chemical production
Energy related impacts have a special place insustainability assessment. In a recently published taxonomy ofsustainability indicators for chemical processes by US-EPA [3],energy related indices are one of the four main classification
categories. In quantitative terms, the importance of energy
related impacts in chemical production is also highlighted in
the work of Wernet et al. [4], summarized in “Table 1” for two
widely used life cycle impact assessment metrics, namely
Global Warming Potential (GWP) and Ecoindictor-99 (EI99).

4. Sustainability assessment of biomass based production
An illustrating example for the use of such frameworks as
decision-support tools in process assessment is the productionof lactic acid, a platform chemical for multiple commodity andintermediate chemicals (e.g., acrylic acid, 1,2-propanediol,
pyruvicacid,acetaldehyde,
2,3-pentanedione)andbiodegradable plastic (i.e., polylactide (PLA). Nowadays, LA is
produced via the anaerobic batch fermentation of glucose
followed by a series of purification steps. However, due tolarge waste generation (gypsum), alternative pathways basedon chemocatalysis have been proposed, such as theaqueous-phase isomerization of 1,3-dihydroxyacetone (DHA)
over Lewis-acid solids, where DHA can be produced fromglycerol, an abundant by-product of biodiesel production.
The study and comparison of such innovative production
paths should be based on a holistic sustainability assessment.
Herein, we demonstrate the synergetic role of the source of raw
materials and catalyst performance in determining greennessand economic attractiveness of the different pathways.

Table 1. Environmental impact of energy use in chemical
production expressed as % of the total impact.
Type of chemical
GWP-100a
EI99 H/A
products(%)(%)
Organic-Ecoinvent
81
43
Organic-Industrial
82
63
Inorganic-Ecoinvent
78
59
Currently, there are a few databases (e.g., Ecoinvent, [5])for obtaining “cradle-to-gate” data of a substantial number ofchemicals based on data standardization techniques forevaluating multiple data sources. However, these databases arefar from being complete. The direct impact of these data gaps
for any process design project is that assumptions have to bemade on the basis of process similarities, which requires
expertise on the specific processes, results in time consuming
modelling, is often case study specific, and, therefore, almost
impossible to automate. Naturally, this phenomenon of data
gaps becomes much more intense for new technologies andproduction concepts such as the biomass based production of

3. Multi-criteria green solvent design for post-combustion
CO2 capture
The life cycle impact assessment metrics can be combinedwith hazard assessment metrics towards a more holistic
sustainability assessment of chemical products and processes.
Such frameworks have been proposed for the design of green
solvents in general [7] and are applied in this case study for thedesign of solvents for post-combustion CO2 capture within thethe FP7-EU CAPSOL project [8]. In a first aspect, theenvironmental
andhazardassessment
complement
computer-aided molecular design for screening a vast list of
potential solvent molecules. In a second aspect, theseframeworks are used for comparing the performance of the
proposed molecules with benchmark molecules, such as
monoethanolamine (MEA), at substance and process level.

References[1] Klatt, K., et al. Comput. Chem. Eng. 33: 536-550, 2009.
[2] Adu, I.K., et al. Process Saf. Environ. Prot. 86: 77-93,
2008.
[3] Ruiz-Mercado, G.J., et al. Ind. Eng. Chem. Res. 51:
2309-2328, 2012.
[4] Wernet, G., et al. J. Ind. Ecol. 15: 96-107, 2011.
[5] Ecoincent
centre,Ecoinventdatabase3,
www.ecoinvent.ch[6] Wernet, G., et al. Green Chem. 11: 1826-1831, 2009.
[7] Capello, C., et al. Green Chem. 9: 927-934, 2007.
[8] www.capsol-project.eu/�������������������������������������������������

28A3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

31

Development of the Risk-based Management System for Chemicals throughout the Supply Chain

Fumiaki Shono,*1 and Satoshi Tokushige1
1Japan Chemical Industry Association, Japan*Corresponding author: fshono@jcia-net.or.jp
1. Introduction"Aiming to achieve, by 2020, that chemicals are used andproduced in ways that lead to the minimization of significant
adverse effects on human health and the environment" that has
been agreed internationally in the Johannesburg Summit in
2002, which was aimed sound management of chemicals.
International Council of Chemical Associations (ICCA)
has pledged to run "Global Product Strategy (GPS)" and "Responsible Care (RC) Global Charter" to achieve this goal, in
2006. In accordance with this, the Japan Chemical Industry
Association (JCIA) started the voluntary activity "GPS / JIPS"
as the new risk-based chemical management system andlaunched the "SCRUM (Supply chain Chemical Risk
management and Useful Mechanism discussion) " project, todeploy its efforts specifically throughout their entire supply
chain in cooperation with JAMP (Joint Article Management
Promotion-consortium, which has developed and promoted an
information transfer scheme for chemicals in article) .
In this session, we will introduce the overview of GPS /JIPS promoted by ICCA and JCIA and SCRUM project aimed
at risk management of chemicals throughout the supply chain
as an voluntary initiative of the industry.
2. Global current stream of chemical management
Chemicals are used for every personal daily necessities
and advanced products and have come to indispensable of ourlife to improve it. On the other hand, they also have their own
risk to adversely affect human health and the environment if
not handled appropriately. "The sound management of thechemicals has been taken up in one of the global environmental
problems while globalization of the business progressed, and
the Plan of Implementation goal that, by 2020, chemicals will
be produced and used in ways that minimize significant
adverse impacts on the environment and human health" wasagreed in the Johannesburg World Summit on Sustainable
Development in 2002. You should note here that the paradigm
shifts from the hazard-based management to pay only attention
to hazard of the chemicals toward more risk-based
management.
3. New activities of ICCA and JCIA
ICCA initiated two voluntary, advanced activities ascontribution to meet the 2020 goal in 2006. They are the
Responsible Care Global Charter and Global Product Strategy(GPS) and the reinforcement of safety of the chemicals in theirwhole life cycle has been committed through these activities.
GPS is an activity to improve industry’s management ofchemicals, including completion of risk characterization andrecommendation for chemicals in commerce, andcommunication of chemical hazards and safe handlingconditions throughout the supply chain.
JCIA formally decided to promote JIPS (Japan Initiative of
Product Stewardship, which is the GPS activity in Japan) in2009 and has actively developed the GPS/JIPS activities suchas the issue of GPS/JIPS guidance document, the constructionof IT tool called "BIGDr (the Base of Information Gathering,
sharing & Dissemination for risk management of chemical
products" to support the member companies in JCIA , theenlightenment to them, the implementation of the risk

assessment for the each products by the individual member
companies and the disclosure of their results.
4. SCRUM project
JCIA has also set up SCRUM Project in cooperation with
JAMP in 2011 to expand GPS/JIPS activity for all industry
through the entire supply chain as well as chemical industry
located in the upper part of the supply chain.
At first, by the SCRUM project, the following two items
were investigated to grasp the actual situation.
① Existing information transfer scheme related the
management of chemicals through the supply chain② The situation of the implementation of risk based
assessment and management for the chemicals in eachcompany through the supply chain related chemicals
which are chosen.
Some problems to be solved were clarified by theseinvestigations.
Therefore, SCRUM Project will develop "the risk
management guidelines on chemical substance in the supply
chain" to solve these problems, and explain the risk-based
assessment and management of chemicals to companies in the
supply chain by using this guideline.

 Figure 1. New scheme for sharing chemical risk information
throughout Supply chain
References[1] Shono, F., and Hirano, S., Chemical Business Journal:
55-61, April 2011.
[2] ICCA:http://www.icca-chem.org/[3] JCIA GPS/JIPS:
http://www.nikkakyo.org/safety_of_chemical_products/g
ps_gips[4] SCRUM:
http://www.nikkakyo.org/content/%E3%82%B5%E3%83%97%E3%83%A9%E3%82%A4%E3%83%81%E3%82%A7%E3%83%BC%E3%83%B3

�������������������������������������������������

28A3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

32

Chemicals Management for Sustainability in Small and Medium-Sized Enterprises
Emi Kikuchi-Uehara*1, Yasunori Kikuchi1, and Masahiko Hirao1
1
The University of Tokyo, Japan*Corresponding author: e-uehara@pse.t.u-tokyo.ac.jp

1. Introduction
The appropriate management of chemicals used in
manufacturing processes is desired in order to pursue
sustainability in industry. Small and medium-sized enterprises(SMEs) have been large emission sources of chemicals,
accounting for approximately 60% of the total emissions to theenvironment from industrial sectors in Japan. The chemicals
management system in small and medium-sized enterprises
tends to be insufficient due to their lack of funds and skills for
management. Many of them have difficulties in process
improvement for controlling risks posed on human health andthe environment. Strategic approaches are strongly needed sothat SMEs can practice appropriate chemicals management intheir process design.
In this study, a framework for chemicals management is
proposed for decision support in SMEs engaged in process
design for environment. Methods for risk analysis and processmodels are proposed in the framework as supporting
mechanisms for process design. A case study is conducted onprocess improvement for VOC control in metal cleaning.
2. VOC control in metal cleaning
Volatile organic compounds (VOC) can cause healthdamage and can be causative agents of air pollution. Paints,
industrial cleansing agents, ink, and adhesives are major VOC
emission sources in industry. In electroplating and thermal
treatment of metal parts, solvents are used for removing
process oils and dirt on surface. Chlorinated organic solvents,
such as dichloromethane and trichloroethylene have been
widely used in metal cleaning processes in Japan.
Voluntary efforts have been made in order to control VOC
emissions from metal cleaning processes. Aqueous detergents
have been substituted for solvents, and devices and operation
conditions have been improved. Although those efforts havecontributed to VOC emission reductions, the lack ofquantitative evaluation of risk reductions associated withprocess modifications have cause several problems. As
presented in Figure 1, chemicals can pose various risks andimpacts from local to global scales. The substitution ofalternative chemicals can lead to the generation of thecountervailing risks. In addition, it is difficult to optimize
device and operation conditions, because factors related tophysical phenomena inside a process are not clarified.
Life cycle of chemicals
Resource procurement

Production

Use

Waste treatment

Chemicals
Local

Occupational
health risk

Ecologicalrisk

Disposal

Risk
Assessment(RA)

NOx, SOx, SPM, VOC
Regional

GlobalUrban airpollution

Photochemicalozone creation

CO2, NOx, SOx, organic contaminants, chemicals
Globalwarming

Acidification Eutrophication

HumantoxicityLife Cycle
Assessment(LCA)
Ecotoxicity

Figure 1. Risks through a life cycle of chemicals

3. Process design based on risk analysis
Figure 2 shows the overview of the chemicals
management framework for decision support in process designof SMEs. In order to facilitate process improvement, risk
analysis based on the integrated life cycle assessment (LCA)
and risk assessment (RA) was proposed. In the case of metal
cleaning, life cycle impacts on the regional and global
environment (e.g., global warming and photochemical ozone
creation) and local risks in and around plants (e.g., workers’
health risk and ecological risk in a river where cleaning
wastewater is discharged) associated with the use of cleansing
agents can be quantified. The effectiveness of processmodifications can be analyzed in consideration of trade-off
relationships among impacts and risks. Process model tosimulate VOC emission from cleaning processes using
chlorinated organic solvents was also developed in order tosupport data collection, which can be an obstacle to practices
of LCA and RA in SMEs.

Figure 2. Process design framework based on risk analysis
On the basis of the developed framework which describes
process design procedures for chemicals management and theintervention of supporting mechanisms, a software tool wasdeveloped for supporting process analysis in industrial cleaning.
The tool contains the developed process model and calculation
modules for LCA and RA. Engineers in cleaning sites canevaluate a process in use by inputting available data on site to
the tool. Some alternatives for process improvement can bealso generated and evaluated with the tool. In addition,
economic performance of alternatives can be analyzed in orderto evaluate their feasibility for SMEs with limited funds forprocess improvement.
4. Conclusions
The practical framework supporting decision-making ofchemicals management in SMEs was proposed. Supporting
mechanisms for risk analysis were clarified in order tofacilitate process design aimed at risk reductions.
Acknowledgments
Part of this study was financially supported by JSPS
KAKENHI Grant Numbers 25740045(Grant-in-Aid for Young
Scientists (B), JSPS G8 Research Councils Initiative on
Multilateral Research Funding, and the Women Researchers
Promotion Program in the University of Tokyo.

�������������������������������������������������

28A4-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan33

The use of LCA as a metrics in advancing and scaling up Green Chemistry research:
the case of black liquor
Amandine Foulet1,2, Hervé Deleuze1,2, Philippe Garrigues1,2 and Guido Sonnemann*1,2
1

Univ. Bordeaux, ISM, UMR 5255, F-33400 Talence, France, 2CNRS, ISM, UMR 5255, F-33400 Talence, France*Corresponding author: guido.sonnemann@u-bordeaux.fr

1. Introduction: Green Chemistry and LCA
A key aspect related of Green Chemistry (GC) is thesustainable management of materials, including adequately
recycling systems and the substitution of toxic substances. In
order to make the GC concept operational, the USEPA
developed a set of 12 guiding principles [1], which constitutethe backbone of GC and a universal code of practice for the
eco-design of chemicals and chemical processes.
However, they have been criticized for their qualitative
nature, which can lead to difficulties when trade-offs between
principles arise. The scientific community noticed thislimitation, and several methods for metrics in GC have been
proposed. LCA has been highlighted as a suitable tool in thiscontext by many authors. [2–4],
2. The case of black liquor
Our paper aims at showing how LCA can help evaluating
the principles by advancing GC research towards sustainable
innovation, using the case of black liquor as an example.
Black liquor, a mixture of water, salts and organic matter,comes from the pulp making process. Its production is up to
1.5 tons for 1 ton of paper pulp. Often, it is used as an energy
source in paper mills, however, from a waste hierarchy point ofview recycling is preferred to energy recovery.
Therefore we consider options to divert black liquor inother ways as biopolymer, particularly taking benefits of thepresence of lignin. A process to prepare porous polymers via
medium internal phase emulsion, called polyMIPEs, has beendeveloped [5].
3. Materials and Methods: Comparison of two scenarios
Two scenarios (S1 and S2) are presented here. Scenario 1(S1) relates to the use of 1,2-dichloroethane (DCE) as the
porogen, whereas scenario 2 (S2) is with castor oil. S1 and S2
share the same processing steps and a few common raw
materials as shown in Figure 1. The recovery of DCE wassuccessfully carried out with an average yield of 80%.

4. LCA – Goal and Scope definition
A comparative LCA of the two scenarios was carried out
according to ISO 14040/44. A cylindrical-shaped monolith of
1kg is the functional unit for this study. The organic phase ratio(ф) chosen was 0.54, as the maximum castor oil ratio wasreached. Life cycle inventory calculations were performed
using SimaPro 7.3.3 software with includes databases, ofwhich EcoInvent and ELCD were used.
5. Results and Discussion
Using the calculated life cycle inventory table the LCIA
was done using CML 2001 v2.05/West Europe 1995.
Comparison of a non-renewable, petrochemical but recyclable
solvent with a renewable one was established in order to pointout the environmental benefits and burdens of each scenario.
The results for each scenario were compared to the highest
environmental impact and are presented in Figure 2.

Figure 2. Env. impacts per kg of porous materials of S1 and S2
6. Conclusions
The LCA results showed that the environmental
performance of S2 was hindered by the production method of
castor oil as well as its in-situ non-recyclability. As for S1, theuse of DCE was found to be a better option, as it was part of an
efficient recycling loop. We have seen that solvent recovery inline with the GC principle of recycling, should always be
considered as a mean to reduce environmental impacts, insteadof focusing on the GC principle of renewable resources only.
Acknowledgments
The financial support of the Aquitaine Region for the
Chair on LCA at the University of Bordeaux is acknowledged.

Figure 1. Flowchart of polyMIPE prep. for each scenario

References[1] Anastas P.T., Warner J.C. Green Chemistry: Theory andPractice, New York: Oxford University Press, 1988
[2] Domenech X. et al. Environ. Sci. Technol. 36: 5517-5520,
2002[3] Anastas, P.T., Lankey R.L. Green Chem. 6: 289-295,
2006[4] Muñoz I. Int. J. LCA 17:517–519, 2012
[5] Forgacz, C. et al. J. Appl. Polym. Sci., 129, 2606–2613,
2013�������������������������������������������������

28A4-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

34

Sulphur distribution to products in wet biomass gasification
Kenji Koido,*1 Yutaro Watanabe,1 and Kiyoshi Dowaki1
1Tokyo University of Science, Japan*Corresponding author: koido@rs.tus.ac.jp

aTable 1. Feedstock analysis results
Proximate analysis [wt.%]
Ultimate analysis [wt.% dry]
C
H
N
S
O
VMa FCb
Ash
MC
54.0 4.4 0.2 3.5 37.9 43.3 36.1 16.2
4.4

VM is volatile matter; bFC is fixed carbon

3. Results and discussion
Yields of sulphur compounds in the products after thegasification reaction was presented in Fig. 1 for different
moisture contents.
The results showed the sulphur
distribution to products in catalytic gasification of lignin at T =900°C (catalyst: NiO/CaO·Al2O3) was 0.79 for gas, 0.04 forchar, 0.003 for water-soluble and 0.378 for catalyst surface in
mmol/g-lignin, whereas the sulphur distribution to products in
non-catalytic gasification of lignin was 0.95 for gas, 0.11 forchar and 0.004 for water-soluble in mmol/g-lignin. With theNiO catalyst, the gaseous sulphur decreased 14.5% sulphur,which showed the possibility of hot-gas cleaning by thecatalyst. With the catalyst, the gaseous sulphur decreased
14.5% sulphur, which showed the possibility of hot-gas
cleaning by the catalyst. Char played a more active role asadsorbent for the non catalytic gasification (Fig. 2).
Sulfur yield [mmol/g-lignin]

2. Material and method
Feedstock was prepared by adding water to a sodium
lignin-sulphonate (lignin, Kanto Chemical Co., Inc.) until the
moisture content (MC) becomes 73–90 wt.%, which is
employed as a model compound of ethanol fermentation
residue with sulphur compounds [1]. Proximate and ultimate
analyses of the lignin are based on JIS-M8812 and JIS-M8813
as presented in Table 1. Catalysts was NiO/CaO·Al2O3 forsteam reforming of light hydrocarbons (HiFUEL R110, Alfa
Aesar) [1]. The catalyst loading (CL) was 0.17 g-cat./g-feed.
The gasifier was fixed-bed downdraft type, which was
suitable for the small-scale gasifier operation. The gasifying
agent, Argon gas, was fed to the top of the gasifier by mass flow
controller with 200 ml/min. The temperature of the gasifier at T
= 700–900°C was attained by the electric furnace. The pressuresin the reaction system were measured by a pressure gauge. The
liquids containing water soluble products are collected by aliquid collector, while the gas was obtained by gas bag, as shownin Fig. 1. The volume of the gas was measured by the gas meter.
The feedstocks with MC = 73–80 wt.% were supplied to thegasifier at 0.5 g/min for T = 750–900°C at a normal pressure for
30–60 mins after reaching the gasifier’s setting temperature.
The details of the measurement were also described at theprevious study [1]. After the measurement, the solid on thegrate is considered to be char.
H2 and H2S and COS composition in product gas isdetermined by analysis of the gas chromatograph (GC-8A,
Shimadzu Co.) equipped with TCD and that with FPD,
respectively.
Sulphur element in produced char wasdetermined based on JIS-M8813. Some produced chars wereanalysed by a scanning electron microscope (SEM, JSM-6500F

by JEOL Ltd.) to see the detailed structures of them forunderstanding reaction order. The detailed analytical methods
were described in a literature [1].

Gas

1.6

Char

Loss

1.2
0.8
0.4
0.0

73.0

77.0 80.0 85.0 88.0
Moisture content [wt. %]90.0

Fig. 1: Sulphur yields after the lignin gasification versus
moisture contents
Sulfur yield [mmol/g-lignin]

1. Introduction
Biomass gasification is a promising technology to produce
synthesis gas for biohydrogen for fuel cell applications. At
the same time, the biomass resource is more sustainable than offossil fuels, and the use of biomass mitigates carbon dioxide
emission due to carbon neutrality. Especially, wet biomass
such as fermentation residue is sustainable. It usually needs
to be dryed to reduce its moisture content for handiness.
However, gasification of the biomass with high-moisture
content produces more hydrogen-rich product gas and less tar
and char in product gas than for dried biomass. Lignin as amodel compound of fermentation residue coproduced atethanol production from ligno-cellulose was gasified forsynthesis gas production.
The produced gas containedhydrogen sulphide and carbonyl sulphide and the existence ofsulphur can cause poisoning of fuel cell catalysts. These facts
indicate that the sulphur removal is one of the most important
treatments for production of bio-hydrogen and the sulphur
distribution to the products (gas, tar, char, water-soluble andcatalyst surface) should be clarified to understand the sulphur
behaviour in the products from wet biomass gasification.

1.2

Gas

Char

Catalyst

W. S.

Loss

1.0
0.8
0.6
0.4
0.2
0.0

0.00

0.16

Catalyst loading [g-catalyst/g-feedstock]

Fig. 2: Sulphur yield after the catalytic or non-catalytic
gasification of lignin at MC = 80 wt.% and T = 900°C
4. Conclusion
Sulphur distribution of products from catalytic (NiO/CaO·
Al2O3) or non-catalytic gasification of wet lignin with MC = 80
wt.% in fixed-bed downdraft gasifier was investigated. With
the catalyst, the gaseous sulphur decreased 14.5% sulphur,which showed the possibility of hot-gas cleaning by thecatalyst. Char can act as adsorbent for the non catalytic case.
References[1] Koido, K. et al. J Jpn Inst. Energ. 93(7):667-674, 2014.

�������������������������������������������������

28A4-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

35

Estimating Optimal Environmental Load Reduction for Resource Recovery from
Plastic Waste by LCA Methodology and Plastic Waste Processing Pathways
Akihiro Izumi,*1 Hajime Munekuni1
1

Plastic Waste Management Institute, Japan

1. Introduction
The Plastic Waste Management Institute publicly discloses
the quantity of plastic production, plastic waste and resource
recovery over the course of its plastic production to disposal
each year in Japan in an official flowchart. The data in thisflowchart indicate that about 10 million tons of plastic is
produced in Japan annually and that discarded products are
effectively used at a rate of 80%. In 2012, effective usecomprised 2.04 million tons of mechanical recycling (MR),
380,000 tons of chemical recovery (CR), and 5.02 million tonsof energy recovery (ER). Plastic that is not effectively used issimply incinerated and placed in landfills, with amounts
totaling 0.96 million tons of incineration without ER and 0.89
million tons of landfilling.
In the current study, we determined basic conditions suchas residue rate and residue pathways successively processed
after the effective use of plastic waste as well as the virginplastic substitution ratio by referencing questionnaires,interviews, and research in relation to plastic waste usage
companies and industry associations. We then developed amore accurate method of estimating optimal environmentalload reduction.
2. Estimation method for environmental load reduction
If we set the amount of environmental load fromproduction to disposal (energy consumption and CO2 emission)to (1) and set the environmental load based on the assumptionthat all plastic waste that should be used effectively is simply
incinerated to (2), the amount of reduction in environmentalload can be shown as (2) – (1).
3. Introduction of basic conditions
This calculation method specifically uses the figures fromthe Institute’s plastic material flowchart as the processing
amount for each effective usage method and applies them tothe substitution subtraction (or deduction) method that regards
goods obtained from recycling as substitutes for virginmaterials and fuel.
4. Results and discussion
We were able to obtain a significantly improved flowchartfrom resin production through the resource recovery process,including residue recycling. This improved flowchart was thenused to develop a new estimating method for much moreaccurate environmental load reduction.
The proposed method estimated the avoided energy
consumption as 229 PJ in 2012 and the ratio of the avoided
CO2 emissions by effective usage versus the total amountof CO2 emissions in Japan to be around 1%.
As shown in Fig.4, it is easier to lower the energy
consumption and CO2 emissions associated with industrial
waste than with domestic waste. The avoided energy
consumption for domestic mechanical recycling is only about
one third that of industrial mechanical recycling.

Figure1.

Residue destination
consumption 2012

after

MR

for

energyFigure2. Resource recovery pathways

Figure3. Accumulation of energy consumption 2012

Figure4. Structure of avoided energy consumption 2012
References
[1]
[2]
[3]

[4]

“Plastic Products, Plastic Waste and Resource
Recovery”, PWMI Newsletter, 2010-2012.
Hajime Munekuni, “Estimation of Effective Use of
Plastic Waste by LCA Methodology”, 2013.
Akihiro Izumi, Hajime Munekuni and Osamu
Sakaguchi, “Effective Use of Plastic Waste by LCA
Methodology”, Japan Society of Material Cycles andWaste Management “, Nov. 3rd 2013.
Hajime Nishihara, "Status of plastic waste recycling
systems in Japan and study on the selection of therecycling methods by LCA methodology", Life Cycle
Assessment IX, 2009.

�������������������������������������������������

28A4-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

36

Applying c-LCA for Challenges to Global Warming at ASAHI KASEI CORP.
Junichi Nakahashi
ASAHI KASEI CORPORATION, Japan
1.

Introduction

manufacturing facilities and another one is the avoided GHG

Human activity has begun to affect significantly to the globe

emissions when our products and technologies are used.

environment. Global warming, water drought, material exhaustion, food(7) Evaluation by independent 3rd party

shortage etc. are primary issues to be tackled.
ASAHI KASEI CORP. has started to implement the activity for

We made the independent expertise 3rd parties account the
avoided GHG emissions on representative products to increase thetackling the global warming issue using the c-LCA..

credibility.

2.

(8) Activity for chemical industry

Applying c-LCA activities at ASAHI KASEI CORP.

(1) Organization

I’ve worked for ICCA (International Council of Chemical

Global warming Committee whose chairman is the holding

Industries) / WBCSD (World Business Council for Sustainable

company’s environmental officer and LCA working group whose leader

Development) Chemical Sector LCATF in generating the avoided GHG

is the holding company’s LCA expertise were settled at 2009. The global

emissions international chemical sector guideline published at 2013 [1].

warming committee has changed into global environmental committee

I’ve also worked for JCIA (Japan Chemical Industry Association)

at 2012.

LCAWG in generating avoided GHG emissions guideline published at(2) Vision and Policy on global warming issue

2012 [2]. These activities were intended to increase the credibility of

ASAHI KASEI CORP. has released a vision “we live together withavoided GHG emissions accounting.

environment” at 2011. This means we treat the global warming issues as
an important element in the business strategy. Our policy on global

3.

Conclusion

warming issues is that we will reduce greenhouse gas (GHG) emissions

We have made much GHG emissions reduction and much avoided

at our manufacturing facilities and will develop and supply innovative

GHG emissions increasing through 5 year activities on global warming

products and technologies which reduce GHG emissions when otherissue since 2009.

industries and consumers use.
(3) Avoided GHG emissions accounting guidance for inner use
We developed an avoided GHG emissions guideline only for inneruse at 2008 and uploaded to the intranet.
(4) Decision making tool for new plant investment
We amended the inner use standard for a new business proposal at

Now at 2014 we are challenging to enforce the function ofdeveloping new products and new technologies in the field of energy andenvironment through direct education for employees.
From now we’ll continuously challenge towards the target we shallmake ASAHI KASEI CORP. the leading company in the field ofglobal environment at 2020.

2010. The amendment was that the avoided GHG emissions amountshall be mentioned in the new business proposal document. By this*note : c-LCA is an abbreviation of “carbon Life Cycle Analysis” andamendment, avoided GHG emissions have become one of the elements

means an accounting method for greenhouse gas emissions along thefor decision making in new business generation.

supply chain.

(5) Accounting avoided GHG emissions on actual products andtechnologies

References

We have made accounting the avoided GHG emissions using our[1] ICCA/WBCSD CHEMICALS, Addressing the Avoided Emissions

inner use guideline for more than 40 actual products including products

Challenge, October 2013

under development.

[2] Japan Chemical Industry Association, Guideline for calculating the(6) Indicators and targets for 2020

Avoided CO2 Emission, 2012

We settled and published 2 indicators and targets for 2020 at 2011.
One indicator is the GHG emissions reduction at our�������������������������������������������������

28A5-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

37

Guidelinee on Quantiifying and R
Reporting the Avoideed Emissionns of Produ
ucts
Motozo Y
Yoshikiyo* , Kiyoshi
K
KasaiiJapan C
Chemical Industrry Association*Corresponding*
g author: myoshhikiyo@jcia-neet.or.jp
1. Introductioon
Chemicall Industry conttributes reducin
ng greenhousee gas(GHG) emissiions through providingpgoods and services thatavoid greenhoouse gas emisssions – such as
a fuel-saving ttires,
LED lamps, innsulation materiials for building
gs and solar cellls.
Reducingg carbon footpprints of produ
uct’s manufactuuringphase is one ppart of the soluution to realizee the environm
mentalbenefits. But rreducing the GHG
Gemissions through the usse of
the products is another important part to realize theenvironmentall benefit. It is well known
n that LED laamps
contribute to rreduce electricity usage. But it is very difficuult toquantify the amount of coontributions off the productss for
reducing the GHG emissionns. Moreover it is very eassy to
mislead the aamount of conttributions throu
ugh the use off the
products. Thee amount of thhe reduction ofo GHG emisssions
depends on the use conditionns by the third partyp(User) andd the
choice of the rreference produucts.
Internatioonal Council ofo Chemical Associations (ICCCA)
and World B
Business Counncil of Sustain
nable Developm
ment(WBCSD) Chemical Sectoor project hav
ve recognized theimportance off establishing thet guideline ono quantifyingg andreporting the contributions ofo the products for reducing G
GHG
emissions thrrough the prooduct life cyccle and develloped
practical guiddelines on quantifyingqandd reportingthecontributions oof the products in October 201
13[1].
2. Definition oof Avoided Em
missions
To evaluaate the contribuutions of the products for reduucing
GHG emissioons through productsplife cycle, ICCA and
WBCSD-Chemmical Sector defineddthe “A
Avoided Emissiions”
that is the am
mount of reduced GHG emiissions throughh the
product life ccycle enabled byb providing th
he same or sim
milar
function as exiisting products in the marketpllace.

Amount oof Avoided Emiissions:440

Fig1. Deffinition of Avoidded Emissions
t compare
3. Selection off the solution to
In order to calculate avoidedaemissions, the chem
mical
product studieed needs to be compared to a specific referrencecase or baselinne, which has tot deliver the same function too theuser. Additionnally, the baselinne solution has to be an establiishedproduct with a high market shares(product levellstudies) oor theweighted averrage based on shhares of all currrently implemeented
technologies aaffording the samesuser bennefit (end-use levelstudies).
4. Functional unit
4.1 Function oof the product/application
As in ISOO 14040/44, a functional unit shall be defineed towhich all inpputs and outpuuts of the prod
duct system canan berelated and which establiishes equivaleency between theprodducts/applicatio
ons under studyy. Companies shhall specify andd
quan
ntify the funnctional unit taking into account theeperfformance, beneefit provided to the customeer and relevantt
quallity criteria.
4.2 Quality requirrements
The following
g three quality properties sho
ould be used too
asseess whether com
mpared solutionns are truly exch
hangeable:
1. Functionality,F
related to the mai
ain function of thet solution
2. TechnicalT
qualitties, such as staability, durabiliity, and ease off
maintenanceA
beneffits rendered duuring use and diisposal
3. Additional
4.3 Service life
The reporting company shalll specify the serrvice life of thee
prod
duct or service in the functionaal unit.
4.4 Time and geog
graphic referennce
Companies shhall specify thee reference perriod chosen forr
the study.
If a company wants to studyy avoided emissions in a futuree
yearr, the reporting company shalll explain the scenarios used too
projject the future.
Companies shhall specify the geographic reggion chosen forr
the study.
.
5. Calculation
C
Meethodology
5.1 Boundary settting
The reportingg company sha
hall describe th
he value chainn
step
ps of all solution
ns being compaared. (From crad
dle to grave)
A flow diagraam shall be provvided to show the value chainn
for eacheof the solu
utions being com
mpared.
All system boundaries shalll be explicitly
y mentioned inn
ordeer to clarify what processes aree excluded or in
ncluded.
5.2 Methods/form
mulas used
The reportingg company shalll describe the methodmused tooacco
ount for emissions at each st
step. (Methodollogy, standardss
chosen)Simplified caalculation methhodology is prrovided in theeguiddeline.
5.3 Key parameters
The reportingg company shalll specify which
h activities andd
paraameters drive generation of GH
HG emissions.
R
guidelines
6. Reporting
The transpareency of commmunication about results off
avoiided emissions studies is enssured by a num
mber of furtherr
repo
orting requirem
ments. These specify detailss of the reporttand include a reporrting template.
Ackknowledgments
We thank the member of IC
CCA and WBC
CSD Chemicall
secttor project whho joined the taskforce of preparing thissguiddeline.
Refferences[1]] ICCA and WBCSD
W
Chemiccals: Addressinng the Avoidedd
Emissions Challenge
C-Guuideline from the chemicall
industry for accountingafor aand reporting GHG
Gemissionss
avoided alon
ng the value cchain based on
o comparativee
studies October 2013�������������������������������������������������

28A5-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan38

Establishment of Kawasaki Mechanism,
The certification program of avoided emissions outside Kawasaki City
Shoichiro TSURUTA,*1 Masayuki KANZAKI,1 Akikazu KOBAYASHI,*2 Toshifumi TAKAMIZAWA,*2 andIchiro DAIGO3
1

Japan Environmental Management Association for Industry, Japan; 2Kawasaki City, Japan; 3The University of Tokyo, Japan*Corresponding author: tsuruta@jemai.or.jp

2. General scheme of Kawasaki Mechanism
As Figure1 shows the procedure of Kawasaki Mechanism,
an application from a business is certificated by Kawasaki city
through the review by the independent body and theconsultation based on the review results by the evaluationcommittee.

Figure1. Procedure of the Kawasaki Mechanism
Kawasaki City has the ordinance that implements the system
of Planning and Reporting of Anti-Global warming Measuresin Business Activities. In this system a business’s effort toward
lifecycle reduction can be reflected on “Adjusted emissions”,

which is obtained by subtracting the certified avoided
emissions from direct emissions.
3. Calculation method of avoided emissions
The calculation guideline for avoided emissions outside
Kawasaki City describes this system. The amount of avoided
emissions is obtained by multiplying the following three items
as shown in Figure2.
(1)

(2)

(3)

The net reduction outside Kawasaki City based on a LCA
per unit of product or service is quantified as thedifference of emissions between “base-line” and the
product or service to be evaluated, where base-line is a
scenario in absence of the product or service.
The rate of contribution of applying business entity in
Kawasaki City is set, where relevant business part
located in Kawasaki City is specified among threecandidate phases; R&D, materials processing, and final
products processing. Portion of these activities are
obtained using any specific parameter, optionally
including Kawasaki City input-output tables.
The number of units sold outside Kawasaki City can becalculated by subtracting sales volume inside Kawasaki
City from total sales volume. If sales volume is notavailable, shipped volume is acceptable.

(1) Net reductions outside Kawasaki City based on LCA(2) Rate of contribution to the reduction in emissions(3) Number of units sold outside Kawasaki City

Avoided emissions
outside Kawasaki City

1. Introduction
Local municipalities have been addressing issues on
reducing greenhouse gas (GHG) emissions within theadministrative district recently. Many of them established thesystems of making the reduction plan of GHG emissions whose
results will be reported by businesses within the administrative
district. Those systems help businesses to reduce GHG
emissions voluntary.
Sometimes GHG emissions of new products becomes
more increased than existing products even if technicalinnovations to reduce the energy contributed to the reduction of
the whole GHG emissions though the life cycle.
In those cases the whole GHG reductions scheme is used
to be negatively evaluated only within the administrative
district. Therefore, it is important to evaluate the reduction of
GHG emissions when GHG emissions from the final products(e.g. Use phase) is larger than the manufacturing phase. Under
the scheme that GHG reduction is evaluated without viewpointof life cycle, requirement of GHG reductions by the local
municipality might cause a risk to lose a chance of overall
reduction.
In order to address this issue, Kawasaki City launched thecertification program named “Kawasaki Mechanism” in
FY2013. The aim is to encourage the businesses to reduce
GHG emissions on a global scale, which is taking advantage ofmany businesses that hold superior environmental technologies
in Kawasaki City. Specifically, Kawasaki City certificates
avoided GHG emissions outside Kawasaki City (avoided
emissions) through a product lifecycle. This paper shows theoutline of this program.

Figure2. Calculation method of avoided emissions
Further improvement of the calculation guideline should bebased on accumulation of case studies of applications, inseveral issues including how to set base-line and rate ofcontribution.
4. Current status of the Kawasaki Mechanism
Ten applications were certificated and published on the
homepage of Kawasaki City in FY2013. The businesses havebeen making appeals to target markets using the certification
results. Kawasaki City intends to operate the system oncontinuing basis in order to encourage the emergence of newenvironmental products or services, which is expected to be a
trigger for this kind of GHG reduction approach to become
widespread among local municipalities.
References[1] Kawasaki city: The calculation guideline for avoided
emissionsoutsideKawasakiCity,
http://www.city.kawasaki.jp/300/cmsfiles/contents/00000
44/44994/guidline.pdf / (Accessed 10.09.2014).

�������������������������������������������������

28A5-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

39

Program for Assessing the Contribution of Business Activities to Avoided Emissions in
Shiga Prefecture, Japan
Maki Ogura,*1 Takeshi Matsuda,1 Ryota Ii,1 and Kohei Ohnishi2
1Pacific Consultants Co., Ltd., Japan; 2Shiga Prefecture, Japan*Corresponding author: maki.ogura@tk.pacific.co.jp

1. Introduction
Shiga Prefecture set a long-term goal of a 50% reductionof greenhouse gas emissions from 1990 levels by 2030. To
achieve that goal it established “Shiga Prefecture’s Ordinanceon Promoting the Creation of a Low-Carbon Society.” Under
the ordinance, businesses that emit above a defined threshold
are required to prepare a Business Action Plan to reducegreenhouse gas emissions. This program includes an evaluationof contributions to create a low-carbon society through thedevelopment, production, and promotion of energy-efficient
products, and other means, as one of the categories to be
indicated in the written plans.

Figure 1. Evaluation of Contribution to Avoided Emission
To help business entities quantify their contribution to
avoided emissions, Shiga Prefecture published a “Guideline forquantifying the contribution to avoided emissions” in 2013. Inorder to develop the Guideline, the Prefecture surveyed the
products/services that contribute to avoided emissions, plus
challenges in quantifying those contributions. It obtained input
about the program through questionnaire surveys, meetings
with business entities, and trial calculations, etc. The results
were published on the Prefecture’s website.
2. Basic Concepts
The Guideline was formulated with these basic concepts:
Products and services that contribute to GHG emission
reductions in society as a whole by being used are thetargets of evaluation.
Production and R&D of parts/materials being
incorporated into energy-saving products, etc., arerecognized as contributing to a low-carbon society.
In principle, a lifecycle assessment is required. However,to promote broad use, the Guideline uses the concept of asimplified evaluation process.
Amounts of avoided emissions and emissions at the
production stage are to be reported and publishedseparately.
3. Calculation methodology
The Guideline identifies the following conditions to be
specified for calculations: product/service assessed, productmodel, time axis, place of use, baseline, life cycle activities,
evaluation of parts/materials. Below is an outline of the“baseline” and “evaluation of parts/materials” steps.
3.1. Baseline
Comparative products should be specified (a comparisonof the assessed product/service versus a comparison product, toidentify GHG emission reductions).
The Guideline offers three concepts for setting baselines:(1) “standard products” now being produced, (2) “pastproducts” (or popular products currently in use), and (3) “thestate alternated by products assessed”. Each business entity
may set the baseline fitted with purpose of evaluation andcalculability.
3.2. Evaluation of parts and materials
When parts/materials are evaluated, consideration must be
given to how to assess their contributions to avoided emissions.
One way is assessing GHG emission reductions of a productusing the parts/materials assessed, compared to product madeusing comparative parts/materials. The other way is calculating
the GHG emission reduction of final products made usingparts/materials assessed, and distributing it to related business
entities. When quantification of the contribution ofparts/materials is difficult, business entities may quantify the
GHG emission reduction of the final product and describe therole of the parts/materials qualitatively.
4. Characteristics of Shiga Prefecture’s Guideline
As shown in Section 3, business entities may choose aevaluation methodology from several options in Shiga
Prefecture’s Guideline, depending on characteristics ofproducts assessed and difficulties of data collection, calculation,and so on. Shiga Prefecture’s aim in providing several options
was to encourage as many business entities as possible toevaluate avoided emissions.
5. Aggregate calculation of avoided emissions
In FY 2013, 120 business entities reported their avoided
emissions in Business Action Reports submitted. Of them,extracted 16 business entities described CO2 emission
reductions quantitatively. The aggregate calculation of the 16
business entities came to approximately 1.2 million t-CO2. This
figure is approximate and may include individual overestimatesand underestimates.
6. Measures to encourage efforts to assess avoided
emissions
To encourage business entities to take action to assess
avoided emissions, Shiga Prefecture implemented thefollowing measures:Support services to assess avoided emissions
Seminars about avoided emissions
Created and distributed brochures to broadly spreadthe word about business entities assessing avoided
emissions, and their products and services.
Acknowledgments
We express sincere appreciation to all members of thereview meeting for assistance formulating the Guideline.
References[1] Guideline for quantifying the contribution to avoided
emissions, Shiga Prefecture, 2013
http://www.pref.shiga.lg.jp/d/new-energy/koukennhyouka.html (in Japanese)[2] Quantifying the contribution to avoided emissions in
Shiga Prefecture, “GHG Action Plan Program for theBusiness Sector” Brief Meeting Material, Shiga
Prefecture, 2014 (in Japanese)�������������������������������������������������

28A5-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan40

Neutralize CO2 Emissions by Product Contributions
Ryo Yokoyama,* Tetsuya Kuwashima, Yasuyuki Fujioka, Masaru Hirose
TDK Corporation*Corresponding author : ryoyoko@jp.tdk.com
1. Introduction
In recent years, many organizations and enterprises arefocusing on CO2 emissions reduction by products or services.
From the perspective of product lifecycle, they recognize that
reducing CO2 emissions during the use phase is as important as
reducing CO2 emissions during the manufacturing phase.
Especially in the electrical and electronic field, it isexpected that applying their products to other industrial fields,
office, home, etc. enables these sectors to reduce huge amountof CO2 emissions. Here, CO2 emissions reduction during theuse phase is called “product contributions”, because it isperformed by the products which demonstrate excellent effectto reduce negative environmental impact.
CO2 emissions reduction amount is quantified as thedifference of GHG emissions amount in the comparison
between target product and baseline.
2. TDK Environmental Action 2020
TDK, electronic components manufacturer, set theambitious goal of to achieve carbon neutrality by 2020. Carbon
neutrality means offset the amount of CO2 emissions during
manufacturing phase by the product contributions.

using contribution ratio to the contributions of the final products.
Former is for the electronic components used on a transmission
route of electric power, and latter is for the others. In otherwords, (a) is the method which extracts and visualizes the effectof electronic components to the energy consumption of final
products. In this method, assessment of electronic components
is carried out in the same way for the final product.
4. Calculation formula
Implementation procedure of (b) already has been proposedby some local governments [2, 3] and association in Japan. On
the other hand, calculation result by (a) is very few. Because
method (a) requires the technical information of actual working
conditions of electronic components. But this information isnecessary to calculate product contributions of electronic
components and also to prevent overestimation.
Calculation formula for (a) is :Product Contributions(a) = ΔWr×L×Hop×Coef×S
ΔWr : reduced electric power at rated condition,
L : load factor, Hop : hours of operation,
Coef : CO2 coefficient, S : sales quantity(1)and calculation formula for (b) is :Product Contributions(b) = Cfp×R×S
Cfp : product contributions of final product,
R : contribution ratio of electronic components,
S : sales quantity

Figure 1. TDK Carbon Neutrality
TDK has made the rational internal standard to calculate
the amount of product contributions of electronic components,and offer to the association’s working group and academic
society.
3. Product contributions of electronic components
For quantifying product contributions of electronic
components, existing guidance [1] proposes that a final
product should be assessed if a target product is intermediate
product. It is considered as an ideal way, but there is adifficulty.
In case only target electronic components was improved,
product contributions amount can be quantified by assessing
final product in which target product is included. However,usually the design of final product and the characteristic ofelectronic components are improved at the same time. This is
the reason why to quantify product contributions amount ofelectronic components is very difficult actually. Hence, moreinterpretation of that guidance which leads to implementation
procedure should be given.
As the solution of this problem, two methods have beendevised. (a) directly calculate from the energy saving amountby electronic components itself, (b) indirectly estimate by(2)

5. Current status of “TDK Environmental Action 2020”
By using above two calculation formulas, TDK makeprogress of calculating product contributions. TDK’s products
are included in a lot of kinds of final products. The number ofusage is goes up to 200. These usages are categorized to 26
groups. For each category, detailed calculation formula, L andHop have been decided.
The annual performance result of product contributions in2013 reached 0.886 Mt-CO2.
TDK will achieve “Carbon Neutrality” in a couple of years.
After that, we are going to build the internal system to promotecreation of products which contribute to CO2 emissions
reduction in the society. In addition, we will try to reconsider
the scope of “product contributions” of electronic components,from the use phase to lifecycle.
References[1] International Electrotechnical Comission (IEC) Technical
Report(TR)62726:2014,
Guidanceonquantifying
greenhouse gas emission reductions from the baseline forelectrical and electronic products and systems[2] Kawasaki city, The calculation guidelines for outsidecontributions, 2012[3] Shiga Prefecture, Guideline for quantifying the contribution
to avoided emissions, 2013�������������������������������������������������

28B4-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

41

Impact of resource-use intensity of goods and services and demand structure on national
resource productivity: Time series analysis for 10countries
Arata Ito*1 and Seiji Hashimoto1
1

Ritsumeikan University, Japan*Corresponding author: rv0001rv@ed.ritsumei.ac.jp
1. Introduction
The resource productivity (RP) indicator has been used
increasingly in Europe and Japan as a metric of sustainable useof natural resources that is an important and underpinning
determinant of sustainable development [1, 2]. The literaturereports that the RP value differs widely among countries.
Nevertheless, it is difficult to say that the resource use
efficiency of a country with higher RP is definitely higher thanthat of a country with lower RP because the efficiency isaffected by diverse factors including material requirements(resource-use intensity, RUI) for producing goods and services
and demand shares of goods and services (demand structure,DS). We had estimated the magnitudes of these factors’ effects
by comparing the RPs of 10 countries, which are importing,exporting, resource extraction and economically developing
countries [3]. In this study, we analyzed factors thatdifferentiated resource productivity of 10 countries (Japan,
Australia, China, Czech republic, Hungary, Indonesia, India,
Netherland, Portugal, and United states) from 1995 through2010.
2. Methodology
We analyzed the effects of the RUIs and DS of goods andservices on national RP by applying index decomposition
analysis. It was performed using the following equation: weused national resource-use intensity, i.e., inverse of RP, for theleft-hand side of the equation because it facilitates theinterpretation of factors on the right-hand side.
DMI
DMI i Fi
F
=∑
× ×
i
GDP
Fi
F GDP

=∑

i

DMI i # Fid Fie &F
×% + (×$ F F ' GDPFi= ∑ RUI i × (FDSid + FDSie ) × (1+ API )iwhere, DMI stands for the direct material input (t); GDPsignifies the gross domestic product (PPP-constant 2005
international $); DMIi denotes DMI induced by the final
demand for goods and services i (t); Fid represents the domestic
final demand for goods and services i (PPP-constant 2005
international $); Fie represents exports for goods and services i(PPP-constant 2005 international $); and F is the total final
demand (PPP-constant 2005 international $).
The first factor, RUIi (=DMIi/Fi), denotes resource-use
intensity per unit of final demand for goods and services i.
Therefore, lower resource-use intensity of goods and services
contributes to lower national resource-use intensity The second
factor, FDSid(=Fid/F) and FDSie(=Fie/F), shows final demand
structures, which respectively denote the ratios of domestic
final demand and exports for goods and services i to the total
final demand. Therefore, lower demand for goods and services
which use more materials improves national resource-use
intensity. API in the last factor is designated as the average
propensity to import: it is regarded as representing thecondition of international trade and the size of an economy.
Lower API implies lower national resource-use intensity.

3. Results and Discussion
Figure 1 presents an illustration of the effects of threefactors on differences in resource-use intensity in 10 countries.
The positive/negative value of a factor denotes its contribution
to an increase/decrease in national resource-use intensity of
2000, 2005, or 2010 compared to 1995. RUI of goods andservices shows negative value for almost all countries, showingthat a decrease in RUI of goods and services compared to 1995
contributed to a decrease in national resource-use intensity inrespective years in those countries. In addition, the DS forexports had an impact on resource-exporting countries such as
Australia and India, while developing countries such as China
and India were affected by the DS for domestic as well.

Figure 1. Effects of three factors on differences in resource-use
intensity among years in 10 countries.
4. Conclusion
We analyzed the effects of three factors on national
resource-use intensity from 1995 through 2010. The changes innational RP during the target period were influenced bychanges in not only RUI of goods and service, but also DS forexports and domestic. Therefore, comparison of the RUIs of
goods and services, rather than just comparing national RP, isrecommended because national RP is affected by difference inother factors examined in this study.
References[1] European Environment Agency. Resource Efficiency inEurope-Policies and Approaches in 31 EEA member andCooperating Countries. EEA Reports No 5/2011.
European Environment Agency, 2011.
[2] European Environment Agency. Survey of Resource
Efficiency
PoliciesandApproaches.
http://www.eea.europa.eu/themes/economy/resource-effic
iency/resource-efficiency-policies-country-profiles(Accessed 01.2014).
[3] Ito, A. and Hashimoto, S. Analysis of factors thatdifferentiate resource productivity of ten countries.
Proceedings of the 24th Annual Conference of Japan
Society of Material Cycles and Waste Management, 2013�������������������������������������������������

28B4-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

42

Selection of Products for Remanufacturing Based on the Designs of End of Life Products
Aditi D. Joshi,*1 Surendra M. Gupta,1 and Tetsuo Yamada2
1

Northeastern University, USA; 2The University of Electro-Communications, Japan*Corresponding author: joshi.ad@husky.neu.edu

1. Introduction
This paper addresses the methodology for the selection ofused products based on the ease of retrieving its components,
their quality level and the total cost of retrieving. A
mathematical model using goal programming is developed byconsidering the goals to minimize the total cost of
remanufacturing (total disposal cost, collection cost, labor cost,and recycling revenue), maximize the quality level of theremanufactured products and the material sales revenue andminimize the total disposal weight.
2. Problem formulation
The total cost consists of the total disposal, collection andlabor costs minus the total recycling revenue [1].
The remanufacturing system is formulated as follows:
1. The first goal is to minimize the total cost. The total
cost is set to be at most TC*. Therefore the first goal can beformulated as follows:
Goal: minimize d1+
Subject to: TC+d1-- d1+= TC*
Where, TC= CCxj +DCx + LCx- RRx
Collection cost: CCxj is the average cost associated withthe collection of used product x from the consumers.
Total disposal cost: Disposal cost index, percentage ofrecyclable contents in each component, the weight of thecomponents, the number of components, the probability of
breakage, the probability of missing components and thedisposal cost factor affect the total disposal cost.
DCx {DCI xj * W xj * (1  PRCxj ) * ( M xj * (1  pmxj )C xj ( Rootx ) M xj * (1  pbxj  pmxj ) * X xj )} * Fdc

Labor cost: Disassembly time of the root node of the usedproduct, the disassembly time of each subassembly in the usedproduct and the reprocessing cost per unit time are the factors
used in the calculation of the labor cost.
Lx
LC x  (T ( Rootx )   T ( S xk )) * CLk 1Total recycling revenue: Percentage of recyclable contents
in each component, the weight of components, the recycling
revenue index, the number of components, the probability of
breakage, the probability of missing components and recycling
revenue factor are the factors that affect this term.
RRx {PRCxj  Wxj * RI xj * ( M xj * (1  pmxj )C xj ( Rootx ) M xj (1  pbxj  pmxj ) * X xj )} * Frr

2. The second goal is to maximize the quality, to achieve
the quality level of at least Q* or more. Therefore the second
goal can be formulated as follows:
Goal: minimize d2Subject to: Q+d2--d2+=Q*
3. The third goal is to maximize the material sales revenue.
Therefore, the third goal can be formulated as follows:
Goal: minimize d3Subject to: MSR+d3-- d3+= MSR*

4. The fourth goal is to minimize the total disposal weight.
Therefore the fourth goal can be formulated as follows:
Goal: minimize d4+
Subject to: DW+d4--d4+=DW*
3. Numerical problem and results
A device-embedded (i.e., sensors and radio frequency
identification tags) residential air-conditioner (AC) case isconsidered here [2]. There are 10 components that the model
deals with. The quality level of a component is defined by theremaining life of that component. Larger remaining life
signifies better quality. Depending on the remaining life,
quality component bins are defined for the remanufacturingsystem. Three quality component bins are considered here (bin1 with the lowest quality, bin 2 with the medium quality andbin 3 with the highest quality). The first bin holds components
whose remaining life is 2 years or less. The second component
bin holds components whose remaining life is between two
and three years. The third bin holds components withremaining life of more than 3 years. Repaired product demands
are assumed to be 8, 10, and 12 for the remaining life bins 1, 2,
and 3, respectively. The mathematical model was solved using
CPLEX.
Table 1: Goals and target values using CPLEX
Goal
TargetStep 1
Step 2
Step 3
Step 4
Value
Total
7500.00 6704.74 7429.66 7429.66 7429.66
Cost
Quality
750.00300.00723.00723.00723.00Level
Material 5000.00 3645.21 4529.82 5291.46 5000.00
sales
revenue
Disposal
0.00
31.69
25.89
20.87
13.84
Weight
4. Conclusion
Environmental conscious manufacturing and productrecovery has gained a lot of attention due to the increasing
environmental concerns. Selection of used products can hence
be proven to be useful in conserving the environment. But thecost of procuring the used products, their quality level as wellas the time and labor cost required to disassemble andassemble the used components can be some of the crucial
decision points. A case example was considered to demonstrate
the application of the proposed model.
References[1] Ilgin, M. A., Gupta, S. M., Remanufacturing Modeling andAnalysis, CRC Press, Boca Raton, Florida, ISBN:
9781439863077, 2012.
[2] Ondemir, O. and Gupta, S. M., “A Multi-Criteria Decision
Making Model for Advanced Repair-To-Order andDisassembly-To-Order System”, European Journal ofOperational Research, Vol. 233, No. 2,408-419, 2014�������������������������������������������������

28B4-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

43

Mathematical formulation of urban mines design problem
Shinsuke Kondoh,*1 Hithoshi Komoto,1 and Keijiro Masui1
1National Institute of Advanced Industrial Science and Technology (AIST), Japan*Corresponding author: kondou-shinsuke@aist.go.jp

1. Introduction
The amount of metals which has been dumped andaccumulated as E-waste to date reaches a scale comparable tonatural reserves. For example, according to the calculation of
National Institute for Material Science (NIMS) in Japan, theamount of gold, silver, indium, tin, and tantalum reach 16%,
22%, 61%, 11%, and 10% of the world’s current reserve,
respectively [1]. These metals are called urban mines [2] andcollect industrial attentions recently. To make full use of today’surban mines as well as those in future (i.e., electrical andelectronic equipment which are currently used but will beavailable in future), it is necessary to design products and theirrecycling/reuse processes considering future reverse supply
chains in a strategic viewpoint. To this end, this study attempts
to mathematically formulate the problem focusing on theinterdependency among product structure, recycling/reuseprocesses, and reverse supply chain network.
Disassembled/dismantled in
PC recycling firms

Note PC
Disassembled/
dismantled in
HDDintermediate
treatment （２）
firms
Al

Magnet

（１）
PCB
（３）

Other
（６）

Ta condenser（４）

Process design
parameters（５）

Refinery

Li
Nd

Dy

Other

Co

Ta

other

Ni

(i) Most influential
RRT/PRN
parameters are
identified throughsensitivity analysis.

Co

Figure 1. RRT model of PCs
Intermediate
treatment
firms

RRT model
parameters

Other

Mn

2

PC recycling firms

3. Urban mines design problem: integrated design of a
product and processes
Through a sensitivity analysis of goal indicators (i.e., profitof each firm, overall recycling rate, etc.), (i) most influential
RRT and PRN model parameters are identified. Correlatingthese parameters with product and process design parameters(e.g., assembly structure, material usage in each component,
usage conditions of recycling facilities etc.), (ii) a set of key
design parameters are identified as shown in Figure 3. A set ofdesign rules for urban mines are derived by interpreting theinterrelationship among these parameters in addition withsensitivity analysis results.

PCB‘

PCB

Fe

Li-ionbattery(or reuse) processes to the firms which are sparsely located inJapan. Figure 2 shows a simplified PRN model of PCs focusing
on material recycling. Each node of the graph corresponds to a
recycling firm. All operations in RRT model can be assigned tosome of the firms included in the PRN model. By correlatingthese two models, an adequate recycling/reuse sequence as wellas corresponding logistic plan among the firms (in terms of apredefined set of goal indicators) are derived considering thecost and revenue of material recovery (or component reuse),which might differ from firm to firm.

(ii) Product/process design
parameters that can control the
key RRT/RPN parameters are
identified.
Goal indicators

Refineries

Product design
parameters

PRN model
parameters
Proposed model

Figure 3. Relationship between parameters
Figure 2. PRN model of PCs

2. Formulation of the modelFirst, the paper introduces recycling/reuse tree (RRT)
model which represents all possible sequences of material
recovery (or component reuse) process in addition with theircorresponding costs. Figure 1 shows a simplified RRT of apersonal computers (PCs). Each node and edge of the graphcorrespond to either a sub-assembly, component, or material
mixture, and either disassembly, dismantling, or refine
operations, respectively. For example, the graph shows that a PC
can be disassembled in a PC recycling firm to obtain hard disk
drive (HDD), print circuit board (PCB), Li-ion battery, and othermaterials.
Then, the provider and receptor network (PRN) model isintroduced to represent all possible assignment of the recycling

4. Summary
This study attempted to mathematically formulate urban
mine design problem by correlating goal indicators with productand process design parameters via an intermediate model
consisting of RRT and PRN models. By interpreting the analysis
results with referring to the interrelationship among parameters,
urban mine design rules can be derived in our future study.
References[1] http://www.nims.go.jp/news/press/2008/01/200801110/p2
00801110.pdf (Accessed 02.09.2014).
[2] Nanjo, M., Toshikouzan kaihatu-houkatuteki shigenkan ni
yoru risaikuru system no ichizuke, Bulletin of the ResearchInstitute of Mineral Dressing and Metallurgy, Tohoku
University, Vol. 43, No. 2, pp.239-251. 1988 (in Japanese).

�������������������������������������������������

28B5-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

44

Sorted Collection of Used Batteries and Small Home Appliances by Municipalities
Atsushi Terazono,*1 Masahiro Oguchi,1 Shigenori Iino,2 and Satoshi Mogi 3
1

National Institute for Environmental Studies, Japan; 2 Tokyo Metropolitan Research Institute for Environmental Protection,
Japan; 3 Bureau of Environment, Tokyo Metropolitan Government, Japan*Corresponding author: terazono@nies.go.jp

1. Introduction
In Japan, municipalities collect and dispose of dry
batteries, whereas the Japan Portable Rechargeable Battery
Recycling Center (JBRC), which is a branch organization of
the Battery Association of Japan (BAJ), is responsible for thecollection and recycling of small rechargeable batteries. This isa major contrast with the collection procedures of EU member
states, where all types of portable batteries are collected
together through a designated collection scheme under the EU
Battery Directive (2006/66/EC).
The objectives of this study were to clarify current
collection rules of waste batteries by municipalities in Tokyoand discuss future challenges for hazardous substance control
and safety.
2. Materials and methods
We reviewed the battery collection rules for each ward in
the Tokyo Metropolitan Area (23 special wards) in 2013 basedon information provided on their websites.
We investigated the characteristics of waste batteries
collected through the battery collection scheme in Ward A ofTokyo. In Ward A, waste battery collection boxes are placed at
public institutions such as city hall and libraries. The following
characteristics were investigated for waste batteries in Ward A:
number, weight, shape, size, type, production country,
expiration date (month-year) of recommended use, hazardous
substance labelling, and insulation.
We also investigated the characteristics of waste batteries
collected with small WEEE through the small WEEE
collection schemes in Wards A and B and City C. Small WEEE
collection schemes began in Ward A, Ward B, and City C in
November 2009, October 2013, and July 2013, respectively,
using collection boxes located in public institutions. The
following characteristics were investigated for the small
WEEE: number, weight, category, presence of a battery, andremovability of the battery (if used). Removability of batteries
was rated on three levels: 1 (manually removable), 2 (easily
removable with a screwdriver, no dismantling needed), and 3(dismantling or destruction needed). We refer to level 1 and 2
batteries as “exchangeable batteries” and level 3 batteries as
and “built-in batteries.”
3. Results
From the review of battery collection rules, each special
ward in Tokyo accepts dry batteries in dedicated collection
boxes for batteries (usually regarded as hazardous waste) at
public institutions or as non-combustible waste. Consumers
need to pay attention to the specific collection rules for eachtype of battery in each municipality.
Our field survey of collected waste batteries indicated that
6–10% of zinc carbon and alkaline batteries discarded in Japan
currently could be regarded as containing mercury. More than
26% of zinc carbon dry batteries currently being discarded may
have a lead content above the labelling threshold of the EU
Battery Directive (2006/66/EC). Figure 1 shows the expiration
dates of alkaline batteries that were collected. Although morethan half of the waste zinc carbon batteries had already passed
their expiration date, most of the waste alkaline batteries had

not expired. The production countries of advanced alkaline
batteries are produced in Japan and Thailand. In terms of safety,
despite announcements by producers and municipalities about
using insulation (tape) on waste batteries to prevent fires, only
2.0% of discarded cylindrical dry batteries were insulated.

5 years
Date of sampling

10 years

Figure 1. Distribution of expiration dates of cylindricalbatteries (from batteries collected in Ward A, on a number
basis): Number of alkaline batteries by expiration dates andproduction countries.
Our field study of small WEEE showed that small WEEE
and batteries were combined in the collection boxes. On aweight basis, batteries made up an average of 4.6% of the totalcollected small WEEE. Exchangeable batteries were used in
more than 90% of mobile phones, digital cameras, radios, andremote controls, but the removal rate was as low as 22% formobile phones.
4. Discussion
In terms of battery collection and recycling, threeperspectives are important: control of hazardous substances,safety, and resource recovery. In Japan, button batteries andsmall rechargeable batteries are required to be disposed of atdesignated BAJ boxes, primarily to remove Hg and Cd fromthe waste stream. Because many municipalities in Japan havecollection schemes for small WEEE in addition to those forconventional dry batteries, municipalities play a significant rolein all three perspectives and in avoiding consumer confusion.
In areas where small WEEE recycling schemes are being
operated after the enforcement of the Act on Promotion of
Recycling of Small Waste Electrical and Electronic Equipment
in Japan in 2013, consumers may be confused about the needfor separating batteries from small WEEE (especially mobile
phones). Given the safety issues and the rapid changes
occurring with mobile phones or other types of small WEEE,
discussion is needed among stakeholders to determine how tosafely collect and recycle WEEE and waste batteries.
Acknowledgments
This research was supported by the Global Environment
Research Fund of the Ministry of the Environment, Japan. We
thank the Tokyo Metropolitan Government and themunicipalities where we conducted field surveys for theircooperation and support.

�������������������������������������������������

28B5-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

45

Life Cycle Assessment of an Automotive Lithium-Ion Battery
In Large-Scale Commercial Production
Hyung Chul Kim*1, Timothy J. Wallington, Renata Arsenault, and Chulheung Bae
1
Ford Motor Company, Dearborn, MI USA*Corresponding author: hkim41@ford.com

1. Introduction
Electric vehicles (EVs) including hybrid electric vehicles(HEVs), plug-in hybrid vehicles (PHEVs), and battery electricvehicles (BEVs) provide an opportunity to reduce carbon
emissions from the transportation sector. To evaluate the full
impacts of EVs requires a Life Cycle Assessment (LCA)
perspective. Published LCAs provide greenhouse gas
emissions for production of LiMn2O4 (LMO) and
LiNi.33Mn.33Co.33O2 (Li-NCM) chemistry batteries in theranges 6-8 and 12-51 kg CO2eq./kg of battery, respectively[1-5].
Primary data are scarce and current LCAs rely on a variety
of sources for the inventory analysis of battery materials
production and manufacturing stages such as literature values,
laboratory scale production data, and estimates based on
similar processes or products. While a few studies use datafrom actual battery design and manufacturing facilities [4, 5],so far no LCAs have been conducted for a commercial
lithium-ion battery used in mass produced EVs.
In this study, we will examine the cradle-to-gate
greenhouse gas (GHG) emissions for the Ford Focus BEV
battery pack. The inventory analysis is based on the actual
design and cell manufacturing for a commercial Li-NCM/LMO battery. The results will be compared with the current
LCA estimates to understand the effect of production scale andenergy mix.
2. Review
Current LCAs focus on the cradle-to-gate emissions of EV
batteries. Figure 1 compares the GHG emissions reported inliterature for Li-NCM batteries. In these studies the GHG
emissions assessed for materials production and battery
manufacturing were 9-27 kg CO2-eq. and 4-24 kg CO2-eq. per
kg of battery, respectively.

Figure 1. GHG emissions from Li-NCM battery production inliterature
The key sources of uncertainties in the studies were theenergy demand during cell manufacturing processes including
lamination, electrode formation, and assembly along with thematerials usages in the battery pack. The manufacturing energy
use in the study by Majeau-Bettez (2011) relies on a top-down
approach based on industry overall energy requirements while

the analysis by the US EPA (2013) uses measured primary datafrom actual cell production. The study by Ellingsen et al.
(2014) is the only study based on data provided by a fullbattery producer.
3. Results and Future WorkIn the screening LCA stage, we estimated cradle-to-gate
GHG emissions for the Focus BEV Li-NCM/LMO battery
based on the bill of materials (BOM). As shown in Figure 2,
cells account for 50% of the battery pack mass with the balance
being structural and electronic component materials. Using
Gabi and Ecoinvent LCA databases along with literature data
for these materials gives GHG emissions of 7-10 kg
CO2-eq./kg of battery. This result falls in the lower bound of
the literature estimates shown in Figure 1.

Figure 2. Material breakdown of Focus BEV Li-NCM/LMO
battery
A follow-on analysis of the environmental impacts of thebattery materials is being conducted and is expected to reducethe current uncertainties for the cradle-to-gate GHG emissions.
In parallel, we are analyzing the inventory of cell and battery
manufacturing, i.e., the electricity, fuel and water demand,
based on primary data from the battery industry.
References[1] Majeau-Bettez, G., T.R. Hawkins, and A.H. Strømman, Life
Cycle Environmental Assessment of Lithium-Ion andNickel Metal Hydride Batteries for Plug-In Hybrid andBattery Electric Vehicles. Environ. Sci. Technol., 2011. 45:
p. 4548-4554.
[2] Notter, D.A., et al., Contribution of Li-Ion Batteries to theEnvironmental Impact of Electric Vehicles. Environ. Sci.
Technol., 2010. 44: p. 6550-6556.
[3] Dunn, J.B., et al., Impact of Recycling on Cradle-to-Gate
Energy Consumption and Greenhouse Gas Emissions ofAutomotive Lithium-Ion Batteries. Environ. Sci. Techol.,2012. 46: p. 12704-12710.
[4] Ellingsen, L.A.-W., et al., Life Cycle Assessment of a
Lithium-Ion Battery Vehicle Pack. J. Ind. Ecol., 2014.
18(1): p. 113-124.
[5] US EPA, Application of Life-Cycle Assessment toNanoscale Technology: Lithium-ion Batteries for Electric
Vehicles, 2013.

�������������������������������������������������

28B5-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan46

The impact of demographic change in Japan on supply security footprint of critical metals
Yosuke Shigetomi,*1,2,3 Keisuke Nansai,2 and Susumu Tohno1
1Kyoto University, Japan; 2National Institute for Environmental Studies, Japan; 3JSPS Research Fellow, Japan*Corresponding author: shigetomi.yosuke.46w@st.kyoto-u.ac.jp

1. Introduction
With expansion of electronics for hybrid vehicle and IT
products, the demand for critical metals including rare earth
metals has been increasing. These metals are strongly related
not only to usefulness for today’s our lifestyles but also to newenergy technologies such as solar power and wind power toensure a low carbon society in the future. Reportedly, in termsof life cycle assessment of the entire nation, household
consumption is the most important factor related toenvironmental burdens in economically developed countries.
[1] Nevertheless, few studies have analyzed metal consumption
from the viewpoint of household consumption similarly toprevious studies particularly addressing greenhouse gas (GHG)
emissions and energy consumption.
This study calculated material footprints (MFs) [2] ofcritical metals caused directly and indirectly by Japanesehousehold consumption using a global link input–output model(GLIO) [3] with international material flow data. The target
metals here are neodymium, cobalt, and platinum of which thedemand is expected to increase along with further expansion of
new energy technologies. Additionally, multiplying MFs by therisk factor of each country involved in the MFs yielded mining
risk footprints (MRFs) [4] of household consumption. MRF isa key indicator to measure supply security of metals with afocus on mining risk of countries where the metals are mined.
We calculated each of the MFs and MRFs in 2005 and thenestimated the impact of an aging Japanese society with fewer
children in the near future on them.

National Institute of Population and Social Security Research[5]. Element t denotes target years in this study as follows:2005 (t=1), 2010 (t=2), 2015 (t=3), 2020 (t=4), 2025 (t=5),2030 (t=6), and 2035 (t=7), since H j  t  was predicted for

2. Methods and Data
To examine the effects of the aging and lower birthrate
trends on the MFs and MRFs specifically in this study, wedefined household attributes (j =1…6) by the age of the head ofa household (1=20s, –29; 2=30s, 30–39; 4=40s, 40–49; 4=50s,
50–59; 5=60s, 60–69; 6=70s+, 70–). We estimated respective
annual expenditures by disaggregating the household sector
defined as a single sector in the 2005 Japanese input–output
table (JIOT) into the six household sectors with national
household statistics. Then we calibrated them withmathematical programming to be consisted with the annual
expenditure of each commodity included in the JIOT.
The most recent JIOT is based on 2005 figures. In thisstudy, we estimated the future household consumption withfocuses on changes in the numbers of households andhousehold sizes due to the aging and lower birthrate trends as
equations (1) and (2).

Rank Commodity Commodity sector
No.
1
JD252
Passenger motor cars
2
JD381
Repair of motor vehicles
3
JI243
Personal computers
4
JD253
Trucks, buses and other cars
5
JD237
Electric audio equipment

fijJD t  fijJD  t  1×

fijJI
 t  fijJI  t  1×

H j t 

H j  t  1

H j t 

H j  t  1×ij (t )(1)×ij (t )(2)fijJD  t  and fijJI  t  respectively represent future household
consumption expenditures of domestic and import commodities
i (i =1...409) by householder age groups j. H j  t  is numberof households by householder age group j according to the2035. ij  t  is the influence coefficient on the future
household expenditure for commodity sector i reflected by thechange in household size. Finally, we obtained each of the MFs
and MRFs of neodymium, cobalt, and platinum by multiplying
fijJD  t  and fijJI  t  by their MFs and MRFs per unit
expenditure [4], respectively.
The detailed methodology in this study is elaborated in
Shigetomi et al. (2014). [6]3. Results
Here we describe a part of results in terms of the MF and
MRF of neodymium. Table 1 shows the 5 commodity sectors
with each of the highest MFs and MRFs of neodymium derived
from household consumption for 2035, differentiating between
domestic products (JD) and imported ones (JI). These 5
commodities dominate in the same rank of largest MFs and
MRFs. The value of MRF of the commodity sector means theratio of mining risk of neodymium induced by Japanesehousehold demand to the global one.
Table 1 Top 5 household commodity sectors and their highest
MFs and MRFs of neodymium for 2035
MF
[t]
83
42
23
18
13

MRF
[%]
0.20
0.10
0.06
0.05
0.04

Acknowledgments
This research was supported in part by JSPS Grant-in-Aid
for Scientific Research (B) (No. 25281065) and JSPS
Grant-in-Aid for JSPS Fellows (No. 26・4971).
References[1] Hertwich, E. G. Environ. Sci. Technol. 39: 4673-4684,
2005.
[2] Wiedmann, T. O., et al. Proc. Natl. Acad. Sci. U.S.A. 2013,
doi/10.1073/pnas.1220362110.
[3] Nansai, K., et al. Econ. Syst. Res. 21(3): 267-290, 2009.
[4] Nansai, K., et al. Proceedings of 22nd International
Input-Output Conference: Lisbon, Portuguese, 2014.
[5] 2013 National Institute of Population Social Security
Research,
Population
Statistics
ofJapan,
http://www.ipss.go.jp/p-info/e/psj2013/PSJ2013.asp(Accessed 20.01.2014).
[6] Shigetomi, Y., et al. Environ. Sci. Technol. 48(11):6069–6080, 2014.

�������������������������������������������������

28B5-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

47

Material Flow Analysis of Heavy Metals in Contaminated Soil – A Case Study on the
Polluted Sites in Taoyuan County, Taiwan
Rong-Hua Lee and Yuh-Ming Lee*
National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
Accompanying with Taiwan’s industrialization, theindustrial wastewater was emitted directly into the irrigation
canals around agricultural areas and created serious heavy metal
contamination, which is a serious threat to human and animals'
health because of bioaccumulation in the food chain. The issueof such contaminated farmlands has emerged as a horrible
problem in Taiwan society recently.
Taoyuan County is one of the most seriously contaminatedareas in Taiwan. Based on the investigation conducted by local
environmental authorities in Taiwan, the agricultural polluted
lands were categorized as five grade, and the total area ofcontaminated farmlands reaching up to fifth grade in Taoyuan
County is 319 hectares. Those lands were legally documented as
Soil Pollution Control Sites according to the newly enacted law
in Taiwan --- the Soil and Groundwater Pollution Remediation
Act of 2000 (SGPRA). The amount of control sites in Taoyuan
County can be ranked as number one in Taiwan.[1]2. Methodology
In this study, substance flow analysis and life cycle impact
assessment of heavy metal in contaminated farmlands in
Taoyuan County will be conducted to fully understand their total
quantity, spatial distribution and fate in economic activities andin the environment by using the information of contaminantconcentration investigated before.
Udo de Haes et al. (1997) define SFA (Substance Flow
Analysis) as a specific brand of MFA(Material Flow Analysis),dealing only with the analysis of flows of specific chemicals. In
general terms, materials flow studies comprise the following
three-step procedure (van der Voet, Kleijn, van Oers, Heijungs,
Huele and Mulder 1995): (a) definition of the system, (b)quantification of the overview of stocks and flows, and (c)interpretation of the results. All three steps involve a variety ofchoices and specifications, each of which depends on thespecific goal of the study to be conducted. [2]The first step in SFA is to define the system, and a numberof choices must be made with regard to the following aspects:
spatial demarcation, functional demarcation, time horizon andmaterials to be studied. The various categories of processes,
stocks and flows belonging to the system must be specified.
Finally, this results in a flow chart: the specification of the
network of nodes. The quantification of the network is the next
step. This involves identifying and collecting the relevant data,on the one hand, and modeling, on the other. Three possible
ways of modeling the system are: (a) accounting or bookkeeping,(b) static modeling and (c) dynamic modeling. All three types
having their own data requirements, as well as their own
potential for policy support. The quantified overview can be
regarded as the result of an SFA study. However it is not easy toderive policy relevant conclusions from this. Two types of‘ interpretation ’ are distinguished here: evaluation of therobustness of the overview quantification, and translating theoverview into policy-relevant terms.[2]3. Site Description
Taoyuan County will be chosen as the research scope in thisstudy, which is one of the most seriously contaminated areas in

Taiwan. Agricultural land in the county is contaminated byheavy metals such as cadmium (Cd), copper (Cu), chromium(Cr), and zinc (Zn).
The remediation technology for contaminated farmlands in
Taoyuan County is generally combined soil turn-over dilution
with excavation method to lower the heavy metal concentrationto achieve the national standards. Those physical treatment
methods (not chemical treatment) could avoid the secondary
pollution to the environment and remedial lands could also
return for agricultural uses. The government in Taiwan havebeen devoted to treat the pollution problem in Taoyuan County
recently. As a result, the contaminated farmlands in Taoyuan
County is a representative area and is a case worth to study.
4. Results and Discussions(a) There are 1,778 contaminated farmlands, which werelegally documented as Soil Pollution Control Sites, at a total areaof approximately 232.32 hectares in Taoyuan County, according
to the preliminary data collected from Environmental Protection
Unit in Taiwan. [1](b) Cadmium is a toxic chemical. Taiwan relies on imports
to supply the demand of cadmium, because there is no locally
produced cadmium in Taiwan. However, due to the change aboutprovisions of the declaration job, there usually exists an
inconsistent of the declaration and the actual amount of import.
For example, the amount of import declaration of cadmium andits compounds was 174 ton in 1982, and up to 477 ton in 1986.
Due to cadmium oxide having not to be declared from 1989, it
reduced to 9 ton in 1990. Consequently, the government should
strengthen the declaration job for import manufacturers andcheck the usage and inventory records regularly, in order toreally control the amount the heavy metal in Taiwan.[3]5. Summary and Conclusion
The interpretation of the results of the material flow
analysis would be divided into two part: (a) economic part, (b)environmental part. First, this study would conduct the resultinterpretation about the flow of heavy metal in economic part.
On the other hand, the analysis and assessment of the heavy
metal released into environment part would also been evaluatedsimultaneously. Finally, this study would combine these twoparts to make a completely interpretation about the flow ofheavy metal in Taoyuan County under the concept of life-cycle.
The results of this study could provide proper suggestions
to management, policy decision making, and draft strategies forcontrolling pollution.
References[1] Environmental Protection Administration Executive Yuan,
R.O.C (Taiwan).
[2] Voet, Ester van der, Rene Kleijn, Lauran van Oers, Reinout
Heijungs, R. Huele and P. Mulder (1995), ‘ Studying
substance flows through the economy and environment ofa region – Part I: systems definition’, Environmental
Science and Pollution Research, 2(2), 89–96.
[3] ‘Material - Flow Analysis on the Non - Ferrous Metals in
Taiwan - Cadmium as an Example’, EPA-91-H103-02-214.

�������������������������������������������������

28C3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

48

Japanese nitrogen footprint model for the prediction of nitrogen loss to the environment
Hideaki Shibata1*, Lia R. Cattaneo2, Allison M. Leach2 and James N. Galloway2
1Hokkaido University, Japan; 2University of Virginia, USA*Corresponding author: shiba@fsc.hokudai.ac.jp
1. Introduction
Nitrogen (N) is an essential nutrient, but reactive nitrogen(Nr, defined as all nitrogen compounds except N2) can cause
many environmental problems (e.g., smog, climate change,
water pollution) when concentrations exceed certain thresholds.
Humans create more Nr than nature, and do so primarily
through food and energy production processes. The main
sources of Nr are cultivation biological nitrogen fixation(several forms of Nr), fossil fuel combustion (NOx), andfertilizer (NH3). The Nr application as fertilizer is necessary tosustain a growing population, so it is important to balance theenvironmental costs and societal benefits of Nr.
The N-Calculator is a tool that allows individuals to
calculate their personal N footprint [1]. The “footprint” is aparameter to help determine human impacts on theenvironment. The N-Calculator takes in information about anindividual’s resource consumption in the food, housing,transportation, and goods and services sectors, and compares
an individual’s footprint to the national average. We developed
the first Japanese N-Calculator [2].
International trade of food and feed is one of the strongest
drivers of global N circulation. Japan relies heavily on
imported food and feed which are increasing relative to internal
production. Countries produce food differently and withvarying nitrogen use efficiencies, so it is important to consider
the environmental impact of international trade on the Japanese
N footprint.
An individual’s N footprint is largely influenced by his/her
choices in food, energy, transportation, and goods and services
sectors. Individual behaviors may be influenced by a variety of
personal, social, and economic factors, including age. Japan is
an aging society; a diminishing population of young people issupporting a growing population of older people. Comparing
the N footprints of different age groups could provide valuable
insight into both current and future Japanese N footprints.
Our primary research questions are: (i) On average, howmuch Nr is released per capita in Japan? (ii) How does theinternational trade of food and feed impact the Japanese N
footprint? and (iii) How does a consumer’s age affect his/her N
footprint?
2. Materials and methods
We applied the N-Calculator developed by Leach et al. [1].
The following equation expresses the general concept used to
calculate an individual’s N footprint:
FPind = FPavg × AUind / AUavg(1)where FPind is the individual footprint for food, energy,transportation, and goods and services, FPavg is the average percapita footprint for the country, AUind is the individual use ineach sector, and AUavg is the average per capita use of eachsector for a country. The food N footprint consists ofconsumption and production. We used food supply data from
FAOSTAT to calculate the consumption footprint. The foodproduction N footprint was calculated based on food intake andthe amount of N lost during the production of that food,presented as virtual N factors (VNFs). Virtual N includes losses

such as fertilizer not incorporated into the plant, crop residues,
feed not incorporated into the animal product, processing waste,and household food waste.
Energy consumption from burning fossil fuels produces
nitrogen oxides. Energy is primarily used in three areas:
housing, transportation and goods and services. We combined
bottom-up and top-down approaches to calculate the energy
consumption N footprint.
We incorporated the import of foods in VNFs:
VNFtrade = SSR × VNFin-country + (1 – SSR) × VNFimport(2)

where VNFtrade is the VNF with food trade (import), SSR is theself-sufficiency rate in Japan of each food category,
VNFin-country is the VNF without food trade, and VNFimport is the
VNF in the exporting country. The further details for the
methods are available in Leach et al. [1] and Shibata et al. [2].
3. Results and discussions
We developed the N-Calculator tool for use in Japan inorder to determine an individual’s current N footprint. Our
results indicated that N footprint in Japan including the impactof trade was 28.1 kg N capita-1 yr-1. The footprint was
dominated by food production. Similar to other countries,
energy, transportation, goods and services sectors made minor
contributions to the Japanese N footprint.
It was found that the total N footprint in Japan wascomparable to European countries and smaller than the US.
Virtual N factors (VNFs) for animal products produced inJapan were relatively higher than previous studies.
We also indicated that incorporating international food andfeed trade affected most VNFs and the overall food N footprint
in Japan. Japan relies heavily on imported food (ca. 61%), so alarge portion of the N lost during the food production process islost to the environment in the exporting country.
The food preferences between different age groups
influenced the food N footprint. Younger age groups, who tend
to prefer meat, have a higher N footprint than older age groups,
who tend to prefer fish and seafood. If younger age groups
continue to prefer meats, then Nr losses could increase evenwith improvements in nutrient use efficiency (NUE).
Consumers can affect their N footprints through dietary
choices.
It was proposed that some challenges for managing N
pollution include limitations in technology for increasing crop
NUE, and the effects of trade on global Nr production.
Acknowledgments
We thank IFES-GCOE at Hokkaido University for theirfinancial support. We also thank Drs. Kasuyo Matsubae,
Keisuke Nansai and Shin-ichiro Mishima for their advice anddata contributions. This is a contribution to the N-PRINT
project (www.n-print.org).
References[1] Leach, A.M., et al. Environ. Development 1: 40–66, 2012[2] Shibata, H., et al. Environmental Research Letters (underrevision)�������������������������������������������������

28C3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan49

Scientific Robustness of including indirect Land Use Change into Life Cycle Assessment
Matthias Finkbeiner*
Technische Universität Berlin, Germany*Corresponding author: matthias.finkbeiner@tu-berlin.de
1. Introduction
The ‘food versus fuel’ debate and the discussion about theenvironmental performance of biofuels in general have led tothe development of the concept of indirect land use change(iLUC) and the proposal to include iLUC factors into
environmental assessments of biofuels. There is disagreement
about how significant the issue is, what is causing it, and what
can or should be done about it.
This controversy is also reflected by the different
approaches in sector specific regulations on biofuels. There areso far two biofuel regulations from the United States ofAmerica that already require the inclusion of iLUC factors, i.e.
the Low Carbon Fuel Standard (LCFS) in California and theRenewable Fuel Standard 2 (RFS2) of the United States federal
government. In Europe, the EU Renewable Energy Directive(RED) includes so far only direct land use change greenhousegas (GHG) emissions, but the future development of a concrete
methodology to include iLUC is noted in the RED.
The early life cycle assessments (LCA) and carbon
footprints (CF) of biofuels did not address the ‘food vs. fuel’issue. Recently, the integration of direct and indirect land usechange effects into the LCAs and CFs of biofuels is proposedby several scholars. Since the first paper on the iLUC issue by
Searchinger et al. was published in Science [1] a number ofdifferent models (economic general equilibrium or partial
equilibrium models as well as simplified models often referred
to as deterministic or causal-descriptive models) were
proposed.
2. Scientific Robustness of LCA and iLUC
A recent paper summarized an analysis of the scientificrobustness of the iLUC concept and its consistency withinternational accounting standards for LCA and CF [2]. The
conclusion was that globally agreed accounting standards for
LCA and CF do exist, while there are currently no accounting
standards for iLUC at all.
The results of assessing the requirements of the leadinginternational standards of LCA (e.g. ISO 14040/44, EU ProductEnvironmental Footprint Methodology, ILCD Handbook) or
CF (e.g. ISO TS 14067, GHG Protocol) are presented in Table
1. It is shown that none of them requires the inclusion of iLUC
factors. They even contain substantial restrictions for apotential future use of iLUC factors, and with good reason.
Fundamentally, LCA and CF focus on real material, energy andemission flows while iLUC is not physically tangible; it isbased on theoretical models that rely on hypotheticalassumptions and market predictions.
Table 1. Requirements for iLUC in LCA/CF standards [2]iLUC inclusion
mandatory

iLUC inclusion
intended - if
methods robust

if iLUC is included, if iLUC is included, if iLUC is included,
restricted tothen also otherthen for all
consequential LCA indirect effects
products

Generic LCA standards
ISO 14040/44

no

EC PEF GuidenoILCD Handbook

noFrench Labelling Scheme

no

yes

yes

ISO DIS 14067

no

yes

yes

GHG ProtocolnoPAS 2050

noJapanese CF SpecificationnoKorean CF Guideline

no

yes

yes

yes

Generic CF standards
yesneutralyes

There is full agreement in the scientific community that
iLUC factors are highly uncertain. As shown in Figure 1, theuncertainty and range of iLUC factors goes way beyond levels
which are state-of-the art in LCA or CF. The uncertainty leads
to the enormous ranges of published iLUC values from 200%
below, up to 1700% above the CF of fossil fuels. This
uncertainty level of several orders of magnitude is significantly
larger than the range of natural science based CFs of all
different types of food. With the uncertainty level of iLUC, it
would be impossible to differentiate between low CF types offood like lentils or tomatoes and high CF types of food like redmeat.

Figure 1. Ranges of iLUC factors [2]3. Conclusion
LCA and CF have a ‘priority for a scientific approach’
principle. This is different from iLUC, which is a theoretical,
hypothetical value based on market predictions and otherassumptions. Therefore, iLUC factors should be reported
separately and not be added to the results of LCA and CF.
Scientific contributions to make environmental policy asfact-based as possible are a key lever for sustainable
development. However, current iLUC factors are not fact-based.
If they are used in the context of LCA and CF, they do notmake the policy any better, but damage the reliability, integrity
and credibility of LCA and CF. The iLUC concept deserves
credit for raising awareness of the important topic of land usechange and associated climate change effects. ILUC was goodto demonstrate the problem, but will be less effective in solving
it - even if further iLUC research makes significant progress.
Zilberman et al. [3] qualified iLUC as “a second-bestsolution to a first-class problem“. Thanks to the iLUC-concept,
we understood that there is a problem. It is now time to shift
priority from reactive ‘penalty factors’ to proactive solutions.
References[1] Searchinger, T., et al. Use of U.S Croplands for Biofuels
Increases Greenhouse Gases Through Emissions From
Land-Use Change. Science 319 (5867), 1238-40, 2008.
[2] Finkbeiner, M. Indirect land use change - help beyond thehype? Biomass and Bioenergy 62, 218-221, 2014.
[3] Zilberman, D., et al. Indirect Land Use Change: A second
best solution to a first class problem. AgBioForum 13,
382-390, 2010.

�������������������������������������������������

28C3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

50

Future perspectives on LCA in agriculture: Lessons from the research in Japan
Masanori Saito
Graduate School of Agricultural Science, Tohoku University, Japan*Corresponding author: msaito@bios.tohoku.ac.jp
1. Introduction
In this presentation, looking back at two decades of LCA in
agricultural sector in Japan, I will discuss some achievements
and the future perspectives.
2. LCA Project by MAFF
The national project on “LCA for environmentally
sustainable agriculture” was started in 1998 in grant-aid by
Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan.
This 5 year project was effective to introduce the concept oflifecycle thinking and LCA into agricultural research sector inwhich these concepts were not well widespread.
In this project, system boundary was set within the
production stage of agricultural products. For example, riceproduction was evaluated from seeding to harvesting. The
collected inventory data in the project were of value as actual
data from field and have been widely referred [1]. The project
unveiled a relatively large impact of Green House Gasses(GHG) emission from natural processes during cultivation suchas CH4 emission from paddy soil as well as from ruminant
livestock.
Another achievement of the project was publication ofmanual for LCA in agriculture [2]. Although the manual was
preliminary and was only for production stage, it was useful for
people who were not familiar with LCA to recognize thesignificance of LC thinking in agricultural sector.
3. Carbon Foot Print
Since the MAFF national project, the number of thestudies on LCA in agriculture increased. However, in the early
2000’s studies, most of their system boundaries were limited toonly one or two stages in a series of lifecycle from production
to disposal through consumption. Not much attention was paid
to cooking and eating.
Food Study Group, The Institute of Life Cycle Assessment,
Japan, started to work in 2003 on LCI analysis of foods
including cooking and disposal [3]. Based upon their studies,looking at total CO2 emission throughout the lifecycle, thefollowing trends are found. (1) A proportion of CO2 emission
at production stage is relatively large, (2) a proportion of CO2
emission at transportation stage is relatively small, (3) aproportion of CO2 emission for cooking is not negligible forsome foods, and (4) a proportion of non-CO2 GHG fromnatural processes is large, especially for rice, dairy and beef
production.
After the project, food chain system was recognized as awhole. Inventory data in not only production stage but alsotransportation, consumption and waste stages were collected.
Furthermore, Act on Promotion of Global WarmingCountermeasures was amended in 2008, so that companies
were obligated to pay their effort for visualization of global
warming impact of their products. This facilitated companies tostart “carbon footprint (CFP)” labelling. In 2009, CFP system
was started on a trial base by Ministry of Economy, Trade andIndustry (METI), Japan. A number of studies relating to CFP offoods indicated that a large proportion of GHG emission
through food chain is from the natural processes and that a
relatively small proportion is from transportation process. The
latter finding is contrast to the concept of food mileage.

4. Database
For practices of LCA of agriculture and food, it is essential
to develop the database for related materials. Ajinomoto Co.
first developed the database for foods and their relatedmaterials [4]. The database has been developed based on 3EID
(Embodied, energy and emission intensity data for Japan)
which was developed using input-output table. This database
was easy to use so that it was widely used especially forcalculation of CFP of foods.
Furthermore, taking the compatibility with otherinternational database such as Ecoinvent into account, moredetailed database, JALCA, has been developed [5]. This
database comprised of various sources including hearing,
literatures, existing database and so on.
5. Perspectives
Numbers of studies on agri-food LCA increased during thelast decade not only in Japan but over the world. LC thinking
has
been
reflecting
variousresearch
topicsinagro-environmental studies. Policymakers have been interested
in LC thinking in agriculture and food industries.
In MAFF, biodiversity has been emphasized as one of theimportant environmental policies. Although biodiversity, one of
the most important impact categories, has been intensively
studied, not much studies among agri-LCA researchers inJapan. We should pay much effort for LCA of biodiversity inagro-environments. Further, integration of various impacts interms of agricultural sustainability is future challenge for the
researchers in agricultural sector.
References[1] National Institute for Agro-Environmental Science, Life
Cycle Assessment for Environmentally Sustainable
Agriculture,
http://www.niaes.affrc.go.jp/project/lca/lca_r.pdf, 2003
[2] National Institute for Agro-Environmental Science, Manual
for Life Cycle Assessment of Agricultural Practices inJapan, http://www.niaes.affrc.go.jp/project/lca/lca_m.pdf,
2003[3] Ozawa T, Inaba A, Introduction of Food Study Group, The
Institute of Life Cycle Assessment, Japan., J. LCA Japan, 4(2), 2008. pp.129-134.
[4] Ajinomoto Co. CO2 emission database of food-relatedmaterials,
http://www.ajinomoto.com/jp/activity/environment/pdf/201
0/lcco2.pdf, 2005
[5] Hayashi, K. et al. Development of a life cycle inventory
database for agricultural production systems in Japan: theJALCA Database Proceedings of the 10th International
Conference on EcoBalance, 2012.

�������������������������������������������������

28C4-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

51

Assessing Impacts of Land Use Change and Management Intensification:
A Life Cycle Perspective on Agricultural Production
Kiyotada Hayashi*
National Agriculture and Food Research Organization, Japan*Corresponding author: hayashi@affrc.go.jp
1. Introduction
Increased land use transformation from natural forest to
agricultural land for large-scale production of food and energy
crops in South East Asia, South America, and East Africa
attracts public attention because of the impacts on global
climate and biodiversity caused by the transformation. In
addition, much interest has been paid to the conversion tosustainable agricultural practices, in which understanding ofmanagement intensity plays an important role. There are,however, inconsistencies between the current progress in land
use change impact assessment within the framework of life
cycle assessment (LCA) and the requirements for conducting
the assessment of agricultural production systems.
The purpose of this study is to provide an integrated
methodological framework through reviewing earlier studies
on land use change in LCA and related studies on land use.
2. Methods
A fundamental research perspective in this study is how
agricultural production can be assessed using land use change
impact assessment within the framework of LCA. Literature
surveys cover the topics such as life cycle impact assessment
for land use change with special attention to biodiversity andrecent discussions on land sharing and sparing.
3. Results
Global characterization factors developed recently forassessing land use in LCA [1] can be used for assessing
agricultural production systems. However, since thecharacterization factors are prepared for each WWF ecoregion
and for limited land use types, it may be difficult to apply themethod to comparative LCA of, for example, organic andconventional farming practices in the same region. Although
the impact assessment method has been applied to thecomparison of organic and conventional milk in Sweden [4],the main difference lies in grass lands for animal feed, which
may be classified as a special case, in which diversity infarmlands is worth assessing. In the assessment of agricultural
production systems, the distinction between biodiversity insideof farmlands and biodiversity outside of farmlands is crucial.
Three methods to assess land use impacts on biodiversity(including the method mentioned already) have been comparedwith each other through the case study of forestry plantations in
New Zealand [3]. One of the important results is that the
impacts are closely related to productivity of the plantations,because of the proximity in characterization factors prepared
for the ecoregions. Therefore, if we use the land-oriented
expression [2], which was developed for explaining thetrade-offs between productivity and environmental impacts perarea unit, we will notice that the differences in the calculated
biodiversity per area unit among alternative production systems
are small.
Modeling management intensity is important in assessing
agricultural production systems and management intensity is
the cause to change productivity and biodiversity per area unit.
However, earlier studies do not necessarily distinguishmanagement intensity and yields [5, 6]. In other words, in

explaining the relationship between intensified agriculture andbiodiversity, agricultural intensification and yield are notseparated [6].
4. Discussion and conclusions
An important implication of this study for LCA ofagricultural production systems is that the methodology tointegrate site specific and local assessment into global
assessment is necessary. This is applicable especially to theassessment of biodiversity and ecosystem services, because theintensity of management practices, which is the decisionvariable farmers and policy makers can control, is the key toimprove sustainability. The development of easy-to-apply
techniques for measuring diversity in the site-specific condition
is an important research topic.
Acknowledgments
This work was in part supported by the Japan Society for
the Promotion of Science, Grant-in-Aid for Scientific Research(B) 26310316 and (C) 26340110, and by the Ministry ofAgriculture, Forestry and Fisheries, Japan through a research
project entitled "Development of technologies for mitigation
and adaptation to climate change in agriculture, forestry andfisheries".
References[1] de Baan, L., Mutel, C.L., Curran, M., Hellweg, S.,
Koellner, T. Land use in life cycle assessment: global
characterization factors based on regional and global
potential species extinction. Environ. Sci. Technol. 47:
9281-9290, 2013.
[2] Hayashi, K. Practical recommendations for supporting
agricultural decisions through life cycle assessment basedon two alternative views of crop production: the example
of organic conversion. Int. J. Life Cycle Assess. 18:
331-339, 2013.
[3] Michelsen, O., McDevitt, J., Coelho, C.V. A comparisonof three methods to assess land use impacts on
biodiversity in a case study of forestry plantations in New
Zealand. Int. J. Life Cycle Assess. 19: 1214-1225, 2014.
[4] Mueller, C., de Baan, L., Koellner, T. Comparing direct
land use impacts on biodiversity of conventional andorganic milk—based on a Swedish case study. Int. J. Life
Cycle Assess. 19: 52-68, 2014.
[5] Phalan, B., Balmford, A., Green, R.E., Scharlemann,
J.P.W. Minimising the harm to biodiversity of producing
more food globally. Food Policy 36, Supplement 1:
S62-S71, 2011.
[6] Tscharntke, T., Clough, Y., Wanger, T.C., Jackson, L.,
Motzke, I., Perfecto, I., Vandermeer, J., Whitbread, A.,
2012. Global food security, biodiversity conservation andthe future of agricultural intensification. Biol. Conserv.
151: 53-59, 2012.

�������������������������������������������������

28C4-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

52

Environmental Impacts of Organic Rice Farming in Thailand by using Life Cycle
Assessment to Support Policy Decision on Sustainable Agriculture

1

Rattanawan Mungkung1,2*, Patthra Pengthamkeerati1, Ratcha Chaichana1, Saranya Watcharothai3, Kittiwan
Kitpakornsanti2, and Supachok Tapananont2

Department of Environmental Technology and Management, Faculty of Environment, Kasetsart University, 50 Ngamwongwan
Road, Chatuchak, BKK 10900 THAILAND; 2 Centre of Excellence on enVironmental strategy for GREEN business (VGREEN),
3
Faculty of Environment; Department of Botany, Faculty of Science, Kasetsart University, 50 Ngamwongwan Road, Chatuchak,BKK 10900 THAILAND*Corresponding author: fscirwm@ku.ac.th
1. Introduction
Organic farming is seen as an alternative system forsustainable rice production due to lower risks from chemical use,
increasing biodiversity [1], lower production costs, and higher
price. At present, the proportion of organic rice is only 0.18% of
the total area of rice production in Thailand (19,994 ha).
However, it is targeted to be increased to 40% in 2016 [2]. In
this connection, there is a concern over the environmental
implications of such policy which areas should be encouraged to
expand more areas for organic rice. This study is then performed
to evaluate the potential environmental impacts of organic riceproduction in Thailand for policy decisions.
2. Methodology
The studied site was a paddy field in Surin province, one of
the key areas for organic rice production in Thailand. Life Cycle
Assessment (LCA) was used as the analytical tool to assess thepotential environmental impacts from cradle-to-gate. The
functional unit was set as per kg of paddy rice. Based on the
production cycle in 2013, the inputs and outputs of organic rice
field and non-organic rice field in the proximity were gathered.
The amount of methane and nitrous oxide emitted from theorganic rice field were directly measured, whereas that from thenon-organic rice was obtained from the previous study. The
method of impact assessment was based on ReCiPe 2008.
3. Results
3.1 Inventory data analysis results
The inventory data analysis results showed that theorganic rice farming required 0.02 L of diesel, 0.36 kg oforganic fertilizer, rain water 4.94 m3; the direct emissions ofmethane was 0.16 kg per kg of paddy rice and that of nitrous
oxide from organic rice farming was 0.09 g per kg of paddy
rice. With respect to the non-organic rice farming, it required
0.098 L of diesel, 0.13 kg of chemical fertilizer, rain water 1.52
m3; the direct emission of methane was lower (0.16 kg per kgof paddy rice) and that of nitrous oxide was higher (9.9 g per
kg of paddy rice) [3].
3.2 Life cycle impact assessment (LCIA) results
The environmental profiles of organic and non-organic
paddy rice indicated that the impact on climate change oforganic paddy rice was 8% lower than the non-organic paddy
rice due mainly to the lower emissions of methane and nitrous
oxide (Table 1, Figure 1). The impact on terrestrial acidication
was associated with the air emissions of organic fertilizer andSO2 and NO2 from the diesel combustion. The impact on water
depletion was realetd to the rainwater used during thecultivation period.
Table 1: LCIA results of organic and non-organic paddy rice
ImpactClimate change (kg CO2 eq)
Terrestrial acidification (kg SO2
eq)
Freshwater eutrophication (kg P

Per kg of organic
paddy rice
3.64E+00

Per kg of non-organic
paddy rice
6.59E+00

3.90E-04

2.83E-03

1.00E-06

3.49E-05

Impacteq)
Water depletion (m3)Per kg of organic
paddy rice

Per kg of non-organic
paddy rice

4.94E+00

1.52E+00

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Climate change

Air emission from fuel combustion
Methane emission

Terrestrial
acidification

Freshwater
eutrophication

Organic fertilizer
Nitrous oxide emission

Water depletion

Fuel consumption
Rain water

Figure 1: Environmental profiles of organic paddy rice

3.3 Biodiversity assessment results
The biodiversity inventory data in terms of flora and fauna
were analysed and found there were more species in organic
than in non-organic rice field (Table 2).
Table 2: Biodiversity assessment results
Type of flora
Fish

Phytoplankton
Zooplankton
Invertebrate
Benthos
Macrophytes

Organic farming
Borapet Rasbosa,Trichopsis vittatus
Phormidium spp.

Arcella bathystoma
Lanchester’s freshwater prawn
Tubiflex worm, Blood worm,
Mayflies, Common skimmer,
MollusqueLophopetalum wallichii Kurz
Eclipta prostrata L.
Ipomoea aquatic Forssk.
Leersia hexandra AW.

Non-organic farming
Flying barb,
Blackline rasbora
Micrasterias foliacea
Bailey var. quadrinflata,
Spirogyra spp.
Difflugia spp.
Pond snail
Lanchester’s freshwater
prawn, Mayflies, Bloodworm

Acknowledgments

Special thank is given to NSTDA: National Science andTechnology Development Agency (Thailand) for funding.

References[1] Halwart Matthias. 2006. Biodiversity and nutrition in rice-based
aquatic ecosystems. Journal of Food Composition and Analysis.
19: 747-751.
[2] Vitoon Panyakul. Status of Organic Agriculture. 2013.
http://www.greennet.or.th/sites/default/files/Thai%20OA%201112.pdf (Assess on 28.03.2014)[3] Mungkung, R., Gheewala, S., Poovarodoom, N. andTaewprayoon, S. 2009. Carbon footprint analysis andmanagement of rice products for carbon label to promote
low-carbon economy for climate change mitigation. TRF(Thailand Research Fund) Technical Report (RDG5130022).

�������������������������������������������������

28C4-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

53

Water Footprint Assessment of Crops Cultivation in Kurdistan Region, Iraq
Marlia Mohd Hanafiah,*1 Hushiar Raheem Hamarash,1 Muhammad Muaz Aminordin,1 and Shabbir Gheewala2
1

Universiti Kebangsaan Malaysia, Malaysia; 2King Mongkut's University of Technology Thonburi, Thailand*Corresponding author: mhmarlia@ukm.edu.my

1. Introduction
Kurdistan region is located in the Northern Iraq, covering
about 28,817 km2 of area and consists of three provinces
namely Sulaymaniyah, Duhok and Erbil. Agriculture is thelargest sector in the Kurdistan region, where wheat is the staple
food of this region. Other major crops in Kurdistan include
barley, sunflower and chickpea. However, irrigation for
agriculture is one of the most water-consuming activities andan increasing demand for food has resulted in an increasing
demand as well as competition over freshwater [1]. This
demand has led to an increased concern of water shortages andwater scarcity due to agricultural practices.
Water footprint is a temporally and spatially explicit
indicator considering location and timing of the volumes ofwater used and polluted and can be applied to assess
environmental impacts of water consumption [2]. This study
estimates the blue and green water footprint of four crops (i.e.
wheat, barley, sunflower and chickpeas) in Kurdistan, Iraq.
2. Methodology
The water footprint of growing crops were evaluated basedon the method of Hoekstra and Chapagain [3] and the
CROPWAT 8.0 developed by the Land and Water
Development Division of FAO was used to compute the cropwater requirement of the four crops grown in the Kurdistan
region, Iraq. CROPWAT 8.0 is a decision support system forcalculating reference evapotranspiration, crop waterrequirements and crop irrigation requirements that based on the
FAO Penman-Monteith model [4]. Inputs of climatic, crop andsoil data were obtained from the Kurdistan Meteorological
Department and Ministry of Agriculture and Water Resources.
The total water footprint (WFtotal,grow), expressed in m3/ton was
calculated by summing the green and blue components of water
footprint.
(1)
The green water footprint (WFgreen,grow, m3/ton) of growing
crops refers to the volume of rainwater consumed and was
calculated by dividing the green component in crop water use(CWUgreen,grow, m3/ha) by the crop yield (Y, ton/ha). This
calculation was also used to derive the blue water footprint(WFblue,grow, m3/ton) and it refers to the volume of surface waterand groundwater consumed. The grey water footprint was notconsidered in the present study.
3. Results and discussion
Figure 1 shows that the green water footprint and blue
water footprint for growing wheat, barley, sunflower andchickpeas range between 100 - 550 m3/ton and 38 – 520 m3/ton,respectively. Barley has the highest green water footprint (546m3/ton), followed by wheat (293 m3/ton), chickpea (247m3/ton) and sunflower (102 m3/ton). The accuracy of the cropwater requirement calculation is strongly determined bymodelling parameters, quality and availability of input data as
well as assumption made in interpreting the results.

Figure 1. Water footprint of growing wheat, barley, sunflower
and chickpeas in Kurdistan region
This study can be used as a starting point to introduce thewise water governance program by developing andimplementing good water policy as well as to give a new
dimension to the concept of water management in Kurdistan
Region. The results of this study also allow the development ofrecommendations for improved irrigation practices, theplanning of irrigation schedules under varying water supply
conditions, and the assessment of production under rainfed
conditions or deficit irrigation. Besides providing updated
status of total water used from the agriculture sector, our results
also show that this baseline information helps in identifying
which area that need to be conserved and what type ofrecommendation that should be drawn.
4. Conclusions
In conclusion, we found that the green water footprint andblue water footprint for growing wheat, barley, sunflower andchickpeas range between 100 - 550 m3/ton and 38 – 520 m3/ton,respectively. The amount of water required in growing crops
can differ depending on the location and climate conditions,
therefore the inclusion of local water stress index andevaluation the water footprint of growing crops under different
scenarios should be considered in the calculation of water
footprint.
Acknowledgments
Marlia Mohd Hanafiah was financed by the UKM research
grants (FRGS/2/2013/STWN01/UKM/03/1 & DLP-2013-034).
References[1] Gerbens-Leenes, W., and A.Y. Hoekstra. The water
footprint of sweeteners and bio-ethanol. Environment
International 40: 202-211, 2012.
[2] Hoekstra, A.Y., and P.Q. Hung. Globalisation of water
resources: international virtual water flows in relation tocrop trade. Global Environ. Change 15(1): 45-56, 2005.
[3] Hoekstra, A.Y., and A.K. Chapagain. Globalization of
Water: Sharing the Planet’s Freshwater Resources.
Oxford, United Kingdom: Blackwell Publishing, 2008.
[4] FAO. CROPWAT a computer program for irrigation
planning and management, by M. Smith. FAO Irrigation
and Drainage Paper No. 46. Rome, 1992a.

�������������������������������������������������

28C4-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

54

Life cycle assessment of biogas production in small-scale household digesters in Vietnam
T. K. V. Vu1*, D. Q. Vu2,3,

L. S. Jensen3, S. G. Sommer4 and S. Bruun3

1National Institute of Animal Sciences, Thuy Phuong, Tu Liem, Hanoi, Vietnam, 2 Vietnamese Academy of Agricultural Sciences,

Thanh Tri, Hanoi, Vietnam, 3University of Copenhagen, Faculty of Science, Department of Plant and Environmental Sciences,
Thorvaldsensvej 40, DK-1871 Frederiksberg C., Denmark, 4University of Southern Denmark, Faculty of Engineering, Department ofChemical Engineering, Biotechnology and Environmental Technology, Campusvej 55, 5230 Odense, Denmark*Corresponding author: vukhanhvan2002@yahoo.com

2. Methodology
In this study LCA was used to assess the environmental impactsof pig manure management systems with and without biogas
digesters throughout the entire life cycle of manure, fromstorage to field application.
The functional unit applied was the treatment of 100 kg ofsolid pig manure and 1000 kg of liquid pig manure collectedfrom animal houses.
The ReCiPe 2008 impact assessment method [8] was applied inthis study to assess the impact in four different categories: (i)global warming potential, (ii) marine water eutrophication, (iii)
freshwater eutrophication, and (iv) fossil fuel depletion.
Two manure management systems, one with a biogas digesterand one without, are compared (Figure 1). The systems were
defined to reflect current farm practices on small andmedium-scale Vietnamese pig farms with and without biogas, as
observed in a contemporary survey [1].

Functional unit: 100 kg of pig solid and 1000 kg liquid manure

Storage

Solid
LiquidmanureSlurrySlurryAp p lication

Discharge to environment

LiquidSolid manure Slurry
LiquidSlurryRice-Rice-Maize
Fish
Vegetable

Vegetable
gardens
Fruit trees

Avoided feed

S ubstitution

1. Introduction
Life cycle assessment (LCA) is a tool that can be used tocompare the environmental impacts of different products
throughout their entire life cycle [2]. LCA has been used tocompare different biogas production technologies [3, 4].
Several studies have also focused on technologies for biogas
production from manure and different co-substrates for manure[3-6]. However, very few studies have focused on the vast
number of small-scale biogas digesters being deployed indeveloping countries. Only one single study has been identified[7] and this study largely ignores the issues of CH4 leakage andrelease and nutrient recycling.
The objective of this study was to use LCA methodology toassess the environmental impacts associated with standard
biogas digesters in Vietnam and to compare them with theimpacts associated with other standard manure management
practices in order to determine whether the current employmentof biogas digesters has net positive or negative environmental
impacts.

Emission

Rice

Emission

Saved N, P and K artificial fertilizer

N, P and K artificial fertilizer production
Feed production

Emission

Marginal
Marginalproduction
productionsystemsystemFigure 1b. Manure management system without biogas
3. Results
Global warming potential. When traditional management
methods were used, the handling of one functional unit ofmanure resulted in an impact of 4.4 kg CO2 equivalents (Figure2a). The greatest proportions of emissions were methane
emissions during solid storage and nitrous oxide emissions
after field application. Some emissions could be prevented dueto the avoidance of fertilizer production, but not enough tocompensate for the emissions during storage and after field
application.

Digestion

Functional unit: 100 kg of pig solid and 1000 kg liquid manure

Biogasproduction

Wood & LPG

Saved wood
& LPG

Emission

Marginal production system

Application

Storage
StorageRelease excessive gas

LiquidLiquidLiquidSlurrySlurrySlurryBiogasdigestate

Solid
SlurrySlurryVegetable gardens

Emission
Discharge to environment

Emission

Figure 2a. Contribution of non-biogas manure management
systems to global warming potential

Substitution

Saved N, P and K artificial fertilizer

N, P and K artificial fertilizer production
Marginal production system

Emission

The handling of a functional unit of manure resulted in a global
warming potential (GWP) of 3.2 kg CO2 equivalents in amanure management system with biogas (Figure 2b).

Figure 1a. Manure management system with biogas�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

55

Freshwater eutrophication potential. The ReCipe method
assumed that biological production in fresh water ecosystems islimited by P availability. Therefore, there is no effect ofemissions from other nutrients in this category. The biggest
environmental burden on fresh water eutrophication comesfrom the discharge of liquid manure and digestate in bothmanure management systems (Table 1). The level of P
discharged from the biogas system was five times higher thanthat from non-biogas systems. This is mainly caused by thedischarge of digestate, which is harder to recycle because of its
high water content. As a result, the impact potential in thiscategory from biogas systems was 0.551 kg P eq. per FU, while
it was only 0.128 kg P eq. per FU from the non-biogas system.

Figure 2b. Contribution of biogas manure management systems
to global warming potential
The greatest emissions in this system are associated with CH4from digestate storage. In addition, the loss of CH4 throughleaks and the intentional release of biogas has a considerable
impact. The results clearly show that emissions of CH4, mainly
from digestate storage and the intentional release of biogas
when production exceeds consumption, may seriously
compromise any benefits in terms of global warming by
outweighing any savings made by replacing alternative fuelswith biogas.
Fossil fuel depletion potential. Figure 3 shows that both manure
handling systems represent net reductions in fossil fueldepletion potential. The reason for this is that manure is a
useful resource that can be used to replace fuels and fertilizers.
The non-biogas management system resulted in greater savings
than the biogas management system. Although the biogas
replaces LPG production, non-biogas farms saved more fossil
resources since this system features a greater recycling of
nutrients and thus leads to replacement of more chemicalfertilizers whose production requires considerable energy.
These results are obviously highly dependent on theassumptions regarding the substitution of mineral fertilizer andthe fact that these substitutions actually happen. However,despite this uncertainty, the result clearly shows that thesubstitution of fertilizers is also important in terms of fossil
fuel depletion potential.

Table 1. Contribution of biogas farms and non-biogas farms tofreshwater eutrophication potential, in kg P eq.
Solid
Farm types
Total
Avoided Liquid
fertilizer discharge
discharg
PeNon-biogas
0.128-0.003
0.115
0.027
farms
Biogas farms
0.551-0.001
0.552
Marine water eutrophication potential. The ReCipe method
assumes that the marine environment is N limited and therefore
that only emissions of N-containing compounds can contribute tomarine water eutrophication.
The non-biogas management system contributed 0.33 kg N eq. per
FU to marine water eutrophication potential (Fig. 4a). The N
content in the discharged liquid manure as well as emissions
during and after application of solid manure are the largest
contributors to marine water eutrophication in this system. The
emission associated with liquid and solid manure application on
agricultural land was 0.24 kg N eq. per FU, which is similar to theemissions saved by not using urea fertilizer.

Figure 4a. Contribution of non-biogas manure management
systems to marine water eutrophication potential
The biogas manure management system contributed 0.82 kg N
eq. per FU to marine eutrophication (Fig.4b). The main
contribution to this is through the discharged digestate. Again
the emissions saved by not using urea prevent an impact
similar in size to the one associated with digestate application.
As with the non-biogas management system, the two processesof digestate storage and digestate application made a negligible
contribution to marine water eutrophication.
Figure 3. Contribution of biogas farms and non-biogas manure
management systems to fossil fuel depletion potential�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

56
Environmental consequences of future biogas technologies
based on separated slurry. Environ. Sci. Technol. 2011, 45,5869-5877.
[7] Chen, S.; B. Chen; D. Song. Life-cycle energy productionand emissions mitigation by comprehensive biogas − digestateutilization. Bioresour. Technol. 2012, 114, 357-364.
[8] M. Goedkoop, R. Heijungs, M. Huijbregts, A. De Schryver,
J. Struijs, and R. van Zelm, ReCiPe 2008: A life cycle impact
assessment method which comprises harmonised category
indicators at the midpoint and the endpoint level. Ruimte en
Milieu: Netherlands, 2009.

Figure 4b. Contribution of biogas manure management systems
to marine water eutrophication potential
4. Implications
The results clearly indicated that losses of biogas fromdigesters as well as the intentional release of biogas andemissions of methane from manure storage compromise thebeneficial effects in terms of global warming brought about by
using the biogas produced to replace other fuels. Although thecurrent results still indicate that there is an overall advantage, it
is clearly diminished by these losses. However, biogas
digesters can become a means of reducing global warming
impacts relatively easily if CH4 emissions can be kept low. Thisknowledge will be helpful for proposing interventions for
efficient manure management through improved biogas
systems.
Furthermore the current analysis clearly demonstrates thatbiogas digesters are exacerbating matters with the low
recycling of nutrients from animal waste. The environmental
costs associated with reduced nutrient recycling caused by thedigesters means that in order to make the digesters moresustainable it is pertinent to develop better methods andtechnologies to ensure the recycling of nutrients contained in
the digestate.
Acknowledgments
The current study was supported by the SUSANE II project
funded by the Danish Development Cooperation Danida.
References[1] Vu, Q.; T. Tran; P. Nguyen; C. Vu; V. Vu; L. Jensen. Effectof biogas technology on nutrient flows for small- andmedium-scale pig farms in Vietnam. Nutr. Cycl. Agroecosyst.
2012, 94, 1-13.
[2] JRC and IES, ILCD Handbook: General guide for life cycle
assessment − Detailed guidance. Publications office of theEuropean Union: Luxembourg, 2010.
[3] Poeschl, M.; S. Ward; P. Owende. Environmental impactsof biogas deployment − Part I: life cycle inventory forevaluation of production process emissions to air. J. Clean.
Prod. 2012, 24, 168-183.
[4] Rehl, T.; J. Muller. Life cycle assessment of biogas
digestate processing technologies. Resour. Conser. Recy. 2011,
56, 92-104.
[5] De Vries, J. W.; T.M.W.J. Vinken; L. Hamelin; I.J.M. de
Boer. Comparing environmental consequences of anaerobic
mono- and co-digestion of pig manure to produce bio-energy −A life cycle perspective. Bioresour. Technol. 2012, 125,239-248.
[6] Hamelin, L.; M. Wesnes; H. Wenzel; B.M. Petersen.

�������������������������������������������������

28C5-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

57

Resource Logistics for sustainable management of agricultural nutrients
Kazuyo Matsubae,*1 Keisuke Nansai2, Kenichi Nakajima2, Tetsuya Nagasaka11

1. Introduction
Agricultural nutrients including phosphorus, potassium,and nitrogen are essential elements for food production. The
global population is predicted to exceed 9 billion by 2050, andfurthermore, bioethanol production has increased by about
three times over the past ten years. As a result, the resources for
agricultural production including water, land and fertilizer will
be of increasing importance in next few decades [1]. However,there are growing concerns over supply strategies for essential
resources because of environmental problems, such as
eutrophication (N, P), acidification (N), resource depletion andprice increases (P) [2]. For the sustainable resource governance,
we proposed resource logistics analysis, based on material flow
analysis and input output analysis, and discuss the strategic
management of the flow of resources through the supply chain
in our society.

Nitrogen flows (kt-N)

Tohoku University, Japan 2National Institute of Environmental Studies, Japan*Corresponding author: matsubae@m.tohoku.ac.jp
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0

1,000
800

3. Results and conclusion
Our results shows that the nitrogen and phosphorus flows
which caused by Japanese final demand were 1,601kt-N and
242kt-P, in which 39% of N (629kt-N) and 46% of P (126kt-P)
from USA (Fig.1-2). Regarding with N flows, direct flows toJapan was originated from Australia, USA, and China. On theother hand, indirect flows have been originated from USA,
UAE, Saudi Arabia, and Russia.
Looking at the P flows, direct flows to Japan was originatedfrom USA, China, and Australia, where are agricultural
production countries. On the other hand, indirect flows havebeen originated from USA, Morocco, and China, where are theP rock mining countries, and fertilizer production countries.
Considering the economic structure and geopoliticalproblems, it was found that special attention should be paid tomaintaining a stable supply of agricultural nutrients resources
to ensure stability in agricultural production as well as in the
many industries which use phosphoric acid (P) and ammonia(N) as an essential chemical material.

0

Material
Fossil fuelFood / Feed

To except Japan

OthersIntermediate goods
Fossil fuel600

Food and feed

400
200

Phosphorus flows (kt-P)

Fig. 1 Direct and indirect nitrogen flows related with Japanese
final demand
200
180
160
140
120
100
80
60
40
20
0

40

Phosphorus flows (kt-P)

References[1] Rockstrom, J., W. Steffen, et al. Nature 461(7263): 472-475,
2009.
[2] Matsubae, K., et al. Chemosphere 84(6): 767–772, 2011.
[3] Nansai, K., et al. Environ. Sci. Technol. 46, 155-163, 2012.

Others1,200

2. Method
This paper incorporates the agricultural nutrient flows into
the 2005 input-output model of the Japanese economy, andintegrates international trade statistics on the basis of Global
Linkage Input Output (GLIO) model [3].

Acknowledgments
This study has been partly supported by research funds
from the Research Institute of Science and Technology forSociety of Japan Science and Technology Agency,(JST-RISTEX) as a research program on Science of Science,
Technology and Innovation Policy.

To Japan

To Japan

Other commodities
Material
Fossil fuelFood /Feed

To except Japan

35

Other commodities

30

Material

25

Fossil fuel20

Food /Feed

15

10
5
0

Fig. 2 Direct and indirect phosphorus flows related withJapanese final demand�������������������������������������������������

28C5-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

58

Monetary and Physical Flow Analyses on Products of Agriculture
Yuko Oshita,*1 and Yasunori Kikuchi2
1

Kobe University, Japan; 2 The University of Tokyo, Japan*Corresponding author: y_oshita@maritime.kobe-u.ac.jp

1. Introduction
Agriculture industry of Japan is facing many critical issue,e.g., aging workers, lack of young workers, climate change,
using biomass resources, food safety, stabilization of income
and free trade restrictions of products. As well as main
products (foods and wood material etc.), by-products (e.g.,bagasse, chaff and timber offcuts) have become important
products as biomass renewable resources, regarding agricultureindustry. To build robust domestic-supply chains, we needinnovation in consideration of process of agriculture, system ofusing by-products, social system and supply and demand
structure. However the flows from agriculture to final
consumers through other industries are still unclear.
This paper analyze not only monetary flows but also
physically flows of products of agriculture and outlines present
structure. Then we propose a new design for robust supply
chains by introducing new biomass conversion technology orsuggestion of the products which they should focus etc.
We apply technique of structural path analysis (Defourny
and Thorbecke, 1984; Lenzen, 2002; Oshita, 2012) to extract
the monetary and physically flows. In this study, we analyze
the flows of 6 products, rice, potatoes, vegetables, fruits, sugar
crops, and logs which cover 90% of their total domestic output.
2. Methodology
Using input-output model, the domestic output of eachindustry can be estimated with the following eq. (1):xI  A 1 y(1)where x is a matrix representing the domestic output, I is an
identity matrix, A is an input coefficient matrix and y is a matrix
representing the final demand. I  A 1 is the Leontief
inverse matrix (L), where the elements of the matrix represent
the demand for each commodity input directly and indirectly to
produce one unit of each commodity. In other words, eq. (1)represents the direct and indirect production of each commodity
induced by each final demand.
The Leontief inverse matrix L can be converted into a
series expansion. Eq. (1) can be converted as eq. (2):x y  Ay  A 2 y  A 3 y 

(2)Each term of the right hand of eq. (2) can be decomposed
to element, which express supply chains. For example, the third
term (A2y) can be expressed by aijajkyif, which represents a
supply chain: industry i (intermediate product)  industry j(intermediate product)  industry k (final product) final
demand f.
Applying the structural path analysis method, we extract
supply chains which start from target products as eq. (3).
Fi  y  a y  a a y  a a a y  if

ij

f; j;k;l; i  target products

jf

ij

jk

kf

ij

jk kl

lf

(3)

The data used in this paper is extracted from the
1990-1995-2000-2005 Linked Environmental Input-Output
Table at the four-digit commodity classification level compiled
by Japan’s National Institute for Environmental Studies.

3. Results and discussion
From the results, it became clear that the structures of flow
are different on each agricultural products. Rice, vegetables
and fruits have relatively simple flows, most of them go to final
consumer directly or secondarily. On the other hand, sugar
crops and logs have complex flows, and they go to final
consumer through many industries, not only food industry but
also chemical industry. Many agricultural products produce
by-products, and the by-products go to agriculture and dairy
farming as compost and feed etc., some by-products from logs
go to energy industry.
According to results of monetary flows, rice are supplied
to grain milling (86%), 60% of domestic output of rice aredemanded by household as grain milling. In short, such supply
chain: rice  grain milling  household occupy 60% of all
supply chain. Other rice (grain milling) are supplied to eating
and drinking services or foods manufacturing. Also more than
60% of all vegetables and fruits are supplied directly to final
consumers, and most of them are household. Rest of direct
consumption are supplied to industries which are like flow ofrice. However it is a noteworthy that by-product of rice: ricestraw and chaff, supplied to livestock sector and vegetables as
fermentation feed and compost. On the other hand, the ratio ofsugar which is supplied to household directly is only 9.5% of
total output of sugar crops. The most of them are supplied toeating and drinking services and food manufacturing.
By-products of sugar crops, bagasse and filter cake etc., also
supplied to livestock sector and vegetables. Potatoes is used for
not only food, but also industrial starch. Therefore the flow
diagram is relatively complex and has many industrial sectors.
Flow of logs is most complex, and their by-products are usedby agriculture and livestock sectors and power generation.
However physically flows of the by-products are large,
monetary flows of them are so small because of low price ofthemselves.
4. Conclusion
It is necessary for sustainability of agriculture that main
products (foods and logs) which have highly-added value evenin small quantities are produced and also flows of by-products
in large quantities make economically feasible. To build a more“benign” process and supply systems, the technology roadmaps
containing future development should be carefully taken into
account within the physical and monetary flow analyses, which
can facilitate the involvement of related stakeholders.
References[1] Defourny, J., and E. Thorbecke. Structural path analysis
and multiplier decomposition within a social accounting
matrix framework. Economic Journal, 94 (373): 111-136,
1984.
[2] Lenzen, M.. A guide for compiling inventories in hybridLife-cyccle assesments: some Australian result. Journalof Cleaner Production, 10(6): 545-572, 2002.
[3] Oshita, Y.. Identifying critical supply chain paths thatdrive changes in CO2 emissions, Energy Economics, 34(4): 1041–1050, 2012.

�������������������������������������������������

28C5-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan59

Evaluation of environmental improvement by introduction of Eco-feed
Hongqin Yu ,*1 and Hiroshi 2
1 Graduate School of Nippon Institute of Technology; 2 Nippon Institute of Technology* yukoukinn@yahoo.co.jp

1. Introduction
90% livestock feed is imported from abroad in Japan1).
Arable land area required for the imported livestock feed
production is estimated as 3.63 million ha, which corresponds
to 77% of the agricultural land area of Japan2).
This study focuses on eco-feed which is made by foodwaste3). The introduction of eco-feed is possible to solve theproblem of waste disposal, to solve the problem of livestock
management, and to suppress the resource depletion. Recyclingof food residue has been attracting attention from the point ofview of environmental protection, but it can not be said thatenvironmental aspects of eco-feed has been fully elucidatedyet.
2. Purpose
The purpose of this study is to assess the environmental
impact by the introduction of eco-feed. Specifically, beer lees
which occurres from Sapporo beer factory in Hokkaido was
ensiled. Beer lees is made it into eco-feed and it is used tolivestock of Tokachi. Environmental load and economic
aspects were considered on eco-feed.
3. Research methods
During the consideration of environmental evaluation of
eco-feed, the model of silage of Sapporo beer lees on Hokkaido
is assumed (Figure 1).
The target of this study is livestock feed combined system
of food waste (Figure 2). The environmental impact of the eco
feed is quantitatively evaluated. GHG emissions is estimatedby JEMAI-LCA Pro and the environmental impact of beer leesis evaluated. The economics of eco-feed is also considered(Figure 3).

One way:
46.427km

Sapporo feed Advancement
CenterAnimal feed (processing)
One way:
193.367km

Transport
Tokachi Livestock(Consumption)

Figure 1. the model of silage of Sapporo beer leesHeatsterilization

Food
waste

Ensiled+Loss-

By-product0

Lactic acidfermentation

Solid-liquid
separation

Waste
eggshellSolid residue

Desalted

Dryingprocess
Mixed feed raw
materials

Figure 2. Livestock feed combined system of food waste

StrengthdemandThe cost of disposal

DryingFigure 3. the economics of eco-feed
4. Result
Table 1 shows the energy of making eco-feed. Table 2
shows the results of the environmental impact of collecting
beer lees, manufacturing, transportation, up to use. Table 3
shows the results of comparison of the environmental impact
and economic of formula feed and eco-feed
Table 1. the energy of making eco-feed3)
Fermentation
DryingBeer lees: 100kg
70kg / batch
Desalted solution: 100kg
Banner fuel: 58kW
Ph for eggshell: 6kg
Gas: 10.8 m3 / batch
Electrical: 3kW
Table 2. the results of the environmental impact
SectionEco-feed(14kg)

Hokkaido Sapporo Beer Factory
Beer lees (raw materials)
Transport

ProfitEmissions of the entire CO2
29.5kgTable 3.Comparison of the environmental impact and economicof formula feed and eco-feed
Feed unit price:
Environmental
Sectionyen / kg
Impact: kg-CO2
0.32
Formula feed50
0.52
Eco-feed
43.25
5. Summary
Both of Environmental and economic aspects impact were
evaluated of silage of beer lees that occurred in the Sapporo
beer factory located in Hokkaido.
Unit price of 1kg eco-feed is 6.75 yen cheaper thanformula feed, but it is 0.2kg CO2 emissions more than formulafeed. It is necessary to improve the environmental technology
of silage of beer lees.
6. References[1] http://www.maff.go.jp/tokai/seisan/tikusan/zansa/pdf/02ki
choukouen.pdf (Accessed 18.01.2014).
[2] http://souchi.lin.gr.jp/skill/pdf/jikyuusoshiryo.(Accessed
18.02.2014).
[3] www.maff.go.jp (Accessed 18.03.2014).

�������������������������������������������������

28C5-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

60

Uncertainty analysis for greenhouse gas impact of feedstuff in Korea
Yoo-Sung Park, Min-Hyuk Lee and Kun-Mo Lee*
Eco-product Research Institute, Ajou University, Suwon, Korea*Corresponding author: kunlee@ajou.ac.kr
1. Introduction
The aim of this study is to assess the uncertainty of thegreenhouse gas (GHG) emission of the feedstuff for the
livestock industry using the linear GHG model equation, and tocompare the model results between the single point estimation
method and the range estimation method.
2. Method
System boundary of this study is the cultivation offeedstuff in an agricultural farm. The system includes
fertilization, chemicals, mechanical treatment and harvest.
Figure 1 shows the system boundary of the feedstuff
cultivation.

of GHG emission of wheat and alfalfa overlaps. Furthermore,
the point estimation results of both feedstuffs are located inside
the overlapped area. This is a clear indication that there is nodifference in both GHG emissions as such one cannot sure bewhich feedstuff is more environmentally significant in thiscase.
Feedstuff
Rice Straw
Rapeseed
Wheat
Alfalfa
Corn

Table 2. Range estimation result
Values (min.)Values (max.)
0.152 kgCO2-eq/kg
0.184 kgCO2-eq/kg
0.623 kgCO2-eq/kg
0.894 kgCO2-eq/kg
0.481 kgCO2-eq/kg
0.624 kgCO2-eq/kg
0.521 kgCO2-eq/kg
0.361 kgCO2-eq/kg
1.090 kgCO2-eq/kg
1.369 kgCO2-eq/kg

Figure 1. System boundary of the feedstuff cultivation
Functional unit is 1kg of each target feedstuff. The target
feedstuff includes straw, corn, wheat, alfalfa and rapeseed.
Input/output data of the feedstuff cultivation and activity
data were collected from the on-site investigation, andbackground data were collected from the statistics Korea,
Ecoinvent and Korean LCI DB Information Network [1-4].
GHG emission from soil was calculated by Greenhouse Gas
Inventory & Research Center of Korea [5].
In this paper two different types of the GHG emission
results of the feedstuff were generated: one is the point
estimation result and the other the range estimation result.
Comparing two different types of the results, one can identify
how they affect decision about the environmental issues aroundthe feedstuff cultivation.
3. Result
GHG emissions of the target feedstuffs based on the point
estimation method and the range estimation method are shownin Tables 1 and 2, respectively. From Table 1, one can identify
clearly the order of the magnitude (rank) of GHG emission of
the feedstuffs. However, Table 2 shows that GHG emission
range of wheat overlaps with that of alfalfa. Figure 1 shows theoverlapped area between wheat and alfalfa.
Feedstuff
Rice Straw
Rapeseed
Wheat
Alfalfa
Corn

Table 1. Point estimation result
Values0.169 kgCO2-eq/kg
0.737 kgCO2-eq/kg
0.552 kgCO2-eq/kg
0.441 kgCO2-eq/kg
1.216 kgCO2-eq/kg

Rank
5
2
3
4
1

Grey area in Figure 1 shows that 95% confidence interval

Figure 1. GHG emission result of the wheat and alfalfa
4. Conclusion
The range estimation result indicates that single point
estimation result cannot be a good indicator for identifying key
environmental issues in some cases.
For identifying the environmental key issues, one must
pay attention to the uncertainty of the data and the impact
model results from the data. At the same time, every effort
must be given to reduce the error of the data and the model
results.
Acknowledgments
This work was supported by the Korean National Instituteof Animal Science and was performed as part of a project
entitled 'Development of an estimation method and tool foraccounting CH4 and N2O emissions from livestock'.
References[1] Ministry of Agriculture, Food and Rural Affairs (MAFRA),
Statistics of Food, Agriculture, Forestry and Fisheries, Korea, 2013[2] Statistics Korea: Korea Statistical Information Service.
http://www.kosis.kr/index/index.jsp (Accessed 17. 08. 2014)[3] Korea Environmental Industry & Technology Institute (KEITI).
Korea LCI Database Information Network. http://www.edp.or.kr/
lcidb/english/main/main.asp (Accessed 17. 08. 2014)[4] Ecoinvent Centre, Ecoinvent version 2.1. http://db.ecoinvent.org/
index.php?newlanguage=en (Accessed 17. 08. 2014)[5] Greenhouse Gas Inventory & Research Center of Korea (GIR),
National Greenhouse Gas Inventory Report of Korea, 2013�������������������������������������������������

28D3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

61

Analyzing the Carbon Emissions of Cloud Computing Facilities
Kendra Tupper1
1City of Boulder (Community Planning and Sustainability), United States

1. Introduction
In 2020, experts predict that the world’s data centers will
use about 285 TWh/year of electricity. With the growing shift toprivate and public cloud computing facilities, it is important tounderstand the key drivers for efficiency and emissions
reductions in these type of data centers.
In addition to large private cloud facilities and publichyperscale cloud providers (e.g., Google, Salesforce), there is a
rapidly growing marketplace referred to as Multi-Tenant Data
Center (MTDC) providers, also known as colocation providers.
Multi-tenant data centers are shared data centers where
customers lease space and power to run their computing
equipment rather than managing their own data center. By 2016,
more than a quarter of all data center capacity will be deliveredby MTDC service providers, rather than being managed inhouse by small, medium and large organizations.
The main drivers of operational efficiency andsustainability for cloud computing facilities are:
 Power Usage Effectiveness (PUE): The efficiency of the
facility housing the servers, including cooling, power
distribution, and lighting
 Hardware efficiency: The efficiency of the servers, data
storage, and networking equipment
 Server utilization factor: How much of the server’s total
processing capacity is effectively utilized Electricity carbon emissions factor (kg CO2eq per kWh):carbon footprint of electricity powering the data center
2. Efficiency Potential of Cloud Computing
Cloud computing holds great potential to reduce data center
energy demand due to both large reductions in total servers
through consolidation and large increases in facility efficiencies
compared to local, smaller counterparts. While studies haveshown that large, internal implementations can be as efficient as
cloud providers, the vast majority of enterprise or small/medium
businesses cannot compete with the cost or efficiency of large
aggregated cloud providers.[1] Further, many cloud providers,
including Google, Microsoft, and Salesforce, have compared thecarbon footprint per user of their services versus on premise data
centers, reporting carbon emissions savings between 50-95%.
However, not all clouds are created equal; there are“green” clouds and “brown” clouds. And while the average
PUE of large cloud facilities is typically at least 35% better
than on premise facilities, a highly efficient and virtualized onpremise facility can have a comparable carbon footprint to an
average cloud facility.
3. Strategies to Reduce Emissions from Cloud Computing
While there are many ways to increase efficiency andreduce carbon emissions in data centers, I will highlight six:
1. Increase Server Utilization: Average server utilization isvery low in most data centers and this has a big impact onenergy use. A McKinsey study [2] noted that as much as
30% of servers are utilized less than 10% of the time.
2. Improve Airflow Management: By isolating the flows ofcold and hot air, you can decrease the amount of cold air
required and increase the efficiency of the HVAC systems.
3. Increase Data Center Temperatures: It is common practicein data centers is to set air conditioning set points between

68oF and 72oF. Most IT equipment purchased since 2006
can easily operate at temperatures up to 95oF.
4. Better IT System Efficiency: More efficient IT equipment(servers, power supplies, etc.) can produce more work per
watt, and significantly reduce energy use when idle.
5. Improve Software Efficiency: New software can shift
where loads are processed when an outage is detected.
With this, the facilities don’t have to be built so
redundantly, leading to more efficient operation.
6. Power the Data Center with Clean, Renewable Energy
4. Relative Impact of Key Variables
While the impacts of improving PUE and the carbon
content of the electricity source is clear, the importance ofutilization is often overlooked. Recent analysis shows that
increasing the utilization of a data center has a far moresignificant impact on energy and carbon emissions thandecreasing the PUE.

Figure 1. Relative Importance of Data Center Efficiency
Variables [1]6. Barriers in MTDCs
There are four primary reasons why MTDCs have not beenable to achieve best-practice energy efficiency performance todate and they cover the spectrum from behavioral, to contractual,and policy-oriented. Specifically, they include:
1. De-prioritization of energy efficiency vs. competing
priorities due to contractual relationship
2. The split incentive and behavioral challenges between
customers and the provider
3. A lack of clear, robust and available incentives andfinancing from policy makers to apply within the MTDC
environment
4. Customer concerns over sharing application instance andserver infrastructure to increase utilization
References[1] National Resources Defense Council and WSP Environment& Energy. The Carbon Emissions of Server Computing for
Small to Medium Sized Organizations. October 2012.
[2] Forrest, Will. Revolutionizing Data Center Efficiency.
McKinsey & Company, July 2008.

�������������������������������������������������

28D3-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan62

New Key Performance Indicators for Smart Sustainable City
Jiro Nakamura and Minako Hara*1
1

NTT Energy and Environment Systems Laboratories, Japan*Corresponding author: hara.minako@lab.ntt.co.jp

We propose key performance indicators (KPIs) based on
the Gross Social Feel-good (GSF) Index [1] to evaluate a Smart
Sustainable City and report the results of a city field trial
conducted in the center of the Tokyo Metropolitan Area.
We developed new KPIs based on the following concepts:
1.
The triple bottom line forms the basis of theevaluation criteria.
2.
The same unit is used for every evaluation
criterion.
3.
The KPIs can be used to measure a diverse range ofSmart Sustainable Cities with different goals.
The GSF Index is used as the basis of the proposed KPIs,
which are aligned with 1, 2, and 3 listed above. Six indicators(“environment”, “economy”, “comfort”, “health”, “safety”, and“happiness”) are proposed for the GSF Index. These indicators
along with the proposed KPIs of the Smart Sustainable City are
divided into four layers for simplicity, and the triple bottom
line and “satisfaction” constitute the first layer. Since thenotion of “society” is broad, this layer is further split into
“safety”, “health”, and “comfort,” and then positioned in thesecond layer. The third layer includes indicators such as“information security” and “ubiquity” from an ICT perspective.
Each KPI was evaluated for one year using the following
procedures.
(1) Environment: Life cycle CO2 emission of the ICT system
and reduced CO2 emission realized by reducing the
movement of helpers by car were calculated based on
L.1410 [2]. An improved KPI value was obtained bycomparison of both scenarios(2) Economy: The construction cost of the ICT system, theoperating expense (electric charge) and the increase in shop
sales were calculated.
(3) Society: The reduction in traffic accidents and the
reduction in time spent in a refuge at the time of a disasterwere calculated.
(4) Satisfaction: The willingness to pay for each ICT service
was obtained by asking users to complete a questionnaire.
We undertook a trial evaluation using the proposed KPI ina Smart Sustainable City where ICT systems including ‘IPannouncement’, ‘Wi-Fi around the station’ and ‘informationtransmission and control’ are introduced.
References[1] Jiro Nakamura et al., Analysis of the potential
contribution of ubiquitous network services to asustainable society, ISEE2006 (IEEE).
[2] Recommendation ITU-T L.1410, “Methodology for theassessment of the environmental impact of informationand communication technology goods, networks andservices”

�������������������������������������������������

28D3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

63

Social Impact Assessment of ICT Services: Case Study and Tool Realization
Julien Boisseau,*1 Tomoko Tanaka,1 Ahmed Zeddam,1 Kazue Takahashi,2 and Takashi Sawada2
1

Orange Japan, Japan; 2NTT Energy and Environment Systems Laboratories, Japan*Corresponding author: julien.boisseau@orange.com

1. Introduction
Information and Communication Technology (ICT)
products and services know a worldwide exponential growth,with notably over two billion people connected to the Internet.
The benefit of telecommunications on the development ofcountries and their people, not only from an economic point ofview, is enormous. This is especially true for emerging
countries where ICT services often compensate for a lack ofinfrastructures such as banks or health centers.
Today, several economic indicators are at our disposal tomeasure part of this benefit. The environmental aspects are also
more and more precisely described through life cycle
assessments. However, the quantitative evaluation of impacts
related to the third pillar of sustainable development – society is still lagging behind, at least at the scale of a service.
2. Social impact assessment principle
NTT and Orange have been working on solving this issue
by co-developing an original tool that considers all impacts ofan ICT service or product and translates them into monetary
values for an easy understanding of results [1-2]. It is
composed of several indexes, with the notion of “society” - toobroad and vague - being subdivided into different notions:
economy, environment, health, comfort, safety, education.
Whether the value of the indexes is positive or negative, small
or high, enables to check to what extent a service contributes or
not to the realization of a sustainable society.
3. Assessment example: solar charger for off-grid areas
To illustrate the concept of social impact assessment, theexample of a portable solar charger, to refill mobile phonebatteries and power LEDs, is chosen. Such products target
off-grid rural populations of emerging countries. They
normally have to walk several kilometers in order to find astore providing a mobile phone battery charging service for afee, and to purchase the kerosene that fuel the lamps in theirhouses at night.

current situation. For instance, the safety index translates theadvantage of eliminating the risk of burn, of house fire and ofkerosene ingestion by children, related to the use of traditional
lamps. The health index deals with the problems of indoor
pollution and respiratory diseases and the comfort index withthe transportation time saved and the increase of humanrelationships if the family uses the solar charger to create its
own charging business.
4. Social impact assessment tool
Use cases conducted in various countries on ICT services
with different profiles (videoconference service, m-healthservices…) proved the relevance of the approach adopted, bygiving results consistent with reality. They also helped
clarifying the definition of each index.
Realizing quantitative assessments based on realistic
scenarios is however quite time-consuming and sometimes
controversial. Monetizing the impacts of ICT services requires
indeed putting figures on notions that can be abstract and hardto quantify or hard to find in the literature, such as the value oflife, the value of time or the value of human relationships.
In order that those obstacles do not slow down thewidespread adoption of social impact evaluation, Orange andNTT have been working on a tool that would integratemonetization equations and a database to automaticallygenerate results. After selecting the category of the service toevaluate, the tool user still needs to input a few data describing
the evaluation boundaries and scenario. But the purpose is todevelop an interface as user-friendly as possible to familiarize
people with the notion of quantitative social impact assessment,
still quite new. Transparency is also an important aspect, data
and monetization equations being visible to enable a criticalunderstanding of the results.
There is of course a trade-off between user-friendlinessand accuracy / degrees of freedom of the evaluation. However,realizing a working version of a social impact assessment tool
still represents an important step for the promotion of such
evaluations.
5. Conclusion
To continue the development and promotion of social
impact assessment tools, additional use cases need to be
conducted to confront the progress made with the tool
realization and its result consistency. Discussions among actors
with different points of view are also essential to improve themethodology and find consensuses, in order to one have at our
disposal social impact assessment tools as sophisticated andwidely used as those for environmental impacts.

Figure 2. Social impact assessment results for solar charger
If the environmental impact of solar charger can alreadybe evaluated [3] and the return on investment easily calculated,bringing to light the numerous social benefits is new. “Figure
1” shows the results of the comparative study, a positive graphvalue meaning that the solar charger is more beneficial than the

References[1] Tsuda, M.. et al. Gross Social Feel-good Index - Social
Impact Assessment for ICT Services. NTT Technical
Review, Vol. 5, No. 3, 43-47, 2007.
[2] Boisseau, J., et al. Social impact assessment tool for thedesign of sustainable ICT services – Case study onvideoconference in Japan and France. Ecobalance, 2011.
[3] Dave, S. Life Cycle Assessment of Off-Grid Lighting
Applications: Kerosene vs. Solar Lanters. Massachusetts
Institute of Technology, 2009.

�������������������������������������������������

28D3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

64

Multiple Environmental Impact Assessment Method on Biodiversity for Industry
Kazue I. Takahashi*1, Eri Matsunaga1, Takashi Sawada1, Norihiro Itsubo2,
Masaharu Motoshita3, and Kayo Murakami4
1

NTT Energy and Environment Systems Laboratories, NTT Corporation; 2Tokyo City University;
3

National Institute of Advanced Industrial Science and Technology; 4Kyoto University*

takahashi.kazue@lab.ntt.co.jp

1. Introduction
People enjoy various benefits from ecosystems.
Therefore, biodiversity has become as important anenvironmental issue as global warming. To promote
environmental management, the total effect on an
biodiversity should be understood quantitatively andobjectively. The ultimate goal of our study is to establish
a biodiversity impact assessment method for evaluating
industrial activities. We proposed a hybrid impact
assessment method consisting of Environmental
Economic Analysis (EEA), Life Cycle Assessment(LCA) and Ecosystem Service Loss Index (ESLI) on
land use [1]. Our integrated method quantifies both
negative and positive effects. If the method is to be
implemented, a single indicator is essential. The resultsof EEA are initially shown in terms of the samemonetary value. And the LCA results can be converted
to a monetary value if we use the Lifecycle Impact
assessment Method based on Endpoint modeling(LIME) 2. On the other hand, the ESLI results have aphysical value, such as volume (m3) and weight (kg) [2].
Therefore, we developed new conversion coefficientsfor transforming a physical value to a monetary value
and reported the impact of typical Japanese corporate
activity as a case study.
2. Method
To obtain the conversion coefficients, we selected analternative cost method and a preference assessment
method. As the former method we referred to thecoefficients used for evaluating the functions ofagriculture and forests [3] concerning the ecosystemservices of carbon storage, flood adjustment and water
preservation. The weight coefficient of LIME wassubstituted in relation to Net Primary Production (NPP).
As the latter method, we used the results of a conjoint
analysis of green space to evaluate willingness-to-pay(WTP) [4]. As a case study, we evaluated the loss to theecosystem caused by companies’ land use by modeling areal Japanese group company that occupies 30 million
m2 of land throughout the country.
3. Results and Discussion

The evaluation results are shown in Figure 1. Carbon
storage had the greatest impact on ecosystem service.
The ecosystem service losses obtained with thealternative cost method were greater than those obtainedwith the preference assessment method. The total
ecosystem service loss was 57 billion yen with thealternative cost method and 9 billion yen with thepreference assessment method. The total impact ofmaterial and energy use by the same group company was
about 1 billion yen from the LCA evaluation. The land
use impact was greater than that of the material andenergy use and so the impact of land use is very
important. We examined the consistency and found thepreference assessment method to be preferable for an
integrated evaluation.

Figure 1. ESLI results shown as monetary values.
References[1] Takahashi K. I., Nemoto Y., Sugiyama Y., Itsubo N.,
Murakami K., Motoshita M., The 8th Meeting of theInstitute of Life Cycle Assessment, Japan, pp. 176-177,
2013[2] Motoshita, M., Nitoh W., Kamo M., and Honda T.,
The 7th Meeting of the Institute of Life Cycle
Assessment, Japan, pp. 188-189, 2011[3] SCJ, Report on evaluation of the various functions ofagriculture and forest, concerning global environmentand human life,
http://www.scj.go.jp/ja/info/kohyo/pdf/shimon-18-1.pdf(Accessed 21.08.2014)[4] Asaki H, Master’s thesis at Tokyo City University,
2014,�������������������������������������������������

28D4-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

65

Case study on effect of mechanics development of telecommunication product on material
efficiency
Lauri Smalen,1 Timo Junno,1 Topi Volkov,1 Timo Galkin,*1 Elisabeth Dechenaux,2 Marc Aubree,2 Tomoko Tanaka,3Heikki Karvinen4
1

Nokia Networks, Finland; 2Orange, France; 3Orange, Japan; 4Aalto University, Finland*Corresponding author: timo.galkin@nsn.com

1. Introduction
The Europe 2020 strategy recognizes the global challenges
and opportunities presented, interpreting sustainable growth as“building a resource-efficient, sustainable and competitive
economy, exploiting Europe’s leadership in the race to develop
new processes and technologies”.
This study is linked to this strategy by being part of ongoing
Opera-Net 2 project activities in Eureka Celtic Plus program.
Aim of this project is to reduce the environmental impact ofmobile radio networks, and focuses on power, material andresource efficiency improvements.
2. Resource efficiency and sustainability
Recently Design for Resource Efficiency (DfRE) has received
an increasing interest. The definition of Resource Efficiency
varies. Sometimes it covers raw material consumption only,
sometimes also pollution of natural resources and ecosystem isincluded. In addition to material efficiency, in this study
resource efficiency covers natural resources (fossil fuels). In
general, DfRE has three objectives: reducing the environmental
impacts, improving resource supply security including lowering
import dependency for example for metals, and saving the
production costs.
The sustainable use of raw materials is widely accepted but there
is no consensus yet how “resource use” should be measured.
The measurement can be made based on definition of physicalindices like mass and material input per service unit or impact
assessment indicators of LCA, like Resource Depletion (fossil
fuel or minerals). From the life cycle based sustainability
assessment point of view, DfRE approaches are not always
suitable, because they only look at the output side of a productand try to make it easy to deal with the scrap at the end of life,
which enables the reusability of the raw material for future
products. From the sustainability perspective it is necessary tolook at the input side, for example recycled material content,
which means how much used materials actually replace primarymaterials.
3. Changes in radio access product mounting kit
The life cycle of the Flexi mounting kit was divided into 4life cycle stages: raw material acquisition, production, use, andend-of-life treatment. The production stage includes die castingof aluminum in versions 104-105 and 206. Kits in this study
were manufactured in China, and then transported to the use
place. The amount of materials used was reduced from 6.7kg to
2.8kg, and the stainless steel was replaced by die cast aluminum.
In this comparative LCA product packaging and use phase were
cut-off because there is no difference between each version.
4. Evaluation of new material possibilities
Materials with low environmental impacts, light weight andstiffness were searched with CES Selector software. Study
showed that cast aluminum is the optimum choice. Other
materials with suitable properties exist like galvanized andstainless steel, magnesium and PC. But, those materials might
not be practical or cost-effective to be processed into products.

4. Impact of changes on environmental parameters
According to LCA methodology results (Table 1), kit
version 206 has the smallest environmental impact due to thehigh percentage of recycled material (100%) and an optimized
structure which allows reducing the amount of used material.
Table 1: Improvement history of mounting kit
Version of
101-102 103
104-105 206
Mounting kit
Main Change

Material Manuf.
tech.
Manufacturing
Stainless Al and
Al dietechnology
steel (SS) SS sheet cast
sheet
parts
Stainless steel
6720
1550
110
Aluminum
0
3071
4120
Polymeric mat. 9
90
Total [g]
6729
4630
4230
RecycledAl0%100%
content [w %]Climate Change 20,56
30,15
16,27
[kgCO2eq]
Resource
253,4
362,2
295,7
Depletion (fossil
fuels)[MJ]

Designoptimizing
Al die cast
110
2720
0
2830
100%
10,85
196,6

6. Conclusions
Our goal was to minimize the impacts on the environmentof the materials used for a mounting kit. The results showed thatcast aluminum is the optimum choice. There are materials withsmaller density (magnesium, engineering thermoplastics) or
smaller environmental impacts (galvanized steel) but aluminumprovides a good combination of properties.
The design of the new kit allows the use of a smaller
quantity of metal and mainly of recycled aluminium. When
metals are recycled, there is a clear reduction in environmental
impacts, especially because the recycling of metals decreases
the demand for primary metals as raw materials.
Acknowledgments
The French Ministry of Industry and the Finnish Funding
Agency for Technology and Innovation (Tekes) have partially
funded this study through Opera-net 2 project.
References[1] ISO 14040/44[2] ETSI TS 203 199[3] ITU L.1410[4] ICT 2013 conference – Casablanca “Environmental
Friendly Mobile Radio Networks: Approaches of theEuropean OPERA-Net 2 Project”[5] European Commission. 2011. Sustainable Industry: Goingfor Growth & Resource Efficiency. 42 p

�������������������������������������������������

28D4-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

66

Five IT Thoughts from a Waste Management Proof-of-Concept Project
Yukihisa Yonemochi,*1 Takashi Sakairi,1 Hiroshi Horii,1 Scott Trent,1 Tatsuya Ishikawa,1 and Heather D. Achilles2
1

IBM Research - Tokyo; 2IBM T. J. Watson Research Center*Corresponding author: pandrbox@jp.ibm.com

1. Introduction
Intelligent Waste Management is a research effort basedon the Smarter Planet and Smarter Cities strategy of IBM
Research. To promote the sustainability ideals of reduce, reuse,
and recycle, sophisticated cities and companies in developed
countries like Japan are efficiently managing recycling with
reduced cost and zero-landfill methods.
This Proof of Concept project was a joint effort between
IBM Research, the IBM Corporate Environment Office and thecity of Dubuque, Iowa [1], USA. We had implemented anddeployed Waste Management software. Data monitoring,
integration, and analysis are key to achieving these goals.
However, today, most systems collect only one type of waste
related data (ex: weight), they do not include other waste datasuch as cost, container sizes, etc. To yield meanful results, allof these waste related data must be integrated and analyzed
together.
Our team identified five information technology issues
related to data integration and analysis. We will show andexplain concrete methods to resolve these issues based on our
IT experience along with associated examples. We will also
briefly introduce a software solution which can be used to
manage and analyze waste data.

variety of options for time range, waste type, process method,customer demographic, etc. Thus our reporting tool includes
data selection functionality.

Figure 2. Selecting types of waste to be reported
5. Prediction of waste trends
Importing data from six prefectures that the Japan
government published on their web[2] into our reporting tools,
we can see a report of that data. In addition, We can predict
goal achievement with forecasting as lines. We can use
simulation to understand the effect of various scenarios forplanning purposes. (Figure 3)

2. Integration into usable information systems
Relevant data include not only weight but also waste type,time stamp, location, process method, etc. However, the data
format for waste related data is not standardized. Hence data
integration is not trivial, and sophisticated data management
techniques are required.

Figure 3. Reporting tool for weight of waste

Figure 1. Data structure for waste management
3. Visualization and Interactive Reporting of Data
There are many reporting methods and tools. Data
presentation (e.g, graph selection) must be discussed. Our tool
can easily display this chart by simply selecting the name of atown, type of waste, or demographic of customer. Figure 2
shows selecting two types of waste.
4. Adoption of data mining methodologies
Many approaches and graphs will be used to understandthe data. The exact method depends on the question-at-hand.
Hence, data mining tools enable us to choose from a wide

6. Including data which may appear unrelated to waste
The goal is to understand and include useful data. For
example, data such as rainfall, temperature, humidity, event
plans, population changes, etc. Integrating this kind of data willproduce a valuable perspective for identifying relationships.
Conclusion
We had implemented the solution software through theseexperiences and provided some clients. The software iscontinuously updated for new enhancements.
References[1] Smarter Discards, THE CITY OF DUBUQUE, 2010,
http://www.cityofdubuque.org/index.aspx?NID=1732[2] Technical information of waste processing, Environment,
Japan government , 2014,
http://www.env.go.jp/recycle/waste_tech/index.html

�������������������������������������������������

28D4-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

67

Environmental Footprint for IT Equipment
Takaaki Kumazawa,*1 Osamu Namikawa,1 and Yasushi Furushima2
1

Hitachi, Ltd.,; 2Mizuho Information & Research Institute, Inc.
*Corresponding author: takaaki.kumazawa.sa@hitachi.com

㻯㼛㼚㼠㼞㼛㼘㼘㼑㼞
Software(firmware, function, etc.)

Hardware㻿㼠㼛㼞㼍㼓㼑㻌㼟㼥㼟㼠㼑㼙（processor, LSI, memory, etc.）㻿㼠㼛㼞㼍㼓㼑㻌㼙㼑㼐㼕㼍㻔㻴㻰㻰㻛㻿㻿㻰㻘㻌㼑㼠㼏㻚㻕

Figure 1. Configuration of storage system
The system boundary of LCIA includes production andtransportation of purchase parts, those of the product, use of the
product, and recovery of the used product. Most environmentalloads are included in these processes. Recycling processes
were not taken into account because the evaluation model had
not been decided in pilot test yet.
3. Evaluation
The breakdown of LCIA results were calculated in order tofind the difference of significant design parameter. Figure 2
shows results of using LIME2 and IDEA1.1.0. We selectedcategories which can be calculated and are relevant tocategories designated in PEF guide.



Use

Use

Use

Use

PCB

Transport
Photochemicalozone formation

PCB
Ecotoxicity,terrestrial

Use

Air pollution

Cable

Ecotoxicity,
freshwater

HDD
PCB
Eutrophication

Climate change

Use

Human toxicity,
non-cancer
effects

PCB

20%
0%

Use

Acidification

40%

Use

Resource
depletion

60%

Use

Use

80%

Human toxicity,
cancer effects

100%

Figure 2. Impact Assessment using LIME2 and IDEA

The power consumption during in use of product, shown as
Use in this figure, has significant impact on the climate change,
eutrophication, etc. This result presents the effectiveness of
conventional approach.

100%

PCB

Use

Use
PCB

PCB

PCB

Land use

PCB

Ionizing radiation,
human health

PCB

Ozone depletion

Use

Particulate matter

Ecotoxicity,
freshwater

Human toxicity, noncancer effects

PCB

Eutrophication,
marineUse
PCB

Resource depletion,
water

PCB

Photochemicalozone formation

PCB

PCB

Human toxicity,
cancer effects

PCB

PCB

Use
PCB

Eutrophication,
freshwater

0%

Use

PCB

40%

20%

Use

Use

Acidification

60%

Eutrophication,
terrestrial

80%

Climate change

2. Scope of LCIA
LCIA of the storage system[4] was carried out on this work.
The function of storage system is to records data and support
retrieval. Storage system is an integration of controllers,
storage devices such as HDD, and software as in Figure 1.

The impact of printed circuit board, shown as PCB, also
have a major impact on resource depletion and human toxicity.
The effects of HDD and the cable can’t be neglected oneutrophication and human toxicity. On the air pollution, theeffect of transportation is observed, which shows ship isassumed to be used for overseas transportation.
Figure 3 shows the preliminary calculations in PEF pilot
test. The impact assessment method is designated in PEF guide.
ELCD 3.0[5] and ecoinvent3.01[6] were used for LCA databaseto take the overseas environmental load into account.

Resource depletion,mineral & fossil

1. Introduction
IT equipment such as a server or a storage system runs
continuously as a data center equipment for enterprise.
Therefore, we have focused on climate change as the impact
category of IT equipment and reduced the power consumption
in use. The Product Environmental Footprint (PEF) [1] in EU,
which is still in pilot phase, will increase the need to consider
more impact categories on product development.
We have used LIME2[2] as an impact assessment method
and IDEA[3] as LCA(Life Cycle Assessment) databasedeveloped in Japan. However, another method is recommended
in PEF guide. Thus, it is important to understand how thedifference of the method affects product development.
The present work discusses the necessary activities ofmanufacturer based on two results of LCIA(Life Cycle Impact
Assessment). One is result of our conventional method and theother is preliminary result in PEF pilot test.

Figure 3. Preliminary calculation in PEF pilot test
The impact of Use and PCB are significant on climatechange and resource depletion of mineral & fossil in common
with Figure 2. However, the impact of PCB is much larger thanFigure 2 on eutrophication and human toxicity. On the other
hand, the impact of HDD and cable are not observed here. The
effect of transportation is not observed, either.
These results indicate a significant design parameter can bechanged in accordance with LCA methodology, that is an
impact assessment method and LCA database. Since theseresults are under discussion so far, we will focus on significant
categories and improve the quality of calculation.
4. Conclusion
The results of LCIA indicate the requirement for productdesign depends on LCA methodology. This means therequirements for manufacturer will expand if the countries orregions where they dispatch their products adopt their own
LCA method. This leads to cost issue.
In order to harmonize economy and ecology, the global
standardization of LCA methodology should be driven forward
as an academic activity. Manufacturers should work together
with them and build the flexible system to meet therequirements from customers.
References[1] COMMISSION RECOMMENDATION of 9 April 2013
on the use of common methods to measure andcommunicate the life cycle environmental performance of
products and organisations(2013/179/EU): 6-106, 2013.
[2] LIME2 summary, JLCA NEWS LETTER, No.12, 2012.
[3] Tahara, K., et al. Dev of Inventory  Database forEnvironmental Analysis(IDEA), EcoBalance, 2010.
[4] The 2014 SNIA Dictionary, SNIA, 2014[5] Joint Research Centre, ELCD 3.0, 2014.
[6] ecoinvent Centre, ecoinvent 3.01, 2014.

�������������������������������������������������

28D4-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

68

Analysis of Influence of ICT Services Including Application-Service and Network-Service
on CO2 Emission
Jiro Nakamura, Tomomi Nagao, Yuichiro Takei, Atsushi Sakurai, Shinsuke Hannoe, and Keiichi Saito 3
NTT Energy and Environment Systems Laboratories*Corresponding author: hannoe.shinsuke@lab.ntt.co.jp
NTT (Nippon Telegraph and Telephone Corporation)
Group formulated THE GREEN VISION 2020, which
composed of three approaches on Information andCommunication Technology (ICT) : “Green of ICT”, “Greenby ICT”, and “Green with Team NTT” [1]. ICT services are
expected to mitigate CO2 emissions through the use of ICTs inother sectors because their features include the improvement ofwork efficiency and the digitalisation of information. “Greenby ICT” means the contributing to the reduction of CO2
emissions of society as a whole through promoting theincreasing utilization of ICT services.
To assess our activities in relation to “Green by ICT”, We
investigated an environmental impact assessment methodology
based on a two-level model consisting of application-service
and network-service levels [2][3].
For our evaluation of application services, we calculated
the reduction in CO2 emission realized for individual services
by comparing the lifecycle CO2 emission before and after
introducing the application services and calculating the total
values for individual services.
We calculated the reduction in the amount of CO2 emitted
per user, and then obtained the total value for all the network
services by multiplying the number of users by the CO2
emission reduction per user.
Using our developed method, we estimated the CO2
emission reduction for NTT Group network services andobtained a value of about 10 million tons. This corresponds tomore than double the value of the CO2 emissions generated by
NTT Group business activities.
References[1] NTT Group, CSR Report 2010, 2010.
[2] Tomomi Nagao, et.al, “Methods for Estimating theEnvironmental Load Reduction Effects of ICT Services”,
IEICE General Conference 2014, 2014.
[3] Shinsuke Hannoe, et. al., “Environmental Load Reduction
Effects of Network Services”, IEICE Society Conference
2014, 2014.

�������������������������������������������������

28D5-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

69

Measuring social impacts of products:
the Handbook of the Roundtable for Product Social MetricsJoão Fontes*, Mark Goedkoop and Anne Gaasbeek
PRé Sustainability, Netherlands*Corresponding author: fontes@pre-sustainability.com
1. Introduction
Measuring and managing social impacts at product level isa driver for companies to innovate and to differentiate in themarket. Companies have started to develop in-houseapproaches based on guidance at global level. These include
the UNEP SETAC Guidelines for Social Life Cycle
Assessment of Products [1] and corporate level standards
including GRI, UNGC and ISO 26000 [2–4]. However, acomplete methodology to measure the social impacts ofproducts was still missing. In response to this, a group of
experts from large companies1 joined forces at the Roundtablefor Product Social Metrics to advance this area. This work
presents the Handbook for Product Social Impact Assessment,
which is the result of the first two phases of this collaboration.
2. Content of the Handbook
The Handbook proposes a complete framework fororganisations to measure social impacts of products andservices on three stakeholder groups as shown in Figure 1:
workers, consumers and local communities. These three groups
include those who are directly impacted by the product, or live
close to its production, use or disposal.

Figure 1. Stakeholder groups covered in the Handbook
The Handbook includes social topics, performanceindicators and impact assessment method. Besides assessing
working conditions in the supply chain, there was need for abalanced framework, enabling objective and unbiased
assessment. Therefore, in addition to topics such as health andsafety, the Handbook also includes topics such as experienced
well-being, work-life balance and local capacity building.
The impact assessment method allows assessment ofoverall performance since the social topics and the respective
performance indicators proposed make both positive andnegative impacts visible. The stages of the method are listed in
Figure 2.

Figure 2. Stages of the impact assessment method
The method supports use of both quantitative andqualitative data. In the referencing stage, quantitative data iscompared with reference values, while qualitative data isconverted to numbers using reference scales. Reference values
and reference scales for each one of the social topics are also
1

Ahold, BASF, BMW Group, DSM, Goodyear, Philips, RB, AkzoNobel,
L’Oréal, Marks & Spencer, Steelcase and a chemical company

provided in the Handbook (see example in Figure 3).
1 hour of training per worker during the reporting period

Figure 3. Reference value and scale for training and education
3. Discussion
The methodology allows identification of points of
excellence, improvement opportunities and risks. It can be used
to support decision-making and communications in numerous
applications, from empowering supply chain management, tosteering product development and social investment.
During the 2nd Phase of the Roundtable the methodology
was tested by the participant companies, confirming that it isapplicable to companies in different sectors and with global
operations. However, the handbook presents limitations,
including i) the performance indicators are not fully applicableto small farmers, small companies and the self-employed, ii)
the handbook does not provide guidance on possible data
sources, neither has it mapped the performance indicators withdata that may be available on public or private databases, andiii) the described methodology is not yet fully aligned withother ongoing global initiatives. The Roundtable will continue
to develop in a way to address these issues in the future.
Acknowledgments
The authors would like to thank the members of theRoundtable for Product Social Metrics: Andrea Bolhuis(Ahold), Peter Saling (BASF), Marzia Traverso (BMW Group),
Jacobine Das Gupta (DSM), Dave Woodyard and Lynn Bell
(Goodyear), Markus Laubscher and Marcel Jacobs (Philips),
Dave Challis (RB), Carmen Alvarado (AkzoNobel), Charles
Duclaux (L’Oréal), Hazel Culley (Marks & Spencer) andSébastien Zinck (Steelcase). The authors also would like tothank the external organisations that provided feedback during
the 1st Phase of the Roundtable.
References[1] Guidelines for Social Life Cycle Assessment of Products.
http://www.unep.fr/shared/publications/pdf/DTIx1164xP
A-guidelines_sLCA.pdf (accessed February 2013)[2] Sustainability Reporting Guidelines, version 3.1.
https://www.globalreporting.org/resourcelibrary/G3.1-Gu
idelines-Incl-Technical-Protocol.pdf (accessed February
2013)[3] The UN Global Compact’s Ten Principles.
http://www.unglobalcompact.org/AboutTheGC/TheTenPr
inciples/index.html (accessed February 2013)[4] ISO 26000:2010 Guidance on Social Responsibility.
http://www.iso.org/iso/catalogue_detail?csnumber=42546(accessed November 2010)�������������������������������������������������

28D5-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan70

Policies promoting ecodesign for energy and resource efficiency in Europe: experiences,barriers and future options
Carl Dalhammar*1
1

Lund University, Sweden*Corresponding author: Carl.Dalhammar@iiiee.lu.se
1. Introduction
In the European Union (EU), numerous policies andregulations are used to regulate the life cycle environmental
performance of products, at both the EU and member statelevels., cf. figure 1.

Figure 1. European Union environmental product policies
2. The product policy mix for promoting energy efficiency
The Ecodesign Directive is an EU framework Directive:
under the Directive, Ecodesign criteria are set for various
product groups. The Directive promotes a life cycle perspective
but so far, it has mainly been used to regulate the energy
efficiency of product groups, including electric motors,
dishwashers, TVs and boilers. In order for the Directive toreach full effect, it should interact well with other policies (cf.
figure 2) [1]. Minimum environmental performance standards(MEPS) set under the Directive should remove theworst-performing products from the market. The application oflabeling, subsidies and public procurement, helps to diffuse thebest performers, and provide continuous ecodesign incentives
for manufacturers

Figure 2. Product energy efficiency policy mix.
In the best case scenario, criteria in both mandatory andvoluntary instruments are continuously strengthened, and the
products on the market become more and more energy efficient.
Over time, the interactions of policies for energy efficiency
have been improved. For instance, the European Union
increasingly coordinates the review of MEPS and energy
labeling to ensure that there is a dynamic.
3. Ecodesign standards for resource efficiency
There is now much interest in using the Ecodesign
Directive also to promote resource efficiency and increased
recycling levels. Potential mandatory ecodesign standards

include requirements that increase product durability; modular
design to facilitate repair and up-grade; ban substances, or the
mixing of certain materials in the product design to allow
cost-effective future recyling; provide information aboutcertain critical materials and where they are located; the settingof maximum time limits allowed for disassembly; andrequirements on recycled content in new products [2, 3]. Suchstandards could support other waste rules. Ecodesign standards
will be part of a policy mix, which includes eco-labels, andpublic procurement. Main research tasks include: 1) how isresource efficiency criteria applied in voluntary policy
instruments, and what can we learn from this in relation to
mandatory standards?; 2) how can mandatory standards bestinteract with voluntary standards?; 3) when should we apply
mandatrosy standards, and when are they unsuitable?
4. Learning from voluntary policies
A review of different policy instruments showed that manydifferent requirements related to resource efficiency alreadyexist in the Eco-labels, EU Green Public Procurement (GPP)
practices, and the business driven scheme EPEAT (a rating
scheme for electronics). Criteria relate to issues likerecyclability, recycled content, hazardous substances, durability
and recycled content. When setting mandatory standards we canlearn from the voluntary instruments [2]. But the compliancemechanisms are different, and this should be considered.
5. The policy mix
A review showed that mandatory and voluntary policies
can interact in various ways [2]; e.g., voluntary policies canaddress product life cycle impacts that are not possible toregulate through mandatory standards. In some cases,
mandatory and voluntary standards can be mutually supportive.
6. When to apply mandatory standards
Interviews with industry and policymakers outline main
criteria that influence when mandatory standards make sense[2]. These include: product life span, whether voluntary
approaches are effective, user behavior, and the potential to set
quantifiable targets and prove compliance. Further, there will
be a need to make a market analysis to examine the need for
mandatory standards and their projected costs and benefits.
Acknowledgments
Funding for the research was provided by the Swedish
Energy Agency and the Nordic Council of Ministers.
References[1] Dalhammar, C. (2014). Promoting energy and resource
efficiency through the Ecodesign Directive. Scandinavian
Studies in Law, Vol. 65.
[2] Dalhammar et al. (2014). Addressing resource efficiency
through the Ecodesign Directive: a review ofopportunities and barriers. Nordic Council of Ministers.
[3] Ardente, F. and Mathieux, F. (2012). Integration of
resource efficiency and waste management criteria in
European product policies. Joint Research Centre.

�������������������������������������������������

28D5-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

71

Reverse Flow of Knowledge and the Development of Sustainable Energy Systems
Harald E. Otto
Polytechnic University of Marche, Italyh.e.otto@univpm.it

1. Introduction
At present, over three-quarters of the world’s primaryenergy comes from fossil fuels. Energy is vital to all kinds ofsocial and economic processes and to human activity per se.
However, as fossil fuel resources are not endlessly abundant,
and their use is associated with a number of negativeenvironmental effects, energy has become an increasingly
socio-economic and geo-political issue. As a result, society
worldwide is facing challenges and pressure to shift from fossil
fuel-based energy technologies to green technologies based on
renewable and low-polluting clean energy resources, while also
restructuring processes, lifestyles, and social structures in order
to both use energy more efficiently and considerably curtail
total energy consumption. The latter reflects not only onsustainable development and energy systems, but also on
current pressing global issues such as climate change andmitigation of carbon emissions.
2. Scope and outline
This represents a global move, which is likely to spur thedevelopment of and encourage a transition towards sustainableenergy systems and a reduced and more efficient use of energy
in both developing and developed countries. Recent studies
have led to an increased promotion and implementation indeveloped nations of innovations originating in developing
countries. This demonstrates that developing countries cangenerate effective solutions for today’s challenges (cf. [1,2]).
However, innovations produced in developing countries do not
automatically transfer effectively to developed countries andtranslate into viable solutions. To tap into the potential ofknowledge and insight generated through technology transfer,research collaboration, and innovation to advance sustainableenergy systems, we need a better understanding of thegeneration and flow not of technology and hardware artifacts,
but of knowledge and expertise. This includes combining thelearning processes of developing and developed countries [3].
Knowledge, expertise, and innovation emerge from anddevelop within and together with societies, technologies, andeconomies, and these evolve and interact with each other in
response to many and various internal and external forces.
3. Conceptualization and approach
To provide solutions within the context outlined above,
knowledge and inventions at different levels and directions
within the socio-technological and economic system need to berealized and implemented. This must be achieved in the form ofinnovations that are in turn feasible from a social, technological,
and economic point of view. For quite some time, starting in
the 1950s, innovation was viewed as a sequential linear process
where investment in research and development would leadalmost automatically to new products or services. This is a viewwhich has been severely criticized, and which has graduallychanged. Newly introduced paradigms and work on innovation
systems focus more on the interaction of the participants, andthe sharing and use of knowledge.
In various fields, studies on innovation as anorganizational phenomenon have a long tradition and havebrought about conceptualizations in a variety of ways.

Innovation can be abstracted as a process or an outcome. The
former views innovation as a series of interrelated activities
from idea to invention, and finally to commercialization, withnew knowledge being created and employed through these
activities, while the latter relates to an idea, product, process,organizational structure, etc. [4]. Knowledge is complex,
abstract, multifaceted and context-dependent. It is considered to
be one major key element in all forms of innovation, withknowledge creation having a high impact on innovation.
However, even though knowledge is essential for innovation, itis the exposure to and subsequent recognition of a problem,
which is considered to be the initiator of the innovation process.
The study presented in this paper provides an analysis
from a knowledge-based viewpoint, looking at knowledge
creation and flows within international research collaboration
and within different forms of innovation. It examines, forexample, product and process innovation, social innovation,and various forms of learning, such as learning-by-using (userinnovation), and learning-by-doing. This in turn is related to
key energy areas, to provide insight and pointers to facilitateand support efforts to address impediments, remove barriersand employ in a systematic and consistent manner the potentialof reverse knowledge flow to support a new generation ofeffective solutions for sustainable energy systems.
4. Conclusion
As the study examines both dynamic and static concepts of
the knowledge-based view in order to shed some light onreverse knowledge flow, it soon becomes apparent that various
barriers have been overlooked or ignored. Moreover, there
remains considerable potential which is still neither enabled nor
supported, and which is thus rendered unused. Empirical dataon international research and development cooperation between
developed and developing countries, and notably innovation in
the latter, are still fragmented and scarce. Therefore, insight
into and understanding of knowledge-based processes andknowledge flows are still elusive. This is reflected in ourcurrent inability to form an integrated theoretical base that canbe employed to better guide planning and policy-making and toestablish conditions that will stimulate the generation anddeployment of effective and efficient solutions aimed at making
sustainable energy systems become a global reality.
References[1] Altenburg, T., Schmitz, H. and Stamm, A. Breakthrough?
China’s and India’s Transition from Production to
Innovation. World Development, 36(2): 325-344, 2008.
[2] Lo, K. A Critical Review of China’s Rapidly Developing
Renewable Energy and Energy Efficiency Policies.
Renewable and Sustainable Energy Reviews, 29: 508-516,
2014.
[3] Tyfield, D. and Wilsdon, J. Low Carbon China: Disruptive
Innovation and the Role of International Collaboration.
Discussion Paper 41, Nottingham, UK: University of
Nottingham, 2009.
[4] Quintane, E., Casselman, R., Reiche, B. and Nylund, P.
Innovation as a Knowledge-Based Outcome. Journal of
Knowledge Management, 15(6): 928-947, 2011.

�������������������������������������������������

29C1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan72

Hitachi’s CO2 visualization effort
Tetsuichi Nomiyama,*1 and Hitoshi Maekawa2
1
Hitachi, Ltd., Japan; 2Hitachi, Ltd., Japan*Corresponding author: tetsuichi.nomiyama.hf@hitachi.com

1. Introduction
Product assessment has been carried out in Hitachi fromthe past and from 1991 Design for Environment was
introduced and LCA was dealt to confirm product enhancement
point or to feedback for next product development. In 1999 “Aassessment guide of Design for Environment” was publishedand Eco-Product, which is assessed using the guide, have been
disclosed to public.[1]Hitachi have tackled environmental issue and havedisclosed environmental information as part of CSR from thepast. Furthermore, this effort will be developed and LCA will
be able to be used to create business activities.
2. Challenge of LCA on business using
To contribute to business activities, it is required to beinteresting for customer, to be easy to understand and not togive false impression. And LCA is required for practitioner to
conduct with not too much load.
Effects of CO2 emission reduction was attracted attention
because business can be streamlined by introducing ICT
solution. So, in 2003 SI-LCA, which assess ICT solution
environmental effect, was developed to compare the effectbefore and after system introduction focusing on global
warming as environmental effect.
Furthermore, for customer to have reliability for quantified
results and comparison results, in 2009 Hitachi participated in“Japan CFP pilot project”, which was propelled by METI andrelated ministries, and after shifting to private operation“Carbon Footprint Communication Program” to disclose
information with high reliability by acquiring third party
certification. But at the beginning, there was a challenge not tobe allowed to compare because there was p principal to express
amount of emission in sales unit in pilot project.[2]3. Effort of IT equipment at Japanese CFP pilot project
Comparing is effective to express a effectiveness of CO2
emission reduction. But IT equipments, which are used bymany people in being concentrated, like server computer or
RAID or something, have flexibility of construction. So
effective comparing could not be conducted in sales unit. So
we proposed “per function”, which make even function unit, of
every IT equipment and it was approved. As a result, withusing same assessment rule (Product Category Rule, PCR),
displaying of CO2 reduction rate compared with previous
model by “per function” was allowed.
Lifecycle stage of every IT equipment except usage (rawmaterial procurement, production, distribution, disposal &recycle ) is common regardless of equipment type. So, PCR for
every equipment was not published but PCR for common IT
equipment was published and PCR was composed to be added
individual matter, which is usage and so on, of every
equipment when PCR is revised.
4. Effort of IT solution at Japanese CFP pilot project
About ICT solution, CO2 reduction rate was considered
like IT equipment. But quantification of reduction rate wasgiven up because comparing target is before and after ICT
solution introduction and assessment using same PCR isdifficult.

And “per function” of CO2 emission amount also intended
to be considered about ICT solution. In approved PCR of“Teleconference Systems” as ICT solution, “per function” wasdetermined to be CO2 emission amount of 1 hour meeting.
5. Effort after Japanese CFP pilot project
Hitachi have acquired CFP declaration certification of IT
equipment such as server computer, auto teller machine, data
storage, network equipment, IP-PBX and WiFi relay equipment
and system product such as teleconference system. In 2011, we
got LCA Japan forum chairman award of 8th LCA Japan forum
award LCA section for “Effort and Business Using of CFP in
Hitachi Group”.

Figure 1. Approved CFP products in 2014
6. Development from now on
We continue to promote expanding approved CFP product.
And for more contribution to business activities, we will tackle
EPEAT registration and will propose to premium standard ofGreen Purchasing Law and so on and we aim advantage of
public procurement and we solve challenge of communicationor quantification method which will be out there.
Acknowledgments
I would like to express my very great appreciation to Mr.
Maekawa for his patient guidance, enthusiastic encouragement
and useful critiques of this work.
References[1] Hitachi, Ltd. Earth Environmental Strategy Division
Hitachi Inspire Environmental Management Tokyo,
Japan : TOYO KEIZAI INC., 2009.
[2] Hitachi Group Journal of Life Cycle Assessment, Japan
10(3): 361–367, 2014.

�������������������������������������������������

29C1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan73

Challenges to Biofuel Production Enhancing Food Production:
A Food and Beverage Alcohol Company Perspective
Satoshi Ohara,* Akira Sugimoto, Kazutoshi Kitai and Takaomi Yasuhara
Asahi Group Holdings, Ltd., Japan*Corresponding author: satoshi.ohara@asahigroup-holdings.com
1. Introduction
The global demand of food and energy is increasing withthe world population growth and a rise in living standards. On
the other hand, the usable land area has become increasingly
limited on the crowded earth. This trend is creating concerns inserious deficit of food and energy in the near future.
From a perspective of a food and beverage company,
finding solutions to these issues not only creates a new
business, but also contributes to an ongoing business by secureand sustainable procurement of raw materials. In other words,
in the highly-globalized market environment, food andbeverage companies will be increasingly needed to tackle
global challenges and local challenges such as the economic
sustainability of farmers, simultaneously.
In this context, the combined production of sugar andethanol from sugarcane, practiced in many countries, has ahigh affinity with the technical background and culture of
Asahi Group Holdings (Asahi) because Asahi’s corecompetence is in the production of ethanol from carbohydrates(i.e., sugars, etc.). In addition, given that the energy cost is
expected to increase in the future, this business is particularly
attractive because bagasses, fibrous residue from pressing ofsugarcane, can be utilized as fuel.
In the sugarcane industry, agricultural and industrial (sugar,
ethanol) technologies are independently developed. Without
departure from this paradigm, sugar and ethanol productivity isin a competing relationship - ethanol production compromises
the production of sugar. Although efforts to modify cultivar toincrease yield per hectare have been made, they usually lead toincrease reducing sugars (glucose and fructose) in thesugarcane juice, which inhibit the crystallization of sucrose,
thereby negatively influence the sugar productivity. Therefore,
it is the common practice to utilize cultivars with high sucrose
and low reducing sugars content with low input of fertilizer,
water and labor. This approach is referred to as unsustainableagricultural practice in both the global and local context.
2. Shifting paradigm with life cycle thinking
Asahi has been tackling the simultaneous increase in sugarand ethanol production in a sustainable manner, applying life
cycle thinking. The life cycle thinking allows re-defining thesystem-wide objective in optimization of technologies. In
Asahi’s case, it meant that sugarcane breeders, processengineers and bio-scientists communicate and work together.
Firstly, a new cultivar KY01-2044 was developed by
Kyusyu Okinawa Agricultural Research Center, as a result of
joint research with Asahi [1]. This cultivar has relatively low
content of sugar, but has excellent biomass-productivity with
low input of fertilizer, water and labor. As this cultivar has highfiber content, it is possible not only to supply the total energy
for producing sugar and ethanol, but also to generate surplus
electricity. In Japan, this energy self-sufficiency in the mill isparticularly meaningful, as sugarcane is grown mainly onsouthwestern islands, where they are disconnected from power
grid with large-scale (and thus efficient) power plant.
KY01-2044 has greater sugar productivity in total.
However, as described above, increased proportion of reducing

sugars makes sucrose-crystallization difficult. Asahi and theircolleagues have developed a new process called “inversion
process” to deal with this problem [2]. Asahi’s technologies
and experiences in fermentation were the key to develop thisprocess - that utilizes yeasts that ferment only reducing sugars
and leave sucrose untouched [3]. By the selective fermentationof reducing sugars before sugar production, the sugarcane juicewith high reducing sugar contents turns into high sucrose
content juice with ethanol.
With the two innovations in the product’s life cycle system,
now it is made possible to increase productivity of sugar andethanol simultaneously without increasing the input to the farm,in the form of fertilizer, water and labor. Currently, the pilot
scale experiments of the inversion process are being conductedin cooperation with the operating sugar mill. With theseexperiments, lots of detailed challenges in technologicalaspects are being identified and solved.
3. Remaining challenges
Communication among different players in technologicalaspect has been successful. As a result, the cross-industrial
innovation is made technically possible. However, there still
remains non-technical challenges to be dealt with.
In order to assure the economic sustainability of the
proposed system, the merits created by the life cycle wide
optimization and multiple innovations must be appropriately
shared among the stakeholders. As the envisioned system
involves lots of stakeholders, it is very challenging for acompany like Asahi to make a proposal to all of them. A
platform to foster the understanding of farmers, policy makers
and other industries that may create symbiotic relation with thesugar mills via heat and power sharing must be established.
On this platform, to achieve a system-wide transformation
towards a sustainable state reflecting the local conditions,participation of all the stakeholders must be achieved under theleadership of local stakeholders.
The collaboration with academia and government is also
necessary. We hope that the researchers in the field of
EcoBalance, together with industry, shed light on the functionof LCA and other associated tools to communicate and arrange
the merits, beyond merely working out the envisioned
system-wide merits.
References[1] National Agriculture and Food Research Organization,
National Agricultural Research Center for Kyushu
Okinawa Region. Reference results on new variety ofsugarcane “KY01-2044”: 1-32, 2010.
[2] Ohara, S., Fukushima Y., Sugimoto A., Terajima Y.,
Ishida T. and A. Sakoda. Rethinking the cane sugar millby using selective fermentation of reducing sugars by
Saccharomyces dairenensis, prior to sugar crystallization.
Biomass and Bioenergy 42: 78–85, 2012.
[3] Ohara, S., Kato T., Fukushima Y. and A. Sakoda.
Selective ethanol production from reducing sugars in asaccharide mixture. Journal of Biosciences andBioengineering 115(5): 540–543, 2013.

�������������������������������������������������

29C1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

74

Experience of EPD Process Certification
Lucia Rigamonti,*1 Mario Grosso,1 and Mino Leo Marucci2
1
Politecnico di Milano, Italy
Reno De Medici S.p.A., Milan, Italy*Corresponding author: lucia.rigamonti@polimi.it
2

1. Introduction
An environmental declaration is defined, in the ISO 14025
standard, as quantified environmental data for a product withpre-set categories of parameters based on the ISO 14040 series,
but not excluding additional environmental information. It iscreated and registered in the framework of a type III
environmental declarations program, such as the International
EPD® (Environmental Product Declaration) System.
The Reno de Medici SpA Group is the first Italian and thesecond European producer of cartonboard based mainly on
recycled material. Its production capacity is spread acrossvarious plants in Italy, Spain, France and Germany.
In 2010 Reno de Medici decided to promote activities for
improving the environmental sustainability of its products. In
particular, it started some Life Cycle Assessment (LCA) studies
to register under the EPD® system some types of chipboards
produced in its Italian facilities. Currently three products are
certified.
As a wide number of different chipboards are produced ineach facility, according to the same overall production process,the traditional approach for the EPD® certification of each ofthem would turn out in a time consuming and expensive
activity. In order to overcome such limitation, Reno de Medici
has recently decided to work in getting the so-called “EPD
process certification” (The International EPD® System, 2013).
This is a possibility that the International EPD® System gives
the organisations to simplify the verification process. In thisway the organisation handles internally the management of
EPD data involved in the verification procedure and issues
individual EPDs without a third party certifier being involvedin each case.
2. Material and methods
The development of the EPD process has followed thepattern of Figure 1.

Figure 1. Pattern of the development of the EPD process
First of all, Reno de Medici has defined the following
roles needed to implement and maintain the EPD process andcontinually improve its effectiveness:- EPD process owner, i.e. personnel having authority andresponsibility in managing the overall EPD process;- EPD responsible publisher, i.e. personnel having authority
and responsibility regarding when to publish EPDs toexternal parties;- EPD independent internal verifier, i.e. a verifier assuring thereliability, relevance and independence in the handling of the

EPD process, and assessing the EPD process to certify its
appropriateness;- EPD independent external verifier, i.e. a third party who
verifies the internal EPD process assurance.
Then, the organisation has developed the EPD process. It
includes the following main steps:- EPDs preparation, i.e. determination of the Central Product
Classification code of the product, of the corresponding
Product Category Rules to be used, of the General
Programme Instructions (GPI) to be followed; performing of
the LCA studies and development of the EPDs; publicationof the EPDs;- EPD process assurance, i.e. internal assessments conductedby the internal verifier at planned intervals to determine
whether the EPD process conforms to the plannedarrangements, to the requirements of the GPI and to the EPD
process requirements established by the organisation, andwhether the EPD process is effectively implemented andmaintained;- EPD management review, i.e. review of the EPD process
conducted by the EPD process owner at planned intervals, toensure its ongoing suitability, adequacy and effectiveness.
This review includes assessing opportunities for
improvement and the need for changes to the EPD process;- EPD process certification, i.e. verification done by anindependent third party verifier during the time of validity of
EPDs following the EPD process, as a complement to theinternal assurance activity.
The EPD process implies that the organisation shall haveinternal competences and skills to conduct the prescribed LCA
calculations and to create EPDs according to the reference
rules, and to have regular follow-up routines in place toaccurately check the relevance of the current information inregistered EPDs. Reno de Medici has chosen to outsource the
LCA studies to LCA experts of Politecnico di Milano. Anyway,
the organisation is in charge to ensure control over this very
important step of the process.
3. Conclusions
Reno de Medici has decided to develop an EPD process
for the products manufactured in its facilities. This will give theorganisation the possibility to simplify the achievement of
EPDs certification for many products, saving time and money.
The increased implementation of environmental
management systems in many organisations will automaticallylead to the establishment of reliable internal follow-up routines
which suit very well many of the requirements of the EPD
process certification procedure. Hence, well managed internal
EPD routines will make data collection and its conversion into
EPDs more straightforward and less expensive, allowing theorganisation to operate it in a resource- and time efficientmanner.
References[1] The International EPD® System, 2013. General Program
Instructions for the International EPD® system. Version
2.01 dated 2013-09-18, www.environdec.com (Accessed
15.07.2014)�������������������������������������������������

29C1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan75

Policy options for LCA deployment in automotive industry
Annekatrin Lehmann,*1 Matthias Finkbeiner1, Kirana Wolf,1 and Cees ten Broek2
1

Technische Universität Berlin, Germany, 2World Steel Association, Belgium*Corresponding author: annekatrin.lehmann@tu-berlin.de

1. Introduction
Life Cycle (LC) Thinking is on the political agenda andmany industries are actively developing LCA approaches since
many years. In 2013 WorldAutoSteel commissioned theTechnical University of Berlin to explore and develop policy
options for integrating Life Cycle Assessment (LCA) into
(automotive) legislation. Phase 1 of the research to define andto compare policy options was centered on the EU.
.
2. ApproachThis research process of exploring and describing different
policy options was done with the following approach:







Identification of various policy options
Prioritization of policy options
Analysis of technical requirements
SWOT-/ RACER analysis (evaluation of strengths,
weaknesses, opportunities, threats and relevance,
acceptance, credibility, easiness, robustness)
Development of scenarios for policy implementation

To identify policy options, different theoretical/structuralelements were used. These are described in Table 1.

Strucural elements
Mandatory
Voluntary
Performance
Process
DirectIndirectMarket accessMarket incentive

Figure 1 Selected policy options for LCA deployment andexamples – theoretical and EU policy ones
environmental NGOs) showed, that generally highest relevanceregarding CO2 reduction, but also highest efforts for
implementation
seem
to
be
relatedtothemandatory-performance-direct option. Moreover, it was shown,that robustness and credibility can principally be guaranteed by
all policy options and that acceptance strongly depends on theperspective of the stakeholder groups and can varysignificantly within one group. Findings from stakeholder
meetings with German OEMs complemented these results.

Table 1. Structural elements to define policy options
Descriptions of policy option
Legally binding, thus, the defined requirements have to be fulfilled.
Not legally binding but intends to have indirect effects, e.g. via market incentives.
Related to the product performance; product needs to be re-designed, if not meeting defined requirements.
Defines process requirements on company level for improvement (not directly leading to product re-design)
Direct definition of LC based limit/ target values or communication of full LCA results“Backoffice” use of LCA or LCA data during policy development, e.g. for impact assessment of
conventional limits or for target value setting processes (e.g. for identified hotspots).
Provides minimum requirements (threshold values) for products to be able to enter the market.
Provides policy framework (e.g. criteria) for promoting environmentally preferred products.

3. Results
As a result, eleven policy options for LCA deployment
were developed. It was found that theoretically a broad range
of options for implementing LCA into policies exist and thatpractically (with focus EU) some of these options are already
implemented in real world legislation. As the granularity level
developed proved to be partly difficult to differentiate without
overlaps it was decided to narrow them down by selecting themost promising ones for each theoretical structure. The four
selected policies are shown in Figure 1, including theoreticalexamples for LC CO2 legislation and existing examples for
European LC based legislation (beyond the CO2 focus).
As a next step technical requirements for implementationof the policy options were identified and described(methodology, models, tools, data, quality assurance,
communication). It was found, that some are the same for bothvoluntary and mandatory policies, that sometimes, voluntarypolicy has strictest requirements and that the differentiation ofrequirements depends on policy implementation.
The SWOT- and a RACER analysis from different
stakeholder perspectives (e.g. OEMs, material industry,

4. Discussion and Outlook
The main findings were that there is no clear analytical,
scientific overall preference for one single policy option andthat technical implementation strongly depends on theimplementation level. Moreover, it was shown, that solutions
for most technical requirements are already available, but that a
consensus on proper setting of these requirements is missing.
Within phase 1 of the research process promising policy
options were identified and possible implementation scenarios
were developed, describing e.g. how current regulations could
potentially be amended to include a LC perspective and/or how
new co-existing LC CO2-regulations could look like.
This research process continues in 2014, including abroader stakeholder dialogue to communicate and refine thepolicy options as well as a broadening of focus beyond Europe.

�������������������������������������������������

29C2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan76

A new Direction for LCA: Organizational LCA
Matthias Finkbeiner,*1 Julia Martínez-Blanco,1 and Atsushi Inaba2
Technische Universität Berlin, Germany; 2Kogakuin University, Japan*Corresponding author: matthias.finkbeiner@tu-berlin.de1

1. Introduction
The benefits and the potential of the life cycle approach
are not limited to the application to products. While it was
originally thought for products, its benefits and potential might
be extended for organization assessment [1].
The discussions on the carbon footprint of organizations
and the development of the so-called "Supply Chain"- or"Scope 3"-Standard of the GHG-Protocol promoted the future
use of such an approach [2]. Grounding on that, the ISO/TR
14069 standardizes the quantification and reporting of GHG
emissions of organizations. Carbon footprinting has shown thatthe environmental impact up- and downstream can play animportant role in the overall impact of an organization.
While it is definitely useful to cover specific importantenvironmental areas such as greenhouse gases emissions, amulti-impact approach is needed in order to prevent trade-offs[1]. Furthermore, assessing multiple impacts may offer moreinnovative and actionable reduction solutions.
Several initiatives exist or are undergoing on thedevelopment and agreement of approaches for the multi-impact
assessment of organizations from a life cycle perspective. At
the global level, ISO developed a Technical Specification
ISO/TS 14072, which also serves as the backbone for theflagship project of the UNEP/SETAC Life Cycle Initiative. At
the regional and national level, the European Commission
launched the Organisation Environmental Footprint (OEF)
Guide and there is a Japanese project with regard to scope 3
and LCA of organizations. These initiatives are briefly
described in the following sections.
2. ISO/TS 14072 (ISO)The technical standard “ISO/TS 14072: Environmental
management — Life cycle assessment — Requirements andguidelines for Organizational Life Cycle Assessment”, to be
published in 2014, gives detail on how to adapt therequirements of product LCA to organizations and states somepotential benefits that LCA can bring to organizations. The
main recommendations for organizational life cycle assessment(ISO abbreviation: OLCA) are regarding system boundaries,
and the limitations on reporting, environmental declarations
and comparative assertions.
An explicit adaptation of the requirements of ISO 14040
and ISO 14044 to organizational context and an example of theapplication of OLCA are included.
3. Flagship project “LCA of organizations” (LCI)
In mid-2013, the UNEP/SETAC Life Cycle initiative [3]launched the flagship project “LCA of Organizations”. The
main outcome is the “Organizational Life Cycle Assessment –Guidance for organizations to conduct LCA considering theirvalue chain”, expected to be published by February 2015.
It is intended to be a detailed document accompanying
ISO/TS 14072. It seeks to go in greater detail on thecapabilities of organizational assessment and on providing
support regarding the methodological framework. The
publication includes eight case studies.
4. Organisation Environmental Footprint, OEF (EC)OEF is a multi-criteria measure of the environmental

performance of a product-providing organization from a life
cycle perspective. The Guide has been developed by the Joint
Research Centre of the European Commission, in parallel tothe so called Product Environmental Footprint. The document
aims to increase reproducibility and comparability byemphasizing prescriptiveness over flexibility to ensure that themethodology is applied consistently [4].
The document has some requirements that do not alignwith life cycle standard principles and which are neither
extensively tested nor used, for example the screening step, thedisallowance of cut-off criteria, the recycling formula for
end-of-life, and the default set of impact categories andindicators [5]. Besides, OEF Guide considers the option ofcomparative assertions intended to be disclosed to the public
within a same sector and according to the Organisation
Environmental Footprint Sector Rules (under development).
5. Related activities in Japan
Several examples of organizations applying life cycle
perspective at the corporate level could be found in Japan,
although mostly focused on carbon and water footprints, e.g.
Shiseido and Honda. An important and closely related event
was the “International Workshop of Scope 3 and LCA for
Organization” held in Tokyo last November, 2013.
6. Conclusions
It was shown that the application of LCA on organizations
is relevant, meaningful and already possible based on existing
standards and guidelines. Due to the unresolved challenges incomparing different organizations, organizational LCA shouldfor now focus on performance tracking for individualorganizations instead of comparing different organizations.
Some early success stories of application of this type ofapproaches were identified by the flagship project of
UNEP/SETAC LCI and the methodology will be tested during
the road-testing of the Guidance. Furthermore, OEF is being
applied to selected case studies during its pilot phase.
Acknowledgments
The authors would like to thank members of theInternational Organization for Standardization and theUNEP/SETAC Life Cycle Initiative for their contribution.
References[1] Finkbeiner, M., and P. König. Carbon Footprint and Life
Cycle Assessment of Organizations. J. Env. AccountManag. 1(1): 55–63, 2013.
[2] WRI and WBCSD. Corporate Value Chain (Scope 3)
Accounting and Reporting Standard. World Resources
Institute and World Business Council for Sustainable
Development, 2011.
[3] UNEP-SETAC.
Life
Cycle
Initiative.
http://www.lifecycleinitiative.org/ (Accessed 02.09.2014).
[4] European Commission. Organisation Environmental
Footprint Guide - Draft. Joint Research Centre - Institutefor Environment and Sustainability, 2013.
[5] Finkbeiner, M. Product environmental footprint—
breakthrough or breakdown for policy implementation oflife cycle assessment? Int. J. LCA. 19, 266–271, 2013.

�������������������������������������������������

29C2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

77

Guidance on Organizational LCA by the UNEP/SETAC Life Cycle Initiative
Julia Martínez-Blanco,*1 Sonia Valdivia,2 Ana Quiros,3 Llorenç Milà i Canals,4 Atsushi Inaba,5 and Matthias
Finkbeiner1
Technische Universität Berlin, Germany; 2World Resources Forum; 3ECOGLOBAL, Costa Rica;
4
UNEP-SETAC Life Cycle Initiative; 5Kogakuin University, Japan*Corresponding author: julia.martinezblanco@tu-berlin.de1

1. Introduction
In order to protect the environment in a credible manner,organizations need to rely on stable schemes. The most appliedand spread approaches for the environmental assessment at theorganization level have only recently considered the full value
chain and mostly concentrate on a single aspect (e.g. [1]).
Life cycle assessment (LCA) has been promoted as arobust quantitative tool, and a keystone in decision making.
While the life-cycle-approach was originally thought for
products, its benefits and potential might be extended fororganization assessment. However, an LCA for an organization
appears to be even more complex, as there are many productlife cycles to follow and a large part of environmental impacts
can reside outside the organization’s gate [2].
In this context, the “Organisation Environmental Footprint(OEF) Guide” was launched by the European Commission [3].
Even more recently, the International Organization forStandardisation (ISO) started a project to develop a Technical
Specification for LCA of Organizations, the upcoming ISO/TS
14072 [4].
2. The flagship project “LCA of Organizations”
In mid-2013, the UNEP/SETAC Life Cycle initiative [5]launched the flagship project “LCA of Organizations”. It aims
to show that the application of the life-cycle-approach onorganizations is relevant, meaningful and feasible within theframework of product LCA standards.
The nearly 60 participants of the project contribute to thedrafting, consolidation and road-testing of the “OrganizationalLife Cycle Assessment – Guidance for organizations to conduct
LCA considering their value chain”. Furthermore, a number ofregional and international stakeholder consultations support thereview process (e.g. in Japan, Panama, Basel…).
3. The Guidance document
The Guidance highlights the potential of organizational
perspective
withinlife-cycle-thinking
andsupports
practitioners facing the main important methodologicalchallenges when using organizational life cycle assessment(O-LCA).
It builds on existing internationally-agreed guides,
methods and standards on the assessment of the environmental
performance of organizations. The Guidance specially strives
to align with the upcoming ISO/ TS 14072.
Because there is not a “one-size-fits-all” approach to
O-LCA, several alternatives of organization’s pathways arepresented with specific guidance for its application. Moreover,the Guidance provides real case studies using organizational
approaches around the world.
4. Organizational life cycle assessment
O-LCA is a compilation and evaluation of the inputs,
outputs and potential environmental impacts (considering a
multi-impact approach) of the activities associated with theorganization adopting a life-cycle-perspective. The three main
items to define within the scope of O-LCA are presented in
Figure 1.

O-LCA is capable of serving multiple goals at the sametime (e.g. to support strategic decisions, to identify shifting
burdens between stages of the value chain, for performancetracking, and to engage suppliers). O-LCA is not intended to be
applied for comparison of different organizations.

Figure 1. Main elements on the scope definition of O-LCA.
5. Future steps
This methodology may overcome some of the barriers forthe spread of LCA in developing countries, for instance thethreat of selecting against non-best available technologies, ascomparative assertions are discouraged. Furthermore, it is apromising field for future advancements on social andeconomic LCA, as social and economic impacts may be better
tracked at the organization level.
The Guidance will be available for public consultation infew months [5]; we would like to encourage you to provide
feedback and help on moving it a step further. The experienceacquired during the upcoming road-testing of the final versionof the Guidance will also contribute to highlight the potentialof O-LCA.
Acknowledgments
The authors would like to thank to the participants of the
project and in general to everybody who has contributed to theflagship project providing valuable background, ideas,
comments, and case studies.
References[1] WRI and WBCSD. Corporate Value Chain (Scope 3)
Accounting and Reporting Standard – Supplement to the
GHG Protocol Corporate Accounting and ReportingStandard. World Resources Institute and World BusinessCouncil for Sustainable Development, 2011.
[2] Finkbeiner, M., and P. König. Carbon Footprint and Life
Cycle Assessment of Organizations. J. Env. AccountManag. 1(1): 55–63, 2013.
[3] European Commission. Organisation Environmental
Footprint Guide - Draft. Joint Research Centre - Institutefor Environment and Sustainability, 2013.
[4] International Organization for Standardization. ISO/TS
14072: Environmental management — Life cycle
assessment — Requirements and guidelines for
Organizational Life Cycle Assessment. Geneva,
Switzerland, 2014.
[5] UNEP-SETAC.
Life
Cycle
Initiative.
http://www.lifecycleinitiative.org/ (Accessed 02.09.2014).

�������������������������������������������������

29C2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

78

Activity to Evaluate a Positive Impact of an Organization
Hiroko Ioka1, Seiya Yamazaki1, Takafumi Hashitani1
1

Fujitsu Ltd., Japan*Corresponding author: ioka.hiroko@jp.fujitsu.com
1. Introduction
ICTs (information and communication technologies) likeother business have let do concerns on their environmental
impact and many companies are keen to assess and disclose
GHG emissions based on harmonized methodologies.
However, business has potential to reduce environmental
impact by its products and services. Indeed, ITU-T points ICT
sector distinguishes itself by its double-edged nature. On the
one hand, ICTs have an environmental impact at each stage of
its life cycle. On the other hand, ICTs can enable vast
efficiencies in lifestyle and in all sectors of the economy by theprovision of digital solutions [1].
Challenge is that there is no commonly agreed definition
and methodology to assess and report an organizational
positive impact. This paper address how to assess such
positive impact – avoided emissions - of an organization basedon the assessment of ICT services.
2. Methodology to assess the environmental positive impactof an organization – in case of Fujitsu Ltd.
Fujitsu, a private company in ICT sector, calculate its
organizational positive impacts (avoided emission of CO2)
based on assessment of more than 300 services sold in markets.
Fujitsu refers ITU-T’s Recommendation ‘L.1410 :Methodology for the assessment of the environmental impact of
information and communication technology goods, networks
and services’ which complements ISO 14040 and ISO 14044
for the assessment of services. Emissions from two target
systems – baseline case and the case where the ICT service isapplied - are compared to get avoided emissions (Figure 1).
The assessment targets use phase in life cycle of the service. It
is because the impact of other life cycle stages is relatively
small. Another reason is that organizational negative emissionof other life cycle stage such as raw material acquisition andend-of-life treatment are reported as part of scope 3.
Figure 1. Overview of assessment methodology

3. Consistency with reporting of scope 1, 2 and 3
Fujitsu reports organizational GHG emissions based on
GHG Protocol Standards (scope 1, 2 and 3) and avoided
emissions could be ideally reported with consistency to thesescopes. In that context, avoided emissions targeted to use phase
could be an extended indirect emissions of ‘use of soldproducts’ in scope 3 (direct emissions are power consumptionof ICT equipment and networks).
4. Limit of accuracy
We examined correlation between the amount of avoided
emissions of a service and its revenue to understand accuracyof the conversion factor (kg CO2 per revenue). We found thatsome type of category show little correlation between them.
(Figure 2.)
Figure 2. Relations between amount of avoided emissions
and revenue of the services in two different types of category

We assumed following reasons why little correlation
occurs in some types of category. First, ICT services andsolutions are typically custom made and also frequently
upgraded. As such, systems and performance could differ byservices and solutions even in the same category. Secondly,
difficulties to identify a system boundary when assessing aservice and solution which may cause inaccuracy of the resultof avoided CO2 emission.
5. Conclusion
We suggest continuing discussions on the assessment
methodology of organizational positive impact including twoquestions we rise above (consistency with existing standards
and limit of accuracy) and reflect on future guidelines orstandards of assessment methodology of organizational
positive impact.
Acknowledgments
I’d like to express my gratitude to Prof. Inaba of Kogakuin
University and members of the Study Group of Scope 3 andOrganizational LCA in LCA Society of Japan for their kind
guidance.

These 300 assessments are used as model cases to set up
conversion factor (tonne of avoided CO2 per revenue) of eachservice category. Accordingly 14 conversion factors are set (e.g.
Information Management, Data Center Services, andApplication Services). These conversion factors are multipliedby revenue of each service category to get total avoided CO2
emissions of Fujitsu.

References[1] Telecommunication Standardization Sector ofInternational Telecommunication Union.
Recommendation L.1410 Methodology for the assessmentof the environmental impact of information andcommunication technology goods, networks and services,2012.

�������������������������������������������������

29C2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan79

Proposal for a Supplementary Calculation Method for Scope 3 Emissions
Sachiko Motoike,* Hideki Sasaki, and Hiroshi Onishi
Panasonic Corporation, Japan*Corresponding author: motoike.sachiko@jp.panasonic.com
1. Introduction
This is to propose a supplementary calculation method forCategory 2 and ways of thinking Categories 4 and 9 of GHG
Protocol Scope 3 Standard for the manufacturing industry.
2. Proposal of Category 2 emissions calculation method
The technical guidance of Scope 3 Standard [1] does notdescribe the calculation method concerning the cases of selling
capital goods or buying second-hand capital goods.
Using the approach toward recycled materials described in
Category 5, we explored a method of calculating Category 2
emissions for cases involving second-hand capital goods. As aresult, we concluded that avoided emissions associated withrecycling/reusing should be counted in the calculation by
subtracting the value of emissions based on the selling pricewhen the product is sold second-hand. Grounds are as below.
When a company purchases second-hand goods andcalculates emissions according to the technical guidance, thesum of upstream emissions originally defined and emissions
from the reuse process corresponds to Category 2. In otherwords, using second-hand goods means using capital goods
with higher environmental impact (see left part of Figure 1).
Meanwhile, when calculating Category 2 emissions based on
the purchasing price, second-hand goods have smaller values(see right part of Figure 1) since they generally have lower
economic value. The avoided emissions by recycling are
regarded as a drop in economic value, and therefore we believe
the latter case better describes the environmental impact of
second-hand goods.
Calculation without avoided emissions
associated with recycling/reusing

Category 2
emissionsCategory 2
emissions＜New

Calculation based on purchasing
price

＜

Second-hand 1 Second-hand 2＞
New

Emissions during manufacturing＞

Second-hand 1 Second-hand 2

Emissions during treatment for reuse

Figure 1. Two methods for calculating Category 2 emissions
for second-hand goods
As for cases of selling capital goods, it can be deemed that
capital goods produced through the same process have thesame upstream emissions caused during manufacturing.
However, those environmental impacts vary significantly
depending on their lifecycles. Figure 2 shows that purchased
capital goods whose lifecycles end in the first company “A”
have the same amount of environmental impact as the upstream
emissions; whereas for products repeatedly resold fromcompanies “A” through “E,” the total amount of environmental
impact excluding the emissions in the recycling process islarger than the amount of upstream emissions. This is because
Category 2 emissions are calculated at each company the
product is resold to.
Disposed without reuse

Disposed after being reused four times
Category 2
emissionsCategory 2
emissions

＜
A

A

B

C

D

E

Figure 2. Difference in the amount of upstream emissions of a
product when disposed of as a new product or second-handPurchasing/Selling prices of capital goods are indicated in
cashflow statements, and upstream emissions can be allocatedusing both values, as shown in Figure 3. In purchasing capital
goods, Category 2 emissions are calculated based on thepurchasing price, and the emissions according to the remaining
value (selling price) will be subtracted when being sold. Thismethod is reasonable in that the buyer of the second-handgoods calculates Category 2 emissions using this subtracted
value (i.e. purchasing price) which is regarded as the remaining
amount of upstream emissions corresponding to the economic
value of those second-hand capital goods at that point.
Upstream emissions associated with manufacturing capital goods = UE
Years until disposal = T
UE = UE1’ + UE2’ + UE3

UE1’
UE2’

Subtract

UE3

Subtract
Company B purchasing
a second-hand productCompany A purchasing
a new product
A: Subtract E20Company C purchasing
a further resold

B: Subtract E3

T1

B: Report E2 as
Category 2 emissions

T2

C: Report E3 as
Category 2 emissions

T3 = T

Figure 3. Allocation of upstream emissions
In this way, Category 2 emissions relating to second-handcapital goods can be calculated appropriately and easily.
3. Consideration to Categories 4 and 9
While Categories 4 and 9 require calculating emissions
caused by transportation in cases where the transportation fee
is paid by a supplier or a customer, collecting activity data as
grounds for calculation is difficult.
Because forms of transportation vary among both
upstream suppliers and downstream customers, it is very
difficult in itself to extract only the activity data relating to thereporting company. Even if activity data is provided by the
supplier, it is unrealistic for a manufacturer like us with over
10,000 suppliers to calculate emissions with actual activity data.
Moreover, although the technical guidance recommends
estimating activity data regarding these Categories, it is alsodifficult to explain the validity of the estimation.
As a result, we consider it acceptable for manufacturers
like Panasonic to indicate N/A for emissions where thesupplier/customer pays the transportation fee.
4. Summary
Through our experiences with Scope 3 calculation, we
proposed a supplementary calculation method for Category 2
and ways of thinking Categories 4 and 9. We will also explore
other Categories in order to materialize meaningful efforts thatwould help reduce environmental impact caused by companies.
Acknowledgments
The authors wish to acknowledge valuable discussions
with Dr. A. Inaba and the members of the working group of
LCA Society of Japan.
References[1] WRI & WBCSD Technical Guidance for Calculating
Scope 3 Emissions, 2013.

�������������������������������������������������

29C3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan80

Estimating multiple changes of GHG emissions on Mitsubishi Electric group’s supply
chain; Category11-possible variation of GHG during use stage
Chie N. Uchiyama*1
1

Mitsubishi Electric, Japan*Corresponding author: Uchiyama.Chie@db.MitsubishiElectric.co.jp
1. Introduction
In recent years, quantitative evaluation methods of GHG
emissions and other environmental impacts on the entire supply
chain of the organization, such as Scope 3 initiated by GHG
protocol, related ISO standards and environmental footprint of
the organization proposed by EU, have been developed.
However, existing approaches define only the framework of
the calculation rules. In fact, evaluation result is largely
dependent on selecting which category in the upstream anddownstream of the organization, setting the system boundary ofeach category, data representativeness. In addition, theoutcome deeply relies on the estimates due to the constraints ofthe data availability in each category.
So far, more companies have disclosed the information on
GHG emissions of the organization based on these methods.
but there is no organization which shows multiple outcomes,
mentioning the change of the evaluation results due to variationin the way of taking selection of categories, system boundaries
and others. This study, providing a case study that targets themain segment of Mitsubishi Electric, aims to evaluate theeffect of a variation of certain conditions in the calculation of
GHG emissions.
2. Methods, Research design
Based on GHG Protocol and the Ministry of theEnvironment guidelines, GHG emissions on the supply chainof HVACs, Mitsubishi Electric Europe (ME-Europe) in
FY2012 were calculated. Two kinds of emission factors wereapplied, Japanese carbon footprint communication programand UK-DEFRA.
3. Analysis
The results of GHG emissions from ME-Europe showsthat, category 11 accounts for more than 90%, then category1 isabout 3 %. This outcome reflects GHGs of electronics usuallyoccur during use stage. Hence, focusing more on category 11,
sensitivity analysis and scenario comparison were examined.
For each analysis, the conversion factors of electricity bothfrom Japan and UK were used. Normally, electronics
companies manufacture a wide variety of products withdiversified specification to meet the needs of users.
Considering countries and use scenarios, the amount ofcomputation will be large and its combination is enormous andcomplex. From a practical viewpoint, the method should be
ideally simple and comprehensive. As the sensitivity analysis,
three calculations were studied, 1) base scenario (calculation
model by model), 2) weighted average, 3) assumption based on
the best-selling model, and 4) simple average and then data
representativeness was compared. Next, different scenarios for
operating conditions were evaluated, temperature, the heating
period and heat insulating performance.
4. Results
The results of the analysis are shown in Figure 1 and 2.
Overall, results from Japanese coefficient exceeded those from
UK. As for representatives of the data, “simple average”
revealed a large value compared to several other cases. This iscaused by the wide range of product lines from low to high–power models. If the discussion is restricted to FY2012, thecase of best-selling model showed the minimum result since
low-power model products were sold well during that period,
Scenario comparison, depending on how wide the assumptionis, the difference by the effect of heat insulating performance
conditions is maximized.

Figure 1. Comparison of different calculation rules
Temperature

Heating period

Insulation

Figure 2. Comparison of different scenarios
5. Discussion and Conclusions
In this study, by applying calculating GHG for supply
chain of electronics, category 11 was especially examined,focusing changes in the calculation results in different situation.
The largest impact on the result is due to the difference inemission factors, which equals roughly the amount of category
1. Considering applications by global companies, the data
quality and sources should be harmonized among countries.
EU has published a guidance of Organization
Environmental Footprint (OEF) and intended comparability
among the same industry sector. However, differences by eachcountry’s conversion factors, representativeness, and scenario
setting might be explained in variation in a mixture of aspects
of product’s performance. Only a sector-specific guideline
would not be enough. This implies that more discussion isneeded with sufficient samples toward standardization forcomparative analysis.
Acknowledgments
This study has been greatly enhanced by the support frommembers of "LCA of organization and SCOPE3" working
group under LCA Japan Forum and MERCE-UK.
References[1] CFP Communication Program, basic data base ver.1.03[2] UK -DEFRA GHG Conversion Factor Repository
http://www.ukconversionfactorscarbonsmart.co.uk/[3] General Guidelines on Supply Chain GHG Emission
Accounting
http://www.gvc.go.jp/business/intr_trends.html

�������������������������������������������������

29C3-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan81

What allocation method should be taken to provide the data for SCOPE3 by supplier tocustomer? - An example of the printing company Hiromichi Sasaki,*1 and Nobuyasu Tanaka1
1

Sun Messe Co., Ltd. Japan*Corresponding author: h-sasaki@sunmesse.co.jp
1. Introduction
Recently, the CO2 emission of organization such as SCOPE3
has been disclosed by many companies in Japan, partly because
they have to report it to the rating organization such as CDP.
In this context, the company that provide products (material,
parts, etc) and service have to disclose the CO2 emission of
their products and/or service to their customers. As Sun Messe
Co., Ltd. Japan is a printing company, the CO2 emission caused
mainly by used paper and energy consumption for printing,which should be allocated into many customers that Sun Messe
Co., Ltd. Japan provide printed materials. In this paper thedifference of the results by allocation methods such as the
product quantity, the cost of printing paper and weights wereintroduced. In addition to this, the measures to reduce CO2
emission in the printing company will be discussed.
According to the guidelines of SCOPE3, it can be based on
the sales, to allocate to each of the customers the whole CO2
emissions of the Sun Messe Co., Ltd. However, this method
can not represent the diversity of order form. All products ofthe printing company are made-to-order. Forms, sizes andquantities are completely different because all productions haveto meet the needs of customers.
In this presentation, we will report the results of a study fromthe view point of suppliers, how to allocate to each customer
the CO2 emissions of the Sun Messe Co., Ltd.
2. The CO2 Emission of Sun Messse CO., Ltd by SCOPE3
The Figure 1 shows the calculation result of the CO2
emissions by the SCOPE3 of Sun Messe Co., Ltd. Category 1
accounts for 70% of the total. In addition, 95% of this category
1 is the emissions for the production of printing paper. From
this result, we would suggest that the method allocating thecustomer the CO2 emissions of printing paper is a major factor
in determining the CO2 emissions of each customer. In thisstudy, we consider the most appropriate method to allocate theCO2 emissions of printing paper to each customer.

Figure 1. The CO2 Emission of Sun Messe CO., Ltd. by SCOPE3

3. Case Study
Case 0 is based on the sales. That is the most popular method
has been shown in the guidance of SCOPE3. Case 1, Case 2
and Case 3 are based on the product quantity, the cost of
printing paper and the weight of printing paper respectively toallocate the customer the CO2 emissions. As the examples of
the customers, three companies are selected. The main productsof company A, B and C are flyers for sales promotion, books,
and direct mails respectively.
4. Results and Discussion
Figure 2 shows the results of Case 0, 1, 2 and 3 allocating thewhole CO2 emission of the Sun Messe Co., Ltd. to eachcompany A, B and C.

Figure 2. Allocation results of the whole CO2 Emission of Sun MesseCO., Ltd. to company A,B and C on Case 0, 1, 2 and 3.

In Case 0, since the CO2 emission is allocated based on thesales, the difference of the amount of printing between thecompanies was not reflected on the results. In Case 1, since it isallocated based on number of volumes, a small volume flyer
has the same result of a large volume book. In Case 2, since it
is allocated based on the cost of printing paper, the weight ofprinting paper that the customer has paid and provided to Sun
Messe Co., Ltd. is not reflected on the results. Considering
printing works, Case 3 which is allocated by the weight ofprinting paper seems to be the best method because it reflects
the energy consumption of printing works.
Table 1 shows the CO2 emission per 1 million yen of the sales
for each company. In Case 0, the CO2 emission of eachcompany is consequentially the same because it was allocatedbased on the sales. However, in Case 3, the CO2 emission ofCompany A is more than over 20 times of Company C.
5. Conclusion
In the guidance of SCOPE3, Table 1. The CO2 Emission of eachthe allocation method based company per 1 million JPY
on the sales is very popular,
but the characteristics of theworks of the company
should be reflected. And, itshould be agreed with thecustomer.
Acknowledgments
I would like to thank Professor A. Inaba of Kougakuin
University, provided helpful comments and suggestions. I also
would like to thank Dr. M. Motoshita of National Institute ofAdvanced Industrial Science and Technology (AIST), provided
incisive comments.

�������������������������������������������������

29C3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

82

Water consumption evaluation along the supply chain
Junichi Nakahashi,*1 Masaharu Motoshita*2
1

ASAHI KASEI CORPORATION, Japan; 2AIST(National Institute of Advanced Industrial Science and Technology),

Japan
1.

Introduction

Db = Ʃ((purchased good amount) x (water consumption factor) x

Human activity has begun to affect significantly to the globe(damage factor))

environment. Climate change, water drought, material exhaustion, foodEffect of using the individual damage factors for countries is evaluated as

shortage etc. are primary issues to be tackled [1].

the value Da / Db.

ASAHI KASEI CORP. has published water consumption

If Da / Db is 1, there is no effect. If Da / Db is less than 1, using theamount at the factories on annual CSR report, but has not tried toindividual damage factors for countries generates larger damage value. If

evaluate the water consumption amount along the supply chain yet.

the Da / Db is larger than 1, using the individual damage factors for

IDEA2, life cycle inventory data base including water

countries generates smaller damage value.

consumption factors on industrial goods is now under construction by

4.

AIST. And so we can try to evaluate the water consumption amount(1) Water consumption amount along the supply chain of purchased

along the supply chain of ASAHI KASEI CORP.’s purchased materials

goods was about 2.9 times as much as water consumption amountusing it.
2.

Objectives

at the factories [2].
(2) The effect of using the individual damage factors for countries Da /(1) To evaluate the water consumption amount along the supply chain

Db was about 0.7.

of ASAHI KASEI CORP.’s purchased materials using IDEA2 and5.

compare to the water consumption amount at the factories.

(1) Water consumption factors on goods derived from wood or timber(2) To evaluate the effect of using the individual damage factors forcountries in IDEA2 comparing to the case using only the damage
3.

ResultDiscussion
are higher than other factors.

(2) Wood and forest seems to keep water rather than to consume water.

factor for Japan for all countries in evaluating the damage value.

Water consumption factors are not generated based on this fact.

Evaluation of water consumption and its damage along the(3) It takes about 60 years for wood to grow up. It is quite different

supply chain

from annual plants like as rice plant or corn etc.. Water(1) Water consumption amount evaluation
Factories(water consumption) = (water amount took from river) – (water amountconsumption factors are not generated based on this fact also.
6.

Conclusion
Water consumption factors have subjects to be solved. And so thereturned to river)water consumption amount calculated using such factors may be

Supply chain of purchased goods

different from the true value.

(Water consumption) = Ʃ((water consumption factor*) x (purchased

Damage factors are generated through multiple assumptions, sogood amount))damage values using such factors have also subjects to be solved and are* referred to life cycle inventory data IDEA2 now under construction by

now difficult to be compared to real economy and also difficult to be

AISTcompared to each other.

(2) Damage evaluation
1) Estimation of the primary purchased goods amount by countries using

References

foreign trade data in IDEA2[1] N. Itsubo, A. Inaba. LIME2 Life-cycle impact assessment Method

2) Evaluation on the effect of using the individual damage factors forbased on Endpoint modeling, Japan Environmental Management

countries

Association for Industry 2010.

Da = Ʃ((purchased good amount by country) x (water consumption[2] CSR Report 2013 ASAHI KASEI CORPORATION

factor by country) x (damage factor by country))�������������������������������������������������

29C3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan83

Supply-chain Environmental Assessment for Sustainable Procurement
Kenji Ohashi
SHISEIDO Co., Ltd.
kenji.oohashi@to.shiseido.co.jp
1. Introduction
SHISEIDO Co., Ltd. is a cosmetic product manufacturer
and seller company in Japan. SHISEIDO provides products andservices that support the beauty and wellness of people withinsustainable thinking. Several efforts are now in progress to thiscommitment. First, we are spreading the re-fill products, which
can reduce the amount of resource for packaging. Second,
SHISEIDO provides the cosmetic products which packaging is
made from sugarcane-derived polyethylene. We have a plan toswitch to green-polyethylene, more than 70% of the total
polyethylene, by 2020.
On the other hand, it is an essential requirement for allcompanies to collect, measure, manage and disclose theinformation about environmental burden in various categories
as well as GHG emissions. We focused on GHG emissions andwater consumption because of the materiality. Here we report
our approach about GHG and water accounting in order tomake sure of some objectives, as following;(1) Total amount of GHG emissions and water consumption(2) Hot spots(3) Avoided load and trade off due to our efforts(4) Weakness and resilience of our supply chain
2. GHG & water accounting through the value chain
We carried out assessing on direct/indirect GHG
emissions and water consumption through the value chain ofJapanese business activity in cosmetic field of Shiseido,
according the method of GHG protocol Scope3 standard [1].

area at the national level and for making a “supply chain watermap”. This map would show us which area’s water ourbusiness depends on.
4. Discussion
Heightened concerns regarding global environmental
problems have led consumers to make strong demands for theincorporation of sustainability into any product development or
economic activity. Indeed environmental issues must be
considered one of the most important tasks in businesses today,and failure to address these issues is now recognized as a major
business risk to any company. In addition, various investment
institutions and environmental NGOs demand us disclosing
certain information relating to environmental issues based on
LCA method. We carried out accounting GHG emissions andwater consumption through our value chain. The results
indicate the importance of environmental management throughthe value chain.
Cosmetic business relies on many kinds of raw materials
made from plants, which are dependent on fresh water resource.
Because the water resource is distributed unevenly [2][3],when it comes to sustainable water use, it is important tomanage not only with its quantity but also with the geographic
data. We are trying to draw a “supply chain water map” bytraceability research about cosmetic raw materials. It cansuggest the supply chain business risk related to water with thevicissitudes of water scarcity [4], flood occurrence [5],demographics, social and economic structure on the cultivation
area in future. While LCA expresses the impacts to theenvironment owing to economic activities, the analysis
combined with some information can improve LCA to the“supply chain business risk assessment tool” and it would help
us to establish sustainable and resilient procurement.
Conclusions
Value chain environmental assessment brings immediately
results on discovering hotspots, avoided load, trade off, cost
reduction opportunities and so on. Moreover it would be useful
to forecast the business risks on the supply chain.

Figure 1. GHG emissions and water consumptionof Scope1, 2 and 3
As a result, the indirect GHG emissions from upstream
and downstream of the value chain are approximately 19 times
as much as direct emissions (Figure 1). Further, the fact that
more than 99% of water was consumed indirectly in the crop
cultivation and in the use stage by consumers has revealed.
Additionally, approximately 17,000 t-CO2e of GHG emissions
was suppressed due to our efforts.
3. Traceability research of the raw materials
The significance of impacts related to water consumption
depends on its locality because of uneven distribution of water
resource. The fact indicates the next goal of our water analysis
with the locality as well as the quantity.
We therefore started traceability research about theplant-derived materials used in the cosmetic raw materials.
This research aims for identifying the growing or cultivating

Acknowledgments
I thank for the fruitful advices and discussions with Prof.
A. Inaba and the member of the “Workshop of Scope 3 and
O-LCA” in JLCA.
References[1] WRI and WBCSD, Corporate Value Chain (Scope3)
Accounting and Reporting Standard – Supplement to the
GHG protocol Corporate Accounting and ReportingStandard (2011)[2] Stephan Pfister et al.: Environmental Science &Technology, 43 (11) 4098-4104 (2009)[3] Shinjiro Yano et al.: Journal of Life Cycle Assessment,
Japan, Vol.10 (3) 327-339 (2014)[4] Naota Hanasaki et al., Hydrology and Earth System
Science, Vol.17, 2393-2413 (2013)[5] Yukiko Hirabayashi et al., Nature Climate Change, Vol.3,
816-821 (2013)�������������������������������������������������

29D1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

84

Green GDP Study Based on Life Cycle Impact Assessment of Refinery Sector in Thailand
Kultida Kunanuntakij, 1 Viganda Varabuntoonvit,1 Natanee Vorayos,2 and Thumrongrut Mungcharoen*1
1

Kasetsart University, Thailand; 2Chiang Mai University, Thailand*Corresponding author: fengtrm@ku.ac.th

1. Introduction
Gross Domestic Product (GDP) is one of the indicators
used to assess economic development and production growthof the country or some specific sectors. In the past two decade,Thailand’s GDP average growth is 0.93 percent, while
petroleum refinery sector average growth is 13% due to thegrowth of energy demand. GDP reflects only wealth of country
but does not reflect other factors such as quality of life, impact
on environment and depletion of natural resources due to theincreasing of production, consumption and the impact ofhuman activities on the environment.
Sustainability Development normally covers 3 factors
which are economic, social and environmental growths. GreenGDP is therefore expected to reflect the impact ofenvironmental degradation and resource depletion on the
traditional GDP. This study aims to develop Green GDP
model for petroleum refinery production sector in Thailand byusing the value of environmental impacts from Life Cycle
Assessment (LCA) results.
2. Methodology
Green GDP is an index which incorporates theenvironmental impacts into the traditional GDP. This can bedone by monetization of the environmental impacts such as
eutrophication, climate change and other relevant impacts.
There are several methods used to convert environmental
impact to monetary term such as weighting factors evaluationfrom environmental taxes or fees. Another method based on
end-point is LIME which converted environmental impact toJapanese Yen. Most of the methods to convert environmental
impact to economic value are based on Willingness to Pay(WTP) or Distance to Target (DtT). However, a method basedon environmental impact treatment cost is an attractive
scientific method to convert environmental impact to monetary
term. This method depends on treatment technologies and uses
interest rate and exchange rate to convert in to Thai Baht.
۵‫ܖ܍܍ܚ‬۵۲‫ ۾‬ൌ ‫ܔ܉ܖܗܑܜܑ܌܉ܚ܂‬۵۲‫ ۾‬െ ‫ܜܖ܍ܕܜ܉܍ܚ܂‬۱‫ܜܛܗ‬is shown in “Table 2”. In this study, economic cost is calculated
by using the average exchange rate with the inflation byinterest rate.
Table 1. The LCA Results by Using ReCiPe Method
ImpactUnit 2010 2011 2012
Photochemical oxidant kg NMVOC 5.0E5 4.9E5 4.4E5
Eutrophication
kg P eq 5.4E1 5.3E1 4.8E1
Acidification
kg SO2 eq 4.3E7 4.2E7 4.4E7
Climate change
kg CO2 eq 1.4E8 1.4E8 1.4E8
Table 2. Technology and Treatment Cost in THB per Unit
Technology
Year
Unit
Lower
Upper
Setting LDAR1,2 2005 kg NMVOC
6.88
15.56
Activated sludge 2004
kg P eq 741,041 1,482,143
FGD
2005
kg SO2 eq
5.48
7.20
CO2 capture
2009
kg CO2 eq
1.88
10.20
3. Results and Discussion
It is found that Green GDP value is about 2-4% less than
traditional GDP. The most impact in the refinery sector comesfrom the increasing use of energy which is caused from theincreasing demand of refinery products.
This study considers 4 environmental impacts which are
the main impacts obtained from the characterization step.
About 80% of the main impact comes from the treatment costof SO2 removal and CO2 capture. “Figure 2” shows thecomparison of traditional GDP and Green GDP for the refinery
sector during the year 2010 to 2012.

(1)“Figure 1” shows the overall methodology of this work.

Figure 2. Comparison of traditional GDP and Green GDP
4. Conclusion
Green GDP is used to reflect the environment impact
comparing to the traditional GDP. The treatment cost for eachof the impact categories can be obtained by conversion of the
impact to monetary term. Green GDP of the refinery sector,
using the treatment cost method, is about 2-4% less than the
traditional GDP. Further study will include other major impacts
such as fossil depletion, eco-toxicity and human toxicity.

Figure 1. Overall Green GDP Calculation Method
Thailand National Life Cycle Inventory Database (Thai
LCI database) of petroleum refined products is used to
calculate environmental impacts. Some of the inventory datafrom petroleum (exploration and production) which is imported
from other countries are from Ecoinvent3 database. “Table 1”
shows some environmental impacts using ReCiPe method. The
treatment cost of specific technology for each impact category

Acknowledgments
The authors gratefully acknowledge financial support fromthe Sustainable Environment Program, National Science andTechnology Development Agency (NSTDA), Thailand.
References[1] Linyu XU, et al. A method of green GDP accounting
based on eco-service and a case study of Wuyishan,
China: 2010.

�������������������������������������������������

29D1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan85

Fast screening of alternative life cycles and system optimization using flexibly linkableprocess subsystems
Bernhard Steubing,*1 Chris Mutel,1 Florian Suter,1 and Stefanie Hellweg1
1
ETH Zurich, Switzerland*Corresponding author: steubing@ifu.baug.ethz.ch

1. Introduction
Life cycle inventory databases, such as ecoinvent, usuallyprovide detailed process models, which has resulted in a large
number of unit processes. While this is necessary to ensurehigh quality data, it would often be handy for LCA
practitioners to aggregate such detailed process chains into asmaller number of major building blocks – only the principal
elements that they are interested in – for example raw material
production, transportation, product manufacture, product use
and recycling.
On the other hand, life cycle inventory (LCI) databases
often contain more useful datasets than is actually made use of.
For example, ecoinvent contains both datasets that describe theproduction of methane from biomass (biomethane) as well as anumber of datasets that describe the use of natural gas for thedelivery of energy services (e.g. electricity). However, datasets
for the generation of the same energy services from biomethane
do not exist, for the simple reason that including all these
possibilities would dramatically increase the number ofprocesses in a database which is meant to serve as a
background database.
Further, in order to solve the inventory problem, LCI
databases generally have square matrices, which means thateach input to a dataset is clearly determined and each output is
unique (e.g. not just “electricity”). In LCA, however,comparable, i.e. identical, products are often required (e.g.
“electricity from natural gas” and “electricity from biomethane”
could be subject to a comparison). Also, many upstream inputs
are in reality substitutable (e.g. heat from different sources, ordifferent machines with the same delivered function). Whenmany choices arise from such upstream (or downstream)
substitutes, the formulation as an optimization problem may be
an insightful way (or the only way) to reach conclusions abouta meaningful system design.
In this paper we make use of what we call process
subsystems to support analysts to build models and overcome
the aforementioned issues more easily.
2. Approach
Based on the open source software Brightway2 [1], wehave developed an approach to group any number of processes
into what we call here process subsystems. Process subsystems
are characterized by a name, its outputs and its inputs, and achain of processes that belong to the process subsystem. The
name can be specified by the user. There can be one or several
outputs for which the user equally provides a name.
Multi-output processes are supported (which is especially
useful in optimization problems). By default, a process
subsystem links to all upstream unit processes of the unit
processes that are included in the chain of a process subsystem(the unit processes that are intended to make up the process
subsystem). However, links to upstream processes are cut (i.e.
not maintained), if the user defines these as “inputs” to theprocess subsystem. In this case, the information contained in
the process subsystem for this previously existing link is anamount and a user-defined name of the input, but not an
explicit link to another unit process or process subsystem. The
required input can later be delivered from another process

subsystem.
To illustrate the advantage of this, we stick with the above
example (Figure 1): natural gas and biomethane are essentiallyequal products, although produced in different ways. By
defining an input “methane” in the process subsystem“electricity production” (for which there will be no link to aunit process anymore; cut-off) and defining two additional
process subsystems “natural gas production” and “biomethane
production” that both produce the product “methane” we havedeveloped three process subsystems that can be combined by
the name of their products.

Figure 1. Example of the usage of process subsystems
While this may seem exceedingly complicated for such asmall system, it is a powerful way of representing often large
numbers of possibilities in more complex systems.
3. Case study
We have applied this approach to analyze the ecologicalbenefits of using the resource wood. First, the approximately
300 life cycle inventories relating to the production of wood
products in ecoinvent 2.2 as well as processes for alternative
non-wood products were associated with less than 40 flexibly
linkable process subsystems to represent the essential
possibilities for the material and energy uses of wood,
including cascade uses. Then, linear programming was applied
to optimize the use of process subsystems based on their LCA
results and other systemic constraints.
4. Discussion
Process subsystems appeared to be useful as they:
Reduce the complexity associated with linked unit
processes to a level that is easier to understand andmanage and communicate by the modeler
Facilitate the modeling of combinations of inprinciple possible, but not yet modelled process
chains (such as electricity from biomethane)Are an important step towards formulating
optimization problems
Naturally there are also drawbacks associated with process
subsystems. For example:

It takes time and good system knowledge toformulate meaningful process subsystems

Errors can be made regarding product equivalencyThe approach relies currently on a specific software
References[1] http://brightwaylca.org/

�������������������������������������������������

29D1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

86

Investigation of the differences between static and probabilistic LCA/LCC results of different
floor finishes
Johannes Gantner*1, Dr. William Fawcett2, and Matthias Fischer3

University of Stuttgart, Germany; 2 Cambridge Architectural Research Ltd, United Kingdom; 3Fraunhofer IBP, Germany*Corresponding author: Johannes.gantner@lbp.uni-stuttgart.de

2. Statement of the problem
Decision makers have to undertake decisions not justbased on limited information but also on uncertain or altering
information. In addition the questions the complexity of thedifferent options increases in terms of influencing parameters
and interconnections. Therefore most of the decisions are basedon experience or simply gut feeling and not on fact basedmodel. Thus methodologies and tools are needed to support
decision makers.
3. Methodological Approach
In order to allow for a better decision making a combined
life cycle costing (LCC) and life cycle assessment (LCA) approach is described that takes into account future changes andevents. Therefore a probabilistic model is set up and cost andenvironmental data is used as an input. Primary focus isthereby on the uncertainty with regards to future changes anddecisions of environmental impacts. In order to develop theenvironmental input needed for the probabilistic model (time-)
dynamic LCIA datasets are set up. For ease of interpretation
several environmental impacts are combined to a single point
indicator. This environmental single point indicator is used in
combination with the economic LCC value to set up an
Eco-portfolio [1] diagram that can be used to allow managers
and designers performing fast decisions.
4. Case Study
Based on this methodological approach, different design
alternatives and material choices of floor coverings are compared with regards to uncertainties of timescale of therefurbishment and production and end-of-life technology. As abasis for the dynamic LCIA datasets the LCA models of the“Ökopot” [2] project were used. The economic vales for
production and end-of-life are based on [3]. Detailed focus ofstudy is on the effect of different estimated service lifes of floor
materials (e.g. 5, 10 or 15 years for carpets) on theenvironmental results over the whole life cycle (production,
refurbishment, EoL) based on dynamic energetic datasets (e.g.
yearly electricity profile (see figure 1)). In addition a LCC
analysis of the different floor finishes is conducted to provide
also an economic decision basis for later eco-design. Figure 2
shows the final results of comparison of different floor coverings over a timescale of 50 years as an Eco-Portfolio diagram.
Within the Eco-Portfolio the uncertainty of the results areshown as well as the probability of occurrence of this values(brighter ellipses). If the results are in the bottom left part ofthe diagram the option is economic and environmentally
beneficial. In contrast, if the option is in the upper right corner
the option is environmentally and economical not beneficial. If
the option is in the upper left or in the lower right corner the
choice depends on whether there is a focus on economic or

environmental aspects.
100%
90%
80%

NuclearHard coalLigniteNatural gas/ oil
CHP Gas, Coal
ImportGeothermal
Biomass
PV
Wind
Hydro

70%
60%
50%
40%
30%
20%
10%
0%

2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050

1. Introduction
Due to technological innovations but also its implications
our world is changing more and more rapid. Assessing theenvironmental impacts of products in context of very long
lifetimes, the uncertainty of future events and decisions ishighly influencing the overall environmental results.

Year

Figure 1. Yearly share of energy sources for the German
electricity mix (based on [4])
1,60
1,40

LCC (Normalized)

1

1,20
1,00
0,80

Stoneware
Linoleum

0,60
0,40

ParquetCarpet

0,20
0,00
0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

Environmental Single Point Indicator (Normalized)

Figure 2. Eco-Portfolio of different floor coverings
5. Conclusion
All in all this methodology could support architects, product designers or engineers to assess not only current
environmental impacts of a product or service, but also estimate the magnitude and likelihood of future impacts. Therefore
it´s possible to avoid misjudgments by only focusing on today´s circumstances and make better decisions. This could
result in more sustainable products for a more sustainable future.
References[1] Fawcett, W., Hughes, M., Krieg, H., Albrecht, S., &Vennström, A. (2012). Flexible strategies for long-termsustainability under uncertainty. Building Research &Information, Volume 40, Issue 5, 2012, DOI:
10.1080/09613218.2012.702565[2] BMBF. Verbundprojekt Ökopot – Ökologische Potenziale
durch
Holznutzung
gezielt
fördern,2008,
http://literatur.ti.bund.de/digbib_extern/dk041313.pdf(Accessed 03.08.2014).
[3] BKI. BKI Baukosten 2010 – Teil 2 Statistische Kennwerte
fürBauelemente.
Stuttgart,
Germany:
BKI
Baukosteninformationszentrum, 2010.
[4] BMU (2011): Langfristszenarien und Strategien für den
Ausbau der erneuerbaren Energien in Deutschland bei
Berücksichtigung der Entwicklung in Europa und global,
online:http://www.fvee.de/fileadmin/publikationen/Politi
sche_Papiere_anderer/12.03.29.BMU_Leitstudie2011/B
MU_Leitstudie2011.pdf

�������������������������������������������������

29D1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan87

Supporting uncertainty evaluation in prospective assessment of innovations:
A case on ecological method in shrimp farming
Heng Yi Teah*1, Yasuhiro Fukushima1, and Motoharu Onuki2
1

National Cheng Kung University, Taiwan; 2The University of Tokyo, Japan*Corresponding author: teah1989@gmail.com

References[1] Kautsky, N., et al. Aquac. 191(1-3): 145-161, 2000.
[2] Cao, L., et al. Environ. Sci. Technol. 45(15): 6531-6538,
2011.
[3] Mungkung, et al. Int. J. LCA 11(1): 55-59, 2006.
Cost benefit strategy[4] Pelletier, N., et al. Environ.
Sci. Technol. 43(23): 87308736, 2009.
Better[5] Bio-Tigermein Scientific Inc. Test & Consult Service.
http://www.biotigermein.com/ Cost
(Accessed
24.03.2014)
benefit strategy
20

100

40

60

rse

BetterReducent

Replace60

Reduce

20

40

Same

80

80

t

40
0

tte

Reduce

nt

20

40

60

80

Worse

0

10

Be

Strategy choices

rce

10

r P
erc
en

Same

60

Pe

Replace

rse
Wo

20

Stagnant

Strategy choices

rce

100

Pe

r P
erc
en

t

80

Wo

3. Case study
Local farmer, Mr. Yan had discovered that specificheterotrophic bacteria (Bacillus spp.) inhibit virus outbreak. He
has successfully implemented his discovery, with a popularshrimp species Penaeus vannamei in 0.2-hectare earthen pondwith zero-exchange of water for 245 days, with a 28-day-interval bacteria application along with total feed of 1953 kg.
These parameters are not yet an optimized recipe. Along thecourse of this experiment, viruses (IHHNV, TSV, WSSV, andYHV) detection test was performed by an ISO-certified
laboratory, Bio-TigerMein [5]. The effect of changes inbacteria addition frequency on shrimp yield is uncertain due toecological variability and experiments are costly; the farmer’s
implicit knowledge may better predict productivity. On theother hand, it is more difficult for the farmer to link theprediction with economic and environmental outcomes.
Heterotrophic microbes and phytoplankton can convert shrimp
metabolic waste into biomass, which serve as alternate shrimp

4. Results and Discussion
Fresh shrimp at farm gate cost 161 TWD kg-1 and isassociated with 3.97 kg-CO2eq. kg-1 in benchmark application.
The indifference curve (Figure 2) shows for example,
increase in bacteria frequency to a 22 day-interval expecting a
1% increase in production is worthy in terms of GHG emission
reduction but does not pay off in terms of cost. The decision
tree analysis for feed altering strategies is illustrated in mixing
triangle (Figure 3), presenting the cost effective and low GHG
domain at given condition.
Any decision must be made under some degree of
uncertainty. Our approach delegates the role of uncertainty
judgment to the experts, while taking responsibilities onremoving the complexity due to expansion of scope across the
product lifecycles. This approach is particularly useful inagri-/aqua- cultural studies, because acquiring sufficientvolume of data for highly variable environments consumes
years of time. Farmers’ experiences and implicit knowledge areassumed to be the best available alternative to scientificallyvalid data in most of the cases.

tte

2. Methodology
First, a cradle-to-gate, stand-alone LCA is performed tobenchmark the contribution of the ecological innovation interms of cost and GHG emission for shrimp production, basedon inventory data farm-scale experiment and literatures [2, 3,
4]. To allow farmers to explore alternatives in bacteria addition
and feeding strategies, 1) an indifference curve, which shows
the required productivity enhancement to outweigh additional
economic and environmental cost on the basis of benchmark
practice and 2) a mixing triangle for two-way sensitivity withthree potential outcomes are developed.

feed, but its substitutability is also uncertain.
We first applied LCA reversely showing farmer theindifference (or tipping-point) curves of productivity to
breakeven the cost and GHG at any given input interval
relative to benchmark. The curves are shown for bacteria
addition support. Next, feeding strategies (same, reduce - direct
feed reduction, and replace – use of low-protein-feed but at thesame amount) are evaluated with scenarios of increase,stagnant, or decrease in shrimp yield with undesignatedprobabilities of occurrence, which are to be judged by farmer
in decision tree (Figure 1). Preference feed strategy isrecommended with the information.

Be

1. Introduction
Innovation of heterotrophic bacteria addition with revised
feeding strategy may improve aqua-cultural pond ecology;
thereby expected to reduce virus outbreaks, main cause of
unstable shrimp production [1]. However, no valid scientificquantification of this effect exists yet. Thus, uncertainties in its
economic and environmental effectiveness hold back the
improvement and implementation of this innovative practice.
This study presents decision tool under the concept of‘indifference curve’, to support farmers in tailoring theapplication strategy to respective ponds. Based on expert
judgments (i.e., local farmer) on expected effectiveness, ourapproach treats the uncertain in prospective changes, andclarifies decision criteria in cost and life cycle environmental
impact (GHG emission in this study) in an integrated manner.

Replace

60

40

Same

Reduce80

Stagnant Percent

20

Same
0
10
20

40

60

80

0
10

Stagnant

Replace

Worse

Figure 3. Mixing triangle for cost benefit feed
altering strategies support (low GHG strategy
is not show due to space constraint).
Stagnant Percent

Figure 1. Decision tree analysis forfeed altering strategies.

Figure 2. Indifference curve for bacteria
addition support.

�������������������������������������������������

29D2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

88

Development of supply-chain matrix database with IDEA aiming
for the application to consequential LCA
Kiyotaka Tahara*1, Masaharu Motoshita1,2, Kotaro Kawajiri1, Hiroki Hatayama1, Chunyoul Baek1
and Tomohiko Ihara3
1National Institute of Advanced Industrial Science and Technology, Japan; 2Techische Universitaet Berlin, Germany;
3The University of Tokyo, Japan*Corresponding author: k.tahara@aist.go.jp

1. Introduction
It is crucial to predict the consequences of introducing
new technologies and policies. However, in many cases, theassessment has been performed based on the attributional
approach without considering the induced changes in the
demand and supply of materials, products and services by the
introduction of new technologies and policies. It is needed toestablish the assessment model that can analyze comprehensive
consequences including the induced results in the wholeindustry. Therefore, we are developing a supply-chain matrix
database to establish a method for assessing consequential
results in industrial activities caused by introducing newtechnologies/policies.
2. Concept of IDEA
All economic activities in Japan are compiled in statistics
according to Japan Standard Industrial Classification (JSIC).
Following the classification, there are various statistics
produced for manufacturing and non-manufacturing industries.
Therefore, IDEA codes were prepared based uponclassification by industry and commodity. Consequently, IDEA
has a hierarchical structure as shown in figure 1, where unit
processes, classified by a 6 digit code, were prepared mainly
using statistics (about 2000 processes), and the more importantinventory data are collected by using process data (about 1800
processes). By classifying and managing all products withIDEA codes, it is expected to provide an exhaustive database
covering a large number of products for use as backgrounddata.
4‐digit industrial 6‐digit commodity
2‐digit industrial
sub classification
classification
classification(XX0000‐000)(XXXX00‐000)(XXXXXX‐000)
09 MANUFACTURE OF FOOD
0911 Meat products
Chop of meat and frozen
meat, except broilers

9‐digit commodity
sub classification(XXXXXX‐XXX)

Use as needed

Canned, bottled andpotted meat
Meat products about 2000 classifications
0912 Dairy products
ButterCheeseProcessed milk
Cream

Ham
SausageBacon
the database will be
more exhaustive

Ice cream

Original
Miscellaneous dairy products classification

Figure 1 Outline of IDEA classification
3. The IDEA Matrix
For supply chain matrix database development, it isnecessary that data flows of products have a representative andcompleteness of the manufacturing process. So, we used IDEA
to create a matrix. The unit process data created the matrix A(IDEA input coefficient matrix), that is 2000 × 2000 matrix.
And then, as shown in figure 2, the matrix M (IDEA matrix)

was obtained by multiplying the matrix P (annual Japanese
production) and the matrix A. The IDEA matrix also
considered the amount of products annually imported (matrixG) and annually exported (matrix E), and final domestic
consumption (matrix C). The balance of the amount of supply(P + G) and demand (AP + E + C) within the IDEA matrix was
confirmed and inconsistencies between supply and demand in
were identified due to differences in classification of IDEA andstatistics, differences of the reference year, differences ofsystem boundary and differences in the unit of products. We
adjusted the supply and demand balances as much as possible.
If balances were not achieved, we added correction terms using
matrix X.

IDEA input
coefficient matrix
A×

annualJapanese
productionP

IDEA Matrix
A･diagP; M

Final domestic consumption
C Import
G Export

Agriculture・・・Food・・・Chemical ・Electricity
Products
Agriculture
・
・
Food
・
・
Chemicalproducts
・・・Electricity
・Japanese Industries
・・

E Correction term
X

DemandAP+E+C
SupplyP+GTime period; 2010

Figure 2 Outline of IDEA matrix
4. Issues to resolve
1) Issues of unit process data
Unit processes should include intermediate parts,
however some unit processes only include input materials,
such as steel. In addition, some chemical products haveintermediate products which are not reflected in statistics.

For some unit processes only one method of production
was chosen even though there are several methods.
2) Issues of data maintenance
There are differences in measurement methods between
domestic products and import and export products. For
example, domestic buckwheat's weight is the weight ofgrains, but imported buckwheat's weight includes theweight of the husk and grains. It is necessary to unify andconfirm the measurement methods and definition of
products.

It is difficult to match the classification of trade statistics
with IDEA classifications as there are someclassifications within IDEA which cover more or lessproducts than trade statistics. The classification of someproducts is in a nested structure.
5. Case study
In order to confirm the validity of the IDEA matrix, we haveconducted a case study on the introduction of next-generation
vehicles.

�������������������������������������������������

29D2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan89

Resolution of Nuclear Power Plant Construction Conflicts—
Argument of Tsunami Issues Through Concept Mapping and Lifecycle Thinking.
Ting-Fang Hsieh and Yuh-Ming Lee *National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw

1. Introduction
The human and economic disaster caused by tsunamis indensely populated and industrial coastal regions has been
documented as horrific tsunami events. Even though thefrequency of tsunami disasters is low, its threat should not be
underestimated. There are three approaches to the argument of
this study. The first is to estimate the features of the tsunami
barrier, one of the parts of nuclear power plant constructions,built as an outside wall to block the tsunami. Besides, try to
discuss the effects on the barrier through lifecycle thinking
assessments. Furthermore, we create the concept mapping todisplay the relationship among the nuclear power plant
construction, the coastal area, and the land use of human beings.
Coastal zone, also an environmentally-sensitive area, isconsidered to reserve plentiful biodiversity.
2. The Influence of the Constructions
The barrier that alters the longshore current which willchange the coastal terrain is called “Jetty Effect”. The
influences are involved in the coastal environmental conflicts,
the biodiversity reduction, and the impact of human use
resulting in the loss of homeland.
Traditionally, coastal protection facilities are mainly used
to prevent disasters. However, under the premise of today'semphasis on sustainable development, the tsunami barrier
setting would be regarded as the detriment on coastal
ecological environment.The impact on the ecology of coastal
constructions:
1)The habitat disappears, leading to reduction in the number ofbiological populations and even species disappearance.
2)The degradation or disturbance of the habitat.
3)The tremendous changes of biodiversity.
4)The coastal constructions block the ecological corridor,
resulting in the disappearance of species.
5)Jetty effect: the barrier which obstructs longshore transport
results in coastal erosion and the loss of land. [1]3. The Twin-Wing Tsunami Barrier
The increasing incidence and frequency of tsunami events,
particularly around the Asia Pacific rim, created an urgent needto respond to the challenge of developing a barrier capable ofdisrupting and neutralizing the overwhelming power oftsunami waves. The Twin-Wing Tsunami Barrier has beendeveloped in order to disrupt and neutralize the tsunami flood
wave. The latest break-through invention, the Twin-Wing
Tsunami Barrier is the ultimate solution which has been
designed to protect designated tsunami prone areas. Lying
passively on the sea bed, it is instantly activated by theapproaching water surge of the tsunami wave and is
automatically deployed to offer large scale coastal protection.
Operating independently from coastal warning systems, it
can be positioned across a bay shape or along a coastal stretch
and in its passive resting position it interrupts neither shipping
nor marine life. Alternatively, the barriers could be built fromgabions and lowered into the sea. The space between thesetsunami barriers and the coast can be filled with solid material,
thus allowing reclamation of new land, or this gap can be used
for fish farming. These barriers can contribute to preservationof beaches and natural ecosystems at the coast. [2]4. The Concept Mapping and Lifecycle Thinking
Minimizing the environmental destruction and damage isnecessary. It’s a very important concept about natureenvironmental protection to make impact-reduced measuresand alternatives in coastal constructions, including seawalls,
tsunami barrier, jetty and so on. This system is the assessment
for evaluating the negative impact from human activities. The
approach processing is: avoidance, minimization, rectifying,
reduction and compensation. [3]Avoidance is in the development of behavioral, biologicalor avoiding protected species habitat protection measures.
Minimization is as far as possible to minimize the impact ofdevelopment. Repair means the restoration of the environment
will be affected. Rectifying is maintained by measures toprotect or to reduce the impact of development activities on theenvironment. Compensation is when you cannot avoid damage
to the environment, you can provide an alternative environment
as a compensation for environmental damage methods.

Figure 1.The ecosystem assessment of coastal constructions
5. Conclusion
Strengthening the nuclear power plant structures toachieve the protective function is imperative; meanwhile,retaining the plentiful ecological function also cannot beignored. Based on the concept of symbiosis with nature, we arebuilding upon the coast, not only consider economic issues ofland use, but also considering the issue of ecologicalenvironmental protection. Thus, how to minimize the impact
on the ecosystem of the natural environment as possible as we
can is a significant topic for implementing the sustainable
management.
References[1] J.R.C. Hsu, Appreciation of static bay beach concept forcoastal management and protection. J. Coastal Research,
24(1): 198-215,2008.
[2]Global Flood Defence Systems. Twin-Wing Tsunami Barrier
Technical Documentation. http://www. globalfloodds. com/
(Accessed 15.08.2014).
[3]Y. Kuo, T. Lin and J. Liao. The Research of Mitigation
applied in coastal engineering. Proceedings of the 33rd
Ocean Engineering Conference, 2011.

�������������������������������������������������

29D2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan90

LCA system boundary selection using the industrial clustering analysis
Shunsuke Okamoto*1
1

Kyushu University*Corresponding author: solitario_halcon_azul@yahoo.co.jp
1. Introduction
In Japan, a large number of organizations have regularly
published life-cycle assessment (LCA) reports as specified
in the ISO 14000 series. An important issue is how anorganization estimates its life-cycle CO2 emissions. An
LCA is divided into two analyses: a process analysis and an
input–output analysis. The process analysis has anadvantage in accuracy in the production processes, while
the input–output analysis has an advantage in its
completeness with regards to the production network
system (i.e., it uses a complete system boundary). The
process LCA method is subjective, in the sense that the
LCA system boundary is freely decided by analysts, whichconsequently leads to truncation error and underestimationof life-cycle emissions. In the present paper, we propose ananalytical method for identifying environmentally
important production processes and production networks
that uses both nonnegative matrix factorization and input–
output analysis. Applying this method to a 2005 Japanese
input–output table, we detected important production
systems for industries with relatively high life-cycle CO2
emissions and determined which production systems
should have a higher priority for being included in the LCA
framework. Finally, we describe the implications for how
industries should manage life-cycle CO2 emissions.

α , n  is the vector representingHere
i   i 1, 2,
CO2 intensities obtained by dividing the amount of sectoral
CO2 emissions by sectoral outputs. The matrix Gj*
represents the CO2 emissions induced by the inter-industry
transaction from industry i to industry j, which is associatedwith the final demand of specific industry j*.
To apply nonnegative matrix factorization, we transformeq. (2) to eq. (3) as below: 1 g j*  g j*
*

ij
ji
Gj  20i  j 
i  j  3j*Here gij is the (i, j)th element of the matrix Gj*. A large
number of existing environmental input-output studies
employ a directed matrix in which each matrix element
represents inter-industry transaction from industry i toindustry j, while this study employs an undirected matrix inwhich each matrix element represents the strength of CO 2
emissions induced by the inter-industry transaction between
industry i and industry j. In this study, we will detect the CO2clusters from the supply chain networks described by eq. (3).
Following the method of nonnegative matrix factorization
introduced in Ding et al. (2005), we can find CO2 clusters
by solving the eq. (4):
Minimize J
H 0

D

1

*

2G j D12  HH 

2
F

 4

Here, D   di  is the degree matrix which represents

2. Methodology
Following the unit structure model (Kagawa et al, 2013),
the intermediate inputs induced by the final demand of j* thindustrial sector, or Bj, is written as eq. (1):the CO2 emissions induced by inter-industry connections ofindustry i and di 

 j gijj .  H  hiK  is the indicator*matrix which is obtained endogenously. The superscript

prime represents transposition of a matrix, K represents the 

number of clusters, and2F

represents the Frobenius norm.

Here A=(aij)(i, j=1, 2, 3, …, n) is input coefficient matrix,
reflecting the input of a commodity from industry i toindustry j, is the vector which represents the final demandof industry j* at the j*th column and 0 at the any othercolumns of this vector, and diag () is the diagonalizaton.
The CO2 emissions induced by the final demand of industry**

Results and conclusions will be shown at the conference.

4. Refernces[1] Kagawa, S., et al. Social Networks 35: 423–438, 2013.

j* can be estimated as below:
G j  diag  α  B j

3. Results and conclusions

 2

[2] Ding, C., et al. Proceedings of SIAM International
Conference on Data Mining: 606–610, 2005.

�������������������������������������������������

29D2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

91

Assessing Climate Impact of Industrial Symbioses: A Dynamic Approach
François Dumoulin,*12 Tom Wassenaar,1 Jean-Marie Paillat,1
1
CIRAD, UPR Recyclage et risque, F-97743 Saint-Denis, La Réunion, France;
ADEME (French Environment and Energy Management Agency), Angers 49004, France*Corresponding author: francois.dumoulin@gmx.com

2

1. Introduction
In economies where natural resources are rarefying,
Industrial Symbioses (IS) are becoming promising solutions tomanage natural resources. IS however do not have as corollary
the absence of environmental impacts, that thus remain to beassessed [1]. Global warming impact (GWI) is anenvironmental phenomenon the reduction of which is at present
of major importance. The most widely used method to link
GWI to GHG emissions of industrial systems (as used in
product life-cycles) is the Global warming potential (GWP)
and its indicator CO2 equivalent (CO2-eq), also commonly used
to express the GWI of IS [2;3] However, although its use isrelevant for assessing GWI of products or comparing
efficiencies between several emission years, it does not express
the GWI at different time horizons. Both dynamics GHG
emissions and their GWI assessment, that are essential to aptly
assessing structural changes engendered by IS projects, are notconsidered while using the GWP, which biases the analysis.
Here, we briefly recall the semantic and mathematicalreason of the limits of assessing an activity's impact through
GWP and propose a derived model and tool that we
subsequently illustrate.
Global warming potential
GWP is defined [4] as the quotient of time-integrated
global mean radiative-forcing (RF) of a pulse emission of 1kgof a gas (g), relative to that of CO2, as follows:t∫ RF g (t )dt

GWP g =AGWP g= t0
AGWPCO
2∫ RF CO (t)dt2(1)

where y is the (variable) emission year, l the last emission year,
Egy temporal inventory of gas emissions (in kg).
Projections comparison and discussion
Once a temporal inventory is established, its AGWP has tobe assessed by using equation (3); we built a R-script for thispurpose that enables to compare it to the current GWP method.
Figure 1 presents the results for two dummy processes
simulated over 30 years (2015-2045). Process 1 is a transporttype process (mainly CO2 and CO emissions) and Process 2 iscomposting-type process (mainly CH4, CO2, N2O emissions).

Figure 1. GWP vs. AGWP from a temporal inventory
On the left, current GWP aggregates all the emission
impact over time and concludes that process 1 is more harmful,while the dynamic AGWP (right) mitigates such a conclusion:
P1 barely exceeds P2 after 100 years.
This clearly calls 1) to reconsider the current use of GWP
and 2) to explicitly address the temporal horizon withstakeholders when eco-designing structural system changes
such as IS.

0where time-integrated RF is equally called absolute global
warming potential (AGWP) and t temporal horizon that inreference to Kyoto protocol in currently set to 100 years [4].
Since CO2 is a persistent GHG, as such the GWP minimizes theimpact of short-lived GHG.
In addition, a fixed time horizon, e.g. from 0 to 100 years,
limits the use of invariant potentials and thus does not allow toassess GWI over time, either residual RF or cumulative RF (i.e.
AGWP).
Assessing AGWP over time
The GWP is inconsistent with the GWI assessment ofstructural system changes. Acknowledging the relevance of RFconcept and its cumulative effect, as suggested by IPCC, we
propose to assess their GWI by using AGWP. This, however,
implies to consider the emission year as variable (temporal
inventory), as well as RF. Indeed, RF is defined as follows:
RF g (t)=ag . C g (t )(2)where ag is the radiative efficiency of a given GHG and Cg its
time dependent abundance function, which has an exponentialform.
The ultimate formula stating the AGWP of multi-annual
system σ then becomes:lt− yAGWP (t)= ∑ ∑ E g y⋅∫ RF g (t )dt
σ

σ

y =0

g

0

(3)

Acknowledgments
This work was supported by the French Environment andEnergy Management Agency (ADEME), the French
Agricultural Research Center for International Development(CIRAD) and the French Ministry of Food, Agriculture andFisheries.
References[1] Boons, Frank, Wouter Spekkink, Yannis Mouzakitis.
The dynamics of industrial symbiosis: a proposal for aconceptual framework based upon a comprehensive literature
review. J. Clean. Prod. 19 (9-10): 905–11, 2011.
[2] Paquin, R. L., Busch, T., & Tilleman, S. G.. Creating
Economic and Environmental Value through Industrial
Symbiosis. Long Range Planning, 2013.
[3] Park, H.-S., & Behera, S. K. (2014). Methodologicalaspects of applying eco-efficiency indicators to industrial
symbiosis networks. J. Clean. Prod., 64, 478–485, 2014.
[4] Forster, P, et al. 2007. Changes in Atmospheric
Constituents and in Radiative Forcing. In Climate Change
2007: The Physical Science Basis. Contribution of Working
Group I to the 4th Assessment Report of the IPCC. Cambridge,
United Kingdom and New York, NY, USA: Cambridge
University
Press.
http://www.ipcc.ch/pdf/assessmentreport/ar4/wg1/ar4-wg1-chapter2.pdf. (Accessed 20.08.2013).

�������������������������������������������������

29D3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan92

Towards a Low-carbon Future in China’s Rural Residential Sector
Rui Xing,* Tatsuya Hanaoka, Yuko Kanamori, Hancheng Dai, Toshihiko Masui
National Institute for Environmental Studies, Japan*Corresponding author: xing.rui@nies.go.jp
1. Introduction
Until recently rural areas accounted for a majority of
population in China. In 2011 urban population surpassed rural
population for the first time due to urbanization process, still
there are over 650 million people and over 210 million
households [1] live in rural areas. Instead of commercial energy,
most of the rural households rely on straw and firewood fortheir daily energy use. It is necessary to increase rural access toless polluting commercial energy and alleviate environmental
problems caused by the highly unsustainable energy structure.

ܵ‫ܦ‬௜ ൌ ܷ௜ ൈ ‫ܣ‬௜ ൈ ܵ‫ܨ‬௜(1)Here, SDi is service demand of each province. Ui represents
service demand of each application per household or per floorarea, Ai represents amount of household or floor area, SFi
represents satisfaction factors.
Satisfaction factors are coefficients which evaluateadequacies of service demands and are closely related to percapita income. Satisfaction factor of each application isresulted by optimization analysis in order to keep model
estimation consistent with historical data in the base year.
For hot water application, SF is calculated by Equation
(2).
SFi 

18653  PCICi
17034  ( PCICi  1619)(2)

where PCICi is rural per capita income (2011 US$) of eachprovince.
For other applications SF is calculated by Equation (3).
SFi 

25775  PCICi
17034  ( PCICi  8741)(3)

Figure 1 shows satisfaction factors of hot water use and per
capita incomes of 31 provinces.
3. Low-carbon technologies
To select effective low-carbon technologies for rural
residential sector, we use the AIM/Enduse model [3], a

0.6
Satisfaction factor

0.5
0.4

0.3
0.2
0.1

0.0
0

500

1000

1500

2000

2500

Per capita income (2011 US$)

Figure 1. Satisfaction factors of hot water use
Heating

Hot water

CookingLighting

Beijing

OthersShanghai

400

Service demand (ktoe)

2. Estimation of service demands
In this research, the service demands of rural residential
sector are estimated by a macro-model [2] through 2030. The
macro-model simulates the demands for final energy serviceson the parameter inputs of futures trends in a variety of factors.
The urbanization process is also taken into account by
estimating future rural population and floor area. The model
estimates the changes in service demands by different
applications every 5 years.
The preliminary estimation from the model appears to bemuch higher than statistical data [1] in base year (2010). One
possible reason is that in the model energy usage patterns such
like frequency of shower times and operation hours ofhousehold electronics are set on standard level of developed
countries. While in rural China these usage terms may not be
fully applied due to the limited financial resource. Thus we
introduce corrective coefficients – satisfaction factors to
calibrate the model estimation. The calibrated service demandis calculated by using Equation (1).

0.7

300

200

100

0
2010

2020

2030

2010

2020

2030

Figure 2. Estimation of rural residential service demands
bottom-up optimization model with a detailed mitigation
technology database, to estimate mitigation potential of
low-carbon policies. In the base year (2010) the estimatedservice demands are disaggregated to energy usage of existing
technologies, while in the target year (2030) service demands
are satisfied with energy efficient technologies. The model
selects technology combination for each province under the
least total-system cost.
4. Results and discussions
Figure 2 indicates breaks downs of service demands from2 regions as an example. In most of the provinces rural
residential service demands will decrease in the future due tourbanization process. Still implementation of low-carbon
technologies will improve rural energy structure and bring CO2
emission reductions as well as financial benefits.
Acknowledgments
This research was supported by the Environment Research
and Technology Development Fund (S-12-2) of the Ministry of
the Environment, Japan.
References[1] China Statistical Yearbook.
http://www.stats.gov.cn/tjsj/ndsj/ (Accessed 03.09.2014).
[2] Xing R. and Ikaga T., Assessment of low-carbon policy
implications in China’s urban residential sector,
International Journal of Sustainable Building Technology
and Urban Development 4(3): 229-242, 2013.
[3] Kainuma M. (ed.), et al. Climate Policy Assessment:
Asia-Pacific Integrated Modeling. Tokyo: Springer, 2003.

�������������������������������������������������

29D3-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

93

Exploring Intersection of Product Lifecycles: GHG Emissions Associated With Vehicles
And Pavement Influenced By Pavement Maintenance Strategies
Yasuhiro Fukushima,*1 Fitria,2 and Shi-Hsien Yang2
1

Tohoku University, Japan; 2National Cheng Kung University, Taiwan*Corresponding author: fuku@sis.che.tohoku.ac.jp

1. Introduction
In a lifetime of pavement, the use and maintenance phases
occupy the longest period. Maintenance is constantly
performed every several years, and the approaches (roughness
thresholds, intervals, used materials, methods, etc.) are diverse
in different countries. Different maintenance strategies
determine emissions occurring during material production,
construction, end-of-life and/or recycling. The works involved
are material and energy intensive, thus have high potential toburden environment. Moreover, the way maintenance isapplied determines the road conditions that influence the fuelconsumption of vehicles.
New materials and methods for maintenance are being
developed, however, there are no platform to evaluate theircontribution in reduction of environmental impacts. This meansthat there is a gap between the technology development and its
swift implementation to start changing the environmental
performance of pavements.
Climate change influences pavement conditions.
Advancement in climate sciences allows predictions for
specific regions of interest; however, currently there is nolinkage with planning of pavement maintenance.
Here, we present results of our ongoing efforts to develop
a platform that incorporate various maintenance technologies
and pavement materials to work out maintenance schedules andmethods based on life cycle thinking. Both the lifecycles of 1)
road materials used, transportation, maintenance, and 2) the
difference in emission from vehicles due to difference inroughness of the pavement are considered in the evaluation.
This platform utilizes the roughness data measured every year,
to update the pavement deterioration model that will be used
for the scheduling.
2. Methods used on the platform
To evaluate the changes in GHG emission of maintenanceactivities and vehicle fuel consumption due to either switchingcurrent maintenance practice to alternative technology or
performing the road treatment based on specified thresholdrather than a fixed timing interval, life cycle inventory androughness prediction models were prepared. The roughness
prediction model predicts International Roughness Index (IRI,
m km-1) over pavement age; it is one of the parameters used tofurther generate maintenance strategies. This model
incorporates climate conditions; therefore, it may be possible toincorporate climate change scenarios in the analyses, although

this is still ongoing. Vehicle fuel consumption was calculated
based on the assumed number of vehicle to use the road every
year and the associated fuel consumed by each vehicle. Most of
the inventory data are taken from literatures [1-3]. Both roadroughness and speed of vehicles were considered in calculationof vehicle emissions using data from literature [4].
3. Case study
In Taiwan, currently, maintenance is performed withoverlay method every 5 years in average. The cumulative GHG
emission reductions related to both maintenance activity andvehicle fuel consumption compared to the current practice (i.e.,
overlay maintenance every 5 year, vehicle avg. speed 88 km
hr-1, traffic intensity of 5000 vehicles day-1) for a specific roadis shown in Figure 2. The compared scenarios here are OL4,
OL4.5, and MS. In OL4 and OL4.5, overlay is applied when
pavement roughness exceeds IRI = 4 and 4.5, respectively. In
MS scenario, micro-surfacing is applied when IRI reaches 3.6.
From the results, despite lower emission associated withrevised maintenance activity or frequency, increase inemissions from vehicle makes the current practice lower in
GHG emission after 25 years.
On this platform, it is also possible to generate scenarios
according to some criteria. In this presentation, we also present
the generated maintenance scenario by minimizing total
emission over 50 years, open to use of both the overlay and themicro-sufacing technologies.
4. Conclusion
Now, by using the platform together with the roadroughness data over years, it is possible to introduce life cycle
thinking in the planning of road maintenance. Methods toincorporate consideration of climate change and new materials
that have no actual deterioration data must be worked out
together with the standardized experimental tests on pavement
deterioration.
References[1] Giustozzi, F., et al. Int. J. LCA 17: 409-419, 2012.
[2] Cerea, P. Preventive Maintenance Treatments on Road
Pavements:
Multi-Approach
Life-Cycle
Assessment.
Politecnico Di Milano, Italy, 2011.
[3] Lin, S.-T., et al. J Architecture, 40: 1-15. 2002
[4] Chatti, K. and Zaabar, I. Michigan State University, 2012.

Figure 1 (left). Cumulative
GHG emissions associatedwith maintenance activity(filled) and vehicle fuelconsumption (hollow) for
various maintenancestrategies.
Figure 2 (right). Cumulative
GHG emissions in total.

�������������������������������������������������

29D3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan94

A Cradle-to-Cradle Assessment Framework for Green Building Evaluation– Emphases on Energy Management and Resource Recovery
Chia-Lin Hsu and Yuh-Ming Lee*
National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
The global resources are gradually depleted due to theexcessive exploitation of natural resources and overdevelopment. In order to reduce the energy consumption andrapid resources exhaustion, the government tempts to promoteplans that reduce carbon footprint. The construction industry isamount the highest carbon dioxide emission industries. It isimperative to endorse the control of carbon emission inbuilding/construction industry to reduce the impact toenvironment.
In this study, People now could leverage of Cradle toCradle to further research on the renewable energy andrenewable green building life cycle model.
2. Methodology
Ever since the industrial revolution, people have beenprioritizing economic development. As a result products aredesigned and manufactured in a linear “Cradle to Grave”
paradigm. This “Cradle to Grave” paradigm means that once anatural resource is excavated, it follows the one way route ofprocessing, manufacturing, usage and disposal (where it
contaminates the environment). To compensate for the
resulting resource depletion the slogan of the 3R (Reduce,
Reuse, Recycle) has been propagated. However, without
making fundamental changes to product design, theenvironment continues to be contaminated, just at a slower rate.
For example, current energy saving strategies simply prolong
the lives of products or optimize them for downcycling (theycannot be recycled at the same quality as virgin material).
Although this reduces the resources and energy consumption
rate, the products still end up in the “grave” in the end.
“Cradle to Cradle" is a concept which put all of thematerials into an endless recycle and encourages to use therenewable energy. The materials for product manufacturing are
no longer purchased, instead, they are borrowed. The life of a
product does not end as a polluted waste, but start from a newlifecycle.
Braungart and McDonough have defined three basic
principles that are essential to make a true transition towards
sustainable society. The following three basic principles arebeing applied:(1) Waste equals Food; everything is a Nutrient for
Something Else.
(2) Use Current Solar Income, Energy that can be
renewed as it is Used.
(3) Celebrate Diversity.[1]3. Green Building Evaluation
The green building of Taiwan is developed based on
Taiwan’s subtropical climate characteristics with hightemperature and high humidity that can sufficiently meet theneed in ecology, energy saving, waste reduction, and health.
The EEWH green building labeling system was established in
September 1999 as the second certification system in the worldright after the US LEED. The original system comprised ofseven evaluation indicators: greenery (vegetation planting),
water infiltration and retention, daily energy conservation,water conservation, CO2 emission reduction, constructionwaste reduction, and sewage and waste disposal facility
improvement. In 2003, two indicators were introduced in thesystem, including biodiversity and indoor environment quality.
The current nine-indicator green building evaluation was thus
finalized, known as the EEWH system (listed in Table 1).
Furthermore, a scoring and rating system was launched in 2007
for enhancing green building design quality and motivatingbuilders/owners to pursue better performance and innovativetechniques. The rating system defines five classes of green
building design, including Certified, Bronze, Silver, Gold, andDiamond. Meanwhile, the green building of Taiwan can be
redefined as a building with Ecology, Energy Saving, Waste
Reduction, as well as Health. [2-3]Table 1 EEWH Green Building Evaluation System of
Taiwan4. Results and Discussions
In this study, the green building material is an ecological,
healthy, recycled, or high-performance building material that is
capable of efficiently minimizing impacts to earth environmentand damage to human health during its entire life cycle, and inaccordance with the cradle to cradle concept.
5. Summary and Conclusion
The Cradle to Cradle concept has been widely embraced
and promoted by the Taiwan government. In order to promote
innovation in industries has incorporated the Concept into
national policy for sustainable development and resource
management, the government understands the challenge thatcreating a sustainable future presents, In addition, thegovernment has brought Concept products into theirsustainable purchasing plan and incorporated the Concept into
the construction of Green Building.
References[1] McDonough W. and Braungart M., Cradle to Cradle:
Remaking the Way We Make Things, 2002.
[2] Ministry of the Interior Architecture and Building
Research Institute, Green Building Promotion in Taiwan,
Taiwan,2011[3] Ministry of the Interior Architecture and Building
Research Institute, Technology Plan for Sustainable
Green Building, Energy Conservation and Carbon
Reduction, Taiwan�������������������������������������������������

29D3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan95

A Life Cycle Assessment of Silica Sand: Comparing the Beneficiation Processes
Anamarija Grbeš
University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, Croatia
anamarija.grbes@rgn.hr

1. Introduction
Silica sand or quartz sand is a mineral resource withwide varieties of applications; glass industry, construction andfoundry are the most common example. Republic of Croatia
has confirmed reserves of 40 million tons and long tradition of
surface mining and processing. Average production of raw
silica sand in Croatia is 150 thousand tons [1]. The presented
results and findings are part of the doctoral dissertation [2].
2. Materials and methods
In this research eight alternatives of silica sand production
process are designed. For the purpose of design, equipment andmachinery database is generated. Designed inputs and outputs
in production processes are checked for consistency withcurrent industry data. Life cycle assessment is performed using
Sima Pro software and the LCIA is performed using ReCiPe
Endpoint method [3].
Alternatives are named as follows: 1-Electrostatic/dry;
2-Basic/wet; 3-Basic/dry; 4-Flotation/wet; 5-Flotation/dry;
6-Gravity/wet; 7-Gravity/dry; 8-Simulation. At the time ofresearch (2009-2012) the glass grade silica sand production in
Croatia corresponded to alternatives 2-3 (basic processing bysizing and washing) and 6-7 (gravity concentration).
Electrostatic separation was considered at the design level,
while flotation was abandoned after plant destruction inaggression 1991-1995.
Analyzed alternatives had in common the mining andbasic processing operation. Main assumptions for the firstseven alternatives were: surface mining using bulldozers;transportation from mining site to the processing plant (3 km)
by dumpers; then washing and sizing in processing plant which
included the sieve washing, attrition scrubbing, hydro-cycloneclassifying and dewatering. The difference between thealternatives was in the concentration/separation operations
following the basic (initial) processing: electrostatic andmagnetic separation; flotation; gravity concentration. Importantdifference in assumptions on water consumption between the
flotation and gravity concentration alternative is made. In the
flotation it is assumed that the process water is collected andrecirculated, while in the gravity concentration water is takenfrom the river and returned into the river downstream after the
sedimentation. The final assumptions were based on whether
the product is sold wet and then dried in glass factory or isdried and then transported to glass factory. Alternatives marked“wet” included: road transportation of wet silica sand (w=6%)
by lorry (truck) on transporting distance 100 km; drying inglass plant using waste heat. Alternatives marked “dry”
included: drying in the processing plant; road transportation ofdried silica sand (w=1%) by lorry on transporting distance of
100 km.
Simulation alternative included surface mining andmineral processing outside the Croatia (data for sandproduction in Switzerland) and silica sand import by railroadtransport on distance 700 km using EcoInvent database.
3. Results and discussion
Results have shown that the basic beneficiation process(sand washing and sizing) had the smallest impacts among theanalyzed beneficiation processes (alternatives 1-7). However,its application for glass-grade silica sand production is limited
only to very pure raw sand, or for construction and foundry
grade products. In more complex processing (electrostatic
separation, flotation and gravity concentration), assuming thatemissions of chemicals into environment are prevented orminimal, deciding factor between the beneficiation alternatives
was the water consumption and petrol based hydrocarbons use(fuels and reagents). Cradle-to-gate LCA of glass grade silica
sand indicated the fossil fuel use as the major contributor to theimpacts. Transportation of naturally dried wet sand (w=6%)
and drying in glass factory using the waste heat resulted insmaller impact than drying in processing plant and thentransporting it into the glass factory. Results of impact
assessment for each alternative are shown in Table 1.
Table 1. Endpoint indicator values per ton of produced silica
sand (ReCiPe Endpoint (H) V1.06 / Europe ReCiPe H)
Alternative
1-Electrost./d2-Basic/w
3-Basic/d4-Flotation/w
5-Flotation/d
6-Gravity/w
7-Gravity/d
8-Simulation

Human Health
DALY
1,12E-04
7,34E-05(L)8,97E-05
9,92E-05
1,59E-04 (H)9,53E-05
1,12E-04
7,14E-05

Ecosystems
species.yr
4,33E-07
2,73E-07(L)3,53E-07
3,58E-07
6,14E-07 (H)3,63E-07
4,47E-07
2,52E-07

Resources$
346,3
187,25(L)287,42
271,54
490,54 (H)247,22349,74
162,69

4. Conclusion and recommendations
Here presented results of LCA for Croatian glass-grade
silica sand are used to identify the main focus for lowering theimpact of silica sand at various production stages in various
beneficiation processes, and to give the recommendations forthe future process design.
•
Surface mining: lowering the diesel consumption byuse of mining machinery with better fuel efficiency
per ton of produced sand; utilization of mining
machinery with continuous work regime (e.g. rotaryor bucket excavator instead of bulldozer).
•
Sand washing and wet classifying: lowering the water
consumption by the use of water collection,
regeneration and water recirculation systems;•
Flotation: lowering the consumption of petrol basedhydrocarbons as flotation reagents;•
Electrostatic separation and drying: lowering thefossil fuel consumption by using more fuel efficientdrier; utilizing as much as possible the gravitational
dewatering and natural evaporation; drying using
waste heat or other heat sources that cause lessdamage than fossil fuels.
References[1] MINGO. Reserves and annual exploitation 1997-2012.
[2] Grbes, A. Life cycle assessment of silica sandexploitation and processing in Croatia. Doctoral
dissertation. RGNF, Zagreb, 2014.
[3] ReCiPe. Methodology. http://www.lcia-recipe.net/

�������������������������������������������������

29E1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan96

A Life cycle thinking Assessment Framework for Land Reclamation Policy in Taiwan
Lih-Ren Liu ,1 Yuh-Ming Lee* 2
National Taipei University, Taiwan*Corresponding author:yml @mail.ntpu.edu.tw
1. Introduction
Taiwan’s EPA is committed to promoting the “resource
recycling and zero waste” program, including the aspects ofreduction, reuse, recycling, energy recovery, and land
reclamation(5R’s).This research aims to realize an effective
cyclic utilization of resources and establish a resource
recycling society. [1]For achieving the goal of “zero waste” and “total
recycling”, Land Reclamation is a key component of resource
recycling and zero waste. The promotion of the resource
recycling and zero waste policies should be based on a reviewof the domestic noncombustible waste management policy.
1. Experience on Policy Implementation.
2. Technical Specifications and the Control of Incoming
Materials.
3. Operation Management and Assurance Mechanism.
EPA try to establish regulatory framework to minimize
environmental impact during the reclamation to conserve themarine ecosystem and environment.
Life cycle assessment (LCA) involves the evaluation ofsome aspects. This research adopt systems thinking to discuss
LCA conceptual framework of Land Reclamation Policy in
Taiwan.
2. Operation Procedure and Standard
ISO14040:2006 describes the principles and frameworkfor LCA,including:definition the goal and scope of the LCA,
the life cycle inventory analysis (LCI) phase, the life cycle
impact assessment (LCIA) phase, the life cycle interpretation
phase, reporting and critical review of the LCA, limitations of
the LCA, the relationship between the LCA phases, andconditions for use of value choices and optional elements. [2]3. Goal and Scope Difinition
LCA is a tool to assess resources used and potential
environmental impacts (inputs and outputs) throughout aproduct’s life from raw material acquisition through production
use and disposal (i.e. from cradle to grave). [3]In this research,noncombustible waste generation, definedas the starting point for LCA scope,after disposal,land
reclamation is the end of the LCA.Newborn land development
for industrial areas,functional unit for each hectare of land to
produce energy consumed.
4. Inventory analysis (LCI)
the phase of LCI will examine the input of
noncombustible waste and the output of reclaimed land. Input
aspects, including the use of equipment, energy consumed ,transportation. Output aspects,including the discharge ofpollutants to the marine ecological damage, destruction
coastline, affecting water resources, etc.(Figure 1) where all
relevant data are identified and quantified. Constructing theprocess flow chart.Defining the system boundaries.
5. Discussion and Conclusion
After Scope and LCI phase , enter the life cycle impact
assessment (LCIA) phase. Environmental problems to be
included are defined and the data from theinventory analysis are grouped with relevant categories.
In summary, this search intends to apply the life cycle
thinking methodologies and employ the tool of system thinking
to construct an impact assessment framework for the
implementation of land reclamation policy. Life cycle
assessment (LCA) framework involves the evaluation ofenvironmental aspects is adopted. In addition, the causal loops
evoked from systems thinking methodologies are toconstructed to discuss the LCA conceptual framework of land
reclamation policy in Taiwan.
Environmental concerns such as siting issues, preservationof coastline,conservation of marine ecosystem, and argumentsof "zero waste" policy are the key "stressors" to be consideredin the phase of life cycle impact assessment. The discussions
on suitability and sustainability of the land reclamation policy
comprise the core of the life cycle interpretation.The research
try to discuss about: [4]1.The necessity of Land reclamation
2.The location choice of Land reclamation
3.EIA Considerations:Ecological compensation principle
4.Feasible construction methods
5.Plant management regulations
6.How land use
7.Regulations
8.Work and Responsibility
Through the above analysis, with the regulations, makepolicy decision.
References[1] Environmental Protection Agency(Taiwan),International
Forum on Land Reclamation-The Critical 5thR to Zero
Waste,Taipei,2013.12.5.
[2] Pavel Gavrilita.Environmental Systems Analysis of
Municipal Solid Waste Management in Chisinau,
Moldova,Royal Institude of Technology,16-17,2006.
[3] Asa Moberg. Environmental systems analysis tools for
decision-making LCA and Swedish waste management
as an example. Royal Institude of Technology Department
of Urban Planning and Environment Environmental
Strtegies search,19-22,2006.
[4] Environmental Protection Agency(Taiwan),Industrial
waste disposal policy – Land reclamation environmental
impact statement,227-231,2012.

�������������������������������������������������

29E1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

97

Constructing a System Thinking Model for Climate Policy Making Based on National
GHG Inventory
Yu-Tsang Lu and Yuh-Ming Lee*
National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
Generally, a climate policy may cover only a sector or
involve many sectors due to causing synergy. A climate policy
may focus on mitigation or adaptation, even both of them.
Under mid-term global climate regime, developing countries
under the United Nations Framework Convention on Climate
Change (UNFCCC) would voluntarily conduct their nationallyappropriate mitigation actions (NAMAs) by 2020. Meanwhile,
to take actions on adaptation to climate change, which may be
integrated in national adaptation plan (NAP) in somedeveloping countries, is beneficial to them. Both mitigation andadaptation activities under climate change policy may affectnational GHG emissions. [1]National Greenhouse Gas (GHG) inventory is awell-defined system for anthropogenic GHG emissions. Basedon sectors and categories of national GHG inventory, thisresearch explores to build up a system thinking model (STM)
forclimatechangepolicyunderthe
Driver-Pressure-State-Impact-Response (DPSIR) framework[3-4] and develop its casual diagram.
2. Boundary and Methodology
The structure boundary of STM is set on sectors andcategories of national GHG inventory, which include energy
sector, industrial process and product use (IPPU) sector,
agriculture, forestry and land use (AFOLU) sector, and waste
sector [2]. Each sector can divide into categories of layers andis like a tree structure. The same category of bottom layer is a
GHG emission source or a removal sink and has the samefeature on social behavior, technology, activity, product orconsumption so that regression approach can apply to it. In
general GHG emission equals to active data multiple emission
factor.
DSPIR framework is utilized to describe the features offactors which could influence emission or removal. And thenthrough casual analysis positive and negative feedback loops
with mitigation and adaptation activities are identified to
combine a casual diagram. System complexity of national
GHG inventory can be simplified to a structure of the life cycle
thinking model.
3. Casual Diagram and System Thinking Model
For forming a system thinking model, the relative patterns
between GHG inventory and DPSIR framework are discussed.
Respectively socio-economic aspects and climate policies are
key factors that comprising Driver and Response.
Environmental considerations, UNFCCC and its corresponding
protocols could be the main sources of Pressure. Factors ofState would be present state of emissions in national GHG
inventory and those of Impact are changes of emissions in
national GHG inventory. A STM for climate change policy
under DPSIR framework is shown on Figure 1.
NAMA may reduce the need of socio-economic activity,
decrease active data, and then GHG emission would decrease.
Adaptation activity may increase the need of socio-economic
activity compared by that of no adaptation, induce active data
increasing, and then emission increases. NAMA also could
induce technology improvement, abate emission factor, andFigure 1. STM for climate change policy under DPSIR
framework
then emission decreases. Voluntary mitigation target may
depend on the reduction credit from emission trading and newmarket mechanism. Casual diagram is shown on figure 2.

Figure 2. Casual Diagram of STM for climate change policy
4. Discussion
STM for climate change policy under DPSIR framework
is clear. Left part on figure 2 has excellent casual loops. Right
part on figure 2 still exist uncertain because the UNFCCC isnegotiating new market mechanism.
5. Conclusion
This study aims at constructing a system thinking model
for climate change policy in order to assist the decision-maker
to identify how mitigation and adaptation activities affectnational GHG inventory. This system and life cycle thinking
model is helpful and successful to describe the systematicfeatures of climate change policy within the boundary ofnational GHG inventory.
References[1] UNFCCC, Decision 1/CP.16, the Cancun agreements,
2010.
[2] IPCC, 2006 IPCC Guideline for National GHG Inventory,
2006.
[3] Kristensen, P., “The DPSIR framework”, Paper presented
at the workshop on a comprehensive/detailed assessmentof the vulnerability of water resources to environmental
change in Africa using river basin approach, 27-29
September 2004, Nairobi, Kenya.
[4] Daniels P. L., Climate change, economics and Buddhism—Part I: An integrated environmental analysis framework,
Ecological Economics 69, 952–961, 2010.

�������������������������������������������������

29E1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan98

Evaluating the change of psychological factors and pro-environmental behaviors throughworkshop about life cycle thinking and social norms
Eri Aoki*, Kiyo Kurisu, and Keisuke Hanaki
The University of Tokyo, Japan*Corresponding author: eri@ir3s.u-tokyo.ac.jp
1. Introduction
Several factors are reported to influence on proenvironmental behaviors, especially in social psychology [1, 2].
However, how it works on behavior change has not been wellinvestigated. Waste reduction and reuse behaviors (referred as
2RBs) have especially been given less attention than other proenvironmental behaviors. 2RBs have big potential to minimize
wastes through minimizing excessive production. Previous
research [3] showed that “Effectiveness and Attitude” have mostinfluence on the behavior of “denial of plastic bags or wrapping(B1: Plastic bags)”, and “Social and Personal Norms” have mostinfluence on the behaviors of “denial of disposable chopsticks
or plastic cutlery (B2: Chopsticks)” and of “Bringing my own
cup (B3: Own cup)” as 2RBs.
We designed workshops to stimulate on “Effectiveness andAttitude” through life cycle thinking (LCT) and on “Social andPersonal Norms” through visual information. The effectivenessof 2RBs is not only cutting wastes but also cutting every step of
its producing, disposing and even recycling. LCT seems to fulfill
this concept of effectiveness. Therefore, it was adopted to main
stimuli of the workshops. The ‘Social Norms’ are perceived
social rules, moral and other people’s behavior and the ‘Personal
Norms’ are strengthened by the ‘Social Norms’. Therefore,
showing social campaign and other people’s behavior wereadopted to main stimuli of the other workshops.
2. Methods
We designed three different types of workshops; workshopE, -N, and -A. Participants were divided into three groups (n =20, 14, and 15) in each. Workshop-E was focused on
effectiveness using LCT method. Workshop-N was focused on
norms. Workshop-A was focused on both effectiveness andnorms. All workshops consisted of 20-minute lecture, 45-minuteactive group work. In the lecture, a project researcher made apresentation on effectiveness and norms respectively. In thegroup work, participants were asked to discuss in small groups
and make some tasks; to write down all steps of “use own cup”
and “use disposable cup”; to compare these in workshops-E and-A; to make approaches that encourage citizens to do the 2RB as
it is the right thing to do imagining if they are local government
officer in workshop-N. In the last part of group work,
participants were asked to fill a worksheet why the 2RBs are
effective for reducing environmental burden in workshop-E andwhy we should act the 2RBs in workshop-N and -A. As ahomework, participants were asked to show the worksheets toothers and get comments from them. This action reminds them
what they did in the workshop. In addition, telling the opinion
makes people’s opinion fit in it.
The participants were university students in Tokyo (18-23
years old; 21 men and 28 women). We made a poster and asked
to join workshop survey program as part-time job. We did not
mention the program was about environmental issues for getting
variable participants. The detailed questionnaire, which
consisted of specific 20 perceptions and practice about each
2RBs, was supplied online to participants two-week before andafter the workshops. Simple printed questionnaire, which
consisted of the rough understanding of their change ofperceptions and intention of 2RBs, was given to them just after
the workshop on July 31, August 2 and 3, 2013.
3. Results and Discussion
The simple questionnaire indicated that the targeted
psychological factors were stimulated and changed by eachrelative workshop. In addition, the intention and the practice of
2RBs were found to be higher than before. The before and after
detailed questionnaire indicated that participating the workshop
made their targeted psychological factors higher, except“Effectiveness” in workshop-E. In workshop-E, eight first-year
students in private university who had the high perception ofperceived effectiveness of B1 changed their perception. Fromtheir free-answer, they said “I believed Eco-bag (bringing ownbag) is a symbol of Ecology”, “I didn’t think using energy andoil for a production of plastic eco-bag”. This means LCT madethem to reconsider their surroundings, especially indirect
consumptions. In some ways, this achieved objective of LCT,
which is to recognize hidden environmental burden. Some ofthem, however, stopped their thinking at first awareness ofhidden burden and not considered nor compered whole lifestyleenvironmental burden. Three of them changed their behavior
lower and other three kept their behavior in medium. In
workshop-N, most participants changed their perception ofnorms and even effectiveness became higher. The number ofchanging perceptions is largest in workshop-N. Even in norm
oriented program, three male students in national university
mentioned. “Concrete data are important for promoting 2RBs”.
In workshop-A, both effectiveness and norms became higher.
Also, the same perceptions, perceived effectiveness, may be
confirmed by different perspective depending on their values.
Some feel effectiveness because the real burden was decreased;
and others feel it because others did or said effectiveness. The
later one is similar to social norms. Therefore, Workshop-N had
most influence on the perceptions and the behaviors. LCT data
reminds participants their indirect impacts of their lifestyle.
However, we need to keep in mind that just one time information
sometimes make people think they do not need to smaller
effective behaviors than their image. Norm activation or
repeated follow-up is needed for practical LCT programs which
encourage people to have environmental-friendly lifestyle.
Acknowledgments
This study was funded by Grant-in-Aid for Scientific
Research about establishing a Sound Material-Cycle Society
offered by Ministry of the Environment, Japan. E.Aoki's work
was supported by Grant-in-Aid for JSPS Fellows.
References[1] Ajzen, I.: From Intentions to Actions: A Theory of Planned
Behavior. Kuhl J. and Beckman J. (eds.), Action control.
Springer Berlin Heidelberg: 11-39, 1985.
[2] Schwartz, S. H.: Normative Influences on Altruism.
Berkowitz R. (ed.), Advances in experimental social
psychology. New York: Academic Press: 221-279, 1977.
[3] Aoki, E. et al.: Exploring Determinants and Models of 2Rs–Waste prevention (Reduction) and Reuse Behaviors, 10th
Biennial Conf. on Environmental Psychology: 142, 2013.

�������������������������������������������������

29E1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

99

People’s environmental consciousness in daily activities
Ai Hiramatsu,*1 Kiyo Kurisu1
1 The University of Tokyo, Japan*Corresponding author: ai@env.t.u-tokyo.ac.jp

1. Introduction
While people's environmental awareness has increased inrecent years, the gap is pointed out between attitude and action
for environment [1]. It is said that people tend to say “yes” whenanswering a questionnaire [2], to meet expected social value
unconsciously or to continue answering affirmative
automatically without deep thinking. As most surveys on
environmental consciousness have been conducted withpositively-phrased questions, in this research, large-scalequestionnaire survey was conducted using negative questions inorder to understand more deeply the actual process fromconsciousness to real action.
2. Materials and methods
The questions were designed in consideration of ‘yestendency’ and that people perform a pro-environment behavior(PEB) without consciousness of environment. Firstly, 25
questions, except for three, on the environmental awareness indaily behaviors were asked in a negative ways (Table1) using thesix-point Likert Scale. Next, free-answer questions were asked
on: (a) behaviors you usually feel good for the environment, (b)behaviors you wonder whether good or bad for the environment,(c) behaviors which are generally said good for the environment
while you do not think so. The survey was conducted as the online survey to the 15-69 year-old citizen in Japan during 24-27
January 2014. Approximately 72,000 valid responses werecollected in accordance with the ratio of the population census.
Table 1. List of negative questions

1. My PEBs come from a custom rather than envtl. consciousness.
2. My concern about envtl. issues is not particularly high.
3. I don’t know how much media information on env. is reliable.
4R. Envtl. issues are important problems to be solved.
5. When acting, I don’t care about env. in particular.
6. I cannot understand a person enthusiastic in envtl. activities
7. The word “Eco/Environmentally-friendly” is suspicious.
8. Companies and industries should take more efforts than individual.
9. Individual action will not improve the env..
10. I don’t think my behavior is responsible for GW.
11. I have no enough time to act for env.
12. When purchasing, I don’t care about env. (e.g. energy, resources andwastes), particularly.
13R. PEBs should be taken even if they are bothersome.
14. I won’t perform PEBs without the eyes of others or society.
15. Even if good for env., I want to avoid life becomes inconvenient.
16. I perform PEBs for saving money.
17R. Individual action is important to solve envtl. problems.
18. There’s not enough useful information for taking PEBs.
19. Honestly I don’t know what behaviors are good/bad for the env..
20. The solution to GW will come from irrelevantly to myself.
21. There’s not much influence even if an individual doesn’t act for env.
22. There’s a more important thing than envtl. problems for me.
23. I perform PEBs depending on whether there are eyes of anotherpeople.
24. I got fed up with being called for PEBs.
25. I don’t mind even if the earth perish in the future.
(env.: environment, envtl.: environmental, GW: global warming,)

3. Results
Results are shown in Figure1. It showed the following
situations apply to 80% of people; "behaviors are taken by habit
or for the money rather than environmental consciousness" and"I don’t know how much media information is reliable". Then,
60-70% of people said “agree” to the questions of "I have more
important things than environmental problems", "honestly I
don’t know what behaviors are good/bad for the environment","there is not enough useful information for taking
environmental-friendly behaviors", "companies and industries
should take more efforts than individual", and "I want to avoid
life becomes inconvenient". On the other hand, 70% of peopleanswered “disagree” to the questions of " I don’t think mybehavior is responsible for global warming", "there is not somuch influence even if an individual does not act", and "I will
not act without the eyes of others or society", with showing
affirmative about an individual's influence and efforts. In total,
positive attitude of people to the environment was seen. In
comparison of other survey with positive questions, rate of
positive attitude for the environment in daily life was about 1020% lower on average overall.
It is implicated that women have more environmentallyfriendly consciousness than men and elder people tend to be
more conscious than younger people, which are consistent withother research results.
For free-answers for the questions shown above (a, b, andc), through word frequency and co-occurrence network analyses,
it turned out that the common behaviors were highly ranked in
all the questions: garbage separation, power saving, recycling
and eco-bags, etc. It was observed that people worried about
actions which had a trade-off relationship from diversified
standpoints.

Figure 1. People’s consciousness of daily life
Acknowledgments
This research was supported by Environment Research andTechnology Development Fund (Development of LCA Databaseand Educational Materials about Daily Behaviors aiming for
Common Platform Provision) of the Ministry of theEnvironment, Japan.
References[1] Kollmuss, A. & A gyeman, J.: Mind the Gap: Why dopeople act environmentally and what are the barriers topro-environmental behavior?, Environmental Education
Research, 8(3): 239-260, 2002.
[2] Berg, I.A. and Rapaport, G.M.: Response bias in an
unstructured questionnaire, The Journal of Psychology.
Interdisciplinary and Applied, 38(2), 475-481, 1954.

�������������������������������������������������

29E2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

100

Visualizing Core Structure of International Carbon Network Associated withHousehold Consumption
Yasushi Kondo,*1
1

Waseda University, Japan*Corresponding author: ykondo@waseda.jp
1. BackgroundThe structure of a production network involved insupplying a given product is generally considered as quite
complex. The transformation of a network into its simplified
structure, or core structure, therefore, offers an effective tool
for better understanding how the environmental impact associated with a product propagates throughout the entire economy.
Further, the simplified structure may be useful in assessments
regarding supply-chain GHG management like the Scope 3
Standard of the GHG Protocol Initiative.
2. Method
In this study, we applied PMDA [1], a method to extract a
core structure entangled in a production network that we haveelsewhere developed, to WIOD [2], an environmentally extended multi-regional input-output table, for understanding theinternational carbon network associated with household
consumption. PMDA is based on structural path analysis (SPA)[3–5]. The utility provided by SPA is its ability to identify theindividual paths and their impacts through the hierarchicalsequences of sectors—each path goes from final demand to an
impact-generating sector via intermediate products-producing
sectors; for example, from household to agriculture via
restaurant and food industry. A core structure extracted by
PMDA is suitable to be visualized, for example, in a Sankey
diagram.
3. Discussion
Widespread use of LCA and carbon footprint has
highlighted consumer responsibility, i.e., accounting of environmental burden from consumer perspective. It provides adifferent point of view from producer responsibility, e.g., in
accounting territorial emission for climate change mitigation.
However, the reality is somewhere in-between, which is calledshared responsibility in literature [6, 7]. A graphical visualization of the core structure allows us to get an insight into
international carbon networks associated with household consumption from producer-, consumer- and shared-responsibility
perspectives.
References[1] Kondo, Y., A.H. Strømman, S. Kagawa S, and K. Nansai.
Path-based Matrix Decomposition Analysis: Theory andApplication. 20th International Input-Output Conference,
24–29 June 2012.
[2] Timmer, M.P. (ed.) The World Input-Output Database(WIOD): Contents, Sources and Methods. WIOD
Working Paper No. 10, 2012, http://www.wiod.org/
publications/papers/wiod10.pdf, (Accessed 09.09.2013).
[3] Defourny, J., and E. Thorbecke. Econ. J. 94(373): 111–
136, 1984.
[4] Peters, G.P., and E.G. Hertwich. Econ. Syst. Res. 18(2):155–181, 2006.
[5] Bourgault, G., et al.. Int. J. LCA 17(6): 774–786, 2012.
[6] Lenzen, M., et al. Ecol. Econ. 61(1): 27–42, 2007.
[7] Rodrigues J., and T. Domingos. Ecol. Econ. 66(2–3):
533–546, 2008.
Acknowledgments
This research was supported by JSPS KAKENHI(24510059).

�������������������������������������������������

29E2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

101

Life Cycle Inventory Database and Its Applications to Support Public Policy
Thumrongrut Mungcharoen*1,2 and Saowalak Olarnrithinun1
1

National Science and Technology Development Agency, Thailand; 2Kasetsart University, Thailand*Corresponding author: thumrongrut@nstda.or.th, fengtrm@ku.ac.th

1. Introduction
With the technical support from the Japanese government,
Thailand has started a life cycle inventory (LCI) databaseproject since 2005. The project was recognised as the national
project in 2007 due to the support from several nationalorganisations.
The applications of LCI database to support public policy
have been promoted since 2009. In this paper, four case studies
implemented by the National Science and Technology
Development Agency (NSTDA) with the support of several
national organisations will be mentioned.
2. Progress of the Thai LCI database
Up to now, more than 800 Thai LCI datasets, according to
ILCD and ISO format, have been collected and maintained at
the National Metal and Materials Technology Center (MTEC)
under NSTDA. The list of datasets is shown in Table 1.
Table 1. Thai life cycle inventory datasets [1]Substances (datasets)
Substances (datasets)
Natural gas
6
Rice
17
Refinery8
Pulp & paper
9
Petrochemical
19
Para-wood
17
Ferrous9
Cassava & products
15
Non-ferrous
5
Longan + Agri-food47
Electricity grid mix
1
Pineapple + Veg.frozen
11
Plantation of plants
Water
6
80
188
Oil palm & biodiesel
Road transportation
24
Ship & rail-transport
43
Coconut milk & Curry
3
Ceramics
7
Paints + Ind. Gases
9
Glass & mirror
7
Fertilizers & herbicides 16
Chemicals & products 47
Alt.mat. for wood3
Incineration
Construction mat.
88
Landfill + recycle
Feed mill
15
20
Wastewater treatment
Livestock & products
33
9
Rubber7
Others (textile, EE, etc.) 116
TOTAL
846
3. Case studies of LCI applications to support public policy
Four case studies of LCI applications to support Thai
public policy will be explained in this section.
For greenhouse gas (GHG) reduction policy, Thai national
carbon footprint (CF) labelling scheme has been establishedsince 2009 under the Thailand Greenhouse Gas Management
Organisation (TGO). The GHG emission factors (EF), generated
from the Thai LCI database, have been supplied to TGO every
six months. The EFs are publicly available on the TGO website
to be used for CF calculation of both products and organisations.
Up to now, there are 1,207 products (from 282 companies) and29 organisations certified with the CF labels.
For the promotion of biofuels according to the Thaialternative energy development plan 2012-2021 [2], LCI
database and LC assessment (LCA) were used for GHG
calculation of Thai Palm Oil Industry during 2011-2012. The
results showed that biodiesel from Thai palm oil could reduce
GHG by more than 60% comparing to the fossil diesel fuel. The
more comprehensive study, including environmental social andeconomic indicators, is on-going with bioethanol fromsugarcane-molasses and cassava using LCI database and LC

sustainability assessment.
For the Thai green public procurement (GPP) policy, the
LCI database has been used in LCA and LC costing study during
2012-2013 to quantify the benefit of this public policy during
the 4-year implementation plan, 2008-2011. The results showed
that, from the 930 million THB spending on green products, thegovernment could reduce the GHG by 25,600 tons CO2e andsave the external cost by 220 million THB. With this impressive
results submitted together with the 2nd phase GPP plan, thenational pollution control board was then endorsed the plan.
For the Green Growth and Green Industry policies
promoted by the National Economics and Social Development
Board and the Ministry of Industry, four pilot research projects(see Figure 1) have already been granted to the researchers, bothscientists and economists. LCI database will be used withtraditional GDP, economic input-output table and system ofenvironmental-economic accounting (SEEA) [3] to quantify thegreen GDP on both national and specific sector levels. These
research projects are expected to complete by the end of 2014.

Figure 1. Framework of the green GDP research projects
4. Conclusions
Since 2009, LCI database have been used as one of the
key infrastructures of Thailand to support public policy on
green growth. The four success cases on carbon footprint,
sustainable biofuels, government green procurement, and green
GDP have been highlighted. It is expected that more
applications of LCI database will be implemented to support
policy justification in Thailand.
Acknowledgments
The authors gratefully acknowledge financial support fromthe Thai government and technical support from the Japanese
government, especially professor Atsushi Inaba and his team.
References[1] MTEC. Thai National LCI Database. http://
thailcidatabase.net/appadmin/db_lci.php/(Accessed
29.08.2014).
[2] Department of Alternative Energy Development andEfficiency, Ministry of Energy. Alternative Energy
Development Plan (AEDP) 2012-2021, 2012.
[3] United Nations. System of Environmental-Economic
Accounting 2012- Central Framework. 2014.

�������������������������������������������������

29E2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

102

Thai CF Pro: a Web-based Program for Evaluating Carbon Footprint of Product
Chantana Yuvaniyama,*1 Wanwisa Thanungkano,1 Ruthairat Wisansuwannakorn,1 Athiwatr Jirajariyavech,1
Thepchai Supnithi,2 Nattapol Kritsuthikul,2 and Thumrongrut Mungcharoen,31National Metal and Materials Technology Center, Thailand; 2 National Electronics and Computer Technology Center,
Thailand; 3 National Science and Technology Development Agency, Thailand*Corresponding author: chantany@mtec.or.th

1. Introduction
Global warming resulted from emissions of excessive
greenhouse gases (GHGs) is a matter of great concern forhumanity nowadays. Various measures to raise public
participation for GHG reduction have been promoted globally
including the use of carbon footprint labels [1]. In 2009,
National Metal and Materials Technology Center (MTEC) incollaboration with Thailand Greenhouse Gas Management
Organization (Public Organization) or TGO have carried out
the development of Carbon Footprint of Products (CFP) in
Thailand [2]. Since then, Thai CFP label has gained
popularity among Thai industries. However, to support theseclients especially SMEs for CFP analysis, an effective CFP
calculation tool is in strong demand. As a result, a new
web-based program called Thai CF Pro has been developed toease users for self-calculated CFP.
2. Features
Thai CF Pro is a web-based tool for evaluating the GHG
emissions accumulated during the life cycle of a product in aunit of carbon dioxide equivalent (CO2-eq). The program wasdeveloped using Drupal version 7.14 — an open-source
content management system (CMS) [3]. Thai CF Pro has been
designed to fulfill various functions as follows: It is free of charge, and can be accessible over the internet
as shown in Figure 1. However, an account registrationis required for each user before using the program.
 It operates with an individual user authentication systemfor data security.
 It can handle virtually any production processes, even withthe highly complicated ones.
 It provides built-in Thai Emission Factor (EF) databases,
mainly derived from Thai National Life Cycle Inventory
database and announced on the website of TGO every 6-12
months [4]. In addition, users can input their own EF tocustomize their databases. Thai EF consider emissions of
the six main GHGs covered by the Kyoto Protocol [5].
 It also offers automatic unit conversions which can
reduce human errors in the CFP calculation process.
 Flow Diagram can be automatically created from thelife cycle inventory database added by a user.
 Analysis results can be output as Table, Graph, and Picture(“.png” file), and exported as Microsoft Excel “.xls” file forpreparation of a CFP report as shown in Figure 2.

Figure 1. The first page of Thai CF Pro Website

Figure 2. Analysis results by Thai CF Pro can be output as
Table, Graph, and Flow Diagram
3. Results and Conclusion
Thai CF Pro was one of National Science andTechnology Development Agency (NSTDA) Flagships in2012. It has been well accepted and wildly used since the firstlaunch to public. As of September 2014, there were 3,403 visitsfrom 1,792 unique visitors to the Thai CF Pro website. Over
400 of these people were registered users working forgovernmental, industrial, or academic sectors. Their main usesof the program were for evaluation of CFP and for conducting
research and development projects in the related areas.
Moreover, Thai CF Pro has been used for teaching of
CFP evaluation in the LCA class at the Faculty of Environment
and Resource Studies, Mahasarakham University located in thenortheastern Thailand. The program benefits not only thestudents for their better understanding of the subject, but also the
Faculty for financial saving on expensive commercial software.
Thai CF Pro is free, and can be accessible at the following
URLs: http://www.thaicfpro.in.th or http://www.mtec.or.th.
However, it is now available only in Thai language.
Acknowledgments
This work has been financially supported by MTEC.
References[1] Santitaweeroek, Y. (ed.) Identifying NSTDA research anddevelopment direction in Carbon Footprint. Final report,
NSTDA, Thailand, 2010.
[2] TGO. Carbon Footprint. http://thaicarbonlabel.tgo.or.th/carbonfootprint/ (Accessed 09.09.2014).
[3] OpenSourceCMS.com. Drupal 7.14: Demo & Information.
http://www.opensourcecms.com/scripts/details.php?script
id=191 (Accessed 09.09.2014).
[4] TGO. Carbon Footprint: Emission Factor. http://thaicarbon
label.tgo.or.th/carbonfootprint/index.php?page=9(Accessed 09.09.2014).
[5] The United Nations Framework Convention on Climate
Change. Kyoto Protocol. http://unfccc.int/kyoto_protocol/items/3145.php (Accessed 09.09.2014).

�������������������������������������������������

29E2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan103

Visualization of Comprehensive Environmental Impacts
Yoshinori Kobayashi*, Kiyoshi Sanehira
Toshiba Corporation, Japan* yoshinori.kobayashi@toshiba.co.jp
1. Introduction
Recently, various framework related to life cycle
management have been proposed and discussed globally. For
example, environmental footprint in Europe has been discussed,
in which environmental impacts throughout life cycle will becompared based on a multi-criteria, meaning, not only
greenhouse gas  emissions but also other environmental
burdens should be quantified and compared. So it is essential todevelop practical life cycle impact assessment (LCIA) method
and establish a communication system with stakeholders basedon LCA results.
In this paper, we will introduce a new concept to visualize
the comprehensive environmental impact according to theglobal new trends mentioned above.
2. Concept
The new concept “T-COMPASS” has been introduced as
Toshiba Group’s compass for its environmental activities. It
defines four domains for the group's environmental
contributions and represents these domains as the symbols of
the four cardinal compass points. The four points are 1)
Reducing natural resource consumption (N; North), 2)
Reducing energy consumption and greenhouse gas emissions(E; East), 3) Minimizing water consumption (W; West), and 4)
Minimizing the risks involved in chemical substances (S;South).

Figure.1 T-COMPASSOne of the features is to provide a visualization of life
cycle impact assessment results. The unique radar chart isintroduced in order to visualize the carbon, water andenvironmental footprint comprehensively and complicated
LCIA results visualized with the several set of charts can beinterpreted for especially non-experts. In addition to typicalenvironmental indicators in the four major domains, otherindicators are also defined in detail (up to eight or twelve
points on the compass). Since highly relevant environmental
indicators are arranged appropriately along different axes, theradar chart depicts the structure of life cycle impact
assessments in a simplified way.
In addition, different environmental indicators are used for
different regions in order to appropriately assess local
environmental impacts, such as air pollution and water
degradation. A global COMPASS system should be establishedto improve environmental impacts by reflecting the regional
characteristics around the world.
3. Case Study
Environmental footprint of Toshiba group was evaluatedas shown in Figure.1. Environmental impacts in the fourdomains were quantified to identify hot spots. Environmental
burdens of its activities were quantified from life-cycle
perspective, combining environmental performance data ingroup sites with product LCA and environmental accounting.
Since energy-saving in use phase has been increasing, energy
consumption, greenhouse gas emissions and other emissions
have been decreasing. On the other hand, wood consumption
from product packaging has increased. 3R of not only products
but also their packaging should be improved. Various measures
to enhance our environmental management with respect toproducts and manufacturing will be introduced based on theevaluation.
4. Conclusion
In this paper, the new concept for visualizing
environmental impacts has been introduced. This concept isthought to be useful to understand and/or communicate the
LCA studies among non-experts for LCA. It makes it possible
to advance and expand an environmental management inindustries. We have a plan to advance the method and apply tovarious businesses in Toshiba group.

Figure.2 T-COMPASS Chart of Toshiba Group Environmental Footprint�������������������������������������������������

29E3-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

104

Life cycle assessment of environmental impacts of crop residue management and manure application in Japanese ricecultivation
Ai Leon, Yasuhito Shirato, Shin-ichi Yoshimatsu, Seiya Tsushima, Kazuyuki Yagi, Kazunori Kohyama
National Institute for Agro-Environmental Sciences, Japan*Corresponding author: kohyama@affrc.go.jp
1. Introduction
Agriculture in Asia covers more than 90% of the world’s
cultivated wetlands [1]. Increasing rice grain yields while
maintaining or improving soil fertility and reducing
environmental loads is a key to feed the rapidly increasing
population in this area.
Applying crop residue or manure is a management practicethat reduces soil erosion and mitigates climate change, byincreasing soil carbon (C) which is an essential property forsoil fertility. However, this practice will increase the nitrous
oxide, nitrogen oxides, and ammonia emissions, and nitrateleaching. Moreover, it will also increase methane (CH4)emissions in paddy soils [2]. Accordingly, benefits of C input
through crop residue and manure will be offset against the
global warming, acidification and eutrophication.
Few previous studies included soil C sequestration into
their analyses when calculating the environmental impacts ofrice cultivation. This study aims to compare the environmental
impacts (global warming, acidification, and eutrophication) ofdiffering scenarios in crop residue management and compost
application while taking account of soil C sequestration.
2. Materials and Methods
The LCA approach is applied to rice cultivations toevaluate the following four scenarios: rice straw incorporation
without application of compost (Scenario 1); rice straw
removal without application of compost (Scenario 2); ricestraw removal with 10 Mg ha-1 of fresh compost application(Scenario 3), and rice straw removal with 20 Mg ha-1 of freshcompost application (Scenario 4). The Rothamsted Carbon
model (Roth-C) was modified for paddy soils [2]. A web-based
Roth-C model is now available in the following web page tosimulate soil C sequestration: http://soilco2.dc.affrc.go.jp. The
soil C sequestration is estimated, assuming that the systemreaches a new equilibrium after a 20 year time period. For thegreenhouse gas emission calculation, global warming
potentials were fixed for a 100 year time horizon: CO2 : CH4:
N2O = 1 : 34 : 298 [3]. For the acidification calculation,
SO2-equivalent factors were used for NO2=0.506 andNH3=1.598 [4]. For the eutrophication calculation, PO4
equivalent factors were used for T-N=0.42, T-P=3.06 and
COD=0.022 [4].
3. Results
Of the scenarios examined in this study, Scenario 4 has thesmallest impact on GHG emissions (Table 1), owing to thegreatest soil C sequestration, while it has the greatest impact on
acidification and eutrophication. Despite having the greatest
CH4 emission, GHG emissions in Scenario 1 are the same as
those in Scenario 2, while Scenario 1 has the smallest impact
on acidification.
After the 20 years, when atmospheric CO2 is no longer
sequestered, total GHG emissions are the lowest in Scenario 2(Table 1) and the largest with Scenarios 1 and 4.
4. Discussion
Due to a greater CH4 emission, it has been recommended

Table 1 Impact of different scenarios on climate change,
acidification and eutrophication
Scenario 1 Scenario 2 Scenario 3 Scenario 4
Agricultural machinery (a)Paddy soils (b)GHG emissions(M g CO2 eq. ha-1 yr-1) Soil C sequestration (C)
Total
Agricultural machinery
Acidification
Fertilizer/Compost(kg SOx eq. ha-1 yr-1)
Total
Eutrophication(kg PO4 eq. ha-1)

Total

N2O emission
CH4 emission
1-20 year (a+b-c)> 20 year (a+b)

0.9
0.5
6.1
1.1
6.3
7.4

1.1
0.2
3.7
-1.2
6.3
5.1

1.1
0.4
4.7
0.7
5.6
6.2

1.2
0.6
5.6
2.6
4.8
7.4

3.8

5.1

5.4

5.6

3.4
7.2

3.4
8.6

6.5
11.9

9.5
15.2

12.4

12.4

20.9

29.5

not to incorporate rice straw residue into paddy fields [5].
In contrast to such recommendation, the present study,
which considered soil C sequestration, found that rice straw
residue incorporation (Scenario 1) is not the worst scenario.
Soil C sequestration is one of the crucial technologies toreduce the atmospheric CO2 as a provisional step until newtechnologies are developed and implemented [6]. However,once soils reach a new equilibrium, the same management must
continue to maintain the equilibrium soil C [6]. Thus, GHGs
are continuously emitted, while no soil C is sequestered.
Therefore, in the long-term, Scenario 2 seems to be a better
management. However, a reduction of soil C for the first 20
years implies a reduction of rice yield [7], and of chemical,
biological and physical properties [8], which in turn will
hamper feeding the rapidly increasing population in the world.
Conclusions
This study explored the influences of differing scenariosof crop residue management and compost application on
climate change. By taking account of the soil C sequestration,
Scenario 1 seems a promising strategy since it is better
environmental performance than scenario 2 in terms of
acidification, and than Scenarios 3 and 4 in terms of both
eutrophication and acidification. Moreover, it is the mostcommon management over the last decades in Japanese paddy
fields.
References[1] Papademetriou et al. Bridging the rice yield gap in the
Asia-Pacific region. FAO, Regional Office for Asia andthe Pacific, 2000.
[2] Shirato, Y. and M. Yokozawa. Soil Sci Plant Nutr 51:
405-415, 2005.
[3] Stocker, T.F. et al. Climate Change 2013: The PhysicalScience Basis. Contribution of Working Group I to theFifth Assessment Report of the Intergovernmental Panelon Climate Change, 2013.
[4] Heijungs, R. et al. Environmental life cycle assessments, A
manual, 1992
[5] Koga, N. and R. Tajima. J Environ Manage 92: 967-973,
2011[6]Smith, P. Eur J Agron 20: 229-236, 2004.
[7] Lal , R. Science 304: 1623-1627, 2004.
[8] Lu, F. et al. Glob Change Biol 15: 281-305, 2009.

�������������������������������������������������

29E3-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

105

Total Material Requirement of Food Production and Related Materials in Japan
Eiji Yamasue,*1 Kazuyo Matsubae,2 and Keiichi N Ishihara1
1
Kyoto University, Japan; 2Tohoku University, Japan*Corresponding author: yamasue@energy.kyoto-u.ac.jp

1. Introduction
Increase in food productivity is an urgent issue in order tocope with population growth, and therefore, for example,
fertilizing to supplement three major nutrients is indispensable
in modern agriculture. Not only fertilizers but also agriculturalchemicals are important substances for agricultural industry.
Further, fishery, livestock industry and dairy farming also
require various material and energy inputs for their products.
National Institute for Agro-Environmental science [1]reported life cycle assessments applied to agricultural industry.
Such the detailed inventory data contributed to LCCO2
analyses. However, it should be noted that although CO2emission by common soil input is thought to be relatively low,such the activities definitely disturb environment at source.
Matsubae et al. proposed a concept of “virtual phosphorusore” and evaluated the amount of phosphorus ore required forfood production in Japan [2]. The concept of virtual
phosphorus ore is important because it can quantify impact that
LCCO2 analysis does not provide. Total material requirement(TMR) can be thought of as an extended concept of virtual
phosphorus ore in terms of land use, since TMR includes not
only direct and indirect material flows upstream of the process,but also hidden material flows, such as overburden and waste
rock [3].
Although it is important to evaluate global warming interms of CO2 emission, the amount of land use as an initialsource of resource utilization should not be ignored. Sincemany of the inputs for food production consist of various
mineral components, they are expected to require great deal ofland use, but no quantitative evaluation has been reported thus
far. Thus, the aim of present study is to estimate and evaluate
TMR of food production.
2. Method
In this abstract, the preliminarily estimated results forsome crop production, meats, fishes, and beverages will beshown. Paddy rice, tomato, cabbage, wheat, potato, sweet
potato, radish (daikon), orange, pear, beet, green tea leaf, silage,
early-harvested maize, beef, squid, saury, salmon, tuna fish, tapwater, some juices, milk, soy milk, and etc were chosen as
targets. Functional unit was 1 kg of target fertilizer production.
System boundary was set as from mining to fertilizer
production and all the direct and indirect inputs, and hidden
flows such as tailings and waste rocks were considered, while
any treatments of tailings such as de-toxification were regarded
as being out of the system boundary.
Inventory data for crop production by National Institutefor Agro-Environmental science were used. Authors havealready reported the specific TMR value of various fertilizers.
Specific TMRs of agricultural chemicals were estimated fromthe report by Kimura and Sugimoto.
3. Results and discussion
Figure 1 shows the results of estimation. The TMR of crop
production range from 1.2 to 7 kg/kg, while fishery from 4 to
30 kg/kg. The TMR of beef is roughly estimated to be about
130 kg/kg. The TMR of milk is 2.6 kg/kg and that of soy milk
is about half of milk.

Figure 1. The TMR of crop production in Japan.
In case of crop production, large proportions of total TMR are
inputs ascribed to fertilizer and agricultural chemicals, and insome crops, inputs due to soil and energy occupy cannot be
negligible.
6. Conclusion
In this study, the TMR of various food production were
estimated. large proportions of total TMR are inputs ascribed tofertilizer and agricultural chemicals, and in some crops, inputs
due to soil and energy occupy cannot be negligible. These
results will be compared with LCCO2 for respective foods.
Acknowledgments
This study has been partly supported by research funds
from Nihonseimei-Zaidan, Arai Science and Technology
Foundation and from the Research Institute of Science andTechnology for Society of Japan Science and Technology
Agency, (JST-RISTEX) as a research program on Science of
Science, Technology and Innovation Policy.
References[1] National Institute for Agro-Environmental science Life
Cycle Assessment for Environmentally Sustainable
Agriculture:2003
http://www.niaes.affrc.go.jp/project/lca(Accessed
01.09.2014)[2] Matsubae, K., J. Kajiyama, T. Hiraki, and T. Nagasaka.
Chemosphere 84(6): 767–772, 2011.
[3] Wuppertal Institute. Mineral Intensity Factors: Overview
on materials, fuels, transport services and food.
http://wupperinst.org/uploads/tx_wupperinst/MIT_2014.p
df (Accessed 01.09.2014)�������������������������������������������������

29E3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

106

Land use change related CO2 emissions in the LCA of biofuel-based electrification in Mali
Joana Almeida1, Jeroen Degerickx1, Wouter MJ Achten2 and Bart Muys1
1

KU Leuven, Belgium; 2Université libre de Bruxelles, Belgium*Corresponding author: bart.muys@ees.kuleuven.be

1. Introduction and objectives
As with other renewable energy sources, bioenergy is
expected to have lower GHG emissions than fossil energy,
hence decreasing greenhouse gas (GHG) concentrations in theatmosphere. This assertion has been disputed on the grounds
that, albeit emitting less GHG during the life cycle, bioenergy
may have higher net emissions if land use change (LUC) is
included in the life cycle assessments (LCA) [1].
In this study, we perform the cradle-to-cradle LCA of
Jatropha oil-based electricity in Koulikoro, Mali. This analysis
abandons the classical carbon neutrality assumption by
including CO2 fluxes of sequestration/release cycles in biomass
and soil; and tailpipe emissions. Two direct LUC scenarios areevaluated, i.e. Jatropha establishment on former cropland or
fallow land. We estimated the life cycle GHG emissions inannual time steps. Carbon stock changes in soil and biomass
were amortized over a 20 year rotation time.
2. Methodology
System boundaries include the production of inputs to thesystem and direct emissions from fertilization and exhausts. The
LCA model was parameterized with direct observations and datafrom literature, ecoinvent® v2.2 (Ecoinvent Center,
Switzerland) and GREET 2013 (Argonne National Laboratory,
USA). Due to high variability in Jatropha yields in the region, ayield of 1 ton ha-1 estimated by Trabucco et al. (2010) was used
as a proxy [2,3]. Allocation to byproducts was avoided throughsystem boundary expansion by including fertilizer and glycerol
as the functional equivalents of seed cake and crude glycerine.
The Global Warming Potential (GWP) was calculated with
IPCC’s Fourth Assessment Report GWP’s for 100 years. The
functional unit is 1 MJ of electricity generated from oil.
In order to estimate CO2 emissions triggered by LUC,
changes in C stocks in biomass and soil were estimated between
Jatropha plantations and previous land uses. A negative
difference was considered to be an emission. Biomass C stocks
in cropland and fallow land in Koulikoro are based on fieldmeasurements [4]. Jatropha biomass C stocks were extracted
from literature [5], whereas the SOC content was modeled with
RothC. RothC was run with litterfall and climatological datafrom literature, starting from soil characteristics measured in thefield under fallow land and cropland conditions [6].
3. Results and discussion
The generation of 1 MJ electrical energy emits 0.48 kg CO2
eq if Jatropha replaces cropland, and 1.43 kg CO2 eq if fallow
land is converted (Figure 1). This difference is mainly driven by
LUC. In fact, LUC is responsible for 58% to 86% of emissions(conversion of cropland and fallow respectively), mainly due tosoil C loss over the years. This explains why cropland results innearly 200% lower GWP, owing to lower initial biomass andsoil C stocks which are lost.
Other relevant emission sources are N2O release frommanure application (11% to 33%) and electricity supply to theconversion facilities (3% to 9%). The remaining inputs to thesystem have a negligible contribution to GHG emissions.
Fossil diesel–based electricity emits 0.29 kg CO2 eq MJ-1.
Although at par with Jatropha-based electricity when direct

LUC is excluded, that figure is 1.7 to 4.9 times lower than when
all biogenic emissions are taken into account. This comparison
illustrates the relevance of LUC-related emissions for the LCA
of biofuels as a tool to show their validity as a climate change
mitigation practice.

Figure 1. GWP of Jatropha-based electrification in Koulikoro
when the plantations are established on fallow land or cropland.
The stacked bars represent the main contributors to the GWP.
Acknowledgments
Joana Almeida holds a doctoral grant from the Foundationfor Science and Technology – Portugal and a travel grant fromthe Research Foundation – Flanders. Field data was collectedwith a VLIR-UOS travel grant of Jeroen Degerickx, under the
auspices of the Jatrophability project, supported by Agricultural
Research for Development – Dimension of the European
Research Area and the Belgian Development Cooperation
coordinated by the Royal Museum for Central Africa.
References[1] Searchinger, T. et al., Use of U.S. Croplands for Biofuels
Increases Greenhouse Gases Through Emissions fromLand-Use Change. Science 319 (5867), 1238-1240, 2008.
[2] Almeida, J. et al., Time explicit global warming potentialof Jatropha biofuel production in Mali. In: Fulfilling LCA's
Promise - Proceedings from the LCA XIII International
Conference, October 1-3 2013, Orlando, FL, United States
68-77, 2013.
[3] Trabucco, A. et al., Global mapping of Jatropha curcas
yield based on response of fitness to present and futureclimate. GCB Bioenergy, 2 (3), 139-151, 2010.
[4] Vervoort, L. Carbon stock in biomass of Jatropha curcas
plantations for the production of biodiesel in Mali. KU
Leuven, Leuven, 2012.
[5] Achten, W.M.J. et al., Global greenhouse gas implicationsof land conversion to biofuel crop cultivation in arid andsemi-arid lands - Lessons learned from Jatropha. Journalof Arid Environment, 98, 135-145, 2013.
[6] Degerickx, J., Soil carbon sequestration and land use
impact of Jatropha curcas cultivation for the production of
biodiesel in Mali. KU Leuven, Leuven, 2012.

�������������������������������������������������

29E3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan107

Eco-efficiency analysis of integrated and non-integrated crop, forestry and livestock
production systems in the Brazilian Cerrado
Marcela P. Costa1,2, Sueli A. Oliveira1, and Gerson A. de Medeiros2
1

Fundação Espaço ECO, BASF SA; 2Universidade Estadual Paulista Julio de Mesquita Filho*Corresponding author: cmarcelaporto@gmail.com

1.

Introduction

Despite the importance of Brazil as an exporter ofagricultural and livestock products, the country has aconsiderable extension of low yield, degraded pasture land
(Figure 1).

3. Methodology
The method used was the Eco-efficiency Analysis tool (EEA)
developed by BASF SE, which consists on the economic andenvironmental life cycle assessment.
4. Results

Eco-efficiency Matrix
The most eco-efficient alternatives are positioned on the
top right of the matrix.

Figure 1. Actual Brazilian landscape – Mha = millions of hectares.

Technical improvement has been achieved aimed atrecovering degraded pastures through integrated systems which
consist on planting forage concomitant with a grain crop (CLi)and the possibility of planting tree species along spaced lines(CLFi).

LCA Indicators of Environmental Impacts

Figure 2 and 3.(2) CLi System (Harvesting)(3):CLFi System(Pasture after crop + Forest)

When the crop is harvested, the forage and the residues of
the crop generate a fresh pasture (Figure 2), livestock grazing in
the dry season (Figure 4). The forest component can promote
thermal comfort for the cattle, increasing weight gain.

5. Conclusion
The combinations using more expressive amounts of
CLFi system followed by CLi system presented themost eco-efficient results in comparison with theconventional systems.

Figure 4:Land Use in different systems in Brazilian Cerrado.
2.

Objective

Evaluate the eco-efficiency of five different combinations ofagricultural (soy, corn, sorghum), forest (eucalyptus for energy
supply) and cattle production systems, in order to meet the needsof 500 people in Brazil, in a period of seven years.

The most significant environmental advantages ofadopting these integrated systems were on energy use,emissions and land use parameters.
The impacts of costs on the integrated systems arelower due to the higher yields.
References
AIDAR, H.; KLUTHCOUSKI, J. Evolução das atividades lavoureira e pecuária nos Cerrados. In: KLUTHCOUSKI, J.; STONE, L.F.; AIDAR, H.
(Ed.).Integração lavoura-pecuária. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2003. p.25-58
ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. Gestão Ambiental – Avaliação do Ciclo de Vida – Princípios e Estrutura. Rio de Janeiro:ABNT,
2009. (NBR ISO 14040)
ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. Gestão Ambiental – Avaliação do Ciclo de Vida – Requisitos e Orientações. Rio de Janeiro:
ABNT, 2009. (NBR ISO 14044).
BALBINO, Luiz Carlos et al . Evolução tecnológica e arranjos produtivos de sistemas de integração lavoura -pecuária-floresta no Brasil. Pesq. agropec.
bras., Brasília, v. 46, n. 10, Oct. 2011b
BASF – Fundação Espaço ECO. Metodologias de Ecoeficiência. Estudo realizado pela TÜV Anlagentechnik em setembro de 2001
Figure1 : redeagro.org.br/
Figure 3: Available on: http://ruralcentro.uol.com.br/noticias/mulheres-no-campo-marize-costa-sistema-ilpf-54526#y=2559

�������������������������������������������������

29F1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan108

How much does Urban Mining reduce the environmental burden?
Kohmei Halada,*1
1National Institute for Material Science, Japan*Corresponding author: HALADA.Kohmei@nims.go.jp

1. Introduction
The potential of urban mining to reduce the environmental
burden is discussed. Reduction of resource-view weight,
namely TMR (Total material requirement), and CO2 emission
in processing are estimated for the potential of urban mining.
2. Procedure
Recycling has following three roles; 1) reduction of
burden of acquisition of resources from the Eco-sphere, 2)
reduction of burden to reassign waste to the Eco-sphere,
reduction of 3) reduction of burden through the life stage in
the Techno-sphere. In this work, reduction of resource-view
weight is subjected as a parameter for the burden of acquisition.
Reduction of CO2 emission through life-cycle is selected as arepresentative parameter through life stage in techno-sphere.
While these two parameters are well established already[1], theparameter of reassign waste to eco-sphere has not been
discussed. Newly developed parameter, waste-TMR, isintroduced. Waste-TMR is the amount of soil which dilutewasted elements into acceptable concentration of eco-sphere.
The acceptable concentration is estimated by the log-log
relation of crust concentration with common soil
concentrations of major elements and restriction concentrationsof hazardous elements. These parameters are listed in the
Table1.
3. Results and Discussion
The effects of recycling in Japan are analyzed with thesethree parameters for annual production and consumption of
metals. The black part of each column is the reduction effect bypractical recycling, obtained by comparing the practicalmaterial flow with the material which would be required if it is
not recycled. The gray part means the difficult portion forrecycling by reason of no-use in Japan and that of
inappropriateness of application or composition for recycling.
Then, the white part is the reduction potential of environmental

burden by recycling.
Fe has reduced the burden by recycling already, and has
further potential in TMR and CO2 emission. Pb has also
reduced the burden and has further potential in waste-TMR. Cu
has further potential in these three area. On the other hand,
REE, which gives relatively higher burden, has less potential
because of the difficulty of recycling.
References[1] Halada,K & Katagiri,N: Proc. Int. Conf. EcoBalance
2010
X100,000

X10,000

X1,000

X100

Figure 1 Effect of recycling in Japan on TMR

X1,000

X10

X100

Table 1 Environmental stresses of metals
㻟 㻸㼕
㻠 㻮㼑
㻡㻮
㻝㻞 㻹㼓
㻝㻟 㻭㼘
㻝㻠 㻿㼕
㻞㻜 㻯㼍
㻞㻝 㻿㼏
㻞㻞 㼀㼕
㻞㻟 㼂
㻞㻠 㻯㼞
㻞㻡 㻹㼚
㻞㻢 㻲㼑
㻞㻣 㻯㼛
㻞㻤 㻺㼕
㻞㻥 㻯㼡
㻟㻜 㼆㼚
㻟㻝 㻳㼍
㻟㻞 㻳㼑
㻟㻟 㻭㼟
㻟㻠 㻿㼑
㻟㻣 㻾㼎
㻟㻤 㻿㼞
㻟㻥 㼅
㻠㻜 㼆㼞
㻠㻝 㻺㼎
㻠㻞 㻹㼛
㻠㻠 㻾㼡
㻠㻡 㻾㼔
㻠㻢 㻼㼐
㻠㻣 㻭㼓
㻠㻤 㻯㼐
㻠㻥 㻵㼚

㻯㻻㻞
㼀㻹㻾㻌㼏㼛㼑㼒㼒㻚 㼣㼍㼟㼠㼑㻙㼀㻹㻾㼠㻯㻻㻞㻛㼠㻹㼑㼠㼍㼘㻙㻛㻙㻝㻚㻥㻱㻗㻜㻝
㻝㻚㻡㻱㻗㻜㻟
㻞㻚㻠㻱㻗㻜㻠
㻣㻚㻠㻱㻗㻜㻝
㻞㻚㻡㻱㻗㻜㻟
㻝㻚㻟㻱㻗㻜㻡
㻢㻚㻜㻱㻗㻜㻝
㻝㻚㻠㻱㻗㻜㻞
㻡㻚㻠㻱㻗㻜㻠
㻣㻚㻞㻱㻗㻜㻜
㻣㻚㻝㻱㻗㻜㻝
㻟㻚㻢㻱㻗㻜㻞
㻥㻚㻞㻱㻗㻜㻜
㻠㻚㻤㻱㻗㻜㻝
㻝㻚㻠㻱㻗㻜㻞
㻣㻚㻞㻱㻗㻜㻜
㻟㻚㻠㻱㻗㻜㻝
㻢㻚㻜㻱㻗㻜㻝
㻠㻚㻤㻱㻗㻜㻝
㻥㻚㻜㻱㻗㻜㻝
㻟㻚㻡㻱㻗㻜㻞
㻞㻚㻟㻱㻗㻜㻝
㻞㻚㻜㻱㻗㻜㻟
㻥㻚㻝㻱㻗㻜㻠
㻢㻚㻥㻱㻗㻜㻜
㻟㻚㻢㻱㻗㻜㻝
㻝㻚㻥㻱㻗㻜㻟
㻞㻚㻡㻱㻗㻜㻝
㻝㻚㻡㻱㻗㻜㻟
㻞㻚㻢㻱㻗㻜㻠
㻣㻚㻥㻱㻗㻜㻜
㻞㻚㻢㻱㻗㻜㻝
㻟㻚㻟㻱㻗㻜㻠
㻞㻚㻤㻱㻗㻜㻜
㻝㻚㻠㻱㻗㻜㻝
㻢㻚㻢㻱㻗㻜㻟
㻤㻚㻠㻱㻙㻜㻝
㻤㻚㻞㻱㻗㻜㻜
㻟㻚㻡㻱㻗㻜㻞
㻝㻚㻡㻱㻗㻜㻝
㻢㻚㻝㻱㻗㻜㻞
㻥㻚㻤㻱㻗㻜㻠
㻤㻚㻞㻱㻗㻜㻜
㻞㻚㻢㻱㻗㻜㻞
㻠㻚㻡㻱㻗㻜㻠
㻟㻚㻡㻱㻗㻜㻜
㻟㻚㻢㻱㻗㻜㻞
㻡㻚㻥㻱㻗㻜㻠
㻞㻚㻤㻱㻗㻜㻜
㻟㻚㻢㻱㻗㻜㻝
㻡㻚㻝㻱㻗㻜㻠
㻞㻚㻢㻱㻗㻜㻝
㻣㻚㻟㻱㻗㻜㻟
㻝㻚㻤㻱㻗㻜㻡
㻟㻚㻣㻱㻗㻜㻜
㻟㻚㻞㻱㻗㻜㻠
㻥㻚㻤㻱㻗㻜㻡
㻞㻚㻥㻱㻗㻜㻝
㻤㻚㻢㻱㻗㻜㻡
㻞㻚㻟㻱㻗㻜㻜
㻠㻚㻡㻱㻗㻜㻞
㻝㻚㻡㻱㻗㻜㻣
㻝㻚㻥㻱㻗㻜㻜
㻝㻚㻟㻱㻗㻜㻞
㻡㻚㻝㻱㻗㻜㻠
㻣㻚㻥㻱㻗㻜㻜
㻡㻚㻝㻱㻗㻜㻞
㻝㻚㻥㻱㻗㻜㻠
㻝㻚㻝㻱㻗㻜㻝
㻞㻚㻣㻱㻗㻜㻟
㻝㻚㻝㻱㻗㻜㻡
㻞㻚㻡㻱㻗㻜㻜
㻡㻚㻡㻱㻗㻜㻞
㻟㻚㻠㻱㻗㻜㻠
㻞㻚㻠㻱㻗㻜㻝
㻢㻚㻠㻱㻗㻜㻞
㻝㻚㻤㻱㻗㻜㻡
㻝㻚㻡㻱㻗㻜㻝
㻣㻚㻡㻱㻗㻜㻞
㻝㻚㻞㻱㻗㻜㻢
㻝㻚㻢㻱㻗㻜㻞
㻣㻚㻥㻱㻗㻜㻠
㻡㻚㻜㻱㻗㻜㻣
㻝㻚㻝㻱㻗㻜㻟
㻞㻚㻟㻱㻗㻜㻢
㻤㻚㻟㻱㻗㻜㻣
㻟㻚㻟㻱㻗㻜㻞
㻤㻚㻝㻱㻗㻜㻡
㻡㻚㻜㻱㻗㻜㻣
㻠㻚㻡㻱㻗㻜㻜
㻠㻚㻤㻱㻗㻜㻟
㻝㻚㻞㻱㻗㻜㻣
㻠㻚㻝㻱㻗㻜㻜
㻢㻚㻤㻱㻗㻜㻝
㻡㻚㻠㻱㻗㻜㻢
㻞㻚㻟㻱㻗㻜㻜
㻝㻚㻞㻱㻗㻜㻠
㻥㻚㻜㻱㻗㻜㻢

㻯㻻㻞㼀㻹㻾㻌㼏㼛㼑㼒㼒㻚 㼣㼍㼟㼠㼑㻙㼀㻹㻾㼠㻯㻻㻞㻛㼠㻹㼑㼠㼍㼘
㻙㻛㻙
㻙㻛㻙
㻡㻜 㻿㼚
㻡㻚㻝㻱㻗㻜㻜
㻞㻚㻡㻱㻗㻜㻟
㻥㻚㻤㻱㻗㻜㻡㻡㻝 㻿㼎㻡㻚㻞㻱㻙㻜㻝
㻡㻚㻢㻱㻗㻜㻝
㻡㻚㻠㻱㻗㻜㻢㻡㻞 㼀㼑㻞㻚㻥㻱㻙㻜㻝
㻝㻚㻜㻱㻗㻜㻠
㻡㻚㻜㻱㻗㻜㻣㻡㻡 㻯㼟㻝㻚㻝㻱㻗㻜㻝
㻥㻚㻤㻱㻗㻜㻡㻡㻢 㻮㼍㻠㻚㻢㻱㻗㻜㻜
㻡㻚㻝㻱㻗㻜㻞
㻞㻚㻟㻱㻗㻜㻠㻡㻣 㻸㼍㻞㻚㻢㻱㻗㻜㻞
㻤㻚㻞㻱㻗㻜㻟
㻝㻚㻣㻱㻗㻜㻡㻡㻤 㻯㼑㻡㻚㻣㻱㻗㻜㻞
㻝㻚㻤㻱㻗㻜㻠
㻝㻚㻜㻱㻗㻜㻡㻡㻥 㻼㼞㻞㻚㻡㻱㻗㻜㻞
㻣㻚㻥㻱㻗㻜㻟
㻠㻚㻠㻱㻗㻜㻡㻢㻜 㻺㼐㻟㻚㻤㻱㻗㻜㻞
㻝㻚㻞㻱㻗㻜㻠
㻝㻚㻤㻱㻗㻜㻡㻢㻞 㻿㼙㻠㻚㻥㻱㻗㻜㻞
㻝㻚㻢㻱㻗㻜㻠
㻡㻚㻥㻱㻗㻜㻡㻢㻟 㻱㼡㻝㻚㻝㻱㻗㻜㻟
㻟㻚㻟㻱㻗㻜㻠
㻝㻚㻥㻱㻗㻜㻢㻢㻠 㻳㼐㻡㻚㻟㻱㻗㻜㻞
㻝㻚㻣㻱㻗㻜㻠
㻢㻚㻡㻱㻗㻜㻡㻢㻡 㼀㼎㻝㻚㻣㻱㻗㻜㻟
㻡㻚㻡㻱㻗㻜㻠
㻞㻚㻣㻱㻗㻜㻢㻢㻢 㻰㼥㻡㻚㻝㻱㻗㻜㻞
㻝㻚㻢㻱㻗㻜㻠
㻣㻚㻟㻱㻗㻜㻡㻢㻣 㻴㼛㻥㻚㻠㻱㻗㻜㻞
㻟㻚㻜㻱㻗㻜㻠
㻞㻚㻝㻱㻗㻜㻢㻢㻤 㻱㼞㻝㻚㻜㻱㻗㻜㻟
㻝㻚㻞㻱㻗㻜㻠
㻝㻚㻝㻱㻗㻜㻢㻢㻥 㼀㼙㻝㻚㻜㻱㻗㻜㻟
㻟㻚㻞㻱㻗㻜㻠
㻠㻚㻜㻱㻗㻜㻢㻣㻜 㼅㼎㻝㻚㻜㻱㻗㻜㻟
㻟㻚㻞㻱㻗㻜㻠
㻝㻚㻝㻱㻗㻜㻢㻣㻝 㻸㼡㻝㻚㻜㻱㻗㻜㻟
㻟㻚㻞㻱㻗㻜㻠
㻠㻚㻜㻱㻗㻜㻢㻣㻞 㻴㼒㻝㻚㻟㻱㻗㻜㻝
㻝㻚㻜㻱㻗㻜㻠
㻥㻚㻤㻱㻗㻜㻡㻣㻟 㼀㼍㻝㻚㻢㻱㻗㻜㻝
㻢㻚㻤㻱㻗㻜㻟
㻝㻚㻢㻱㻗㻜㻢㻣㻠 㼃㻝㻚㻥㻱㻗㻜㻜
㻝㻚㻥㻱㻗㻜㻞
㻝㻚㻥㻱㻗㻜㻢㻣㻡 㻾㼑㻞㻚㻜㻱㻗㻜㻜
㻝㻚㻤㻱㻗㻜㻠
㻤㻚㻟㻱㻗㻜㻣㻣㻢 㻻㼟㻥㻚㻡㻱㻗㻜㻞
㻡㻚㻠㻱㻗㻜㻡
㻤㻚㻟㻱㻗㻜㻣㻣㻣 㻵㼞㻟㻚㻥㻱㻗㻜㻞
㻠㻚㻜㻱㻗㻜㻡
㻤㻚㻟㻱㻗㻜㻣㻣㻤 㻼㼠㻥㻚㻜㻱㻗㻜㻞
㻡㻚㻟㻱㻗㻜㻡
㻤㻚㻟㻱㻗㻜㻣㻣㻥 㻭㼡㻡㻚㻝㻱㻗㻜㻞
㻝㻚㻝㻱㻗㻜㻢
㻝㻚㻢㻱㻗㻜㻤㻤㻜 㻴㼓㻞㻚㻜㻱㻗㻜㻟
㻝㻚㻤㻱㻗㻜㻣㻤㻝 㼀㼘㻝㻚㻟㻱㻗㻜㻝
㻠㻚㻟㻱㻗㻜㻞
㻡㻚㻠㻱㻗㻜㻢㻤㻞 㻼㼎㻟㻚㻠㻱㻗㻜㻜
㻞㻚㻤㻱㻗㻜㻝
㻠㻚㻠㻱㻗㻜㻡㻤㻟 㻮㼕㻡㻚㻟㻱㻙㻜㻝
㻞㻚㻞㻱㻗㻜㻞
㻥㻚㻜㻱㻗㻜㻢㻥㻞 㼁㻞㻚㻜㻱㻗㻜㻜
㻞㻚㻞㻱㻗㻜㻠

Figure 2 Effect of recycling in Japan on CO2 emission
X10,000,000

X1,000,000

X100,000

X10,000

Figure 3 Effect of recycling in Japan on waste-TMR�������������������������������������������������

29F1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan109

Designing Strategic Urban Mining in Japan for Criticality Mitigation
Hiroki Hatayama,*1 Kiyotaka Tahara,1 and Ichiro Daigo2
1 National Institute of Advanced Industrial Science and Technology, Japan; 2The University of Tokyo, Japan*Corresponding author: h-hatayama@aist.go.jp

1. Introduction
Highly-developed industrial activities in Japan have beenfounded on a massive amount of metal consumption.
Meanwhile, a large part of the metal supply is depending on theimport from foreign countries. Therefore, Japan’s governments
and industries have been giving much importance on a securityof metal resources. As mentioned in the governmental resource
securement strategy, both common and minor metals arerecognized to have a high criticality for Japan [1]. As well as areinforcement of mineral supply from abroad, reducing
dependence on imported metals by substitution and recycling
are also recognized as the significant measures for criticality
mitigation. All of these measures are more or less effective;
however, adequate combination between mitigation measuresand target metals should be explored in constructing along-term resource strategy. The goal of this study is torepresent how the effectiveness of recycling on criticality
mitigation differs among metals and how it will change infuture.
2. Methodology
Recovery from end-of-life products should be enhanced
for metals that meet the following conditions:(1) There is a high risk in supplying necessary amount ofmetals to the domestic industries.
(2) Mineral demand can largely be reduced by recycling
promotion.
One possible index for representing the first point is a
criticality score that integrates several sub-scores provided tovarious criticality components such as production
concentration and future demand growth. The index that
represents the second point could be evaluated from acomparison between the amount of metal demand and discard
which are provided by substance flow analysis (SFA).
The effectiveness of recycling promotion in the future will
be affected by the change in metal demand and discard. As well,criticality of metals would change in the future in tandem withincrease/decrease in geological reserves, metal demands, prices
and so forth. The transition can be illustrated as 3D chart
shown in Fig.1. Some measures to mitigate criticality should betaken for the metals placed at the left side in Fig.1. For metals
placed at the upper left, recycling promotion becomes one of
the significant measures for criticality mitigation. Conversely,
recycling cannot fully mitigate the criticality when metals areat the bottom left area. For these metals, other measures suchas substitution must be rather effective.
Seeing the snapshot in the present year, a necessity forsecuring resources is relatively small for the metal placed at thebottom right area. However, criticality of the metal could risein the future. At the same time, potential of urban mining may
also increase due to the spread of products containing metal.
By depicting the time change of the position in the Fig.1,
effective timing for developing urban-mining technologies
would be indicated. Furthermore, cross-metal evaluation cansuggest the comprehensive strategy for domestic recycling andresource management.

Japan’s criticality assessment was done by NEDO in 2009,
where the criticality of 39 minor metals were evaluated [2].
However, common metals like steel and copper, which are also
designated as “strategic minerals” in Japan’s resource strategy[1], were not focused on. On the other hand, there have notbeen enough dynamic SFA studies for minor metals. To build
the chart in Fig.1 for Japan, we conducted the criticality
assessment and dynamic SFA of several common and minor
metals. The method of criticality assessment basically followed
the NEDO approach, but a criticality component that represents
the sufficiency of resource entitlements [3] were additionallyconsidered.
3. Summary of the Results
The results of criticality assessment and dynamic SFA are
presented by 2030 for several metals e.g. steel, aluminum,
copper, lead, cobalt, tantalum, dysprosium. etc. As with NEDO
assessment in 2009, our criticality assessment also show highcriticality scores for minor metals like indium and dysprosium
under the conditions prevailing in 2012. Furthermore, ourassessment clarified that the criticality of steel and somecommon metals are nearly at high level compared to minor
metals. The results of criticality assessment and SFA led to thesuggestion of metals that recycling should be promoted at thepresent situation. Furthermore, adequate measures in the futurewere also indicated based on the dynamic analysis.
References[1] Prime Minister of Japan and His Cabinet. Resource
securement strategies.
http://www.kantei.go.jp/jp/singi/package/dai15/sankou01.
pdf (Accessed 07.09.2014)[2] New Energy and Industrial Technology Development
Organization (NEDO). Trend Report of Development inMaterials for Substitution of Scarce Metals. 2009.
[3] Hatayama, H, et al. Abstract for the 9th ILCAJ Meeting:312-313, 2014.

Figure 1. Conceptual chart for long-term strategy of urban
mining.

�������������������������������������������������

29F1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan110

Comparison of End-of-Life Recycling Rates of Common Metals in Japan
Ichiro Daigo *1, Kohei Iwata 1 and Yoshikazu Goto 1
1

Graduate School of Engineering, The University of Tokyo, Japan*Corresponding author: daigo@material.t.u-tokyo.ac.jp

1. Introduction
Material recycling is a measure to conserve natural
resources. An efficiency of material recycling from recovered
end-of-life products can be evaluated by end-of-life recycling
rate (EoL-RR). The EoL-RR has been defined in the reportfrom International Resource Panel, UNEP[1], i.e. the amountof recycled EoL materials divided by the amount of thematerials contained in discarded EoL products. In addition,
significance of evaluating EoL-RR has been pointe out by
Reck and Graedel[2]. Several EoL-RRs for specific regions in
specific time points could be obtained by results of MFA
studies[1]. On the other hand, time-series change of EoL-RR
has not been evaluated, except for the case of aluminum in the
U.S. [3]. Furthermore, EoL-RRs have not been comparedamong different materials due to a lack of availability on flux
in recycling chain[2], especially due to difficulty of observing
the denominator of the rate.
The goal of this study is to estimate time-series EoL-RRs
on the basis of the same definition and calculation method andcompare them.
2. Methodology
In this study, we focused on recycling of six metallic
materials; such as steel, aluminum, copper, austenitic stainlesssteel, ferritic stainless steel and zinc in galvanized steel inJapan. In general, it is difficult to estimate the amount of thematerials contained in discarded EoL products. A possible
method to estimate the amount is a dynamic material flow
analysis (dMFA) which requires lifetime distributions of
products. The lifetime distributions adopted in the previous
studies employing dMFA were generally constant over time
due to insufficient information on chronological change of the
lifetime. In order to reduce uncertainties of estimated EoL-RRs,time-series change of products’ lifetime distribution wasinvestigated. Time-series change of lifetime distribution could
be obtained for automobiles and buildings, which account for
more than a half of consumption in every metal evaluated here.
Time-series change of lifetime for other end uses have beenremained as a factor of uncertainty in the results.
Using the lifetime for each end use and time-series
consumption for each end use in the past, the time-series
EoL-RRs were estimated. The numerators of the rates, i.e. theamount of recycled obsolete scrap, were estimated by
combination of some statistics. Due to restriction of data
availability, the numbers of end uses classified for six metals
are different as shown in table 1.
3. Results and Discussions
Estimated EoL-RRs for the six metals are shown in figure
1. EoL-RRs have been changed over time in quite large ranges;
25, 52, 53, 40, 47 and 35 %-points for steel, aluminum, copper,
austenitic stainless steel, ferritic stainless steel and zinc,respectively. At least during the evaluated period, EoL-RR ofsteel has been the highest in almost every year, followed bycopper and austenitic stainless steel. EoL-RRs for steel, copperand stainless steels indicated relatively high values during theyear 2005 to 2008, which is considered due to high prices ofresources which include scraps of the metals. This results are inagreement with the results on aluminum in the U.S. reported byChen[3]. Especially, the rates for steel, copper and austenitic
stainless steel exceeded more than 100%. Even if the results
would have uncertainties to some extent, the results implies
that a certain amount of disused metals can remain in
anthroposphere as hibernating stock[4] during a period in low
metal prices and will be drawn to the market in high metal
prices. Our results might be the first evidence which indirectly
observe the phenomena of hibernation from a macroscopic
view. On the other hand, chronological changes of EoL-RRs ofaluminum and zinc have no relation with prices of those metals.
In spite of the same material to ref.[3], the relations with prices
were different in Japan and the U.S.
Table 1. Data used for estimation on EoL-RRs
MetalsNumber of end uses
Steel
11
Aluminum
11
Copper6
Austenitic stainless steel
10
Ferritic stainless steel
10
Zinc in galvanized steel
11

Figure 1. Time-series change of EoL-RRs for the six metals inJapanAcknowledgments

The research was partially funded by MEXT/JSPS
KAKENHI Grant Numbers 22686084. The authors
gratefully acknowledge industrial associations relevant tothe six evaluated metals.
References[1] UNEP. Recycling Rates of Metals - A Status Report, A
Report of the Working Group on the Global Metal Flows
to the International Resource Panel. Graedel, T.E.,
Allwood J., Birat J.-P., Reck, B.K., Sibley, S.F.,
Sonnemann, G., 2011.
[2] Reck, B.K. and Graedel, T.E. Challenges in metal
recycling: Science 337(6095): 690-695, 2012.
[3] Chen, W-Q. Recycling Rates of Aluminum in the UnitedStates: Journal of Industrial Ecology 17(6): 926-938,
2013.
[4] Brunner, P.H. In search for the final sink. Environmental
Science & Pollution Research. 6(1): 1, 1999�������������������������������������������������

29F1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

111

Framework and Applications of Time-Series Material Flow and Stock Analysis
Shotaro Nakanishi,*1 Jun Nakatani,1 and Yuichi Moriguchi1
1University of Tokyo, Japan*Corresponding author: nakanishi@env.t.u-tokyo.ac.jp

1. Introduction
It is considered that many fixed capital in Japan will
become superannuated in several decades. At the same time,
aging and depopulation will progress in the nation. These two
conditions make the nation manage superannuated fixed capitalwith decreasing social vitality. Therefore, the information on
future fixed capital is important. Murakami et al. [1] states thatthe number of studies using material flow and stock analysis
has increased, however few researchers study about social
overhead capital (SOC), namely, infrastructure. Moreover,most studies have not focused on both SOC and durable goods,
such as cars and machineries.
The objective of this study is to develop a framework andcomprehensive database of fixed capital, which contributes
material flow and stock management in Japan.
2. Method
We used the Japanese Input-Output Tables (IOT) from1990 to 2005 [2] as basic datasets. We calculated
type inverse matrix from input tables with original 105 sectors,
and defined these tables as [-]. We rearranged value andquantity tables with the 105 sectors, divided them by domestic
production, and defined them as[ton/million yen]. We
rearranged fixed capital matrixes with the 105 sectors, anddefined them as[million yen]. Finally, we defined as
lifespan curve of each fixed capital as in Table 1.
Table 1. Lifespan curve of fixed capital [3]Fixed capital
Type of function, parameter
Machinery
Weibull, m=2.9, μ=10
Construction (wooden)
log-normal, μ=3.7, σ=0.6
Construction (nonwooden)
Weibull, m=14, σ=-112.4
Civil engineering structurenormal, μ=70, σ=4.8
Othersnormal, μ=5, σ=1.3
Using these matrixes, we calculatedof each fixed capital stock in Japan.

, the amount(1)

where, denotes final demand sectors of fixed capital,
denotes the types of fixed capital,
denotes the types ofintermediate input, anddenotes the types of material.
denotes the year of manufacture of fixed capital, anddenotes the year of observation. Using Equation 1, we
calculated, gross stock of fixed capital.
(2)
where,
denotes the oldest year of manufacturing. In
general,should be sufficiently older than .
3. Result and Discussion
Figure 1 shows the fixed capital input of the 4year when
IOTs exist. Compared with the estimation of the White Paper[4], our value was 40% larger in 1990, but became a close
value in other years. Because the demand of mineral was
overestimated in 1990, we should review matrixes. Figure 2
shows the fixed capital stock, and Figure 3 shows the obsolete

Figure 1.Produced fixed capital

Figure 2.Stocked fixed capital (produced in 1990-2005)

Figure 3. Obsolete fixed capital (produced in 1990-2005)

Figure 4. The legend of Figure 2 and 3,
fixed capital. Figure 2 and 3 used the 15-years input dataobtained from the result of Figure 1 with interpolation. Figure
3 shows that the type and amount of capital was significantly
different depending on the .
4. Conclusion
This study developed the framework that contributes tomaterial stock and flow management in Japan. Input, stock andoutput of fixed capital, produced from 1990 to 2005 were
estimated. To improve the utility of the framework, we have to
use older data, and estimate future input.
Acknowledgments
This research was supported by the Environment Research
and Technology Development Fund (1-1402) of the Ministry of
the Environment, Japan.
References[1] Murakami, S., et al. Int. J. LCA 6(2): 76–87, 2010.
[2] Statistics Bureau. Input-Output Tables for Japan.
http://www.stat.go.jp/ data/io/ (Accessed 10.09.2014)[3] Hashimoto, S., et al. Proc. 6th International Conference on
Ecobalance, 193-196, 2004
[4] Ministry of Environment. White Paper.
http://www.env.go.jp/en/wpaper/ (Accessed 10.09.2014)�������������������������������������������������

29F2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

112

Value added Material Flow Analysis of NdFeB magnets in Denmark
Komal Habib,*1 and Henrik Wenzel1
1

University of Southern Denmark. Niels Bohrs Alle 1, DK-5230, Odense M, Denmark.
*Corresponding author: koh@kbm.sdu.dk

1. Introduction
Neodymium-iron-boron (NdFeB) magnets have become
highly desirable for modern high-tech applications. Thesemagnets contain two key Rare Earth Elements (REEs) i.e.
neodymium (Nd) and dysprosium (Dy), which are consideredas critical resources by a number of governing bodies including
the European Commission. These magnets are used in products
ranging from electricity generators and medical equipment to
the household appliances and personal care products [1, 2].
This study is aimed at mapping the stocks and flows of Nd
and Dy contained in the NdFeB magnets in Denmark, where
the reference year is 2012.
2. Methods
In order to estimate the in-use stocks of NdFeB magnets in
Denmark, both top-down and bottom-up approaches are used[3]. The inflow of these magnets to Denmark in the form ofmagnetic alloy or finished goods is estimated based on tradeand sales statistics [4-8]. To know the NdFeB magnets
composition for various products, a total of 157 different
electronic products representing 7 various product categories
were dismantled. After dismantling, the NdFeB magnets weretaken out to perform the elemental analysis with the help of
Electron Dispersive X-ray spectroscopy (EDX) system toreveal their composition. For the products which could not bedismantled e.g., home appliances, data regarding the magnet
weight and composition was collected from leading NdFeB
magnet and final product manufacturers.
3. Results
Our results show that in 2012, nearly 975 Mg of NdFeB
magnets were imported to Denmark, either contained in theend-use products such as Information Technology (IT)applications or in the form of magnetic alloy to be further usedin finished goods. This value corresponds to almost 283 Mg of
Nd and 17 Mg of Dy. The largest import category is windturbines, which alone represents almost half of the total NdFeB
magnets import to Denmark in 2012. The remaining half of theimports comprise passenger vehicles, home appliances, IT &telecommunication products, medical equipment such as
Magnetic Resonance Imaging (MRI) machines, personal careproducts, industrial motors and circulator pumps. Figure 1
presents the simplified results for the Material Flow Analysis(MFA) of NdFeB magnets in Denmark in 2012.

Figure 1. MFA of NdFeB magnets for Denmark (2012)

The results further reveal that the in-use stocks of NdFeB
magnets in Denmark are approximately 5000 Mg, whichcorresponds to 1400 Mg of Nd and 100 Mg of Dy. Nearly 38%of the in-use stocks of NdFeB magnets are contained in thewind turbines, followed by home appliances (28%) andpassenger vehicles (18%). The remaining 16% of the in-use
stocks of NdFeB magnets consist of IT & telecommunication
products, personal care products, medical appliances andothers.
Our estimates show that in 2012, only 10 Mg of NdFeB
magnets appeared in the Danish waste stream. This
corresponded to almost 3 Mg of Nd and 0.2 Mg of Dy. The
dominant category is IT & telecommunication which represents
nearly 65% of total NdFeB magnets appearing in the waste,followed by MRI machines (35%).
The estimated amount of NdFeB magnets appearing in thewaste stream (10 Mg) is quite low compared to what was
imported to Denmark (975 Mg) in 2012. This is mainly
because of the long lifetimes of key end-use products such as
wind turbines (25 years) and passenger vehicles (16 years) etc.
4. Conclusion
The NdFeB magnets are currently not recycled in
Denmark to recover the critical resources i.e. Nd and Dy
contained in them. This is primarily because of the challenges
attached to isolate the small amount of magnets contained in alarge variety of end-of-life products found in waste flows,
making their efficient recovery unattractive at the moment
considering the economic feasibility.
Acknowledgments
We acknowledge the TOPWASTE (www.topwaste.dk) and
the REEgain (www.reegain.dk) projects for providing us theopportunity to carry out this research.
References[1] Habib, K., Schibye, P.K., Vestbø, A.P., Dall, O.L., andWenzel, H. Material Flow Analysis of NdFeB magnets for
Denmark: A comprehensive waste flow sampling andanalysis approach. Environmental Science & Technology
2014. DOI: 10.1021/es501975y.
[2] European Commission. Report on critical raw materials
for the EU: Report of the Ad hoc working group on
defining critical raw materials. 2014.
[3] Müller, E., Hilty, L. M., Widmer, R.., Schluep, M., andFaulstich, M. Modeling Metal Stocks and Flows: A
Review of Dynamic Material Flow Analysis Methods.
Environmental Science & Technology 2014, 48,
2102-2113.
[4] UN Comtrade. Commodity search database: HS 850511,
2014. (Accessed January 13, 2014).
[5] UN Comtrade. Commodity search database: HS 850519,
2014. (Accessed March 21, 2014).
[6] Euromonitor International. Mobile Phones in Denmark,2013.
[7] Euromonitor International. Computers and peripherals in
Denmark, 2013.
[8] Euromonitor International. Consumer appliances inDenmark, 2013.

�������������������������������������������������

29F2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan113

Ultra-High Temperature Materials for Higher-Efficiency Energy Conversion
of Heat Engines
Kyosuke Yoshimi
Tohoku University, Japan
yoshimi@material.tohoku.ac.jp
1. Introduction
Since the Great Eastern Japan Earthquake on March 11th,
2011, the world has reaffirmed the significance of energy
conversion by heat engines. High-temperature andhigh-strength materials are one of the most important
technological components in achieving more efficient heatengines and attaining more stable energy supplies. Basically,
the hotter the operating temperature of heat engines is, thebetter its energy conversion efficiency is improved [1].
Unfortunately, the operating temperature of the heat engines
such as gas turbines and jet engines exceeds the melting pointof nickel-base superalloys which are a main and key
heat-resistant material in the engine system, and thus theirenergy conversion efficiency has almost peaked these days. If
the nickel-base superalloys are replaced with betterheat-resistant materials, the efficiency will be dramatically
improved.
In this paper, the current situation of the engines is briefly
reviewed. And then, their future prospects are discussed
involving ultra-high temperature materials such as SiC/SiC
composites (CMC), Ti-based alloys and Mosibtic alloy whichhave been developed in our recent project.
2. Current situation of the energy conversion efficiency ofgas turbines and jet engines.
To improve the energy conversion efficiency of the heatengines, gas pressure in compressor and turbine inlet
temperature are increasing with development. The turbine inlet
temperature of a land-based gas turbine for power generation
has reached approx. 1600°C [1]. However, as Perepezko
pointed out [2], the deviation of the specific core power ofactual equipment from the ideal performance has becomelarger with increase in turbine inlet temperature (Figure 1). It
has been considered that the inefficiency losses are induced bycooling system in turbine blades since the system enhancesinternal stress due to stress concentration. Weight reduction is
one of the ways to solve the trade-off problem. The other way
is to enhance the heat-resistant properties of the turbine bladesby replacing nickel-base superalloys with ultra-hightemperature materials.

Figure 1. Specific core power output of gas turbines vs. turbine
inlet temperature reported by Perepezko [2].

3. Novel ultra-high temperature of TiC-added Mo-Si-B
alloys beyond nickel-base superalloys
Mo-Si-B-based alloys are a leading candidate forultrahigh-temperature materials available above the operating
temperature of nickel-base superalloys because of their highmelting point, excellent high-temperature (creep) strength andmoderate oxidation resistance in the ultrahigh temperature
range [2–4]. However, as these alloys have a higher density
than nickel-base superalloys and poor room-temperature
fracture toughness [5], their practical use is limited. To
improve the physical properties of Mo-Si-B-based alloys,
attempts have been made to include a fourth element andcontrol their microstructure.
We recently developed novel TiC-added Mo-Si-B alloys
using a conventional arc-melting technique. Through theprocess, fine microstructures of three- and four-component
eutectic phases such as Moss + Mo5SiB2 (T2) + (Ti,Mo)C +(Mo,Ti)2C, Moss + T2 + (Ti,Mo)C, and Moss + T2 + (Mo,Ti)2C
with a primary phase of Moss, T2 or (Ti,Mo)C depending on thecomposition are created [6]. The density reduces to ≤9.0 g/cm3
as a result of the TiC addition, even though the volume fractionof Moss is over 60%. Alloys containing an elongated coarse T2
primary phase has low deformability at 1400 °C, whereas
alloys containing a Moss or TiC primary phase has good
deformability and high strength of 800 MPa at 1400 °C alongwith a strain rate of 2.1 × 10-4 s-1. TiC-added Mo-Si-B-based
alloys thus have a high potential to be used as
ultrahigh-temperature materials.
Acknowledgments
This work was supported by the funding program for Next
Generation World-Leading Researchers (NEXT Program) (No.
GR017) and the Advanced Low Carbon Technology Researchand Development (ALCA) Program of the Japan Science andTechnology Agency (JST).
References[1] https://www.mhi.co.jp/news/story/0903124805.html[2] Perepezko, J.H., The Hotter the Engine, the Better.
Science 326: 1068–1069, 2009.
[3] Yoshimi, K., Nakatani, S., Suda, T., Hanada, S.,
Habazaki, H., Oxidation behavior of Mo5SiB2-based
alloy at elevated temperatures. Intermetallics 10: 407–414,
2002.
[4] Yoshimi, K., Nakatani, S., Nomura, N., Hanada, S.,
Thermal expansion, strength and oxidation resistance of
Mo/Mo5SiB2 in-situ composites at elevated temperatures.
Intermetallics 11: 787–794, 2003.
[5] Lemberg, J.A., and Ritchie, R.O., Mo-Si-B Alloys for
Ultrahigh-Temperature Structural Applications. Advanced
Materials 24: 3445–3480, 2012.
[6] Miyamoto, S., Yoshimi, K., Ha, S.H., Kaneko, T.,
Nakamura, J., Sato, T., Maruyama, K., Tu, R., and Goto,
T., Phase Equilibria, Microstructure, and High
-Temperature Strength of TiC-Added Mo-Si-B Alloys.
Metallurgical and Materials Transactions A 45A:
1112–1123, 2014.

�������������������������������������������������

29F2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

114

Advanced Green Innovation Discovered by Self-healing Ceramics
Wataru Nakao
1
Yokohama National University, Japan*Corresponding author: wnakao@ynu.ac.jp

1. Introduction of fiber reinforced self-healing ceramics
Self-healing is the capability (or function) for material torestore autonomically the damage, similarly as the living thing,
thereby adapting the function to the materials for structural andmechanical use gives rise to the huge enhancement in its
lifetime and reliability. The self-healing materials for structuraland mechanical use usually include the healing agent whichacts as adhesives to re-bond the crack surfaces, because theself-healing target should be the cracks. The healing agent isflowed into the space between the cracks at the crack initiationand propagation, thereby reacts at the crack surface to re-bondthe crack surfaces.
Oxide based fiber reinforced self-healing ceramiccomposite (shFRC) developed by the present authors has
human bone-like structure (Figure 1), which consists of oxidefiber bundles, oxide matrix and non-oxide interlayer.
Especially non-oxide interlayer is most important andcharacteristic consistent. Crack initiation and propagation
allows the non-oxide interlayer react with the oxygen in thesurrounding atmosphere, and then the formed oxide and thereaction heat bond the branched crack. Furthermore, theinterlayer possesses the function to branch the crack
propagation. The crack branching leads to the huge resistanceto crack propagation and the conducts the crack to the healing
agent. Due to these functions, shFRC can exhibit the highself-healing ability.

resistance of ceramic materials is quite low so that the cracks
introduced by the excessive load propagate to the opposite sidein an instant. Therefore, the life time of ceramic components is
exhausted abruptly by generating of excessive load. Similarly
silicon carbide based fiber reinforced ceramics reach the final
fracture by repeating the excessive loads although thecomposites have the high fracture resistance. On the other hand,
shFRC can autonomically recover the strength degraded by theexcessive load, so that one can use the shFRC components withhigh mechanical reliability until the self-healing capability is
exhausted.

Figure 2 Time dependent deterioration in strength offiber-reinforced self-healing ceramic

Figure 1 Schematic of fiber-reinforced self-healing ceramics
2. Most attractive feature of shFRC
The life time of shFRC can be considered to be the sametime-dependent type (Fig. 2) as metal material, although thelife time of the ordinary ceramics must be considered to take
into consideration the probability of occurrence of excessive
load. Ceramic materials, which are well-known as brittle
materials, are easily fractured by the excessive loads due tocrush of foreign objects and thermal shock. The fracture

3. Environmental effects
Large green innovation which is to develop an advanced
jet engine with ultrahigh fuel efficiency can be achieved byusing shFRC. The enhancement in fuel efficiency of jet engine
has been attained by the increment in the combustion gas
temperature (turbine inlet temperature) with the aids of theheat-resistant improvement in a base material as well as thedevelopment of cooling technology, such as adapting air
cooling blade and thermal barrier coating. Alternatively theincrement of the combustion gas temperature gives rise to theincrease in NOx concentration in combustion gas. Thus, it ishard to further increase the combustion gas temperature, basedon the view of environmental protection. If one substitutes the
shFRC turbine blade for the ordinary blade, the advanced jetengine with non-cooling of turbine blade and ~22% weight
reduction can be actualized. The advanced engine can exhibit~15% higher fuel efficiency than the latest jet engine, and thefuel efficiency enhancement corresponds to the reduction of theCO2 exhaust by half of the total CO2 emission equivalency of
our country.
shFRC possesses large potential to adapt many application
except turbine blade. The present author wishes that the readers
will be interested in the self-healing materials.

�������������������������������������������������

29F2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

115

Environmental Barrier Coating on SiC Fiber-Reinforced SiC Matrix Composites for Low
Pressure Turbine in Jet Engine
Hideki Kakisawa
The University of Tokyo, Japan
kakisawa@hyper.rcast.u-tokyo.ac.jp
1. Introduction
SiC fiber-reinforced SiC matrix composites (SiC/SiCs) are
the promising candidate structural materials for the hot sectionsin the next generation jet engines [1]. In dry oxygen
atmosphere, a protective SiO2 layer is formed on the SiC
surface preventing further oxidation. However, when the
SiO2 is exposed to water vapor in combustion gas, it reacts toform gaseous silicon hydroxide as [2]
SiO2 (s) + 2H2O (g) = Si(OH)4 (g).

(1)

This oxidation and the following volatilization in the
combustion environment cause weight loss of SiC which
decreases the lifetime. Thus environmental barrier coatings(EBCs) have been developed to protect the surface of SiC
based materials from such corrosive behaviors [3-5].
Mullite EBCs has been developed because of its hightemperature stability, coefficient of thermal expansion (CTE)close to SiC and chemical compatibility. Then for further
protection performance at higher temperatures, YSZ,
Ba1-xSrxAl2Si2O8 (BSAS) and rare earth silicates (RESi2O7 andRESiO5) (RE: rare earth element like Y, Sc and Yb) have been
considered as protective materials. However, mullite is still
an important material for lower temperature EBCs and for anintermediate layer material in BSAS EBCs.
In the EBCs, cracking through the coating thickness often
occur and reaches to the substrate. CTEs of most oxidematerials used for EBCs, including mullite, are larger than thatof SiC and thus in-plane tensile stress is induced in the coating
during cooling in the fabrication process and in service. The
thermal tensile stress reaches several hundred MPa at
maximum and causes mode I cracking across the coating14-15.
Such cracks through the thickness make paths of oxygen andwater vapor to the substrate, which may cause significant
damage of substrate materials.
In this study, to prevent cracking through the thickness
and to enhance the gas shielding properties, Al2O3 flake isdispersed in mullite EBC. Design of the flake-dispersed
structure is done for an inexpensive, damage tolerant andrepairable EBC and based on the design, Al2O3 flake-dispersed
mullite matrix composite coating is developed by sol-gel andslurry techniques.
2. Structural design
Crack propagation resistance through the coating thickness
was discussed in terms of the dimensionless cracking number,≡  √

(2)where σT is in-plane thermal stress, Kc is fracture resistance andh is coating thickness. The cracking number Ω is calculated
as a function of flake volume fraction and flake size. An
optimum structure for maximizing fracture resistance issuggested through the discussion.

3. Experimental procedure
Based on the structural design, Al2O3
flake-dispersed mullite matrix composite coating was
fabricated on SiC discs synthesized by melt infiltration process.
The disc was 12.7mm in diameter and 1.8 mm in thickness.
α-Al2O3 flake powder (Serath 10030, Kinsei Matec Co., Ltd.,
Osaka, Japan) was used as the dispersed flake material. It had
a nominal diameter of 10µm and a thickness of 300nm (aspectratio: 33). Raw material of mullite matrix was a mixture ofmullite powder (KM101, KCM Corporation Co., Ltd., Nagoya,Japan), Al2O3 sol and SiO2 sol. The Al2O3 flake powder andmullite powder were put in the mixture of Al2O3 and SiO2 solswith the ratio of 5.5:1.2:1 (sol mixture : flake powder : mullite
powder). The expected final volume fraction was ~30%.
The prepared slurries were coated on the SiC
substrate by doctor blade technique. The gap between the bladeedge and the substrate surface was set 200µm. The coatings
were dried in air for 24h and sintered with a tubular furnace at
1200 ͦC or 1400 ͦC for 2h in flowing N2 gas atmosphere with aheating rate of 2 ͦC/min. After the heating the coatings were
furnace cooled.
4. Results and discussion
The coating was bonded to the substrate throughthe drying, sintering and polishing process, although a partial
delamination was observed at the interface. The thickness ofthe coating was 64µm at 1200 ͦC and 59 µm at 1400 ͦC; they
were almost the same despite the difference of the sintering
temperature of 200 ͦC.
The flakes remained in the mullite matrix, keeping
a distinguishable interface without significant reaction or
diffusion. The flakes were aligned fairly parallel to thesubstrate surface by shear force induced by the blade in thecoating process. Pores of ~1-3µm were distributed mainly
between the flake planes. Cracks with opening displacementof ~2µm were propagated in the matrix and connected to thepores. The cracks were arrested at the pore or the interface
between the flake and matrix; no network of cracks and pores
seemed to make an open path from the surface to the substrate.
References
1. J. A. DiCarlo, “Advances in SiC/SiC Composites for
Aero-Propulsion,”
NASA
tech.
repts
NASA/TM-2013-217889, July 2013.
2. N.S. Jacobson, “Corrosion of Silicon-Based Ceramics in
Combustion Environments,” J. Am. Ceram. Soc., 76 [1]
3–28 (1993).
3. K.N. Lee, R.A. Miller, N.S. Jacobson, “New generation ofplasma-sprayed mullite coatings on silicon-carbide,” J.
Am. Ceram. Soc., 78 [3] 705–710 (1995).
4. K.N. Lee and R.A. Miller, “Development andenvironmental durability of mullite and mullite/YSZ dual
layer coatings for SiC and Si3N4 ceramics,” Surf. Coat.
Tech., 86–87 [1] 142–148 (1996).
5. K.N. Kee, “Current status of environmental barrier
coatings for Si-Based ceramics,” Surf. Coat. Tech., 133–
134 [11] 1–7 (2000).

�������������������������������������������������

29F3-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

116

Metal Recovery from Urban Mines by Hydrometallurgical Methods
Mikiya Tanaka*1, Hirokazu Narita1, Tetsuo Oishi1, Takeshi Ogata1, Yuiko Tasaki-Handa1, and Kazuya Koyama1,21National Institute of Advanced Industrial Science and Technology, (AIST), Japan; 2Chiba Institute of Technology, Japan*Corresponding author: mky-tanaka@aist.go.jp

log SF(Dy/Nd)

Extraction (%)

2. Recovery of rare earth elements from scrap magnets byan oxidative roasting - acid leaching - solvent extraction
process
Neodymium magnets, indispensable in electronic andelectric appliances, automobiles and other industrial products,
contain neodymium and a small amount of dysprosium as the
additive. Because no rare-earth metal resources exist in Japan,
exploration, stockpiling, and recycling should be promoted inorder to secure the stable supply of these rare-earth metals.
The hydrometallurgical route would be one option for the
neodymium magnet recycling, particularly, from the end-of-life
scrap of which the composition is rather diverse. For thehydrometallurgical process of neodymium magnet scrap, one
has to consider that iron amounts to more than 70 wt% of themagnet. When all the iron is dissolved in the acid, not only
excess acid, but also a significant amount of alkaline forneutralization of the leach solution are required, which would
be quite uneconomical.
From this viewpoint, we showed that the dissolution ofiron can be controlled, and, at the same time, rare-earth
elements can be efficiently dissolved by acid leaching at 453K
after oxidative roasting, in which both nickel and boron are
also dissolved [1].
A method to mutually separate dysprosium andneodymium from this selective leach solution using solvent
extraction was then investigated. A process using acidicorganophosphorous extractant is proposed on the basis of theexperimental data.
Figure 1 shows the effect of the equilibrium pH on thepercentage extraction of neodymium and dysprosium with 5
vol% PC88A (active component: 2-ethylhexylphosphonic acidmono-2-ethylhexyl ester) at the unit phase volume ratio. The
separation factor, SF(Dy/Nd), is also shown, where SF(Dy/Nd)
is
equal
to
100
3
D(Dy)/D(Nd)andlog SF(Dy/Nd)
80
2.8
D
is
the
Nd
distribution ratio
Dy
60
2.6
defined as theratio of the metal
40
2.4
concentration in
the organic phase20
2.2
to that in the0
aqueousphase.
2
From this figure,
0
0.5
1
1.5
2
pHeq
it is understoodthat dysprosium is
Figure 1. Effect of the equilibrium pH on
selectively
the extraction of neodymium andextracted at a pH
dysprosium by 5 vol% PC88A.
1 - 1.2.

3. Nickel recovery from spent electroless nickel plating
baths
Electroless nickel plating is now an important surface
finishing technology in many fields such as the electronic andautomobile industries. However, the treatment of the spentbaths is becoming a serious problem. We proposed a nickel
recovery process from the spent electroless nickel plating baths
using solvent extraction, where the impurity metal ions such asiron and zinc are initially removed by solvent extraction withacidic organophosphorous reagent and then the nickel in the
aqueous raffinate is separated by solvent extraction using achelatingextractant,
LIX84I(activecomponent:
2-hydroxy-5-nonylacetophenone oxime). The extracted nickel
is stripped with sulfuric acid in order to obtain nickel sulfate
which is reused in the plating process [2].
Recently, we have done some fundamental studies related
to the solvent extraction involved in this process. One of themis to study the effect of aqueous organic acid on the extraction
equilibrium of nickel. This is because the electroless nickel
plating baths contain considerable amounts of organic acids
such as lactic, malic, propionic, and succinic acids ascomplexants and buffers, and quantitative prediction isnecessary to predict the nickel extraction behavior in order todesign and control the process.
Figure 2 shows the log D values as a function of theequilibrium pH of the aqueous phase at various lactic acidconcentrations. The log D values monotonically increase with
pH and decrease with the lactic acid concentration.
Equilibrium
1.5
0.05
0
analysis revealed
Lactic Acid (mol/L)
1
0.1
that the decrease in
Calc.
0.2
0.5
log D with lactic
0.3
acid concentration0
is due to the-0.5masking
effectcausedbythe-1complexationof-1.5
nickel(II) ion withlactate anion. It was
-2
3
3.5
4
4.5
5
found that log 1 =pH
1.52 ± 0.12 and log
2 = 2.46 ± 0.12.
Figure 2. Extraction of nickel with
Here 1 and 2 are
LIX84I in the presence of lactic acidthe overall stability
at ionic strength of 1 mol/L.
constantsforNi-lactate and Ni-(lactate)2 complexes, respectively. Solid
curves in Figure 2 present the fitted values and are in good
agreement with the experimental data.
log D

1. Introduction
Recently the recovery of valuable metals from urban
mines is receiving more and more attention to stabilize their
supply chains. Hydrometallurgical processes, consisting ofleaching, purification, and metal winning, are suitable for fineseparation and small scale operation and have wide
applicability to the metal recovery from urban mines. In thispresentation, we will outline our studies on thehydrometallurgical processes and related unit operations.

eq

Acknowledgments
We are deeply indebted to NEDO and JOGMEC for theirfinancial supports.
References[1] Koyama, K., Kitajima A., Tanaka, M. Preprints of SCEJ
40th Autumn Meeting (Sendai, 2008), A320 (2008)[2] Tanaka, M., Huang, Y., Yahagi, T., Hossain, M. K., Sato, Y.,
Narita, H. Sep. Purif. Technol., 62, 97–102 (2008)�������������������������������������������������

29F3-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan117

Evaluation of novel processes for precious metals recovery using organic aqua regius
Kana Umehara, Akihiro Yoshimura and Yasunari Matsuno*
The University of Tokyo, Japan*Corresponding author: matsuno@material.t.u-tokyo.ac.jp
1. Introduction
The recovery of precious metals from secondary sources
like waste of electric and electronic equipments has received
much attention, and various recovery techniques have beendeveloped, e.g. pyrometallurgy, hydrometallurgy andbio-hydrometallurgy techniques. Among these methods, with
their relatively low capital cost, reduced environmental impact(e.g., no hazardous gases/dusts), potential for high metal
recoveries and suitability for small-scale applications,hydrometallurgical processes are recognized as promising
options for the treatment of secondary sources [1]. However,restrictions on waste disposal, safety concerns, and stringent
environmental regulations have motivated the further
development of economically, eco-friendly and fewer healthrisk technologies.
Therefore, we have developed a novel method for therecovery of gold using “organic aqua regius”: the leaching ofgold by dimethyl sulfoxide (DMSO) solutions containing
CuBr2 and precipitation by water [2]. We have also investigated
the use of a more environmentally benign solvent, Propylene
Carbonate (PC) with CuBr2 and KBr for leaching and recovery
of precious metals [3]. Our methods offer a number ofadvantages, including eco-friendliness, ease of operation, lowcost and the minimization of chemical sludge production.
2. Characteristics of the precious metals recovery usingorganic aqua regius
2.1 Leaching of precious metals
In the organic aqua regius, the high redox potentials of
precious metals are significantly lowered in the presence of
halogens and corresponding halides. In addition, copper (II)ions act as an oxidizing agent and are reduced to copper (I)ions by oxidizing precious metals. It was found that the
dissolution rate of gold is relatively large compared with thoseobtained with other leaching methods [2].
2.2 Recovery of precious metals
2.2.2 DMSO solutions with CuBr2 and KBr
DMSO solvates water in any concentration. The additionof water in DMSO solutions drastically changes the solution
characteristics, in particular resulting in high redox potentials
of gold in mixed solutions. So, water can be used for the
precipitation of gold. Furthermore, DMSO does not form anazeotrope with water and can be separated by distillation,
which enables the repeated use of the solutions (Fig. 1).
2.2.3 PC solutions with CuBr2 and KBr
When PC is used instead of DMSO, the dissolved Au andPd can be effectively separated from other metals by thebiphasic separation with sulfuric acid. Then the dissolved Au in
the PC solution can be recovered by reduction with ascorbic
acid, or calcination (Fig. 2).
3. Cost analysis and LCA
Preliminary cost analyses and LCA were conducted toevaluate the cost and CO2 emissions for the proposed system ofprecious metal recovery. Solvents (DMSO, PC), solutes (CuBr2
and KBr), energy required for the processes were taken into
account. The results will be presented in the session.

Acknowledgments
This work was supported by JSPS KAKENHI Grant
Number 25550067 and the Environment Research andTechnology Development Fund (3K133006) of the Ministry of
the Environment, Japan
References[1] Syed, S. Recovery of gold from secondary sources—A
review. Hydrometallurgy 115-116, 30-51, 2013.
[2] Yoshimura, A., Takai, M. and Matsuno, Y. Novel process
for recycling gold from secondary sources: Leaching ofgold by dimethyl sulfoxide solutions containing copper
bromide and precipitation with water. Hydrometallurgy
2014., DOI: 10.1016/j.hydromet.2014.08.003[3] Umehara, K., Yoshimura, A. and Matsuno, Y. Novel
recycling process of precious metals from secondary
sources using “organic liquor regius”. Proc. of Going
Green – CARE INNOVATION 2014, Vienna, 2014

Water
WEEE

Leaching ofgold by DMSO
with CuBr2

Separation by
distillation

Precipitation

Filtration

Water,
Sulfuric acid

Precious metals

Figure 1 Precious metal recovery system using DMOS
solutions with CuBr2

WEEE

Leaching ofgold by PC
with CuBr2
Biphasic
separation

Sulfuricacid

Precious metals(Au, Pd)
Reduction byascorbic acid,and filtration

PC to calcination
Sulfuric acid,other metals

Figure 2 Precious metal recovery system using PC solutions
with CuBr2

�������������������������������������������������

29F3-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan118

A recycling system for poly (methyl methacrylate) in Japan
Yasunori Kikuchi,*1 Masahiko Hirao,1 Hirokazu Sugiyam,1Stavros Papadokonstantakis,2 Konrad Hungerbühler,2 Takashi Ookubo,3 Akinobu Sasaki3
1The University of Tokyo, Japan;

2Swiss federal institute of technology (ETH) Zurich, Switzerland; 3 Mitsubishi Rayon, co., Ltd., Japan*Corresponding author: kikuchi@platinum.u-tokyo.ac.jp

1. Introduction
Recycling systems for highly functional plastics such aspoly (methyl methacrylate) (PMMA) have not been studied
sufficiently.
Along
with
the
popularizationofPMMA-containing products such as liquid crystal displays(LCDs), the use of PMMA is steadily increasing, which will
result in more waste of PMMA in the next decades.
In this study, pyrolysis process for recycling waste PMMA
into methyl methacrylate (MMA) monomer was examinedconsidering environmental impacts, chemical hazards andresource availability. We applied life cycle assessment (LCA),
environment, health, and safety (EHS) assessment as well as
material flow analysis (MFA) to the evaluation of the recycling
system as discussed in the previous researches [1, 2]. In thispaper, the statistical data is updated on the latest one [3] andfurther discussion regarding the scenario analyses of themultiple aspects of a process system is performed.
2. Materials and method
A process system has multiple aspects to be examined
carefully and designed through adequate analyses of them asshown in the center of Figure 1. Although their importance isdifferent on a case-by-case base, all aspects should be checkedby some methods. Especially for recycling system, theenvironmental performance and the feasibility of the collectionof waste with quality enough for utilized technology must be
examined. As an industrial process, the safety aspects must be
also taken into account in the decision making. Through theseanalyses, the process system for PMMA recycling is proposedin this study.
Based on the differences between PMMA grades and theirlife cycles, we developed a life cycle model and designed arange of scenarios for PMMA recycling. We obtained monomer
recycling process inventory data based on the operational
results of a pilot plant. Using this process inventory data, wequantified life cycle greenhouse gas (LC-GHG) emissions,fossil resource consumption, and the LIME single index.
Additionally, process EHS hazards assessment was conducted
to quantify the local effects of the PMMA monomer recycling
process. Besides the process hazard, the availability of waste
PMMA was quantified by analyzing the material flow ofPMMA-containing products. PMMA contained in LCDs as
light guide panels was selected as a feasible source of waste
PMMA and the quantity of PMMA flows in the society wasevaluated.
4. Results
Through scenario and sensitivity analyses, wedemonstrated that PMMA monomer recycling is more effective
than mechanical recycling on environmental impacts evaluatedby LCA. EHS hazard assessment results showed the lessprocess hazard of monomer recycling than the production of
fresh MMA from crude oil. The implementation of circulatedcooling water could significantly decrease the process hazard
in PMMA pyrolysis attributable to chemical hazards. MFA
revealed that the availability of waste PMMA shows afluctuating trend in the next 20 years because of the sharp peakdemand for LCD television sets around 2010. In fact, theshipment of television sets has been significantly decreased
after 2011 July, when the switch over to terrestrial digital
broadcasting was implemented.
EHS assessment

Life cycle assessment(LCA) Safer than any other
MMA production
processes

 Moreenvironmentallybenign than MR
 Enhancing
recycling effects
by increase ofyield despite
additional fuel use

PMMApyrolysis

 Decrease ofsafety hazard
by elimination of
circulation flow forcooling despiteslight increase ofenergy use forcooling water

Material flow analysis (MFA)
 Continuous PMMA waste by the spread of LCD panel About 10,000 ton-PMMA/y scale plant in maximum case

Figure 1. Analyses of multiple aspects of PMMA pyrolysis
6. Conclusion
Through the multiple analyses organized in Figure 1, thePMMA monomer recycling has a potential to achieve a
closed-loop recycling of PMMA reducing environmental
impacts with a less process hazards than fresh MMA
production from crude oil. The availability of waste PMMA
has a strong relationship with the lifetime of LCD television
sets. The multiple and comprehensive assessments can reveal
various aspects of a process technology.
Acknowledgments
A productive discussion on MFA with Dr. Ichiro Daigo isappreciated. Part of this study was supported by a grant-in-aid
for scientific research (B) (no. 23360404) and scientificresearch (A) (no. 24246150) from the Japan Society for the
Promotion of Science.
References[1] Kikuchi, Y., M. Hirao, T. Ookubo, and A. Sasaki, Designof Recycling System for Poly (Methyl Methacrylate)(PMMA) Part 1: Recycling Scenario Analysis,
International Journal of Life Cycle Assessment, 19(1):120-129, 2014.
[2] Kikuchi,
Y.,
M.
Hirao,
H.
Sugiyama,
S.
Papadokonstantakis, K. Hungerbühler, T. Ookubo, and A.
Sasaki, Design of recycling system for poly (methyl
methacrylate) (PMMA). Part 2: Process hazards andmaterial flow analysis, International Journal of Life
Cycle Assessment, 19(2): 307-319, 2014[3] Japan Electronics and Information Technology Industries
Association (JEITA) (2014) Statistics on domestic
shipments of major consumer electronic equipment.
http://www.jeita.or.jp/english/stat/index.htm. Accessed 10
September 2014�������������������������������������������������

29G1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

119

Life cycle assessment inventory of energy technologies – survey and application to energy
technologies
Andrew J. Chapman1, Benjamin C. McLellan*1, Tetsuo Tezuka 1
1Graduate School of Energy Science, Kyoto University, Japan*Corresponding author: b-mclellan@energy.kyoto-u.ac.jp

1. Introduction
In the context of future scenarios for energy systems, theoperational emissions from a given energy mix are typicallycited as the critical environmental criterion. By comparison,
when the comparative benefits of alternative technologies are
identified, the operational and construction-related emissions
are often accumulated into a levelised emissions rate (g CO2-eq/ kWh) across the lifecycle of the technology. The results ofsuch studies often indicate that low-carbon technologies may
not be as ideal as their operational impacts imply. Many LCA
studies have been produced – often with widely varying results
depending on the underlying assumptions utilized.
This study reviewed a wide range of LCA’s on energy
technologies, and identified important factors for harmonizing
alternative studies so that the results could be readily integrated
and later adapted to studies of different alternative energy
futures. The importance of this harmonization is to create acommon basis for comparison, and to thereby enablenon-identical conditions to be applied for scenario-building.
In this study, solar (PV), wind, nuclear, geothermal,hydropower and carbon capture and storage technologies werereviewed. Each study was analysed against a set of criteria
including: date of study; level of detail; and completeness, andthose studies not complying with the requirements were
eliminated. The final set of results was compared on an
as-presented basis as well as post-harmonisation.
2. Results
Table 1 shows the number of studies considered for eachtechnology, and the initial range (pre-harmonisation) of
alternative emissions intensities. These studies were selectedfrom a review of more than 300 studies, but only those capableof being adequately harmonized, recent and sufficiently
detailed were chosen. Geothermal and Carbon Capture andStorage (CCS) technologies were also examined, but notpresented due to lack of sufficient samples. Harmonisation wasundertaken using technology specific factors, particularly the
lifetime and capacity factor for most technologies.
Table 1. Technology un-harmonized emissions intensities
Emission
Final
intensity
Technology and types
accepted(g CO2-eq /studies
kWh)
Photovoltaics (Mono-Si, Poly-Si,
16 - 61
10
Cd-Te thin film)
Wind (Onshore, Offshore)
10
6 - 31Hydro(run-of-river,dam,
4 - 6108pumped-storage)
Nuclear10
7 - 527
The wide range of emissions intensity was particularly
apparent in the hydropower and nuclear power studies. In theformer, the contribution of power mix attributed to pumped
storage was the main factor that exacerbated the upper end of
the range. In the latter, the assumptions of ore grade, mining
and milling energy and mine decommissioning were the largest

factors. These are indicative of the challenges to appropriate
harmonization of the emissions factors. Further, harmonizedfactors were presented, and will be described in a full paper.
3. Discussion
Considering the wide disparity between the raw study
results for LCA-based emissions factors for global warming
potential, the alternative scenarios for sustainable energy
systems, and the optimization of such systems onlowest-emissions bases can be drastically altered. As shown in
Figure 1, the range of emissions that would be predicted underscenarios for the Japanese energy future would drasticallychange according to the emissions factors applied. Here we use
the emissions factors representing the maximum range for eachof the technologies surveyed (assuming that the renewableenergy technologies are used in equal proportion) to thescenarios of the Japanese government [1] tested by McLellan etal. [2]. The harmonized figures use the range considered mostrepresentative (with the elimination of extreme outliers in the
nuclear and hydropower cases).

Figure 1. Emissions ranges for Japan – 2030 scenarios(standard values from [2], LCE is the Life Cycle Emissions)
The important conclusions from Figure 1 are that the LCE
exacerbates the emissions of each scenario (as expected), but
the impact of increasing nuclear is to increase the uncertainty(range) in the emissions, due to the large range of emissions
intensities in the studies assessed.
Acknowledgments
This study was initiated as part of a project funded by the
Research Institute for Humanity and Nature and completed
under a JSPS Grant-in-Aid (No. 26701014).
References[1]
National Policy Unit. Options for Energy andEnvironment - The Energy and Environment Council Decision on June29, 2012 2012
[cited 2012 August 22nd]; Available from:http://www.sentakushi.go.jp/english/.
[2]
McLellan, B.C., et al., Analysis of Japan's
post-Fukushima energy strategy. Energy Strategy Reviews, 2013. 2(2):p. 190-198.

�������������������������������������������������

29G1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

120

Network Theory Integrated Life Cycle Assessment for an Electric Power System
Heetae Kim and Petter Holme*
Department of Energy Science, Sungkyunkwan University, South Korea*Corresponding author: holme@skku.edu
1. Introduction
Electricity consumers utilize transmission facilities
differently according to their own location and the topologicalstructure of electric power grid. For example, when a consumer
lives far from a power plant, he or she requires longer
transmission lines than others who live near the power plant. It
implies that the formers are more responsible for theenvironmental impacts of transmission system than the latter.
However, the environmental impacts of transmission
facilities are yet to be considered separately. In other words,
conversion factors for environmental impact of electric power
are set based not on the transmission load as a whole but on theamount of electricity consumption alone. The reasons are
twofold. First, the transmission impacts are considerably lessthan the one of primary resources combustion [1]. In addition,
it is methodologically nontrivial to fully reflect complex
supply-demand paths on the power grid. Therefore, theenvironmental impacts of electric power are currently allocatedto the users regardless of their transmission facility load.
To circumvent such as discrepancy, in this study, wedevelop a method in order to properly allocate environmental
impacts of electricity to the electricity consumers considering
the transmission load. We incorporate network theory [2] toanalyze the electricity transmission flow in the electric power
grid. We introduce energy distance as an index representing
both the amount of electricity consumption and the electricity
transmission distance. As a case study, we estimate regional
life cycle greenhouse gas emissions caused by electricity
consumption in Chile. We show that network-theory-basedenergy distance is a useful complement to the conventional life
cycle assessment (LCA).
2. Method: network theory integration into LCA
We follow the standard LCA protocol [3] to estimate thetotal greenhouse gas (GHG) emissions caused by the Chilean
electric power system. In order to analyze the regional GHG
emissions of each substation, we allocate the total GHG
emissions according to the functional load of the substation. Asa quantitative approach, we introduce energy distance as the
allocation standard. Figure 1 illustrates our scheme of network
integration (gray boxes) added to the standard LCA process(white boxes).

consider transmission distance in addition to the amount ofelectricity consumption. Given network structure, we analyze
the electricity supply and demand pairs, transfer quantity, andtransmission path length. The standardized energy distance Ediof node i [between 0(no contribution by i) and 1(the entire
contribution by i)] is defined ask∑ f (a ,d )Edi = nj∈nhd (i )ijij

∑ ∑ f (a ,d )i=1 j∈nhd (i )

ij

(1)

ij

where aij is amount of electricity transmission and dij istransmission distance between nodes i and j, nhd(i) is the set ofneighbors of node i, n is the total number of nodes, and f(a,d) is
the function representing systemic load calculated from the
input variables the nodal consumption (a) and the transmission
distance (d).
4. Results
The total GHG emissions of Chilean electric power system
are 23.07 Mt CO2eq. We reallocate the total GHG emissions toeach region according to the energy distance. We confirm thatthe energy-distance-based allocation reflects real situations ofChilean electric power system. For instance, as a heavy
consumer Santiago needs to be supplied through faraway
power plants, so that the regional GHG emissions of Santiago
are effectively larger than the one solely from energy
consumption. In contrast, even though Conception (the largest
industrial city in Chile) consumes a large amount of electricity,
the transmission loads are not so significant thanks to many
local power plants around the city. As a result, the GHG
emissions for Conception are effectively smaller thanconsumption-only-based ones.

Goal and scope
Network
analysis

Inventory
analysisInterpretation
Impactassessment

Figure 2. Regional GHG emissions of Chilean electric power
Energydistance

Impactre-allocation

Figure 1. Scheme of network theory integration into LCA
3. Energy distance
Energy distance is a nodal index that enables us toReferences[1] Harrison, G. P., et al. Energ Policy 38: 3622–3631, 2010.
[2] Newman, M. Networks: An Introduction. Oxford
University Press, 2010.
[3] ISO 14044:2006, Environmental management - Life cycle
assessment - Requirements and guidelines. ISO, 2006�������������������������������������������������

29G1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

121

Life Cycle Greenhouse Gas Emission and Land Use Change Impact onCompressed Natural Gas as Alternative Vehicle Fuel in Thailand
Worayut Saibuatrong, Viganda Varabuntoonvit and Thumrongrut Mungcharoen*
Chemical Engineering Department, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand* Corresponding author: fengtrm@ku.ac.th
3. Results and discussion

The growth of the natural gas consumption will be
driven by increased own production, the development of
distribution pipeline network and the need to reduce emissionsof Greenhouse gases (GHG) [1]. Natural is gas is a less carbon
intensive fuel than diesel and GHG emission reductions can be
expected by the use of CNG instead of diesel in vehicle. On theother hand, some of the emissions of interest are in fact higher in
the CNG case than their counterparts in the diesel case eventhough the major items are typically lower. For this reason ourcomparative analysis of CNG and conventional diesel was
conducted using the Life-Cycle Assessment (LCA) method andconsidering all the GHG emissions produced throughout the
fuel’s life cycle. The LCA study of Compressed Natural Gas for
Vehicles (CNG) production covered the inventory datacollection throughout the entire life cycle based on the
Well-to-Wheel approach. This study illustrates the change in the
carbon balances of LUC for pipeline transportation, using
methodology and data from the IPCC Guidelines for National
Greenhouse Gas Inventories.
2. Methodology
The LCA study of CNG production covered theinventory data collection throughout the entire life cycle basedon the Well-to-Tank approach. This included the natural gas
extraction, production and separation, transport and gas service
stations, as shown in Figure 1. Since the natural gas extraction,
production and separation had already been done by National
LCI database [2] and Ecoinvent 2.0 database [3]. Therefore, thescope of this study covered mainly on the natural gas
compression process, CNG distribution and the operation at theservice stations. Finally, the impact of transportation of CNG
distribution to the emission of GHG by both transportations(truck and pipeline) was compared. For pipeline transportation,
the land used change (LUC) of the area planned to construct thepipeline was considered. The major sources of information forassessing the GHG emission from LUC are the IPCC
methodologies used for the national GHG inventories [4].
Crude oil extraction

Natural gas extraction

Crude oil transportation

Natural gas transportation

Oil refinery

Natural gas separation

0.10

0.08
kg CO2 eq/ MJ

1. Introduction

0.05

0.03

0.00
CNG - Scenario 1

CNG - Scenario 2

Feedstock production

DieselFeedstock Transport

Fuel distribution

Fuel production

Land use change

Figure 2. Life cycle GHG emission of diesel and CNG
Life cycle GHG emissions of transportation fuel are
shown in Figure 2. The results indicate that life cycle GHG
emissions of CNG have 12% lower than conventional diesel, themajority of which was attributable to the fuel production phase.
The distribution of CNG by pipeline has increased GHG
emission due to GHG emission from LUC.
4. Conclusion
This study compared diesel and CNG fuels for use in
vehicles in terms of GHG emissions throughout their life-cycle.
The GHG emissions of the CNG distribution have 2 scenario
were comparable with those of the diesel cycle. It emerged that
CNG afforded a reduction in GHG emissions by comparison
with diesel. The distribution of CNG by truck has GHG
emission lower than pipeline distribution.
Acknowledgments
The authors gratefully acknowledge financial
support from Center for Petroleum Petrochemicals andAdvanced Materials, Center for Advanced Studies in Industrial
Technology, Department of Chemical Engineering, Faculty ofEngineering, Kasetsart University.
References[1][2]

Fuel distribution

Fuel distribution (Truck)

Fuel distribution (Pipeline)

Oil station

Oil station

Oil station[3]

Conventional diesel

CNG- Scenario 1

CNG- Scenario 2[4]

Figure 1. System boundary of this study

Department of Alternative Energy Development andEfficiency,2013, Thailand energy situation2012,
Ministry of Energy, Bangkok, Thailand.
National Metal and Materials Technology Center, 2012,
Life cycle inventory database of Thailand. Science Park,
Pathumthani, Thailand.
Ecoinvent 2.0, 2012, Final report ecoinvent
2000.SimaPro7.3, Amersfoort
IPCC 2006, In: Agriculture, forestry and other land use,
prepared by the National Greenhouse Gas Inventories
Programme. IPCC Guidelines for National Greenhouse
Gas Inventories, vol. 4. Japan.

�������������������������������������������������

29G1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

122

Life Cycle Assessment of Biodiesel in Hong Kong
Ya Hong Dong,1 and S. Thomas Ng*2
1,2

The University of Hong Kong, Hong Kong
*Corresponding author: tstng@hku.hk

1. Introduction
Biodiesel is an environmental-friendly alternative of
petroleum diesel. Biomasses, such as soy bean, rape seed,sunflower, palm oil, are usually the sources of biodiesel [1]. It
is believed that biodiesel is a carbon-neutral solution, since the
combustion of biodiesel generates the same amount ofgreenhouse gases (GHGs) as those which have been absorbedby plants [2]. Petroleum diesel, produced from fossil fuel thatstocks carbon for millions of years, is generally not recyclable.
In Hong Kong, biodiesel is made from a multi-feedstock that
includes waste cooling oil, grease waste, palm fatty acid andanimal fat. About 100,000 tons of low carbon fuel ismanufactured in the biodiesel factory and this can lead to 3.6%of GHG reduction in Hong Kong [3].
In this study, a life cycle assessment (LCA) is carried out
to evaluate the environmental performance of biodiesel inHong Kong. The inventory is established based on the material
and energy consumed in a local biodiesel factory. Results of
biodiesel are further compared with petroleum diesel.
2. Life cycle inventory
The LCA model considers the ‘cradle-to-grave’ processes,
including raw material extraction, in-plant manufacturing,transportation, waste treatment, combustion in engines, etc. In
order to analyze the environmental impacts of biodiesel before
combustion, ‘cradle-to-delivery’ processes are studied as well
to exclude fuel combustion. The manufacturing process flow
chart of the biodiesel plant in Hong Kong is given in Figure 1.
The inventory data are mainly acquired from the Project Profile[4]. The Ecoinvent database [5] is adopted to provide thebackground data of environmental impacts of the processes.
The functional unit of biodiesel is 1 kilogram (kg) of biodiesel
produced in the Hong Kong plant. As shown in Figure 1, theplant generates three products: biodiesel, glycerin andbioheating oil. The allocation percentages of the three products
are proportional to their weights. When establishing the model,
it is assumed that carbon dioxide is captured by the biomass, sothat carbon sink is calculated to close the carbon balance. No
environmental burden is accounted in the waste oil feedstock.
Besides, infrastructure is not considered in the model.

Figure 1. Manufacturing process of a biodiesel plant in Hong
Kong (Adapted from [4])3. Life cycle impact assessment
The impact assessment is carried out using ‘ReCiPe’ [6]and the results are computed in SimaPro 7. It is found that the
carbon emissions to produce 1 kg of biodiesel is 0.32 kg. By
considering the carbon sink to biomass, the net carbon balanceis -2.2 kg, indicating that the carbon emitted to produce
biodiesel is less than the carbon captured in the biomass. The
results show that the carbon emission is 33.2% originated frommaterial manufacturing and 47.6% due to in-plant processes.
The LCA model also considers other impact categories ofozone depletion, human toxicity, particulate matter formation,
eutrophication, ecotoxicity, metal depletion, etc.
4. Comparison with petroleum diesel
The environmental impact of biodiesel is further comparedwith the impact of petroleum diesel. It is found that biodiesel
performs much better than petroleum diesel in most impact
categories, except agriculture land occupation. The endpointscore of biodiesel is -0.069 (combustion excluded), indicatingthat by considering the processes from ‘cradle-to-delivery’,biodiesel has positive environmental impact and canconsiderably reduce the carbon emissions as compared withpetroleum diesel. If the combustion process is included (i.e.
‘cradle-to-grave’), the environmental impact of biodiesel ismuch less than that of petroleum diesel. Single score of
biodiesel becomes 0.16, which is much less than 0.53 ofpetroleum diesel. This indicates that the environmental impactof biodiesel is only about 30% of petroleum diesel.
5. Conclusions
Environmental impacts of biodiesel produced in thebiodiesel plant in Hong Kong were studied using LCA. The
impact assessment results were compared to petroleum diesel.
The results indicated that petroleum diesel can lead to about
three-fold of environmental influence of biodiesel when‘cradle-to-grave’ life cycle processes are considered.
References
1RIT, Waste cooking oil to fuel program“how to start yourown biodiesel fuel program. 2012.
2 Cherubini, F., et al., Energy-and greenhouse gas-based
LCA of biofuel and bioenergy systems: Key issues, ranges
and recommendations. Resources, Conservation andRecycling, 2009. 53(8): p. 434-447.
3
ASB.
2014;
Availablefrom:
http://www.asb-biodiesel.com/about.php(Accessed
12.2013).
4ERM, Development of a Biodiesel Plant at Tseung Kwan
O Industrial Estate - Project Profile. 2007,
Environmental Resources Managemen.
5 Frischknecht, R., et al., Overview and methodology, in
Ecoinvent report. 2007.
6Goedkoop, M., et al., ReCiPe 2008, in A life cycle impact
assessment method which comprises harmonised
category indicators at the midpoint and the endpointlevel. Report I: Characterisation, First Edition. 2009.

�������������������������������������������������

29G2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan123

Ecological Effects from Operating a Biomass Power Plant
Akito Murano, 1 Satoshi Nakano,2 and Ayu Washizu*3
1

Toyo University, Japan; 2The Japan Institute for Labour Policy and Training, Japan; 3Waseda University, Japan*Corresponding author: washizu@waseda.jp

1. Introduction
Introducing renewable energy sources is indispensable toconstruction of an energy system that is not only sustainable
but also resilient. Toward these ends, we have studied the effectof the spread of power generation using renewable energy
using input-output analysis. As the existing Japanese
input-output table doesn't include renewable energy activities,
we construct an extended input-output table for the analysis ofrenewable energy based on technical literatures and interviews.
(See Nakano and Washizu [1].) In this study, we focus inparticular on the effects of constructing and operating abiomass power plant with a capacity of 5700 kW. The
operation of such a power plant may result in preservation of
the nearby forests, so we also estimate the amount of publicbenefit from preservation.
In the following sections, by using our input-output table,
we first estimated output and CO2 emissions induced byconstruction and operation of a woody biomass power plant,
and the amount of CO2 reduction from reducing the amount offossil fuel used in thermal power plants. Then, we estimatedincreased CO2 storage from forest preservation domesticallyand overseas, and calculated reducing fuel used for marine
timber import. Finally we estimated public benefit from thepreserved forest as a monetary amount using a method of
cost-benefit analysis on public works projects.
2. Method
We calculated the direct and indirect effects ofconstructing and operating a biomass power plant by using a
conventional static open IO model. For estimation of increased
CO2 storage from forest preservation, we calculated CO2
absorbed by photosynthesis. Figure1 summarizes the using
method of cost-benefit analysis. See Nakano, Murano andWashizu [2] for details.
Costs
for

setting out plants
weeding and cutting bushes
pruning branches
improvement cutting
flood mitigation

Benefits water purificationfrom watershed cultivation

Valuation
methodcarbon storage

Reduction of(triggered fromforestimprovement)

cost of maintaining flood-control dam
cost of maintaining water utilization dam
cost of stormwater treatment, water billcost of carbon dioxide capture and storage

Figure 1. Cost and benefit analysis for forest preservation by
Forestry agency (MAFF)
3. Results
Table 1 shows annual monetary effect induced byconstruction and operation of a woody biomass power plant.
The total annual monetary effect of a biomass power plant is
4.822 billion yen. A plant of 5700kW can generate 46.4GWh ofelectricity per year. The procurement cost of electricity
generated from unused woody biomass is 34.56 yen (after tax)
per kWh under the current feed-in tariff, so 46.4GWh ofelectricity earns about 1.6 billion yen. We can see the monetary
effect of a biomass power plant is 3 times as large as theamount spent.

Table 2 shows annual environmental effect of a woody
biomass power plant. The total environmental effect of aconstructing a woody biomass power plant is a reduction of
52,881 t-CO2. In our previous study [3], we found that annual
household CO2 emissions total about 7.5 t-CO2, so this amountcorresponds to CO2 emitted by 6,500households.
Table 1. Annual monetary effect of a biomass power plant(5700kW）(billion yen)Page dimensions*Service life:15 years

Construction* Operation
DirectDirect+Indirect

0.184

1.560

0.436

2.466

Increase inpublic benefit

1.920

Total inducement 4.822 billion yen
Table 2. Annual environmental effect of a biomass power plant(5700kW）（t-CO2）
CO2 emission
construction*

operation

16
503

339
1,261

DirectDirect + Indirect
Total(a) 1,764*Service life:
15 years

CO2 storage or reduction
Substitution
effects forthermalgeneration

DirectDirect+Indirect
Total-30,485-30,934

Increase in CO2 CO2 storage bystorage bypreserved foreign
domestic forest
forest-3.76-5,200

Reduction of CO2
from oceantransport oftimber-18,508(b) -54,645

4. Discussions
Woody power generation brings favorable effects toJapanese forest areas, so we should encourage construction of
power plants like these using a feed-in tariff, which are
subsidies that stimulate plant investment. However, in the caseof woody biomass generation, the operational cost, namely thefuel cost, is considerably high, so a feed-in tariff or similar
subsidy is needed after capital depreciation. From there, thesubsidy can triggers many favorable effects for the local
economy and environment.
Acknowledgments
This study was supported by a Grant-in-Aid for Scientific
Research (B) (KAKENHI), 2011–2014, (No. 23310033 to Ayu
Washizu).
References[1] Nakano, S., Washizu, A., Working Paper Series No.
2013-7, Faculty of Social Sciences, Waseda University,
1-16, 2013.
[2] Nakano, S., Murano A., Washizu, A., "Economic andEnvironmental Effects of Utilizing Unused Woody
Biomass" Grand Renewable Energy 2014 proceedings,
2014, Forthcoming[3] Murano, A., Matsuno, K, Architecture Production
Symposium Proceedings, 2011, pp.171-176.
[4] Nakano, S., Takase, T., Shimizu, H., Washizu, A., Journalof Life Cycle Assessment, Vol.7 No.1, 2011, pp.48-58

�������������������������������������������������

29G2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

124

Load flexible power plant concepts – a comparative analysis from a life-cycle perspective
Witold-Roger Poganietz,*1 Yasushi Kondo,2 Hans-Joachim Gehrmann,1 and Shinichiro Nakamura 2
1

Karlsruhe Institute of Technology, Germany; 2Waseda University, Japan*Corresponding author: poganietz@kit.edu

1. Introduction
The strategic goal of the German government is toestablish a sustainable energy system. The keystone of such asystem is the use of renewable energy carriers [1], whereas
solar and wind energy will dominate power generation (e.g.
[2]). These renewables are characterized by the intermittencyof supply. A possible way to bridge diverging demand andsupply pattern are load flexible power plants, like gas power
plants. An alternative could be to increase the flexibility ofgrate stoker furnaces by combining them with dust furnaces.
Depending on the used feedstock the environmental impacts ofenergy conversion could be reduced. Furthermore, theinternational dependency of Germany on imported energy
carriers could decline either, increasing the internal energy
supply security.
In the following the economy wide environmental impacts
are discussed, when load flexible power plant concepts could
enter the market of electricity. Furthermore potential impacts
on energy carrier imports will be analyzed.
2. Load flexible power plant concept
The proposed plant concept consists of a grate firing
which is operated in base load mode and a dust burner which isoperated in peak load mode (s. Figure 1).

Figure 1. Scheme of a load flexible power plant concept [owncompilation]
The feedstock of the grate firing is hard coal. The flexible
burner will be fed either with pulverized biomass (variant I) orwith pulverized reduced derived fuels (RDF) (variant II).
3. Method
To assess the economy wide environmental impacts ofestablishing load flexible power plants in a first step a physicalInput-Output model of Germany, named Carbon-PIOT, is
combined with ReCiPe methodology.
Carbon-PIOT depicts the carbon relevant material flows inGermany in a setting of a physical input-output table. The
approach makes use of CarboMoG [3]. CarboMoG (short for
carbon flow model of Germany) is a dynamic process-basedmaterial flow model of the German carbon system, which links
carbon flows on the scale of production processes. The
backbone of Carbon-PIOT is 369 production processes with
about 332 carbon-related material and energy flows. In contrast,
the German Input-Output Table consists of just 71 processes on
the scale of sectors. The reference year is 2005.
In a second step scenarios is created and calculated. A
reference scenario with no load flexible power plants will becompared with a scenario with this type of power plants. In thelatter scenario load flexible power plants will experience amarket share of 6.75%. Assuming that load flexible power
plants will crowd out about 50% of gas and oil power plants,
their market shares will decline respectively. Since the impacts
depend crucially on the assumed power mix, two different
cases are analyzed. The first case depicts the power mix in
2005; the second one considers a power mix, which isdominated by solar and wind energy [2].
The assessment of the reliability of imports makes use of
the REES index, which also considers political and institutional
stability of export countries [4].
4. Discussion of the results
The environmental impacts of substituting mainly gas
power plants by load flexible power plants are not clear. On the
one hand, mainly methane emissions would decline in any caseanalyzed. On the other hand, coal induced carbon emissions
and RDF induced emissions (variant II) will increase.
Depending how biogenic emissions are valued, additionalemissions could occur in variant I. All in all, the global
warming potential shall increase; but the entire impact depends
on the chosen time horizon and on the power mix.
The market entry of load flexible power plants will change
the import mix of energy carriers. The share of gas and oil will
decline. On the other hand, imports of coal and to some extent
biomass shall increase; RDF is assumed not to be tradedinternationally. With the change of the import mix therelevance of specific export countries will alter, too. The main
supplier of gas is Russia, whereas the main suppliers of coal
are amongst others Colombia, Russia and USA. Depending on
how the political stability is assessed the switch in the export
countries could lead to an increased security of supply.
5. Concluding remarks
Balancing power supply and demand in a system withdominant solar and wind energy is demanding. Convincing
solutions are still not available, but different options are
discussed. Whether load flexible power plants could fulfill the
expectations depends crucially on the success of competing
technologies, like storage systems. But also whether
technological problems of the concept, like controlling or
combustion behavior of biogenic inputs, could be solved isrelevant.
Acknowledgments
Funds of the Japan Society for the Promotion of Science
are gratefully acknowledged.
References[1] The Federal Government (of Germany) National
Sustainable Development Strategy – 2012 Progress
Report.
http://www.bundesregierung.de/Content/DE/_Anlagen/Na
chhaltigkeit-wiederhergestellt/2012-06-07-fortschrittsberi
cht-2012-englisch-barrierefrei.pdf?__blob=publicationFile (Accessed 22.09.2014)[2] Pregger, T. et al. Energy Policy, 59: 350-360, 2013.
[3] Uihlein, A. et al. Resources, Conservation and Recycling
46: 410-429, 2006.
[4] Le Coq et al. Energy Policy, 37: 4474-4481, 2009.

�������������������������������������������������

29G2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

125

Small Hydro Power Plants: A Modular LCA Approach for Optimization
Beatrix F. Becker,* Liselotte Schebek
Technische Universität Darmstadt, Germany*Corresponding author: b.becker@iwar.tu-darmstadt.de
1. Introduction
Small Hydro Power Plants (SHPP) do interest as renewableenergy technology for mitigating climate change. There is alarge variety of sites for SHPP, resulting in a large variety ofpossible individual technological solutions: SHPP combine
different components and their variants like rake and hydraulicmachinery. Yet nature conservation also has to be considered,notably as to the inclusion of fish passes. As to ecologicalassessment, several LCA studies are available [1][2][3][4],however they don’t display current developments in technology nor river continuity, which is requested by the EU commission. So, in order to support the ecological assessment andoptimization for future SHPP, a novel approach for LCA andan appropriate database are needed.
The lay-out of SHPP requires the technological approach ahydraulic dimensioning as a first step. Further an economic
evaluation is performed, which may change the first outline ofcomponents. In addition, specific local framework conditions
have to be met, usually leading to individual solutions. This
technological approach is costly reverted to the energetic output of SHPP which is rather low. So, different technologicalcomponents and all their variants have to be analyzed regarding their ecological assessment in consideration of the efforts
needed for different locations. Therefore, the following approach aimed for a parameterized procedure.
2. Method
Modular LCA follows the technological approach described above. Parameterized unit modules provide the database from which the product system for a specific plant isgenerated. To develop this database, datasets for components of
SHPP have been developed from literature evaluation, producer
information and site investigations. This modular database uses
open source software developed in a project for LCA of bioenergy (BioEnergieDat). So, datasets are compatible and convertible. Based on this database, our methodology for optimization combines the following steps:
1. Input of parameter by user: specific local framework conditions (head, flow rate, fish species, natural requirements)
2. Automatized generation of combinations and their
LCI-Data by program: definition of variants with input parameters and background information within the program,combinations added by LCI-Data, based on existing andnewly generated datasets for technological components
3. Generation and optimization of LCIA results of variations
by program: evaluation of all combinations by impact categories (global warming potential (GWP) and cumulated
energy demand (CED)), optimization by input parameters
3. Results
Following the aforementioned methodological approach, acase example is displayed, wherein all technological combinations were estimated and the best and worst combinations were
calculated for the LCIA category GWP100. As input parameterin Table 1 the values are shown. With the input parameter theparameterized LCI-datasets of technological components will
be calculated. Here the number of technological variants varies: Rake (10), bypass (7), fish pass facility (2), hydraulicmachinery (3) and generator (1). Figure 1 shows the result of

the variations of components for the case example. These range
from 0,062 kgCO2eq/kWh up to 0,082 kgCO2eq/kWh.
Table 1: Input parameter in case example
Parameters
Value
Head
2m
Flow rate
0.5 m³/s
Fish species
ZanderIntake sizes
5m x 4m
Natural requirements
River continuity
Here, the characteristic picture of the variants results fromthe high influence of the fish passes facility on the total emissions. But, it is also obvious, that the percentage share of technological component varies depending on each variation. For
example the share of hydraulic machinery on total emissions
varies from 1% (in minimum) up to 12% (in maximum).

Figure 1. The GWP100 of variation of technologicalcomponents of SHPP
With this methodological approach and implementation in a
program structure, it is possible to calculate a high number oftechnological component variations (here: 420) very easily.
5. Discussion
The open modular programming structure ensures the extension of this methodological approach for more component
variants, impact categories and for the transition of other energy technologies. So, the currently existing datasets do notdisplay all components of SHPP neither all existing technological variants yet. More datasets will be created, parameterized
and validated in the future. So more studies will be analyzed
for a more detail view of total emission and the influence oftechnological components depending on input parameters.
References[1] Suwanit, W. and Gheewala, S. H. Life cycle assessmentof mini-hydropower plants in Thailand. In: Int J Life Cycle Assess 16 (9): 849–858, 2011.
[2] Varun et al. Life Cycle Analysis of Run-of River Small
Hydro Power Plants in India. In: The open renewable Energy Journal (1): 11–16, 2008.
[3] Varun, P. and Ravi, B. Life cycle greenhouse gas emissions estimation for small hydropower schemes in India.
In: Energy 44 (1), S. 498–508, 2012.
[4] Pascale, A. et al. Life cycle assessment of a communityhydroelectric power system in rural Thailand. In: Renewable Energy 36 (11), 2799–2808, 2011.

�������������������������������������������������

30A1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

126

Global flow of nickel: Identifying its supply chain and implication for sustainable
resource management
Kenichi Nakajima*1, Keisuke Nansai1, Hiroya Yamano1, Kazuyo Matsubae2,
Shinsuke Murakami3, Yuto Ohtsuka2, Yasunori Iwatsuki3, and Tetsuya Nagasaka2
National Institute for Environmental Studies, Japan; 2 Tohoku University, Japan; 3The University of Tokyo, Japan*Corresponding author: nakajima.kenichi@nies.go.jp

1. Introduction
The UNEP International Resource Panel pointed out theimportance of decoupling resource use and negativeenvironmental impacts from economic activity. The economic
growth also induced a rapid rise of metals, and sometimes thegreen technology, such as low carbon power generation,
triggered the rapid rise of metals and minerals. Nickel andnickel-containing materials play a major role in modern society,which are also key materials for low-carbon technologies. At
the same time, environmental risks and challenges are always
attaching through the life cycle of nickel-containing materials,
and the biodiversity impact by nickel ore mining has also
received attention in recent years [1]. In this study, we present
the results of global material flow analysis of nickel, anddiscuss the importance and possibility to control its resource
logistics. This study also introduces the challenge to identify
the land-use changes in nickel mining site by remote-sensing
technique, and knowledge to increase the resource efficiency inrecycling based on metallurgical thermodynamic approach.
2. Global supply chain analysis of nickel
This study clarified the worldwide nickel flow in the
global supply chain by analysing the volume of international
trade among the world’s 231 countries and regions. For
considerations of space, we omit a description on themethodology. (Please see the detailed descriptions ofmethodology in previous publications [2-3]) With respect to thevolume of international trade, we extracted trade volumes foreach commodity group in monetary or physical units for 231
countries and regions, using the BACI (Base pour l’Analyse duCommerce International, CEPII). The estimates were converted
to the flow of nickel embedded in trade by multiplying thevalues by the nickel content rate of each of the goods available
from various sources and the WIO-MFA model [4-5].

3. Land-use changes in nickel mining sites
The quantitative analysis on the relationship between theland-use changes and mineral production is quite few, and thus
the effect of mining on land-use change, and further
environmental impacts, remains to be examined. This paper
performed a preliminary case study in New Caledonia, because
it is a major nickel mining area, and is also known as one of thebiodiversity hotspots, where exceptional concentrations ofendemic species are suffering from extensive decreases in theirhabitats [6]. The laterite nickel deposits are relatively thin andusually located close to surface, therefore the depth of the pit
will be shallow. We chose five mine sites at which Société Le
Nickel operates, and compared the temporal changes in land
use with statistics of nickel ore production published by SNL
Metals & Mining. We used historical satellite images toreconstruct temporal changes in bare land areas due to mining
activities from 1999 to 2012. Figure 2 shows the cumulative
nickel production and land-use change in nickel mining sitefrom 1995 to 2012. Our result shows four out of the five minesites have similar tendency of land-use change per kg-Ni ofnickel of mining, however the Tiebaghi mine site has quite
large land-use change. From the satellite image for 2007 in the
Tiebaghi mine, we observed a new facility on the western sideof the mine. Then, in 2012, we also found out a new area wasunder development (stripped) at the northern side of the current
pit. The area was not in operation stage and therefore notrelated to the production until 2012, while the area was not
small compared with that of the pit.

Bare land area, x 106 m2

1

Nickel production, x 106 kg‐Ni

Figure 2: Cumulative nickel production and land-use
change in nickel mining site (from 1995-2012)
Figure 1 The 50 largest global flows of iron throughinternational trade in 2005
The result of our analysis indicated that the worldwide
follow of nickel though the trade in 2005 was 2.7×106 t-Ni,
with the largest 10 flows accounting for 17% of the entire flowof nickel among 231 countries and regions, and largest 50
accounting for 43% (Figure 1). The percentage of the BRICS
and the Next Eleven in the worldwide flow is worthy of special
mention. The BRICS excluding China accounted for 5% in theworld’s resource imports. Adding the N-11, the percentage of
15 countries was no more than 11%. These results indicate thevital importance of Japan’s and Europe’s actions to control thenickel supply chain and its environmental impacts.

Acknowledgments
This research was partially supported by JST-RISTEX, theEnvironment Research and Technology Development Fund
(1-1402) of the Ministry of the Environment, Japan and theJapan Society for the Promotion of Science (KAKENHI
26281059 and 26550104).
References[1] Mudd, G.M. Ore Geology Reviews 38, 9-26, 2010[2] Nansai, K., et al., Environ. Sci. Technol. 48, 1391-1400,
2014[3] Nakajima, K. et al., Tetsu-to-Hagané 100, 750-755, 2014[4] Nakamura, S., et al., J. Ind. Ecol. 11, 50−63. 2007[5] Ohno, H., et al., J. Ind. Ecol. 18, 242-253, 2014[6] Myers, N., et al., Nature 403, 853-858, 2000

�������������������������������������������������

30A1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

127

Sustainability of Rare Metal Supply Chains from Unconventional Resources
Glen Corder,*1 Saleem Ali, 1 Artem Golev, 1 and Ben McLellan2
1

Centre for Social Responsibility in Mining, Sustainable Minerals Institute, University of Queensland, Australia; 2 Graduate
School of Energy Science, Kyoto University, Japan*Corresponding author: g.corder@smi.uq.edu.au

1. Introduction
There has been heightened interest in rare earths in recent
years driven by a variety of reasons, including concerns overthe security of supply for modern high efficiency electronics
and energy technologies. As a result, rare earths have beenplaced on the list of “critical” or “strategic” elements incountries such as the United States of America (USA), theEuropean Union (EU), Japan and in the largest producer andholder of reserves, China [1].
This increasing demand for rare metals and subsequent
price fluctuations as well as potential squeeze on supply of
conventional resources has been prompting examination of
unconventional resources such as recycling, urban mining anddeep ocean resources.
2. Potential from Unconventional Resources
By utilizing an industrial ecology approach, extraction,
recycling and re-use of rare earths metals from unconventionalsources is possible and thereby both influencing their supply
and implementing solutions that are a means of retaining
materials in a circular economy. Industrial ecology, using
nature as a metaphor, closely examines the opportunities toreuse and recycle different waste streams arising in industrial
and consumer activities, as well as reorganizing the industrial
systems to ensure resource efficiency and resilience [2]. Suchexamples of industrial ecology for rare earths are shown below.
The potential for the recovery of rare earths via recyclingof low value waste streams such as bauxite residue,
phosphogypsum, waste water, slag and mine tailings has
recently been examined by workers; and in addition there iscontinuing activities in recycling of end-of-life batteries,
fluorescent lamps and magnets [1]. Deep sea mining is a new
potential high concentration source of rare earths withnumerous sites being identified throughout parts of the Pacific[3]. Coal and coal ash are another potential unconventional
resource for rare earths [4].
There
are
also
environmental
benefits
fromunconventional resources. Environmental impacts related to
extraction, processing and final application of rare earths frommining are positive in terms of clean energy and negative interms of waste. However, high environmental impacts of rareearth mining and processing (on a per kg basis), as indicated bylife cycle assessment, coupled with supply constraints provide
a sound incentive to investigate recycling and recovery of rareearths or minerals containing rare earths [5].
The resistance to social aspects of rare earths mining
typically is related to concerns about environmental and healthimpacts making it more difficult to gain approvals of new minesites in some countries, such as Australia and the USA. This isalso another driver for sourcing rare earths fromunconventional sources where the concerns of environmental
impacts can be potentially minimized.
3. Applying Industrial Ecology
Although utilizing unconventional sources for rare earths
can appear more attractive than conventional sources, there are,however, challenges for the implementation of industrial
ecology solutions that are more than technological, especiallywhen organizational boundaries are crossed. Having a thoroughunderstanding of these challenges greatly helps in identifying
the barriers and enablers to developing feasible industrial
ecology strategies that can move a group of commodities, suchas rare earth metals, closer to a circular economy paradigm andin doing so deliver enhanced sustainability benefits.
Determining factors related to the industrial ecology barriersand enablers include: suitable economic returns for businesses
along the circular value chain, fitting regulations thatencourage an industrial ecology approach, technical feasibility
for recovering value from waste materials and availability of
information and data across businesses that have traditionally
not necessarily worked together [6]. It is important to weigh up
these factors when comparing with the production of rareearths from conventional mining.
4. Conclusions
The demand for rare earths will drive the interest insourcing rare earths from unconventional resources. Thisextended abstract has illustrated some potential unconventional
resources and associated challenges for extracting or
recovering rare earths. However, each needs closer
examination of their life cycle sustainability impacts, focusing
on the technological constraints, social responsibility andenvironmental implications, to fully understand potential
benefits and possible detriments. Without such knowledge,
appropriate systems and policies cannot be developed.
Acknowledgments
The authors would like to acknowledge that funding forsome of the authors’ involvement in this work has been
provided through the NextMine™ Initiative of the Universityof Queensland's Sustainable Minerals Institute.
References
McLellan, B., et al., Sustainability of Rare
Earths—An Overview of the State of Knowledge.
Minerals, 2013. 3(3): p. 304-317.
[2]
Corder, G.D., et al., The Status of Industrial Ecology
in Australia: Barriers and Enablers. Resources, 2014.
3: p. 340-361.
[3]
Kato, Y., et al., Deep-sea mud in the Pacific Ocean
as a potential resource for rare-earth elements.
Nature Geosci, 2011. 4(8): p. 535-539.
[4]
Seredin, V.V., et al., Coal deposits as promisingsources of rare metals for alternative power andenergy-efficient technologies. Applied Geochemistry,
2013. 31(0): p. 1-11.
[5]
Tharumarajah, R. and P. Koltun, Cradle to gateassessment of environmental impact of rare earth
metals, in ALCAS Conference 2011. 2011, AustralianLife Cycle Assessment Society: Melbourne.
[6]
van Beers, D., et al., Industrial symbiosis in theAustralian minerals industry - The cases of Kwinana
and Gladstone. Journal of Industrial Ecology, 2007.
11(1): p. 55-72.
[1]�������������������������������������������������

30A1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

128

Refinement of a Simulation Model to Analyze the Formation of Urban Mines with
Demonstrative Experiments
Hitoshi Komoto,*1 Shinsuke Kondo,1 and Keijiro Masui1
1National Institute of Advanced Industrial Science and Technology, Japan*Corresponding author: h.komoto@aist.go.jp

1. Introduction
Used products accumulated at the end of life cycles arepotentially used as alternative reserves of natural resources,
and thus named urban mines [1]. To promote the development
and utilization of urban mines in Japan, a law about therecycling of Small Waste Electrical and Electronic Equipment(SWEEE) was introduced in 2013 [2]. Related work has
quantified the impact of the recycling processes of specificmetals from urban mines in terms of the total material
requirement (TMR) and compared the TMR from urban mines
with that of from natural mines (e.g., [3]), which addresses thesuperiority of the recycling of specific metals (e.g., gold, silver,
and coppers) from urban mines to the extraction of these metals
from natural mines. However, these studies have excluded theinvestigation of the potential amount of these metals recovered
with these processes from the scope of the study.
To estimate the amount of metals recovered from urban
mines with the current state of the art of recycling processes,
the authors have developed a simulation system to analyze theformation of urban mines [4]. The system deals with thegeographical distribution of the users of products, local
governments, and operators in the recycling processes in Japan,
and their rational decisions about the execution of operations.
This report introduces the simulation model and a type of
empirical data recently collected by the Ministry ofEnvironment [5] used to refine the simulation model.
2. Overview of the simulation procedure
Figure 1 shows the overview of the simulation procedure.
The simulation uses the following information as inputs.

Physical and material composition of products, which
defines the recycling processes applied to the products
and their inputs and outputs, and their prices.

Population, location, and area of local governments,
which define the distributed amount of used products.

Location of operators in the recycling processes (e.g.,mechanical separation and refinement).

Fixed and variable costs of the recycling process, andtransportation costs.
With these inputs, the simulation computes the execution ofindividual recycling process that generate the transportationand transformation of products, parts, and materials defined intheir physical and material composition. Finally, the simulated
results are visualized as material flows and the breakdown ofprofits and costs of the operators in the recycling processes.
Figure 2 shows illustrative results of the simulation. The graydots show the location of the local government. The red andblue spots indicate the accumulation of different types ofmetals of specific recycling processes.

Figure 1. Overview of the simulation procedure

Figure 2. Illustrative results of the simulation
3. Demonstrative experiments
Ministry of Environment started to conduct demonstrative
experiments about SWEEE collection with participation of
more than 40 local governments (which have 3.8 million
population in total) [5]. In spite of the limited period, they
could collect over 20,000 units (over 42,000 kg) of SWEEE. In
comparison, the target amount of SWEEE to be collected is
1kg per person per year, which is 20% of the amount ofdisposed SWEEE in 2011 [2]. Since the number of theexperiments is still limited, the results are not enough toperform the analysis of the collection process from a statistical
viewpoint. Similar experiments are planned in this year [5].
4. Future work
The input of the simulation model will be refined with theinformation obtained from the demonstrative experiments,
which includes the deviation of the total amount of collected
SWEEE regarding the regional characteristics (e.g., geographicand demographic population distribution), collection means(i.e., box, station, pick-up, and event-type collection), andseasonal characteristics, and the proportion of collected
SWEEE in terms of product types. The information about thestate of the art of recycling processes for SWEEE is also
crucial to estimate the amount of metals and other resources
recycled from SWEEE.
References[1] Nanjo, M. Urban mine, new resources for the year 2000
and beyond. Bulletin of the research institute of mineraldressing and metallurgy, Tohoku Univ., 43(2): 239-251,
1988.
[2] Ministry of the Environment. Act on Promotion of
Recycling of Small Waste Electrical and Electronic
Equipment. 2013.
[3] Yamasue, E., Minamino, R., Daigo, I., Okumura, H.,
Ishihara, K.N. Evaluation of total materials requirement
for the recycling of material (urban ore TMR) fromend-of-life electric home appliances, J. Japan Inst. Metals.
74(12):811-819, 2010.
[4] Komoto, H., Kondo, S., Masui, K. Simulating theformation of urban mines considering the rational
decisions of distributed end-of-life stakeholders. Int. J.
Autom. Technol. 8(5): 653-663, 2014.
[5] MinistryofEnvironment,
http://www.env.go.jp/recycle/recycling/raremetals/index.html [accessed on June 30, 2014].

�������������������������������������������������

30A1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

129

Quality-Oriented End-of-Life Vehicle Scrap Recycling Aimed at Efficient Utilization of
Steel Alloying Elements
Hajime Ohno,*1 Kazuyo Matsubae,1 Kenichi Nakajima,2 Yasushi Kondo,3 Shinichiro Nakamura,3and Tetsuya Nagasaka1
1

Tohoku University, Japan; 2National Institute for Environmental Studies, Japan; 3Waseda University, Japan*Corresponding author: fy11041@mail.kankyo.tohoku.ac.jp

1. Introduction
For the achievement of quality-oriented steel recycling,exogenous contamination should be avoided by the removal ofcontaminant before re-melting. Although alloying elements(AEs) should also be removed, they cannot be separated
mechanically because they are alloyed with iron matrix.
Therefore contents of AEs in recycled steel must be controlled
within requirement and/or regulation during re-melting process
to save not only the quality of steel but also precious AEs.
For this background, focusing on the recycling of AEs in
End-of-Life vehicle derived scrap (ELV-dSS), this study
evaluated alloying elements contents in an ELV-dSS by meansof input-output (IO) based material flow analysis. Furthermore,
efficient use of AEs oriented ELV-dSS recycling was optimized
by integrating IO with linear programming (LP).
2. Methodology
This study considers an LP model to find out optimal
technology choices to utilize ELV-dSS in crude steelmaking byelectric arc furnace (EAF), which is the main process to recycle
iron and steel scrap. Let there be 𝑛𝑛𝑛𝑛 𝑔𝑔𝑔𝑔 goods- andservice-producing sectors (hereafter ‘goods sector’) except
sectors of crude steel made by EAF, 𝑛𝑛𝑛𝑛𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 crude steel made by
EAF sectors (hereafter ‘EAF-CS sector’), and 𝑛𝑛𝑛𝑛 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 ELV-dSS
sectors. The present LP model is concerned with identifying
which types of EAF-CS should be made from which types of
ELV-dSS. Formally, the problem is given as follows
minimize(1)
R𝑔𝑔𝑔𝑔 x𝑔𝑔𝑔𝑔 + R 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
subject to(2)
x𝑔𝑔𝑔𝑔 = A𝑔𝑔𝑔𝑔,𝑔𝑔𝑔𝑔 xg + A𝑔𝑔𝑔𝑔,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + f𝑔𝑔𝑔𝑔(3)
H𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 = A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑔𝑔𝑔𝑔 x𝑔𝑔𝑔𝑔 + A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + f𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
xss = A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + 𝑤𝑤𝑤𝑤𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐(4)
x𝑔𝑔𝑔𝑔 ≥ 0𝑛𝑛𝑛𝑛𝑔𝑔𝑔𝑔 , x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 ≥ 0𝑚𝑚𝑚𝑚𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 , x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 = 0(5)where R𝑔𝑔𝑔𝑔 and R 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 are 1 × 𝑛𝑛𝑛𝑛 𝑔𝑔𝑔𝑔 and 1 × 𝑚𝑚𝑚𝑚𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝑛𝑛𝑛𝑛 𝑔𝑔𝑔𝑔 ≤ 𝑚𝑚𝑚𝑚𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 )vectors representing the objective function, x𝑔𝑔𝑔𝑔 , x𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 andx𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 are output vectors of goods sector, EAF-CS sector and
ELV-dSS, respectively, As are input coefficient matrices, andfs are final demand vectors. The vector 𝑤𝑤𝑤𝑤𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 indicates weightsof each ELV-dSS in negative values. In this model, ELV-dSS is
supplied exogenously and there is no process producing scrap
in the IO system. Consequently, equation (4) is the constraint
representing that all amounts of supplied ELV-dSS are used in
EAF-CS making process. The (𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗)-component of A𝑔𝑔𝑔𝑔,𝑔𝑔𝑔𝑔 (orA𝑔𝑔𝑔𝑔,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 ) refers to the input of the 𝑖𝑖𝑖𝑖th goods par unit of productionof the 𝑗𝑗𝑗𝑗th goods (or the 𝑗𝑗𝑗𝑗th EAF-CS sector, respectively). The(𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗)-component of A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑔𝑔𝑔𝑔 refers to the input of the 𝑖𝑖𝑖𝑖th goods
par unit of production of the 𝑗𝑗𝑗𝑗th goods. Because crude steels
are not input to other crude steelmaking, A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 is basicallyzero in this model. The (𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗)-component of A𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 refers to
the input of the 𝑖𝑖𝑖𝑖th ELV-dSS par unit of in EAF-CS production.
H𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 is 𝑛𝑛𝑛𝑛𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 × 𝑚𝑚𝑚𝑚𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 matrix of zeros and unities, and its(𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗)-component ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 is defined as
1 technology 𝑗𝑗𝑗𝑗 produces goods 𝑖𝑖𝑖𝑖
(6)
ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = �0otherwiseThis matrix to calculate the total quantity of each crude
steel produced by multiple technologies was employed, forexample of the application of matrix H , see Kondo andNakamura[1]. The objective function Rs consists of zeros andunities to see the changes in productions of AE virgin souces
caused by utilization of ELV-dSS for simplicity in this paper.
3. Results and discussion
Focusing on the efficient recycling of AEs in the ELV-dSS,
the matching of each part scrap and secondary steels were
optimized by means of IO-based LP. Figure 1 (upper half)shows optimized matching of separated ELV-dSS with steel
materials to efficiently recycle AEs in the ELV-dSS under theobjective function aimed at minimizing total consumption ofvirgin sources of AEs. Relatively low AEs concentration ofparts scrap such as body, steering, and breaks were mainly
matched with ordinary steel. In contrast, parts scrap whichhave over 0.5% of AE concentration such as suspension, shaft,and exhaust tend to be used to produce alloy steels in the
optimal matching. As a consequence of the optimized
utilization, 88% of AEs contained in ELV-dSS were efficiently
used as secondary AEs source in secondary steelmaking.

Figure 1. Optimized matching between sorted ELV-dSS andsecondary steels
Acknowledgments
This research was supported by the Japan Society for the
Promotion of Science (JSPS) (KAKENHI 23686131, 258801),
the Iron and Steel Institute of Japan (a research group forrecycling automobiles from the perspective of the material
industry), and the Research Institute of Science andTechnology for Society of the Japan Science and Technology
Agency (JST-RISTEX).
References[1] Kondo, Y. and S. Nakamura, Waste input–output linear
programming model with its application to eco-efficiency
analysis. Econ. Syst. Res., 2006. 17(4): p. 393-408.

�������������������������������������������������

30A2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

130

Measuring supply risk footprints of critical metals for Japanese goods and services
Keisuke Nansai*1, Kenichi Nakajima1, Shigemi Kagawa2, Yasushi Kondo3 and Sangwon Suh4
1National Institute for Environmental Studies, Japan, 2Kyushu University, Japan, 3Waseda University, Japan, 4University ofCalifornia Santa Barbara, USA;
*Corresponding author: nansai.keisuke@nies.go.jp

1. Introduction
Exotic metals, which are those metal resources that are
particularly essential to future energy technologies but to whichaccess is limited to certain counties where they are mined, arerecognized as critical metals [1-3]. Discussions are taking place[1-4] regarding their economic importance, as well as the risks
from a resource security perspective. In light of the dependenceof the Japanese economy on all import of such critical metals
through international supply chains, it is increasingly becoming
important to identify the amount of their supply security related
to Japan. Against the background, this study proposed a newindex to measure supply security of the metals for a nation
using the concept of an environmental footprint. Especially, themining risk and trade risk are considered as key factors thatcompose supply security. In this paper, we describe themethodology to identify the mining risk that a nation bears as
mining risk footprint (MRF) of a nation. The case study of
MRF calculation for Japan in 2005 was performed.
2. Methods and data
First, the international trade through which critical metals
moved from countries of origin to consumption countries was
examined using material flow analysis (MFA) based on a
global system boundary [5]. The MFA encompasses 231
countries and regions and considered all trade commodities thatwould contain the metals. Our focused critical metals areneodymium (Nd), which is used for motors associated withwind power and EV, cobalt (Co), for electrodes in EV batteries
and platinum (Pt) for catalysts in fuel cells.
Subsequently, a global link input-output model (GLIO) [6]that incorporates the MFA data obtained above was used to
calculate the output of the metals in mining courtiers or thematerial footprint [7] which Japan caused directly andindirectly. The GLIO is designed to reduce the labour requiredfor data compilation by employing a simple accounting
framework that differs from that of conventional multiregional
input-output models. The accounting framework of GLIO
enables the definition of about 400 sectors of the Japanese
products, the inclusion of 230 nations and regions except forJapan.
Then, we combined the metal output gpJPD (MF) induced
by Japanese domestic final demand measured and the mining
risk value ηp of mining country p, and quantified the mining
risk footprint of the Japanese economy. The basic concept of anenvironmental footprint index is the allocation of anenvironmental burden such as carbon emission in a country toeach country that induces the environmental burden on thebasis of some allocation factor closely related to the generationof the environmental burden. In the same manner, we allocatedηp to a country that induces the mining in country p inproportion to the share of output induced by the country in the
total output of country p. Specifically, when the annual total
output of country p is gp and the output induced by Japan is
gpJPD, ηp (gpJPD/ gp ) of country p's mining risk is attributed toJapan. Then this mining risk was normalized by dividing by the
global mining risk η, and MRF (%) of Japan was determined.

3. Results and discussion
MRFs of Japanese final consumption were measured as
10.3 % for neodymium, 5.0 % for cobalt, and 14 % forplatinum, measured in % of global mining risk of each material.
The MRFs of Japan were all dominated by export demand.
[%]
100

9

80

8

60

7

40

6

20

5

0

4

-20

3

-40
-60

2

-80

1

-100
-200

-150

-100

-50

0

50

100

150

200

0

Figure 1: Global distribution of mining risk footprints ofneodymium associated with Japanese total final demand in2005
Acknowledgments
This research was supported in part by a Grant-in-Aid forresearch (No. 25281065) from the Ministry of Education,
Culture, Sports, Science and Technology of Japan, and theEnvironment Research & Technology Development Fund
(3K122024) of the Ministry of Environment, Japan.
References[1] National Research Council, Minerals, Critical Minerals,
and the U.S. Economy. The National Academies Press:
2008.
[2] EU Critical raw materials for the EU; The Ad-hoc
Working Group on defining critical raw materials: 2010.
[3] U.S.D.O.E Critical Materials Strategy; U.S. Departmentof Energy: 2011.
[4] Erdmann, L.; Graedel, T. E., Criticality of Non-FuelMinerals: A Review of Major Approaches and Analyses.
Environmental Science & Technology 2011, 45, (18),7620-7630.
[5] Nansai, K.; Nakajima, K.; Kagawa, S.; Kondo, Y.; Suh,S.; Shigetomi, Y.; Oshita, Y., Global Flows of Critical
Metals Necessary for Low-Carbon Technologies: The
Case of Neodymium, Cobalt, and Platinum.
Environmental Science & Technology 2014, 48, (3),1391-1400.
[6] Nansai, K.; Kagawa, S.; Kondo, Y.; Suh, S.; Inaba, R.;
Nakajima, K., Improving the Completeness of Product
Carbon Footprints Using a Global Link Input-Output
Model: The Case of Japan. Econ Syst Res 2009, 21, (3),267-290.
[7] Wiedmann, T. O.; Schandl, H.; Lenzen, M.; Moranc, D.;
Suh, S.; West, J.; Kanemoto, K., The material footprint of
nations. P Natl Acad Sci USA 2013.

�������������������������������������������������

30A2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

131

Material Flow of Cobalt in Taiwan
Lu-Yen Chen,*1 Shun-Tian Huang,1 and Yu-Wen Huang1
1
National United University, Taiwan*Corresponding author: lychen@nuu.edu.tw

1. Introduction
Cobalt is widely used in alloys for different industries
worldwide. Scott F. Sibley(1998) reported the material flow ofcobalt in the United States, about 32 percent of U.S. cobalt
supply came from scrap in 1998. "The ratio of cobalt consumed
from new scrap to that from old scrap was estimated to be
50:50. Of all the cobalt in old scrap available for recycling, anestimated 68 percent was either consumed in the United States
or exported to be recycled."[1] It was reported in the website of
National Institute for Materials Science that cobalt were used
to produce some special iron, catalysts, and magnets in Japan.
The possible recycle ratio was reported as 87%.[2]The importand export information of cobalt were reported by
USGS(2005).[3] The price of cobalt made from electrolyzed in
China as well as the global supply-and-demand of cobalt werealso reported.[4] In addition to other metals used intransportation, the use of cobalt was also reported by
UNEP(2010).[5] However, there are no cobalt reserves in
Taiwan. In order to investigate the processes in which cobalt
was used, and the amount of cobalt consumption in Taiwan, thematerial flow of cobalt had been carried out.
2. Materials and Methods
Figure 1 is the flow chart of this study. The study beganfrom the investigation of cobalt-containing products in Taiwan.
The scope of this study is the material flow of cobalt in Taiwan
during 2011.

Figure 1. The methodology of this study
All the data used to construct the cobalt inventory wereshown in Table 1.
Table 1. Data used to construct the cobalt inventory
Database
Content
Resolution
Import/Export
Some lack
Customs Administration,amount ofof detailMinistry of Finance[6]products information

Information System of
Stationary Sources of Air
Pollutants[7]Taiwan Economic Data
Center[8]Process
description

Amount ofproducts

Rawmaterial
andproduct
amountOnly larger
categories
available

3. Material flow results
The material flow of cobalt can be shown as Figure 2.

Figure 1. The logo of EcoBalance 2014
4. Summary
About 89.73% of the import of cobalt raw material isunder further treatment. The usage of cobalt as catalyst was
about 24.34%, that hint the recycle of waste catalyst should be
helpful for creating new sources of cobalt.
References[1] Shedd, K. B. Cobalt Recycling in the United States in
1998. Flow Studies for Recycling Metal Commodities in
the United States (edited by Scott F. Sibley), U.S.
Department of the Interior, U.S. Geological Survey, 2004.
[2] The National Institute for Materials Science .
http://www.nims.go.jp/emc/ecoinfo2/pages/Co/Co_md.ht
ml, "cobalt", (Accesed 25.03.2014).
[3] Charles G. Groat, “Mineral Commodity Summaries”, U.S.
Geological Survey, (2005).
[4] Asian Metal.
http://www.asianmetal.cn/price/initPriceList.am，(Accesed 25.03.2014). (in Chinese)[5] UNEP, “Metal Stocks in Society”, International Panel for
Sustainable Resource Management, (2010).
[6] Customs Administration, Ministry of Finance .
http://www.customs.gov.tw/StatisticWeb/IESearch.aspx，(Accesed 25.03.2014). (in Chinese)[7] Information System of Stationary Sources of Air
Pollutants . http://ernet.epa.gov.tw/, (Accesed 25.03.2014).
(in Chinese)[8] Taiwan Economic Data Center .
http://2k3dmz2.moea.gov.tw/Gwweb/, (Accesed
25.03.2014). (in Chinese)�������������������������������������������������

30A2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan132

Sustainability Assessment of Deep Ocean Resources
Benjamin C McLellan,*1,2
1Graduate School of Energy Science, Kyoto University, Japan

2Sustainable Minerals Institute, The University of Queensland, Australia*Corresponding author: b-mclellan@energy.kyoto-u.ac.jp

1. Introduction
Critical minerals have become of concern in recent years
due to the increasing demand from use in new energy
technologies and the limitations on supply due to price,capacity and political reasons. Deep ocean resources (DOR) –e.g. rich cobalt crusts, massive sulphide deposits andmanganese nodule deposits – have been of increasing interest
to provide supply security for strategic minerals for sustainableenergy futures, but are currently inaccessible due to lack ofappropriate technology or economically unfeasible to extract.
This is despite many decades of investment and investigation.
The actualisation of this mining activity would the start of a
new mining revolution, and the social and environmental
implications are as yet unclear. The life cycle sustainability
assessment of critical minerals from DOR in comparison withconventional resources is therefore vital and urgent.
2. BackgroundThe deep ocean seabed is a vast, largely unexplored andlargely unknown area, which has been found to containpotentially valuable deposits of minerals. Particularly forresource-poor countries such as Japan, the available DOR
maybe attractive as a method of improving resource security.
Mining these on an industrial scale has only really been
contemplated seriously since the 1960`s, but is coming closer
to fruition with the Solwara I project in Papua New Guinea.
The main types of DOR are designated in Table 1.
Cobalt-rich crusts are layers of precipitated material similar to
manganese nodules, but formed in a continuous layer oftypically 4-15cm for commercially considered deposits, on theflanks of seamounts, ridges and undersea volcanoes.
Polymetallic sulphides are often associated with activehydrothermal vents, occurring as muds or hard consolidated
deposits depending on their mixture with sediments, and someconcern has been raised over the potential for mining of these
deposits to impact on the unique ecosystems associated withhydrothermal vents (although only inactive vent deposits are
currently being considered).
Table 1. Deep ocean resource classifications
Resource type
Description
Hard surface layered deposits containing
Cobalt-rich
Mn, Fe, Cu, Ni, Co, Zn
crusts(depth ~ 800 – 3000m)“Potato-like” nodules on seabed containing
ManganeseMn, Fe, Cu, Ni/Co, Zn (5-15 kg / m2 seabed)
nodules(depth ~ 4000-6000m)
Seafloor
Surface layered deposits formed aroundmassivehydrothermal vents, containing Mn, Fe, Cu,
sulfidesNi, Co, Zn (depth ~ 700 – 2400m)
3. Discussion
The technological components of deep ocean mining are
all individually feasible from a technical perspective, but as awhole the economic operation is yet to be proven. Depth, gradeand form of the deposit are important characteristics
influencing the potential environmental impacts associatedwith extraction and the economic viability. In comparison withabove-ground resources, the reduction in blasting requirement,
and minimal overburden (in many cases) can possibly reducethe mining impacts. However, the greater the depth, the higher
the impact of the pumping processes to transport the ore to thesurface. For a depth of 1500m, this results in estimated mining
energy 2-3 times, and emissions of greenhouse gases 2-4 times
that of land-based ores (based on estimations of existingstudies [1, 2]). Increasing the depth significantly increases that
impact. Importantly, there are limitations on the potential tomitigate such impacts by, for example, utilizing renewableenergy – as the distance offshore is generally quite far, and thedepth of the water makes floating installations difficult.
After extraction and transportation to land, the processingthese deep ocean minerals is typically quite similar toland-based ores, hence the grade and specific mineralcomposition will be the key determining factors in theminerals-processing stages of the life cycle. Typically higher
grade deposits are likely to reduce such impacts. The treatment
and disposal of wastes from the process is a key area ofconcern.
Despite being able to give a quantitative estimate of many
impacts on the environment, the impact on deep ocean
biodiversity is controversial and unclear. Many deep ocean
ecosystems are locally specific, and the extraction of minerals
is likely to cause significant damage which in some cases willbe irreversible. Environmental management plans are being
developed, but it is uncertain what level of disturbance or lossof biodiversity can be classed as acceptable.
On the social pillar of sustainability, the identification of,and interaction with, stakeholders is an important aspect forconsideration. In particular, mining in “The Area” beyond theboundaries of national exclusive economic zones is remote,uninhabited, and recognized as being the common heritage ofhumanity – requiring a very broad consultation that has yet to
be undertaken. The ongoing social license to operate is
uncertain in such context.
4. Conclusions
Some of the life cycle impacts of deep ocean resources
will be highlighted in the poster presentation of this paper.
Importantly, the lifecycle requirements for energy and theemissions of greenhouse gases will be compared withland-based minerals.
Acknowledgments
Funding for this project has been supplied by a research
grant from the Japan Society for the Promotion of Science anda travel grant from the University of Queensland.
References[1] McLellan, B.C., et al., Renewable energy in theminerals industry: a review of global potential. Journalof Cleaner Production, 2012. 32(0): p. 32-44.
[2] Nautilus Minerals. Nautilus Minerals Inc. - Solwara I
Project. 2013 [cited 2013 April 8]; Available at:
http://www.nautilusminerals.com/s/Projects-Solwara.asp.

�������������������������������������������������

30A2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan133

Indicators for environmental impacts at mine sites: Case studies for large-scale
underground mines
Shinsuke Murakami*1, Tsuyoshi Adachi2, Yoshihiko Wada3 and Satoshi Kojima4
1 The University of Tokyo, Japan; 2 Akita University, Japan; 3 Doshisha University, Japan, 4 Institute for Global Environmental Strategies*Corresponding author: smurakam@sys.t.u-tokyo.ac.jp

1. Introduction
Discussion on decoupling resource use and its negativeenvironmental impact from economic growth has attracted
great attention recently. Unfortunately, we have not found out
any absolute answer to how we achieve this goal. Accounting
the environmental impacts in the resource extraction stage is
one of our important jobs. However, in the LCA context, eventhe inventories for a specific type of resource may vary amongsites. Therefore the impacts of course vary. Mining operation isalways forced to be adapted the situation of the mine. Recently,
decreasing grade and increasing depth of the operation are twohuge concerns for the industry. These issues require the mines
to change their methodology sometime and eventuallyenvironmental impacts will change.
In this paper, we analyze one specific case study withthree different approaches; TMR (Total Material Requirement),
CO2 emission and EF (Ecological Footprint.) These three are
not necessarily the environmental impact indicators, however,somehow widely applied and common. In this extended
abstract, we will organize the characteristics andmethodologies and lead the pros and cons for all three
approaches. Results of our case study will be introduced in theoral presentation.

3. EF (Ecological Footprint)
It can be defined as follows; the corresponding area of
productive land and aquatic ecosystems required to produce theresources used, and to assimilate the wastes produced, by adefined population at a specified material standard of living,wherever on Earth that land may be located. [4] This indicator
works well to see the overall sustainability. However, thisindicator also has some shortcomings to capture the delayed
impact from our activity. For now, most of EF analysis
depends on the NFA (National Footprint Account) data, which
is on a single year basis. If an impact caused by our current
activity will occur in next year, the impact will not be
accounted. Once again, the dynamic nature of mining activities
seems difficult to be analyzed with this methodology.
4. Conclusion
As mentioned, all three approaches show the difficulty toappropriately account for the impacts throughout the lifecycleof the mine. Environmental impacts vary among sites, but also

2. TMR (Total Material Requirement)
TMR is originally designed as the indicator in the EWMFA (economy wide Material Flow Analysis,) which accounts
all the material flows caused by the economy’s activity
including hidden flows. [1] The hidden flows include stripping,wastes or tailings for resources. Some researchers realize thischaracteristic may be useful for first order estimation of theenvironmental impacts of mining, because it can reveal the real
size of activities. Bringezu et al. provided the rationale tounderstand TMR as an environmental impact indicator. [2] In
this context, methodologically, TMR is quite close to theecological rucksack. All we have to do is to account all thematerial flow caused by the production of our concerned
resources. In the case of metals, we often set the material
production as the system boundary and to see how much offlows caused for the production of 1 unit of the material.
EW-MFA is originally a static snapshot analysis. However, thecaused flows significantly change in the stage of the mining
operation. Some flows may be generated even after the mineclosure. [3] Therefore biggest issue is the correct accounting
for this indicator for now.
3. CO2 emission
We already have various inventory databases for thisindicator. However, it is not necessarily sufficient, because theoperation is always changing due to the situation of the mining
sites. From our case study, the electricity use and fuels fortransportation cause most of the CO2 emissions from mining
activities. Difficulty exists once again in the consideration of
dynamic nature of mining operation. Annual CO2 emission canbe relatively easily accounted but, it may change as operation
proceeds. For example, if the pit becomes deeper, simply thetransportation distance of the mined ore will become longer.
Also, it drastically changes if mining method is changed.

Figure 1. Example of the difference of impacts in stages

among the stages. (Figure 1.) However, considering ourultimate purpose is to assess the sustainability, our interests
surely exist in the dynamic analysis. In the oral presentation,
we will discuss these points with the case study. A case study
for underground mining reveals another concern for accounts.
Recently, the number of large-scale underground mines isincreasing. But the land use change is hardly accountable and
TMR often decreases comparing to large-scale open pit mining.
Obviously we need some method to compare the impacts ofunderground and surface mining appropriately.
Acknowledgments
The authors acknowledge the financial support from the
Ministry of the Environment Japan (MOEJ) under the projectof Policy Study on Environmental Economics (PSEE).
References
Eurostat, ed. 2001. Economy-wide material flow accounts
and derived indicators: A methodological guide. Eurostat,
Luxembourg.
[2]
Bringezu, S., et al. Journal of Industrial Ecology 7(2),43-64, 2003
[3]
Koide, R., et al., Mine Water and the Environment, 31 (4),287-296, 2012
[4]
Rees, W. E., Population and Environment 17 (3), 195-215,
1996
[1]

�������������������������������������������������

30B1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

134

Repercussion Effects of Final Consumption on Production and Environmental Loads
Using a China-Japan Waste Input-output Table
Makiko Tsukui,*1 and Chen Lin2
1

Tokyo International University, Japan; 2Shandong University, China*Corresponding author: makiko@tiu.ac.jp

1. Introduction
The economic relationship between China and Japan is
one of the most important bilateral relationships in East Asia.
China has mainly exported goods and services to supplement
final demand in Japan, while Japan has mainly exported goods
that are required as intermediate inputs for industries in China.
Consumption in Japan directly and indirectly induces both
economic benefits (e.g., production, employment) andenvironmental loads (e.g., CO2 emissions, waste generation) in
China. The issue of production activities in China inducing
large amounts of GHG emissions for exports has been
extensively examined in empirical investigations [1-3].
However, the amount of waste generated in China by industrial
sectors that produce products to satisfy the demand that is
induced by consumption in Japan has not yet been clarified. We
therefore investigated the direct and indirect effects ofconsumption in Japan on the Chinese economy and on
environmental loads, particularly in the area of waste
generation. To this end, we compiled a China-Japan waste
input-output table for 2007 (CJWIOT 2007) and examined thedifferences in the types and amounts of waste generated by theindustrial sectors of China and Japan.
2. Model and data
The model described in this study is essentially based on
the MRWIO model of Kagawa et al. [4], which itself is an
expansion of the conventional MRIO model of Isard [5] andthe WIO model of Nakamura and Kondo [6].
Table 1. The basic structure of the CJWIOT 2007

to estimate MSW generation and waste treatment.
3. Repercussion Effects of Final Consumption in China andJapan
Figure 1 shows the results of the repercussion effects offinal consumption in China and Japan. The 74 billion
dollars-worth of final consumption imported into Japan from
China induced considerable production value in China, whichis accompanied by large environmental loads.

Figure 1. Repercussion effect of final consumption in Japan
6. Conclusion
The repercussion effects of final consumption in Japan on
China are considerably larger than the repercussion effects ofChina on Japan, both economically and environmentally. Large
imports of textile products by Japan from China induced
production value, not only within the textile industry, but also
in the chemical and agricultural industries. The repercussion
effects associated with the importation of textile products by
Japan from China induced large amounts of GHG emissions
and waste generation. It is considered important to improve theenergy efficiency in the extraction of “petroleum and coalproducts” and in “electricity and heat supply” sectors in China.
In order to reduce waste generation in China, it will benecessary to improve the efficiency of the mining and heat
supply industries in China.
Acknowledgments
This work was supported by a JSPS KAKENHI Grant (No.
23510051). We would like to thank Ms. Kaiyan Ji, Mr.
Xiaoliang Lang and Mr. Takazumi Sato for their kindassistance with the compilation of the Chinese part of the
China-Japan WIO table for year 2007 employed in this study.

The Japanese and Chinese parts of the CJWIOT 2007 eachhave 30 industrial sectors, but the number of waste categories
differs between the two countries. The Japanese part has 49
municipal solid waste (MSW) categories and 19 industrial
waste categories. The Chinese part has 29 MSW categories but
only four industrial sectors: “smelting waste”, “fly ash”, “slag”
and “other industrial waste”. To compile this table, we used the“Japan-China international input-output table 2007” (METI,
Japan), “Japanese input-output table 2005” (MIC, Japan),“Industrial waste generation and treatment survey 2007”(Ministry of the Environment, Japan), “Chinese input-output
table 2007”, “China statistical yearbook on environment 2008”,“China classification garbage statistics”, “China statistical
yearbook for 2008”. We applied the model of Habara et al.[7]References[1] Guan, D., et al. Geophysical Research Letters 36, L04709,
2009.
[2] Chen, G.Q., et al. Energy Policy, 38(10), 6180–6193,
2010.
[3] Peters, G.P., et al. Environmental Science and Technology,
41, 5939-5944, 2007.
[4] Kagawa et al. Resources Conservation & Recycling, 51,
141-174, 2007.
[5] Isard, The Review of Economics and Statistics, 33(4),319-328, 1951.
[6] Nakamura and Kondo, Journal of Industrial Ecology,
6(1), 39-63, 2002.
[7] Habara et al. J. Jpn. Soc. Waste Management Experts,
13(5), 315-324, 2002.

�������������������������������������������������

30B1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

135

The Immplementaation of Finnancial Inceentive on Single-Use
S
Takeout
T
Cuup Source Reduction
R
and Reecycling in Taiwan
Wei--Kai Yang,*1 Y
Ying Hsuan Lin
L 1 and Chih-K
Ku Chen1
1

Sustain
nable Environm ental Technolog
gy and Manageement, Taiwan*C
Corresponding aauthor: greg521
10@sustainable.com.tw

1. Introductioon
Taiwan E
Environmental ProtectionP
Admministration (TEEPA)
enacted “Enfoforcement of Source
S
Reductiion and Recyccling
Incentives for Single-Use Taake-Out Cup” ordinanceoto resstrict
designated venndor (includes convenient stoore, fast-food sstore,
coffee shop aand non-alcoholic beverage shhop) to recyclee thesingle-use cupp or to encouragge consumer Brring Your Own Mug(BYOM)[1]. C
Consumers shoould be feedbacck with at leastt one
New Taiwan D
Dollar (NTD) if
i they return th
he single-use cuup to
the vendor. Foor exemption, vendorv
should offer an alternnativeplan called “soource reductionn program” to providepa favorrable
price when connsumers bring theirtown reusaable mug.
A total of 17,926 storess of 419 brandds offer discounnt to
BYOM consuumers and 70 stores of 6 brands offer usedsingle-use cupp recycling inncentive after the ordinance wasenforced. Stattistics of overaall designated vendor shows that
4.6% [2] singlle-use cup conssumption is rep
placed by BYOM
M in
2012. An averrage of 69 milllion single use cups reductionn peryear was estim
mated as a resullt of the ordinannce. The correlaation
between BYO
OM and variouus incentives is analyzed. It was
found that connsumers purchaasing at coffee shop show higghest
potential to BY
YOM.
2. Case studybconsumumers
To furtheer understand thhe correlation between
purchasing habbits and the orddinance implem
mentation outcoomes,
qualitative annd quantitative marketing research analysis was
conducted [3]..
Public poll was used for qualitativ
ve investigationn tounderstand coonsumers’ enviironmental opiinion. Field suurvey
method was uused for quantittative investigaation. The scennarios
for this investigation includee: Scenario 1 (SS1), consumers withsingle-use cuup; Scenario 2 (S2), BYOM
M consumers; andScenario 3 (S33), consumers sit-in with reusaable cup.
For qualiitative investigaation, public poll was carriedd out
by phone inteerview. The suubjects were geeneral public oof 20
years old andd above with a sampling sizze of 1,073 peeople
throughout thhe country, the confidence leevel was 95%±
±3%,completed byy May 2013. The results of the investigaation
showed that 555% of the connsumers wouldd purchase takee-out
beverages, annd 15% were willingw
to BYOOM, among whhich,coffee purchasers formed thhe major groupp, see the resullts in
Figure 1.

Figgure 1. Analysiss of questionnaiire result
For the quantitative innvestigation, data were colleectedfrom the convvenient chain stores,sbeveragge chain storess andcoffee chain stores in nearbby areas of traain stations, scchool
areas, and weell known com
mmercial shopping districts off thefive major citties in Taiwan to understand the practice off theconsumers. Samples of 4,6602 consumptio
on purchases from

September to October in 2013 were taken acccording to thee
he investigationn
threee scenarios. Taable 2 shows tthe results. Th
foun
nd that only cooffee shops proovide sit-in andd most vendorss
prov
vide consumerss beverages usiing reusable cu
ups. Therefore,,
this data analysis does not incluude difference analysisaof S3,,
le cup. Data analysis wass
consumers sit-in with reusable
ducted only forr take-away connsumer behavio
or, and includess
cond
the ratio of BYOM (R). Equatiions included the number off
consumers of S1 an
nd S2, as followws.
R � �SS� � �S� � S���� � ����(1)

Table 2. Classsification of coonsumer by studdy object
Coffee shop
Conveniennt store Beveerage store
S1 1,439
585
2,363
S2 32
21
41
S3 121
0
0
R
2.2%
3.5%
1.7%
%
Table 3. Classsification of connsumer by inceentive type
2NTD off
3NTD off
5NTD off
10NTD off
S1 2,208
791
286
1,102
S2 2
24
40
28
S3 0
22
48
51
R
0.1%
2.9%
12.3%
2.5%
3. Results
R
Consumers makingmpurchahases at coffeee shops andd
conv
venient stores are more likeely to bring thheir own cupss(2.2
2%-3.5%). Conssumers makingg purchases at beveragebstoressare less willing to bring their ow
wn cups at 1.7%
% BYOM ratio..
Thee common featture between ccoffee shops andaconvenientt
storres is that both sell coffee. C
Cross analysis withw the publicc
polll results shows that 70% of thhe consumers who
w bring theirrown
n mugs are mainnly for coffee ppurchases.
In addition, th
he amount of the incentive does not showw
signnificant correlattion to BYOM.. When vendorss come up withh
inno
ovative practices, such as inn the case off the NTD $55
disccount, vendors offer reusable PE plastic bottles along withh
disccount. Thus, th
his greatly incrreases the willlingness of theeconsumers to cooperate.
4. Conclusions
C
ow-carbon bussiness service that enhancess
Innovative lo
consumers linkagee and consumpttion reward sy
ystem is arisingg
after the ordinancee was implemennted and these operations willl
deco
ouple tradition
nal over prooduction-consum
mption modell
grad
dually that increases both the rresource utilizaation efficiencyy
and living environm
mental quality.
knowledgments
Ack
This study waas supported by the Promoting General Wastee
Work
Sou
urce
Reductiion
Related
Project
P
20133
(EPA
A-102-H101/H103-02-221) tthat is granteed by Taiwann
Envvironmental Pro
otection Adminiistration. The authors also likee
to thhank Ms. Chin-Wei Tang for hher supports in thet work.
Refferences[1]] Taiwan EPA
A, Disposable Products Sou
urce Reductionn
Program 2010
0, EPA-99-H1101-02-214, 201
10.
[2]] Taiwan EPA, Source reducction and prod
duct packagingg
light-weightinngennhancement
project,,
EPA-100-H10
01-02-221, 20112.
[3]] Dawn Iacobu
ucci, Gilbert Chhurchill, Markeeting Research::
Methodologiccal Foundation..

�������������������������������������������������

30B1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

136

Environmental impacts assessment of plastic waste in Thailand

Unchalee Suwanmanee, 1 Thanawadee Leejarkpai, 2 Wanwilai Kraipech Evans,1
Shinatiphkorn Pongpinyopap,3 and Thumrongrut Mungcharoen, *3
1

Department of Chemical Engineering, Faculty of Engineering, Srinakharinwirot University,
Nakhon-nayok 26120 Thailand

2

National Metal and Materials Technology Center, National Science and Technology Development Agency,
Pathumthani 12120 Thailand,
3

Department of Chemical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900 Thailand,*Corresponding author: fengtrm@ku.ac.th

2.1 Goal and scope of the study
The scope of the study was shown in Figure 1. The
functional unit was set as 1% of total plastics waste in Thailand
or 2.22 104 tons in each year.

impact values were obtained by the increasing of compostingrate. The total GWP impacts of PLA and PLA in scenario 2
were significantly decreased by 60.8% and 23.8% of the total
GWP impact of PLA and PLA in scenario 1 respectively. It
clearly seen that the impact value during resin production
exhibited the most important contribution as 57-97% of thetotal GWP impact of PLA and PLA boxes. Figure 3 showedthat the land use impact from both scenario 1 and 2 were very
highest impact for PS boxes about 2.073  106 m3 per year.
This is because of PS is not degraded under real landfill andcomposting conditions.
4.0.E+04

Total

3.0.E+04
tons CO2 eq. per year

1. Introduction
Currently, the annual Municipal Solid Waste (MSW)
generation in Thailand was 14 million tons. About 15.88% of
total MSW was accounted as 2.22 million tons of plastics waste
which need to be disposed each year. The MSW in Thailand
has been steadily increasing which bring a crisis in many areaof country because of lack of potential site for the sanitary
landfill. Nowadays, Thailand has a total of 127 waste disposalsites. Many landfill sites are now facing with the overload
capacities and will have a shorter life time than expected. In
this study was analyzed and evaluated two environmental
impacts, global warming potential (GWP) and land use
capacity of bio-based boxes, PLA derived from sugarcane(PLA) and PLA derived from corn (PLA), andpetroleum-based box, PS derived from natural gas and crude
oil. Two waste management scenarios were considered, namely
the combination of 25% composting cooperation with 75%
landfill (scenario 1), the combination of 50% composting
cooperation with 50% landfill (scenario 2).

Waste management scenarion

2.0.E+04

Packaging waste transportation

1.0.E+04

Transportation
Boxes forming

0.0.E+00

Resin production-1.0.E+04

PLA

PLA

PS

PLA

Scenario 1

PLA

PS

Scenario 2

Figure 1. The GWP impact of PLA, PLA and PS boxes.
2.5.E+04

Oil and gas explorationand production

2.0.E+04
3

Land use (m )Crop plantation and harvesting(Sugarcane and Corn)

EnergySugar production

PLA
pellets production

Dextrose production

Monomer production(styrene)

PLA
pellets production

AiremissionsPSpellets production

1.5.E+04
1.0.E+04
5.0.E+03
0.0.E+00

PLA

Water
Box forming of PLA, PLA and PS boxes

Water
emissions

PLA

PS

PLA

Scenario 1

PLA

PS

Scenario 2

3

Figure 2. Land use capacity (m ) of PLA, PLA and PS boxes.
Use by consumer
Rawmaterials
Disposal of PLA, PLA and PS boxes
1) 25% Composting 75% real landfill 2) 50% Composting 50% real landfill

SolidwastesFigure 1. System boundary of PLA, PLA and PS boxes.
3. Results and Discussion
3.1 Life Cycle Impact Assessment or LCIA
It was found that the PLA in scenario 1 contributed thehighest GWP impact of 3.45  104 tons CO2 equivalent per year
as shown in Figure 2. In scenario 1, PLA revealed higher the
total GWP impact than PLA  and PS by 2.5 and 2.8 times
respectively. This was because of the high amount of GWP
impact of PLA during resin production of 3.37  104 tons CO2
equivalent per year or 97% of total GWP impact. It can beobserved that the increasing of 50% composting rate (50C/50L)
give significantly different value of the total GWP impact of
25C/75L. The significant and benefit effect on the total GWP

4. Conclusion
It was found that the PLA in scenario 1 contributed thehighest GWP impact of 3.45  104 tons CO2 equivalent per
year. The significant and benefit effect on the total GWP
impact values of PLA and PLAwere obtained by theincreasing of composting rate. PS in both scenario 1 and 2
showed the highest land use capacity of 2.073  106 m3 peryear.
Acknowledgments
This work has been supported by Faculty of Engineering,
Srinakharinwirot University and Kasetsart University, Thai
Research Fund (TRG5780114) and National Science andTechnology Development Agency (NSTDA) Fund.
References[1] PCD., Information & services solid waste generation in
Thailand. 2012.

�������������������������������������������������

30B1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

137

Assessing Environmental Impact of Fiber Reinforced Plastic Table Top Product Mixed
With Non-Metallic Fraction from Printed Circuit Board Waste
Sawanya Jareemit,1 Suphaphat Kwonpongsagoon,*1 and Premrudee Kanchanapiya2
1

Department of Sanitary Engineering, Faculty of Public Health, Mahidol University, Thailand;
National Metal and Material Technology Center, National Science and Technology Development Agency, Thailand*Corresponding author: suphaphat@hotmail.com.

2. Methodology
According to the ISO 14040 and 14044 [3-4], Life Cycle
Assessment (LCA) methodology is used in this study toevaluate the environmental impact from a gate-to-gate of the
new FRP product. The functional unit of this LCA study is 1x1
m2 of a table top product. The data used in life cycle inventory
was primarily collected from F.R.P. Industry Co., Ltd. anddatabases provided in SimaPro software Version 7.3. The
World ReCiPe Midpoint impact assessment method wasapplied to estimate the environmental impacts of this product[5].
3. Results and Discussion
The LCA results of the new FRP using the World ReCiPe
Midpoint impact assessment method result in six damage
categories. These consist of human toxicity, marine ecotoxicity,
climate change, fossil depletion, ionising radiation and metal
depletion (see Figure 1). It shows that the highest
environmental impacts of the new FRP product are human
toxicity and marine ecotoxicity, accounting for 480.2 kg
1,4-DB eq and 372.1 kg 1,4-DB eq, respectively. These twoenvironmental impact categories are the most concern as the
production process of this new FRP product is achemical-based process and labor intensity, as mentioned
above. In order to study the environmental impact related toMetaldepletion(kg Fe eq)

Ionising
radiation(kg U235 eq)

Fossildepletion(kg oil eq)

500
400
300
200
100
0

Climatechange(kg CO2 eq)

raw material use of the new FRP production process, all raw
materials were assessed and divided into 4 groups: 1) polyester
resin, 2) styrene monomer, 3) glass fiber, and 4) others
including electricity and water consumption, acetone andhardener. The comparison of environmental impacts between
these raw materials is shown in Figure 2. About 80-90% ofeach environmental impact category results from polyester
resin which is used as a raw material in the FRP process, whencompared to other raw materials, like styrene, glass fiber, andothers.

Figure 1. Environmental Impact of a new FRP product byWorld ReCiPe Midpoint impact assessment method
100%
90%

Metal
depletion

Fossildepletion

Styrene monomer

Ionising
radiationpolyester resin

Climatechange70%

Marineecotoxicity

80%
Human
toxicity

1. Introduction
Non-Metallic Fraction (NMF) is non-valuable waste fromthe copper recovery process of Printed Circuit Board Waste(PCBW). According to waste management options, we tried to
study the potential of NMF recycling from PCBW as a
substitution material in a Fiber Reinforced Plastic (FRP)
furniture product. Normally, the FRP furniture products in
Thailand consist of 3 main layers [1]. For top and bottom
layers, they are laminated structure of polyester resin and glass
fiber made by a hand lay-up technique. In the middle layer, aplywood or particle board is used to increase the thickness of
product. According to our study, it is possible to use NMF fromPCBW recovery process replaced plywood in a traditional FRP
product. Since the NMF is a powder therefore it was mixed
with polyester resin and other additives (styrene monomer andmethyl ethyl ketone peroxide as hardener) and casting in mold.
Focusing on the hand lay-up process of FRP laminate and themixing and casting processes of NMF, there are many
chemicals that used in the production process. Moreover theprocess depends on labor intensity. So these may cause thehuman toxicity such as skin irritation, allergic reaction, andburn [2], as well as a chemical contamination to thesurrounding that would effect to the environmental toxicity.
Therefore the objective of this paper is to investigate theenvironmental aspects of a new FRP product (FRP productmixed with NMF) by applying Life Cycle Assessment (LCA)
methodology. This study is the part of a whole research projectwith the National Metal and Materials Technology Center,
carried out in co-operation with the SMEs companies inThailand.

Humantoxicity(kg 1,4-DB
eq)
Marineecotoxicity(kg 1,4-DB
eq)

2

Glass fiber

OthersFigure 2. Environmental Impact related to raw materials
4. Conclusion
In conclusion, the highest environmental impacts of a 1 x
1 m2 FRP table top product mixed with NMF from PCBW
recovery process are human toxicity and marine ecotoxicity. It
was also found that polyester resin is the most potential raw
material contributing to all environmental impacts.
Acknowledgments
The authors would like to thank NSTDA University
Industry Research Collaboration (NUI-RC) for researchfunding, and Chatumit Recycle Company and F.R.P. Industry
Co., Ltd for their data support in this study.
References[1] F.R.P. Industry Co., Ltd., Thailand. Interview. 2013.
[2] Cao, L. Y., Sood, A., Taylor, J. S. Hand/Face/Neck
Localized Pattern: Sticky Problems-Resins. Dermatologic
Clinics 27(3): 227-249, 2009.
[3] ISO. ISO 14040: Environmental management-Life Cycle
Assessment - principles and framework. 2006.
[4] ISO. ISO 14044: Environmental management-Life Cycle
Assessment - Requirements and guidelines. 2006.
[5] PRé Consultants, SimaPro LCA software, Netherlands,
2010.

�������������������������������������������������

30B2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

138

WEEE management in Lombardia region (Italy): an LCA-based evaluation
Laura Biganzoli1, Alida Falbo1, Federica Forte1, Lucia Rigamonti*1 and Mario Grosso1
1
Politecnico di Milano, Italy*Corresponding author: lucia.rigamonti@polimi.it

1. Introduction
Waste electrical and electronic equipment (WEEE) is oneof the fastest growing waste streams in Europe. It is strategic
not only because of the presence of hazardous substances,which require a great attention during treatment and disposal
operations, but also for its high content of recyclable materials[1]. With regard to this aspect, Life Cycle Assessment (LCA) isa fundamental tool to assess the environmental benefits andburdens associated with WEEE management; however, most of
the works available in the open literature focus on a specific
WEEE product [2, 3] and only few of them extend theevaluation to the whole WEEE collection and recovery systems
on a given geographical area [4].
2. Material and methods
This research investigates the WEEE management system
in Lombardia Region (Italy). The focus is on two WEEE
categories: TV and monitor, and small household appliances(which includes the IT and telecommunication equipment, theconsumer equipment, the electrical and electronic tools, toys,leisure and sports equipment).
The aim of the research is to quantify the environmental
benefits/burdens associated with the treatment and the recoveryof these two WEEE categories. The LCA methodology isapplied to evaluate the current management in Lombardia
Region and identify possible improvements.
The functional unit is defined as 1 kg of collected WEEE.
The system boundaries include the collection, thepre-processing and the treatment of the waste, thedisposal/treatment of the residues and the recycling of therecovered materials, accounting for the benefits of theconsequent substitution of primary raw materials and energy.
The WEEE flows from the collection platforms to the firsttreatment plants were assessed by means of the official regional
database. The most important treatment plants were identified
and visited, in order to gather primary data about the process
layout, the energy and material consumption, and the material
flows in output. As an example, the main outputs of the firsttreatment of small household appliance are reported in Figure 1.
Primary data were also collected about the destination of the
WEEE components separated after the first treatment and theirsubsequent recovery processes. This means that the inventory
is mostly based on primary data, reflecting the real
management system implemented in the region under study.
When primary data were not available, data from literature
were used.
The model was implemented in the SimaPro software. For
each process, a new dataset was designed, including thesubstituted avoided materials, with the same approach adopted
in previous studies [5, 6].

Figure 1. Small household appliances treatment outputs (wt.%)
3. Conclusions
The detailed material flow analysis performed has allowed
the identification and quantification of the materials recoveredby the treatment of TV and monitor and small household
appliances. The subsequent LCA has quantified the impacts
associated with this treatment and the benefits associated withthe recovery of material and energy. Recommendations wereadvanced to improve the environmental performances of thesystem currently implemented in Lombardia Region.
Acknowledgments
The authors wish to thank all plant operators who havesupplied primary data for the LCA.
References[1] Bigum, M., Brogaard, L., Christensen, T.H.. Metal
recovery from high-grade WEEE: a life cycle assessment.
Journal of Hazardous Materials 207-208: 8-14, 2012.
[2] Lu, L.T., Wernick, I. K., Hsiao, T.-Y., Yu, Y.H., Yang,
Y.M., Ma, H.-W.. Balancing the life cycle impacts ofnotebook computers: Taiwan’s experience. Resources,
Conservation and Recycling 48: 13-25, 2006.
[3] Park, P.J., Tahara, K., Jeong, I.T., Lee, K.M.. Comparisonof four methods for integrating environmental andeconomic aspects in the end-of-life stage of a washingmachine. Resources, Conservation and Recycling 48:
71-85, 2006.
[4] Wäger, P.A., Hischier, R., Eugster, M.. Environmental
impacts of the Swiss collection and recovery systems for
Waste Electrical and Electronic Equipment (WEEE): A
follow-up. Science of the Total Environment 409:
1746-1756, 2011.
[5] Rigamonti, L., Falbo, A., Grosso, M.. Improving
integrated waste management at the regional level: thecase of Lombardia. Waste Management and Research
31(9): 946-953, 2013.
[6] Giugliano, M., Cernuschi, S., Grosso, M., Rigamonti, L..
Material and Energy recovery in integrated waste
management system. An evaluation based on life cycle
assessment. Waste Management 31: 2092-2101, 2011.

�������������������������������������������������

30B2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

139

Investigation of Effects of Waste Recycling from Food Supply Chain Using Hybrid
AnalysisTamon Maruyama,* Jun Nakatani, and Yuichi Moriguchi
The University of Tokyo, Japan*Corresponding author: maruyama@env.t.u-tokyo.ac.jp
1. Introduction
Food recycling law and containers and packaging
recycling law in Japan have some problem, so there is room for
improvement on these laws.
So our research objective is to evaluate effects of whole
existing industries by recycling of food wastes and containers
and packaging wastes attendant on foods, and then compare
scenarios with current recycling system.
2. Method
It is effective to use bottom up approach for analyzing
individual recycling technology or wastes treatment system,
while using Input-Output analysis is valid for evaluating effectsof whole existing industries by recycling of food wastes andcontainers and packaging wastes attendant on foods.
So we used Integrated Hybrid Analysis which is themethod for calculating environmental load discharged fromwhole supply chain without overs and shorts by making up
information which is not written in process data for bottom up
approach from Input-Output table.
3. Connection between process data and IO table
Suh and Huppes [1] formulized the method to calculate
environmental load by using Integrated Hybrid Analysis.
𝑀𝑀𝐼𝐼𝐼𝐼 = 𝐵𝐵𝐼𝐼𝐼𝐼 𝐴𝐴𝐼𝐼𝐼𝐼 −1 𝑘𝑘𝐼𝐼𝐼𝐼−1
̃̃
𝑌𝑌 ] [𝑘𝑘̃] (1)= [𝐵𝐵 0 ] [𝐴𝐴
0 𝐵𝐵 𝑋𝑋 𝑋𝑋 𝑋 𝑋𝑋
0𝐵𝐵̃, 𝐵𝐵 are environmental matric for process data and IO
table, 𝐴𝐴̃, 𝐴𝐴 are technology matrix, 𝐼𝐼 is identity matrix, 𝑘𝑘̃ isan arbitrary vector, 𝑋𝑋 is upstream cut-off flows from IO tableto process data, Y is downstream cut-off flows from processdata to IO table.
Specifically, 𝐴𝐴𝐼𝐼𝐼𝐼 is written in matrix form as follows.
Table 1. 𝐴𝐴𝐼𝐼𝐼𝐼 in matrix form

In Table 1, Sector A and B are sectors of process data, andSector 1, 2, and 3 are sectors of IO table.
4. Case study
Using Integrated Hybrid Analysis, we calculated CO2
emission when we bought one lunch and one canned aluminum
drink and took out lunch and drink by using plastic bag. And
then, we analyzed change of CO2 emission when lunch box or
aluminum can or plastic bag was recycled.
We can analyze about reusing, recycling, waste fromhousehold, separating action of consumer, imported material byIntegrated Hybrid Analysis.
When we took note of canned aluminum drink, flow ofcanned aluminum drink was written as figure 1.

Figure 1. Flow of canned aluminum drink
Then we are going to show the matrix which is made bytransforming process data of canned aluminum drink into
matrix form. That matrix corresponds 𝐴𝐴̃ in formula (1).
Table 2. Matrix form of canned aluminum drink

Value of elements shows the amount of flow of material.
Red elements show input of goods and services, blue,
light blue, and yellow elements show production of goods andservices, and green elements show recycling. And we canchange value of yellow elements by scenario.
We made same type of matrix of lunch and plastic bag,and connected them. Then we can get matrix 𝐴𝐴̃, so we cancalculate CO2 emission discharged from whole supply chain byformula (1).
In the result, electricity and transportation sector in the IO
sector, and new metal importing sector in the process data
sector have large CO2 emission. When recycling is done, CO2
emission from IO sector seldom changed, however CO2
emission from new metal import sector largely decreased.
4. Future plan
We are going to collect process data using inventory
database and data about environmental load by statistic, andevaluate effects of reduction of environmental load byrecycling food wastes and containers and packaging waste.
And then, we are going to make recycling scenarios not only
for containers and packaging wastes but also for food wastes
References[1] S. Suh, G. Huppes, Methods for Life Cycle Inventory of a
product, Journal of Cleaner Production, 13, 687-697,
2005�������������������������������������������������

30B2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan140

Climate Co-Benefit from Improving Food Waste Management: A Case of Small
Communities in Thailand
Amornchai Challcharoenwattana,*1,*2 Chanathip Pharino,2,31International Postgraduate Programs in Environmental Management, Graduate School, Chulalongkorn University, Thailand
2

Center of Excellence on Hazardous Substance Management (HSM), Chulalongkorn University, Thailand

3Department of Environmental Engineering, Faculty of Engineering, Chulalongkorn University, Thailand*Corresponding author: amornchai.c@student.chula.ac.th
1.

Introduction
Higher levels of urbanization are often accompanied withhigher activities on MSW generating but lesser percentage offood waste in the waste stream1. Interestingly, percentage offood waste in Thailand’s MSW stream seemed to be increasedin the same direction with the level of urbanization. Thiscondition does not agree with the global trend as Thailand’s
percentage of food waste in all town sizes remained at similarlevel2. This trend posts significant concerns as decompositionof food waste in landfills under anaerobic condition can
produce greenhouse gas emission up to
0.945 tons CO2 eq
of 1 tons landfilled food waste. Therefore, GHG emission fromfood waste, under doing-nothing condition, will worsen climatechange problem but can also help to shed GHG contribution if
the food waste is managed in appropriate manner. Hence,scenario developments and analyses for food waste
management are needed in order to extend the concept ofclimate co-benefit to strengthen supports for waste
minimization especially when 74.76% of all Thai population
has resided in small towns.
2.

Methodology
Four food waste management scenarios were developed
based on the following conditions: completely landfilled offood waste (s1), 30% of food waste was fermented to produce
biogas at home and 70% of those were collected and thenlandfilled (s2), and 30% of food waste was composted on-siteor at community center and 70% of those were collected andthen landfilled (s3), and the dehydration of food waste by 20%
by sun-drying and then collected to be landfilled (s4). The
functional unit for this study was defined as 1.740 tons/day ofthe mean daily food waste generation from 1,020 small
municipalities in Thailand with registered population of
5,000-10,000. For the transportation part, the waste collection
system was based on a standard 6-wheel garbage collection
truck with the carrying capacity of 5 metric tons. Daily MSW
collection route within the city was defined at 20 km and the
distance between the city’s perimeters to landfill is 5 km.
Emission factors from Thailand Greenhouse Gas Management
Organization were primary employed before emission factors
from other sources were employed.

4.

Conclusion
Overall, GHG reduction in (s2) and (s3) were found at thesimilar level. Therefore, both options can be selected tobased-on the need of soil amendment (s3) or energy (s2) of thecommunity. Removal of moisture by residents prior to waste
collection (s4) may be more appropriated if the demand forenergy/soil amendment is not met.
Acknowledgments
The authors would like to acknowledge and thank research forfinancial supports from CEHSM CHULALONGKORN
UNIVERSITY and the 90th ANNIVERSARY OF
CHULALONGKORN
UNIVERSITY
FUND( Ratchadaphiseksomphot Endowment Fund) )References[1] Hoornweg, D., Bhada-Tata, P., 2012. What a waste : a
global review of solid waste management, Urban
development series. The Worldbank, Washington D.C.
[2] Thailand Pollution Control Department, 2004. Survey andAnalysis of Municipal Solid Waste Characteristics of all
Municiplaities in Thailand.

3.

ResultFor GHG emissions from the decomposition of food waste
and the waste collection, the baseline scenario (s1) contributethe highest GHG emission of 1.238 and 2.078 tons of CO2eq per
day respectively. In term of the ability to reduce GHGs,
employing household biogas system (s2) was able to reduce
43.62% from (s1) while composting system (s3) was able toreduce 41.83% from (s1). 20% Removal of moisture content(s4) can help to reduce 28.74% of GHGs from (s1) due to thelesser fuel consumption compared to (s1).

�������������������������������������������������

30C1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

141

Material Flow Cost Accounting - MFCA:
Simple Approach, Untapped Opportunities, Upcoming Tasks
Bernd Wagner*1

1
University of Augsburg, Germany*Corresponding author: wagner@wzu.uni-augsburg.de

1. Simple approach and communication of the MFCA idea
Since its conceptual birth in the early 1990s and its global
appearance as ISO standard 14051 in 2011 [1] MFCA has
come a long way. MFCA’s basic idea, which is easy tounderstand and to communicate, has experienced global
dissemination. This idea behind MFCA is to show material
flows in physical as well as in monetary values. Using thissimple approach MFCA integrates economic andenvironmental thinking. Its goal is to insure long-term
corporate sustainability by increasing material or resource
efficiency, decreasing the environmental burden and at thesame time saving cost. While much of the corporate world
today still sees a clear distinction between two separate views,
the economic or business view on the one hand and thesustainability or environmental perception on the other, MFCA
is based on the idea that for long-term corporate survival bothsides have to be considered in their mutual interdependence. To
this end it uses simple instruments such as material flow charts
and aggregated material flow data matrices showing their costdimension of materials used (business view) as well as their
physical properties (production, engineering, environmentalview) as two sides of the same coin. MFCA uses readily
available data from Accounting, LCA or other, compacting thisdata to indicators for managerial planning and steering
purposes.
With its international diffusion MFCA has grown inbreadth, e.g. by including social aspects of sustainability, it has
focused in-depth e.g. on waste management issues, and it has
been linked to other concepts such as Supply Chain
Management or LCA. But with these developments newquestions arise: Does MFCA, as it is generally practiced today,
meet the concept’s original expectations and opportunities?
Where is there room for further development andimprovement? Which upcoming tasks can be identified inorder to target potential opportunities of MFCA?
Despite widespread awareness of the MFCA, there is still,
extensive room for broader application and adoption and notjust in the so far predominantly targeted area of resource saving.
Main reasons why companies have not more fully implemented
MFCA is their fear that data collection will be too costly, andestablished accounting procedures will be disrupted. [ 2].
2. Opportunities of MFCA
Looking at reported MFCA applications and case studies one
can get the impression that MFCA so far mainly is used toincrease resource efficiency through waste reduction and thus
save costs [3]. This seems to be the low hanging fruit of MFCA
application. But there are a number of opportunities thatcompanies are currently missing, such as:• a stronger integration of sustainability aspects(environmental, social) into corporate decision making fromstrategies and policies to operation management• facilitating the integration of available tools: e.g.
Managerial Accounting, ERP, LCA, SNA [4], and profit fromsynergies• making use of material flow charts and data, supporting aholistic view, as a communication tool between functional
corporate departments (e.g. waste management and R&D) or

between partners along the supply chain.
• strengthening strategic resource planning and risk
assessment, e.g. through integrating criticality assessment, into
MFCA [5]3. Upcoming tasks and developments
A great number of next steps or measures are available to betaken in order to reach these opportunities. Some selected
examples from practical experiences are provided:• We show a Quick Results Assessment Tool that allows in
a two day workshop to estimate possible resource saving
potentials and to spot deficits of existing material efficiency
information regarding product material, waste, and energy.
• Most MFCA applications focus on waste reduction. But
increased resource efficiency can also be achieved by reducing
product materials, even auxiliary materials, not going to waste.
In order to uncover these hidden treasures MFCA must delve
deeper into ERP and controlling systems, allowing exact
Input-Output-Mass-Balances, for the company as a whole, forquantity centers, products, selected materials etc. MFCA canhelp companies focus on the critical and the strategicallyessential resources within the vast varieties of materials andparts.
•
Despite the fact that MFCA originated fromenvironmental management, many present applications havebeen reduced in scope to pure cost saving exercises. Yet
companies will increasingly be under strategic pressure to deal
with topics like GHG effects, Carbon and Water Footprint,
effects on eco-systems and biodiversity, on health and social
issues. MFCA has significant untapped potential to bridge thegap between financial (cost) and sustainability considerations
and to highlight the mutual interdependencies.
• A frequently neglected strength of MFCA is its use as aninterdepartmental communication tool. While many
optimization processes focus on departmental tasks, corporate
MFCA flow charts and the corresponding data show “the big
picture”, and one that is cross functional from input to output.
In addition to the listed examples above other opportunities
on hand will be identified.
References[1] ISO
14051:2011-09
Environmental
management-Material flow cost accounting - General framework[2] Wagner, B., Strobel, M., Flow Management for
Manufacturing Companies, Sustainable Re-organisationof Material and Information Flows, 2003, pdf:
www.resource-lab.de/documents/flow_management.pdf[3] Kokubu, K, Campos, M., Furukawa, Y., Tachikawa, H.,
Material flow cost accounting with ISO 14051, ISOManagement Systems – January-February , 15-18, 2009;s. also MFCA Case Examples, METI, 2010[4] System of National Accounts (SNA), using linking terms
such as stocks, movements, mass balance, s. System ofEnvironmental-Economic Accounting (SEEA),
http://unstats.un.org/unsd/envaccounting/seea.asp[5] s. Helbig, S., Extending raw material input evaluation in
the MFCA framework through implementation ofcriticality assessment, session M 1-2 in this conference.

�������������������������������������������������

30C1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

142

Extending Raw Material Input Evaluation in the MFCA Framework throughImplementation of Criticality Assessments
Christoph Helbig,*1 Christoph Kolotzek,1 Andrea Thorenz,1 and Axel Tuma1
1

Resource Lab, University of Augsburg, Germany*Corresponding author: christoph.helbig@wiwi.uni-augsburg.de
1. Introduction
Material efficiency is a main focus of Material Flow Cost
Accounting (MFCA), which provides a well-established,standardized method for evaluation within a company.
Evolving from a mass-based Material Flow Analysis (MFA) for
any process within the company or the complete company, it
allows for the identification of cost-saving efficiency
improvements by linking mass flows to costs. This material
flow data is essential for efficiency considerations and can be
the starting point for resource-based improvements.
2. Integrating Supply Chain Impacts into Material Flow
Cost Accounting Framework
Current research extends the MFCA approach to the
supply chain, collecting data even outside the company system,
looking for further improvements [1]. Due to data issues aswell as the increasing complexity, this can be very expensive.
However, this supply chain approach is essential for systemic
improvements concerning sustainable resource use.
Figure 1 displays the advantages of data exchange
between MFCA and ‘Criticality Assessments’. While MFCA isuseful for analyzing intra-organizational processes in search forcost optimization and waste reduction potential, criticality
assessments are best for estimating upstream raw material risks.
Synergies emerge from considering both evaluation methods.
- Input & output
products- Auxiliaries & wastes- Mass & value flows

Data requirements

Material flow data

MFCA

Supply chain
proxy data

- Cost optimization- Waste flow
reduction- Ecological impacts

Knowledge gained- Effective for
intraorganizational
processes

Special strengths- Production & resource
data- Supply & demand trend- Corporate input flowdata

Criticality
Assessment- Supply risk evaluation- Upstream ecologicalimplications- Social alert signals- Effective for upstreamrisk assessment

Figure 1: Relations between MFCA and Criticality
Assessments
3. Criticality Assessment as Raw Material Input Evaluation
Scarcity of metal and mineral resources in combination
with company guidelines for the security of sustainable supply
for companies is a main focus in a well evaluated project of the
Resource Lab of the University of Augsburg. The result of our
project is a criticality assessment with evaluated indicators thatcan be used by companies for sustainability evaluation of the
upstream supply chain, which is essentially determined by
input flows quantified in the MFCA.
These criticality assessments emerge from a raw material
conception involving geological, technical, political, economicand ecologic considerations [2, 3]. Indicators identified in ourwork touch the dimensions supply risk, ecological implications
and social circumstances. In the dimension supply risk, risks
emerging from the market concentration, the political situation
as well as supply reduction and demand increase estimations
are evaluated, emerging from existing supply risk evaluations[4]. The ecological dimension includes indicators about the
impacts on human health as well as ecosystem quality. In thesocial dimension indicators like the control of corruption are
considered.
These risks are valuable information for a rapid proxyevaluation in supply chain material flow cost accounting. The
quantifiable indicators are evaluated by a multi-step process,starting with the selection of relevant resources (available from
MFCA data collection [5]), continuing with the raw material
based assessment, giving information about the interpretation
within the MFCA framework, leading to decision support for
mitigation efforts. Input flow evaluation is exemplified on casestudies for companies (e.g. electronics industry).
4. Conclusion
This presented evaluation method gives companies theopportunity to use the data collected in standardized MFCA inorder to reduce the resource-based criticality of its input flows,i.e. by reducing its supply risk or the upstream environmental
and social implications. The methods presented can beextended in future research on product and waste outputs, toget a more complete view on the supply chain implications
connected to the MFCA-based efficiency improvements.
Acknowledgments
This work was supported by the German Environment
Foundation (DBU) and the Bavarian graduate school (Resource
strategy concepts for sustainable energy systems) of the
University of Augsburg.
References
1. Wagner,
B.,
M.
Nakajima,
and
M.
Prox,
Materialflusskostenrechnung – die internationale Karriere
einer Methode zu Identifikation von Ineffizienzen in
Produktionssystemen. uwf UmweltWirtschaftsForum, 2010.
18(3-4): p. 197-202.
2. Graedel, T.E., et al., Methodology of Metal Criticality
Determination. Environmental Science & Technology,
2012. 46: p. 1063-1070.
3. Reller, A., Criticality of metal resources for functional
materials used in electronics and microelectronics. physica
status solidi (RRL) – Rapid Research Letters, 2011. 5(9): p.
309-311.
4. Achzet, B. and C. Helbig, How to evaluate raw material
supply risks-an overview. Resources Policy, 2013. 38(4): p.
435-447.
5. Bensch, S., et al. Conception of a Novel Open Source
Environmental Management Information System Design toAssess the Availability of Resources: Status Quo andDirections for Future Research. 2015. Springer
International Publishing.

�������������������������������������������������

30C1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan143

Cost Accounting Instruments as Components in a Material Flow Analysis Tool-Chain
Andreas Moeller*1 and Martina Prox2
1

Leuphana University Lueneburg, Germany; 2ifu Hamburg GmbH, Germany*Corresponding author: moeller@uni.leuphana.de

1. Introduction
In the field of life cycle assessment (LCA) [1] andmaterial flow analysis (MFA) [2] several cost accounting
instruments are discussed: at least life cycle costing (LCC) [3],conventional cost accounting (based on an analysis of material
and energy flows) and material flow cost accounting (MFCA)[4]. It is more and more important to provide an integrated
approach to the economic impacts of activities within theframeworks of MFA and LCA.
2. Purposes of Cost Accounting Instruments
The concepts of instruments and the computational
structures behind are not alternative approaches to the sameproblem. The purposes of LCC, conventional cost accounting
and MFCA are different:(1) Conventional cost accounting is focused on thenegative economic impacts (costs) and positive outcomes(revenue) of management decisions [5, 6, 7]. Compared with
LCA, the accounting entities (or controlling areas) are
different: business units, production plants, single production
processes and not entire product life cycles. As a consequence,the challenges and calculation approaches [8, 9] are similar:
application of matrix methods, allocation problems, fixed costs
etc. The integration of LCA, LCC and conventional material
and energy-based cost accounting is quite simple as all
instruments use (life cycle) inventories as a starting point anddata source [2].
(2) Life cycle costing brings together different companies(business units) and their perspectives. LCC analyses the value
added, the business units realize – and not the difference ofrevenues and costs. The accounting entities in conventional
cost accounting become the nodes in life cycle costing:conventional cost accounting is embedded into LCC. As aresult, conventional cost accounting, related to accounting
entities, and LCC can be implemented as components of asingle calculation procedure [10].
(3) The purpose of MFCA is to quantify improvement
potentials. Starting point of MFCA is that unit processes can be
improved by reducing the waste streams. By reducing thewaste streams (material loss), not only the costs of waste
treatment can be reduced but also the input of raw materials
and intermediate goods [4]. Life cycle approaches are applied
to represent the means/end relationships between the final
products and required raw materials and emissions. MFCA
provides two complementary performance indicators: theproduct costs and the costs of material loss. It is obvious to use
such an approach in carbon footprinting or LCA in general. By
doing so, LCA can quantify the reduction of environmental
impacts connected of possible improvements.
1. Computational Structure of MFCA
Unfortunately, the computational structures of MFCA are
more complex. Whereas conventional cost accounting and
LCC can be realized as instruments within a life cycle
assessment tool-chain, MFCA requires preparatory material
flow analysis steps which deal with non-linear process
specifications and recycle streams [11, 12] (e.g. based on an
sequential modular or equation-based approach). In principle,
MFCA consists of two calculation steps: for default scenarios

and improved scenario, in which material loss is avoided.
When wasteful processes and in particular their material loss
are involved in recycling loops, the reduction of material canhave an impact on the steady states of the loops. For instance,
the reduction of material loss may result in reduced recycle
streams so that the production coefficients of the mixer process,which mixes the recycle streams and virgin raw materials, must
be updated.
It is necessary that the tool-chain integrates MFA and
LCA. The MFA component allows calculating all absolutematerial and energy flows, the flow properties, components andstocks for a given sequence of time periods. The data can beused to perform LCAs and cost accountings as evaluation steps.
In case of MFCA, the tool-chain has to be applied twice, andthe difference of the two scenarios quantifies the improvement
potential. Again, an integration of the instrument is possible sothat an integrated calculation procedure can determine the data
for all cost accounting instruments based on only one material
and energy flow model.
References[1] Guinée, J.B. (ed.) Handbook on Life Cycle Assessment:
Operational Guide to the ISO Standards. Dordrecht, The
Netherlands: Kluwer Academic Publishers, 2002.
[2] Moeller, A. Grundlagen stoffstrombasierter betrieblicher
Umweltinformationssystem. Bochum, Germany: Projekt
Verlag, 2000.
[3] Hunkeler, D., K. Lichtenvort and G. Rebitzer (eds.)
Environmental Life Cycle Assessment. Boca Raton,
London, New York: CRC Press, 2008.
[4] Schmidt, M. and M. Nakajima Material Flow Cost
Accounting as an approach to improve resource
efficiency in manufacturing companies. Resources 2 (3):358-369, 2013.
[5] Maennel, W. (ed.) Handbuch Kostenrechnung.
Wiesbaden, Germany: Gabler, 1992.
[6] Kilger,
W.
Flexible
Plankostenrechnung
undDeckungsbeitragsrechnung. 10th ed. Wiesbaden,
Germany: Gabler, 1993.
[7] Riebel, P. Einzelkosten- und Deckungsbeitragsrechnung.
7th ed. Wiesbaden, Germany: Gabler, 1994.
[8] Heijungs, R. A generic method for the identification of
options for cleaner products. Ecological Economics 10,
69-81, 1994.
[9] Heijungs, R. and S. Suh The computational structure oflife cycle assessment. Dordrecht, The Netherlands:
Kluwer Academic Publishers, 2002.
[10] Heijungs, R., E. Settanni, and J.B. Guinée Towards acomputational structure for life cycle sustainability
analysis: unifying LCA and LCC. International Journal ofLife Cycle Assessment 18, 1722-1733, 2013.
[11] Westerberg, A.W., H.P. Hutchison, R.L. Motard, and P.
Winter Process Flowsheeting. Cambridge, London, New
York, Melbourne: Cambridge University Press, 1979.
[12] Barton, P. I. The Equation Oriented Strategy for Process
Flowsheeting. Department of Chemical Engineering,
Massachusetts Institute of Technology, Cambridge, MA,
2000.

�������������������������������������������������

30C1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan144

New Challenge to develop Sustainable Value Chain Management by MFCA Information
Michiyasu NAKAJIMA,*1 and Asako KIMURA2
1

Kansai University, Japan; 2Kansai University, Japan*Corresponding author: nakajima@kansai-u.ac.jp

1. Introduction: Purpose of the ResearchMaterial Flow Cost Accounting (MFCA) is one of themost useful tools on Environmental Management Accounting(EMA) in practice. MFCA makes new visibility in a process onmaterial efficiency, concretely with material loss. When acompany introduces MFCA into own process and find out
some material losses, the company tries to reduce
simultaneously material losses and manufacturing costs. As aresult, the company improves material inefficiency in own
process. The reduction of material loss is evaluated as both of
economic performance and environmental one. Companies use
MFCA as EMA in own process, for example, production line.
The visibility of MFCA expands usually to supply chain
between buyer and supplier. Some material losses are
generated by transaction with supplier or customer. So MFCA
users try to improve own material losses with supplier or/andcustomer. We have researched MFCA to be developed as a toolof value chain management. MFCA methodology has
improved material in-efficiency in process that covers between
buyer and supplier. We have analyzed the relationship inJapanese listed companies and Malaysian listed companies by
Questionnaire Research. And we have conducted MFCA
project between buyer and suppliers in Japan to makecollaboration on improvement of material inefficiency insupply chain. We found new future subjects and successful
possibilities to establish Sustainability Value Chain in practice.
In Sustainability Value Chain, MFCA will be integrated
with LCA. We have researched to establish a new MFCA
method to integrate MFCA information with LCI data in some
Asian countries. And this method will be expanded to MFCA
analysis in global supply chain with LCI. This method intends
to improve or reduce CO2 emission from material inefficiency
in process.
This research shows the possibilities to develop MFCA asa new EMA tool of sustainability value chain.

The Figure 1 shows a result of case study. The member
companies made factory tour to look/check at factory
management, equipment and wastes/losses in production
process at the factories of them. As the result, the collaborative
relationship between buyer and each supplier became closer,
and new technical collaborations were occurred independently.
On the other hand, new collaborations between suppliers,
without X, were occurred on other business of suppliers, as
shown Figure 2. Usually the supplier tried to make more
appropriate product mix with other suppliers to accept an orderfrom other customers.

2. Results of Case Study between Buyer-Suppliers
The case study had been started to improve material
in-efficiency in production process by a buyer (Assembler X)
and suppliers (Supplier A, B, C and D), based on MFCA
information. All of 5 companies produce own products throughplastic injection molding process. From viewpoint of MFCA,
all companies generate the same material losses cased bymolding. To improve these material losses needs acollaboration between buyer (X) and suppliers (A, B, C, and D),
and some revolutionary technologies or production way. A
project to achieve it was established in Dec. 2011(closed in Oct.
2013), and then, periodically the project meetings were held at
the factories of 5 member companies.

Figure 3. Sustainable Value Chain Management based on the
Extended MFCA Information             
  





        







 


 


           Figure 1. Result (1)


Figure 2. Result (2)3. Conclusions
The project was intended to reduce material losses by
revolutionary technologies or production way, based oncollaboration between buyer and suppliers. But this kind ofcollaboration couldn’t be occurred in this case study, because
each supplier had original philosophy of production andproduction way. And each supplier exercised caution to othersuppliers.
MFCA can show bigger potentials of material loss
between buyer and supplier (in supply chain), fromaccumulated case examples of MFCA. To reduce material
losses in supply chain needs to share MFCA information in
supply chain, and to establish collaboration between buyer andsuppliers, based on extended MFCA information in Figure 3.
Information-Sharing between suppliers





Resources Flow
Material Loss
Energy Use

Material Loss
CO2 Emission

Material Loss
Energy Use

Material Loss
Energy Use

Material Loss
CO2 Emission

General
MFCA
Information
The 1st Step on
Sustainable
Management
Information

Acknowledgments
This research was partially supported by theEnvironmental Research and Technology Development Fund
(E-1106) of the Ministry of the Environment, Japan, and
KAKENHI (25380629), Grant-in-Aid for Scientific Research(C), Japan.
References[1] Kimura, A. and M. Nakajima. The Potential for MFCA
Spread in Supply Chains Through Information Sharing. Kansai
University Review of Business and Commerce 15: 15-35, 2014.
[2] Kokubu, K., N. Itsubo, M. Nakajima and T. Yamada.
Constructing Low-Carbon Supply Chain in Asia and the Roleof Accounting 182(1): 82-97, 2012. (only in Japanese)[3] Nakajima, M., and A. Kimura. Challenges to Implement
Material Flow Cost Accounting (MFCA) in Supply Chain
Management: Through Case Study on a Buyer-Suppliers
Workshop. The Journal of Cost Accounting Research 38(1):59-69, 2014. (only in Japanese)�������������������������������������������������

30C2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

145

Integrating LCA Into a Design Innovation Method
Jeremy Faludi*1
1
University of California Berkeley, USA*Corresponding author: faludi@berkeley.edu

1. Introduction
Companies still primarily use life-cycle assessment (LCA)
for measurement after a product has been designed, or after
idea generation—this relegates LCA to the role of gatekeeper,
which designers and engineers consider a burden on theircreativity and productivity [1]. Since most experts argue that
80% of a product's environmental impacts are set during theearly design phase [2, 3], many have tried to move LCA into
early-stage design. Past efforts have primarily focused on
making LCA easier [4, 5], improving the cost-benefit ratio bydecreasing the perceived cost. The method described here
focuses instead on increasing perceived benefit, by using LCA
to help design teams work more effectively. It also aims, assome previous tools have [6], to both lower cost and raise
benefit by smoothing communication between LCA experts
and designers.

method as providing not just sustainability but also innovation.
One representative said, "Your process was as valuable as theactual concepts it produced."

2. The Design Method
A design method was developed for the Autodesk
Sustainability Workshop [7]. It moves LCA into the earlystages of design, using LCA to set initial design specifications
which designers use to create new solutions, not just disqualify
solutions created with other methods.
The Whole Systems + Life Cycle design method (WSLC)
is a four-step process. Step 1: designers / engineers / business
managers visually map the whole system of the product orservice—all major components, sub-systems, life-cycle stages,
inputs and outputs, customer usage and context, and theconnections / flows between these nodes. (See Figure 1.)
Step 2: boundaries for LCA are drawn on the map and LCA is
performed on the system inside the boundaries. This LCA
sets the top-priority sustainability problem(s) to solve, forwhich the team sets goal(s) and concrete metrics alongside theproject's top business goals and metrics. Step 3: the teambrainstorms on their top-priority sustainability goal, using thevisual system map to facilitate the brainstorm. The map helps
designers be more thorough and more radical in their ideation.
Step 4: estimated LCAs are used to judge the brainstorm results,
fulfilling their traditional gatekeeping role. While imprecise,such estimates are still far wiser guidance than untrained
guesswork, since the designers, engineers, and businessexecutives making design decisions are not environmental
scientists but are experts in their product area.

Figure 1. Example system map showing LCA boundaries.

3. Anecdotal Trials
This method has been used at UC Berkeley, California
College of the Arts, Minneapolis College of Art and Design,
Emily Carr University, and elsewhere, with student groups
redesigning real products for real companies such as Motorola,
Steelcase, Hamilton Beach, HP, Thermarest, Oboz, Panasonic,
and several others.
Design students have shown great improvement in theirunderstanding of how to choose functional units andboundaries, as well as their ability to interpret LCA
results—even students who were previously trained in LCA.
Choosing functional units spurred and refined discussion ofwhat user needs each product fulfills, helping designers focus
their ideation. Using LCA to set priorities focused thebrainstorms. Moreover, company partners have praised the

3. Conclusion
This design method attempts to integrate LCA better into
the early-stage design process, using it to focus design teamideation and thus actually improve innovation, not merely act
as gatekeeper that is perceived as a burden. Anecdotal
evidence suggests it fulfills these goals. Further studies
should test other ways that LCA may be used to benefit designteam effectiveness, and compare design methods.
Acknowledgments
Thanks to Adam Menter and Dawn Danby of Autodesk
for their support in the development of the method.
References[1] Millet, D., et al. Does the potential of the use of LCA
match the design team needs? Journal of Cleaner
Production 15.4 (2007): 335-346.
[2] Charter, M., and Tischner, U., eds. Sustainable solutions:developing products and services for the future. Greenleaf
publishing, 2001.
[3] Lagerstedt, J., et al. Functional priorities in LCA anddesign for environment. The International Journal of Life
Cycle Assessment 8.3 (2003): 160-166.
[4] Lu, B., P. Gu, and S. Spiewak. Integrated Life Cycle
Design Approach for Sustainable Product Development.
Proceedings of the Canadian Engineering Education
Association (2011).
[5] Keoleian, G. The application of life cycle assessment todesign. Journal of Cleaner Production 1.3 (1993):
143-149.
[6] Rio, M., et al. A framework for ecodesign: an interface
between LCA and design process. Conference MOTSP
2010: Management of Technology, Step to sustainable
Production, Rovinj, June 2010.
[7] Autodesk, Inc., Autodesk Sustainability Workshop.
http://sustainabilityworkshop.autodesk.com/products/who
le-systems-and-lifecycle-thinking (Accessed 13 /62014).

�������������������������������������������������

30C2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan146

Product and Organisation Environmental Footprint – Challenges in theory and practice
Annekatrin Lehmann,*1, Vanessa Bach1, Matthias Finkbeiner1
1Technische Universität Berlin, Germany,*Corresponding author: annekatrin.lehmann@tu-berlin.de
1. Introduction
ISO 14044:2006 is a standardised method to assess arange of potential environmental impacts of products andservices [1]. It is transparent, worldwide used and accepted
throughout policy and in the market and can amongst others beapplied for environmental labeling of products, e.g. as basis for
type III label. In 2013 the European Commission published theProduct and Organisation Environmental Footprint (PEF/OEF)
methodology ‒ a life cycle based multi-criteria measure of theenvironmental performance of products, services andorganisations [2] developed as part of the 2020 European
strategy “A resource efficient Europe”. It aims at harmonisingexisting methods, while decreasing the flexibility provided by
the ISO standards regarding methodological choices. Currently,
a three year pilot phase is running, aiming at testing themethodology and developing product category andorganisation sector rules (PEFCR/OEFSR). The first
PEFCR/OEFSR drafts of the pilots from the first wave (start:
Nov 2013) were publicly consulted in May/June; first drafts
from the 2nd wave pilots (start: June 2014) are expected to beavailable also this year.
2. Analysis of the PEF/OEF method and identification ofchallenges
The idea of a harmonised, life cycle based method
enabling comparisons of products/organisations within thesame product category/sector is principally good. However, itis accompanied by various risks and challenges andcontroversially discussed by organizations, associations,science etc. In order to identify the challenges, a thoroughanalysis comparing ISO 14044 and PEF/OEF methodology
was conducted. Moreover, the ongoing pilot phase is followed
and the first PEFCR drafts were evaluated – again aiming at
highlighting challenges. Based on these analyses
recommendations for adaptations of the PEF/OEF
methodology and pilot phase were formulated.
3. Results
It was found, that the PEF/OEF methodology shows
various differences to ISO 14044 – it is e.g. communication
driven – and that some methodological aspects of the PEF/OEF
methodology are even contradictory to ISO 14044, e.g.:allowing for weighting of LCA results to single
scores orproviding predefined impact categories and a fixed
EoL formula.
These differences and contradictions may cause confusionand proliferation rather than harmonisation. Moreover, many
aspects seem to be hardly applicable in practice, e.g.:
exclusion of cut-off criteria,
use of certain predefined impact assessment methods– some, for which only insufficient inventory data
exists (PM10, land use)
Also, it is unclear which measures might be appropriate tocommunicate the results, how the intended benchmarks andenvironmental performance classes will be defined and if the
PEFCRs/OEFSRs will be indeed a suitable basis for comparisons and comparative assertions of products/organisations [3].

Besides this, following main criteria need to be considered
for the success of the PEF/OEF methodology: consistency ofpilots, clear goal formulation and measurable added value
compared to existing systems for environmental analysis anddeclaration. However, with regard to first results of the pilot
phase, namely the definition of the scope in the particular
PEFCR drafts, none of these criteria seem to be fully met.
Some general challenges and inconsistencies between key
features of the PEFCR drafts are summarized in Table 1.
Table 1. General challenges/inconsistencies between key
features of the first PEFCR drafts
Key features
Inconsistencies and resulting risks
Product cateSome product categories are very broad,gory; CPA/
others very narrow. For both, it is unclear,
NACE code
if comparability is indeed supported
Some are not suitable for functionally
Functional unit
equivalent comparability; an added value
to current practice is not provided
Representative
Some do not fulfill the functional units
product/ Bill ofchosen; are defined based on different
materials
approaches; aim/ application is unclear
life cycle phases are treated inconsisSystemtently; capital goods are partly missing
boundaries(contradicts the ban of cut-off)
4. Discussion and Outlook
The idea of the PEF/OEF methodology – harmonizationand comparability – is good and supported and thecomprehensive and intensive work on the pilot projects is
acknowledged and appreciated. However, several challenges
exist and needs to be considered in the ongoing pilot phase andthe upcoming adaptations of the PEF/OEF methodology, e.g.:clear definition of the goal of each pilot project andthe use of PEFCRs/OEFSRs in policy/ market

ensuring consistency between the pilots

discussing about communication, specification of theprocess on defining benchmarks/environmental
performance classes and consideration of existing
schemes for environmental analysis and declaration
reconsidering some methodological requirements, e.g.
predefined impact categories, ban of cut-offs etc.
We think that following these recommendations could
help to position PEF/OEF as useful instruments facilitating theuse of LCA and providing a basis for sound political decisions.
References[1] ISO 14044. International Standard – Environmental
management – Life cycle assessment – Requirements andguidelines, 2006.
[2] European Union. Commission Recommendation of 9
April 2013 on the use of common methods to measure
and communicate the life cycle environmental
performance of products and organisations. Off. J. Eur.
Union L124 56, 2013.
[3] Finkbeiner, M. Product environmental footprint –breakthrough or breakdown for policy implementation oflife cycle assessment? Int. J. LCA 19:266–271, 2013.

�������������������������������������������������

30C2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan147

20 years of LCA development, have we understood the user needs?
Mark Goedkoop1
1

PRé Consultants, The Netherlands; Goedkoop@pre-sustainability.com

Introduction
LCA methodology is used by thousands of companies, and has
proven to be a relatively robust tool for understanding theimpacts of products. Most major multinational companies
nowadays have something like an LCA department, a team ofusually a handful specialists that perform LCA’s mostly tosupport internal decisions. Yet one may wonder why it is still a
relatively small community that performs LCA, and why LCA
has not become more main-stream in business processes.
This paper reports from a number of workshops we haveorganized in various countries in 2012 and again in 2014 withrepresentatives of corporate LCA teams. We listened to theirconcerns and bottlenecks, challenges and successes.
Process
For this research, we worked together with a number ofbusiness partners of our organisation in Europe. We asked themto invite their corporate clients, to come together for an open
discussion on how they see the future of LCA, what theirchallenges are and how they cope with them. Of course we also
asked them what kind of features and tools would help themmost. We clearly explained that we like to organise this as alistening session; a clear goal was to create an atmosphere inwhich these corporate clients could learn from each other andshare common issues. The meetings were organised early 2012
with 7 partners.
Before the 2012 meeting the PRé organiser phoned allparticipants in advance (about 50) to ask them what theirbusiness objectives are and what they expected, in order to bewell prepared. Although we wanted the participants to talk andexplain their issues many also wanted to hear the vision of PRéand the partner, so we inserted that subject as last part of theagenda, in order to keep the discussion free and open. In the2014 version of the meetings these phone calls were no longer
necessary, as many came back.
The overarching message
Many Corporate LCA experts are telling us they have difficulty
to communicate their findings to the internal stakeholders. Oneof the problems is that the results are not well understood by
their colleagues in marketing, research and productdevelopment; it is as if they speak a different language. LCA
results do not really connect to what they want to know. Thismeans many are seeking for ways to drastically simplify results
or translate them into guidelines.
Getting the results out and understood is a problem, getting
data in is another big problem; often other departments are notreally motivated to supply data. Getting access to data held by
the purchasing department can also be difficult.
The general picture that emerges, is that the LCA department
finds it difficult to connect and to be relevant, while at the sametime companies have committed themselves to improve thesustainability of products in a rational way. This seems to
imply there is a disconnect between the ambitions of thecompanies, and what the LCA experts can offer; do they speak
different language, or why are they not able to connect; this is
an intriguing question.

More detailed findings
From all the comments and discussions we got some reallyinteresting additional insights
1. Participants were very happy with the workshop format, as
they told us they had learned so much from each other, andthey saw comfort in the thought that the issues they arefacing are often very similar to the issues, other face intheir company. Some said: “this is great, finally a meeting
where I can talk and do not have to listen to the opinion of
consultants”
2. Although we expected there would be much attention on
software features, most told us that this was not theirproblem; they are generally happy with what they have; sofeatures are not the bottleneck. They do however see a need
to better manage their data, which refers to keeping track of
all the questionnaires they are sending out and getting
access to data held in other systems, such as ERP.
3. Data was an important discussion point. There is always aneed for more data, especially data representative for theirsector. On the other hand there was a clear understandingthat this need will always exist. In the 2014 sessions the
new ecoinvent version 3 with its new modelling
approaches was also a topic for some members.
Alternative approaches to LCA
We also tried to discuss the merits of what people see as"alternatives" for LCA, like Circular Economy, Natural Capitaland the Sustainability Consortium approach; which problems
do they solve and which new problems do they create, or are
they just new names for LCA? Interestingly not many hadstudied these new approaches and were sometimes only
vaguely aware of them. We were surprised as these“ alternatives” do often appeal to management, marketing anddesigners; at least in our experience. So we also have theimpression that many LCA experts should do more tounderstand these alternatives, and especially why otherdepartments find them more appealing. If connection with theother department is a bottleneck, both sides should do their best
to try to understand each other. So is the LCA department too
much focussed inward, and not really exploring what ishappening outside the LCA community? Have LCA experts agenuine interest in alternative approaches?
Conclusions
The project has resulted in very valuable insights, both for theorganisers and for the participants. In the new roundtables in
2014, people acknowledged this and proudly told what they
had been doing with the insights and told about how they
improved the connection and the relevance of the LCA team in
the organisation. We will use the findings to develop softwarethat overcomes the communication bottlenecks, both incollecting and sharing the data and findings. We are alreadypiloting this with a number of participants, to learn more.
As a message to the LCA community and the researchers: thebottleneck is not in the lack of sophisticated tools andmethodologies. Companies need LCA departments that are
better connected with other departments, and shows genuineinterest in alternative approaches. The solution is not to makebetter LCA’s but get a better understanding of what marketing,design, research and purchasing departments need.

�������������������������������������������������

30D1-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan148

The significance of land use effects on groundwater resource availability in Japan
Masaharu Motoshita*1,2, Stephan Pfister3, Brad Ridoutt4, Yuya Ono5, Kiyotaka Tahara1 and Atsushi Inaba6
1Natioanal Institute of Advanced Industrial Science and Technology, Japan; 2Technische Universitaet Berlin, Germany; 3Swiss
Federal Institute of Technology Zurich, Switzerland; 4The Commonwealth Scientific and Industrial Research Organization, Australia;
5Tokyo City University, Japan; 6Kogakuin University, Japan*Corresponding author: m-motoshita@aist.go.jp

2. Method
Simple water flow model was applied on mesh scale(1km*1km) to estimate the change of rain water infiltration due
to the land occupation by the artificial land cover. The balanceof water in each mesh was calculated by estimating the amountof evapotranspiration and infiltration to underground based on
climatic data and physical characters of land surface covers. The
target land use types were classified into five (forest,
uncultivated land, paddy field, arable land, urban area)according to the definition of statistical data of land use. The lossof infiltration rate in different types of land use was assumed tobe the shortage of ground water availability. The effects of land
use by goods and services production on water availability werealso assessed based on Input-Output analysis [2] with comparing
those of water consumption [3] and water degradation (pollutant
emissions) [4].
3. Results and discussions
As a result of calculating water balance, the average volume
of water recharge loss to groundwater was calculated as 0.97
[m3/m2/yr] for the case of land occupation as urban area. It was
accounted as around 58% of the average annual amount ofprecipitation in Japan, which implied that the large part ofpotential water input to groundwater by rain might be lost by
artificial land occupation. However, the effects of land use on
the availability of groundwater were different from region toregion and the differences could be counted up to 70 times at
maximum.
In the aspect of direct effects of goods and services
production (without considering retroactive effects in supply
chain), the effect of land use accounted for around 9% of total
loss of water availability (Figure 1). On the other hand, theeffects of land use were different among goods and services incomparison with water consumption and pollutant emissions. In
particular, the impacts of land use was assessed as moresignificant in case of considering impacts (water stress) of water
availability loss because the water stress (rate of demand toresource amount) of groundwater is relatively higher than thatof surface water. By including the effects of whole supply chain,
the significance of land use on water footprinting seemed to bealmost same as water degradation. The results of this analysis

180

The amount of water consumption/depletion[Billion m3]

1. Introduction
Water footprinting is expected to play a very important role
as a tool for managing environmental impacts related to water
use through life cycle of products, services and organizations. In
the discussion of drafting the international standard of water
footprinting (ISO14046 [1]), all the relevant factors to thechange of freshwater availability are required to be considered,like not only physical scarcity of freshwater but emission ofpollutants and land use (may affect the freshwater availability ofdownstream users). Thus, the significance of land use effects on
groundwater resource availability in Japan was assessed andverified in terms of water footprinting considering both effectsof physical and qualitative changes.

Unspecified
Services

160

Information and communication

140

Transportation
Commercial, finance and estate

120

Infrastructure, electricity, gas, water , waste

100

Other manufacturing
Machinery prod.

80

Steel and metal prod.

60

Ceramic, stone and clay prod.
Petroleum and coal prod.

40

Chemical prod.
Textile, pulp, paper, wooden prod.

20

Food and beverage0

Water consumption
by withdrawal

Grey water

Water deprivation byland use

Mining/material
Agriculture., forestry, fishery

Figure 1 Water availability loss due to three factors(withdrawal, pollution, land use) for whole activities in Japan
indicated that the effects of land use on water footprinting ofproducts, services and organizations could not be disregarded.
4. Summary
The amount of the availability loss of freshwater due toartificial land use was relatively smaller than those due to water
withdrawal and pollution. However, the dominant factor(withdrawal, pollution, land use) were dependent on thecharacteristics of industrial sectors and some of the sectors
showed high significance of land use in terms of the availability
loss of freshwater. In addition, regional differences could befound in the effects and the availability of each resource (surface
and groundwater) of freshwater was also different among
regions. In this context, the loss of groundwater availability may
have significant meanings in some sectors and some regions. In
this analysis, only inventory analysis related to land use was
focused on and more precise analysis including impact
assessment will be expected.
References[1] The International Organization for Standardization:
ISO14046: 2014, Environmental management - Water
footprint - Principles, requirements and guidelines,
http://www.iso.org/iso/catalogue_detail.htm?csnumber=43263&utm_source=ISO&utm_medium=RSS&utm_camp
aign=Catalogue, (Accessed 18.08.2014).
[2] Horiguchi, K., and Itsubo N. Papers on environmental
information science, 25: 19-24, 2011 (in Japanese).
[3] Ono, Y., et al. Journal of the institute of Life Cycle
Assessment, Japan 9(2), 108-115, 2013.
[4] Ono, Y., et al. Journal of the institute of Life Cycle
Assessment, Japan, Submitted (in Japanese).

�������������������������������������������������

30D1-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

149

Human health impact models from water use: comparing to better harmonize
Anne-Marie Boulay,*1 Masaharu Motoshita,2 Stephan Pfister3, Cecile Bulle1, Manuele Margni1
1

CIRAIG, Ecole Polytechnique of Montreal, Canada; 2 National Institute of Advanced Industrial Science andTechnology, Japan; 3 Institute of Environmental Engineering, ETH Zurich, Switzerland*Corresponding author: anne-marie.boulay@polymtl.ca
1. Introduction
In the past decade, several methods have emerged toquantify human health impacts of water use [1–4]. Since thesemodels cover the same impact pathways, this paper aims to (i)identify the key relevant modeling choices that explain themain differences between characterization models leading to
the same impact indicators; (ii) quantify the significance of thedifferences between methods, including the assessment ofmodel uncertainty and (iii) discuss the main methodologicalchoices and provide recommendations to guide method
development and harmonization efforts.
2. MethodA general framework describing the impact pathway
leading to human health impact is presented and the modelingchoices for each of the modeling steps are analyzed for
difference in results (using mean relative difference) and model
response consistency (through rank correlation coefficient).
Uncertainty data associated with the choice of model isprovided for the results of each of the model, and an averagevalue is provided as a tool for sensitivity analyses.
3. Results
The results determined the modeling choices thatsignificantly influence the indicators and should be further
improved and harmonized (see Tab.1). The inclusion or
exclusion of (1) quality when assessing water deprivation, (2)impacts from domestic user deprivation, and (3) trade effects,
significantly influence human health impacts. The differencesamong the models are substantial, as can be seen in Fig.2.
Tab.1: Table of results describing the importance ofspecific modeling choices in human health impact models (thelonger the red bar the lower the correlation, the longer the blue
bar, the higher the difference)
Consistency*
Difference**
Modeling Choice
Highercomplexity: water quality specification at endpoint
100% consumption good quality water46%
0.79
100% consumption poor quality water59%
1.24
100% degradation good quality water into very poor quality
43%
0.83
Inclusion or exclusion of user deprived
Aquaculture
100%
0.0004
Domestic
84%
0.69
Source of data for user distribution
Watergap - Aquastat
93%
0.30
Watergap - Vorosmarthy87%
0.59
Vorosmarthy - Aquastat
89%
0.60
Socio-economic
Trade effect
E-Motoshita_agri / E-Motoshita_agri (no TE)76%
1.32* the longer the red bar the lower the correlation**the longer the blue bar, the higher the difference

Figure 2: Maximal difference found between human healthimpacts from agricultural deprivation using different models(Boulay, Pfister and Motoshita).
6. Conclusion
This paper provides useful insights to better understandhuman health impact models for water use and identifies the
key relevant modeling choices and differences, making it
possible to quantify model uncertainty and the significance of
these choices in a specific regional context. Deconstructing theexisting models into a common framework and highlighting thedifferences and similarities has helped to determine building
blocks to support the development of a consensual method.
Such model will soon become essential to ensure consistent
application of the forthcoming ISO 14046 international
standard on Water Footprinting.
References[1] S. Pfister, A. Koehler, and S. Hellweg, “Assessing theenvironmental impacts of freshwater consumption in
LCA,” Environmental Science & Technology, vol. 43, no.
11, pp. 4098–4104, 2009.
[2] A.-M. Boulay, C. Bulle, J.-B. Bayart, L. Deschenes, and
M. Margni, “Regional Characterization of Freshwater
Use in LCA: Modeling Direct Impacts on Human Health,”
Environmental Science & Technology, vol. 45, no. 20, pp.
8948–8957, 2011.
[3] M. Motoshita, N. Itsubo, and A. Inaba, “Development of
impact factors on damage to health by infectious diseases
caused by domestic water scarcity,” The International
Journal of Life Cycle Assessment, vol. 16, no. 1, pp.
65–73, 2010.
[4] M. Motoshita, N. Itsubo, and A. Inaba, “Damage
assessment of water scarcity for agricultural use 1,” inProceedings of 9th international conference on
EcoBalance., 2010, pp. 3–6.

�������������������������������������������������

30D1-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

150

Functional mapping for sustainable consumption: an example through drinking water
consumption.
Sébastien M.R. Dente,* Seiji Hashimoto
Ritsumeikan University, Japan*Corresponding author: 13v00202@gst.ritsumeik.ac.jp

1. Introduction
Environmental system analysis uses decomposition
technics in order to distinguish between relevant parameters ofan environmental impact. The purpose is to find lever ofactions for solving environmental issues. One of the most
famous decomposition technics is the I=PAT equation whichallows the decomposition of environmental impacts into
population, affluence and technology factors [1, 2]. These
factors are nevertheless not treated equally as environmental
policies have so far mainly focused on the management oftechnological factors (carbon, energy efficiency) leaving theaffluence factor to be mainly represented through the GDP
economic indicator.
2. Functional mapping
The present presentation aims at filling this gap by
providing a clear linkage between affluence and technologicalfeatures, notably applicable at the micro-economic level. Thisway, a more sounded lifecycle perspective of products could be
driven. This new methodology considers affluence as a set offunctions defined at the final consumer level which determines
his/her welfare. Therefore welfare is understood as a functional

system specific to the final consumer. Then, a functional
mapping is established transforming the welfare functions into
technical functions manageable by producers [3].
3. Application to drinking water consumption
This new methodology is illustrated through the study caseof household drinking water consumption based on thecomparison of the systems presented in Figure 1 . The
customer’s function considered is the quality of water whichshould be adapted to each particular use. This way, in systems
2 and 3, the water quality and associated treatments isdifferentiated in “drinking-cooking use” (around 8% ofHousehold consumption [4]) and “other use” (92%). The
environmental gains that could be expected from this new
design of water supply system is then made explicit incomparison to the usual conventional treatment systems inwhich water uses are not differentiated (system 1). The
potential for the application of these new water supply systems
in developed and developing countries is then discussed
together with the usefulness of process-based LCA in thedesign of functional oriented systems.

Figure 1. Comparison of use-differentiated (system 2 and 3) and non-differentiated (system 1) water supply systems

References[1] Ehrlich, P. R. and J. P. Holdren. Impact of population
growth. Science, New Series 171 (3977): 1212-1217, 1971.
[2] Waggoner, E. P. and J.H. Ausubel. A framework forsustainability science: A renovated IPAT identity. PNAS 99(12): 7860-7865, 2002

[3] Van Ostaeyen, J., et al. A refined typology of
product-service systems based on functional hierarchymodeling. Journal of Cleaner Production 51 (15): 261-276,
2013.
[4] Euzen, A., and Levi Y. (ed.). Tout savoir sur l'eau durobinet. Paris, France: CNRS Editions, 2013.

�������������������������������������������������

30D1-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

151

Economic Water Productivity of Polylactic Acid (PLA) Production Chain in Thailand
Shinatiphkorn Pongpinyopap,1 Unchalee Suwanmanee,2 and Thumrongrut Mungcharoen*1
1Center for Petroleum Petrochemicals and Advanced Materials, Center for Advanced Studies in Industrial Technology,
Department of Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand;
2
Department of Chemical Engineering, Srinakharinwirot University, Nakhon-nayok 26120 Thailand*Corresponding author: fengtrm@ku.ac.th

1. Introduction
Thailand will establish PLA factory in order to reduce
PLA import and add value to agricultural commodities.
Cassava, corn and sugarcane have a high potential to use as
feedstock for PLA production [1]. Although it is an attractive interm of reduce GHG emission but it is an unattractive in termof increase water consumption. Moreover, a few studies areinterested in the value per unit of water used in agriculture(economic water productivity) more than the physical waterproductivity [2]. This study aims to evaluate and analysis the
economic water productivity (baht/m3) associated with PLA
production chain using cassava, corn and sugarcane as thefeedstock in Thailand based on the Water Footprint Network(WFN) approach [3]. The functional unit is 1 ton of PLA
granulate at the factory gate in Thailand. The system boundaryis drawn to include water consumption of all steps from crops
cultivation and harvesting, transport to intermediate production
factory, intermediate processing process, transport to PLA
factory and the polymerization process to produce PLA
granulate.
2. Methodology
The economic water productivity (EWP) is the net
financial returns for a unit of water used. The EWP (baht/m3)
was estimated as the ratio of the PLA price to the blue water
footprint. The blue water footprint was the volume of surface
and groundwater consumed as a result of the production of agood or service. In the PLA production chain, there are two
types of blue water consumption which relevant to each stageof PLA production chain; 1) Water consumed during theprocessing step (i.e. the consumptive water used over theperiod of crops cultivation, the consumptive water used forcooling system) and 2) Water consumed to produce raw
material for the processing step. The crop water requirement(CWR) was calculated by multiplying the reference crop
evapotranspiration (ETo) by the crop coefficient (Kc). The
reference crop evapotranspiration (ETo) was calculated bymultiplying the pan evaporation coefficient (Kp) by the pan
evaporation (Ep). All data sources for calculation were takenfrom local data. Integration of Daily Soil Water Balancemethod with Geographic Information System (GIS) was used
to distinguish between green (effective rainfall) and blue
(irrigation requirement) water component. The amount of water
use to produce raw material in each stage of PLA production
chain were obtained from Ecoinvent [4] and converted to water
consumption with the consumption factors [5].
3. Results and Discussion
Table 1 shows the economic water productivity of PLA
production chain. The results indicated that the cassava-based
PLA production chain had the highest economic waterproductivity followed by the corn-based and thesugarcane-based. The advantage of cassava-based comparedwith the other crops was its potentially low evapotranspirationand could grow without irrigation water. Thus, the PLA
production chain, that using cassava as the feedstock was
attractive crop in water perspective. The strategies forincreasing the EWP could be done by increasing crop yield or
re-allocating water from low to higher valued uses.
Table 1. Economic water productivity of PLA production chain
Economic water productivity
Crops(baht/m3)
Cassava
57,803Corn
45,662
Sugarcane680
4. Conclusions
In this study, we evaluate and analysis the economic waterproductivity of PLA production chain using cassava, corn andsugarcane as the feedstock in Thailand. The results show thatthe cassava-based PLA production chain had the highest
economic water productivity. It can be concluded that thecassava was attractive crop for using as the feedstock in PLA
production chain in water perspective. Moreover, this study
provide information for operational planning and managementof PLA production chain for maximizing net financial returns
from limited land and water resources.
Acknowledgments
The authors gratefully acknowledge financial support from
National Science and Technology Development Agency(NSTDA) and from Commission of Higher Education
Chemical Engineering Department, Kasetsart University under
the National Excellence Center for Petroleum, Petrochemicals
and Advanced Materials.
References[1] Suwanna, C. Bioplastic’s industry outlook … anotherbusiness
opportunityforThailand.
https://www.scbeic.com/ENG/document/note_20140108_
bioplastic_en (Accessed 25.02.2014).
[2] Molden, D., Oweis, T., Steduto, P., Bindraban, P., Hanjra,
M.A. and J. Kijne. Improving agricultural waterproductivity: Between optimism and caution. Agricultural
Water Management. doi:10.1016/j.agwat.2009.03.023,
2009.
[3] Hoekstra, A.Y., Chapagain, A.K., Aldaya, M.M. and M.M.
Mekonnen. The Water Footprint Assessment Manual:
Setting the Global Standard. London, The United
Kingdom. Earthscan, 2011.
[4] Ecoinvent. Swiss Center for Life Cycle Inventories.
Switzerland, 2006.
[5] Flury, K., Jungbluth, N., Frischknecht, R. and I. Muñoz.
Recommendation for life cycle inventory analysis for
water
use
and
consumption.
http://www.esu-services.ch/fileadmin/download/flury-201
2-water-LCI-recommendations.pdf (accessed 3 July2014).

�������������������������������������������������

30D2-1

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

152

Environmental Life Cycle Emissions for Vegetable oil Microemulsion-based Biofuels
Noulkamol Arpornponga1, Virin Kittithammavong1, David A. Sabatini2, Sutha Khaodhiar1, Ampira Charoensaeng1
1

Chulalongkorn University, Thailand, 2The University of Oklahoma, USA.
*Corresponding author: ampira.c@chula.ac.th

1. Introduction
To date, a variety of biofuel productions have beentechnologically developed to reduce greenhouse emissions(GHGs). A microemulsion biofuel (ME) as an emerging
technology for bio-based diesel production presets
environmental
advantages
in
terms
of
replacingthermochemical conversion of transesterification process andavoiding byproduct and wastewater. The microemulsion fuel isa thermodynamically stable mixture of at least two-immiscible
liquid fuel blends, which the polar ethanol phase dispersed in
non-polar oil phase, stabilized by surfactant. Several vegetableoil feedstock and surfactant/cosurfactant systems have been
employed to achieve comparable fuel properties to those of theno. 2 diesel standard [1,2]. In order to promote the ME
technology, GHG emissions and environmental implications
need to be addressed. This study reveals the GHG emissions
and impacts through Life Cycle Analysis (LCA) approach for
the ME production from palm oil/diesel and ethanol blends as
an alternative fuel for sustainable future.
Surfactant

Ethanol droplet

99% of all GHG emissions. Whereas GHG emissions generated
from production stage were relatively low, due to the fact that
only electrical mixing the main process consumes small
amount of electricity to produce the biofuel. Among all of thematerials preparation, the production of palm oil indicates alarge contribution about 315 kg CO2/ton (27.6 percent), due tofertilizer loading during cultivation, and energy uses andwastewater discharges during the oil extraction.

Cosurfactant

Figure 3
Oil (Vegetable oil/Diesel blend)Figure 1

Reverse micelle (W/O)

Microemulsion fuel and reverse micelle structure

2. Methodology and system boundary
In this study, the microemulsion biofuels (so called
ME50) formulated by the mixture of palm oil/diesel (50:50v/v%) blend (58 vol.%) with ethanol (20 vol.%), and stabilized
by methyl oleate/1-octanol (22vol.%) as surfactant andcosurfactant, respectively [1]. The system boundary of theME50 production covered from palm oil cultivation to liquid
fuel (cradle to gate). The production of the ME50 was
separated into three main stages; palm oil cultivation, palm oil,extraction and refinery and microemulsion process. The GHG
emissions were calculated based on the standard for carbon
footprint of product (ISO14067) as described by CO2eq. The
environmental impacts were evaluated through LCA approachby the SimaPro (v. 7.1).
Refined palm oil

DieselEthanolSurfactant

Cosurfactant(326.2kg)(294.5kg)(184kg)(68.5kg)(126.8kg)

Electricity(7.4 kWh)

Microemulsification(Mixing process)

Biofuel (ME)
(1 ton)Figure 2 Production of microemulsion biofuel (ME50)
3. Results
3.1 The GHG emission of microemulsion biofuel
The GHG emissions from the ME production stage were
estimated to be 1,140 kg CO2eq per ton of ME50. The
significant GHG emissions during the ME50 production
influenced from its raw material preparation, accounting for

GHG emissions of ME50 production and each raw
material acquisition

3.2 Environmental impact assessment of ME50 production
The ME50 production contributes significantly toenvironmental impact categories including, global warming,
acidification, eutrophication, human toxicity, aquatic andterrestrial ecotoxicity, land use, water depletion. The emissionsof each impact category were compared to those of thebiodiesel B50 (biodisel: diesel 50:50 v/v%) and pure biodiesel(the data is not shown). Based on the inventory data, the ME50
presents a benefit regarding with less impact to water
environment due to no water supply being required for
purifying biodiesel. Moreover, the ME50 production also
indicates remarkably positive impacts due to less toxic impacts
contributing to aquatic and terrestrial environments as well as
human health.
4. Conclusion
The production of microemulsion biofuel from palm oil causes
1,140 kg CO2eq per ton. Based on GHG emission calculationand LCA analysis, the raw material selection and formulationto achieve a stable single-phase microemulsion fuel are the key
parameters to optimize its emissions. Thus, the microemulsion
biofuel could be considered as eco-friendly sound technology
for future biofuel production.
Acknowledgments
Grant supported by the Royal Golden Jubilee Ph.D. Program(RGJ) under the Thailand Research Fund (TRF) and the newresearcher grant from TRF (grant number TRG 5780163) and. In
additional, grant support from Chulalongkorn University(Ratchadaphiseksomphot Endowment Fund)
References[1] Arpornpong N., Attaphong C., Charoensaeng A., Sabatini D.
A., Khaodhiar S., Fuel 132:101-106, 2014
[2] Attaphong C., Do L., Sabatini D. A., Fuel 94:606-613, 2014�������������������������������������������������

30D2-2

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

153

Life Cycle Assessment of Biofuels and the Issue of Indirect Land Use Change
Liselotte Schebek*1, Yalda Cikovani1
1

Technische Universität Darmstadt, Institute IWAR, Chair of Material Flow Management and Resource Economy, Franziska-Braun-Straße 7, D-64287 Darmstadt, Germany*Corresponding author: l.schebek@iwar.tu-darmstadt.de

1. Introduction
Today, biofuels play a major role in climate policies
worldwide. In 2008, however, the well-known study by
Searchinger et. al. postulated that biofuels might on the contrary enhance climate change, due to the effect of indirect land
use change on the carbon balance which had not been taken
into account so far. Since then, the assessment of indirect land
use change is an ongoing but highly challenging issue for LCA.
Controversial views exist how to tackle this problem methodologically. It is even questioned whether it should be included in
LCA at all because of the large variety of results studies revealed. As part of a current research project on biofuel policy
we investigated the state of the art for assessment of land usechange in connection with LCA, focusing on the interlinkage
between LCA and models for Land Use Change (LUC).
2. Methodology
We carried out a comprehensive literature review, fromwhich we identified types of LUC and of models applied forassessment of LUC from biofuels. By comparing characteristics of these types to typical research cases of LCA, we derived
a mapping to support the choice of adequate approaches forincorporation of LUC.
3. Land Use Change and Land Use Change Models
LUC is the conversion of one type of land to another [1].
In connection to a certain driver, e.g. the demand for biofuels,
LUC is discerned in direct and indirect LUC: DLUC means,that land is changed from any previous use to biofuel feedstock
production. ILUC denoted LUC that is induced by the production of feedstock for biofuels because the former feedstock
now has to be produced elsewhere. As to LUC models, economic and deterministic (or allocation) models are discerned,
e.g. [1]. Economic models market equilibrium models, covering CGE and PE models. Deterministic models base on allocating LUC to certain biofuels by fixed assumptions, mostly
derived from historical data. Above these, in recent years also
spatially explicit simulation models have been used which are
based on the general concept of land-use systems [2][3]. For allmodels it has to be noted, that they deliver LUC as a result,where DLUC and ILUC are identified from interpretation of
results.
4. Interlinkage between LCA and LUC modelling
In LCA methodology, assessment of ILUC is conceived tobe part of Consequentional LCA (CLCA). CLCA aims to coverchanges in the economy, where ideally economic models are
the corresponding tool. However, as LUC models are complex
and need a high degree of expertise, our review showed that infact assessment of ILUC is no integral part of LCA: on one
hand, those approaches focusing on ILUC assessment stand on
their own and do not necessarily follow the methodologicaloutlines of CLCA. On the other hand, most publications on
biofuels based on LCA ISO 14040 do not incorporate ILUC
assessment, and if, only by adopting results from ILUC studies
performed independently. If LCA and ILUC assessment are
independent, however, there is no attention to the question
which model fits to goal and scope of the respective LCA.

Consequently, combining LCA and assessment of ILUC
comes down to a conceptual interlinkage between LCA and therespective LUC model. This interlinkage has to be based ongoal and scope and has to bridge the basic difference generally
inherent to CLCA approaches that LCA looks from the individual product or technology respectively, while LUC models
look for the macroeconomic level.
Possible cases for studies on biofuels cover the range fromregional case studies to the assessment of biofuel policies. Here,different levels are encountered as to the incorporation of global economy and trade as well as to the regionalization of land
use change and carbon flow assessment. Based on these considerations, we propose a matching between goal and scope
and the ILUC modelling, based on three criteria (Table 1).
Table 1 Criteria for mapping of LUC Model to application case
BiofuelImportance Spatial indemandof internaformation ontional trade soil/aboveground C
high
high
low
Economicmodelslow
low
low
Deterministic
modelsmediumlow ahighLand Useto lowmodelsa(if high: coupling to economic models)
5. Conclusions
It has to be emphasized that as to LUC assessment a
trade-off exists between a most comprehensive inclusion of
global market effects, where economic models are best state ofscience and an easy to use and transparent assessment where
deterministic approaches are advantageous. The discussion
presented above therefore is in line with a general argumentation introduced in the discussion on ALCA versus CLCA, saying that CLCA should be performed as far as uncertainties andintransperancy of consequential modelling do not outweigh theinsights gained from it [4]. On this basis our matching approach presented above should support the appropriate treatment of ILUC by combining LCA and LUC modelling.
References[1] Wicke, B. et al. Indirect land use change: review of existing models and strategies for mitigation. In: Biofuels 3(1):87-100, 2012.
[2] Lapola D.M. et al. Indirect land-use changes can overcome carbon savings from biofuels in Brazil.
http://www.pnas.org/content/early/2010/02/02/090731810
7 (Accessed 01.09.2014)[3] Humpenöder, F. et al. Effects of land-use change on the
carbon balance of 1st generation biofuels: An analysis for
the European Union combining spatial modeling and
LCA. In: Biomass and Bioenergy 56(0): 166-178, 2013.
[4] Finnveden, G. et al. Recent developments in Life Cycle
Assessment. In: Journal of Environmental Management
91 (1). 1-21, 2009.

�������������������������������������������������

30D2-3

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

154

Evaluation of uncertainty in for- and background systems:
A case study of municipal wastewater treatment plant
Hiroko Yoshida*, Charlotte Scheutz, and Thomas H. Christensen
Technical University of Denmark*Corresponding author:hyos@env.dtu.dk
1. Introduction
The quality of a Life Cycle Assessment (LCA) depends
on the availability of input data for constructing a Life Cycle
Inventory (LCI). Nonetheless, collecting a site-specific input
dataset could be prohibitively time- and resource-consuming.
As a consequence, LCA practitioners rely heavily on existing
emission and operational data for target systems. For instance,
LCA of 400 wastewater treatment plants (WWTPs) in
Denmark was conducted based on the information compiled
under existing regulation [1], yet this approach could result in
the underestimation of environmental impacts from theforeground systems and overlook the uncertainty due to thevariation in daily operation [2]. The other source of uncertainty
is the uncertainties embedded in the background systems. Since
the previous studies [1, 2] shows that more than half of theenvironmental impacts for WWTPs, the evaluation of
uncertainties ought to be extended to the background systems.
For this purpose, LCA of a municipal wastewater treatment
plant in the Danish capital region was used as a case study
2. Approach
The functional unit of the assessment involved thetreatment of average daily inflows of wastewater at the
Avedøre WWTP. The assessment was conducted in the fourlevels to illustrate the source of uncertainties in the backgroundsystems. The baseline scenario only includes the foregroundsystem and the uncertainties embedded in each emission data
(L3). Then, the system expanded to include the backgroundsystem and here the source of variation of energy and chemical
demand by the WWTPs were regarded as the source of
uncertainty (L3+). The uncertainties of external process were
evaluated in two steps; first the quality and representativenessof each external process LCI data was evaluated following thepedigree matrix developed by [3] (L3+DQ). Finally, theuncertainty embedded in the Ecoinvent process was included in
the assessment (L3+DQ+DB). EASETECH model was used to
conduct the assessment including uncertainty analysis and the
LCI data for the background systems were taken from
Ecoinvent database. Detail description of study site andtechnical modeling approach was provided in [2]. The
uncertainty was evaluated by using Monte Carlo simulation
with 100,000 simulation runs .Nine impact categories (global
warming (GW); acidification (AC); terrestrial eutrophication(TE); marine eutrophication (ME); photochemical ozone
formation (POF); ecotoxicity (ET); human toxicity- cancer(HTc); human toxicity, non-cancer (HTnc); particulate matter(PM)) and the ILCD recommended characterization method
and normalizing factors were adopted [4].
3. Result and Discussion
The outcome of the assessment is presented in the Figure
1. With exception of marine eutrophication in which majorityof impact comes from the foreground systems, the inclusion of
background system has more than doubled the median impact
potential. The uncertainty factor for data quality andrepresentativeness ranged from 1.2 to 12% of mean value andthe inclusion of uncertainties in the Ecoinvent database
introduced two to three folded the uncertainty range though themedian impact potential remain unchanged. Based on the
results, it is recommended to extend the uncertainty analysis
not only to the data quality assessment but also to include theuncertainty embedded in the LCI dataset, especially for the
toxicity categories.

Figure1. Normalized impacts obtained for data collection
schemes L3, L3+, L3+DQ, and L3+DQ+DB.
Acknowledgement
The authors thank Dr. Julie Clavreul for assisting EASETECH
modeling and Dr. Thomas Guildal for providing operational
data of WWTPs.
Reference[1] Niero, M., Pizzol, M., Bruun, H.G., Thomsen, M., 2014.
Comparative life cycle assessment of wastewater treatment
plant in Denmark including sensitivity and uncertainty analysis.
Journal of Cleaner Production 68, 25-35.
[2] Yoshida, H., Claverul, J., Scheutz, C., Christensen, T.H.,
2014. Influence of data collection schemes on the Life Cycle
Assessment of municipal wastewater treatment plant. Water
Research, 56, 292-303.
[3]Weidema, B.P., Bauer, C., Hischier, R., Mutel, C., Nemecek,T., Reinhard, J., Vadenbo, C.O., Wernet, G. 2012 Overview
and Methodology – Data Quality Guideline for the Ecoinvent
Database Version 3. Retrieved fromhttp://www.ecoinvent.org/fileadmin/documents/en/Data_Qualit
y_Guidelines/01_DataQualityGuideline_v3_Final.pdf[4]Laurent, A., Hauschild M.Z., Golsteijn, L., Fontes, M.,
Simas, J., Wood, R., 2013. Prosuite Deliverable 5.2:
Normalisation factors for environmental, economic and socioeconomic indicators. Copenhagen, Denmark. P 54.

�������������������������������������������������

30D2-4

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

155

Basin-scale Multi-objective Optimization of Water and Wastewater Systems Considering
Global and Regional Impacts
Seiya MAKI*1, Jun NAKATANI*1, Kiyo KURISU*2 and Keisuke HANAKI*1*1 Department of Urban Engineering, The University of Tokyo, Japan*2 Research Center for Advanced Science and Technology, The University of Tokyo, Japan*Corresponding author: maki@env.t.u-tokyo.ac.jp1. Introduction
Water use systems include stakeholders who have various
preferences. Hence, their planning requires a comprehensive
assessment of various evaluation axes including environmental,
economic and social aspects. However, it is considered thatdesirable systems are different depending on stakeholder
preferences when tradeoffs exist among evaluation axes.
The objective of this study is to obtain the Pareto optimal,
necessary and sufficient alternatives of a water use system inconsideration of diverse stakeholder preferences for evaluation
axes. The study area of this study is Arakawa basin, Japan. We
applied multiple-objective optimization using a mixed integer
linear programming (MILP), with an objective functions that iscomposed of global warming, water pollution substance and soon, and with design variables including components of water
purification plants, wastewater treatment and reclamation
plants and pipe networks.
2. Methods
An optimization problem indicates a mathematical methodthat makes a search for a solution that maximizes or minimizes
its objective function under constraints. In general, a weighted
multi-objective optimization model is expressed by Equation
(1).

min

3. Results and Discussion
As a result of optimization for 10,000 sets of random
numbers, we obtained 68 Pareto optimal solutions, which could
be alternatives of the water use systems. Those solutions wereclassified into five groups using k-means clustering.
Figure 1 illustrates distributions of the optimal solutions.
The upper figure presents their relationship between global
warming and water pollution substances, and the lower figure
presents that between global warming and surplus reclaimed
water. There is a tradeoff between global warming and waterpollution substance, or surplus reclaimed water. As shown in
the lower figure, an increase in the amount of reclaimed water
increases the impact on global warming. Alternatives with thepositive amount of surplus reclaimed water were derived only
when the weighting coefficients of surplus reclaimed water
were significantly large.

nz ( x)   wi･f i ( x)



i 1

sub.toquality according to application (e.g., water for flushing toilets,
general service water).
By applying various sets of weighting coefficients to the
optimization problem of Equation (1), alternatives reflecting
various preferences can be obtained. In this research, we input
10,000 sets of random numbers as weighting coefficients. Sum
of weighting coefficients in each set was equal to 1.

g ( x) ≦ 0 x ≧ 0nw 1 w ≧0
i 1

i

(1)

i

where, fi(x) is ith objective function, x is design variables.
g(x) is a constraint functions, and wi is a weighting coefficientof the ith objective function.
The evaluation axes relevant to desirable water use system
include fundamental performances and regional impacts, suchas the business cost, the amount of water pollution substances,
surface water and groundwater intakes. As global impacts thatthe water use system imposes on outside the region, life cycle
impacts on global warming, acidification and eutrophication,
life cycle fossil resource, mineral resource and water resource
consumptions are evaluated using LCA. In addition, thequantities of good-tasting clean water and surplus reclaimed
water are considered for evaluation of amenity.
We applied components of water use systems such as theamount of groundwater intakes in water purification plants,
purification methods (flocculation-sedimentation or ozonation
processes), wastewater treatment methods (conventional
activated-sludge or A2O processes), sizes and lengths of waterand sewage pipes between cities, water-supply pipes in eachcity, as design variables. Wastewater reclamation methods(ozonation or RO processes) and sizes and lengths of reclaimed
water pipes between cities were also taken into account as
design variables.
As constraints of optimization problem, we considered theminimum requirements of water use system as follows:
1. The amount of water demand in each city should be fulfilled.
2. All wastewater generated in each city should be treated.
3. Reclaimed water should satisfy the required level of water

Figure 1. Distribution of Pareto optimal solutions and theirclusters
4. Conclusion
Each Pareto optimal solution can be regarded as the best
feasible alternative corresponding to a particular stakeholder
preference. Owing to the feature of MLIP, we could obtain arelatively small number of Pareto optimal solutions from alarge number of weighting coefficient sets. In addition, we
could classify those Pareto optimal solutions into a small
number of groups using cluster analysis.
Acknowledgment
This research was supported by CREST, a funding
program of the Japan Science and Technology Agency (JST)�������������������������������������������������

P-001

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

156

Life Cycle based Sustainability Solutions: How successful companies turn sustainability
solutions into company benefit and business value.
Martin Baitz,*1 Masahiro Osumi2, Hatori Yukiyoshi2 and Harald Florin1
1PE International AG, Germany; 2PE Asia Corporation, Japan*Corresponding author: m.baitz@pe-international.com

1. Introduction
Sustainability is core to a company’s ability to prosper in acompetitive and changing global business environment.
Companies which can successfully anticipate and manage
economic, environmental and social opportunities and risks will
emerge as leaders. A focus on quality, innovation andproductivity is likely to create a competitive advantage and longterm stakeholder value.
Life Cycle Solutions established in industry as importantpillar in the sustainability domain, as it helps to prevent
spreadsheet sustainability approaches, greenwashing, single
metric evaluation and unacceptable inaccuracy or arbitrary.
Life Cycle Solutions are supporting trends like “innovationand clean tech”, strategic energy management, sustainablesupply chains and “next generation strategies”. Successful
sustainability implementation is not “doing what you have todo”, but succeeding in doing innovation with sustainability.
2. Landscape of stakeholder
Life Cycle based approaches is practiced andcommunicated differently amongst stakeholders.
Academia focuses on public and influenceable data, model
theory and system behavior and uses Life Cycle Assessments.
Politics focuses on reproducibility and method regulation,
has stimulation interest and uses Life Cycle Thinking [1].
Industry focuses on company and supply chain data,
product stewardship, decision support and integration in daily
operation and uses Life Cycle Management.
If these 3 interests and 3 different mindsets are understood,
companies can focus on value creation in the life cycle of theirproducts, if their solution respects political initiatives andfacilitates practice-proven scientific improvements.
3. Standards as basis, networks as connection
International standards e.g. [2], [3], [4] support the setup of
consistent supply chains across nations and markets. Standards
must be met and be applicable in IT tools and databases to enablescalability. International networks e.g. [5] support
interoperability and data access if common format andnomenclature rules are defined and applied.
4. Materiality, practicability, quality, transparency
The four core pillars of successful sustainability solution
implementation in industry are materiality (which data do I have
and which data is relevant?), practicability (where do I get thedata from and which tool and databases do exist to support mygoal?), quality (which are relevant quality indicators for my goal
achievement?) and transparency (are processes clearly
documented, is change monitored and are routines auditable?).
5. Tools, databases and user responsibilities
The need for technology to support sustainability is obvious.
Initial motivation of companies may vary, however successfulcompanies act now or already did. The industry has a prominentrole to play in sustainability; either through design, sustainable
practices in the development process or in response toregulations and customer demands. It doesn't matter how to startsustainable business, but it does matters which tools and datasolutions are chosen; ideally those fits the company and cover
multiple purposes such as compliance & reporting, productdevelopment & innovation, sales & marketing, performance
communication and attracting shareholders.
6. The business value of sustainability
Successful companies create value through sustainability in
4 discrete ways:
in sales over increasing market share or new market entry
by quantifying of benefits B2B or B2C or by promoting
Innovation and new products based on solid facts.
through cost reduction due to increase of value chain andoperational efficiency as well as over employee
productivity.
risk mitigation like operational risk management or
regulatory management supports business continuity.
the brand value is increased due to reputation as well as
employee attraction and retention.
7. Screen, Scope, Scale
To generate value on sustainability in a company a platform
combining IT technology (like software and data exchangesystems), content (like adequate databases) and a positive user
experience is key. The positive user experience is mostefficiently implemented by an adequate and balanced sharetechnology and service support.
In sequence, companies want to determine more quickly
what the social, environmental and economic tradeoffs of theirproducts are (screening)? How they can provide more value by
combining multiple data sources (scoping)? And how thecompanies may integrate sustainability management withexisting management systems, such as ERP, PLM, CAD or
supply chain management (scale)?
8. Example(s)We will present different ways of different companies tocreate their optimal value with sustainability.
References[1] EU Commission, Environmental Footprint Pilot
Guidance document, Guidance for the implementation of
the EU Product Environmental Footprint (PEF) during
the pilot phase, v. 4.0, May 2014.
[2] ISO 14044, Environmental management - Life cycle
assessment - Requirements and guidelines, 2006
[3] ISO/TS 14067, Greenhouse gases - Carbon footprint of
products - Requirements and guidelines for quantificationand communication, 2013[4] ISO 14046: Environmental management - Water footprint- Principles, requirements and guidelines, 2014[5] Joint Research Center EU, Life Cycle Data Network, 2014�������������������������������������������������

P-002

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

157

Guidance to assess avoided emissions of GHGs
Atsushi Inaba1 and Masaharu Motoshita*2,3
1Kogakuin University, Japan, 2Natioanal Institute of Advanced Industrial Science and Technology, Japan; 3Technische

Universitaet Berlin, Germany*Corresponding author: m-motoshita@aist.go.jp

1. Introduction
It will be advantageous for LCA practitioners to assert thecontribution of their new products to the avoidance ofenvironmental impacts compared to the current/past situations.
In fact, some methods for estimating the contribution of products
to reduce greenhouse gas emissions (GHGs) have beendeveloped and proposed by several industrial associations fromthe viewpoints of specific sectors (e.g. chemical, electrical andelectronics) [1] [2]. Some local governments also encourage
industries to quantify and assess the contribution by publishingguidelines [3] [4].
On the other hand, there is still no consensus on themethodology to assess the effectiveness of so-called green
products in terms of reducing environmental impacts. A study
group was established in the Institute of Life Cycle Assessment,
Japan to discuss about the crucial issues and build up theguidance for practitioners to assess avoided GHGs emissions of
their products based on scientific knowledge of experts.
2. Critical points raised in the group
At the first step, current existing practices andmethodologies for assessing the effects of products on the
avoidance of GHGs emissions were reviewed and several points
for discussion were extracted and argued by proceeding thedrafting of the guidance. Regarding the calculation andassessment of avoided emissions by introducing newtechnologies and products, several points are carefully
mentioned in the draft of the guidance from the viewpoints ofexperts. Some crucial points are raised and mentioned in thedraft of the guidance as follows.
2.1. Definition of the term “Avoided emissions”
As a fundamental issue, the definition of “Avoided
emissions” is absolutely one of the most significant points. As aresult of discussion, “Avoided emissions” has defined as “thequantified amount of reduced GHGs emissions through life cycleof the final products compared to the base-line situation with theconsideration of the contribution of the target”. The definitionsof “the target”, “final product(s)” and “base-line” should beclarified as explained in the following section.
2.2. Definition of the target, final product(s) and base-line“The target” is defined as the target technologies, materials,
parts and products that practitioners aim to assess thecontribution to GHGs reduction. This should not be necessarily
the “final product(s)” that will directly contribute to the
reduction of emissions. In that sense, not only an automobile assuch but also tires could be the target if tires actually contributeto reduce emissions through the life cycle of an automobile.
“Base-line” is also one of the key issues in the assessmentof avoided emissions. For preventing from misleading andmalicious assertions, “base-line” shall be defined and explainedin clear and appropriate ways. In the draft of the guidance,“base-line” is defined as the final product(s) that would be used
when the target is not on the markets. Obviously, the functional
unit shall be the same as the case with the target and the spatial
information shall be considered for the calculation of avoided
emissions. In the setting of “base-line”, sufficient attentions
shall be paid to a case of comparative assertion with regard to
ISO14044.

2.3. Calculation procedures of avoided emissions
The amount of avoided emissions should be assessed bymultiplying the following three items; (1) the amount of net
reduction of emissions of the final product(s) with the target
compared to base-line, (2) the total amount of the target productson the market, (3) the rate of contribution of the target to the total
reduction by the final product(s) in accordance with ISO14040
and ISO14044.
2.4. Simplified approach for the calculation
In the case that the final product(s) with the target and baseline have absolutely same processes on some stages of life cycle,
simplified approach can be applied by skipping the calculationof emissions on the same stages of life cycle. It would be
profitable for practitioners to save their efforts. On the other
hand, the rate of the contribution amount on limited life stages
by simplified approach shall not be used for declaring to the
public to prevent from misleading.
2.5. Contribution rate of the target
The reduction of emissions may be achieved by many ofstakeholders on the supply chain of the final product(s). The
contribution rate of the target will be desirable to be determined.
There are several sorts of options to allocate the reduction
amount to the target (e.g. technical aspects, consensus among
stakeholders, value add-base, and decisions by practitioners). In
any cases, the contribution rate should be clearly stated with thesupporting evidences.
3. Summary
This guidance is expected to support practitioners to
perform the assessment and assert the effectiveness in an
appropriate way for avoiding confusion and mislead due to thedisclosure of results in different methodologies. Further steps to
finalize the guidance will be proceeded to achieve this scope.
Acknowledgments
We greatly thank all of the contributors in the discussion
group, and especially acknowledge Ms. Maki Ogura and Mr.
Shoichiro Tsuruta for great efforts in drafting the guidance.
[Note] The definition of the words in English have not been
approved by the study group of the guidance for avoided GHGs
emissions in the Institute of Life Cycle Assessment, Japan.
References[1] International Council of Chemical Associations/World
Business Council for Sustainable Development Chemicals.
Adressingthe
AvoidedEmissions
Challenge.
http://www.icca-chem.org/iccadocs/
E%20CC%20LG%20guidance_FINAL_07-10-2013.pdf,(Accessed 21.08.2014).
[2] Green IT Initiative in Japan.
http://home.jeita.or.jp/greenit-pc/activity/reporting/110628/pdf/survey01.pdf (Accessed 21.08.2014).
[3] Kawasaki city.
http://www.city.kawasaki.jp/300/cmsfiles/contents/00000
45/45020/guideline.pdf (Accessed 25.08.2014)[4] Shiga Prefecture.
http://www.pref.shiga.lg.jp/d/new-energy/files/
kouken_tebiki_kaisetu.pdf (Accessed 25.08.2014).

�������������������������������������������������

P-003

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

158

Life Cycle Inventory Analysis for Environmental Footprints – Case Study on
Skin Care and Cosmetic Products
Hsin-Jui Wu and Yuh-Ming Lee*
National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
Because of global climate, the amounts of GHG emissions
become very important. Moreover, after Kyoto Protocol in
1997, the term “carbon footprint” is promoted globally. Until
now, the green mark and normal become very complex whichmake consumers confuse and decreased the credence.
European Union(EU) has a 3 years trial program, it’s
according to Product Environment Footprint Guide. From 2013
to 2016 .It has a unified standardization include scope
definition, reduction of carbon dioxide, which can countenvironment data and set up unitary label with one
standardization to resolve the firm verifies many times fromstate to state and load double fee for the same verification item.
[1]

information on green product market. It can help consumers toknow and recognize environment information easier andconsumers can compare different products using one standard.
For firm, besides cutting the multi-verification cost, there is also
a better public image via transparency of information.

2. Methodology
Along with the concept - life cycle analysis, this study isbased on inventory product environmental footprint especially
product carbon footprint.
According to British Standards Institute, Specification for theassessment of the life cycle greenhouse gas emissions of goods
and services, PAS2050 and ISO / DIS 14067, Taiwan
Environmental Protection Administration announcement“Carbon Footprint of Products and Services Guidelines” in
2008.
3. Study Targets
Information of green products, such as green shampoo orbody wash. We are seeking for a benchmark company, whichhave been coordinating with government’s policy, revealing
information that benefits the environment, conducting a
streamlined self-audit regarding corporate social responsibility
issues. For example, the specific product with PAS_2060 carbon
neutral.
TaiwanUK.

CarbonLabeling
4. Results and Discussions
We anticipate that, according to this 3-year trial program of
Product Environmental Footprint Guide [2], Program Industry
will use their successful experiences to make policy consensus.
One of the goals of environment footprint is to clarify

This table compare two products[3] [4], along with
Life-cycle analysis counts carbon emissions by each emission.
For all stages of a product-and-service cycle which frommaterial extraction through materials processing, manufacture,
distribution, use and disposal or recycling.
5. Summary and Conclusion
Since 2009, Taiwan government has been promoting
carbon label. There is still a limited usage for cosmetics
industry, mostly dish washing cleansers. If the corporations
would implement this concept to various types of the cosmetics
products, exposing the environment information of products,
then consumers would know carbon emissions in each stage of
cosmetic products, and furthermore industry can cut down
costs and improve profits by analysis every stage’s emissions.
Through this process, the value of green products should beenhanced.
References[1] Ning,Yu et al. ,Looking into EU's environmental footprint
laws from aspect of Taiwan's green products assessment,
Sustainable
Industrial
Development
Quarterly
no.66,2014.
[2] European Commission, Product Environmental Footprint
Guide , European Commission, 2013.
[3] HairO‘right
International
Corporation,
The
Carbon-Neutral report for 400ml green tea shampoo,
2011[4] The Carbon Trust, Product carbon footprinting: the new
business opportunity-Experience from leading companies,
The Carbon Trust, 2008.

�������������������������������������������������

P-004

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

159

Estimation of the Workload of Calculating GHG Emissions of Scope 3
Hideki Sasaki,* Sachiko Motoike, and Hiroshi Onishi
Panasonic Corporation, Japan*Corresponding author: sasaki.hideki001@jp.panasonic.com
1. Introduction
Withstrongerdemands
fordisclosureofenvironment-related information, disclosure of GHG emissionsin accordance with the Scope 3 Standard [1] is increasingly
expanding [2]. On the other hand, there is an issue that
calculation of emissions requires significant workloads.
Based on our review of calculated emissions andnecessary workloads, this is to propose ways to reduce
workloads required for emissions calculation.

accounted for about 93% of the total.
Figure 1 indicates category-specific relations between
emissions and workloads for specific categories. Emissions for
Categories 8 and 5 were low at around 0.03% of the total.
While exclusion from the scope of calculation had nearly no
impact on emissions, workloads decreased by 80%,
demonstrating that excluding these categories from calculation
was effective in reducing workloads.
(Million tons)

90
90

2. Approaches to reducing workloads
1) Given the relation between calculated emissions andnecessary workloads, we explored excluding categories of lesssignificance from the scope of calculation.
2) We considered using alternative activity data forcategories with large amounts of emissions and thereby subject
to calculation.

80
80

3. Exclusion of categories of less significance3-1. Estimation of workloads
Table 1 shows the estimated workload for each category.
Workloads necessary for garnering energy consumption
data of manufacturing sites are assumed as 4 man-hours permonth, based on information obtained from persons in charge
at said sites.
The total amount of workloads of all categories subject tocalculation of emissions was estimated to be 744,748
man-hours. Categories 1 and 5 accounted for about 95% of thetotal.

33

Table 1. Category-specific workload
Scope/Category
Scopes 1 & 2
1

Purchased Goods andServices

2 Capital Goods

Work subject to estimation;
Method of estimation or assumption

Fuel- and Energy-Related
3 Activities Not Included in Scope (Use the same data as Scopes 1 & 2)
1 or Scope 2

Upstream Transportation
4and Distribution

5
Scope 3

Waste Generated in
Operations

6 Business Travel

7 Employee Commuting

8 Upstream Leased Assets
Downstream
9 Transportation andDistribution
11 Use of Sold Products
End-of-Life Treatment of
12
Sold Products
Scopes 1, 2, and 3 total

Workload (man-hour)

Identify and report energy use per site;
Information obtained from person in charge
Implement survey per supplier (Of re-estimation
for Panasonic, costs paid by Panasonic);
Assumed as the same as Scopes 1 & 2
Identify and report the types of capital goods andamount of money per business division;
Information obtained from person in charge

Product weight and transportation distance;
Assumed as five times the workload after
introduction of system, based on information
obtained from person in charge
Measure, identify, and report the weight of waste
per site;
Information obtained from person in charge
Identify and report transportation-specific distanceand amount of money for business travels per site;
Information obtained from person in charge
Identify and report transportation-specific distanceand amount of money for employee commuting
per site;
Information obtained from person in charge
Identify and report energy use per site;
Information obtained from person in charge
Survey sales companies per country;
Assumed as the same amount of workload
required for supplier surveys
Identify and report the lifetime power consumption
per product;
Information obtained from person in charge
Identify and report the weight per product;
Assumed as the same as Category 11

13,2481.8%

659,520

88.6%

86

0.0%

-

14,8002.0%46,368

6.2%

528

0.1%

528

0.1%

3,648

0.5%

690

0.1%

2,666

0.4%

2,666

0.4%

744,748100.0%

Category 10 cannot be identified by Panasonic and therefore is not calculated. Categories 13-15 are inapplicable toPanasonic activities and are also not calculated.

3-2. Relation between emissions and workloads
Emissions for all categories amounted to approximately
168,060,000 tons. The top three categories with the mostemissions, namely Category 11, Category 1, and Scopes 1 & 2,

Category 11

Category 1

14
14

Reduction of workload through use of procurement costs data

12
12

44

Scopes 1 & 2More workloads

Category 7

22
11
00

0.5% of total emissions
Category 5

Category 8
0

10
10,00020
20,00030
30,00040
40,00050
50,000600
60,000700
70,000(Thousand Man-hours)

Figure 1. Relation between emissions and workloads
4. Use of alternative activity data
Workload required for calculating Category 1 throughsupplier surveys was estimated to be about 660,000 man-hours.
To reduce this workload, corporate procurement costs data andinput-output basic unit were used.
As a result, the workload necessary for calculation was
about 4-5 man-hours, showing that employing procurement
data in lieu of supplier surveys reduced workloads.
5. Proposals
1) Based on calculation of all items throughout Scopes 1-3,
exclude from future calculation the categories whose emissions
are small but workloads are heavy.
2) When the workload required for supplier surveys isextremely heavy in calculating Category 1, use procurement
costs data and input-output basic unit.
6. Summary
From the relation between GHG emissions and necessary
workloads, we explored reducing workloads required for
calculating emissions. We conclude that workloads can be
reduced by: excluding categories of less significance from thescope of calculation, or using procurement costs data in lieu ofsupplier surveys for calculation of Category 1.
References[1] WRI & WBCSD Corporate Value Chain (Scope3)
Accounting and Reporting Standard, 2011.
[2] CDP Global 500 Climate Change Report 2013, 2013.
https://www.cdp.net/CDPResults/CDP-Global-500-Clima
te-Change-Report-2013.pdf

�������������������������������������������������

P-006

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

160

Application of Life Cycle Assessment and Economic Rationality: A Cost Survey
Tomohiro Tasaki*1, Koichi Shobatake2, Kenichi Nakajima11, Carl Dalhammar3
1

National Institute for Environmental Studies, Japan; 2TCO2 Co. Ltd., Japan; 3Lund University, Sweden*Corresponding author: tasaki.tomohiro@nies.go.jp

2. Methods
First, we surveyed websites of 35 program operators in theworld, and obtained information about cost for the assessment.
We determined cost items (tasks) to be investigated (see Table1). Then, questionnaires asking costs and man-hour of the tasks
of a program were sent to the program operators by email. Thiswas carried out in April and May, 2014, and we received 15
effective responses (Europe 6; North America 5; Asia 4). For
cases when a program operator wanted to account for morethan one representative case, we asked the proportion of theoccurrence of each case in addition. The costs surveyed wereconverted from local currencies to USD, and adjusted with thecountry's PPP (purchasing power parity).
3. Results and discussion
The results of the cost survey are shown in Table 1. The
median of the overall cost (PCR and EPD) was $19k (Theaverage was $29k). Among the individual costs, the cost for
LCA and EPD preparation (hereinafter referred to as “cost of
LCA”) accounted for $15k and the largest. The median of the
man-hours for 1) PCR and EPD, and 2) LCA and EPD
preparation were 26 and 15, respectively. Deviations of the
distributions of man-hours were smaller than those of cost. The
total costs were smaller than the sum of their subitems, which
implies that program operators make effort to reduce costs by
avoiding duplicating tasks, etc. (e.g. for PCR and EPD, thetotal was $19k and the sum of subitems was $33.)
There are a variety of individual products from simple
ones to complex ones, and the cost of LCA varies depending

Table 1. Results of cost survey to program operators
Task

PCR

Scoping
Research & drafting
Review
Total
LCA & EPD preparation
Verification
Registration
Initial fees other than registration
Running fee
Total
Total

EPD

1. Introduction
Life cycle assessment (LCA) and similar tools based onlife cycle thinking have been used as a basis for many global
standards, product policy, and corporate decisions for a green
industry. Carbon Footprints and Type III labels are examples ofsuch practical applications. While LCA has become a very
important tool, it has not reached widespread application. LCA
has been developed with many discussions over its precision,comparability, verification and validity. Such a pursuit toward
objectivity and robustness of results may hinder its widespreaduse due to the high costs involved. Simplified assessment [1, 2]
is an alternative approach, used to increase the practicalusefulness. Moreover, emergence of social LCA [3] and LCSA(Life Cycle Sustainability Assessment) [4] expands impact
categories to be assessed and makes it harder to conduct such
LCAs. Is a limited number of applications with a detailed oradvanced assessment preferable to a large number ofapplications with a simpler assessment? How do stakeholders,
especially decision makers in industries, value such different
ways of application of LCA and similar tools? One of themetrics to determine what is preferable is cost: economic
rationality. However, information on the actual cost andworkload associated to conducting LCAs and creating PCRs
(Product Category Rule) and EPDs (Environmental ProductDeclarations) has been very limited.
In this study, we conducted a survey on the average roughprice and workload to create PCRs and EPDs of different
program operators with a purpose of examining what would bea rational, practical application of LCA for the whole society.

* Totals are not the sum of the subitems.

Lower
485
2,114
1,013
2,738
8,365
2,108
663
528
587
10,30912,509QuatilesMedian
1,693
5,928
5,072
15,00015,250
2,447
1,312
750
973
12,826
18,761

Upper
3,375
17,563
8,587
25,62522,745
3,413
2,629
947
1,531
30,001
41,238

n
6
8
7
9
12
12
9
6
10
15
15

on products. Iteration of LCA of similar products would reducethe cost of LCA. Moreover, a PCR can be reused by otherindividual products belonging to the same commodity. Hence,the cost of assessing an individual product is somewhere
between the cost of LCA & EPD preparation and the cost of thesum of all the cost items (i.e. from $15k to $33k). Next,
neglecting these diverse situations, we discuss what the cost oftens of thousand dollars implies for the use of LCA.
Measures should be taken if benefits are larger than costs.
When considering product sale and implementation of anenvironmental measure, this can be written as:
Sales profit + Environmental benefit by implementing ameasure > Cost of LCA + Cost of implementing a measure.
However, the environmental benefit is usually externalized in anormal economic state, and therefore excluded for the
economic calculation, so
Sales profit > Cost of LCA + Cost of implementing a measure> Cost of LCA;
that is, cost of LCA must be smaller than profit of sales unlessprivate companies gain a profit from the environmental benefit.
Assuming that profit is about 10% of sales, annual sale of$100k, equivalent to 107 yen, would be required. FromJapanese point-of sales data obtained in 2008 or 2009, 49% of
TVs were sold more than this figure while only 14% of clothes
detergents and 21% coffees were done so. This suggests that
only expensive or major products can afford to apply
conventional, detailed LCA.
If we would like to expand items of assessment, like
LCSA, we need to devise alternative approach of assessment.
We also should examine what kinds of products are suitable toapply conventional LCA methodology from a viewpoint of
economic rationality, and specify such products concretely.
Acknowledgments
Several anonymous program operators kindly participatedin this survey. We sincerely express our appreciation to theircooperation.
References[1] SETAC Europe. Simplifying LCA: just a cut? 1997.
[2] Tasaki, T., et al. J. Ind. Ecol. 11(4): 64–84, 2007.
[3] UNEP. Guidelines for Social Life Cycle Assessment for
Products. 2009.
[4] UNEP. Towards a Life Cycle Sustainability Assessment. 2011.

�������������������������������������������������

P-007

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan161

SCOPE3 of Kogakuin University
Atsushi INABA1*, Kou MIYATA1, Koji TANAKA2
1
Kogakuin University,Japan; 2es.feed, Japan*Corresponding author: a-inaba@cc.kogakuin.ac.jp

1. Introduction
Recently the Scope3 GHGs emissions have been paid
attention by large companies in the world and also in Japan,
which guidance published in November 2011 by WRI/WBCSD(They called it as Scope3 Standard). The Ministry ofEnvironment and the Ministry of Economy, Trade and Industryof the Government of Japan followed this activity andpublished the guidance in March 2012 to show how it should
be conducted exactly in Japanese companies [1]. The guidanceof WRI/WBCSD listed 15 categories related to the activities of
the targeted organization, in which the organization shallcalculate the whole GHG emissions related to their activities
including the organizations underlining in their value chain. In
this paper, the calculation result of Scope3 CO2 emission of
Kogakuin University was reported. It might be the first casestudy of Scope3 by University in Japan.
2. Calculation
The calculation of the Scope3 CO2 emission was
conducted mainly using the expenditure data of Kogakuin
University in fiscal 2012, and the energy and water
consumption data collected for ISO-14001 was usedcomplementarily.
Around 110 thousand items of the expenditure wereclassified into 465 categories, and then they were multiplied by
the CO2 emission factor of each items provided by the Milca[2]and the 3EID[3] database for LCA..
3. Results and Discussion
3.1. Expenditure of Kogakuin University
The total amount of the expenditure of Kogakuin
University in fiscal 2012 was 11.3billion yen. The expenditures
such as salary of employee were excluded because they are notrelated to the CO2 emissions. And also, the leased assets, which
are shown as category 8 and 13 in the guidance of Scope3,
were excluded because the calculation method has not beestablished yet. As the result, we calculated Scope1, Scope2
and Scope3 for the expenditures of 47.5 billion yen, which was
53.0% of the total expenditure, which included the expenditure
for education and research, administration, maintenance offacilities, commuters tickets, business travel and so on.
3.2. Ratio of each Scope on Expenditure and CO2
The CO2 emission of Kogakuin University was totally
1.61E+04t. The amounts of Scope1, Scope2 and Scope3 were
1.19E+02t, 7.13E+03t and 8.81E+03t respectively. Fig.1 shows
the ratio of each scope on the expenditure and on the CO2
emission. The scope3 had 92.9% on the expenditure, but only
54.8% on the CO2 emission.
The ratios of the CO2 emission of each category of Scope3
to the total CO2 emission of Scope3 are shown in Table 1. The
CO2 emissions of Scope3 in Kogakuin University could be
divided into 7 categories among 15 categories listed in theguidance. The largest amount (68%) of the Scope3 CO2emission was caused by category 1, the goods and services
purchased by Kogakuin University. The second was thecategory 2 like purchasing machine and vehicle. The businesstravels and commuters tickets were almost the same, which had
the third position.

Expenditure
0.06%

5.37%

Scope10.74%

94.58%

Scope3

Scope2

54.8%

44.4%

CO2 Emission
0%

20%

40%

60%

80%

100%

Fig.1 Ratio of Scope1,2 and 3 on Expenditure and CO2
emission
Table1 CO2 emission of Kogakuin University
Total
16,631t
Scope1119t (0.74 %)Scope2
7,135t (44.4 %)Scope39,377t (54.8 %)Category 1
68%
Stationery, PC, printer,
book, paper, experimental
goods, maintenance offacilities ...
2
13%
machine, vehicle...
55%waste treatment, recylce ..
66%business travel ..
75%commuters ...
82%rental91%
mail
4. Conclusions
The Scope3 CO2 emission had 54.8% of the total CO2
emission of Kogakuin University. The measures to reduce
Scope1 and 2 CO2 emissions were executed so far, but themeasures to reduce Scope3 CO2 emission shall be executed in
the future. It includes the measures to buy the eco-products
more, to reduce the amount of waste and so on.
This study has a limitation using the data provided by
Kogakuin University. It does not include the life of the students
such as commute from home to University, having a lunch,buying PC, etc. The system boundary of the Scope3 CO2emission for University shall be re-considered.
Acknowledgments
This study was conducted by "Grants-in-Aid Scientific
Research".
References[1] Ministry of Environment, (accessed on 30.08.2014)
http://www.gvc.go.jp/business/files/GuideLine_ver2.1.pdf[2] LEMAI, http://www.milca-milca.net/ (accessed on
30.08.2014)[3] 3EID,
http://www.cger.nies.go.jp/publications/report/d031/jpn/in
dex_j.htm (accessed on 30.08.2014)�������������������������������������������������

P-008

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

162

Life cycle co-benefit of industrial and regional symbiosis: Environmental input-output
analysis on typical resource dependent city in China (P008)
Liang Dong,*1,2 Tsuyoshi Fujita,1 Minoru Fujii,1 Satoshi Ohnishi,1 Takuya Togawa,1 Huijuan Dong,1

1Center for Social and Environmental System Research, National Institute for Environmental Studies, Japan; 2Graduate schoolof Environmental studies, Nagoya University, Japan*Corresponding author: dong.liang@nies.go.jp

utilization could generate more co-benefits, flying ash reuse
could only reduce the total amount of solid wastes, but increaseenergy consumption and related air pollutants. Hence, smart
design on IS patterns by considering the local realities iscritical.
S4:Straw/biomass
Powergeneration

Waste steel

Steam

Steel

Ammonia

Fertilizer

COG

AmmoniumsulfateIron and steel
makingSteel slag

Steam

BF slag

1. Introduction
Resource dependent cities, in which natural resource
mining and material process industries (e.g. iron/steel, cement,
ferrous and non-ferrous metallurgy industry) are dominated, is
big issue for China’s sustainable urban development (emissions,bulky solid waste…). NDRC launched “Resource dependent
cities project” (2013->2020) to address this issue.
Industrial symbiosis (IS) provides smart solution toresource dependent city. It emphasizes unrelated industries
exchange materials, energy and/or by-products in a mutually
beneficial way (Chertow, 2000, 2007). Through IS, it could
optimize the flows in the network.
This study conducts a scenario analysis on co-benefit, in
typical resource dependent city in China. Focusing on: (1)Co-benefit: evaluating how IS can facilitate energy saving,
CO2 and air pollutants reduction in the life cycles, using I-O
model. (2) Investigate CO2 emissions particularly. (3)Address
policy implications for China’s sustainable urban development.

S2：
Scrap tire

Communities

S1：Waste plastic
Unit: per year
>2 Mt

S3：Coal flying ash

Cement &Construction

1 to 2 Mt
0.2 to 1 Mt
10 to 200 kt

2. Methodology and Case study
This paper applied hybrid physical input and monetary
output model (HPIMO) to assess how industrial symbiosis
could affect the energy consumption and waste reduction foreach sector (Table 1). For specific IS process, it is analyzed
with process LCA. We calculated the life cycle CO2 emission
change from the change of raw material consumption, energy
consume in production, waste emissions/disposal andtransportation in up-stream and down-stream under the
scenarios.

PlannedFigure 1 Current (solid line) and planned (dotted line) IS
network and quantified material flow in Liuzhou, China

Table 1. Structure of HPIMO model

Figure 2 CO2 and Air pollutants reduction in total life cycles
4. Conclusion and policy implication
IS is one effective and efficient approach to reduce both
virgin material consumption and waste emissions. Particularly,
IS could not only contribute to solid waste reduction, but also
to the CO2 reduction and SO2, NOX reduction.
Select one typical resource dependent city in southern
China, named Liuzhou. Based on an analysis on the industry
and current IS in Liuzhou, design BAU/4 IS scenarios in year
2015 (Figure 1): (1) S0-Business as usual; (2)S1-Waste plastics
recycling(red line); (3) S2-Scrap tires recycling(blue line); (4)S3-Flying ash recycling (green line); (5) S4-Biomass
utilization (yellow line).
3. Results and discussion
The results show that IS could contribute to waste
reduction and further generate co-benefits of energy saving,
CO2 mitigation and air pollutants reduction (Figure 2).
Dramatic life cycle emissions could be reduced by IS.
Results also indicate that different IS efforts may bringdifferent benefits. While waste plastics recycling and biomass

Acknowledgments
This research is financially supported by the Environment
Research and Technology Development Fund (2-1404) of the
Ministry of the Environment, Japan.
References[1] Chertow, M.R., 2000. Industrial symbiosis: literature andtaxonomy. Annual Review of Energy and the Environment 25,
313-337[2] Chertow, M.R., 2007. “Uncovering” Industrial Symbiosis.
Journal of Industrial Ecology 11, 11-30.
[3] H. Zhang, L. Dong, H. Li, B. Chen, Q. Tang and T. Fujita,
Investigation of the residual heat recovery and carbon emission
mitigation potential in a Chinese steelmaking plant: A hybridmaterial/energy flow analysis case study, 2013. Sustainable
Energy Technologies and Assessments, 2:67-80.

�������������������������������������������������

P-010

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

163

Projection of demand and supply change of first generation biomass
Yuri Hirako,*1 Kenji Koido1 and Kiyoshi Dowaki1
1

Tokyo University of Science, Japan;*7413612@ed.tus.ac.jp

1. Introduction
Recently, the large amount of greenhouse gases (GHGs)
emissions due to the fossil fuel use has caused the serious
problem all over the world. For the abatement countermeasure,the promotion of renewable energy, especially, bio-fuel would
be promising. However, in the case that the biomass material isconsumed as feedstock of bio-fuel, it is said that the serious
competition between food and feed would be faced. For
instance, in US, the agricultural products which are harvested
are mainly maize. The agricultural product would be available
for food and/or feed, too.
On the other hand, a couple of researches on foodconsumption are being executed. But, according to the recent
results, it implies that the serious food competition would notalways occur, if its consumption rate and sustainable supply
chain are considered.
In this paper, on the supplies and demands of barley, maize,
sugarcane, rice paddy and wheat from 2020 to 2030, we
estimated the potential on whether the food balances of these
agricultural products would fall into critical situations in thefollowing countries: Australia, Brazil, Canada, India, Indonesia,
Japan and US. We showed the extremely significant evidences
based on the pass analysis and/or the system dynamics model.
2. Materials and methods
According to FAO data, the large amounts of barley, maize,
rice paddy, sugar cane and wheat in our target countries are
harvested, and they are consumed for diet, feeding for livestock.
Or they would be biomass material for fuel production.
Especially, using the feedstock, bioethanol production has
already been established. Every country that doesn’t include
Japan are major agricultural producers and their all
governments have had their own bioenergy policy [1].
Table1. Each country’s bio-fuel policy
Countries
Brazil
India
Japan
U.S.

Bio-fuel policy
Flex cars or E25
E20 by 2017
0.5 million KL by 2017
136 million KL by 2022

In this paper, we focused on total LCCO2 mitigation policy,
especially, in Japan. Because EU countries who are very far
from Japan would not bring the good effect.
So far, we executed the total biomass material balances ineach agricultural product [2]. This time, we investigate thedynamic effect of these products. That is, we think that thecrops yield, GDP, the population and food balances etc. would
be influenced. Thus, at the second step, we estimated the
products composition of every year in every target country andthe feed consumption per protein [t-crop/ t-protein].
The future prospects of demand and supply on the first
generation biomass material were calculated based on the pathanalysis, which is one application technique of multiple linear
regression analysis.
The system dynamics which can deal with internal
feedback loops and time delays is an approach to understandthe behavior of complex systems over time.
3. Results
Table 2 shows the results of path analysis First generation
biomass consumption forecast in 7 areas. The sign of ○represents “non-competitive” and that of × represents“competitive”. According to the result of path analysis,
although there would be competitive status in almost countries,
it implies that 3 countries and 4 corps would not cause theserious problem. For instance, the amounts of sugar cane andwheat in Brazil would be available for bioethanol production of
4,753 KL/yr and 352 KL/yr as of 2020 (See Figure 1). Those ofbarley and maize in Japan would be 3,353 KL/yr and 7,596
KL/yr as of 2020.
Table 2. First generation biomass consumption forecast
Rice
Sugar
Barley
Maize
Wheat
Paddy
Cane
Australia
×××××
Brazil×××○○
Canada
×
×
×
×
×
India
○
×
×
×
×
Indonesia
×
×
×
×
×
Japan
○
○
×
×
×
U.S.
○
×
×
×
×
䢳䢼䢢䣄䣴䣣䣼䣫䣮䢢䣖䣱䣶䣣䣮䢢䣇䣶䣑䣊䢢䢳
䢳䢼
䢴䢼
䢵䢼

䢶䢲䢲䢲䢲䢲䢲䢲
䢺䢲䢲䢲䢲䢲䢲䢲
䢴䢲䢲䢲䢲䢲䢲䢲䢲

䢳䢼
䢴䢼
䢵䢼

䢴䢲䢲䢲䢲䢲䢲䢲
䢶䢲䢲䢲䢲䢲䢲䢲
䢳䢲䢲䢲䢲䢲䢲䢲䢲䢴䢼䢢䣄䣴䣣䣼䣫䣮䢢䣖䣱䣶䣣䣮䢢䣇䣶䣑䣊䢢䢴䢵䢼䢢䣄䣴䣣䣼䣫䣮䢢䣖䣱䣶䣣䣮䢢䣇䣶䣑䣊䢢䢵

䢴
䢳

䢳䢼
䢴䢼
䢵䢼
䣒䣣䣩䣧䢢䢳

䢲
䢲
䢲

䢳
䢳
䢲䢰䢲䢲

䢴

䢵

䢳
䢴䢰䢹䢷

䢴

䢴

䢵

䢵

䢵
䢷䢰䢷䢲
䣛䣧䣣䣴䣵

䢺䢰䢴䢷
1:55

䢳䢳䢰䢲䢲
2014年9月2日

Note: low variant (blue line) shows 40,000KL/yr, and highvariant (pink line) shows 200,000KL/yr.
Figure 1. Brazil case from 2020 to 2030
䣗䣰䣶䣫䣶䣮䣧䣦

4. Discussion
In this study, there should be uncertainties to some extent
in the future projection. Also, we have to pay attention to theirtrends which are food security and energy security,
simultaneously. Considering these issues, we try to propose thefood and bio energy policy.
References[1] JX Nippon Oil & Energy:http://www.noe.jx-group.co.jp/b
inran/part01/chapter06/section03.html (Accessed
22.07.2014).
[2] Yuri Hirako., et al. Future prospects on demand andsupply of bio-ethanol of the first generation biomass
resource origin : The 9th Meeting of the Institute of Life
Cycle Assessment, Japan: 282-284,2014�������������������������������������������������

P-011

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

164

Deecision supporting toool for sustainable dairry cow systeemCChun-Youl
Baeek*1, Kiyotaka
ka Tahara1, Ku
un-Mo Lee 2, anda Kyu-Hyunn Park3
1

AIST, Japan,, 2Ajou Universsity, Korea, 3Ka
angwon Nationa
al University, K
Korea*Corresponnding author: c.baek@aist.go.jjp

1. Introductioon
One of tthe major objeectives of this research wass todevelop a tooll that allows thee control of env
vironmental asppect
and economic aspect from a dairy cow systeem by considerringmposition, grow
wth phase, enteeric
variables suchh as feed com
fermentation, and manure management. Of these, ffeed
ntrollable variabble.
composition iss the most influuential and con
Therefore, anyy abatement measuremappliedd for the reducttionof environmenntal load and growthgof econoomic profit frommadairy cow syystem must innclude the con
ntrol of the ffeed
composition. Thus, it requires that a tool for control ofparameter succh as feedstuffss with lower ennvironmental looad,high economicc profit on similar nutriment shhould be used.
2. Materials aand Method
Decision supporting toool (D.S. tool) was proposed forsustainable daairy cow system
m based on a GHG
Gemission forenvironmentall aspect and Liffe cycle cost (LLCC) for econom
mic
aspect from eaach life cycle sttage of dairy cow system. For tthis
tool, the param
meter and system boundary off dairy cow systtem
was identifieed in shownn fig.1. The GHG emisssion
qualification was used a methodmbased on a life cyycle
assessment (LLCA) approach incorporating the IPCC’s GH
HG
emission calcuulation equationns. The annualized net revenuee of
feed companyy and farm was used for LCC byb integration ffeed
company-oriennted LCC and farm-oriented LCC in orderr tocontrol variablle parameter.

Pre-faarm�������� ��������������� � �∑������ � ������ � ����� �� � ��� �������
�������� ���������� �∑�����������
��� ��������� ������������� ������
���� ��������������� �����������

�������� ���������� ��������� ����������� � ������� ����������

wheree, ������� �����
C of jth feed pro
oduction due too����������� , LCC
thhthe feeding in the k growth phase,, won/f.u.; ������ , raw materiall
cost ofo ith feedstuff, won/kg; ����� , transport cost of ith feedstuff,,won/kkg; ����� , manufacture cosst of ith feed
dstuff, won/kg;;���������� , ratio in maass fraction of tthe ith feedstuff
ff to the jth feeddth
in the k growth phase; �������� ���������� , LCC of feedd
produ
uction due to the feedingg on farm, won/f.u.
w(feeddcompaany-oriented LCC);
L�������� ���������� ���� , profit off����feed companycdue too the feeding onn farm, won/f.u..
On-fa
arm
����������� �∑������������ �� �������� �����
��������� �������������� ���� �������������������� ������������
∑������ ���������
�������� ������� ���������� ������� �������������� ������������ ��������� � ��� �������� � ����� �������������������� ����� ������������������ � ���������� �

wheree, ���������� , LCC due to th
the feeding in the kth growthh
phase (farm-orienteed LCC), wonn/f.u.; ��� �������������������� ,LCC of operation, won/f.u; ��� ��������� , incom
me due to theesellingg raw milk (FPM
MC), won/f.u.
4. Ressult and discusssion

Figure 1 S
System boundaary and 3 aspectts for D.S. tool
We consiidered two asssumptions related to the datacollection andd processing parameter:pi) datadcollection andprocessing in each life cyclee stage, which includes
ithe groowth
phase of the llivestock and thhe type of feed
d in a given groowth
phase, followss the national feedingfstandarrd for dairy coow inorder to meett the requiremeent of nutrimen
nt, and ii) pre--farmand on-farm w
were limited to one
o feed compaany and one farmrm.
The GH
HG emissions for environm
mental aspect wascalculated by a method [1] anda LCC of daairy cow system
m foreconomic aspeect was describbed in this papeer as below andd thefunctional uniit (f.u.) of a daairy cow systemm and the referrence
flow chosen w
were 1kg of raaw milk FPMC. The key equaationw.
(feed production and breedingg) for LCC calcculation is below

Figurre 2 Result of L
LCC and GHG
D.S tool was pro
oposed in orderr to control the environmentall
aspectt and economicc aspect of dairry cow system by consideringg
the opperating variables of the systeem such as feeed composition,,
growtth phase, enterric fermentationn, and manuree management..
The proposedptool allows straighttforward identiification of thee
key activities and paarameters and ccan support thee policymakingg
for suustainable dairy cow system.
Referrences[1] Baek, C.Y. et al. Quantification and control of the greenhouseegaas emissions fromfa dairy cow system. J of Cleanerrprroduction 70: 50
0-60, 2014�������������������������������������������������

P-012

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

165

Domestic Consumption and Household Stock of Storage Media in Japan
Junya Yano,*1 Misuzu Asari1, and Shin-ichi Sakai1
1

Environment Preservation Research Center, Kyoto University, Japan*Corresponding author: yano@eprc.kyoto-u.ac.jp

1. Introduction
Some studies have focused on the disposal of
consumer-grade media reproduction devices, such as DVD(digital versatile disc) recorders, audio players, digital cameras,
and so on [1, 2]. However, few studies have focused on waste
management of the storage media itself. The purpose of thisstudy was to research the current domestic consumption andstock of household storage media in Japan.

billion, accounting for 13% of the accumulated total number ofsales. Of the total sales of magnetic tape, roughly 37－40%
were stocked.
There were some uncertainties for the newer storage
media, such as BD, which, due to their relative recentness on
the market, have low recognition with the public. It should also
be noted that the amount stocked changes from year to year.
HDD (3.5 inch)
HDD (2.5 inch)
Compact memory cards
BD (for video)
Rewritable BD (many)
Rewritable BD (once)
DVD (for video)
Rewritable DVD (many)
Rewritable DVD (once)
CD-RW
CD-R
CD (for music)
Recordable MD
Floppy disk
MO
Recorded VHS
Recordable VHS
Recorded ACC (music)
Recordable ACC

𝑆𝑆𝑗𝑗

𝑁𝑁𝑖𝑖

𝑃𝑃𝑖𝑖,𝑗𝑗

𝑈𝑈𝑖𝑖,𝑗𝑗::::

𝑆𝑆𝑗𝑗 = ∑ 𝑁𝑁𝑖𝑖 × 𝑃𝑃𝑖𝑖,𝑗𝑗 × 𝑈𝑈𝑖𝑖,𝑗𝑗(1)

Stock number of storage media 
Population of age group Percent of people in age group  who own one
or more storage media 
Unit stock per person of age group  whoowns one or more storage media 

2. Results and discussion
Estimated results of domestic storage media consumption
by weight between 1988 and 2011 is shown in Figure 1. In
2011, consumption by weight decreased to around 100 Kt. The
most storage media consumed was around 140 Kt in 1998.
These data are attributable to the changes in media types over
the years, trending towards smaller, more compact forms.
Consumption increased by 73% from 1.1 billion units in 1988
to 1.8 billion units in 2011. The data capacity of the media
consumed in 2011 was 58 EB (1018 bytes), which is 37 times
greater than that of 1988.
Estimated household stock and disposal potential as of2011 is shown in Table 1. The accumulated total number ofsales before 2011 was estimated to be 34 billion. Of that,approximately 60%, 21 billion was stocked in households. This
number was roughly 11 times the annual number of sales in
2011, 1.8 billion. Disposal potential was estimated to be 4.5

Domestic consumption （103 ton/yr）

160

2. Materials and methods
Domestic storage media consumption was estimated using
statistical data reported by such agencies as METI [3] andRIAJ [4]. This data included domestic production, import,
export, and domestic sales, all between 1988 and 2011. Theseestimations included storage media used in both households
and businesses because the distribution rate was unidentified.
To estimate household stock and disposal potential, aninternet-based survey was conducted in January 2013. Three
thousand people over the age of 15 were sampled and separated
into six age groups. Questions included input, stock, and output
numbers of each storage medium in the respondents’ household.
Each storage medium was distinguished by two groups basedon intended use, “for personal use” and “for sharing withfamily.” The reported number of storage media shared withfamily was divided by 2.14, the average number of people perhousehold in Japan, to estimate the total number of storage
media per person. Then, stock number of storage media wasestimated by using by Eq. (1). In addition, the number ofdisposal potential was also questioned.

140
120
100
80
60
40
20
0

Figure 1. Domestic consumption of storage media type
between 1988–2011 by weight
Table 1. Household stock and disposal potential ofstorage media in 2011 by millions of units sold㻭㼏㼏㼡㼙㼡㼘㼍㼠㼕㼚㼓㻿㼠㼛㼏㼗㼠㼛㼠㼍㼘㻌㼟㼍㼘㼑㼟 㼕㼚㻌㼔㼛㼡㼟㼑㼔㼛㼘㼐㼟㻿㼠㼛㼏㼗㻌㼕㼚
㻰㼕㼟㼜㼛㼟㼍㼘
㼔㼛㼡㼟㼑㼔㼛㼘㼐㻛㻭㼏㼏㼡㼜㼛㼠㼑㼚㼠㼕㼍㼘㼙㼡㼘㼍㼠㼕㼚㼓㻌㼠㼛㼠㼍㼘㻛㻭㼏㼏㼡㼙㼡㼘㼍㼠㼕㼚㼓㼟㼍㼘㼑㼟㼠㼛㼠㼍㼘㻌㼟㼍㼘㼑㼟㻰㼕㼟㼜㼛㼟㼍㼘
㼜㼛㼠㼑㼚㼠㼕㼍㼘㻔㻹㼕㼘㼘㼕㼛㼚㻕㻔㻹㼕㼘㼘㼕㼛㼚㻕㻔㻹㼕㼘㼘㼕㼛㼚㻕

㻙

㻭

㻮

㻯

㻮㻛㻭

㻙
㻯㻛㻭

㼂㼕㼐㼑㼛㻌㼠㼍㼜㼑

㻡㻘㻟㻥㻝

㻞㻘㻝㻟㻣

㻝㻘㻝㻥㻠

㻟㻥㻚㻢㻑

㻞㻞㻚㻝㻑

㻭㼡㼐㼕㼛㻌㼠㼍㼜㼑

㻡㻘㻣㻟㻟

㻞㻘㻜㻥㻝

㻤㻞㻢

㻟㻢㻚㻡㻑

㻝㻠㻚㻠㻑

㻯㻰㻙㻾

㻠㻘㻡㻥㻡

㻞㻘㻤㻠㻞

㻢㻡㻢

㻢㻝㻚㻥㻑

㻝㻠㻚㻟㻑

㻻㼠㼔㼑㼞㻌㻯㻰㼟

㻤㻘㻝㻠㻤

㻡㻘㻥㻥㻤

㻣㻠㻡

㻣㻟㻚㻢㻑

㻥㻚㻝㻑

㻰㼂㻰㻙㻾

㻢㻘㻤㻥㻟

㻟㻘㻤㻠㻟

㻢㻡㻡

㻡㻡㻚㻣㻑

㻥㻚㻡㻑

㻻㼠㼔㼑㼞㻌㻰㼂㻰㼟

㻞㻘㻟㻠㻤

㻞㻘㻜㻥㻠

㻞㻣㻤

㻤㻥㻚㻞㻑

㻝㻝㻚㻥㻑

㻾㼑㼏㼛㼞㼐㼕㼚㼓㻌㻮㻰

㻡㻤㻠

㻡㻤㻠

㻠㻤

㻝㻜㻜㻚㻜㻑

㻤㻚㻞㻑㻻㼠㼔㼑㼞㻌㻮㻰㼟

㻢㻥

㻞㻝㻢

㻝㻟

㻟㻝㻞㻚㻢㻑

㻝㻥㻚㻠㻑㼁㻿㻮㻌㼒㼘㼍㼟㼔㻌㼙㼑㼙㼛㼞㼥

㻺㻭

㻞㻡㻞

㻟㻟

㻺㻭

㻺㻭

㻯㼛㼙㼜㼍㼏㼠㻌㼙㼑㼙㼛㼞㼥㻌㼏㼍㼞㼐㼟

㻠㻞㻜

㻟㻤㻟

㻟㻥

㻥㻝㻚㻟㻑

㻥㻚㻟㻑

㻱㼤㼠㼑㼞㼚㼍㼘㻌㻴㻰㻰㼀 㼛 㼠 㼍㼘

㻺㻭

㻥㻤

㻝㻝

㻺㻭

㻺㻭

㻟㻠㻘㻝㻤㻝

㻞㻜㻘㻡㻟㻥

㻠㻘㻠㻥㻤

㻢㻜㻚㻝㻑

㻝㻟㻚㻞㻑

NA: no statistical data
3. Conclusion
This study clarified the transition from domestic
consumption to household stock and the disposal potential forstorage media. Some storage media contain valuable
substances such as cobalt in magnetic tape and silver in digital
optical disks. In the future study, evaluating the resource
potential of each storage medium is needed in considering
proper waste management.
4. References[1] Oguchi M., et al. Resource, Conservation and Recycling
52 (3): 463-480, 2008.
[2] Oguchi M., et al. Waste Management 31(9-10):2150-2160, 2011.
[3] Ministry of Economy, Trade and Industry (METI),
Yearbook of machinery statistics,
http://www.meti.go.jp/statistics/tyo/seidou/result/ichiran/0
8_seidou.html (Accessed 01.08.2013) (in Japanese).
[4] Recording Industry Association of Japan (RIAJ), Web site,
http://www.riaj.or.jp/(Accessed 01.08.2013) (in Japanese)�������������������������������������������������

P-013

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

166

Eco-Efficiency Assessment of ICT Product Systems
An Example of Set--Top Box
Jun-Yi Chiang and Yuh-Ming Lee*

National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
Eco-efficiency has been established as a crucial concept
for corporate environmental management. However thisconcept has been discussed in the environmental management
discourse for more than a decade (Schaltegger and Burritt 2000,
49ff). On the institutional level, the World Business Council of
Sustainable Development (WBCSD) has strongly promoted
ecoefficiency as a concept for businesses to pursue.
“ways of reducing their impact on the environment while
continuing to grow and develop” (WBCSD 2000; cf. Verfaillieand Bidwell 2000;DeSimone et al. 1997). [1]Organization for Economic Cooperation and Development(OECD) has developed and promulgated international policies
which aimed at preventing and reducing waste generation andmanaging the residues in an environmentally sound manner. [2]
2. Methodology：：Life cycle assessment and Eco-Efficiency
Evaluation
Life Cycle Assessment is a process to evaluate theenvironmental burdens associated with a product, process, or
activity by identifying and quantifying energy and materials
used and wastes released to the environment; to assess theimpact of those energy and materials used and releases to theenvironment; and to identify and evaluate opportunities toaffect environmental improvements. The assessment includes
the entire life cycle of the product, process or activity,
encompassing, extracting and processing raw materials;
manufacturing, transportation and distribution; use, re-use,maintenance; recycling, and final disposal.
There are four linked components of LCA: [3]• Goal definition and scoping: identifying the LCA's
purpose and the expected products of the study, anddetermining the boundaries (what is and is not included in the
study) and assumptions based upon the goal definition.
•Life-cycle inventory: quantifying the energy and raw
material inputs and environmental releases associated witheach stage of production.
•Impact analysis: assessing the impacts on human healthand the environment associated with energy and raw material
inputs and environmental releases quantified by the inventory.
•Improvement analysis: evaluating opportunities to reduceenergy, material inputs, or environmental impacts at each stageof the product life-cycle.
Eco-efficiency embraces other business concepts, such as“pollution prevention”, “cleaner production” and “ waste
minimization”. It shares characteristics with “design for theenvironment” and features a “life-cycle” perspective. In
addition, it is a logical extension of the “Total Quality
Management” concept. Where eco-efficiency differs from andgoes beyond other managerial instruments is in its strong focus
on creating value by making the challenge of sustainability abusiness opportunity. And this is what eco-efficiency is allabout: combining the goals of business excellence andenvironmental excellence and creating the link through which
corporate behavior can support sustainable development.[4]Eco − eficiency =Product or service value
Environment inluence

3. Study Target : Set-Top Box – An ICT Product
The emergence of internet and communication technology
has led to the development of ICT industry. ICT plays animportantroleofunifying
communications
andtelecommunications industries. The ICT industry includes
electronic components manufacturing, computer Electronic andoptical products, telecommunications and information industry.
Set-top box is one of the important industries under the
category of ICT. A set-top box (STB) or set-top unit (STU) is
an information appliance device that generally contains a
TV-tuner input and displays output connects to a television set
and an external source of signal, turning the source signal into
content in a form that can then be displayed on the televisionscreen or other display device.
4. Inventory and Indicators
This study conducts a Life Cycle Inventory analysis ofproduct and computes the Environmental Footprints of a
set-top box by evaluating the input and output of the raw
materials provided by supply chain, the production process, theemission of pollutants, the waste disposal, and so on.
They are recommending five generally applicableindicators for measuring environmental influence:[5]• Energy consumption• Materials consumption• Water consumption• Greenhouse gas emissions• Ozone depleting substance emissions
5. Conclusion
This article presents a procedure for calculating
eco-efficiency on the operational level. The proposed
procedure for calculating operational eco-efficiency combines
environmental assessment and valuation. Relying on the toolsof life-cycle assessment (LCA) and environmental impact
assessment (EIA), The proposed definition incorporates direct
and indirect (external) environmental costs and benefits. point
to the challenges of implementing this tool in a scientificallyaccurate and practically cost-efficient way.
Eco-efficiency
reports
informabout
economic
performance in addition to the environmental performance
while sustainability reporting encompasses social, economicand environmental aspects. In the search for an eco-efficient
corporate investment policy.
6. References[1] World Business Council for Sustainable Development.
2000; cf. Verfaillie and Bidwell 2000; DeSimone et al.
1997[2] IPCC, 2006 IPCC Guideline for National GHG Inventory,[3] SETAC, 1990, Technical Framework for Life-Cycle
Assessments, SETAC and SETAC Foundation
Washington, DC.
[4] World Business Council for Sustainable Development,
2008, Operational ECO-EFFICIENCY.
[5] Department of Industrial Economics and Technology
management, 2002 , Industrial Ecology and
Eco-Efficiency - An introduction to the concepts.

�������������������������������������������������

P-014

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

167

A visualization system for carbon footprint of products on mobile devices
Zhao Peijiang*1, Gun Suzuki1, Koji Nagano1 and Kazuhiko Sato1
1
Muroran Institute of Technology, Japan*Corresponding author: 14096014@mmm.muroran-it.ac.jp

1. Introduction
Carbon Footprint of Products (CFP) is a term used todescribe the amount of greenhouse gas (GHG) emissions
created in all processes from raw material production todisposal or recycling [1]. The CFP can not only show thequantity of GHG emissions, but also the data for the CFP can
indicate details of production. Manufacturers can know how
much they create GHG in each process based on the CFP.
Therefore the CFP can help the manufacturers to cut down
GHG emissions. It is necessary to collect data on raw material
and all processes of production when we calculate the CFP. The
data on the production are important in product security,especially for food. Consumers buy products whose security
are proven. The CFP can also help consumers to create theirsecure and low carbon life.
This report describes our new system on mobile devices
that inform the CFP to consumers. Our system is designed sothat consumers can be familiar with the CFP.
2. Outline of the system
Our system consists of a data visualization system, adatabase. The data visualization system is built on Android OS.
The Android OS is a popular mobile device OS. Consumers
can use this visualization system on their Android mobile
devices to see the CFP. The CFP database and the data
management system are located in a network server. The CFP
database is the data source for the CFP data visualization
system.
3. CFP data visualization system
The visualization system combines convenience of use
and visibility of the CFP. Figure.1 shows a configuration
diagram of the CFP data visualization system. There are 4 partsin our system: starting part, CFP searching part, CFP data
display part and CFP data note part. For the convenience of use,
this visualization system is built on the mobile devices.
Therefore, consumers can use this system to see the CFP dataat anytime and anywhere. The visualization system helps
consumers to understand the environmental impact of products
and consumer’s life.
Starting part is a launch point of the CFP datavisualization system. When the system starts, the visualization
system is connected to a computer server in order to check
whether CFP data are updated. The computer server is a
network server where all of the CFP data are stored.
CFP searching part consists of 2 functions, barcode decode
function and CFP data search function. We find product data byreading its product barcode in the visualization system. Due toits uniqueness, the barcode is used as a key word on the
searching part. For convenient use, a Smartphone camera isused to read the barcode. Consumers can get the CFP data only
by taking a photo of the barcode. In this function, we use theZxing [2], an open source, to decode the barcode. The productdata are searched by using the SQL select code in the CFP data
search function. If the product data is found in the database,this function starts the CFP data display part, else it will returnto the starting part.
CFP data display part is used to exhibit a detail of the CFP
data for a product. For the visibility of CFP, the CFP is shown

product

Figure.1 The Configuration diagram of the CFP datavisualization system
in both a pie chart and a data list. Geographical data of the
product are shown on Google maps. The pie chart is used to
inform a ratio of four processes in the CFP data to consumers.
The four processes are raw materials, raw materials transport,
factory, and product transport.
CFP data note part is used for recording the CFP
consumption history. From this data note, the consumers can beaware of how much CFP they spent. This information helps theconsumers to control their CFP consumption. The data of the
CFP, which the consumers spend in a month and in a day, areshown on the CFP note interface. Details of the CFP
consumption data are shown on the CFP note list. The CFP
consumption histogram is used to exhibit the CFP consumption
by month.
The visualization system has a SQLite database to recode
the CFP data. SQLite is a database system that works on themobile devices. The CFP database was made by the authors.
We calculate the CFP based on the product data and the GHG
emission factor. CO-OP Sapporo and Muroran Institute ofTechnology collected the data to calculate the food CFP [3].
4. Summary
We have built the CFP data visualization system. We have
130 kinds of product data in our database. We hope theconsumers can use this visualization system to know more
about CFP and to realize their low carbon life.
References[1] Atsushi Inaba, Carbon Footprint, Kogyo Chosakai
Publishing, Tokyo, pp. 8-9, 2009.
[2] “Zxing”, Google, <http://code.google.com/p/zxing/>,
Dec. 20, 2013.
[3] Koji NAGANO, Yoichi YOSHIDA, Hisoshi KOMATSU
and Shingo MURAKMI, Journal of Life Cycle
Assessment, 9(4), ,pp.299-305,2013.

�������������������������������������������������

P-016

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

168

Forecasting Electricity Consumption of the Japanese Information and Communications
Sector toward Green of ICT
Yusuke Kishita,*1 Kohei Kuroda,1 Yasushi Umeda,2 Yohei Yamaguchi,1 Yoshiyuki Shimoda,1Minako Hara,3 Hiroki Oka,3 and Jiro Nakamura3
1

Osaka University, JapanThe University of Tokyo, Japan
3
NTT Energy and Environment Systems Laboratories, Japan*Corresponding author: kishita@ceids.osaka-u.ac.jp
2

Ei (n)  Pi ( n)  Qi (n)(1)

where Ei(n) is the electricity consumption of facility i in year n,
whereas Qi(n) and Pi(n) are the amount of a dominant factor
over the electricity consumption of facility i and the intensityof the electricity consumption of facility i per unit amount of
Qi(n), respectively. For example, we choose broadband traffic
as Qi(n) for IP communication facilities in subsystem (a) since,on an empirical basis, there is a strong correlation between
broadband traffic and the electricity consumption of IP
communication facilities.
3. Case study
We estimated the electricity consumption of the Japanese
ICT sector in 2020. We collected past data mainly from CSR
reports issued by three Japanese telecommunication companies(NTT, KDDI, and Softbank). Based on the collected data, we
obtained concrete formula of Eq. (1) for each facility. For
example, as described in Figure 1, we defined Pi(n) for IP
communication facilities as:

Pi (n)  0.0291 Qi (n)0.522(2)

4. Summary
We presented a prototype model for forecasting the electricity
consumption of ICT sectors. Future work includes sensitivity
analysis of electricity reduction by countermeasures, e.g.,
replacement of old equipment with more energy-efficient one.
References[1] Koomey, J. Estimating Total Power Consumption byServers in the U.S. and the World (Final Report), 2007.
[2] Hoshino, T., et al. Development Engineering 18: 71-82, 2012.
[3] Cisco. Visual Networking Index (VNI): Forecast andMethodology, 2013-2018, 2014.
Intensity of Electricity Consumptionof IP Communication Facilities(TWh/year/Mbps)

2. Methodology for forecasting electricity consumption of
ICT sectors
Each of four subsystems (a)-(d) encompasses several
facilities. For example, subsystem (a) is composed of fourtypes of facilities, i.e., fixed-telephone communication, IP(Internet Protocol) communication, air-conditioning, and power
feeding facilities. We model each of the facilities in the four
subsystems in the following formula:

We assumed three scenarios (i.e., Reference, Rapid, andSlow scenarios) responding to the amount of IP traffic as it is
one of the most uncertain factors in the ICT sector. In
Reference Scenario, we assumed that the IP traffic in 2020
increases by 10 times more than the 2012 level based on the
Cisco’s prediction [3]. On the other hand, we assumed Rapid
and Slow Scenarios by changing the annual increase rate of IP
traffic by +5% and -5% from Reference Scenario, respectively.
Figure 2 showed that the total electricity consumption in2020 becomes 1.4-1.6 times more than in 2012. The fixed-line
and mobile networks in 2020 will consume 1.2-1.6 times and1.5-1.6 times more electricity than in 2012, respectively.

0.00120.00102005

0.00082006

0.00062007

0.00042011

2012

y = 0.0291x-0.522
R² = 0.966

0.00020.00002010
2008 2009

0

500
1000
1500
2000
2500
Mean Annual Broadband Traffic (Gbps)

3000

Figure 1. Relationship between broadband traffic andelectricity consumption of IP communication facilities
Electricity Consumption of
the Japan's ICT Sector (TWh/year)

1. Introduction
As the electricity consumption of information andcommunication technology (ICT) equipment (e.g., personal
computers and smartphones) is increasing, the concept of green
of ICT is becoming more important for achieving a low-carbon
society. Much work has been done to estimate the electricity
consumption of ICT equipment. For example, Koomey [1]estimated the electricity consumption of servers in the world,
while Hoshino [2] forecast the number of Internet users andpersonal computers in the world until 2025. Regardless ofexisting studies as partially listed above, analysis of theelectricity consumption of a whole ICT sector is insufficient.
An ICT sector here consists of four subsystems – (a) fixed-line
network, (b) mobile network, (c) office, and (d) others.
For helping to reduce the electricity consumption of ICT
sectors, it is needed to analyze (i) the electricity consumptionof subsystems (a)-(d) in the future and (ii) the effects ofelectricity reduction by various countermeasures. To undertakethe analysis of (i) and (ii), this paper aims to propose a method
for forecasting the electricity consumption of ICT sectors. A
case study is carried out to estimate the electricity consumptionof the Japanese ICT sector from 2012-2020.

3025(d) Others(c) Office(b) Mobile network(a) Fixed-line natwork

20
15
10
5
0

2012

Reference
Rapid Scenario Slow Scenario
Scenario (2020)(2020)(2020)

Figure 2. Electricity consumption of the Japanese ICT sector�������������������������������������������������

P-019

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

169

Life Cycle Assessment of PVC Products Based on Material Flow Analysis (MFA)
in Thailand: A Focus on End-of-life Management
Pomthong Malakul,*1 Thanakorn Rodcharoen,1 and Manit Nithithanakul1
1

The Petroleum and Petrochemical College, Chulalongkorn University, Bangkok, Thailand*Corresponding author: Pomthong.m@chula.ac.th

1. Introduction
Polyvinyl-Chloride (PVC) is a plastic product which has
matchless versatility. It effectively replaces wood, paper andmetal in several applications due to its favorable balance ofproperties. PVC products are light in weight, suitable for use
under pressure, easy to install, low maintenance cost, longservice life, and recyclable. However, there are several
concerns about the environmental problems of PVC that cannot
be ignored such as a large amount of solid wastes generated
from post consumption of PVC products. Therefore, The
purposes of this research work were: 1) to study material flows
of selected PVC products based on life cycle approach,covering raw materials, production, usage, and end-of-life; 2)
to develop material flow analysis (MFA) [1] models in order tostudy the metabolism of PVC products in Thailand; and 3) toconduct LCA on PVC products based on MFA.
2. Methodology
For MFA study, the system boundary was set to cover allprocesses after the PVC products were produced anddistributed to the consumers which includes material (product)
input, product metabolism (use phase followed by disposal)
and material (product) output (post consumption) [2]. The
selected PVC products in this study were pipe, profile, cable,
floor tile, floor covering, and foot wear which represent both
hard and soft PVC products. Primary and secondary data suchas actual resin consumption, the domestic production andconsumption of PVC products in Thailand were used as input
into the MFA models. Adjustable parameters of the model are
the average service lifetime of each product, variation of theservice lifetime, and different PVC waste management schemes(recycle, landfill, and incineration). The models were used to
calculate and predict of the amount of PVC materials flow out
to the environment in different pathways per year in the past,present, and future. The results from the MFA models werethen compared with data collected at actual waste collection
sites, disposal sites, and recycle shops.
For LCA study, since life cycle inventory (LCI) data of
PVC resin already exist in the Thai National LCI Database, thescope covers processing, use and disposal of PVC products.
Scenario analysis was used to assess and compare various
waste management schemes for PVC products in Thailand.
3. Results and Discussion
Figure 1 shows the inflow and outflow of mixed PVC
products from MFA model during 1971-2051. The results
reveal significant increase of PVC wastes due to increasing
consumption of PVC products. This dynamic MFA model also
shows estimated amount of PVC waste outflow in the past,present and future. For example, in 2013 the outflow of mixed
PVC products was equal to 128,934 tons. From MFA-based
LCA study of pipe and fitting (Figure 2), scenario with 100%
recycle of PVC (S1) is the best one which gives the lowest
GWP and energy consumption whereas scenarios withincineration and landfill treatment are relatively unfavorable
end-of-life management for PVC products.

Figure 1. Profiles of PVC inflow and outflow of mixed PVC
target products.
¥

Figure 2. GWP of PVC pipes and fittings for various
end-of-life scenarios
4. Conclusion
The results of MFA study indicated that significant amountof wastes from PVC products has been released every year,
especially at increasing rate. The amount can reach several
hundred thousand tons per year in the near future if no proper
end-of-life management is not employed or enforced. Based on
our MFA model which is the first one in Thailand for PVC
products, the accumulative amount of PVC wastes can be as
high as 7 million tons in 2051. This can cause serious waste
and environmental problems to people and ecosystems in
Thailand. The results from LCA study based on MFA of pipeand fitting clearly show that end-of-life management is an
important factor affecting the whole life cycle environmental
performance of PVC products and recycling has shown to be
the best in both energy and environmental aspects.
Acknowledgments
We would like to thank ASEAN Vinyl Council (AVC) for
the financial support and all providers of data used in thisstudy.
References[1] Brunner, P.H., and Rechberger, H. Practical Handbook ofMaterial Flow Analysis. Florida: Lewis Publishers, 2000
[2] Zhou, Y., Yang, N., and Hu, S. Industrial metabolism of
PVC in China: A dynamic material flow analysis.
Resources, Conservation and Recycling 73: 33-40, 2013�������������������������������������������������

P-020

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

170

Sustainability of 3D Printing vs. Machining: Do Machine Type & Size Matter?
Jeremy Faludi*1, Rishi Ganeriwala1, Brett Kelly1, Toril F. Rygg1, Chi Yang1
1
University of California Berkeley, USA*Corresponding author: faludi@berkeley.edu

1. Introduction and Background3D printing is booming, now competing with CNC
machining and other methods, particularly for prototyping [1].
However, its environmental impacts are still poorly understood.
Here, impacts of four 3D printers were compared to two CNC
mills to find if larger or smaller, or certain types of machine(FDM vs. SLA vs. polyjet) are more sustainable for general
prototyping, or if such statements can even be made.
Some environmental impacts of machining have been wellstudied [2, 3]. Likewise, some environmental impacts of 3D
printers have been well studied [4, 5]. However, most ofthese studies are single-issue (e.g. just energy use), and few ofthem compare different 3D printers, much less compare themto machining. Also, some 3D printing enthusiasm has led tomisleading comparisons (e.g. solar-powered printers vs.
grid-electric injection molding [6]).
3. Methods and Results
This study continues recent work [7] providing the firstlife-cycle assessment (LCA) of multiple 3D printers using
comprehensive multi-variable impacts, and the first suchcomparison of additive manufacturing vs. machining. In thisstudy, new machines were measured and the functional unit
was adjusted from the making of two solid parts to making one
thin-walled part, for more realistic comparison of the
prototyping most often performed by 3D printers, according toindustry sources. See Figure 1.
Machines measured were a Mori Seiki NVD1500 DCG("small" CNC mill), a Haas VF0 ("large" CNC mill), an Afinia
H480 ("small" desktop FDM printer), a Dimension 1200BST("large" commercial FDM), an Objet Connex 350 ("large"
commercial polyjet), and a Projet 6000 ("large" commercial
SLA). Scoring used ReCiPe Endpoint H. Printer usage
varies widely, so scenarios included theoretically making parts
24 hrs/day, 7 days/wk, as well as making just one part per week,
either leaving machines idling or turning them off when not inuse (except the Objet, for which shutoff is prohibitive).
Figure 2 shows maximum utilization results. Only one
part was printed per machine, but SLA and polyjet machines
can print several parts in nearly the same time as one part, so
this was modeled, denoted by (*). The Mori Seiki had
anomalously long operation time, which may have been due tooperator inexperience. Thus, an alternative was calculated forit with more optimal operation time, denoted by (**).

Figure 3. Impacts of idling vs. maximum utilization.
6. Discussion and Conclusion
Environmental impacts per part made depended much
more on machine utilization than machine type or size (Figure
3 shows an 18x to 80x difference vs. Figure 2's 20% to 14x, or
up to 27x if the anomalous datapoint is included.) Printing
multiple parts at once in the polyjet and SLA also made larger
differences than machine type (see Figure 2).
Thus, although some machine types do have lower
impacts than others (e.g. the desktop FDM), sharing ofmachines to maximize utilization is the top-priority
sustainability strategy for all machines, more important thanmachine type or size.
Acknowledgments
Thanks to Marco Teran and Patrick Dunne at 3D Systems,
and Gordon Long of UC Berkeley, for machine access.
References[1] 3D Hubs. Trend Report June.
http://www.3dhub s.com/trends/2014-june (Accessed 13
Jun 2014).
[2] Dahmus, J. and Gutowski, T. An Environmental Analysis
of Machining. Proceedings of IMECE04 ASME, 1–10,
2004.
[3] Muñoz, A. and Sheng, P. An analytical approach for
determining the environmental impact of machining
processes. Journal of Materials Processing Technology,
53:736–758, 1995.
[4] Luo, Y., et al. Environmental performance analysis ofsolid freedom fabrication processes. Proceedings of the1999 IEEE International Symposium on Electronics andthe Environment, pp. 1-6. IEEE, 1999.
[5] Choi, A., et al. Manufacturing processes modeling forenvironmental impact assessment. Journal of Materials
Processing Technology, 70(1), 231-238, 1997.
[6] Kreiger, M., and Pearce, J. Environmental Life Cycle
Analysis of Distributed Three-Dimensional Printing andConventional Manufacturing of Polymer Products. ACS
Sustainable Chemistry & Engineering 1.12: 1511-1519,
2013.
[7] Faludi, J., Bayley, C., Bhogal, S., & Iribarne, M.
Comparing Environmental Impacts of Additive
Manufacturing vs. Traditional Machining via Life-Cycle
Assessment. Journal of Rapid Prototyping. Acceptedfor publication in 2015.

Figure 2. Impacts per part, operating at maximum utilization.

�������������������������������������������������

P-021

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

171

Life Cycle-based Exergy Analysis and Its Application to Japanese Case
Ryota Ii,*1 Eiji Yamasue,2 Shinsuke Murakami,3 Jun Nakatani,3 Takeshi Matsuda,1 Ken Horiguchi,1Yuusuke Kousaka,1 Rintarou Terada,1 Kei Gomi2 and Makoto Inari4
1 Pacific Consultants Co., Ltd., Japan; 2 Kyoto University, Japan; 3The University of Tokyo, Japan; 4 Inari Consulting Office*Corresponding author: lcateam@ss.pacific.co.jp

1. Introduction
Studies on life cycle assessment (LCA) using exergy
which is an indicator concerning ‘available energy’ correspondto the second law of thermodynamics [1]. This presentation
summarized current studies based on some review papers
outside Japan [2][3][4], and discussed availability andproblems of exergy as an indicator.
2. Outlook of recent exergy LCA studies
Examples of LCA studies using exergy as an indicator are
the followings;
Cumulative Exergy Consumption (CExC) [5] is a method
to cumulate exergy contained in all resources throughout
a supply chain of reference products. Cumulative Exergy
Demand (CExD) [6] is a result of a test calculation using
Ecoinvent database.
Exergy Life Cycle Assessment (ELCA) [7] implements
exergy analysis within the framework of LCA. However
essential differences with CExC do not seem to be clear.

Life Cycle Exergy Analysis (LCEA) [8] is considered tocumulate input and output exergy and divide them into
renewable / unrenewable.

Ayres et al. (1998) took advantages of using exergy as anindicator of both inputs and outputs. What this method
enables is: to calculate easily, to assess different kinds ofenvironmental impacts with a single index, and tocompare environmental performances with large scales
such as industries and countries.

Finnveden & Östlund (1997) [9] proposed to use exergy
inventory data as an indicator of characterization factor
of natural resources.
3. Availability of exergy indicator in the research field ofenvironment and energy
The exergy indicator used for environment and energy
realm can be categorized into the following three categories.
(1) Exergy efficiency
Exergy efficiency has more advantages than thermal efficiency,
as it includes irreversible loss which can not be estimated byenthalpy.
(2) Exergy inputs
Exergy inputs can be gained to converse the amount of energy
including input resources, hence it can be calculated easily inthe exiting LCA infrastructure.
(3) Exergy outputs
The amount of exergy outputs is an indicator representing
potential environmental impacts focusing on emissions whosebalances with the environment have not been achieved yet.
However environmental impacts caused by the same amount ofexergy vary according to types of interventions such as thermaland concentration.
4. Discussion
After the Great East Japan Earthquake in 2011, enhancing
independence of production systems and regional activities, inaddition to improving energy efficiency, is required in Japan. In
order to assess and design low-carbon society system and its
infrastructure, it is valuable to apply exergy, which represents
various quality of energy, for LCA as an assessment method tofocus on the entire reference system. Moreover developing theway for its application and verifying the effectiveness isrequired. In LCA realm, input-output analysis is often applied.
When exergy is included to the LCA practice, it is applicable tothe same way. Some of the authors referred to in this study
have begun to create a table including the amount of input andoutput exergy for each industrial sector in 2005 Input-Output
Table of Japan as its annex table, and discussed how to create
and use the annex table.
Acknowledgments
This presentation is based on our current papers, such as
Yamasue et al. [10] and Ii et al. [11]. The authors are also
grateful to Ms. Akiko Ohsawa for supporting this work.
References[1] Sciubba, E., and Wall, G., “A Brief Commented History
of Exergy from the Beginnings to 2004”, Int. J. of
Thermodynamics, 10(1), 1-26, (2007)[2] Dewulf, J., Van Langenhove, H., Muys, B., Bruers, S.,
Bakshi, BR., Grubb, GF., Paulus, DM., Sciubba, E..:
“Exergy: its potential and limitations in environmental
science and technology”, Environ Sci Technol., 42(7),2221-32, (2008)[3] R. U. Ayres, L. W. Ayres, K. Martinas, “Exergy, Waste
accounting, and Life‐Cycle Analysis”, Energy, 23(5),355‐363, (1998)[4] Davidsson, S., “Life Cycle Exergy Analysis of Wind
Energy Systems”, Uppsala Universitet, (2011)[5] J. Szargut, D. R. Morris, “Cumulative Exergy
Consumption and Cumulative Degree of Perfection ofChemical Processes”, Energy Research, 11, 245-261,(1987)[6] M. E. Bösch, S. Hellweg, M. A.J. Huijbregts, R.
Frischknecht, “Applying Cumulative Exergy Demand(CExD) Indicators to the ecoinvent Database”, Int J LCA
12 (3) 181-190 (2007)[7] R. L. Cornelissen, “Thermodynamics and sustainable
development - The use of exergy analysis and the
reduction of irreversibility”, Ph.D. Dissertation,
University of Twente, (1997)[8] M. Gong and G. Wall, “On Exergetics, Economics andOptimization of Technical Processes to Meet
Environmental Conditions”, TAIES'97, June 10-13,
Beijing, China, (1997)[9] Göran Finnveden, Per Östlund , “Exergies of natural
resources in life-cycle assessment and other applications”,
Energy, 22(9), 923-931, (1997)[10] Yamasue, E., Murakami, S., Nakatani, J., Ii, R., Matsuda,T., Horiguchi, K., Kosaka, Y., Terada, R., Gomi, K. andInari, M., “Recent LCA studies by exergy andapplicability for low-carbon society system design”, The
9th meeting of the institute of Life Cycle Assessment,
Japan, (2014)[11] Ryota Ii and Ken Horiguchi, “Study on compilation of theannex table of input-output table for life cycle exergy loss
analysis”, the 33rd annual meeting of Japan Society ofEnergy and Resources. (2014)�������������������������������������������������

P-022

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

172

Compilation of Embodied CO2 Emission Inventory Using China’s Input-Output Tables:
Implication for Environmental Public Utilities
Qian Zhang,* Jun Nakatani, and Yuichi Moriguchi
The University of Tokyo, Japan*Corresponding author: zhang_qian@env.t.u-tokyo.ac.jp
1. Introduction
Accompanying rapid economic growth, the urbanization
rate in China has dramatically increased to around 50% during
the past 30 years. Energy-related CO2 emission in China has
also enlarged to 8 Gt, accounting for one quarter of the world’s
total CO2 emission [1]. China needs more materials and energy
to build or renovate numerous cities to supply clean living
environment for people. Our motivation is to understand how
much CO2 emission and other environmental burdens cost in
exchange for maintaining and expanding this kind ofenvironmental public utilities in China’s urbanization process.
In this study, we adopted environmental input-output analysis
to compile China’s embodied CO2 emission intensity andinventory as a basis for computation of CO2 emissions related
to environmental public utilities in cities. Impacts from watersupply and wastewater treatment services were picked up in
discussion as one of meaningful implications.
2. Data sources and methodology
Detailed fuel consumption in 2007 was cited from the
China Energy Statistical Yearbook (CESY 2008), and the China
Statistical Yearbook (CSY 2008) as a complement [2, 3]. Not
only final use of energy in all sectors but also energy input inpower and heat generation and energy loss in othertransformation processes were taken into account. Most recent
and specific 135-sector input-output (IO) tables of China in2007 [4] were assembled with above energy consumption data
to produce an “energy IO table”. Based on carbon contents infuels in IPCC’s guideline [5] and heat values indicated as
standard coal coefficients in CESY [2], the energy IO table
could be transformed as a dataset of embodied CO2 emissionsof China (2007). Non-energy CO2 emissions from industrial
processes were collected from literature [6].
We mainly followed the instruction of 3EID database forJapan [7] to compile China’s embodied CO2 inventory incompetitive model. Embodied CO2 intensity e exclusively indomestic products and embodied CO2 emission ECO2 inducedby final demands could be calculated as follows [8].
(1)e=d (I-(I-M) A)-1
ECO2=e f=d B [(I-M) (fc+fk) +fx)](2)
where d represents direct CO2 emission factors in sectors, I
means unit matrix, M is a diagonal matrix of import ratio, A
represents input coefficient matrix, f represents domestic final
demand, and B=(I-(I-M) A)-1 for simplification of the formula.
We disaggregated final demand f into domestic
consumption (urban, rural and governmental) fc, gross capitalformation (fixed investment and storages) fk, and export fx toevaluate relative importance in embodied CO2 inventory.
3. Results and discussion
Based on our evaluation, China emitted 2.1 Gt of CO2(30%) induced by domestic consumption, 3.0 Gt (42%) by
capital formation and 2.0 Gt (28%) by exports. Figure 1 shows
the composition of this embodied CO2 inventory via
consumption perspective in category of final use (inner) andproduction perspective in economic sectors (middle and outer).
As a case, we found that 24 Mt CO2 embodied in services

of water supply and wastewater treatment, whereas 22 Mt CO2
embodied in construction of related infrastructure in 2007. The
decomposition results of these embodied emissions are shownin Figure 2. Maintaining the services of water supply andwastewater treatment requires dozens of times of carbon
footprint than its direct CO2 emission.
It demonstrates that China’s own embodied CO2 dataset
could give more detailed and precise insights on
consumption-based GHG responsibility, which is helpful todecision-making about effective potential of carbon abatement
while keeping a healthy economy.
Inner

Middle7.1 GtCO2

Outer

Figure 1. Embodied CO2 of China, 2007

Figure 2. Embodied CO2 in operation (left) andconstruction (right) activities of water supply and wastewater
treatment in China, 2007
References[1] IEA. CO2 Emissions From Fuel Combustion Highlights 2013.
http://www.iea.org/publications/freepublications/publication/nam
e,43840,en.html (Accessed 14.01.2014).
[2] NBS of China. China Energy Statistical Yearbook 2008, China
Statistics Press, 2008.
[3] NBS of China. China Statistical Yearbook 2008. http://www.stats.
gov.cn/tjsj/ndsj/2008/indexch.htm (Accessed 14.01.2014).
[4] NBS of China. Input-Output Tables of China 2007, China
Statistics Press, 2009.
[5] IPCC. 2006 IPCC Guidelines for National Greenhouse Gas
Inventories.
http://www.ipcc-nggip.iges.or.jp/public/2006gl/(Accessed 14.01.2014).
[6] Wang Y. et al. J. Clean. Prod. 53: 252-260, 2013.
[7] NIES of Japan. Explanation of methodology in 3EID. http://www.
cger.nies.go.jp/publications/report/d031/jpn/page/document_file.
htm (Accessed 14.01.2014).
[8] MIC of Japan. Methodology for input-output analysis. http://
www.stat.go.jp/data/io/bunseki.htm (Accessed 08.01.2014).

�������������������������������������������������

P-023

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

173

Integration of material performance index for a comprehensive change-oriented LCA:
the biopolymer caseBruno De Benedetti,* Pierluigi Freni, Paolo Tecchio and Sara Rollino
Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy*Corresponding author: bruno.debenedetti@polito.it
1. Introduction
The fast pace of technological progress and the increasingpressure on natural ecosystems put forward the urgent need forthe assessment of the impact of human activities, especially inthe early stage of development. In particular, the possibility toestimate the potential impact that a new material could have on
environment and human health, ahead of its adoption, is offundamental importance during the design phase of a product [1].
The selection process of a new material, to be used in placeof another, is mainly based on the intrinsic properties of thematerial itself (e.g. mechanical characteristics). Therefore, aproper comparison in a change-oriented perspective should take
into account both the properties of the material and its
environmental performance. In particular, to support thedecision making process Life Cycle Assessment (LCA) should
be complemented with other tools [2].
Currently, LCA is internationally considered the standard inenvironmental impact assessment and represents an extensive
and comprehensive methodology. In order to perform suchanalysis, a complete and deep understanding of the overall life
cycle of a product system is required. This condition can besatisfied only once the material itself has been alreadyintroduced onto the market.
Given the previous considerations, full-fledged LCA shows
two major limitations: it can be performed only ex-post (i.e. after
the development at industrial scale of the new material) and it
accounts mainly for the environmental performance of thematerial, regardless of its intrinsic properties. To overcome such
limitations and to forecast the potential impact of a productbeforehand, a radical change of perspective must be prompted:
a shift from an ex-post approach to an ex-ante analysis is needed.
In the present work, it is proposed a comprehensive design tool,
which is aimed at assessing the environmental sustainability andeconomic feasibility of the introduction of a new material onto
the market. The developed method synergically combines theresults deriving from ex-ante LCA with multi-criteria analysis
for material selection, allowing a comprehensive and consistentcomparison between the emerging material (e.g. new polymers
produced from renewable sources) and the “traditional”
materials that are intended to be replaced.
Interest in bio-based plastics as substitution materials for
petroleum-based plastics has risen in past years and the global
industrial production is expected to have 400% growth by 2017[3]. This rise is due to a market demand for products with lower
environmental burden compared to traditional plastics. Thus, theneed to quantify biopolymers environmental impact is becoming
meaningful in order to provide a concrete and objective answer
to the market. Biopolymers production technologies are, inmany cases, still at lab/pilot plant scale. Therefore, no reliableprimary data are available in order to perform a proper
environmental impact assessment, by means of LCA. For thisreason, an ex-ante LCA approach is here proposed to assess theenvironmental performance of innovative bio-based products,
starting from both primary data on lab/pilot scale andchemical/thermodynamic considerations.
The final goal of the authors’ work is to integrate ex-ante
LCA with multi criteria material selection, moving from anevaluation based on the unit of mass of the material to anassessment that takes into account at the same time both the
intrinsic properties of the material and its environmental burden.
This synergic integration represents a relevant novel element of
the methodology proposed hereinafter.
2. Ex-ante LCA
The operational framework of ex-ante LCA is definedaccordingly to ISO 14040 standards for full-fledged LCA. The
ex-ante LCA strategy proposed in the present work is groundedon the Generic Approach, developed by Patel et al. and mainly
focused on the analysis of bio-based products (fuels, chemicals
and polymers) in the context of the White Biotechnology [4, 5].
In fact, most of the goods produced from biomass are subjected
to similar processes. The Generic Approach is defined as amethod that allows to estimate, ex ante, the environmental
impacts and the basic economics of new biotechnologicalprocesses for which data from pilot plant or on laboratory scale
are not yet available, or for which industrial scale data are notpublicly accessible due to confidential agreements [4]. The
authors of the current work implemented such methodology
including primary data from pilot plant scale production andsecondary data obtained from inventories in LCA databases andby means of a stoichiometric model of the chemical processes
involved. The aim is to perform a multiscale analysis in order togather enough results to enable a consistent scale-up of theenvironmental burden on industrial scale.
The main objective of such analysis is to evaluate theenvironmental burden associated with the production of goods
and, in particular, to allow a comparison with traditional
products of the chemical industry. In this context, the scope ofinvestigation is limited from cradle to factory gate: i.e. thesystem boundaries are chosen so that the final output is thestudied chemical. As far as biopolymers are concerned, thescope of the change-oriented assessment is extended to the usephase by means of material indices (detailed hereinafter § 3) thatcombines mechanical properties with environmental burdens fora straightforward comparison with oil-based polymers currently
used. In the case of compostable or biodegradable polymers
appropriate considerations are required and, possibly, thehorizon of the analysis has to be extended from cradle to grave,in order to take into account also further benefits.
In a full-fledged LCA, consistently with the chosen level ofdetail and the quality and quantity of available data, manifold
impact categories are considered. Each category summarizes theenvironmental effects associated with specific emissions. Due tothe scarcity of data on which an ex-ante LCA is based, the impact
categories used in the present work are limited to: Cumulative Energy Demand (CED). It measures theamount of energy involved in a system, considering theupper heating value, both from renewable and nonrenewable source.
 Greenhouse Gas emissions (GHG). It takes into account,
first and foremost, the emissions of carbon dioxide, andother greenhouse gases, such as CH4, N2O, etc.
The choice of such a small set of indicators, however, does
not affect the validity and comprehensiveness of the analysis. In�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

174

fact, by linear regression, it is possible to associate the totalenergy consumption (CED) to most impact categories, such asacidification, eutrophication, human toxicity, etc. This
correlation has been verified for a large number of products, inparticular commodities, and it is justified by the fact that energy
consumption (in particular from fossil sources) is the main
source of all impacts associated with their production [6]. CED
does not take into account the impacts resulting from land use
and, for this reason, it cannot be regarded as a comprehensive
indicator in the case of agricultural products and/or derivatives[7]. Therefore, in future works, the authors will complement theassessment of energy-related impact categories with land use
and land use change indicators.
2.1. Scale-up protocol
The scale-up protocol is here presented in general terms and,afterwards, it is applied to the bio-based polymer chosen as casestudy: polybutylene succinate (PBS). This methodology is basedon the identification of a proper mathematical relation between
the environmental burden on stoichiometric scale, pilot scale
and industrial scale. Such a relation is called scale-up function(𝑓𝑓). The protocol is made up of five fundamental steps:(1) Choice of reference polymer. Since data on industrial
scale are missing for innovative bio-based products, thedefinition of the scale-up function requires the choice of areference polymer. This is selected according to the following
considerations: (a) the process of synthesis of the reference has
to be analogous to the one of the biopolymer under analysis; (b)for the reference, data on industrial scale have to be available.
(2) Pilot scale production and assessment. One or morebatches of the bio-based polymer have to be produced in amonitored pilot plant: all the inputs and outputs of the process
and the pilot scale environmental impacts of the biopolymer are
determined with the ex-ante LCA approach. Afterwards a batchof the reference polymer has to be produced in the same pilot
plant, monitoring again all the inputs and outputs of the process,and the pilot scale environmental impacts of the reference aredetermined with the ex-ante LCA approach. This way two setsof data on the environmental burden of both the biopolymer andthe reference are straightforwardly obtained, on the same
production lab/pilot scale.
(3) Industrial scale assessment of the reference polymer. The
environmental impact related to the production of the reference
polymer on industrial scale is assessed, by means of full-fledged
LCA, using available secondary data or product ecoprofiles.
(4) Stoichiometric baseline. Both for the bio-based polymer
and for the reference it is possible to define stoichiometricmodels for the chemical conversions (e.g. polymerization),based on theoretical information. These models are
representative of ideal systems, perfectly efficient, and therefore
their environmental impact (assessed by means of ex-ante LCA)
is the lowest possible for the production routes considered and it
is used as baseline.
(5) Scale-up function definition. The result of previous steps
is a set of environmental impact values on pilot, industrial andstoichiometric scale for the reference polymer, while theenvironmental burden on industrial scale is still missing for the
new biopolymer. Therefore, considering the complete set of data
about the reference polymer, a relation among different scales
impacts (Environmental Impact, 𝐸𝐸𝐸𝐸) is defined as function of
the mass conversion yield (𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 ) of the chemical conversion
process.
𝐸𝐸𝐸𝐸𝑟𝑟𝑟𝑟𝑟𝑟 = 𝑓𝑓(𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚,𝑟𝑟𝑟𝑟𝑟𝑟 )(1)

The mass conversion yield is, in fact, a valid indicator forthe scale of a chemical process: the pilot scale is characterizedby high inefficiency and then it has a low 𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 , conversely theindustrial production is optimized (hypothesis of Best Available
Technology, BAT) and it has a much higher 𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 . Finally, thestoichiometric model is representative of the ideal process and𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠
represents the upper limit for the conversion. Since the𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
stoichiometric mass conversion yield is characteristic of thespecific process considered and it does not depend on factors
other than chemical and physical ones, the 𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 at each scale
𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠
is normalized with respect to 𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
in order to enable thefollowing application of the function to slightly different
processes. Therefore, equation (1) is rewritten as:
𝐸𝐸𝐸𝐸𝑟𝑟𝑟𝑟𝑟𝑟 = 𝑓𝑓(𝑦𝑦̅𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚,𝑟𝑟𝑟𝑟𝑟𝑟 )(2)where 𝑦𝑦𝑦𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 is the normalized mass conversion yield.
Equation (2) is the scale-up function in the generalized form.
The set of data for the environmental impact of the reference
is made up of discrete points, thus a regression or interpolationis required to obtain a proper mathematical function.
2.2. Case study: polybutylene succinate
The methodology previously described has been applied topolybutylene succinate (PBS), a biopolymer that is gaining
interest, particularly in the packaging sector. PBS is an aliphatic
polyester with mechanical properties and processability
performances similar to those of widely used polymers. It is
proposed as an alternative in the production of polymeric films
for use in agriculture (mulching film), shopping bags, bags forcomposting, etc. [8].
PBS is obtained from succinic acid and 1,4-butanediol
monomers by means of a polycondensation reaction that forms
the polyester and water as byproduct. Currently, the monomers
used are fossil, but alternatives from renewable sources havebeen studied to replace one or both of the reactants. In particular,
succinic acid can be produced from starch, glucose or cellulose,
through bacterial fermentation. Furthermore, bio-based succinicacid can become the source for a “green” C4 chemical
derivatives platform, including 1,4-butanediol [4].
The Japanese company Showa Highpolymer successfully
produced PBS on pilot scale, using bio-based succinic acid. The
mechanical properties and processability (extrusion bubble test)of the resulting bio-based PBS are in line with the performanceof the oil-based counterpart [8]. Since the production process of
PBS from biomass is at pilot plant stage, an estimate of theenvironmental impact on industrial scale has significant interest.
The starting monomers for the production of PBS are adicarboxylic acid and a diol that undergoes an esterification
reaction. A common polymer obtained by means of the samechemical reaction is polyethylene terephthalate (PET): inparticular it is produced starting from terephthalic acid
(dicarboxylic acid) and ethylene glycol (diol). Therefore, PET isa suitable candidate to be used as reference polymer for the
scale-up of the environmental impact of PBS.
Accordingly with the scale-up protocol previously described,
some batches of PBS and PET were produced in a pilot plant [9],monitoring process parameters, i.e. input and output flows ofreactants and products, as well as energy consumptions. These
primary data were used to determine CED (EcoInvent v2.0) andGHG (IPCC 2007 GWP 100a) impact categories for both thepolymers produced on pilot scale. Afterwards, the impact on
industrial scale for the PET was assessed with secondary data
(Polyethylene terephthalate, granulate, amorphous, atplant/RER U, EcoInvent). Finally, the stoichiometric baseline
was evaluated from the chemical reactions involved in thepolymerization of both PET and PBS.
Monte Carlo analysis was used to process uncertainty data
for all of the assessments: this way, for each scale, there is not
only one value representative of the impact, but a range of data
points. Data uncertainty in the inventory tables was associated�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

175
70

50
GHG (kg CO2 eq/kg PBS)

GHG (kg CO2 eq/kg PET)

45
40
35
30
25
20
15
10
5
80%

85%

90%

95%

𝑦𝑦̅𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

Figure 1. Linear interpolation of PET data points for GHG
emissions at different production scales
using Pedigree Matrix [10].
The scale-up functions were determined starting from thedata points of the CED and GHG impacts of PET at pilot,
industrial and stoichiometric scale. The functions are linear
interpolations of data points and they are represented by the
concatenation of the linear interpolants between each pair ofpoints. In Figure 1 it is reported the resulting linear interpolation
for GHG emissions of PET. Because of the large number of data
points, the scale-up function is not limited to just one polygonal
chain, but to a bundle of lines (grey area in Figure 1). Each scaleup function was then applied singularly to the respective data
points representative of the environmental impact of PBS
production at pilot scale and of the stoichiometric model. Theintersections of such functions identify the GHG emissions of
PBS produced from bio-based succinic acid (Figure 2). Finally,
the Monte Carlo distribution of results for PBS is presented in
Figure 3. Following the same methodology, the CED for biobased PBS on industrial scale was assessed. The results are
summarized in Table 1.
Table 1. Environmental impact of PBS at different production
scales (mean values)
CED(MJ/kg PBS)

GHG
(kg CO2 eq/kg PBS)

Pilot

893,55

36,57

Industrial

138,85

6,35

Stoichiometric

123,305,50

Production scale

The outcomes of the scale-up protocol here proposed wereused for a multi-criteria comparison between bio-based PBS andtraditional polymers.
3. Multi-criteria material selection
The multi-criteria material selection aims at comparing
different materials on the basis of more than one property. Thismethod is grounded on the identification of a proper material
index, defined combining solid mechanics and materials science.
It is the result of considerations about the geometry of thecomponent and the stress conditions. This index combines a setof properties (e.g. density, Young modulus, tensile strength,
environmental impact, etc.) and it is used to compare alternative
material options, targeting the maximization of the required
performance. To carry out such a comparison, material indices

50

40
30
20
10
0
70%

100%

75%

80%

85%

90%

95%

100%

𝑦𝑦̅𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

Figure 2.GHG emissions of PBS at different production scales60
GHG (kg CO2 eq/kg PBS)

0
75%

60

50
40
30
20
10
0

Pilot

Industrial

Stoic

Figure 3. GHG emissions of PBS (Monte Carlo distribution
from 5th to 95th percentile)
are implemented with the bubble diagrams. These are graphicalrepresentations in which a property, or a combination ofproperties, is plotted as a function of another: the materials are
represented by bubbles localized within the area of the map [11].
Multi-criteria material selection can be integrated with LCA
to extend the system boundaries and empower a comprehensive
comparison among alternative materials (polymers in thisparticular case). The turning point of the methodology here
proposed is the shift from the “kilogram based” analysis to afunction oriented assessment, which is specifically necessary inthe design step. This change in paradigm passes through the
adoption of appropriate material indices which include LCA
results. Once identified, these indices are used in combination
with bubble diagrams for a final screening of available
alternatives.
As far as PBS is concerned, in the present work it was
performed a comparison between this bio-based polymer and the
traditional polymers that are currently used in packaging sector.
The definition of material indices was modelled considering afilm of material undergoing a uniaxial planar tensile stress. The
mechanical properties included in the model are Young modulus( 𝑌𝑌 ) and tensile strength ( 𝜎𝜎𝑓𝑓 ), while the environmental
performance is represented by CED and GHG impact categories.
Each index corresponds to a bubble diagram whose axes arerespectively the numerator and the denominator of the index
𝜎𝜎𝑓𝑓, the resultant bubble
itself. Taking, for example, the index
𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺

diagram is presented in Figure 4. The sloping lines on the graphare called iso-performance lines since the points on such lines�������������������������������������������������

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

176

100

PBS (SA Lignocellulosics)
PBS (SA Maize Starch)

Tensile strenth (MPa)PBS (SA Sugar Cane)50

20

PP (homopolymer, low flow)

PP (homopolymer, high flow)
PE-HD
PE-LD

10

1000

2000

GHG · density

5000

10000

Figure 4. Bubble diagram Tensile strength vs GHG·density
are characterized by the same value of the material index. It
follows that the bubbles lying on the same line are representativeof materials with an equivalent eco-mechanical performance(with reference to tensile strength and GHG emissions for theparticular case of Figure 4). At the same time, moving upwards
perpendicularly to iso-performance lines, the eco-mechanicalperformance increases. The dispersion of values for GHG
emissions of PBS produced at industrial scale (showed in Figure3) defines the dimension of the PBS bubble (horizontal axis of
PBS ellipses in Figure 4). Therefore, as it can be seen in Figure
4, bio-based PBS is comparable with Polyethylene (PE) and only
slightly inferior to Polypropylene (PP).
Performing such analysis for the other indices previously
identified, bio-based PBS proved to be a valuable candidate in
the replacement of PE and PP for film packaging applications.
Conclusions
The proposed methodology, combining ex-ante LCA andmulticriteria material selection, proved to be suitable to assess
the environmental burden of newly developed bio-based
polymers. The scale-up protocol developed by the authors is
aimed to overcome the “scale issue” arising in the comparison
between innovative processes, at early stage of development,
and industrially optimized ones. Furthermore, the use of materialindices as functional unit for LCA of materials shows a great
potential that goes beyond the scope of the present work and thathas to be explored for other materials.
As far as PBS and biopolymers in general are concerned, themethodology herein presented points out that it is notrecommended an approach which indicates the biobased
polymer to be the best choice by default. In fact, in the case study
previously described PP performs better even if it is fossil based.
Finally, the method can be used to outline the targeting
context in which the new material should be introduced. In
practice, it is possible to define the constraints that the newmaterial needs to respect, in order to be competitive with current
solutions, in terms of material properties (mechanical, thermal,etc.) and environmental impact (CO2 emissions, etc.).
References[1] J. Thackara, In the Bubble, Design in a complex world,
MIT Press, 2005.
[2] M. A. Curran, «Life Cycle Assessment: a review of themethodology and its application to sustainability,»
Current Opinion in Chemical Engineering, n. 2, pp. 273277, 2013.
[3] European Bioplastics | Institute for Bioplastics andBiocomposites, «Bioplastics facts and figures,» 2013.
[4] M. Patel, M. Crank, V. Domburg, B. Hermann, L. Roes,
B. Husing, L. Overbeek, F. Terragni e E. Recchia,«Medium and Long-term Opportunities and Risks of the
Biotechnological Production of Bulk Chemicals from
Renewable Resources (BREW),» Utrecht, 2006.
[5] A. Roes e M. Patel, «Ex-ante environmental assessmentsof novel technologies - Improved caprolactam catalysis
and hydrogen storage,» Journal of Cleaner Production, n.
19, pp. 1159-1667, 2011.
[6] M. Huijbregts, L. Rombouts, S. Hellweg, R. Frischknecht,
J. Hendriks, D. Van de Meent, A. Ragas, L. Reijnders e J.
Struijs, «Is Cumulative Fossil Energy Demand a Useful
Indicator for the Environmental Performance ofProducts?,» Environmental Science & Technology, vol. 4,
n. 3, 2006.
[7] M. Huijbregts, S. Hellweg, R. Frischknecht, H. Hendriks,
K. Hungerbuhler e J. Hendriks, «Cumulative Energy
Demand As Predictor for the Environmental Burden of
Commodity Production,» Environmental Science &Technology, vol. 44, n. 6, 2010.
[8] Y.
IchikawaeT.
Mizukoshi,«Bionolle(Polybutylenesuccinate),» Advances in Polymer Science,
vol. 245, pp. 285-314, 2012.
[9] N. Jacquel, F. Freyermouth, F. Fenouillot, A. Rousseau, J.
P. Pascault, P. Fuertes e R. Saint-Loup, «Synthesis andProperties of Poly(butylene succinate): Efficiency ofDifferent Transesterification Catalysts,» Journal of
Polymer Science Part A: Polymer Chemistry, n. 49, pp.
5301-5312, 2011.
[10] B. P. Weidema and M. S. Wesnaes, "Data quality
management for life cycle inventories - an example ofusing data quality indicators," Journal of Cleaner
Production, vol. 4, no. 3-4, pp. 167-174, 1996.
[11] M. Ashby, «Multi-objective optimization in material
design and selection,» Acta Materialia, pp. 359-369,
2000.

�������������������������������������������������

P-024

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

177

Environmental profile of Stone-Paper
Atsushi INABA1*, Nobuharu SHINOZAKI1, Takumi KAWASHIMA1, Masaharu MOTOSHITA2,3
1
Kogakuin University, Japan;
National Institute of Advanced Industrial Science and Technology,Japan; 3Technische Universitaet Berlin, Germany*Corresponding author: a-inaba@cc.kogakuin.ac.jp

2

1. Introduction (Goal and Scope Definition)
The environmental profiles of stone paper and conventional
pulp paper were analyzed in this study. The functional unit was
1m2 in size and 200μm thickness of each paper, which weights
were 240g/m² and 155g/m² for stone paper and for pulp paper,
respectively.
2. Inventory Analysis
2.1 System Boundary
The overseas crude oil is imported, and then polyethylene isproduced in Japan, which is a raw material of stone paper.
Lime stone, which is another raw material of stone paper, ismined in Japan.
The conventional pulp paper is made of woodchip imported
in Japan. The overseas forestations and cultivations of wood
are included, and the recycled waste paper is not used for the
production of pulp paper in this study.
After the production, both papers are printed and used. The
printing is included but the use stage is excluded because there
are many options to use both papers.
On the end of life stage, pulp paper is incinerated in thefacility with the electric power generation. For stone paper, two
scenarios, the incineration with the power generation and thelandfill, are assumed. The efficiency of the power generation in
the incineration facility is assumed to be 15% for both papers.
2.2 Calculation
The data of materials and utility to manufacture stone paper
is provided by TBM, the company importing stone paper toJapan. High density polyethylene of 0.048kg and lime stone of
0.192kg are used for 1 m2 of stone paper.
The manufacturing data of pulp paper is cited from thedatabase of the society of LCA, Japan[1]. Which is provided by
Japan Paper Association. 0.246 kg of woodchip is used for 1m2
of pulp paper.
The materials and energy to photogravure on pulp paper andon stone paper is not different, which is cited by Uchida[2]. For
the other background data, Milca[3] by JEMAI is used.
3. Impact Assessment
LIME2[4] is applied for the impact assessment in this study.
The environmental impact of the certified forest is notconsidered, but the damage to biodiversity and net primary
production were assessed for uncertified forest. In addition,
pulp paper is considered to be carbon neutral in this study.
The environmental impacts such as acidification and urban
air pollution caused by SOx in the sea lane are not taken into
account in this study, although it is not negligible compared tothat in the other life cycle stages of pulp paper.
In this study, the environmental impacts for both papers wereassessed firstly, and then the environmental impacts of the caseif the forest was not certified as responsibly managed wereanalyzed. It might be useful to clarify the contribution of thecertified forest.
3.1 Impact Assessment of the paper with certified forest.
Fig.1 shows the contributions of the emissions and resource
consumption in the weighted result of the environmental
impacts in the whole life cycle stages.
As pulp paper is carbon neutral, the CO2 emission due to theincineration of pulp paper is not counted. For the case of stone
paper (incineration), ashes after the incineration have to belandfilled and they give the significant effects on the damage ofthe social asset. The CO2 emission of stone paper (landfilled) is
a little smaller than stone paper (incineration), but the damageof the social asset due to the landfill of stone paper itself islarger than ashes of stone paper (incineration). As the result,
the weighted result of stone paper (landfilled) is about 10 %larger than stone paper (incineration).
If the ashes obtained after incineration could be used as therecycled materials, the environmental impacts caused by theashes could be avoided in the case of stone paper (incineration).
The recycling of the ashes must be a target to be developed.
4.00E+00

3.74E+00

3.95E+00
waste power

3.50E+00

slag

3.00E+00

rime stone

2.50E+00
2.00E+00

N2O
natural gas

1.79E+00

CH4

1.50E+00

Coal

1.00E+00

NOx

5.00E‐01

crude oil

0.00E+00

PM2.5‐1.57E‐01‐1.70E‐01

pulp paperstonepaper(incine.)SOx‐5.00E‐01

stonepaper(landfill)

ash
CO2

Fig.1 Weighted Impact using certified forest
3.2 Impct Assessment including the end of life
Fig.2 shows the weighted environmental impact for the casethat 51.8% of the total forest is uncertified [5]. As the impacts
for stone papers are the same as those shown in Fig.1, it is clearthat the environmental impacts to biodiversity and net primary
production of uncertified forest are very significant.
4.00E+01

3.85E+01

3.50E+01
3.00E+01
2.50E+01
2.00E+01
1.50E+01
1.00E+01

3.74E+00

5.00E+00
0.00E+00‐5.00E+00‐1.57E‐01‐1.70E‐01

pulp paperstone paper(incine.)wood
waste powerslagrime stone
N2O
natural gas
CH4
Coal
NOx
3.95E+00
crude oil
PM2.5
SOx
ash
stone
paper(landfill) CO2

Fig.2 Weighted Impact using 51.8% of certified forest

References[1] http://lcadb.jemai.or.jp/lca/servlet/Default(Accessed
30.08.2014)[2] H.Uchida,NihonHosoGakkaishi,16, 2007, pp.397-404[3] JEMAI; http://www.milca-milca.net/(Assessed 10.08.2012)[4] JLCA News Letter, No.12,http://lca-forum.org/english/
pdf/No12_Summary.pdf(Assessed 10.08.2012)[5] Nippon Paper Group(Accessed 30.08.2014)
http://www.nipponpapergroup.com/common/pdf/nipponp
apergroup/200218155.pdf

�������������������������������������������������

P-026

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan178

LCA for environmental policy in case of Japanese local governments
Yasuyoshi TARUTA,*1 Yoshiteru NAKAMORI1
1

Japan Advanced Institute of Science and Technology*Corresponding author: y-taruta@jaist.ac.jp

1. Introduction
Human activities have produced many wastes. Thosewastes need to be dealt with appropriately. Problems associatedwith them, have recently been studied in many fields of studies
in terms of waste management and environmental policy. [1][2]Research of Life Cycle Assessment (LCA) gives significant
attention to waste management, relevant decision-making andso on. [3] This research focuses on environmental policy ofJapanese local governments. Nowadays many Japanese local
districts are enforcing a project about biomass produced from(kitchen) garbage in each city unit. The purpose of this policyin each district is to make the best use of biomass and topromote it. Then, in terms of LCA, we examined the change in
the CO2 emission by this project for a local city. This casestudy is expected to contribute to the improvement of local
waste management.
2. Environmental load view point of LCA
This project started in 2007. A city government chose one
dealer to promote this project. They have been collecting waste
garbage from kitchen by trucks. Then they used mixer cars toferment compost from garbage and applied it to farm in the city.
We evaluated the project of CO2 emission from the viewpointof environmental load in LCA.
The system boundaries are shown in figure 1 and figure 2.
Fig 1 shows the system of compost-ization project. Fig 2 isabout incinerator. The amount of garbage handled byincinerators has shown some declining trend due to the use of abiomass like compost.

Figure 1. System boundary of Compost-ization project.

Figure 2. System boundary of incinerator.
The research aims at explicating through calculation CO2emission of compost-ization project and incineration flow. The
Units of CO2 emission factors in the boundaries of collection(to collect garbage), fermentation (to ferment as compost) andtransportation (transport for farm).are shown in Table1. This
project covered about 2,700 households (about 10% in city) as
participants in 2008. And the amount of garbage collected wasabout 360 tons (2008).
Specific formula is not shown in the abstract due to thespace limitation.
Table 1. CO2 emission factor
Boundary
Content
State CO2emission- Unit
factorCollection
Diesel-oil Burn 2.64*10-3
tCO2/L
Fermentation
Diesel-oil Burn 2.64*10-3
tCO2/L
Transportation Gasoline
Burn 2.31*10-3
tCO2/L3. Results
The Result of CO2 emission in the compost-ization plan isshown in Chart1. The duration of time for data collection wasfrom October 2006 to September 2009. In 2006 project wasstarted as a demonstration. The CO2 emission of incineration isshown in Chart2. The city has 2 incinerators. One incinerator
has an ability to burn 160tons of garbage par day and the other
20tons of garbage. Those incinerators use electrical power andfossil fuel (include kerosene and heavy oil) for their operation.
Electrical power needed for CO2 emission unit is5.55*10-1tCO2/MWh. Heavy oil needed for CO2 emission unit
is 2.77*tCO2/kl.

Chart1. CO2 emission of “Compost-ization project”

Chart2. CO2 emission of “Incinerator”
4. Summary and Conclusions
Our calculation result of life cycle CO2 emission ofcompost was about 20t-CO2/half-year in the first half of 2008
and that of incinerator about 1500t-CO2. In the following
period the CO2 emission of incinerator was decreasing to1330t-CO2/half-year in the first half of 2009 because theamount of general garbage was decreasing due to the biomass
policy enforced in 2007. Another reason is that one of thetwo incinerators was abolished because of the decreased
garbage. Actually this biomass policy was effective in lowering
environmental load. Additional studies of the relations between
governmental biomass policies and environmental impact arestrongly suggested.
Acknowledgments
This paper use raw data as much as possible. They were
supplied by the city government and the selected dealer. We
express our gratitude to their cooperation.
References[1] Wittmaier, M, et al, Possibilities and limitations of life
cycle assessment (LCA) in the development of waste
utilization systems–Applied examples for a region in
NorthernGermany.
WasteManagement
29:1732-1738,2009[2] Cherubini, et al, Life cycle assessment (LCA) of waste
management strategies Landfilling, sorting plant andincineration. Energy 34:2116-2123,2009[3] Heijungs, et al, Allocation and ‘what-if’ scenarios in life
cycle assessment of waste management systems. Waste
Management 27(8):997-1005,2007�������������������������������������������������

P-028

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan179

Eco-design of Tableware from Palm Fiber Bio-composite
Singh Intrachooto*1,Rattanawan Mungkung2,3, Kanokon Hancharoen2, and Chiravoot Pechyen41Creative Centre for Eco-Design, Department of Building Technology, Faculty of Architecture; 2 Department of Environmental
Technology and Management, Faculty of Environment; 3Centre of Excellence on enVironmental strategy for GREEN business(VGREEN), Faculty of Environment; 4Department of Packaging Technology and Materials, Faculty of Agro-industry,Kasetsart
University, Bangkok, Thailand*Corresponding author: archsit@ku.ac.th
1. Introduction
Thailand has a national policy to increase palm oil
plantation areas for alternative energy production. As a result,a huge amount of palm wastes are being generated from both theplantationas well asfrom processing plants. This study exploredpotential uses of palm wastes - turning them into bio-composite
materials for tableware. Life cycle assessment is conducted inparallel to the development of bio-composites. It is expectedthat the palm-fiber bio-composite and the resulted tableware
will be commercially viable, which will eventually enhancesustainable consumption and production policy.
2. Methodology
Specific palm wastes, i.e., mesocarp and empty fruit bunch,
were collected from the plantation and palm oil manufacturing
facilities.Thesetwo palm wastes were selected because of
theirlargewaste volumesof 5.4 million tons per year [1]and there
is no alternative application aside from being incinerated forheat or being turned intoparticleboards[2, 3].These wastes weredried and grinded before being exploded with steam pressure tofurther reduce fibers into 3 different sizes (small, medium, large).
In this study, matrix composites (i.e.,melamine, palm fibers, UV
absorber, heat stabilizer and calcium carbonate) at different
ratios are investigated by using Central Composite Design(CCD) program. The designed formulae are tested to identify
optimal conditions for forming tableware and ensure that thecomposite material will meet all tableware safety requirements.
Life Cycle Assessment (LCA) is a tool to assess the potential
environmental impacts of product along its life cycle. Alongwith applying eco-design concept, LCA results are used as the
inputs for design from the very early stage (i.e., conceptual
design).By doing so, the environmental aspects are captured,sothat the designed tableware will be environmental friendly.
LCA of early prototypes provides supporting data for therefinement of composite formulae. It is worth mentioning herethat the amount of palm fiberwill be at least 20% for recycledcontent requirement or 35% for bio-based material requirement.
3. Preliminary results
3.1 Potential formulae of palm-fiber bio-composite
Different ratios of various components were tested anddesigned by using CCD program based on 95% of confidence
levelto identify the optimize conditions (Table 1). UV absorberis added to minimize discoloration,whereas Coad® 21 Zinc
Stearate (clear melt) is used to increase tableware’s heat
resistant.
Table 1: Ratios of melamine matrix with palm fibers
Component
Level
-2
-1
0
1
Palm fiber
15.0%
20.0%
25.0%
30.0%

2
35.0%

UV
absorber

0.0%

0.5%

1.0%

5.0%

10.0%

Heat
stabilizer

1.0%

3.0%

5.0%

7.0%

10.0%

Calciumcarbonate

0.1%

0.3%

0.5%

0.7%

1.0%

3.2 LCA results for the concept design
Figure 1 showed the results of LCA study which indicatedthat the life cycle impactof melamine composite with palm
fibercould be reduced by 20-50%, if palm fibers are used in themelamine matrix (assuming that the quality of tableware madeof 100% of melamine and melamine mixed with natural fibers
are similar).

Figure 1: Potential impact reduction of melamine mixed with
palm-fibrebio-composite (20%,35%, and 50%)

3.3 Design of tableware from palm- melamine composites
Tableware made with palm-melamine can give a natural
aesthetics. Market studies have shown that Japanese food andrestaurants have enjoyed popularity in Thailand with its growthof 15-20% since 2011, ranking 5th behind USA, China, South
Korea and Taiwan, in terms of number of restaurants [4]. The
designs of tableware cater toward Japanese cuisine sector. Allof proposed designs will be evaluated in terms of quality andenvironmental performances as well as the design that meets
potential markets.
Acknowledgments
Special thank is given to ARDA: Agricultural Research
Development Agency (Thailand)for funding.
References[1] OAE:
OfficeofAgricultural
Economics.
2013.
http://www.oae.go.th/download/prcai/farmcrop/palm.pdf.
(Accessed on 24.03.2014)[2] Hashim R, Nadhari W.N.A.W., Sulaiman O, and Sato M., et al,
2012. Properties of binderless particleboard panels manufactured
from oil palm biomass. BioResources, 7:1352–1365[3] Rokiah H, Wan Noor Aidawati Wan N, Othman S, and Fumio K,
et al, 2011. Characterization of raw materials and manufactured
binderless particleboard from oil palm biomass, Materials andDesign, 32:246-254.
[4] Brandage. 2008. Sushi-Ramen: Opportunity only, NoCrisis.
http://www.brandage.com/Modules/DesktopModules/Article/Arti
cleDetail.aspx?tabID=7&ArticleID=1597&ModuleID=701&Gro
upID=469 (Accessed 17.03.2014)�������������������������������������������������

EcoBalance 2014

P-029

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

180

Critical Material Footprint of Household Consumption
Stefan Pauliuk,*1 Sebastiaan Deetman,2 Richard Wood, 1 and Edgar Hertwich1
1

Norwegian University of Science and Technology (NTNU), Trondheim, Norway; 2Institute of Environmental Science, Leiden
University, Leiden, The Netherlands; *Corresponding author: stefan.pauliuk@ntnu.no

1. Movitation
Critical materials or critical metals are used in moderate tosmall quantities only, but they are essential to modern
technology. Massive use of critical materials in new energy
technology and consumer electronics may lead to supply
shortage, price shocks, and unwanted dependency from regionswith exclusive mineral resources.
Recycling of materials is an important way to reduce
primary material consumption, and hence it helps to reducepressure on mineral resources. An illustration of the general
metal system is provided in Figure 1.

Figure 1� The connection between modern technology andmetal cycles�
In developed countries, households are major driver ofindustrial activity� The contribution of goods for final use inhouseholds, especially consumer electronics, is significant inthese countries [1]�To help to provide a scientific basis for the criticality
debate, we conduct a prospective study of the material footprintof future household consumption� We assess the potential
consequences of material recycling on imports of criticalmaterials to the EU, and provide a discussion of how ourresults can inform policy makers and how they can be used todetermine criticality indicators�
2. Methodology
Our study does not aim at forecasting future development�
Rather, we conduct a scenario analysis using the GEO4
scenarios as a starting point [2]� This family of scenarios
contains a set of socioeconomic parameters following fourstory lines termed “market first”, “policy first”, “security first”,
and “sustainability first”� These parameters, including future
population and per capita GDP, are fed into the system
dynamics model TIMER [3] to obtain region-specificprospective time series for the end-user stocks for passenger
vehicles (4 sub-categories) and domestic appliances (12sub-categories)� These stocks provide service to their users, andthey represent valuable material deposits [4]� Using
stock-driven dynamic MFA [5], time series for inflow andoutflow of products are determined� From life cycle inventories
and other published sources, we compiled the metal content of
the different product groups for about 15 metals, including
copper, cobalt, silver, gold, lead, zinc, and tin� We use thesedata to estimate the total metal content of the different productgroups in the 26 regions of TIMER� We apply a simple modelof material recycling or down-cycling, similar to the one usedby Modaresi and colleagues [6], to estimate the future extent of

secondary material production with the given outflow data�Two scenarios for recycling, “Business as usual” and “closed
loop recycling”, are presented� The remaining result is the net
demand for the metals that needs to be supplied by the metal
producing industries�
3. Results and Discussion
We present time series of apparent metal consumption in
12 types of household appliances for about 15 potentiallycritical materials in 26 world regions� This level of detailallows us to get an overview over possible future consumption
patterns� We compare the stocks of materials in appliances tothe current global reserves to demonstrate how important
anthropogenic stocks or ‘urban mines’ will become in the
future�We subtract the possible levels of material recycling fromthe apparent consumption and present time series of theresulting net metal demand for the different regions� This
figure is an important indicator for the dependency oftechnology from material input, and we discuss how it could be
used to inform policy makers about material criticality�
Acknowledgments
This work was made possible by the European
Commission under the DESIRE Project (grant number
308552)�
References[1] Buchert, M�, et al� Recycling critical raw materials fromwaste electronic equipment Darmstadt, Germany, Institutefor Applied Ecology, 2012�
[2] Hughes, B�B�, UNEP GEO4 Driver Scenarios: Using Ifs
with Pardee University of Denver, 2005�
[3] De Vries, B�J�M�, et al� The Targets Image Energy
Regional (TIMER) Model. Technical Documentation�
RIVM, Bilthoven, The Netherlands, 2001
[4] Pauliuk, S� and Müller, D�B� The role of in-use stocks inthe social metabolism and in climate change mitigation�
Global Environmental Change 24, 132-142, 2014�
[5] Müller, D�B�, Stock dynamics for forecasting material
flows - Case study for housing in The Netherlands,
Ecological Economics, 59(1), 142-156, 2006
[6] Modaresi et al�, Global carbon benefits of material
substitution in passenger cars until 2050 and the impact
on the steel and aluminum industries, Environmental
Science and Technology, 2014, in press� DOI:
10�1021/es502930w

�������������������������������������������������

P-030

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

181

Life Cycle Assessment (LCA) of the Supercritical Production of Barium Titanate
Michael Tsang1,2, Gilles Philippot3,4, Cyril Aymonier3,4, Guido Sonnemann*1,2
1
Univ. Bordeaux, ISM, UMR 5255, F-33400 Talence, France, 2CNRS, ISM, UMR 5255, F-33400 Talence, France,
Univ. Bordeaux, ICMCB, UPR 9048, F-33600 Pessac, France, 4CNRS, ICMCB, UPR 9048, F-33600 Pessac, France*Corresponding author: guido.sonnemann@u-bordeaux.fr

3

1. Introduction
The perovskite barium titanate (BaTiO3) belongs to agroup of materials categorized as ferroelectric. It has many
applications in industry and electronics including computers,
microspeakers, and optical communications devices, forexample. In particular, barium titanate nanomaterials can beused as capacitors. Industry and technology are moving
towards electronics with greater capabilities in smaller devices.
Capacitors will have to become ever smaller to meet thesegoals. By reducing the size, but increasing the number of layers,a high capacitance can be met [1]. Decreasing the size ofbarium titanate should be done while preserving the
crystallinity and narrowing the size distribution [1].
Currently there are three main synthesis routes for
producing barium titanate in the nanomaterial size range:solid-state, sol-gel and hydrothermal [1]. These methods eachhave their advantages and disadvantages, but also they have
limitations in desired material characteristics, costs, and timerequirements that could be overcome by one other synthesis
route; supercritical fluid synthesis [1]. This scalable technology
is possible in a single step at moderate temperatures in only
tens of seconds, while producing high quality nanomaterial.
The objective was to study the environmental footprint of
this technology using life cycle assessment and identify what
opportunities may exist over the other traditional methods.
2. Methods
The goal and scope of this life cycle assessment is tocomplete a life cycle assessment on the supercritical synthesisof barium titanate nanomaterials compared to the traditional
solid-state, sol-gel, and hydrothermal synthesis routes.
Production up to the creation of the nanomaterial as a driedparticle is considered. The functional unit considered is 1 kg ofdry barium titanate nanomaterial. Production of barium titanate
using supercritial fluids is not currently practiced at theindustrial scale. Data from the laboratory scale of thistechnology is used to complete the supercritical fluid inventory.
Inventory data for the other synthesis routes are a mixture ofindustrial and lab scale data. These routes all produce
nanomaterials with different size distributions but the pathways
studied are assumed to produce materials in a similar size
range.
It was acknowledged that the supercritical system uses ahigh volume of solvent in its lab scale process, which adversely
affects its environmental footprint. To assess this situation
further, a range of supercritical production scenarios were
included in the LCA. This included comparing different
solvents, recycling and regeneration of the solvent, or using
only water.
The life cycle assessment was carried out in openLCA 1.4
using a combination of primary laboratory data, Ecoinvent 2.2,
previously reported literature and stoichiometric calculations.
ReCiPe is used to calculate the impact assessment.
3. Results
The initial results of the life cycle assessment demonstratethat the supercritical method is more impactful than the othersynthesis routes. For example, Figure 1 shows the impact

results for fossil fuel depletion. The major contributions to this
impact are the large quantity of ethanol used as a solvent, theenergy required for heating the solvent, and energy used for the
set-up pumps. For instance, nearly 66% of the fossil fueldepletion in the default supercritical method (1st bar in Figure1) is due to ethanol use. Figure 1 shows that a hypotheticalsupercritical method using water only as a solvent (“Super
Sans EtOH”) has a significantly reduced impact compared tothe default supercritical method.

Figure 1. Fossil fuel depletion impact results
4. Discussion and Conclusion
The impacts for the supercritical method were overallmuch higher than the other synthesis routes. However, theinventory data used for this LCA was purely laboratory scale
and provides a conservative baseline of worst-case impacts forthis technology. The impact results demonstrate that there are a
few key improvements in the synthesis route that can lead to agreener system overall. Ethanol use was a large contributor to
many of the impact categories. In this LCA, solvent use wastested among a few scenarios. Regeneration of the solvent andor use of alternate solvents such as methanol can help lower
impacts, and in the case of a synthesis route where only water
is used as a solvent, the impacts are reduced significantly. The
laboratory scale necessarily produces disadvantages to thesupercritical method from a LCA standpoint. For example,
solution concentrations must be kept low in order to keep thereaction tubes free of clogging and efficiently heated. A crucial
step will be determining how nanomaterial output can beincreased in the system using higher solution concentrations,and what the demands of such a system would be in terms ofindustrial scale setup and performance.
We feel that the supercritical route is still an importantroute to produce high quality, highly crystalline nanomaterials
for capacitor production. The environmental profile can also be
improved upon by learning from the results of this LCA.
Acknowledgments
The financial support of the Aquitaine Region for the
Chair on LCA at the University of Bordeaux is acknowledged.
References[1] Gilles, P. et al. Journal of Advanced Power Technology,
DOI: 10.1016/j.apt.2014.02.016, 2014.

�������������������������������������������������

P-031

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

182

Integration of geopolitical related criticality assessment for resources into the Life Cycle
Assessment framework
Eskinder D. Gemechu1,2, Christoph Helbig3, Guido Sonnemann*1,2, Andrea Thorenz3 and Axel Tuma3
1

Univ. Bordeaux, ISM, UMR 5255, F-33400 Talence, France, 2CNRS, ISM, UMR 5255, F-33400 Talence, France, 3University of Augsburg, Germany*Corresponding author: guido.sonnemann@u-bordeaux.fr

1. Introduction
Specific materials are becoming essential for thefunctioning of modern societies, as advanced technologies arehighly dependent on them. Criticality assessment has been
recently developed and used by material flow analysts as astand-alone evaluation tool for resource strategies in response
to growing concerns over sustainable supply of resources [1].
LCA has been used to quantify impacts from the direct useof resources by estimating their depletion time, an assessment
limited to geological availability. Geopolitical, economic,
social and other factors that put limits on the sustainable supplyof resources are not meaningfully addressed. This paper,
therefore, aims at looking how resource criticality could be
brought under the framework of life cycle sustainability
assessment (LCSA). A method to assess geopolitical related
supply risk is proposed and applied to selected resources.

The risk would have been lower if France imports REE fromother countries with relatively lower WGI values than China.

2. Method
The geopolitical related supply risk is calculated using thefollowing equation:(1)

Table 1. Geopolitical related supply risk for selected countries
CA

BR

EU

FR

IN

UK

US

Sb
Be
Co

.41
.31
.12

.39
.26
.19

.42
.43
.27

.42
.32
.12

.41
.21
.12

.27
.41
.12

.43
.45
.14

Ge

.25

.28

.26

.22

.28

.14

.27

C

.18

.17

.23

.25

.19

.20

.24

In
Mg
PGM

.20
.17
.28

.24
.21
.24

.27
.17
.30

.24
.16
.26

.30
.21
.30

.22
.14
.26

.27
.17
.25

REE

.19

.19

.17

.13

.16

.13

.19

Se
Ta
U

.55
.08
.10

.55
.09
.14

.50
.11
.10

.53
.08
.08

.54
.09
.07

.45
.08
.10

.48
.10
.11

W

.08

.07

.09

.10

-

.05

.07

where SRc,i expresses the supply risk of country i forcommodity c. sk is the global production share of country k ofthe commodity c. gk referees to the political instability
indicator of country k. It is derived from the Worldwide
Governance Indicators (WGI) of the World Bank. fi,k is importshare of country k in the supply-chain of country i. The
geopolitical related supply risks are then expressed as an LCA
midpoint characterization factors with values between 0 and 1,
indicating a share of the commodity supply being at risk.
3. Results and discussion
Table 1 summarizes the geopolitical supply risk ofresources. Rare Earths Elements (REE), Sb, Nb, and Be are themost crtical resources that are subjected to high supply risk.
They are also among the 20 resources indentified as critical by
the EU report on critical raw materials [2].
Figure 1 highlights the risk contribution assocoated with
the import of REE for France. The largest portion of the risk
comes from China. It is due to the global market concentrationof REE, in which China holds more than 90% of production
share, and high import dependency of France for REE on
China. In most criticality assessments, the geopolitical supply
risk is addressed by weighting the WGI scores by average
production share; whereas in this method the import share isconsidered. It is in line with way of doing LCA, in which theresource flows to a product system are taken into account todetermine the proportional environmental burden associated tothe inputs and outputs. In the same way, the overallgeopolitical supply risk at national, regional or company levelis estimated to be the sum of risks from different regions
proportional to the import contributions and political stabilities.

Figure 1.Supply risk contribution of REE for France
4. Conclusions
The proposed method allows assessing the accessibility ofresources in LCSA, which is beyond the geological availability.
It helps countries and companies to identify geopolitical related
supply risk of resources so that they can take relevant measures
to avoid any potential supply disruption. Inclusion of such
indicator could broaden the scope of mainstream LCA under
the LCSA framework by complementing the usually reported
environmental dimension on resource depletion withgeopolitical and socio-economic aspects related to resources.
Acknowledgments
The financial support of the Aquitaine Region for the
Chair on LCA at the University of Bordeaux is acknowledged.
References[1] Graedel et al. Environ. Sci. Technol. 46(2):1063-1070,
2012[2] EC. Report on Critical Raw Materials for the EU.
Brussels, Belgium, 2014�������������������������������������������������

P-033

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan183

Toward Sustainable Energy Business Using Woody Biomass in Rural Communities
Yusuke Kishita,*1 Noriaki Nakatsuka,1 Yukari Fuchigami,1 and Fumiteru Akamatsu1
1
Osaka University, Japan*Corresponding author: kishita@ceids.osaka-u.ac.jp

3. Case study
We conducted a case study to assess the profit and CO2
emissions of the woody biomass energy business. The regionof interest is Maniwa City, Okayama Prefecture, Japan. The
population and the area of the city are 47,096 and 828.4 km2,
respectively. The period covered ranges from 2013 to 2032 (i.e.,
20 years). We collected relevant data through interviews andliterature review (see [2] in details). We assumed two scenarios
for analyzing the impacts of the biomass energy business:(A) Baseline Scenario: The wood residues (e.g., shaving
and bark, 76 thousand ton/year) from the timber mills areincinerated and landfilled, while thinned wood (90thousand ton/year) is discarded in forests.
(B) Energy Business Scenario: The wood residues from thetimber mills are used for producing wood pellets (18thousand ton/year) and electricity (58 thousand ton/year)that is sent to the electrical grid based on the FIT scheme.
In addition, a larger amount of virgin timber (90 thousand
ton/year) is collected from domestic wood producers forgenerating electricity.

4. Summary
We evaluated scenarios of woody biomass business in a
Japanese rural community. Future work includes evaluating
scenario variants to clarify conditions for sustainable energy
businesses from economic and environmental viewpoints.
References[1] Umeda, Y., et al. Artificial Intelligence for Engineering
Design, Analysis and Manufacturing 14(2): 149-161, 2000.
[2] Kishita, Y., et al. Proceedings of the 13th International
Design Conference: 679-688, 2014.
Annual costs & sales (million JPY)

2. A method for modeling renewable energy businesses
We model a renewable energy business as a process
network based on the concept of the life cycle simulation(LCS) [1] to evaluate various scenarios of renewable energy
businesses. LCS is a method to analyze the flow of a product,
money, and information throughout a product life cycle basedon a discrete event simulation technique.
We define five categories of processes – material
extraction, production, collection/distribution, selling, andend-of-life (EOL). In each process, we define equations to
calculate costs, sales, and CO2 emissions based on the relationshipof inlet and outlet flows between neighboring processes.

Figure 1 shows the cost structures in the two scenarios.
The annual profit of Scenario A is -456 million JPY, while thatof Scenario B is 958 million JPY. Since the profit of thebiomass energy business in Scenario B heavily depends onelectricity sales (2,100 million JPY/year), critical factors ofdriving the business include “the amount of inflow wood forelectricity generation” and “the price of electricity from woody
biomass to sell.” According to our sensitivity analysis, it ispointed out that the business becomes economically unfeasible
if “the price of the electricity from woody biomass to sell”
decreases to 50% of the price as of 2013.
As shown in Figure 2, the CO2 emissions in Scenarios A
and136,000
tCO2/year,
and B are 203,000 tCO 2/year
respectively. That is, Scenario B reduces CO2 by 32.8 % from
Scenario A. This reduction comes from electricity sales andpellet sales, which contributes to saving fossil fuels.

2,800Electricity sales

2,400
2,000

Pellet sales

1,600

Landfill cost

1,200

Labor cost

800

Maintenance cost

400

Land transportation cost

0-400

Initial cost

-800

Electricity cost

-1,200Wood procurement cost

-1,600

Scenario A Scenario B

Figure 1. Cost structures in Scenarios A and B
250,000

Annual CO2 emissions (tCO2)

1. Introduction
After the Feed-in tariff (FIT) scheme was enforced in 2012
in Japan, much attention is being paid to renewable energy
sources, such as solar, wind, and woody biomass. While theexpansion of renewable energy would reduce CO2 emissions,on critical problem is how to ensure economic sustainability of
renewable energy businesses in a long run (e.g., 20 years). In
this paper, a renewable energy business refers to economic
activities where various actors (e.g., business provider,consumer, government, and non-governmental organization(NGO)) exchange materials, energy, money, and information
which are associated with renewable energy.
When attempting to design sustainable renewable energy
businesses, we are faced with many unpredictable factors that
may support or inhibit the business, such as national energy
policies (e.g., nuclear power policies), lifestyles, economic
situations, and technological advancements. Aiming to clarify
conditions for sustainable renewable energy business, thispaper undertakes scenario analysis for evaluating the profitsand environmental impacts of the business. For enabling
scenario analysis, we develop a method for modelingrenewable energy businesses. A case study of a woody biomassenergy business in a rural community in Japan is demonstrated.

Discard (thinned wood)

200,000

Landfill (wood residue)

150,000

Land transportation

100,000

Pelletizing

50,000Chipping
Energy conversion

0

Pellet sales-50,000-100,000

Electricity sales
Scenario A Scenario B

Figure 2. CO2 structures in Scenarios A and B�������������������������������������������������

P-036

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

184

System Dynamics Model for Sustainability Assessment of Mineral Resource Consumption
Considering both Environmental and Resource Constraints
Tatsuhiko Kawamoto,*1 Shinsuke Murakami1, and Jiro Yamatomi1
1

The University of Tokyo, Japan*Corresponding author: 1196824376@mail.ecc.u-tokyo.ac.jp
1. Introduction
Millennium Development Goals (MDGs) with target dateof 2015 were set in 2000, which include eradicating extreme
poverty and hunger. While Ensure Environmental
Sustainability is one of the MDGs, in order to put moreemphasis on the issue, setting Sustainable Development Goals(SDGs) was agreed at Rio+20 Conference. MDGs and SDGs
will ultimately converge in Post-2015 Development Agenda.
One of the goals discussed in SDGs is “ensure access toaffordable, reliable, sustainable, and modern energy for all”.
Increasing energy demand usually means more demands forsome mineral resources and may realize the resource constraint,
which means we will fail to achieve the goal itself.
The ultimate goal of this study is to check the consistency
between multiple goals and resource constraints. Therefore, thesupply and demand balance of the resources and the associatedenvironmental impacts to the areas in Planetary Boundaries [1]will be simulated under the scenarios to achieve the energy
related SDGs.
2. Simulation Methods
In this research, a system dynamics model is constructed
to simulate the supply-demand balance of the targetedresources and related environmental impacts under the energy
scenarios, which make the energy-related SDGs come true. For
example, the electricity supply system consists of generatorsand transmission cables. The model can reflect the detailed
scenarios such as the grid access ratio and the share of
renewable energy and even on-grid/off-grid scenarios.
Three minerals of copper, steel and PGM (platinum groupmetals) are selected as targets. The simulation period is set to
until 2050, and all countries are categorized into 6 regions.
3. Case study for transmission cable
In this paper, the analysis for transmission cable isintroduced as a case study. Figure 1 shows the relationshipbetween electricity consumption and transmission cable length
by countries. Developing countries have relatively small values
in both parameters. On the other hand, the cable length ofdeveloped countries are scattered in wide range even forsimilar electricity consumption. Table 1 shows the result ofmultiple regression analysis. It shows that transmission cable
length is correlative to generator capacity per capita and landarea per capita (the reciprocal of population density). GDP per
capita, even though we often forecast minerals demand withthis parameter, is not statistically significant. These coefficientsare used in the estimation and simulation hereafter.
Unfortunately, sufficient time-series data of transmission cable
length is not available.
Figure 2 shows the forecast of the amount of copper
demands for transmission cable by regions until 2050 based on
the demand forecast of transmission cable. Asia grows
outstandingly until 2050, but Africa has the highest growth rate,
which suggests huge demand after 2050. In 2010, total copper
demand for electricity system including generators accounts forabout 30% of all copper demand [2], so it is significant for thismodel to cover the whole system.

Figure 1. Electricity consumption and transmission cable
length by countries
Table 1. The result of multiple regression analysis
Estimate
Pr(>|t|)(Intercept)
0.3462 0.00012***Generator Capacity per capita
0.2153 0.00050***[kW per capita]
Land area per capita
0.0253 0.00720**[ha per capita]GDP per capita-0.0009 0.81487[current 1000 US$ per capita]Figure 2. Copper input to transmission cable
4. Conclusion
This paper introduced the case study for transmission
cable length estimation and the associated copper demand until
2050. The electricity infrastructures and the demands ofmineral resources for it in developing countries grow rapidly inthe near future and this is essential for their economic growth.
In order to avoid realizing the resource constraint, we need toincrease the resource efficiency in other sectors.
References[1] Johan Rockström et al, 2009, Ecology and Society (14) 2,
Art.32[2] IWCC, End-Use data�������������������������������������������������

P-037

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

185

Global supply chain analysis for sustainable utilization of nickel
Yuto Ohtsuka*1, Hajime Ohno2, Kazuyo Matsubae1, Kenichi Nakajima3, Keisuke Nansai3, Tetsuya Nagasaka1
1Tohoku University, Japan; 2Yale University, the United States; 3 National Institute for Environmental Studies, Japan;*Corresponding author: b3tm5004@s.tohoku.ne.jp

1. Introduction
Nickel is one of the most important and widely used
metals which are used for various industrial products and steel
materials including stainless steel, heat and corrosion resistantalloys, electroplating, and a secondary battery. Thus thedemand forecast of nickel will become increasingly importantin the future [1]. Considering the sustainable supply of nickel
resource, the reserves that can be economically mined are
estimated about 219,500kt. This might suggest the low
possibility of resource depletion in near future. However,looking at the mining area of nickel resources, major nickel
mines are in tropical areas including Indonesia and New
Caledonia, this strongly suggests that there is a big possibilityof biodiversity loss caused by the nickel mining activity. In
addition, the dissipation of resources and hazardous elements
associated with the life cycle of nickel has been becoming aserious problem. Cobalt, for example, is one of the mostconcerned elements which are being lost to the tailing during in
the hydro-process of laterite ore [3]. Heavy metals such as
chromium are also deposited on the soil at Cu-Ni refinery in
Russia or ferronickel smelter in Greece [4-5]. In this study, we
identified (1) the worldwide nickel flow in global supply chain,and (2) flows of cobalt and chromium with nickel production.
2. Worldwide nickel flow in global supply chain
This study estimated the amount of nickel accompaniedwith each item traded among 231 countries and regions withthe equation (1). 123 nickel containing products were chosenfrom HS code (the number indicating the classification ofinternational trade items unified worldwide).

Fi , j Ti , j (1  Wi )Ci(1)

Fi, j: Flow of nickel from country i to j, Ti, j: Flow of commodity
from county i to j, Wi: Moisture content rate of commodity I,
Ci: Nickel content rate of commodity i,
Fi,j was calculated by using the BACI (Base pour l’Analyse duCommerce International, CEPII). Ci was availed from various
sources and the WIO-MFA model [6].

Figure 1 Worldwide nickel flow in 2005
The result of estimation indicated that the amount ofnickel though the trade in 2005 was 2.7 ×106 t-Ni (Figure 1).
And Japan was the top importer with more than 10% of global
flows of nickel. So Japan is the most influential in global
supply chain of nickel.
3. Flows of nickel depended on final demand in Japan
This study estimated the flow of nickel which directly andindirectly caused by Japanese final demand, which is thebiggest nickel resource consumer, on the basis of GLIO

analysis [7] (Figure 2). The nickel flows which caused by
Japanese final demand was 223,256t-Ni (accounted for 8.3% of
the flows all over the world). Direct flows to Japan was
originated from Indonesia, Philippine, and New Caledonia,
where are the laterite mines. On the other hand, indirect flows
have been originated from Australia, Canada, Russia, andSouth Africa.

Figure 2 Flows of nickel depended on final demand in Japan
4. Substance flow of Co and Cr associated with Ni
production
Figure 3 shows the estimated amount of a) nickel,
chromium, and cobalt contained in nickel laterite ore imported
into Japan, and b) those in nickel laterite ore for imported
ferronickel production. For the estimation, we assumed thelaterite ore contains 0.57-3.37 mass%-Ni, 0.31-2.2 mass%-Cr,
and 0.02-0.18 mass%-Co (available from such as [7]), and 1kg
of Ferronickel is produced from 22kg of nickel ore [8].
Our result shows that 20-100 kt-Cr and 650-900 t-Co were
imported to Japan contained in nickel ore. Looking at theJapanese import of ferronickel, 4-23 kt-Cr and 150-200 t-Co
were imported with ferronickel or remained at nickel mine or
ferronickel smelter. This gives us the important suggestion toutilize nickel-ore contained resources in more efficient way.
For this, the material flow of these metal associated with Ni
production must be investigated in more detail.

Figure 3 Estimated amount of Ni, Cr and Co contained ina) nickel ore imported into Japan, and b) nickel ore forimported ferronickel production.
References[1] Mudd, G.M. Ore Geology Reviews 38, 9-26, 2010
[2] Gamini, S., Hydrometallurgy 105, 60-68, 2010[3] Tor, N., Sci. Total Environ. 148, 103-108, 1994
[4] Artemis, N., Sci. Total Environ. 84, 113-117, 1989
[5] Nakajima, K. et al. Environ. Sci. Technol. 47, 4653-4660,
2013[6] Nansai, K., et al. Environ. Sci. Technol. 46, 155-163, 2012[7] Ezequiel, C.S., Journal of MMIJ 113, 35-38, 1997[8] Hinbrans, H. et al. Geologisches Jahrbuch 7, 1999,
ISBN 3-510-95829-2

�������������������������������������������������

P-038

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

186

Mining impact on the changes in land use measured by satellite images analysis
Yasunori Iwatsuki,*1 Hiroya Yamano,2 Kenichi Nakajima,2 Shinsuke Murakami1
1

The University of Tokyo, Japan; 2National Institute for Environmental Studies, Japan*Corresponding author: yasunori_i0617@yahoo.co.jp

3. Result
Figure 1 shows the result of satellite images analysis fortwo mime sites (Tiebaghi [8] and Thio). Thio mine has
operated since 1875 and Tiebaghi mine has operated since1997. Stripped areas can be categorized into two types, pits andrelated facilities such as stockyards or exporting ports. The
areas for facilities built in bare lands vary among the sites.

Pit 2

Pit

Pit 1

Facilities

2km

2km

Figure 1. Satellite images analysis (Left: Thio, Right: Tiebaghi)
4,500,000
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
0

facilities
pit

Figure 2. Area of land usechangeAmount of ore and waste [kt]2. Purpose of this study
In this study, we focused on nickel mines in New
Caledonia. New Caledonia is the 4th largest nickel producer inthe world and it also is a biodiversity hotspot [4]. Therefore, wechose the nickel mines, owned by Societe Le Nickel (SLN) in
New Caledonia [5] and compared the changes of land use andits nickel ore productions.
We evaluated the mining impact on land use change
through a direct observation. We analyzed the satellite images
in 3 years (1986, 1999, and 2012), and measured each scale ofbare land area to be compared. The stripped area in a mine site
can be measured by quantifying the changes of bare land area
in historical satellite images. We used various historicalsatellite images, including those of Landsat /TM/ETM+, SPOT
HRV, and Terra ASTER, to reconstruct temporal changes inbare land areas due to mining activities during each period (1st :1986~1995, 2nd : 1996~2012).
In order to distinguish bare land from others, we used redband data that is expected to show greater difference between
bare soil and vegetation than other bands. Aftergorthorectifying the images by referring to orthorectificed
ASTER Level 3 products and ASTER GDEM data, density
slicing was performed based on the threshold values between
bare land and adjacent vegetated areas calculated by Otsu
(1979) [6-7]. Enclosed boundary lines, extracted based on thethreshold value, were converted to polygons, and the areas
were calculated using the software ArcGIS version 10 (ESRI,
380 New York Street, Redlands, 92373).
Operation data (ore production, total excavation) was
obtained from commercial databases (Raw Materials Data,minecost) to analyze the relationship between mining activities
and land use change.

Tiebaghi mine has two pits: pit 1 being operated and pit 2 in adevelopment stage.
Figure 2 shows the area of land alienated for mining ineach mine site during the 2nd period. In the graph, the area ofland for the site in Tiebaghi is much bigger than others. During
the 2nd period, the area for the pits sharply increased in a shortterm. Moreover, a construction of related facilities started andfinished during this period. Figure 3 shows the amount of Ni
ore and waste extracted during the 2nd period. Ni ore and waste
extracted in Tiebaghi mine is not so huge despite the presenceof large scale land use change in a short term. Using these data,
we calculated the scale of land use change expressed as square
meters per nickel in ore in each mine site. Compared to a value
shown by Nickel Institute (0.0018m2/kg [9]), estimated values
for all mine sites except for Tiebaghi have the same order ofmagnitude. In Tiebaghi mine, top soils in a huge area can be
stripped in advance of extracting ore.

Area of land use change [m2]1. Background
Mining activities often cause a major change in land use
around the sites. Land use change is one of the major reasonsfor the impacts on biodiversity by mining activity, as well as
the heavy metal pollution in acid mine drainage and so on.
In the field of forest policy or urban planning, direct
observations through satellite images are conducted to quantify
land use changes [1]. There are a few researches which
evaluate the mining impact on land use changes, but theobservations in those researches are less precise [2].
Several life-cycle impact assessment tools prepare thecoefficients of land use change [3]. However, the coefficientsare standardized and therefore we cannot see the each minesite’s specific situation. Environmental impact from mining
activities is usually site-specific. Therefore, more detailed
researches to evaluate and compare the land use change at
individual mine sites are useful to understand the mining
impact on land use change.

90,00080,00070,00060,00050,00040,00030,00020,00010,000
0

waste
ore

Figure 3. Amount of ore
and waste

References[1] J. Mwitwa, et al., Int. J. Forest Policy and Economics 25(2012) 19-30.
[2] América P. Durán, Jason Rauch, Kevin J. Gaston,
Biological Conservation 160 (2013) 272-278.
[3] Mila i Canals L, et al. Int. J. LCA 12:5–15.
[4] Norman Myers, Russell A. Mittermeier, Cristina
G.Mittermeier, Gustavo A. B. Da Fonseca & Jennifer
Kent : NATURE, 403, (2000), pp.853-858.
[5] DIMENC/SMC - Mise à jour le 1/04/2012.
[6] Nobuyuki Otsu, IEEE Trans. SMC, (1979) 62-66.
[7] Yamano et al, Int. J. Geomorphology, (2006) 398-411.
[8] Nakajima, K. et al., Metallurgical Research &Technology, (2014) in press.
[9] Nickel Institute, Life Cycle Assessment of Nickel
Products (2000) 97.

�������������������������������������������������

P-039

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

187

Potential Self Supply of Local Resources towards Regional Sustainability:
Case Study of Shinjo Village in Okayama prefecture, Japan
Kazutoshi Tsuda,*1 Hirokazu Makino, Keishiro Hara,2 and Michinori Uwasu2
1

School/Graduate School of Engineering, Osaka University, Japan;
Center for Environmental Innovation Design for Sustainability (CEIDS), Osaka University, Japan*Corresponding author: tsudakazutoshi@lce.mech.eng.osaka-u.ac.jp

2

3. Example results
Historical transition of energy production and utilizationin Shinjo village was estimated through interviews andnarrative recordings. During that field research, collecting
photos taken from the 1960s onwards and interviewing withthat were an effective way to reflect on that time for residents.
As for biomass energy, production of wood charcoal was oneof important forestry work for almost residents. However,traditional charcoal producers have decreased since the 1960s,
and there are only 10 producers in the village these days.

700
600

350
Generation
Consumption

300

500

250

400

200

300

150

200

100

100

50

0

Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
2013

2014

0

Electricity Self-sufficiency Ratio [%]2. Methods
We first conducted interviews and narrative recordings toresidents in Shinjo village, from which we obtained invaluable
data for assessing the potential utilization of local natural
resources. We also developed inventory data of renewableenergy and commodities available within the region by
applying material flow analysis methodology and results frompast studies. Based upon the information obtained from theinventory as well as results of stocks and flows of natural
resources within the village, we demonstrated the assessmentof the regional sustainability from the viewpoint of demandand supply balance for commodities as well as self reliance ofeconomic conditions, addressing the transitions of energy use
including recent introduction of renewable energy sources inthe village.

Demand of firewood for thermal energy utilization has also
decreased because of electrification and dissemination ofelectric appliances and gas-driven equipment.
As for other renewable energy, the small scalewater-power plant was introduced in 1923 by the Chugoku
Electric Power Company. For household use, solar-powered
hot water heater has been introduced around since the 1980s,
and solar power generation system has been introduced byaround 10 households recently. Meanwhile, renewable energies
highly depend on the local conditions such as natural resource
endowments. Thus, this paper investigated an energy balanceof supply and demand of a household as a case study.
Figure 1 shows an example data of the monthly amount ofelectricity generated by the solar power generation system(4kW of capacity) and that consumed by one household(three-member family), and the electricity self-sufficiency ratio.
The average yearly temperature in Shinjo village is 11 degrees
Celsius and refrigerated air conditioning is less than necessary
in summer season. Even though the heating demand is quite
high during the winter season, the power generation amount is
low and not sufficient to meet demand because the solar panel
was covered with snow from December to March. The total
yearly amount of selling and purchasing electricity is more orless the same; however the gap between supply and demand issignificant. There is a need for figuring out the supply
potentials more precisely and the ways to balance between
supply and demand of energy utilization.

Amout of Electricity [kWh]1. Introduction
Ensuring regional sustainability is becoming increasingly
important. In Japanese context, because hilly and mountainous
areas are approximately three-quarters of the total land areasand cover the forty percent of the total cultivated areas, theseareas hold the key to regional sustainability. In pursuit ofregional sustainability, securing the potential of self supply for
essential commodities of daily life within local communities is
one of the essential conditions. In order to discuss suchpotential of self supply for these commodities, re-valuing local
natural resources and enhancing a proper balance between
supply and demand of renewable resources within a region isof critical importance.
In our previous studies [1, 2], we investigated the stocks
and flows of natural resources with a focus on forestry andagriculture sectors in Shinjo village of Okayama Prefecture.
We found that Shinjo village has sufficient food production
while it heavily relies on energy inflow for fossil fuels. On theother hand, the village has large supply potentials forrenewable materials and energy. In order to explore thepotential of self supply for commodities, however, further
investigation is needed to understand the balance between
potential of supply and demand.
In this study, we aim to look into the potential utilizationof local natural resources to understand demand levels foressential commodities of daily life and then to discuss thepotential of self supply of such resources within the boundaryof Shinjo village. To this end, it is significant to understand thehistorical transitions of energy resource use of the villagers.

Month

Figure 1. Monthly amount of electricity generated by solar
power generation system (4kW) and that consumed by one
household, and electricity self-sufficiency ratio.
References[1] Tsuda, K., Hara, K., and Uwasu, M. Designing
Supply-Demand Relationships of Food and Renewable
Energy towards Ensuring Regional Sustainability.
EcoDesign 2011: 11–14, 2011.
[2] Tsuda, K., Hara, K., and Uwasu, M. Supply-Demand
Balances of Food and Energy in Mountainous Rural
Areas to Help Ensuring Regional Sustainability. LCA
Food 2012: 909–914, 2012.

�������������������������������������������������

P-041

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

188

Anthropogenic Earth Movement Analysis Based on Geomorphological Change
by Digital Elevation Model
Keisuke Yoshida*1, Keijiro Okuoka2, Kenji Sugimoto3 and Hiroki Tanikawa4
1,2,3,4

Nagoya University, Japan, Japan*Corresponding author: keisuke.cf@gmail.com
1. Introduction
Material Flow Analysis (MFA) would be interaction
between economy and the environment by analyzing andquantifying material use of national and regional scale.
However Hidden Material Flow (HMF) do not enter the
economy. It is known as displacement of environmental assets
without absorption into the economic sphere, such as plant andoverburden flow caused by mining, farming and construction.
Generally, HMF is estimated by using statistics data, whereas
the geospatial data and the amount of exact HMF is notincluded the estimation. In this study, amount of anthropogenic
earth movement was estimated by using Geographic
Information System (GIS) and Digital Elevation Model (DEM).
DEM is known as height map, which represents the bareground surface without any objects such as plants andbuildings. Large scale of anthropogenic earth movement isobserved as elevation change by using time series DEM. In thisstudy, quarry in west Japan where the producing site ofconstruction resources, such as gravel, sand and aggregate is
focused on as a study area.
2. Methodology
Two types of DEM, 10m mesh and 50m mesh were usedand 10m mesh was resampled into the 50m mesh. Then theraster surface model would be created. It represents theelevation change, and with surface imagery data, those twocontributed to distinct and extract quarries (Fig.1).
Digital'Eleva6on'Model
Basic'Map'
Informa6on0m'Mesh'

Sta6s6cs'Data

Digital'Map''0m'Mesh'Resamle

Crushed'Stone,'etc.'Sta6s6cal'Yearbook[ton)

Fiscal'Gravel'Business'
Status'Report'Summary'Table'[m3]

Weight'Conversion'
Factor[ton/m3]

Raster'Surface'Model

Imagery

Earth'MovementPercent'Swell'and'ShrinkageComparison

Earth'MovementFigure 1. Research Flow
Amount of anthropogenic earth movement is estimatedthrough the use of following equation:

MF (soil, sand) = ∑(V − V )
i

0,i

1,i

Table 1. Result of the Earth movement#$"$
%""'"! 
"$!& $! 

 !% %!%!$
 




 



  

0	
 	
 	
 	
 50	
 	
  100km	
 Figure 2. Distribution map of quarry
Basically, HMF is not quantified by statistics data, such as
Crushed Stone, etc. And Statistical Yearbook and Fiscal Gravel
Business Status Report Summary Table in Japan. In this study,
HMF is included into the results of amount of earth movement.
Therefore, the potential of HMF would be estimated bycomparing DEM based estimation and statistics based
calculation of amount of earth movement. For global
anthropogenic earth movement quantification, high accurate
and automatic estimation system should be build.
Acknowledgement
This research was supported by the Environment Research
and Technology Development fund (1-1402) of the Ministry ofEnvironment, and Grants-in-Aid for Scientific ResearchA(25241027) and B(26281056) of JSPS, Japan.

Dis6nguish'Height''
Decrease'Mesh

Extrac6on'of'Quarries

distinguished and it is spreading all over the west Japan (Fig.2).
Amount of earth movement estimation is bank measure, massof soil and rock before excavation.

(1)

MF (soil,sand): amount of earth movement[m3], V0,i :volume [m3] (point i, at the time of 0), V1,i : volume [m3](point i, at the time of 1)
3. Result and Discussion
This results show amount of anthropogenic earth
movement of quarry, 1.8 billion m3 in west Japan (Table.1). In
addition to this, the number of quarry, 279 and the total quarry
area, 50 million m2 are also estimated. Each quarries are

References[1] H. Tanikawa., et al. Quantification and Evaluation of Total
Material Requirement Related to the Urban Construction: Casestudy for Residential Development, Journal of JSCE, Vol.671,
35-48, 2002.
[2] Y. Shimizu., et al. Temporal Change in the Sediment
Discharge from the Gigantic Landslide occurred on Mt.
Bawakaraeng, Indonesia, Journal of the Japan LandslideSociety. Vol.45, No.2, 95-105, 2008.
[3] F. Kuroiwa., et al. Study on the Estimation of
Anthropogenic Disturbance of Soil and Stone Using the Time
series Elevation Data-Case Study in Misaki-cho, Osaka
Prefecture-, Journal of Environmental System, Vol.40, 35-40,
2012.
[4] A. Adriaanse., et al. Flows-The Material Basis ofIndustrial Economies, World Resource Institute, 7-8,
1997.

�������������������������������������������������

P-042

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan189

A Review of Methodology for Critical Materials Evaluation
Lu-Yen Chen,*1 Jia-Huei Huang,1 and Mei-Chiun Chou2
1

National United University, Taiwan; 2National Taiwan University, Taiwan*Corresponding author: lychen@nuu.edu.tw

1. Introduction
Several works were reviewed to illustrate the methodology
used for assessing critical substances assessment in this study.
The economic importance and the demand for clean energy ofcritical materials were emphasized in the report by the U.S.
DOE [1]. In contrast, the impact of the supply constraints andthe availability risk were chosen as assessment indicators by
the National Research Council of the National Academics of
the U.S.[2]. However, the economic importance the supply risk
and environmental the countries risk received more attention
by the European Commission [3]. The critical substances usedin low-carbon energy technologies were examined by Dawkins
et al. (2012) to show supply and demand of critical substances[4]. The evaluation of mineral deficiency and geopolitical
impact were performed by HCSS to show the price dynamics,
primary/secondary production and reserves[5]. The mining
amount was surveyed with the supply and demand information
to present the status as quo in global scale[6]. Hatch predicted
the future economic importance of several key materials usedin clean energy[7], especially emphasized on the rare earth.
2. Page layout
As summarized in figure 1, the supply risk and thepotential demand were found to be the most common adopted
indicators. The economic importance of critical substances
should also be considered to resolve the market dynamics. As
shown in Figure 1, different indicators were used in different
reports based on the purpose of assessment. These indicators
can be classified into two main categories considering thematerial supply risks and the potential demand.

Figure 1. Indicators proposed by different works.
Further inspection of these indicators demonstrated theutilization of these factors were different in different works, as
shown in Figure 2, the upgrading of recycling technologies was
the most common adopted strategy, which was mentioned in atleast four reports. In addition, the trade cooperation withrestrictions was adopted by U.S., EU, and Netherland; theeffort to find the substitute materials was considered by both
EU and Sweden.

Figure 2. Policy alternatives raised by different countries
and/or regions.
3. Summary
The critical substances will be the important elements withhigher indicators, especially the indicators adopted by morecountries. In conclusion, the supply risk and potential demand
are important to indicate the critical of material scarcity, they
are important for cases in different nations, different
technology levels, and the capacity of recycling. In addition,
the restrictions on trade and adoption of alternative substances
are also good choices.
Acknowledgments
Acknowledgments may be made right before the reference
section. This heading should not be numbered.
References[1] USDOE, 2010. Critical Materials Strategy. U.S.
Departmant of energy, 6-13.
[2] National Research Council of the National Academics.,
2009. MINERALS, CRITICAL MINERALS, AND THE
U.S. ECONOMY, 14-24.
[3] European Commission. , 2010. Report of the Ad-hoc
Working Group on defining critical raw materials, 5-10.
[4] Elena Dawkins., Matthew Chadwick., Katy Roelich.,
Richard Falk., 2012. Metals in a Low-Carbon Economy:
Resource Scarcity, Climate Change and Business in a
Finite World, 7-19.
[5] HCSS, 2010. Scarcity of Minerals. A strategic security
issue, 11-17.
[6] Huib Wouters., Derk Bol., 2009. Material Scarcity, 13-38.
[7] Gareth P. Hatch, 2011. Earths Global supply & demand
projections and the leading contenders for new sources ofsupply, 3-68.

�������������������������������������������������

P-043

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

190

Modeling climate effects of biogenic carbon flows from forests and wood products at thenational level
Bernhard Steubing,*1 Esther Thürig,2 Golo Stadelmann,2 Florian Suter1and Stefanie Hellweg1
1
ETH Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Switzerland*Corresponding author: steubing@ifu.baug.ethz.ch

2

1. Introduction
Most LCA studies have in the past assumed biomass fromsustainably managed production systems to be carbon neutral
and therefore climate neutral. More recent research has shownthat next to carbon stock changes, it is essential to account for
the timing of emissions in order to assess the effects on climatechange. Cherubini et al. [1] introduced GWPbio factors thatreflect the global warming impact of biomass relative to that offossil carbon emissions depending on a given rotation period
and time horizon. Their subsequent work extends this toinclude other factors, such as carbon stock changes andtemporary carbon storage.
Within the research project “Ecological use of wood
resources in Switzerland” we assess the optimal uses of woodamong a multitude of applications, ranging from direct energy
to cascade uses. We tried to directly implement the method of
Cherubini et al., however, we encountered some challenges.
The first one relates to data for the calculation of the
GWPbio: while Cherubini and colleagues calculate GWPbio
values generally at the stand level, for which the forest growth,rotation period, carbon stock changes, and subsequent
temporary carbon storage duration can be more readily
described, our scope was a nation-wide assessment of wood
product flows from forests with high spatial variability.
The second challenge relates to calculating the GWPbio in
the case of temporary carbon storage. Due to cascade use andmixing of wood sources in between each use (e.g. if waste
wood is collected from several sources, mixed, and then reusedfor several products) it is impossible to keep track of thestorage time of biogenic carbon relating to a specific harvest
site, which would be needed for a proper calculation (see [2]).
The methodology section describes how these challenges
were met. We then use a simplified model of the Swiss wood
use to calculate the climate impacts including biogenic carbon.
2. Methodology
In order to work with Swiss-specific GWPbio factors at
the landscape level, i.e. for a larger area or the total national
forest area, average growth curves and rotation periods wereneeded. These were empirically derived based on Swiss
National Forest Inventory data for different forest types andelevations. GWPbio factors were subsequently calculated fromthis data and applied to biogenic carbon emissions (e.g. fromcombustion/disposal of wood products).
To solve the problem of tracking carbon stored in wood
products, we calculated an annual storage benefit (a reductionof the GWPbio) and used this value in our model. Since the per
year storage benefit is originally a non-linear function of time[2], we had to first linearize this function. This does lead to anunderestimation of the GWPbio for short storage times, whichis, however, rather small, especially if long time horizons are
considered (e.g. 500 years). The advantage is, however, that it
is sufficient to know the lifetimes of different wood products
instead of having to track forest carbon throughout its entire
lifecycle of possibly different products. This allows a model tocontain “mixing” processes with several inputs and outputs. It
also enables the modeler to select the lifetime of wood products

as a decision variable in an optimization model.
The modified approach of Cherubini was then used in a
simplified model of the Swiss wood use. Differences withregards to a theoretical optimal wood use are also analyzed.
3. Preliminary results
GWPbio factors depend to a great extent on the following
key factors (see also Table 1):Tree species

Altitudinal vegetation zone
Rotation period length
Choice of time horizon (TH)
Table 1. GWPbio values as a function of different parameters
Forest type
Altitudinal
Rotation GWPbio GWPbio
period
TH=100 TH=500
vegetation(years)zone
Theoretical;Cherubini 2011 100
0.42
0.07
Coniferous
Submontane 120
0.53
0.08
Deciduous
Submontane 140
0.66
0.11
Coniferous
Montane
160
0.64
0.11
Deciduous
Montane
140
0.66
0.11
Coniferous
Subalpine
180
0.73
0.14
The reason why all Swiss GWPbio values are higher than
the theoretical values calculated in [1] is to a large extent due
to more realistic growth curves and longer rotation periods.
The annualization procedure for the temporary carbon
storage was successfully implemented in a model of the Swissnational wood use.
Considering biogenic carbon exchanges with theatmosphere due to the timing of the release and removal ofcarbon from the atmosphere leads to considerably higher
climate change impacts than if this was ignored. Considering
temporary carbon storage in wood products leads, naturally, toa decrease in climate impacts. However, the temporary carbon
storage was not enough to offset the climate effect of theadditional temporary carbon in the atmosphere from woodincineration, at least in the context of our model.
References[1] Cherubini, F.; Peters, G. P.; Berntsen, T.; Strømman, A.
H.; Hertwich, E., CO 2 emissions from biomass combustion forbioenergy: Atmospheric decay and contribution to global
warming. GCB Bioenergy, 3(5), 413-426, 2011.
[2] Guest, G.; Cherubini, F.; Strømman, A. H., Global
Warming Potential of Carbon Dioxide Emissions from Biomass
Stored in the Anthroposphere and Used for Bioenergy at End of
Life. Journal of Industrial Ecology, 17(1), 20-30, 2013.

�������������������������������������������������

P-044

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

191

Material flow analysis of Swiss waste management
Melanie Haupt,*1 Carl Vadenbo,1 Bernhard Steubing,1 and Stefanie Hellweg1
1
ETH Zurich, Switzerland*Corresponding author: haupt@ifu.baug.ethz.ch

1. Introduction
Closing material cycles can help to mitigate many of theadverse effects associated with the ever-increasing demand formaterials. To map the present material recovery potential ofsolid waste in Switzerland, a national material flow analysis(MFA) of waste streams originating in households and fromcommercial sources, as well as in construction and demolition(C&D) was performed. The work presented here is part of alarger project on the Swiss municipal solid waste (MSW)
management, based on MFA, life cycle assessment andoptimization. The project includes all waste streams withdetailed studies of some recycling fractions and recoveredmaterials. The recovery of secondary resources from MSW
incineration (MSWI) is also considered as it has been shownthat there is still a considerable improvement potential for
metal recovery from MSWI bottom ash [2].
2. Method
MFA was used to analyze the material turnover of the
Swiss waste management for the year 2012, including all waste
streams occurring in Switzerland. In addition to thermal
treatments, paper, cardboard, PET bottles, glass, tinplate andaluminum recycling were analyzed. The residues from MSWI
were also included. Data for material recycling was found innational statistics from the Federal Office for Environment andgathered in collaboration with recycling associations andcompanies. As the consistency of the data available varied
significantly between waste streams, data reconciliation was
performed together with the respective industries.
3. Results
In total, 70% of all occurring waste was sent to recycling,including 2 million tons from households and 13 million tonsof C&D waste (Figure 1). 4% of all wastes were treated inbiological processes, and 22% were thermally treated andenergetically utilized in industrial furnaces, cement production,and MSWI. The remaining 5% were exported for eithermaterial or energy recovery. The MFA showed a significant
share of separately collected fractions from households to beexported. 40% of collected paper, 100% of separately collectedaluminum and 52% of cullet’s were exported (see Figure 2).
Although recycling networks are well-established in
Switzerland, a significant amount of reusable material ends up
in MSWI. While only 13,000 tons of tinplate were collectedfrom households, 19,000 tons of ferrous scrap are found in
MSW. 48,000 tons of ferrous scrap were recovered fromMSWI bottom ash (also including scrap from industrial anddirectly delivered waste for incineration).

Figure 2. Recycling and recovery from Swiss MSW in 2012.
Fractions marked as export are recovered and recycled outsideof Switzerland. Residues from recycling processes going to
MSWI are not shown.
4. Discussion
The MFA highlighted important decision nodes with
implications for further treatment and use of secondary
materials. The point of separation is, for example, decisive forthe quality of the recovered product and, therefore, itsreusability. The MFA results do not, however, offer any insights
to the environmental relevance of the mass flows, but will in a
subsequent step serve as the basis to assess the related
environmental impact. Designing sound material cycles is ofgreat importance and environmental impacts should becompared using a life cycle perspective: Indicators like energy
demand, climate change, toxicity, and resource depletionshould be analyzed. Guidance for policymaking and for
optimal waste management should only be provided after
obtaining a holistic view of the relevant environmental impacts
and may benefit greatly from the application of optimization
techniques.
Acknowledgments
The authors would like to thank Rytec AG and econcept
AG for their support in data collection.
References[1] Dettli, R., et al. Transformation der Abfallverwertung inder Schweiz für eine hohe und zeitlich optimierte
Energieausnutzung. Zurich, 2014.
[2] Morf, L. S., et al. Waste Manage 33: 634-644, 2013.

Figure 1. MFA of the primary treatment routes of the Swiss waste management system 2012, based on 1.

�������������������������������������������������

P-045

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

192

Metrics for Performance Measurement of Advanced Repair-To-Order, Disassembly-To-Orderand Refurbishment-To-Order
Ammar Y. Alqahtani,*1 Surendra M. Gupta,2 Kenichi Nakashima3
1

King Abdulaziz University, Saudi Arabia; 2Northeastern University, USA; 3Kanagawa University, Japan*Corresponding author: aaylqahtani@kau.edu.sa

1. Introduction
This paper presents an Advanced Repair-To-Order,
Disassembly-To-OrderandRefurbishment-To-Order(ARTODTORTO) model with disassembly precedence
relationships among components of an air conditioner (AC). It
also inspects and analyzes the impact of using smart sensors in
End-of-Life products (EOLPs) on system performance. Various
experimental design studies are run based on orthogonal arrays(OAs). The customers’ demands may be satisfied either bypurchasing new components, reassembling components fromthe returned used products, refurbishing product, or
remanufacturing used products based on customer’s remaining
life needs. Discrete event simulation models are used to
calculate various performance measures under different
experimental conditions.
2. Literature review
ARTODTORTO system built in this study is based on
disassembly-to-order research. Ondemir and Gupta (2013)
proposed a multi-criteria decision making model for advanced
repair-to-order and disassembly-to-order system with productsthat are embedded with sensors and radio frequency
identification (RFID) tags. In a comprehensive study
incorporating quantitative evaluation of sensor embedded
products (SEPs) on the performance of a disassembly line
(Ilgin and Gupta in 2010), it was showed that smart SEPs are
better in handling remanufacturing uncertainties.
3. Objective of the study
The objectives of this study include examining anddetermining the influence of SEPs and RFID tags on various
performance measures (viz., disassembly cost, disposal cost,backorder cost, holding cost, testing cost, transportation cost,
total cost, total revenue, and profit) and determining how toprocess EOLPs to meet product, component and material
recovery demands of ACs. Specifically, there are four
objectives for the ARTODTORTO system to optimize viz.,minimize the total cost, minimize the number of disposed items,
maximize the material sales revenue, and maximize thecustomer’s satisfaction level by meeting the demand.
4. System Description
ARTODTORTO system considered in this study is shown infigure 1. Based on the arriving EOLP’s condition, it will go
through a series of recovery operations. ARTODTORTO
system not only considers EOLPs disassembly, it also
refurbishes and repairs the EOLPs. Refurbishing and Repair
processes may require reusable components to meet thedemand of the product. Nine components of AC are consideredviz., evaporator, control box, blower, air guide, motor,
condenser, fan, protector, and compressor precedence
relationships. Exponential distributions are used to determine
disassembly times at each station, interarrival times of eachcomponent’s demand, and interarrival time of EOLPs. Two
different types of disassembly operations are performed, viz.,destructive and nondestructive depending on the component’s
condition. ARTODTORTO model assumes that the demands
and life cycle information are known. It is also assumed that
retrieval of information costs less than inspection and testing.

Figure 1: ARTODTO system material Flow
Recovered product, components and materials arecharacterized based on their remaining life times and areplaced in different life-bins (e.g. 1 year, 2 years, etc.) waiting to
be retrieved via a customer demand.
5. Methodology
A simulation model was built to represent the full recovery
system and observe its behavior under different experimental
conditions. Arena version 14.5 was used to build thediscrete-event simulation models. A full-factorial design with
69 factors at 3 levels each would require an extensive numberof experiments. To reduce the number of experiments to apractical level, a smaller set of all the possible experiments(139) was picked using orthogonal arrays designed by Taguchi.
6. Results
Metrics for performance measurement of ARTODTORTO
for the 139 experiments was collected. Table 1 shows a sampleof the performance measures.
Table 1: Performance measures of the ARTODTO system
Experiment #Total Revenue Total Cost
Profit$1,452,500$1,113,805 $338,694
1
:
:
:
:
$1,400,444$944,146$456,298
139$1,278,555$1,006,844 $271,711
Average
References[1] Ilgin, M. A., & Gupta, S. M. (2010). “Evaluating the impact of
sensor-embedded products on the performance of an air conditioner
disassembly line”, The Int. Journal of Advanced Manufacturing
Technology, Vol.53, Issue 9-12, 1199–1216, 2011.
[2] Ondemir, O. and Gupta, S. M., “A Multi-Criteria Decision Making
Model for Advanced Repair-To-Order and Disassembly-To-Order
System”, European Journal of Operational Research, Vol. 233, No.
2,408-419, 2014.

�������������������������������������������������

P-047

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

193

An Estimation of Ship Waste Quantities at Port:A Case Study in Haiphong, Vietnam
To Ngoc Thang, Takaaki Kato
Graduate School of Environment Engineering, The University of Kitakyushu, 808-0135, Japan

2. Methodology
In the first stage, calculation formula for quantity of shipgenerated waste was established. Then, input data including thenumber of vessel docking, type of ships, number of crewmember
and generating rate of daily garbage were defined. Because maintypes of docking ships in Haiphong port are bulk ships andcontainer ships, we did the survey with 150 container ships and150 bulk ships to gather the average number of crew per ship
and average time in voyage. Number of ships and time spent inport of every ship during 2009-2013 period were collected fromPort Operation. Garbage generating rate from ship is based on
the guideline of International standard, ISO 21070 (Handling ofship generated garbage). There are 03 scenarios (low, medium,high) of domestic waste while one ship generates approximately
11 kg for maintenance waste per day.
3. Results and Discussion
3.1. Difference between data of bulk ships and container ships
Two main types of ship in Haiphong port have specified
characteristic that require calculating quantity of garbage
separately. From 2009 to 2013, while bulk ships docked mainlyat HoangDieu terminal, container ships were trending to dock at
Chuave and Tancang terminals.
Table 1. Distinguish between bulk ship and container ship
Bulk ships
Container ships

Averagemember
16.18
23.04

Time in voyage(days)
6.44
3.03

Time spent inport (days)
3.08
1.09

Table 1 provides the difference on input parameters
between bulk ships and container ships. We observe that both“time in voyage” and “time spent in port” of bulk ships were
almost twice to three times longer than those of container ships.

That also explains one reason why there were more crewmemberof container ships than bulk ships.
3.2. Quantity of ship waste in medium scenario
From 2009 to 2013, although HoangDieu terminal had thebiggest volume of garbage from ship, its number was decreasing
because of the decline of docking vessels. The same trend wasobserved in Chuave terminal whereas it recorded the upward
trend in the number of garbage in Tancang terminal. In total, thehighest quantity of garbage was 1072.6 tons during the year
2010 before decreasing to 803.7 tons in 2013. (Figure 1)
1,200

Quantitiy of garbage, tons

1,000
800
600

400
200

0
2009

2010

Hoangdieu

2011

Chuave2012

2013

Tancang

Total

Figure 1. Quantity of garbage in medium scenario
3.3. Assessment of collected rate by port reception
1,600

Quantity of garbage, tons

1. Introduction
Marine transportation affects to environment in number ofways including emission, oil spills risk, sewage and garbage
from ship. Among them, garbage including domestic andmaintenance waste from ship are significant sources of marine
pollution. To prevent marine environment from pollution, theAnnex V of the International Convention for the Prevention of
Pollution from ship (MARPOL) has been released. It requests
the responsibility of Port Authorities and Ship Operators formaking garbage management plans, which are necessary tocontrol and monitor procedures for storing and disposing of
garbage. To make garbage management plan, quantities of shipgenerated garbage is essential data. Currently, a few studies tocalculate ship-garbage was conducted in Mediterranean Sea(REMPEC, Activity A, 2003) and Serbia (Vladanka et al., 2011).
However, these studies contain limitation because of ignoring
influence factors on calculation processes, for instance, garbage
generation during voyage and maintenance waste on ship.
My research shows an advanced study method that has
considered almost influence factor on calculation process. The
research uses Haiphong port – one of the biggest port of Vietnam
as case study, where they do not have specialized research on
calculating the quantities of garbage from ship. Quantitative
estimate was carried out to determine amount of garbage that has
been generated from ships at 03 terminals of Haiphong port from2009 to 2013.

1,400
1,200
1,000
800

600
400
200
0

2009

2010

2011

2012

Medium scenario

Collected volume

Low scenario

High scenario

2013

Figure 2. Quantity of generated collected garbage
Based on the data from a collecting company collecting
ship garbage from 2009 to 2013, volume of collected garbage
from ship in Haiphong port are shown in Figure 2. Comparedwith medium scenario, garbage collected rate at the port was
fluctuated between 10% and 45% of total generated volume.
This percentage is obviously lower than collected rate in urban
area of Haiphong (more than 80%).
4. Conclusion
This study has provided quantity estimation for ship waste
in Haiphong port. The garbage quantity data is need forestablishing waste management plan at port as well as on ship.
Even the total amount of garbage in Haiphong port was
decreasing from 2009 to 2013, the collected rate of garbage byport reception facilities was still low. Therefore, Haiphong’s port
authority should improve reception facilities of garbage andencourage ships to bring back garbage to shore, which help toreduce illegal dumping garbage into sea.
References[1] IMO, Annex V, Marpol 73/78 Convention.
[2] ISO 21070:2011, Management and Handling of shipboard
garbage, Annex 2.
[3] http://www.marinetraffic.com(Accessed 15.05.2014)[4] www.haiphongport.com.vn�������������������������������������������������

P-048

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

194

Optimal Improvement of Waste Plastics Recycling System in Tianjin Based on
Environmental Evaluation and GISRichao Cong,*1 Toru Matsumoto,1 Takamasa Hayashi,2 Wenchao Li3
1

The University of Kitakyushu, Japan; 2NTT DATA, Japan; 3Nankai University, China*u3dac404@eng.kitakyushu-u.ac.jp

1. Introduction
Zi’ya Circular Economy Industrial Park, a waste home
appliance dismantling base, was recently established in Tianjin
to handle domestic and imported waste. However, it was said
more than half of the waste plastics (WPs) was transported
outside of Tianjin after treatment [1]. To solve the problems
arising from the current recycling system, we have suggested
Tianjin set up a WP recycling factory in Zi’ya Industrial Park
that uses recycling technology from Japan and improve thecurrent collection and processing system.

the proposed case and present case. Finally, a life cycle analysis(LCA) was conducted for a projected scenario and a baseline
scenario [3-4].
3. Conclusions
The CO2 emissions reduction between the proposed case
(90% loading rate) and the present case (50% loading rate) is
about 3,977 t per year, or about 46% of present emissions. As
shown in Figure 2, the reduction in CO2 emissions in the
projected scenario was 111,621 t per year as compared to thebaseline scenario.
Thousand tons-CO2/yr

2. Methodology
Based on an investigation we conducted in August 2011,
we estimated the amount of WPs generated from households tobe 35,760 t per year.
In our study, GIS technology was used to determine theoptimal locations for WP recovery stations and intermediate
disposal plants, as well as to simulate the recovery
transportation process and calculate transportation distances.
The resolution processes are shown in Figure 1[2]. The CO2
emissions reduction was obtained from comparison between

150
120
90
60
30
0
-30
-60
-90
-120
Project scenario

Baseline scenario

Reduction

Figure 2, The result of LCA
4. References[1] Shintaro H., The Material Recycling Project ofWaste Plastics in Tianjin(in Japanese) INDUST Nov,
2011[2] Yonghai X., Toru M., Jian Z., Study on the GIS
based Visible Analysis of Waste Disposal Flow of
Beijing,

Abstract

ProceedingsofInternational

Conference on CERSD, p.36. 1-4, 2005
[3] Plastic Waste Management Institute) LCI data
survey report of Petrochemicals (in Japanese), 2009
[4]

Figure 1. Schematic flow of the GIS analysis

Plastic Waste Management Institute

LCA

Research Report on treatment and disposal of Waste
Plastic (in Japanese), 2001�������������������������������������������������

P-049

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

195

Life Cycle Assessment of Reuse System for Surgical Gowns
Naoki Yoshikawa,*1 Nobumitsu Kitanishi,1,2 Koji Amano,1 and Koji Shimada1
1Ritsumeikan University, Japan; 2Takasago Thermal Engineering Co., Ltd., Japan*Corresponding author: n-yoshik@fc.ritsumei.ac.jp

2. Methodology
This study evaluated two types of surgical gown, disposable
and reusable. Details of the gowns are shown in Table 1. Bothgowns have roughly the same level of liquid barrier
performance. Figure 1 illustrates the system boundaries of thetwo products. The life cycle stages of the reusable products
consist of raw material procurement, manufacturing, delivery,
maintenance, and waste management (disposal). The
disposable product stages are raw material procurement,
manufacturing, delivery and waste management (disposal). The
average number of uses of reusable products in a life cycle isTable 1. Detail of products compared
Reusable

Disposable

Material

Polyester (100㸣)Polypropylene (100㸣)Liquid barrier
performance
Usage (time)
WeightLevel 3 or 2
㸦AAMI Standard㸧
50
0.460kg

Level 3㸦AAMI Standard㸧
10.115kg

Sterilization

Autoclaving

EOG

Raw
material
Reusable

Manufacturing MaintenanceTransportation

Disposalassumed to be 50 times. After using the reusable gowns 50 tim
es and the disposable gowns once, both types of gowns areincinerated. Foreground data of reusable products was obtained
from a questionnaire presented to manufacturers of gowns andservice providers and deliverers of laundry. Data related todisposable products in raw material procurement andmanufacturing processes is based on Ponder [1] and METI [2].
The potential of GHG emission reduction was based on aquestionnaire to medical institutions. Questionnaires were sent
to 994 facilities, of which 9.2% responded. The survey asked
about their awareness of reuse systems and the conditions theywould need to have met to change to such systems.
3. Results
Figure 2 shows the life cycle GHG emissions of thereusable and disposable products per use. Most GHG emissions
come from the washing, drying, and sterilizing processes forthe reusable products. Manufacturing and waste management(incineration) processes are the main factors in GHG emissions
for the disposable products. Results showed that the reusesystems can reduce life cycle GHG emissions(0.38kg-CO2eq/use) by 35% in case of 50-times use. GHG
emissions start to diminish after 14-times use, which is lower
than expected.
The results of the questionnaire to medical institutions
showed that about 11% of gowns used are supplied by a reusesystem. Additionally, 11% of medical institutions are
considering introducing reuse systems, if the liquid barrier
performance and cost of the system meet their demands. Thisway, about 500t-CO2eq of GHG can be reduced per year.
1.2

GHG emission kg-CO2eq/use

1. Introduction
An important role of surgical gowns is preventing the
medical staffs and patients from infection. Suppliers mustensure that standards of sterilization and liquid barrier
performance meet this function. Disposable products have alarge share of the surgical gown market in Japan. However,reusable products and systems recently developed by somecompanies, which have same level of the function, seem to beable to reduce medical waste and the consumption of fossil
resources because both products are made from chemical fibers.
However, no existing study evaluates the life cycle
environmental load of surgical linen reuse systems, includingcommercial laundries. This study evaluates the life cycle
environmental load of reusable surgical gowns as compared todisposable gowns. We also surveyed the interest of medical
institutions in introducing reuse systems and estimated thepotential reduction of greenhouse gases (GHG) emissions.

Disposal

1.0

Transportation

0.8

Sterilization

0.6

Drying0.4

Laundry
Manufacturing

0.2

Raw material

0.0

Reusable
Monomer

Weaving

Laundry

Polymerization

DyeingDryingSpinning

SewingSterilization

ReusableRawmaterial
Reusable

Manufacturing

Monomer

Weaving

Polymerization

DyeingDying

Spinning

Sewing

DisposablepTransportation
Tation

Disposal

Use

Dispose after
50 times use

Transportation

Disposal

Transportation

Disposal

Sterilization

Use

Figure 1. System boundaries

Disposable

Figure 2. Comparison of GHG emissions from reusable anddisposable products
6. Conclusion
This study compared life cycle environmental loads ofreusable and disposable surgical gowns. Results showed thatafter 50-times use, reusable products reduce GHG emission
from disposable products by 35%. Comprehensive assessment
covering other medical supplies is needed to support decision
making for sustainable procurement by medical institutions.
References[1] Ponder, C.S. PhD thesis, North Carolina State University,
2009, 87–106.
[2] METI, Research report on LCA of fabric products(clothes) (in Japanese), http://www.meti.go.jp/policy/
fiber/ downloadfiles/LC A -h ontai.pdf (Acces sed
05.09.2014).

�������������������������������������������������

P-051

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

196

Analysis of Contamination of Impurities in Steel Recycling
Chihiro Murayama 1, Ichiro Daigo *1 and Yoshikazu Goto 1
1

Graduate School of Engineering, The University of Tokyo, Japan*Corresponding author: daigo@material.t.u-tokyo.ac.jp

1. Introduction
When steel scrap is recovered from end-of-life products,
components containing Cu and Sn are mixed into the scrap.
The elements; Cu and Sn, cannot be extracted in EAFs (electricarc furnaces), which are regarded as tramp elements. The
contents of the tramp elements may become higher due torepeated recycling. High contents of the tramp elements cause
surface cracks in the hot strip being manufactured, known as
surface hot shortness. Therefore, it is preferable tomechanically remove the components containing the tramp
elements from steel scrap before melting in EAFs.
Although there are problems in the contamination of tramp
elements, there is very few information about contents of tramp
elements in steel scrap. One of the reasons is difficulty ofobserving and quantifying the tramp elements in steel scrap[1].
Another reason is that many steelmakers do not seriously think
about the problems because contents of tramp elements incurrently produced steel can be diluted by using high purity
scraps, DRI (direct reduction iron) and/or pig iron[2]. In thisstudy, we aim to understand the behavior of tramp elements ina steel recycling system with modeling the relation between the
tramp elements contents in recycled steel and contents ofunintentionally mixed components containing tramp elements
in steel scrap.
2. Development of a steel recycling model
We developed quite a simple model to observe thebehavior of tramp elements in a repeated steel recycling system.
In our model, we suppose that steel is repeatedly recycled in
one and only one furnace and that there is no trade with outsideof the recycling system. Figure 1 shows a schematic illustrationof the supposed recycling system at the nth time recycling.
Portions of inputs in the furnace; old scrap, a tramp
element contained in mixed components, processing scrap and
pig iron, are set to x, y, z and w, respectively, as shown infigure 1. The balance of tramp elements in raw materials andsteel products at nth time recycling can be formulated by arecursion formula expressed as equation 1.

C n xC n 1  y  zC nyy
 x  Cn  
  C0 1 x  z  1 x  z
1 z  

Figure 1. Schematic illustration of the supposed recycling
system at the nth recycling.

Figure 2. Distributions of impurity contents in cases ofrelatively large y (a) and small y (b), estimated by Monte-Carlosimulation.

(1)

where C is a content of tramp elements in materials and n is thenumber of recycling times in the system.
Consequently, solving the recursion formula, the content
of tramp element in the steel product after recycling any
number of times can be expressed as equation 2.
n

On the other hand, in a case of relatively small y, an
unsymmetrical distribution spreading for high content direction
was shown, as shown in figure 2 (b). We compared the shapesof distribution with the distributions of tramp elements contents
in EAF steel bars observed in Japan[3]. The shapes of
distributions for Cu and Ni contents were symmetrical, and for
Sn content was unsymmetrical, as shown in figures 3 (a) to (c).
According to our model, Cu and Ni contents are influenced bymixing components despite Sn content is not likely influenced
by them. Thus, behavior of contaminating tramp elements
could be estimated from the shapes of distribution of impurity
content by using our developed model.

(2)

3. Results and Discussions
On the basis of the developed mode, Monte-Carlosimulation was employed to estimate distributions of the tramp
elements content in recycled steel during repeated recycling bygiving random values obeying standard distributions to x and yin the equation 2.
In a case of relatively large y, a symmetrical distribution
like standard distribution was shown, as shown in figure 2(a).

Figure 3. Distributions of Cu (a), Ni (b), and Sn (c) contents insteel bars in Japan.
References[1] Toi, A., Sato, J., Kanero, T. Analysis of Tramp Element inIron Scraps. Tetsu-to-Hagane 83(12): 850, 1997.
[2] Daigo, I., Fujimaki, D., Matsuno, Y., Adachi, Y.
Development of a Dynamic Model for Assessing
Environmental Impact Associated with Cyclic Use ofsteel. Tetsu-to-Hagane 91(1): 171-178, 2005.
[3] Daigo, I. and Goto, Y. Comparison of Tramp Elements
Compositions in Steel Bars between Japan and China
Tetsu-to-Hagane 100(6): 756-760, 2014.

�������������������������������������������������

P-054

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

197

Matching Reused Products with Users Considering Their Satisfaction
Yuki Yamamori*1, Keisuke Nanjo, and Hiroyuki Hiraoka
1
Chuo University, Japan*Corresponding author: yamamori@lcps.chuo-u.ac.jp

1. Introduction
In order to change the consumption society to therecycling society, we focus on promotion of reuse of parts andmachines. We are developing a part agent system for
management of individual parts that is required for an effective
reuse [1]. A part agent is a network agent applied to each part.
A part agent follows its corresponding part through the networkand manages the information on state of the part as well asplace and situation where it is used. The agent advises the userof the part on its reuse based on the information on other parts
obtained from other agents.
In this paper, a function of part agent is described thatmatches a seller, i.e., a user who has a reused product, and abuyer, i.e., a user who wants to use it. Further, a new function
is proposed based on the discussion of the scheme.
2. A Scheme that matches reused products with users
considering their satisfaction

Fig. 2 Concept of the reuse of products using matching
function based on user’s satisfaction
We focus on reuse of used home electric appliances amongneighboring homes. A part agent advises the user on
replacement of its product when the product deteriorates. The
part agent proposes to the user a used product that a seller
possesses by the following procedure.
A part agent collects information on the same kind of
products that are on sale by sellers as candidates to bepurchased. The agent evaluates every candidate products using
an index of degree of satisfaction described later. Each agent
transmits the evaluated results to a matching-server as apreference list of its user. The matching-server matches a buyer
and a seller based on this preference list using Gale-Shapley
method [2] and notifies every matched users via their agents.
Thereby, a buyer can purchase a used product from anappropriate seller.
Degree of satisfaction: A buyer's agent calculates hedegree of satisfaction using a formula (1) on a home applianceowned by a seller. It is assumed that a buyer’s satisfaction isdetermined by the following four elements; 1) the distance tothe seller, 2) the difference between the price of candidate
product and the price the buyer wishes (shown as X in theformula), 3) the difference between the specification ofcandidate product and the specification the buyer wishes(shown as Y), and 4) residual life of candidate product.

(1)

3. Simulation of the proposed scheme based on user’s
satisfaction
We performed a simulation on the reuse of refrigerators
based on this scheme [3]. In the simulation, each user has arefrigerator and resides at an intersection of roads composing agrid pattern. The result reveals a positive effect when thematching is made with the proposed method and when the
distance is considered in calculating the degree of satisfaction.
4. Discussion: multiple groups for the reuse
One of the problems of the proposed method is that a single
matching server is assumed for all the users, which requires
enormous capacity of the server and may cause a matching ofusers with low satisfaction in, for example, distance. Instead, itwould be practical to divide users in multiple groups, for eachof which a matching server is provided. For this purpose, we
consider a new function is required for part agent that enables
part agents to create an appropriate group by themselves andany part agent to take the role of matching server.
Taking the distance as an example, we are developing amethod for part agents to create multiple groups autonomously.
If we assume that distances among agents in a group must be
less than a predefined value, a part agent decides by itself
whether it joins a neighboring existing group based on the
maximum distance.
5. Conclusion
We developed a function of the part agent who chooses areuse partner in consideration of the user’s satisfaction.
Problem of the method with a single matching server isdiscussed and a new method with multiple groups of agents is
proposed. We will validate the proposed method by conducting
further experiments.
Other remaining issues include revision of the formula
representing user’s satisfaction and selection of matchingalgorithm.
References[1] K. Nanjo, Y. Yamamori, H. Kawaharada, H. Hiraoka,:
Part agent’s selection of action considering the life cycleof part and change of its status, The 23rd Japan Society of
Mechanical Engineers Design & Systems Division
Conference, 2309, 2013 (in Japanese).
[2] Shuichi Miyazaki, Stable Matching Problem, Information
Processing, Vol. 54, No. 10, p.1064-1071, 2013 (inJapanese).
[3] Y. Yamamori, K. Nanjo, H. Hiraoka, Reuse of Products
Considering Distance among Users and their Satisfaction,
EcoDePS, p. 131-134, 2014 (in Japanese).

�������������������������������������������������

P-058

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

198

Review of Excessive Packaging Restriction Implementation in Taiwan
Chih-Ku Chen,*1 Chin-Wei Tang,1 Ying-Hsuan Lin1 and Yen-Lin Chen1
1

Sustainable Environmental Technology and Management, Taiwan*Corresponding author: ckchen@sustainable.com.tw

1.Abstract
To reduce the packaging material consumption and theenvironmental impact of packaging waste at source, Excessive
Packaging Restriction (EPR) has been enforced by the Taiwan
Environmental Protection Administration (TEPA) since 2006 in
Taiwan. Aimed on excessive gift box packaging, the EPR
restricts the packaging volume and packaging layer of 5
designated products by numerical standards. The analyzed
result of EPR implementation shows that 26% gift box
packaging material consumption is eliminated. Moreover, theindustry voluntary packaging reduction champion is triggeredthat unlocks the innovations for more integrativeenvironmental management on product packaging via green
packaging design in Taiwan.
2.Introduction
Afterdeposit-and-refund
recycling
schemeon
post-consuming container was established in 1999, effective
reduction on packaging gift box was highly concerned andpromoted. Several product packaging surveys and public polls
were conducted. 60.9% of the public felt that excessive productpackaging was severe which may be the reason why 77.5% of
people were unwilling to pay more for excessive packaging
product. Designated products were selected to reduce gift box
packaging at source by restriction. Extensive enforcement
scope, audit procedure, examination mechanism andimplementation framework was achieved. Legal promulgation
roadshow, green design seminar and green packaging contest
were organized to encourage more business recognition andparticipation during 2004-2008.
3.Excessive Packaging Restriction Design
Gift box packaging of 5 products (pastry, cosmetic,
alcoholic, processed food and computer software disk) aredesignated to restrict in prior.
Packaging Volume Ratio (PVR), the calculation as shownin equation 1 (eq.1), and the number of packaging layer ofdesignated product packaging are regulated. The standard isharmonized and localized from related international standards.
Reporting on World Trade Organization (WTO) is proceeded to
avoid possible Non-Technical Barrier on Trade (TBT). The
standard content is shown in Figure 1.
Packaging Volume Ration�PVR� ������� �� �������������

��������� ������ �� ��������������

………Eq.1

The designated industry includes the manufacturer,
importer and seller of designated products. However, productdesigned for export, packaging for insulation or transportation
purpose, such as carrying bag, logistic cartons and packaging
requested by consumers are exempted from EPR.
4.Implementation and Results
A serial communication to designated industries anddesign association member were taken before EPR
announcement and enforcement. Necessary assistance was
deployed to support packaging redesign.
Training program on local municipalities’ auditors washeld for proper auditing.
Promotions like (1) international management information,(2)green packaging contest, (3)green packaging assessment
procedure, handbook and tool were developed (Figure 2), (4)sharing case studies, (5) encourage industry’s participation and(6) green packaging workshop were proceeded.

Figure 2. Green packaging assessment
It was estimated that 6,900 tons of packaging material
could be reduced per year, a reduction rate of 26% wasestimated.
To empower EPR implementation, the Department ofEnvironmental Protection of Taipei City Government (TDEP)
organized Packaging Reduction Declaration agreement withmajor retailers in 2006. It was required the product vendors not
to supply excessive packaging product. Total 6,893 retailer
stores were inspired to join the agreement.
Since 2010, TEPA actively encourages computer notebook
and LCD panel manufacturers to sign voluntary packaging
reduction agreement (VPRA) with TEPA. An accumulated
8,600 tons packaging material consumption elimination isachieve, as shown in Figure 3. The sources reduction from
VPRA is not focused on weight reduction, but also through theuse of eco-friendly printing and light weighting.

�� V� P� � ∑ ������ �� ���� ������� ����� � ����� �� ��������� ������………Eq.2

VP= the volume of the minimum cuboid that circumscribes the product
VuP= the Volume of the minimum cuboid that circumscribes the unit productFigure 1:EPR regulation contents

Figure3. the voluntary packaging reduction results
5.Conclusions and Recommendations
The experience of promoting EPR regulation in Taiwan
showed that restricting excessive packaging was feasible
through careful design and planning, and developing programs
that would give support and flexibility for enterprises tocomply with the law and gradually shifting to management
conformity with its supply chain members. The EPR
implementation during these past few years set the foundation
to the adoption of green package concept, in the coming years,
voluntary agreement could be further enhanced as an incentive
for the enterprises to expand collaboration.

�������������������������������������������������

P-060

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

199

International Interdependencies Analysis using
Detailed Asian International Input-Output Table
Hiroshi Yamaguchi*, Norihiro Itsubo
Tokyo City University, Japan;*Corresponding author: hirosy@tcu.ac.jp
1. Introduction
Recently, Asian countries are developing rapidly invery tight connections with each other. Therefore to
perform the material flow cost accounting in Asia, it ismost important visualizing the environmental loads for
Asian supply chains and products. To estimate theenvironmental emissions and resource consumption, inventory
databases are necessary to be developed for GHGs, air
pollutant substances and water of Asian countries by using IO(Input Output) method applicable for comprehensive and quick
estimation of environmental loads.
2. Purpose
Using Asian International Input-Output Table (AIIO)
with 76 sectors for each country1) GHG database has
been developed and used for the interdependence
analysis of products in Asia.3) Because of rather roughclassification of 76 sectors, the results can be usedmainly for screening analysis. To make a precise
analysis, detailed GHG database are necessary. Thus
detailed AIIO using each country’s Input-Output Table(IOT) are under development4,5).
3. MethodFirstly, detailed AIIO for Japan is developed.
Classification of Japan is divided into 405 sectors from76 sectors of AIIO using IOT of Japan2) by eachsectional production amount of money, while othercountries stay with 76 sections.
Inputs from Japan into other countries and outputs
from other countries into Japan are divided using
Japanese trade statistics7).
㻌㻌㻌㻺㼡㼙㼎㼑㼞㻌㼛㼒㻌㻿㼑㼏㼠㼛㼞㼟㻌㻺㼡㼙㼎㼑㼞
㻌㻌㻌㼛㼒㻌㻿㼑㼏㼠㼛㼞㼟

㻠㻜㻡

㻣㻢

㻣㻢

I ・・・・ ・I I

J・・・・・・JJ

K・・・・・・KK

I ・・・・ ・I I㼄㼄

0・・・・・・n 90・・・・・・n 90・・・・・・n 90・・・・・・n 9 0・・・・・・n 9 0・・・・・・n 9 00・・・・

㻜㻢

0・・・・・・n 00・・・・・・n 00・・・・・・n 00・・・・・・n 0 0・・・・・・n 0 0・・・・・・n 0 㻜㻜㻜㻜

1・・・・・・n 0

1・・・・・・n 0

1・・・・・・n 0

1・・・・・・n 0 1・・・・・・n 0 1・・・・・・n 0 㻝㻝㻝㻜㻌㻱㼤㼜㼛㼞㼠㼟㻌㼠㼛 㻿㼠㼍㼠㼕㼟㻙㻵㻌㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟 㻶㻌㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟 㻷㻌㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟 㻵㻌㻲㼕㼚㼍㼘㻶㻌㻲㼕㼚㼍㼘
㻷㻌㻲㼕㼚㼍㼘
㼀㼛㼠㼍㼘㻱㼤㼛㼓㼑㼚㼛㼡㼟 㼠㼕㼏㼍㼘㻿㼑㼏㼠㼛㼞㼟㻚
㻿㼑㼏㼠㼛㼞㼟㻚
㻿㼑㼏㼠㼛㼞㼟㻚
㻰㼑㼙㼙㼍㼚㼐㻚 㻰㼑㼙㼙㼍㼚㼐㻚 㻰㼑㼙㼙㼍㼚㼐㻚㻻㼡㼠㼜㼡㻯㼛㼡㼚㼠㼞㼕㼑㼟 㻱㼞㼞㼛㼞㼠
A・・・・・・AA
A・・・・・・AA
A・・・・・・AA
F・・・・・・FF F・・・・・・FF F・・・・・・FF 㻸㻸㻽㼄
J・・・・・・JJ

K・・・・・・KK㻴㻴㻭㻵㻌㻜㻜㻝

㻯㼛㼡㼠㼞㼥㻌㻵

㻠㻜㻡㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟㻿㼑㼏㼠㼛㼞㼟

・・㻌㻌㻌㻌㻌㻌㻌 㻭㻵㻵㻌㻌㻌㻌㻌㻌㻌 㻭㻵㻶㻌㻌㻌㻌㻌㻌㻌 㻭㻵㻷㻌㻌㻌㻌㻌㻌㻌 㻲㻵㻵㻌㻌㻌㻌㻌㻌㻌 㻲㻵㻶㻌㻌㻌㻌㻌㻌㻌 㻲㻵㻷㻌㻌㻌㻌㻌㻌 㻌㻸㻵㻌㻌㻌㻌㻌 㻽㻵㻌㻌㻌㻌 㼄

㻵㻌㻌㻌㻌㻌㻌㻌 㻭㻶㻵㻌㻌㻌㻌㻌㻌㻌 㻭㻶㻶㻌㻌㻌㻌㻌㻌㻌 㻭㻶㻷㻌㻌㻌㻌㻌㻌㻌 㻲㻶㻵㻌㻌㻌㻌㻌㻌㻌 㻲㻶㻶㻌㻌㻌㻌㻌㻌㻌 㻲㻶㻷㻌㻌㻌㻌㻌㻌 㻌㻸㻶㻌㻌㻌㻌㻌 㻽㻶㻌㻌㻌㻌 㼄

㻶㻭㻵㻌㼚㼚㼚
㻭㻵㻌㻥㻜㻜
㻭㻵㻌㻜㻜㻝

㻯㼛㼡㼠㼞㼥㻌㻶

㻣㻢㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟㻿㼑㼏㼠㼛㼞㼟

・・㻭㻷㻌㻜㻜㻝

㻯㼛㼡㼠㼞㼥㻌㻷
㻱㼚㼐㼛㼓㼑㼚㼛㼡㼟㻿㼑㼏㼠㼛㼞㼟

・・㻌㻌㻌㻌㻌㻌㻌 㻭㻷㻵㻌㻌㻌㻌㻌㻌㻌 㻭㻷㻶㻌㻌㻌㻌㻌㻌㻌 㻭㻷㻷㻌㻌㻌㻌㻌㻌 㻌㻲㻷㻵㻌㻌㻌㻌㻌㻌 㻌㻲㻷㻶㻌㻌㻌㻌㻌 㻌㻌㻲㻷㻷㻶㻌㻌㻌㻌㻌㻌 㻌㻴㻲㻷㻷㻶㻌㻌㻌㻌㻌 㻌㻌㻴㻲㻷㻷㻷㻶㻌㻌㻌㻌㻌 㻌㻌㼃㻲㻷㻶㻌㻌㻌㻌㻌 㻌㻌㻰㻲㻌㻌㻌㻌㻌㻌 㻌㻸㻷㻌㻌㻌㻌㻌 㻽㻷㻌㻌㻌㻌 㼄

㻷㻭㻷㻌㼚㼚㼚
㻭㻷㻥㻜㻜㻲㼞㼑㼕㼓㼔㼠㻘
㻵㼚㼟㼡㼞㼍㼚㼏㼑㻌㻌㻌㻌㻌㻌㻌 㻮㻭㻵㻌㻌㻌㻌㻌㻌㻌 㻌㻮㻭㻌㻌㻌㻌㻌㻌㻌 㻴㻭㻵㻌㻌㻌㻌 㻌㻌㻴㻭㻵㼙㼜㼛㼞㼠㼟㻌㼒㼞㼛㼙 ・㻵・㻻㼠㼔㼑㼞㻌㻌
㻌㻌㻌㻌㻌㻌㻌 㼃㻭㻯㼃㻌㼚㼚㼚
㻯㼛㼡㼚㼠㼞㼕㼑㼟㻌㻌㻌㻌 㻌㻌㼃㻭㻮㻲㻌㻜㻜㻝

㻶㻌㻌㻌㻌㻌㻌㻌 㻮㻭㻷㻌㻌㻌㻌㻌㻌㻌 㻴㻲㻵㻌㻌㻌㻌 㻌㻌㻴㻲㻷㻌㻌㻌㻌㻌㻌㻌 㻴㻲㻷㻵㻌㻌㻌㻌㻌 㻌㻌㻴㻲㻷㻌㻌㻌㻌㻌㻌㻌 㼃㻲㻷㻵㻌㻌㻌㻌㻌 㻌㻌㼃㻲㻷㻌㻌㻌㻌㻌㻌㻌 㻰㻲㻷㻵㻌㻌㻌㻌㻌 㻌㻌㻰㻲㻯㻴㻌㻜㻜㻝

㻵㼙㼜㼛㼞㼠㼟㻌㼒㼞㼛㼙㻌㻴㼛㼚㼓㻌㻷㼛㼚㼓・・㻶㻌㻌㻌㻌㻌㻌 㻌㻴㻭㻶㻌㻌㻌㻌㻌㻌 㻌㼃㻭㻯㻴㻌㼚㼚㼚
㻯㻴㻌㻥㻜㻜
㻯㼃㻌㻜㻜㻝
㻷㻷㻯㼃㻌㻥㻜㻜

㻯㼡㼟㼠㼛㼙㼟
㼂㼍㼘㼡㼑㻌㻭㼐㼐㼑㼐㻰㼀㻌㻌㻜㻜㻝 㻌㻌㻌㻌㻌㻌㻌 㻰㻭 㻵㼂㼂㻌㻜㻜㻝
㻵・㻌㻌㻌㻌㻌㻌㻌 㼂㻌㻌㻌㻌 㻌㻰㻭

㻶㻌㻌㻌㻌㻌㻌 㻌㻰㻭㻌㻌㻌㻌 㻌㼂

㻶㻌㻌㻌㻌㻌㻌 㻌㼂㻌㻌㻌㻌 㻌㼄

㻶㻌㻌㻌㻌㻌㻌㻌 㼄㻷㻷㻷㼂㼂㻌㻜㻜㻠
㼂㼂㻌㻥㻜㻜

㼀㼛㼠㼍㼘㻌㻵㼚㼜㼡㼠㼄㼄㻌㻢㻜㻜

㻌㻌㻌㻌㻌㻌㻌 㼄

Figure1

㻵Fig.2

GHG Emission Coefficient Databasefor Japan using Detailed AIIO

4. Results
The results of the GHG database developed by detailed AIIO
are shown in Fig.2
Then, using the details of indirect GHG emission
coefficient of each sectional GHG emission,interdependence of resources, products and services ofAsian countries are analyzed.
These results shows the detailed AIIO using eachcountry’s IOT will work well for developing Asian
environmental load database including GHG, water,
air polluting material and so on.
The analysis using AIIO 200511) and comparison with
3EID12) will be discussed.
Acknowledgments
This research was supported by the Environment
Research and Technology Development Fund (1E-1106)
of the Ministry of the Environment, Japan..
The authors are greatful to Dr. Hiroshi Kuwamori, Institute ofDeveloping Economy (IDE), JETRO and Mr. Ryouta Ii, Pacific
Consultants for their helpful discussionss and supports.
References㻭㻶㻌㼚㼚㼚
㻭㻶㻌㻥㻜㻜㻣㻢

IEA/OECD8,9) and EDGAR10) statistics are used for
calculating the enveloped GHG emission database 6).

㻷

Detailed Asian AIIOThe direct GHG emission coefficient derived from

[1] IDE JETRO:Asian International IO Table 2000
[2]2005 Input-Output Tables of Japan[3] H. Yamaguchi et al.: 8th Meeting of ILCAJ, C1-25 (2013)[4] H. Yamaguchi et al.: 24th Conference of PAPAIOS. (2013)[5] H. Yamaguchi et al.: 9th Meeting of ILCAJ, D3-07 (2014)[6]K. Horiguchi et al.: 7th Meeting of ICAJ, D2-03 (2012).
[7]Ministry of Finance: Trade Statistics of Japan.
[8] OECD/IEA: Energy Statistics of OECD Countries
2004-2005.
[9] OECD/IEA: Energy Statistics of non-OECD Countries
2004-2005.
[10] European Commission Joint Research Center：Emissions

Database for Global Atmospheric Research[11] IDE JETRO：Asian International Input-output Table 2005[12] K. Nansai, National Institute of Environment: 3EID2005

�������������������������������������������������

P-061

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

200

Study on framework of life cycle sustainability assessment and social life cycle assessment:
As a subject of biorefinery
Tomoko Fuchigami,*1 Xiao-Zheng Sun,2 and Yutaka Genchi2
1

The University of Tokyo, Japan; 2National Institute of Advanced Industrial Science and Technology, Japan*Corresponding author: tomoko_fuchigami@bs.s.u-tokyo.ac.jp

1. Introduction
Sustainability assessments are required for technologies,
products, and human activities to realize sustainable society.,
Standards and guidelines for sustainability assessment havebeen presented by many countries and internationalorganizations. However, the specific discussions of theassessment methodologies based on lifecycle thinking are notenough.
Biomass is a promising industrial feedstock for both
energy production and materials production because of its
renewability. However, the social impacts of a large-scaleutilization of biomass on local agriculture and food market aswell as the impacts on agricultural field and ecosystem cannot
be ignored.
The purpose of this study is to propose a framework forsustainability assessment based on lifecycle thinking through acase	  study on biomass refinery. Social impact assessment,
which is necessary for sustainability assessment, is performed
using Social Hotspot Database (SHDB) developed by New
Earth [1]. SHDB goes back to upstream and calculates work
hours by country and by sector, and indicates potential ofsocial risk which the sectors with high contributing ratio hold,according to the Input Data given in amount of money. The
SHDB assessment on biorefinery process from sorghum
cultivation to phenyllactic acid production is conductedconsidering two cases of production in Vietnam or in Japan.
2. Scope of SHDB assessment and inventory data
The subjects for this assessment are a cultivation processof sorghum [2] and a fermentation process of phenyllactic acidwith glucose as a raw material [3]. Table 1 shows the inventory
data for the assessment presented by amount of dollars. The
mass data are obtained from the published literature of Shimizu
et al. (2009) and Fujita et al. (2013). The price data arecollected from catalogs and inquiries. Finally, they are all
converted to dollars data using the exchange rate. All input are
assumed to be collected from the country in which the process
is carried out. Calculations are performed using the SimaPro8
software implementing SHDB.
Table 1. Inventory data for SHDB analysis
I. Sorghum cultivation process
Input process

Material

Crops
Chemical, rubber, plastic products
Petroleum, coal productsElectricity

Grain
Fertilizer
FuelElectricity
	 Cultivation

Output process

Sugar cane, sugar beetAmount
/USD
0.039
0.15
0.093
0.00051
	 1

II. Phenyllactic acid production process
Input process

Material	  Electricity
	  Petroleum, coal products	  Chemical, rubber, plastic products	  Food products	  Water
	  Sorghum cultivation process

Electricity
Fuel
Chemicals
Medium additive
Water
Glucose	 Production

Output process
	  Food products

Amount/USD
0.096
0.00240.31
0.22
0.00033
0.15
	 1

3. Results of SHDB assessment
The sectors with a lot of work hours (WH) and potentialsocial risks are calculated when assumes that the phenyllactic
acid is produced in Japan or in Vietnam. Table 2 shows thehigher potential social risks with higher WH.
The work hours for production in Vietnam are much
longer than that for production in Japan. The social risks withhigh contribution rate for production in Japan are related tolabor rights in many cases. On the other hand, the characteristicsocial risks for production in Vietnam are risk of forced labor
and risk of HIV.
Table 2. High social risk items with high contributing ratio
I. High risk items for the production in JP

Risk that Country does not ratify ILO conventions
Risk of LLY by silicosis due to atm. Part. in occupation
Risk of LLY by asbestosis due to atm. Part. in occupation
Characterization. of Global Gender Gap
Risk that a country lacks or does not enforce Freed. Of Ass. rights
Risk that a country lacks or does not enforce the Right to Strike
Risk of Tuberculosis
Risk of excessive working time by sector
Risk of Mumps

II. High risk items for the production in VN

Risk that Country does not ratify ILO conventions
Risk of Forced Labor in Country
Characterization of People Under Threat Score
Risk of HIV
Risk of LLY by asthma due to atm. Part. in occupation
Risk of LLY by chronic obstructive pulmonary disease due to atm. Part.
Risk of LLY by airborne particulates in occupation
Risk of LLY by mesothelioma in occupation
Risk of Tuberculosis

WH

0.057
0.047
0.046
0.045
0.042
0.041
0.041
0.040
0.040

WH

2.872
2.871
2.869
2.858
2.858
2.858
2.858
2.858
2.856

With regard to the sector contribution of each risk, theprocess of phenyllactic acid production and the process ofsorghum cultivation show a large contribution ratio in the caseof production in Vietnam, however each sector shows the sameratio in the case of production in Japan.
4. Future work
It is necessary to evaluate both risks and values forsustainability assessment. The first step is to meet the risk
criteria. We will investigate the statistical data that is used toevaluate each risk in SHDB, and determine whether it issuitable as the assessment criteria or not. Then, the criteria
improvement for sustainability assessment will be conducted toapply the assessment results from SHDB.
Acknowledgments
This work was supported by the NC-CARP project of the
Ministry of Education, Culture, Sports, Science andTechnology in Japan.
References[1] SHDB(2013): Social Hotspot Database website,
http://socialhotspot. org, (Accessed 31.08.2014).
[2] Shimizu, N., Yuyama, Y., Yamaoka, M. and Nakamura,M., Technical report of the National Institute for RuralEngineering 209: 29–56, 2009.
[3] Fujita, T., Hieu D. N., Ito, T., Shengmin Z., Osada, L.,
Tateyama, S., Kaneko, T., Takaya, N., Appl. Microbiol.
Biotechnol., 97: 8887-8894, 2013.

�������������������������������������������������

P-062

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan201

Global Scale Fate Factor of Nitrogen for Aquatic Eutrophication
Using Water Circulation Model
Yuya Ono, *1 Masaharu Motoshita, 2, 3 Norihiro Itsubo1
1Tokyo City University, Japan; 2National Institute of Advanced Industrial Science and Technology, Japan; 3Technische

Universitaet Berlin, Berlin, Germany*g1293101@tcu.ac.jp

1. Introduction
Eutrophication is a serious problem by heavy consumptionof fertilizer and population increase. The Water Resource
Institute sum up an eutrophication and hypoxia influence mapthat occurred in 762 area of the world from 2000 to 2010.
Nitrogen cycle due to human activities has been pointed out asnecessary items to be managed urgently by Johan et al [1]. Fromsuch a background, public concern for eutrophication isincreasing.
Though LIME2(Life-cycle Impact assessment Method
based on Endpoint modeling 2), EDIP(Environmental
Development of Industrial Products), TRACI(The Tool for the
Reduction and Assessment of Chemical and otherenvironmental Impacts) and Recipe have been developed as
methods for assessing eutrophication in LCA, these methods
have been developed using model for one region or country. The
aim of this study is to develop eutrophication assessment factors
on a global level.
In this study eutrophication is defined as a degradation ofdissolved oxygen with nitrogen. And degradation of dissolved
oxygen relate to nitrogen fertilizer is calculated in each water
catchment area globally. It is assumed that after fertilization
related to nitrogen, nitrogen becomes nitrate and moves tocatchment area like a lakes or seas by water circulation. Water
catchment area consists of 8 regions and 66 sea area. This study
used mainly data of NOAA (Large Marine Ecosystems of theWorld) data. In this study global map is divided into a mesh sizeof 0.5 ° * 0.5 ° and simulations are performed on daily basis.
It is possible to apply consistent assessment globally by thisstudy.
2. Development of eutrophication assessment methods
This study are tried to estimate amount of dissolved oxygen
reduction per unit of nitrogen in the catchment area. Each data
are divided into a mesh size of 0.5 ° * 0.5 ° (length 360, width
720, total 259,200) using the GIS, and simulations were
performed in each day. Process of method development are
shown by below (Fig.1).
Fertilization of nitrogen fertilizer
Degradation of nitrogen
Flows out to the river
The consideration of the rejection in the river

Consideration of catchment
Reduction of the amount of dissolved oxygen

Figure.1 Process flow for method development

It was assumed that after nitrogen are applied fertilizer ineach country, nitrogen becomes nitrate nitrogen and these nitrate
nitrogen are moved catchment such as sea or lake with water
circulation. These flow are modeled in this study. Nitrate
nitrogen are estimated by using simulation results of TBNCUpdated model (Lin, et al. [2]). Amount of world nitrate nitrogenare calculated by multiplying farmland area [3] and nitrate
nitrogen. Secondly river inflow was set at 70% of the amount ofleaching, nitrogen removal rate in the river was 0.06day-1(Sugaet al [4]). Process until the water catchment area from each grid
was applied TRIP (Total river channel network). TRIP (Oki et al[5]) shows falling-sequence, falling-direction and under a streamof dates map. The amount of nitrogen that reaches to eachcatchment area are estimated by sea ID data (Large Marine
Ecosystems of the World) and lakes ID. The catchment area isdivided into 74 areas. Finally, reduction of dissolved oxygen
concentration are calculated by using the Redfield ratio.
3. Result and conclusion
Result of simulation, Patagonia coastal, Gulf of Mexico,
Bay of Bengal, Black Sea, Yellow Sea, Arabian Sea andMediterranean show large amount of nitrogen. As a common
point, farmland area and amount of nitrate nitrogen per area arelarger than other area and cover huge catchment (Fig. 2).
This study aimed development of impact assessment factor
which focus on eutrophication (characteristic factor) in global
level. Though global map are divided into grid of 259200 and
Nitrogen movement were simulated, this study reflect theregional characteristics.

Figure.2 Catchment area of the world
3. References[1] Johan RockstrÖm et al.(2009):Nature 461, 472-475[2] Bin-Le Lin, A. Sakoda, R. Shibasaki, N. Goto, and M. Suzuki(2000): Modelling a Global Biogeochemical Nitrogen Cycle
Model in Terrestrial Ecosystems, Ecological Modelling, Vol.
135, No. 1, 89-110[3] FAO, FAOSTAT, FAO web. http://faostat3.fao.org/faostatgateway/go/to/home/E Accessed 17 September 2012[4] Yoshito S, Taikan O, Shinjiro K (2004):59th Japan Societyof Civil Engineers Annual Scientific Conference Abstracts
493-494[5] Taikan O, Y. C. Sud (1998): Design of Total Runoff
Integrating Pathways (TRIP) — A Global River Channel
Network.
EarthInteract.,2,
1 – 37.
doi:
http://dx.doi.org/10.1175/10873562(1998)002<0001:DOTRIP>2.3.CO;2�������������������������������������������������

P-063

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

202

Methodology to Assess Sustainability of Biomass Utilisation in East Asia
Yuki Kudoh*1, Masayuki Sagisaka1, Sau Soon Chen2, Jessie C. Elauria3, Shabbir H. Gheewala4, Udin, Hasanudin5,Jane Romero6, Vinod K. Sharma7 and Xunpeng Shi8
1
National Institute of Advanced Industrial Science and Technology, Japan; 2SIRIM Berhad, Malaysia; 3University of thePhilippines Los Baños, Philippines; 4The Joint Graduate School of Energy and Environment, Thailand; 5University of Lampung,Indonesia; 6Asian Development Bank, Philippines; 7Indira Gandhi Institute of Development Research, India; 8National University ofSingapore, Singapore*Corresponding author: kudoh.yuki@aist.go.jp

1. Introduction
Utilisation of biomass resources both as energy andmaterials has attracted worldwide attention for its potential to
improve environment and to contribute to rural development
and employment generation. However, some potentiallynegative issues have also been recognised with the increased
demand of biomass resources and the implementation ofpolicies for the enhanced the use of biomass. These issues aremainly related to environmental or social concerns about
increased greenhouse gas (GHG) emissions, loss of diversity,
unwanted impacts on the livelihoods of local communities, andincreased food insecurity. As concerns over these issues
increase, especially as they relate to the utilisation of biomass
for energy, several initiatives on the assessment of bioenergy
sustainability have emerged in recent years [1]. These
initiatives are working to develop sustainability criteria,
indicators, certification schemes, and legislation for theprocessing bioenergy feedstock as well as the production andconsumption of bioenergy.
Although some stakeholders from East Asia are involved
in some of the bioenergy sustainability initiatives, most of
those are led by developed countries. To develop sustainability
assessment methodologies for biomass utilisation suitable for
East Asian countries that are rich in biomass resources, it isimportant to consider the feedstock availability andsocio-economic conditions in this diverse group of countries.
Given this context, an expert working group (WG) of
researchers from East Asian countries was formed in 2007 andworked towards a sustainability assessment methodology ofbiomass utilisation in East Asia until 2013 [2]. This article
introduces the indicators WG has identified to assesssustainability of biomass utilisation in East Asia.
2. The Methodology and Its Way Forward
In response to increasing needs for utilisaion of biomass
resources in East Asia and growing worldwide discussions forsustainable use of biomass, the WG aimed at proposing an
academically-sound and practically-relevant methodology toevaluate the sustainability of biomass utilisation in East Asia
from environmental, economic and social pillars. Since thetarget users of the methodology is the decision makers (notacademia or experts) in this region, the sustainability indicatorscomprising the WG methodology should be relevant andapplicable to any kinds of biomass utilisation initiatives; theWG thinks those indicators that are too scientific, complicatedand have high uncertainties should not be included.
The sustainability indicators are classified to main and sub
indicators (Figure 1). GHG emissions as environmental, total
value added (TVA) as economic and Human Development
Index (HDI) as social indicator are identified from the earlier
phase of the project and checked the relevance and theapplicability at the field studies conducted in four selected East
Asian countries. From the lessons learned from the field studies,
HDI was found to be applicable mainly at large-scaleinitiatives and employment generation and access to modern
energy were identified as more practicable indicators forassessing social impact of biomass utilisation in the local level.
In line with the latest discussions made at the other initiatives
for biomass sustainability, the WG finally added sets of sub
indicators to complement the main indicators.
The project was ended in 2013 but the methodology cancontribute to policy support on what kinds of and how biomass
should be utilized and implemented in a sustainable manner in
East Asian counties. In this context, the WG thinks it important
to assess the sustainability of biomass utilisation using the WG
methodology and share the results in East Asian counties.
Small scale initiatives
Project

Community

Large scale initiatives
ProvinceState

Country

Life cycle GHG emissions

Environment

System boundary: Direct land use change, feedstock cultivation,
feedstock collection, biomass products production(Follow internationally-accepted methodology)

Sub indicators:
Water consumption, Soil quality(but have to wait for a standardised methodology to emerge)

Total value added
Income approach

EconomicProduction approachSub indicators:
Net profit, Productivity, Net energy balanceMidpoint
indicator

SocialEmployment generation
Access to modern energy“A long and healthy life”(Improvement in health, life expectancy, etc.)“Knowledge”(Enrolment in education, improvement in adult literacy rate, etc.)“A decent standard of living”(Increase in personal income, etc.)
Endpoint
indicator

Sub indicator: HDI

Figure 1. Sustainability Indicators for Biomass Utilisation in
East Asian Context
Acknowledgments
This project was supported by Economic ResearchInstitute for ASEAN and East Asia (ERIA).
References[1] Ismail, M., et al. A Compilation of Bioenergy
Sustainability Initiatives: Update. Food and Agriculture
Organization
of
the
UN
(FAO).
http://www.fao.org/energy/befs/compilation/en/(Accessed 02.09.2014).
[2] ERIA WG on “Sustainability Assessment of Biomass
Utilisation in East Asia”. Extending the ERIA WG
Methodology for Sustainability Assessment of Biomass
Utilisation
in
East
Asian
Countries.
http://www.eria.org/publications/research_project_reports/sustainability-assessment-of-biomass-energy-utilisation-in-selected-east-asian-countries.html(Accessed
02.09.2014)�������������������������������������������������

P-064

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan203

New Version of Simple LCA Software Including a Comprehensive Inventory Database(IDEA)
Kuan Jay Bartel,*1 and Kiyotaka Tahara1
1National Institute of Advanced Industrial Science and Technology (AIST), Japan*Corresponding author: k.bartel@aist.go.jp

1. Motivation and overview
The goal of Simple LCA has been to provide an LCA
software package for use in education and small to medium
enterprises to support the further expansion of LCA use within
Japan. It provides an easy to use interface to assist non-LCA
professionals to conduct an ISO14040 based LCA project,including inventory analysis and impact assessment.
Traditionally, LCA software has been designed for trained
LCA professionals who undertake extensive studies of large
complex systems. For professionals it is important for theirsoftware to provide advanced functionality to support them intheir work. However for non-LCA professionals, and thoselearning the LCA methodology, these software packages can bedifficult to use and can be a barrier to the understanding and useof LCA.
There are now many LCA software programs and online
tools available which could be considered simple or easy to use.
For use in Japan however these tools are not appropriate as they
do not have a Japanese user interface and include limited or nobackground data, or the data included is not specific to Japaneseindustry. The first version of Simple LCA, released in 2007 [1],was available in English and Japanese releases and included
limit background data. Version 2 now provides user interfaces inboth English and Japanese in a single release and includes acomprehensive background database, version two of IDEA
(Inventory Database for Environmental Assessment), developedin Japan [2].
2. Software features
Simple LCA has the following key features:Model product and service systems using a visualsystem diagram
Undertake an LCA study of a system following the
ISO 14040 series of standards producing results for
LCI and LCIA
Updated easy to use user interface making entering ofactivity data quick and easyUser interface in English and Japanese
Version 2 of IDEA providing comprehensive
background data [2]Impact assessment methodologies including LIME2[3] and ReCiPe 2008 [4]3. System modelling
In modelling a system it has become the normal practice forthe system to be split into foreground and background activities.
Foreground activities being the activities which the LCA
practitioner has specific data for, such as production and use, andbackground data for activities which the practitioner does nothave specific data for and are used as inputs to the foreground
activities, such as electricity and materials. Simple LCA is thus
also divided into two sections: ‘Assessment’ and ‘Database’.
The ‘Assessment’ section is the main section which users will
use for entering foreground activities and calculating results
which are part of a target system. The ‘Database’ section allows
for viewing of background data, environmental flows, impact
methods and units.

4. Background database (IDEA)
The first version of Simple LCA only included 189
background activities for some of the most commonly usedmaterials and processes and only a limited number ofenvironmental flows. The included activities are a small subsetof those in AIST-LCA Version 4 (JEMAI-LCA Pro) [5].
Version 2 now includes the complete set of systemprocesses from version 2 of the IDEA database [2]. This
database includes over 3800 activities with inventory data forover 500 environmental flows. The database is very
comprehensive covering all products classified within the scopeof the Japan Standard Commodity Classification and additional
services and processing activities.
Due to the large increase in activity and environmental flow
numbers compared to the original version a completely new
database engine was used in version 2 so as to still provide thesame fast and efficient searching and selection of data.
5. LCA results
Simple LCA allows for the quick easy calculation of LCI
and LCIA results of a system. Results can be viewed for eachactivity, stage or the total system. LCIA results are calculatedusing the LIME2 [3] and ReCiPe 2008 [4] impact assessment
methodologies with characterization, mid-point, end-point andsingle index results for each activity, stage and the total system.
Results may be exported for use in Microsoft Excel.
6. Technical details
System Requirements

Microsoft Windows 7, 8, 8.1 (x86 or x64)

1 GHz or faster processor
1 GB of RAM

8 GB of available hard disk space
Software architecture
Simple LCA was developed in C# targeting theMicrosoft .Net Framework version 4.5.2
Backend database engine uses Microsoft SQL Server
2014 Express LocalDB and SQLite version 3.8.6
References[1] Bartel, K.J., et al. Development of a Simple LCA Software
Program. Proceedings of the 2nd Meeting of the Instituteof Life Cycle Assessment, Japan: 164-165, Tokyo
University, Tokyo, Japan, 2007.
[2] Tahara, K., et al. Development of comprehensive
inventory database based on process analysis. Proceedingsof the Eighth International Conference on EcoBalance,
Tokyo, Japan, 2008.
[3] Itsubo, N. and Inaba, A. LIME2 (Life Cycle Impact
Assessment Method based on Endpoint Modeling).
Maruzen, Tokyo, 2010.
[4] Goedkoop, M.J., et al. ReCiPe 2008, A life cycle impact
assessment method which comprises harmonised category
indicators at the midpoint and the endpoint level. Report 1:
Characterisation, 2009 http://www.lcia-recipe.net.
[5] AIST-LCA Ver.4. http://www.aist-riss.jp/main/modules/
product/software/nire.html (Accessed 09.09.2014)�������������������������������������������������

P-065

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

204

Land Use, an Important Midpoint Category Indicator in Agriculture:
How Should We Deal with It?
Takahiro Nakashima* and Shoko Ishikawa
NARO Agricultural Research Center, Japan*Corresponding author: tnakasim@affrc.go.jp
Increased attention has been paid to agriculture as one of thetargets to apply life cycle assessment (LCA). Midpoint
impact categories that are popular in this field includes
fossil-fuel energy demand, global warming, acidification,
eutrophication and land use [1]. In the present study, we paid
special attention to the last mentioned impact category, landuse, as unlike most of other categories that are “outputs” of acrop/product production, it is also an “input” and therefore
could be manipulated by farmers. Farmers allocate their land
to different crops in such a way that they could obtain what
they aim in their farming (e.g., maximization of profit) while
taking into consideration technical and resource constraints aswell as market conditions such as prices of crops, fuels andchemical fertilizers. To treat multi-dimensional aspects ofland use in a balanced manner, we proposed, in Ecobalance
2008, an idea of linking agricultural LCA to activity-based
economic model of farming [2, 3], with the aid of positive
mathematical programming (PMP) initially formulated by
Howitt [4]. The linkage gives us a theoretical framework to
examine impacts of changes in the technical and economic
conditions on environmental loads, thereby to quantify
trade-offs (or perhaps complementary relationships) between
economic gain and negative environmental impacts fromfarming. This line of multidisciplinary study is considered to
be of particular importance for policymakers, who need todesign and implement agricultural and environmental policies
that balance such economic gain and consequential loads
released to the environment. In addition, the employment of
PMP enables us to calibrate an economic model of farming
which is formulated by nonlinear programming (NLP) so as toexactly represent observed levels of the land area allocated toeach crop grown at the reference point where the model iscalibrated [5]. This function in static analysis allows us tocalculate the amount of environmental loads on farms or
regions, multiplying the land area allocated to each crop by the
midpoint environmental impact category indicators on areabasis, for example, the amount of CO2-equivalent greenhousegas emitted on hector basis. As reported by Nakashima [3],however, orthodox PMP does not always ensure reliable or“positive” results when it comes to comparative statics. In
PMP, the objective function of a NLP model is calibrated on
the basis of Kuhn-Tucker conditions for the NLP model and fora linear programming (LP) model, which is preparedhypothetically for the calibration of the NLP model, and then
the two types of optimum conditions derived are combined toderive equations for the calibration, which are linear inparameters to be calibrated when the NLP model is quadratic
programming (QP), the simplest and probably most frequently
employed in this field. The equations for the calibration are
indefinite as the number of the parameters to be calibrated
surpasses the number of equations [6], meaning that there are
numerous ways of representing the original land-use pattern as
the result of optimization, but that the calibrated models canyield different simulation paths in terms of both economic andenvironmental aspects. This is not necessarily welcomed bypolicy makers, who need sound basis to implement measureseffectively. Nakashima [4] has pointed out the need todevelop procedures for selecting the appropriate calibration
method in the light of comparative statics, and proposed a
simple and tractable framework to deal with the issue (butverification with empirical data remaining the subject of future
research). In the present study, we applied the proposed
framework to upland cropping systems of winter wheat, beat,bean, potato, and cabbage in Hokkaido, Japan, and investigatedthe extent to which a selection of calibration methods
influences on simulation results on land-use allocation andresultant calculation of environmental load on an area basis.
The impact category considered in the present study was global
warming, and the functional unit was one hector of land. The
LCA data was cited from the study conducted by Koga et al.
[7], while farm management data was collected from statistics
published from the Ministry of Agriculture, Forestry and
Fisheries, the regional government and related sources tocalibrate an economic model of farming. By showing
strength obtainable through the numerical application, some
implication to conduct agricultural LCA will be discussed.
Acknowledgments
This study is financed by NARO Agricultural ResearchCenter (114a0, socioeconomic evaluation of new farming
systems).
References[1] Von Blottnitz, H. Curran, M.A. A review of assessments
conducted on bio-ethanol as a transportation fuel from a net
energy, greenhouse gas, and environmental life cycle
perspective, J. Clean. Prod. 15 (2007) 607– 619.
[2] Nakashima, T. Life cycle assessment integrated into
positive mathematical programming: a conceptual model
for analyzing area-based farming policy. JARQ 44(3):301–310, 2010.
[3] Nakashima, T. Positive mathematical programming forfarm planning: review. JARQ 45(3): 251–258, 2011.
[4] Howitt, R. Positive mathematical programming. Am. J.
Agric. Econ. 77(2): 329–342, 1995.
[5] Buysse, J. Van Huylenbroeck, G. Lauwers, L. Normative,
positive and econometric mathematical programming as
tools for incorporation of multifunctionality in agricultural
policy modelling. Agric. Ecosyst. Environ. 120(1): 70–81,
2007.
[6] Paris, Q., Howitt, R.E. An analysis of ill-posed production
problems using maximum entropy. Am. J. Agric. Econ.
80(1): 124–138, 1998.
[7] Koga, N. Sawamoto, T. Tsuruta, H. Life cycle inventorybased analysis of greenhouse gas emissions from arable
land farming systems in Hokkaido, northern Japan. Soil Sci.
Plant Nutr. 52(4): 564–574.

�������������������������������������������������

P-066

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

205

Setting Method of the Evaluation Boundary from the Viewpoint ofUncertainty Management in LCA for Transport System Development
Ryoko Morimoto*, Hirokazu Kato1, Naoki Shibahara 2 and Yuki Masuda3
Nagoya University, Japan; 2Japan Environmental Management Association for Industry, Japan;
3
JR-Central Consultants Company, Japan*ryosoup@gmail.com

1. Introduction
In order to reduce the environmental load from transport
infrastructure provision, it is necessary to evaluate theenvironmental load emissions at an early stage in the projectplanning. However, the earlier an evaluation is carried out, themore it becomes necessary to use values with large
uncertainties as input data such as the predicted or estimatedvalues of demand.
This paper proposes a method of managing uncertainties
for decision making by LCA for transport system provision.
Setting the evaluation is investigated using an example fromthe viewpoint of the reducing uncertainties, and it is shown
what setting scope of evaluation boundary is desirable for
ensuring accuracy in the judgment of the relative merits ofalternatives.
2. Uncertainty Analysis Methods
A crossing removal of road and railway evaluated by theauthors boundary[1] a case study is evaluation boundary
included the construction of a railway elevated bridge(including 1 station) associated with removal of the crossing,and the necessary changes in the driving conditions for cars
after commencement of service. However, here the relationshipbetween setting the system boundary and the uncertainty in the
results is investigated. The system boundary was set in 3 stages,
and the uncertainties in the judgment results were calculated
and compared (See Figure 1). The environmental load
evaluated was CO2 only, and the life time was assumed to be
60 years.
From the result of life cycle CO2 (LC-CO2) estimation,
emissions from automobiles account for a large proportion of
the total. Therefore an uncertainty analysis was carried out for
the input data relating to automobiles.
Probability distributions obtained from previous research[2]were used as input data of road traffic volume and travelingspeed of automobiles. Using the Monte Carlo method, theeffect of uncertainties of the data on the estimation results wasanalyzed. The number of trials was 10,000.
System boundary (large)

Alternative road

System boundary (medium)
Systemboundary (small)Road in front of crossing : 500m
2.1km
Crossing
StationFigure 1. Setting the evaluation boundary
3. Results
The difference in LC-CO2 between the case with andwithout crossing removal project was represented as E. Whenthe sign of  E is positive, it means there is a reduction in
LC-CO2 due to the project.
Figure 2 shows the probability distribution of E obtained.
It is considered important to judge whether or not it is possible

to reduce CO2 (E<0) by implementing the project. Hence thereduction probability is used as an index expressing thereliability of the judgment result. Although there is not a majordifference in the variation of  E, it increases from ‘small’evaluation boundary to ‘large’ evaluation boundary. This isbecause as the evaluation boundary becomes broader more
uncertainty factors are included. As a result, the reduction
probability for the ‘large’ evaluation boundary is 74%. The
next section discusses the potential for reducing uncertainty.
If it is not possible to obtain the required reduction
probability even though the data accuracy is improved, it ispossible to deal with this by either making the decision
recognizing that the result is uncertain, or by re-examining theevaluation boundary to reduce the uncertainty. From Figure 2,
if a reduction probability of 95% is required, it is appropriate touse the ‘medium’ evaluation boundary for decision making.
However, in that case it is important to provide a comment to
the effect that the important load generating factor of induced
traffic has not been included in the estimate.
0.40

Probability density

1

Systemboundary
0.20 (small)

Reduction
probability
92%

0
0.40

(medium)

96%

0.20
0
0.40

(large)

74%

0.20

0

0
50
△E (amount of reduction) [kt-CO2/60 years]

Figure 2. Probability distribution of reduction amount E
and probability of reduction
4. Conclusion
A method managing uncertainty in LCA for transport
infrastructure provision has been constructed, and a method ofsetting the evaluation has been proposed. Consequently, it ispossible to improve the concern that it is difficult to use fordecision making because the uncertainties are large.
References[1]
Morimoto, R., Shibahara, N. and Kato, H. Life
Cycle Assessment of Road Improvement Projects
Considering Innovations in Vehicle Technology andChanges in Traffic Demand. Journal of Eastern Asia
Society for Transportation Studies 10:1189-1202, 2013.
[2]
Morimoto, R., Shibahara, N. and Kato, H.
Uncertainty Analysis of the LCA Results of Transport
Infrastructure Development by Mode. Proceedings of the10th International Conference on EcoBalance: P-112,
2012.

�������������������������������������������������

P-067

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

206

Uncertainty Analysis for Infrastructure LCA
Hirokazu KATO, 1* Yuki MASUDA,2 Naoki SHIBAHARA,3
Ryoko MORIMOTO, Koh KANAI,1
1Nagoya University, Japan; 2JR-Central Consultants Company, Japan
3 Japan Environmental Management Association for Industry*Corresponding author: kato@genv.nagoya-uac.ac.jp

1. Introduction
It is important to consider uncertainties during decision
making regarding infrastructure development. Decision makers
select better alternatives among at the stages of conception,
design, and construction. The information that can be obtained
and the options available vary depending on the stage, so it isnecessary to consider the uncertainties in accordance with therespective stages. This research analyzes a specific example intransport infrastructure development. The uncertainties in thelife cycle CO2 emission estimation results are analyzed at eachdecision making stage.
2. Analysis Method
This paper discusses the uncertainties in the inventory
analysis stage for estimating the environmental loads in the
LCA. A Monte Carlo simulation was applied to obtain thevariation of results. The number of trials was 1,000.
The following decision making stages were determined toinfrastructure development. There are concept stage, design
stage and construction stage. The uncertainties in each stage
were set and the uncertainty analysis in each stage was carriedout.
(a)Analysis of uncertainty during construction
1) Concept stage: From among the accumulated emissions
data for each transport infrastructure project, one project isselected at random.
2) Design stage: From among the basic data on materials
and equipment in the database, one type is selected at random.
Analysis is carried out for errors in the quantities of materials
and equipment and measurement of emission factors, in thesame way as for the construction stage.
3) Construction stage: Estimation is conducted by theauthors’ methods[1] based on the summation method, withreference to the LCA database.
(b)Analysis of uncertainty during service
Uncertainties were allocated to a) errors in measurementof emission factors for fuel in public transport, b) errors inemission factors for fuel for automobiles and transport volumes,
and c) errors between the relation equations and measured data.
For the errors in measurement of emission factors for fuel,the probability distribution in the emission factors data in the
database was used. For the errors in traffic volumes, thedifference between the planned values and the actual measured
values was represented as a probability distribution[2]. The
Q-V equation and the V-fuel consumption equation wereobtained from the measured data, and errors between measured
data were represented by applying a probability distribution
based on the variance in the parameters.
3. Results of Analysis
This paper an uncertainty in the design and construction
stages after it has been decided to develop an LRT in theconcept stage. An alternative to replace existing route bus
service by railway is examined. In addition to the public
transport system as a whole, the evaluation boundary also
included the quantity of automobile traffic on the road
alongside the LRT, with reference to Morimoto et al[2]. The
life time was set to 60 years for infrastructure and 20 years forvehicles.
The results of the uncertainty analysis for the design stage
is that reduction probability of the life cycle CO2 emission after
introduction of the LRT is 84.2%. (See Fig. 1)
If it is not possible to obtain a sufficient probability of
reduction, it is necessary to take further measures. This paper
considers the more reduction probability in the construction
stage by selection of construction materials and construction
methods with low emissions. Fig. 2 shows the results of theuncertainty analysis during construction for the design andconstruction stages. Compared with the design stage, thevariation in the construction stage is reduced, as the materials,
equipment, and construction methods are decided. Also, thetotal emissions are reduced because materials and equipment
and construction methods with low emissions are selected.

Figure 1. Results of uncertainty analysis in the design stage

Figure 2. Results of uncertainty analysis for construction ineach stage
4. Summary
By taking uncertainty into consideration, there is apossibility that the relative merits of alternative schemes could
be reversed, and that by taking appropriate measures it ispossible to reduce the possibility of a reversal.
References[1] Y.Masuda et al. The Analysis of Uncertainty Effects on
Infrastracture LCA in Environmental Intensity ofConstruction Materials (Japanese): Proceedings ofinfrastructure planning (48) CD-ROM,2013[2] Morimoto, R., Shibahara, N. and Kato, H. Uncertainty
Analysis of the LCA Results of Transport Infrastructure
Development by Mode. Proceedings of the 10th
International Conference on EcoBalanc: P-112, 2012.

�������������������������������������������������

P-068

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

207

Calculation and Comparison of Weighting Factors Based on Different Approaches in LCIA
Ryosuke Yokoi,*1 Jun Nakatani,1 Masaharu Motoshita,2 and Yuichi Moriguchi1
1

The University of Tokyo, Japan; 2 The National Institute of Advanced Industrial Science and Technology, Japan*Corresponding author: yokoi@env.t.u-tokyo.ac.jp

1. Introduction
Though weighting in life cycle impact assessment (LCIA)
is widely used in practice, it is still a controversial issue. There
are many kinds of weighting approaches and the choice of theweighting approaches influence the interpretation of the LCIA
results. Approaches for weighting can be classified into
distance-to-target (DtT), panel, and monetization approaches.
From the other viewpoint, approaches for weighting can beclassified into midpoint and endpoint approaches. There exist
previous studies that compare LCIA results based on multiple
methods including weighting phases. However those studies
have compared their weighting factors and/or calculated results
without considering the difference in weighting approaches orframeworks of LCIA methods.
The objective of this study is to calculate multiple sets ofweighting factors using different approaches based on theidentical LCIA framework, and to investigate the difference inweighting factors among the type of weighting approaches.

tive relationship between noise and endpoint categories otherthan human health have not been presented in LIME2. On theother hand, it is considered that importance of the noise issue
was more intuitively evaluated in classification of importance.
Compared with the weighting factors based on DtT
approaches, there was less difference among the weights ofimpact categories calculated based on panel approaches.

2. Methods
Weighting factors of both midpoint and endpoint impact
categories were calculated using a panel approach and a DtT
approach based on the framework of LIME2 [1].
Three types of questionnaire surveys for panel approaches
were conducted for different respondent groups including LCA
specialists and practitioners in Japan. (1) For calculation ofweighting factors of endpoints, which are called “safeguard
subjects” in the LIME2 framework, each respondent was asked
to give weights directly to four safeguard subjects of LIME2,
by following the weighting approach of Eco-indicator 99 [2].
(2) For calculation of weighting factors of midpoints in relation
to endpoints, each respondent was asked to compare theimportance of midpoint impact categories of LIME2 from theviewpoint of damages on the respective safeguard subjects.
Weighting factors were calculated by combining its results withthe above-mentioned weights of the safeguard subjects. Thismethod is referred to as “paired comparison”. (3) Besides, each
respondent was asked to evaluate the importance of midpoint
impact categories into four grades without information on therelationship between midpoint and endpoint impact categories.
Weighting factors were calculated by following the weighting
approach of BEES [3]. This method is referred to as“classification of importance”.
In calculating weighting factors based on a DtT approach,target levels of respective impact categories were defined basedon the environmental standard or policy objectives of Japan.

Figure 1. Weighting factors from paired comparison

3. Result and discussion
Figures 1 and 2 show the results of calculating weighting
factors for midpoints based on panel approach. The variabilityof calculated weighting factors among specialists was larger
than that among practitioners. The weighting factors frompaired comparison and classification of importance were different. This may mean the difference between the midpoint andendpoint approaches. For example, noise, as one of the midpoint impact categories of LIME2, was evaluated to be more
important by paired comparison than classification of importance. It is because noise was associated with multiple endpoint impact categories in paired comparison, though quantita-

Figure 2. Weighting factors from classification of importance
4. Conclusions
The results suggest that weighting factors can be affectedby various factors such as the choice of weighting approaches.
It was found that weighting factors obtained from the panel
approach were variable depending on the style ofquestionnaires and respondent groups. When practicing LCIA,
interpreting or using the results of LCIA, it is important tounderstand the characteristics of weighting approaches behindthe variability of weighting factors.
Acknowledgments
The authors are grateful to the members of The Institute ofLife Cycle Assessment, Japan, the study group of Life Cycle
Impact Assessment (ILCAJ), a private enterprise for answering
the questionnaire surveys.
References[1] Itsubo, N., Inaba, A. LIME2 Life cycle Impact assessment Method based on Endpoint modeling, JLCA newsletter. http://lca-forum.org/english/ (Accessed 2.09.2014)[2] Goedkoop, M., and Spriensma, R. The Eco-indicator 99.
A Damage Oriented Method for Life Cycle Assessment,
Methodology Report, Third Edition, 2001.
[3] Lippiatt, B.C. BEES4.0. Building for Environmental andEconomic Sustainability Technical Manual and User
Guide, NIST, 2007.

�������������������������������������������������

P-069

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

208

Spatial Variation of Health Damage Factors for PM2.5 on a Continent Level
Longlong Tang*1, Tatsuya Nagashima1, Kouichi Hasegawa2, Toshimasa Ohara1, Kengo Sudo3 and Norihiro Itsubo 41 National Institute for Environmental Studies, Japan; 2 Chuden CTI Co.,Ltd., Japan; 3Nagoya University, Japan; 4 Tokyo City
University, Japan*Corresponding author: tang.longlong@nies.go.jp

R4
R3

R10

R8
R5

R1

R7

R6

R2
R9

Figure 1. Boundary of 10 regions considering in this research

16

OC,BC

14

SO2

12

NOx

10
8

6
4
2
0

R1

R2

R3

R4

R5

R6

R7

R8

R9

R10

Figure 2. Damage factors of SO2, NOx, OCBC for 10 regions
100%

R10
R9
R8
R7
R6
R5
R4
R3
R2
R1

75%

50%
25%

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

OCBC
NOx
SO2

R2

R3

R4

R5

R6

R7

R8

R9

OCBC
R10 NOx
SO2

OCBC
NOx
SO2

0%

R1

2. Method and data
The damage factors express the change in disability
adjusted life years (DALYs) of the world due to change inemissions of organic carbon and black carbon (OCBC),
nitrogen oxides (NOx) and sulfur dioxide (SO2). The 10
regions’ damage factors were calculated by three steps below.
Firstly, after we divide the whole world into 10 regions(Fig. 1), the change of concentration of PM2.5 on whole world
per kg targeted pollutant emitted from one region is estimatedby dividing the difference between a base concentration and an
additional concentration due to a 20% increased emission by
the amount of pollutant emitted additionally. The non-linear
atmospheric fate model MIROC-ESM-CHEM, which includes
an aerosol component (SPRINTARS) and an atmosphericchemistry component (CHASER), was used to calculate bothof base and additional concentration of PM2.5 [3].
Secondly, increment of mortality and morbidity of theworld per unit of concentration of PM2.5 are calculated by using
concentration response functions (CRFs) which estimated by
epidemiologic studies [4]. CRFs of both mortality andmorbidity are assumed as linearity and with no threshold andregional variation.
Finally, data of population and DALY per case of
mortality and morbidity are collected to calculate DALYs as
health damage from results of the above. DALY per case of
diseases for all regions are rough estimated by data from WHO(2008) [5] and Hofstetter (1998) [6]. Based on the method
above, damage factors of SO2, NOx and OCBC for 10 regions
were estimated.

3. Results
Damage factors for NOx, SO2 and OCBC on all regions
were estimated as 0.1~3.3, 0.3~2.2 and 0.8~15.8 (10 -4
DALY/kg) respectively (Fig. 2). The difference of DFs among
10 regions can be up to 1 order of magnitude. DFs of regions ofIndia and China were biggest due to the higher exposure
population.
Influence on DFs due to considering the transboundary
effects of PM2.5 for each substance and each region was shownin figure 3. For most of regions, the share of damage occurredin the outside of the emission region for SO2 was estimated as
the biggest and the smallest for OCBC. This is because that thesecondly PM2.5 can move to a larger range of area than the caseof primary PM2.5. Especially regions of Europe, Russia andMiddle East showed large shares of damage outside emission
region around 1/4, 1/4 and 1/3. It is disclosed that the DFs will
be underestimated when the transport of PM2.5 to outside is nottaken into account in those regions. For further research toquantify regional differences, it is important to consider theregional values of CRF and DALY loss per case of disease ordeath.

(10-4) DALY/kg

1. Introduction
PM2.5 emitted in local area can move on anintercontinental or hemisphericscale.
Furthermore,concentration and long-range transportation of PM2.5 havesignificant spatial variations due to different meteorologicalconditions of the area where it emitted. However existingdamage factors on human health in life cycle assessment(LCA) are calculated for several limited regions and based on
different regional chemical transport models [1,2]. The aim of
this research is to estimate human health damage factors of
PM2.5 on 10 regions of the world by using one global chemicaltransport model.

Figure 3. Ratio of damage effect on 10 regions caused by one
source region for SO2, NOx and OCBC
References[1] Van Zelm, R. et al. Atmos Environ 42 (3): 441-453, 2008.
[2] Itsubo, N. and Inaba, A. LIME2 Life-cycle Impact
assessment Method based on Endpoint modeling. JEMAITokyo, 2010. (in Japanese)[3] Watanabe, S., et al. Geosci. Model Dev. 4: 845-872, 2011.
[4] European Commission (ed.) ExternE – Externalities ofEnergy – Methodology 2005 Update. Luxembourg, 2005.
[5] WHO (ed.) The Global Burden of Disease: 2004 Update.
Geneva, 2008.
[6] Hofstetter, P. Perspectivesin life cycle impact assessment,
A structured approach to combine models of thetechnosphere, ecosphere and valuesphere. Kluwer
Academic Publishers, 1998.

�������������������������������������������������

P-070

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan209

The role of world structural changes on CO2 emissions
Kayoko Shironitta†*, Shunsuke Okamoto†, Shigemi Kagawa††Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581 Japan*kayoko.s137@gmail.com
1. Introduction
Global territorial emissions of CO2 have been
continuously on the rise as nations pursue economic growth,
averaging a 2.2% annual increase in emissions in the decadefrom 2000 through 2010 (IPCC, 2014). The increases inemissions accompanying economic growth have been offset by
reductions in emission intensities and energy consumption. The
process of industrialization, one of the sources of economic
growth, is also known to contribute to reductions in emissions.
The shift to a service economy (i.e., the expansion of service
industries as a fraction of domestic production) strongly affects
the domestic emissions of greenhouse gases. Needless to say,these structural changes in economy are greatly swayed by thescale of a country’s imports and its import structure.
In this study, we focus on production-based CO2 emissions
from domestic industries and import-based CO2 emissions inforeign countries and analyze the effects of the changes in thefollowing seven factors: economic scale, industrial output
compositions, import scale of intermediate products, importcompositions of intermediate products, import scale of final
products, import compositions of final products, and emission
intensities on the CO2 emissions.
2. Methodology
We applied the Shapley-Sun decomposition method andthe Logarithmic Mean Divisia Index decomposition method tothe linked world input-output tables during 1995 to 2009 anddecomposed the changes in the production- and import-based
CO2 emissions of 40 countries into those seven factors. Using
the time series multiregional input–output tables, total
territorial emissions due to manufacturing in country s in year t
are expressed as follows:
Qdt  s  N eit  s  θit  s  X dt  s i 1

 e sθ stet  s   eit  s 

t



X dt

s

(1)

 , and X dt  s  are the emission

θt  s   θit  s 

where,intensity row vector showing CO2 emissions per unit of output
of industry sector i in country s in year t, the industrial
composition column vector showing the fraction of output ofindustry sector i of total production across all industries incountry s in year t, and total industrial output summed over allindustry sectors in country s in year t, respectively. N is thenumber of industrial sectors.
The annual change in total territorial emissions from year t toyear t+1 is then,Qd  s  et 1  s  θt 1  s  X dt 1  s   et  s  θt  s  X dt  s (2)which can be re-arranged asQd  s  e  s  θt  s  X dt  s   et  s  θ  s  X dt  s 

et  s  θt  s  X d  s   e  s  θ  s  X dt  s 
et  s  θ  s  X d  s   e  s  θt  s  X d  s (3)e  s  θ  s  X d  s 

The first term on the right-hand side of Eq. (3) represents
the effects of changes in CO2 emission intensities on theestimated CO2 emissions, and the second and third terms
represent the influences of changes in industrial composition

and in gross output, respectively, on CO2 emissions. The
remaining four terms are interaction terms. Using
Shapley–Sun–Dietzenbacher–Los decomposition to classify theseven terms (including the interaction terms among thetechnology effect, the industrial composition effect, and theeconomic scale effect), the following is obtained:11eθX dt  eθt X dt  eθX d
2
3
Technology effect1
1
 et θX dt  eθX dt  et θX d  eθX d
2
3
Industrial composition effect1
1+ et θt X d  eθt X dt  et θX d  eθX d
2
3
Economic scale effectQd eθt X dt 











(4)



3. Results
The results of year-to-year changes in territorial CO2
emissions in 40 countries over the 15 years from 1995 to 2009
are described using the decomposition method formulated in
the previous section. The per capita incomes defined by theWorld Bank for the 40 countries were used as standards (World
Bank, 2013) to classify the countries into three groups: thehigh-income nation group with per-inhabitant incomes$12616, the middle-income nation group with per-inhabitant
incomes $4086 and <$12616, and the low-income nationgroup with per-inhabitant incomes <$4086.
From the results, we found that the average industrial
composition effect of high-income countries during 1995 to2009 was -60 Mt CO2, whereas that of mid-income countries
including China was 81 Mt CO2. The average importcomposition effects for intermediate products and for final
products in high- income countries were 3 Mt CO2 during thestudy period respectively. Our results show that even if thechange in CO2 emissions associated with imported products is
considered, domestic structural change of high-income group
has not contributed to increasing CO2 emissions. However,when we think about the net effect which is the total of theaverage industrial composition effect and the average importcomposition effect of high-income group, the net reduction inemissions accompanying the structural changes in thehigh-income group during the study period amounted to about
9% of the entire world’s territorial CO2 emissions in 1995; thus,
they were a non-negligible factor in reductions.
References[1] IPCC (2014), Climate change 2014: Mitigation of climatechange, https://www.ipcc.ch/report/ar5/wg3/[2] Okamoto, S. (2013), Impacts of growth of a service
economy on CO2 emissions: Japan’s case, Journal of
Economic Structures, 2:8, pp.1–21.
[3] Dietzenbacher E, Los B, Stehrer R, Timmer M, de Vries
G (2013), The construction of world input–output tablesin the WIOD project, Economic Systems Research, 25:1,
pp.71–98.

�������������������������������������������������

P-071

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

210

Pedagogical Training for Environmental Education Based on Life Cycle Thinking
for Engineers
Hatsuna Tadaka,*1 Shinya Matsumoto,1 Reiko Tomaru,2 and Chiake Fukasawa2
1

Yokohama National University, Japan; 2Sanden Kankyo Mirai Zaidan, Japan*Corresponding author: tadaka-hatsuna-dj@ynu.jp

1. Introduction
Various environmental issues, such as global warming,
have attracted worldwide attention and come to be viewed as
matters of urgency. Our mass-consumption lifestyle is one
major cause of the drastic changes in our environment in recent
decades, and the move from a mass-consumption lifestyle to a
low carbon lifestyle is needed for future sustainability of theenvironment. In Japan, local governments and volunteers havebeen taking action to effect environmentally beneficial changes
in our lifestyles through a wide range of policies and measures
employed by the government. Environmental education (EE) is
recognized as an effective means to aid us to move to a low
carbon lifestyle. Therefore, many EE activities have been
implemented in Japanese schools and local communities.
However, there has been no major change in the
mass-consumption lifestyle of the Japanese as a result of thisactivity. One change needed to alter this trend will be to spreadawareness of the concept of life cycle and its relation to ourown living environments and lives. It is necessary for people tounderstand the potential environmental load of their own daily
lives from a bird’s eye view in order to consider what lifestylechanges are needed. This recognition has motivated teachersand scientists involved in LCA research activities to develop a
program and teaching materials for EE based on life cycle
thinking (LCT) [1-3]. One of the authors developed an EE
program based on LCT of a mobile phone and implemented it
in schools in Japan [4-6]. Through this activity, we found that itwas very important to increase the number of instructors in
LCT-based EE programs. We also found that it was important
to increase communication among stakeholders in theenvironment, particularly with respect to the influence of ourliving activities on the environment. In this work, therefore, we
attempted to develop a new training program for engineers inorder to deliver our EE program on a mobile phone in schools
and local communities.
2. Development of a new training program
Our EE program of a mobile phone uses three important
industrial products, plastics, semi-conductors and batteries, as ateaching subject for learning a product life cycle [6]. Students
learn about the fundamentals and life cycle of these products
and then think about their sustainable use through group
working.
Three young engineers who work in the development
section of a Japanese automotive parts supplier were selected
to be students in the new program. The three products
discussed in the mobile phone program are essential to theirwork, from development to production. This suggests that theyshould be able to understand and convey the fundamentals andlife cycle of these products and the reality of their position in
Japanese industry. Learning content and messages will be morepersuasive if they are tailored to students’ understanding byconsidering their own individual experience. There will
therefore also be differences in awareness between students
and working engineers in this regard that should be considered
for effective EE.
The new training program had four parts: a homeworkassignment on plastics, semiconductors, and/or batteries, taking
lectures of the mobile phone program with instruction materials,
pedagogical skills practice, and an actual lecture delivered by
the student in a school. The engineers first read several
designated books on at least one of the three products. Thenthey experienced the mobile phone program and its instruction
methods. After their teaching skills were checked andimproved, each of them delivered a lecture at a school.
One of the instruction materials for this new training
program is depicted in Figure 1. Materials were designed toreflect several areas of focus: 1) the aim and scope of education,
including an educational objective; 2) typical instruction
methods, such as interactive questioning and education using
the Blackboard content-sharing system; and 3) special attention
to other important items.

Figure 1. A part of the teaching materials
3. The implementation of the training program
We carried out the new training program with the three
engineers in two days in June 2012. Then, in October of thesame year, each of them conducted continuous two 50-minuteclasses on environmental matters at a Tokyo metropolitan
senior high school. After the class, a questionnaire survey was
conducted among the students and also the engineers. The
results indicated that the class had been the students’ firstopportunity to become aware of the relationships among their
daily lives, environmental issues, and industrial activities. We
also obtained positive responses from the engineers, who had
experienced communications that were unachievable in theircompany.
References[1] T. Mizuno. Development of environmental education text
taking into life cycle consideration. ILCA-J 2010,
Yokohama (Japan), 174–175, 2010.
[2] Y. Hirayama., et al. J. LCA 5(3): 367–381, 2009.
[3] T. Ando. J. LCA 5(3): 382–392, 2009.
[4] A. Narita., et al. J. LCA 5(3): 393–402, 2009.
[5] S. Matsumoto. J. LCA 5(3): 338–343, 2009.
[6] Y. Nakahara., et al. Development of teaching materials
for environmental education based on battery
technologies. Eco Balance 2010, Tokyo (Japan), 913–915,2010.

�������������������������������������������������

P-072

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan211

Eliminating mottainai product features for our sustainable society
Masatsugu Kitamura,* Hidetaka Hayashi
EcoDesign Promotion Network(NPO), Tokyo, Japan*Corresponding author: m.kitamura@ecodenet.com
1.Introduction
This is a study report on elimination of components ofproducts to reduce and to find limit of resource consumption
toward sustainable society. Eliminating any unwanted or out ofuse functions in mass products, that is eliminating mottainai
shapes, is the most concerned scheme for this objective, prior
to the 3R schemes. And it is useful to describe such elimination
oriented market of mass products in our Sustainable Society innear future. All the nodes on industrial supply chain are in
combination directly to the objective that fulfills people’s
desires while sustaining resources by means of restriction of
resource consumption.
It is important for the industry to reach rapidly to our
Sustainable Society while respecting updated analysis on
global warming and also for conquering resource shortages.
And also to find strong high potential engine node in theindustry, to make cooperation among nodes on industrial
supply chain ,community having limited system of power supply. Smartpower system of each home will be a member of community
power cloud system that can eliminate redundancy of batteries
in homes.
A study of music source on the web case, the scorecharacteristics of access of each source shows decaying patternalong with its preferred rate, and also data volume of eachsource clearly restricted within updated digital format. Then
whole amount of traffic and storage will be shrank into small
cloud.

2. Views from Consumer
To promote the scheme there are cases of optimism thatpeople’s good sense of mottainai shows strong effect to drasticchanging of mass products such as lamps of Incandescent toCompact Fluorescent and cars of Fuel only to Hybrid [1]. And
consumers also show their good eco-citizenship to reduce
electricity and food when confronting big accident as in
Fukushima. While housekeepers may think first their budget
when to purchase necessities in their homes, but they haveshown further.

6. Promotion of EcoDesign Industry
A scheme of division and integration for common use
functions and custom oriented functions with a new electro andmechanical interface, built in a package, welcome to be
standardized, rather than as PC peripherals via cable interfaces.
Prioritization of functions from Resource Performance Ratio(RPR) view, enables selection of a set of common use
functions showing high RPR. .
RIRS-chain serves to transfer resources which are given
specific potential value of a layer such as material, parts orassembly along with value added integration with Reciprocal
Manufacturing Robots, avoiding loss of total added values in a
Printed Circuit board (PC-board) by recycling for a small
partial damage.

3.Views from Industry
People could get their expected functions with ease but
together with of no use functions carried both by hardware andsoftware. Because recent mass producing industry, designs
were done directly to consumer’s desires which are allowing
resource consumption with ease. Resource Performance Ratio[2] will show low figures when there are no-need functions
included.
It is required a common interface for each customer inorder easy to select and mount a set of devices to be used andto dismount out of use devices. And industrial supply chain isrequired to act reciprocally with backtrack facility s Reciprocal
Industrial Resource Supply Chain (RIRS-chain) to treat devices
for each customer without applying to recycle system [3].
4.Views from society
So structuring Resource Community is shown logicallyand also mentally effective to the sustainability, during bothsupplying and using mass products.
Smart power system comprises solution of greatly
reducing electric power generating capacity in contrived

5. Limiting resource consumption
Consumers’ desire seem to require resources infinitely but
most needs of products show saturation along with their
popularization followed by their replacement needs, so it isuseful to define selected minimal profile for most preferredfunctions particularly in saturated state after market risingphase . Then the resource consumption will be minimized.

7.Summary - invention and innovation
To act on mind of avoiding mottainai lifestyle is necessary
for us to sustain society with reusable reasonable lightweight
products which will limit resource consumption. And to live on
inventions mproving mottainai method of production will leadinnovation upon our sustainable society.
References[1] Kitamura,M, “A CFL goes through the Border Less
Supply Chain”, JST-study internal document, Jul.2007[2] Kitamura,M.,Hayashi,H., “Resource Performance
Ratio
ofsustainable
electronics
devicedesign”,
EcoDesign2009, Sapporo,Dec. 2009.
[3] Kitamura,M.,Hayashi,H., “Reciprocal Design ofIndustrial Value Chain”, EcoDesign2011, Dec. 2011.

�������������������������������������������������

P-073

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

212

Environmental Performance of Biodiesel Productions Using Waste Cooking Oil
Shogo Eguchi†*, Shunsuke Okamoto† and Shigemi Kagawa††Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581 Japan*Corresponding author: shogoeguchi43@gmail.com
1. Introduction
Biodiesel is one of the biomass fuels for diesel engine
produced from vegetable or animal fat-based oil. Biodiesel has
the following four advantages: carbon neutrality, potential forsustainable production, positive contribution to the energy
self-sufficiency rate, and prevention of air pollution(Matsumura, 2006). The Japanese government is attempting toincrease the percentage of freight vehicles using biodiesel
among all freight vehicles in Japan to 80% by 2050 (Ministryof the Environment, 2009) and usage of biodiesel for aircraft
fuel is also being investigated. Thus, we expect biodiesel
demand to grow rapidly in the future. However, most biodiesel
plants in Japan have difficulty making a profit and need todepend on subsidies from their local governments. Therefore, itis necessary to raise the efficiency of their plant activities.
This study considers life-cycle CO2 emissions associatedwith biodiesel production and employs the DEA framework
considering two goods (biodiesel and glycerin as a by-productof the biodiesel) and one bad (CO2). From the results estimatedusing the time series database on monthly biodiesel production
during August 2010 to March 2013, we demonstrate how aparticular biodiesel plant can achieve efficient production while
reducing life-cycle CO2 emissions. In addition, we also show
how much the biodiesel plant can reduce the production cost of
biodiesel by improving its productive efficiency.
2. Methodology
We employed DEA with variable returns to scale toanalyze environmental and productive efficiency (Tone, 1993).
The DEA framework without considering life-cycle CO2
emissions can be formulated as follows:min s.t.  x z  X  s zx 0
 y z  Y  s zy 0(1)

szix i 1,2, , m   0sziy i 1,2, , n   0
 j  j 1,2, , l   0
where x z   xz,i bz  b  szb 
0(2)

szb  0(3)

where bz is the amount of life-cycle CO2 emissions associatedwith biodiesel production in the month z and b=(bj) is theemission vector representing the amount of life-cycle CO2
emissions in the month j. szb denotes the slack on life-cycle
CO2 emissions. Solving the DEA problem considering
life-cycle CO2 emissions provides efficiency scores under theenvironmental externality, ˆ .
Furthermore, we defined the following efficiency scores τand ˆ considering the endogenously determined slacks on thematerial inputs, product outputs, and life-cycle CO2 emissions(Tsutsui, 2001).

x z s zx  y z s zymnx s x  y z s zy  bz szbˆ ˆ  z z
m  n 1  

(4)
(5)

where
 1
xz  
 x1z
 1yz  
 y1z
bz 

1
x2 z

...

1 

xmz 

1
y2 z

...

1 

ynz 

1
bz

Then we define the environmental performance indicator(EPI) as follows (Tsutsui, 2001):(6)

is the input vector representing the inputof material i (i =1, 2,…,m) in month z (target month) andy z   yz,k  is the output vector representing the output of
product k (k=1, 2,…,n) in month z.

months are m  5 , n  2 , and l  32 , respectively.
We also formulated the DEA framework considering
life-cycle CO2 emissions by adding constraints (2) and (3) tothe above linear programming problem (1).

X = xij andY = ykj  denote the input matrix representing the input
amount of material i in month j (j =1, 2, …, l) and the output
matrix representing the output amount of product k in month j,  is the endogenously determined activity

respectively.    jyxweight of month j. s z and s z are the slack vectors ofmaterial inputs and product outputs, respectively (e.g., Tone,
1993). In this study, the numbers of materials, products, and

EPI is greater than 1 if and only the target activity
increases productive efficiency under the environmentalpressure.
References[1] Tone, K., 1993. Data Envelopment Analysis. JUSE Press,
Tokyo.
[2] Matsumura, M., 2006. Illustration on Biodiesel. Kogyo
Chosakai Publishing Co., Ltd.,Tokyo (in Japanese).
[3] Tsutsui, M., 2001, The analysis of the efficiency taking into
account the environmental performance of electrical industry:
application of DEA. Central Research Institute of ElectricPower Industry Report (in Japanese).
[4] Ministry of the Environment, Japan, Report on the vision of
reducing
greenhousegasemissions,2009,/http://www.env.go.jp/earth/info/80vision/vision.pdfS (accessed
23.04.14) (in Japanese).

�������������������������������������������������

P-074

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

213

Life cycle CO2 emission of wind energy at optimum locations in the world
Kotaro Kawajiri*1
1

National Institute of Advanced Industrial Science and Technology, Japan;*Corresponding author: kotaro-kawajiri@aist.go.jp

1. Introduction
Renewable energies are expected as the important energy
sources because the risks of global warming and resource
exhaustion, improvement of efficiency and their costs.
However, the one of problems of them is the energy generation
highly changes by its location. Therefore, it is important toevaluate the geological energy potential for the renewables toreduce the cost and environmental impacts per kWh. Especially,
the variance of potential would become large from global
perspective.
The potential of photovoltaic (PV) energy in the world is
clarified in the foregoing study [1]. In addition, the potential of
reducing the environmental impacts per kW nominal power of
PV by changing its global supply chain is also investigated [2].
On the other hand, wind energy is also promising
renewable energy. However, there are few studies investigating
the global wind energy potential. Archer et al clarified the windenergy potential in the world using the actual measurement
data [3]. Liu et al clarified the global wind energy potential
using the GEOS-5 data in 2006 [4].
The objective of this study is to investigate the windenergy potential in the world using the NASA weather datafrom 2000 to 2010. Also, the method to estimate the windenergy potential using the data is proposed. Finally, the results
are compared with those by the foregoing studies.
2. Method
The CO2 emissions per kWh of wind energy cw and CO2
payback time CPT at each location in the world are theobjective variables of this study. The analytical method andassumptions are shown as follows.
Firstly, the annual wind energy potential E [MWh/MW] ateach location is estimated using the NASA weather database[5] and the method of foregoing study [3]. According to theirwork, we assumed the capacity of wind power plant is 1.5 MW
and its hub height is 80m according [3]. The life time tL is 20
years, which is usually employed in the foregoing studies.
Since the estimation of embodied CO2 emissions of windturbine is not the scope of this study, we employed the CO2
emission of wind power plant Cm [kg] from the foregoingstudies. Reviewing the LCA studies of wind turbine, the CO2
emissions of wind turbine vary because of the size of plant andits site condition (on shore or off shore) [6-8]. Here, we
adopted nearly 400 t CO2 emissions per MW are assumed forthe 1.5 MW wind power plant [8].
The CO2 emissions per kWh in the grid ce are estimatedusing AIST-LCA ver.5 and IEA data [9-11].
The CO2 emissions per kWh of wind energy and the CO2
payback time is estimated as the following equation.

cw 

Cm
Et L

(1)

Cm
ce E

(2)

CPT 

3. Result
The wind energy potential in the world is estimated using
the analytical method by foregoing studies and NASA databaseas shown in the method section. The variance of wind energy
potential in the world is quite large. There are large potentials
in the central region in US, the central and south regions in thesouthern America, the Midwest in China, and some regions in
Europe.
On the other hand, the suitable locations to reduce the CO2
emissions are different from those to increase the wind energy
because the CO2 emissions per kWh in the grid also changes by
the country. Considering the CO2 emissions per kWh in thegrid, the suitable locations are Mongolia, Midwest China,
Kazakhstan, Australia, and so on because of their large CO2
emissions per kWh in the grid. The countries with large CO2
emissions per kWh depend on the coal fired power plant.
The CO2 payback time is a few months in the locations
with large potential of wind energy and large CO2 emissions
per kWh in the grid. Compared with the results in the foregoingstudy [2], the CO2 payback time of wind energy is relatively
smaller than that of PV at the optimum locations for the bothrenewables.
4. Conclusion
In this study, we investigated the wind energy potential ateach location in the world using the analytical method of theforegoing study and the NASA weather database. Also, weestimated the CO2 emissions per kWh and CO2 payback time
considering the embodied CO2 emissions of wind turbine andCO2 emissions per kWh in the grid. We found that the suitablelocations to reduce CO2 emissions by wind energy are different
from those to generate wind energy itself because of the CO2
emissions per kWh in the grid. Therefore, it is important toconsider the CO2 emissions per kWh in the grid to reduce theCO2 emissions by wind energy. Finally, we found that the CO2
payback time of wind energy is relatively smaller than that of
PV at the most suitable locations for the both renewables.
References[1] Kawajiri, K., et al. Environ. Sci. Technol, 45; 9030-9035,
2011.
[2] Kawajiri, K., and Genchi, Y. Environ. Sci. Technol., 46(13): 7415–7421, 2012.
[3] Archer, C. L., and Jacobson, M. Z. J. GeophysicalResearch, 110, D12110, 2005.
[4] Lu, X.et al. PNAS 106 (27),;10933-10938. 2006.
[5] NASA: “Surface meteorology and Solar Energy”,
http://eosweb.larc.nasa.gov/sse/.
[6] Tremeac, B., and Meunier, F. Renewable and Sustainable
Energy Reviews, 13: 2104-2110, 2009.
[7] Martinez. E. et al. Int. J. Life Cycle Assessment, 14;
52-63. 2009.
[8] Ecoinvent 2.0, Swiss Centre for Life Cycle Inventories.
[9] National Institute of Advanced Industrial Science andTechnology, AIST-LCA ver.5, Japan.
[10] IEA, Energy Balances of OECD Countries 2005-2006,
Paris, France; IEA, 2008.
[11] IEA, Energy Balances of Non-OECD Countries
2005-2006, Paris, France; IEA, 2008.

�������������������������������������������������

P-075

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

214

Life Cycle Environmental Impacts of Electricity from Renewable Resources in Turkey
Burcin Atilgan1* and Adisa Azapagic1
1
The University of Manchester, UK*Corresponding author: burcin.atilgan@postgrad.manchester.ac.uk(ADP elements and fossil), acidification potential (AP),eutrophication potential (EP), fresh water aquatic ecotoxicity
potential (FAETP), global warming potential (GWP), human
toxicity potential (HTP), marine aquatic ecotoxicity potential(MAETP), ozone layer depletion potential (ODP),
photochemical ozone creation potential (POCP) and terrestrial
ecotoxicity potential (TETP).

Hydro

Plant
construction

Hydro energy

Hydropower plant
operation

Electricity

Plant
decommissioning

Wind

Turbineconstruction

Wind energy

Wind turbine
operation

Electricity

Turbinedecommissioning

Geothermal

Geothermal energy

Plant
construction
Geothermal plant
operation

Electricity

Plant
decommissioning

Figure 1. The life cycle stages of renewable electricity
There are 55 reservoir hydropower, 205 run-of-riverhydropower, 39 wind and 6 geothermal power plants in Turkey
all of which are considered in this study.
3. Results and discussion
The environmental impacts have been estimated following
the CML 2001 impact assessment method [5]. The following
eleven impacts are considered: abiotic depletion potential

Wind

Geothermal

11.6

12
11

8.8

10
9

6.8

7

6.3

6.7

8

4.9

6

2.2
0.01

1.2

1.8
2.1

0.9

0.8

2.5

3.5
0.5

1.1
0.1

0.3
0.7

0.0

0.7
0.4
0.7

1.5
0.7

0.1

0.2
0.6

1.1
0.2

0.1
0.4

0.6

0.004
0.02
0.03

0

0.5

1

2.1

2.1

4

3

4.1

5

2

2. Methodology
The LCA has been carried out following the ISO
14040/14044 guidelines [3]. GaBi v.6 [4] has been used for
LCA modelling and estimation of the impacts.
The goal of the study is to estimate the life cycle
environmental impacts of electricity generation from renewablesources in Turkey, using 2010 as the base year. Two functional
units are considered:i) generation of 1 kWh of electricity by reservoir,
run-of-river, wind and geothermal power plants; andii) annual generation of 55,379 GWh of electricity fromthese power plants in 2010.
The scope of the study is from cradle to grave, comprising
electricity generation as well as plant construction anddecommissioning (Figure 1).

Run-of-river

12.5

Reservoir
13

2.1

1. Introduction
Turkey is a developing country with a rapidly growing
economy and population. The electricity demand in Turkey has
been growing rapidly, reaching 211,208 GWh in 2010, almost
seven-fold higher than in the mid-80s. The high share of fossil
fuels in Turkey’s electricity mix (73.6%) together with theincreasing demand has led to a steady increase in greenhousegas (GHG) emissions from the sector, growing by 115%
between 1990 and 2010 [2]. It is, therefore, important that
Turkey identifies and implements sustainable energy
technologies suitable for the country, if climate change andother environmental impacts are to be curbed.
In an attempt to effect this, the government has been trying
to increase the share of renewables which in 2010 contributed
26.4% to the total electricity generation, with hydropower
being the major renewable source (24.5%) [1]. However, theirpotential to help Turkey reduce its GHG emissions and otherimpacts is currently unknown. Therefore, this is the subject of
this paper.

ADP
ADP fossil x AP [g SO2- EP x 0.01 [g FAETP [g GWP x 0.01 HTP x 0.01 MAETP [kg ODP x 0.1 POCP [mg TETP x 0.1
elements x 0.1 [MJ]eq]
PO4-eq]
DCB-eq] [kg CO2-eq] [kg DCB-eq] DCB-eq] [μg R11-eq] C2H4-eq] [kg DCB-eq]
0.01 [mg Sbeq]

Figure 2. Environmental impacts from renewableelectricity sources in Turkey, expressed per kWh
The results indicate that electricity from onshore wind is
the worst option overall, with nine out of 11 impacts higher
than for hydroelectricity options and geothermal. This is due tothe impacts from the materials used to manufacture windturbines. However, its GWP is 89% and 43% lower than forgeothermal power and run-of-river hydropower, respectively.
The GWP is similar for reservoir and wind, estimated at 7 g
CO2-eq./kWh. The AP of geothermal power is around 293
times higher than for wind power.
As the results of this study suggest, construction of thepower plant is the main contributor to the impacts. Recyclingof materials at the end of their useful time instead of landfilling
reduces the environmental impacts by up to 40%.
The annual GWP is estimated at 404 kt CO2-eq., of which
reservoir power contributes 76.8%, geothermal 10.4%,
run-of-river 7.5% and wind 5.3%.
References[1] EUAS, Annual Report 2011, Turkish Electricity
Generation Company: Ankara.
[2] TUIK, National Greenhouse Gas Inventory Report,
1990-2010, 2011, Turkish Statistical Institute: Ankara.
[3] ISO, Environmental Management - Life Cycle
Assessment - Requirements and Guidelines, 2006a&b,
International Organisation for Standardisation: Geneva,
Switzerland.
[4] PE International, GaBi v.6, 2013: Stuttgart.
[5] Guinée, J.B., et al., Life Cycle Assessment: An
Operational Guide to the ISO Standards: Part 2a, in
Ministry of Housing, Spatial Planning and Environment(VROM) and Centre of Environmental Science(CML)2001: The Netherlands.

�������������������������������������������������

P-076

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

215

Water-based life cycle assessment of power generation and supply in Thailand
Tomohiro Okadera,*1 and Shabbir H. Gheewala2, 3
1National Institute for Environmental Studies, Japan; 2King Mongkut’s University of Technology Thonburi, Thailand; 3Ministryof Education, Thailand*Corresponding author: okadera@nies.go.jp

1. Introduction
Energy demand of Thailand is rapidly increasing because
of industrialization, urbanization and increasing number oftourists [1]. Especially power consumption, where the annual
growth rate was 10% for 2010 [2], significantly increases
making sustainable power supply one of the most important
policies for the residents, industries and tourists. The Thaigovernment promotes development of renewable energy
systems such as solar, biomass and hydro power systems andimportation from foreign power suppliers as well as theexisting power generation plants [3]. With increasing energy
consumption, domestic power generation and importation has
also increased; especially the imported electricity for 2010 was
89% more than the previous year [2].
Power generation requires a lot of water, so in this study
we attempt to evaluate water for power generation and supply
in Thailand using a life cycle perspective.
2. Methodology
First we identify a life cycle inventory of the power
generation and supply systems in Thailand for 2010 based onenergy statistics [2, 4, 5]. This indicated that 574 million GJ ofelectricity is produced by thermal, hydro and other power
plants with 1,495 million GJ of fuels such as natural gas, coaland its products, petroleum products, hydro, renewable energy
and waste, geothermal, solar, wind, black liquor and residualgas. In addition, 26 million GJ of electricity is imported from
Laos and Malaysia whereas 5 million GJ is exported to Laos,
Cambodia and Malaysia.
Next we set water consumption parameters (WCPs) ofpower generation based on fuel oil, lignite, coal, natural gas,
diesel, hydro, solid biomass, biogas, solar, wind, geothermaland others, and fuel production such as coal, natural gas,petroleum products, solid biomass and biogas [6-9]. Then we
calculate the life-cycle water consumption by a bottom-up
approach, namely multiplying fuel input, power generation,
imported and exported electricity by WCPs.
Furthermore, we calculate stress-weighted water footprint,
which takes water stress characterization by nation into account[10, 11], for evaluating the environmental impact to water
ecosystems. Thailand trades electricity with Laos, Malaysia
and Cambodia, whose water stress indices 0.0252, 0.0434 and0.0893 respectively while that of Thailand is 0.534 [11].
3. Results and discussion
The results show that 415 million m3 of water is directly
consumed at the power plants while 229 million water m3 is
indirectly consumed for the fuel production.
Additionally, 140 million m3 of water is virtually imported
for power supply in Thailand whereas 4 million water m3.is
exported for foreign power supply. Thus the water footprint to
supply electricity (sum of direct water consumption ofdomestic power plants and net virtual water imports) is
estimated as 551 million m3. However, the stress-weighted
water footprint is only 222 m3 because water stress indices of
Laos and Malaysia which are the foreign power suppliers are
significantly lower than Thailand, which itself has a medium
water stress index.

Table 1. Water footprints of the power generation in Thailand
Net
Direct water
Methods
Water footprint
importconsumption
Standard
136.4
415.1
551.5
Stress1.3
221.7
223.0
weighted
With taking account of water stress, the share of net
import (2%) gets smaller than that of the standard method(24%).
4. Conclusion
This study evaluates the pressure to water ecosystems bypower generation and supply in Thailand. We found that morewater corresponding to 55% of the direct consumed water isindirectly required for the power generation. 24% of water isvirtually imported for the power supply, but the environmental
impact is not so much from a water stress perspective.
Acknowledgments
We are especially grateful to Mr. Noppasan Muensang,
Department of Energy Business, Ministry of Energy, Thailand,for his cooperation in collecting data on water resources andenergy.
References[1] Hedrick-Wong Y, Choog D. MasterCard Global Destination
Cities Index. MasterCard Worldwide Insights 2Q2013.
[2] EPPO. Energy Statistics of Thailand 2011. Bangkok2011.
[3] DEDE (Department of Altenative Energy Development andEfficiency ). Annual Report 2010 Thailand Alternative Energy
Situation. Bangkok: Department of Altenative Energy
Development and Efficiency (DEDE), Ministry of Energy,
2010.
[4] DEDE. Pcoket book 2011 Energy in Thailand. Bangkok:
Alternative Energy and Efficiency Information Center,
Department of Alternative Energy Development and Efficiency,
Ministry of Energy, 2011.
[5] EGAT (Electricity Generating Authority of Thailand ).
EGAT Annual Report 2010. Bang Kruai: Electricity Generating
Authority of Thailand (EGAT), 2010.
[6] Gleick PH. Water and energy. Annu Rev Energ Env.
1994;19:267-99.
[7] Carrillo AMR, Frei C. Water: a key resource in energy
production. Energ Policy. 2009;37(11):4303-12.
[8] Harto C, Meyers R, Williams E. Life cycle water use of
low-carbon transport fuels. Energ Policy. 2010;38(9):4933-44.
[9] Okadera T, Chontanawat J, Gheewala SH. Water footprint
for energy production and supply in Thailand. Energy. 2014(0).
[10] Ridoutt BG, Pfister S. A revised approach to water
footprinting to make transparent the impacts of consumption
and production on global freshwater scarcity. Global
Environmental Change. 2010;20(1):113-20.
[11] Pfister S, Koehler A, Hellweg S. Assessing theEnvironmental Impacts of Freshwater Consumption in LCA.
Environ Sci Technol. 2009;43(11):4098-104.

�������������������������������������������������

P-077

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan216

The Concept of Efficiency in the Context of Sustainable Energy Consumption:
Theoretical Considerations and Legacy
Harald E. Otto
Polytechnic University of Marche, Italyh.e.otto@univpm.it

1. Introduction
Work on energy analysis and energy consumption researchbegan in the 1970s in response to the energy crisis. Initialresearch concentrated mainly on improvement of the technicalproperties of equipment, and, to some extent, on behavior
aimed at increasing energy efficiency. In both areas, efforts
were directed towards the creation of change using energy
efficiency as a leading principle. Now, over the past decade,sustainability and climate change have become increasingly
important both locally and globally, and have influenced thedecision making and activities of all communities and of
humanity as a whole as we work towards a future which offers
increased harmony between human activities and the systems of
the biosphere.
The requirement for research into energy efficiency has
made it necessary to broaden the approaches that were definedby the traditional boundaries of disciplinary concepts andmodels. Multi-disciplinary and interdisciplinary concepts andapproaches are necessary not only to help us to develop better
technology but also to enable us to understand how energy isused. Thus we can envision means of change for the better
within a socio-technological and economic context.
2. Notion and conceptualization
Efficiency is a context-dependent notion. In the technicalor engineering sense, efficiency is defined as the ratio of output
to input, thus quantifying yield achieved compared to resources
used. This is different from the concept of effectiveness, which
relates to the capability of producing a desired result or
outcome (cf. [1,2]). It describes the degree to which outcomesof programs or strategies match previously set objectives. Of
particular interest to program and strategy assessment is theconcept of cost-effectiveness, which relates the input of aprogram or strategy to outcomes achieved. Hence, effectivenessis focused on the achievement of desired outcomes as such,
while cost-effectiveness considers the resources required andactually spent in achieving given objectives.
From an historical viewpoint, efficiency developed from aphilosophical concept in early modern periods to a concept
used to express specific forms of rationality. Efficiency evolved
into an important technological value supporting theconstruction of modern industrial societies and it has become
increasingly important to post-industrial societies andeconomies, especially in relation to our efforts to reduce waste
and to manage resources sustainably [3,4]. As a particulartechnical assessment, its legacy is linked to the experience ofindustrialization, while being bound to measurements ofperformance in systems and processes considering thethermodynamics of energy. Hence, efficiency is not just an
intellectual concept nor an instrumental value attached to goals,
but a value attached to systems and processes entailing theapportioning of means to ends. Here, efficiency can be seen asa measure of surmounting and controlling the means forachieving such ends, i.e. facilitating the use of the least or
desired amount of resources to achieve a predeterminedoutcome.

3. Scope and outline
However, due to its defining properties and the variety ofways in which it can be used, efficiency is not limited toapplications within contemporary engineering and technology.
It rather represents a construction which is designed to help
control and manage systems and processes, but which also
provides for an intellectual understanding that can be madepractically effective. Hence, efficiency is likely to become
increasingly instrumental in the translation and implementationof visions and efforts worldwide (cf. [5]). It has the potential totransform current unsustainable human behavior anddevelopments by reducing the steadily increasing per capita
input in consumption to levels that make human endeavorsustainable again in respect to our planet’s ecosystems. In thisfirst part of a two-part paper, several important issues
connected with efficiency are examined in relation to its
historical background and scope. The focus will be on theconcept of efficiency and its use, the metaphors developed andused, the methods of measurement, and the conditions andcontext within which it is pursued. This will provide a basis tofacilitate analysis of the current technical, social, and economic
implications of the concept of efficiency, and of any
shortcomings in the application context of sustainable energy
consumption. Such analysis will then be presented in thesecond part of this paper in [6].
4. Conclusion
Since the concept of efficiency is context-dependent, there
exists no general efficiency formula as such, because thetechniques for interpreting and measuring efficiency depend on
the model that is also the benchmark. Efforts to design ways of
optimizing the output-input relationships of processes have tocontend not only with a virtually unlimited number ofparameters, but also with the fact that those parameters are
subject to technological conditions. Moreover, they are alsosocially determined and influenced by economic pressures.
References[1] Mitcham, C. Thinking Through Technology: The Path
Between Engineering and Philosophy. Chicago, Illinois,
USA: University of Chicago Press, 1994.
[2] Feenberg, A. Transforming Technology: A Critical Theory
Revisited. New York, USA: Oxford Univrsity Press, 2002.
[3] Alexander, J.K. The Mandra of Efficiency: From
Waterwheel to Social Control. Baltimore, Maryland, USA:
Johns Hopkins University Press, 2008.
[4] Moezzi, M. and Bartiaux, F. Liberating Energy Analysis. in:Proc. of the ECEEE Summer Study on Energy Efficiency,
St-Raphaël, France, 147-154, 2007.
[5] Brewer, G. Inventing the Future: Scenarios, Imagination,
Mastery and Control. Sustainabilty Science, 2(2): 159-177,
2007.
[6] Otto, H.E. The Concept of Efficiency in the Context of
Sustainable Energy Consumption: Current Practice andShortcomings. in: Proc. of the International Conference on
EcoBalance, Tsukuba, Japan, 2014.

�������������������������������������������������

P-078

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

217

Life Cycle Energy and Environmental Assessment of Bio-CNG Utilizationfrom Cassava Starch Wastewater Treatment Plants in Thailand
Seksan Papong,1 Paritta Rotwiroon,2 Thawach Chatchupong,2 Pomthong Malakul1,3,*
1National Metal and Materials Technology Center, Thailand; 2PTT Research and Technology Institute, Thailand;
3
The Petroleum and Petrochemical College, Chulalongkorn University, Bangkok, Thailand*Corresponding author: Pomthong.m@chula.ac.th

1. Introduction
In Thailand, cassava starch extraction processes require alarge volume of water and these in turn produce a large amountof wastewater as 20 m3 of water is required per ton of starch
being produced. The cassava processing plants usually generate
two types of wastewater. The first type is generated fromwashing and peeling cassava roots in the rotary drum. The
second is generated from draining the starch sedimentation
tank which has high COD and BOD [1]. The purpose of thisstudy was to assess life cycle energy and environmental
performance of biogas from cassava starch wastewater
treatment plant as a transportation fuel.
2. Methodology
The analysis of this paper was done based on theguidelines for LCA according to ISO 14040 series [2]. LCA
modeling was complied by using SimaPro v7.3 software (PreConsultants b.v.) with the CML 2 baseline 2000 method. The
functional units for this study were set to be 1 MJ ofbiomethane gas (CBG or bio-CNG) and 1 km of vehicle driven.
Figure 1 shows the system boundary of the whole life cycle(from Well-to-Wheel) of biogas in this study which covers six
stages: digestion, purification and upgrading, compression,
distribution, refueling, and combustion.

Figure 2. NER of CBG systems.
3.2. Global warming potential (GWP)
Figure 3 shows that the overall GWP from feedstock to
combustion ranged from 175 to 194 g CO2 equivalent per 1 km
car driven, depending on the upgrading technology. When
comparing three biogas upgrading technologies, WS had theleast GHG emission.

Figure 3. GWP indicator of CBG WTW phase.
Figure 1. System boundary of this study.
The feedstock for biogas production in this study was
primarily the wastewater from cassava starch production. The
technologies for biogas production considered in this analysis
were anaerobic digestion based on UASB system and threedifferent biogas upgrading technologies including water
scrubbing (WS), pressure swing absorption (PSA), andmembrane separation (MS). For vehicle operation, only theexhaust emissions from the vehicle based on compressed
natural gas were studied. Most data were collected at actual
sites in Thailand.
3. Results and discussion
3.1 Net energy ratio (NER)
As shown in Figure 2, the NER of the CBG systems basedon WS, PSA, and MS was 4.81, 4.26, and 4.73, respectively.
The energy use in the biogas upgrading stage was the highest(42.0-48.4%) followed by anaerobic digestion (20.8-23.2%).

4. Conclusions
From the life cycle energy analysis, NER values forcassava starch wastewater were 4.81, 4.26 and 4.73 for WS,
PSA and MS, respectively. The results of the life cycle GHG
emissions show that the major environmental impacts resulted
mainly from CH4 loss in the anaerobic digestion and biogas
upgrading stage.
Acknowledgments
This research was supported by PTT PLC. The authors
would like to thank all contributors for providing data.
References[1] Chavalparit O, Ongwandee M. Clean technology fortapioca starch in Thailand. Journal of Cleaner Production
17:105-10, 2009.
[2] ISO. ISO 14040-44: environmental management - life
cycle assessment - principals and framework.
International Organization for Standardization, 2006.

�������������������������������������������������

P-081

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan218

The Concept of Efficiency in the Context of Sustainable Energy Consumption:
Current Practice and Shortcomings
Harald E. Otto
Polytechnic University of Marche, Italyh.e.otto@univpm.it

1. Introduction
Efficiency, a context-dependent notion and important
technological value, was instrumental in supporting theconstruction of modern industrial societies. It has contributed tothe successful development of new sources of power, totechnologies for converting energy into useful work, to mass
production, to scientific management, and to modern businessenterprises. Those productivity-improving technologies andwork processes, combined with efforts to foster economic
growth, have led to a steadily increasing per capita input into
the consumption of resources so that we have now reachedlevels that make human endeavor unsustainable in respect toour planet’s ecosystems. Efforts worldwide within sustainable
development place high expectations on efficiency due to its
successful legacy and its capacity to represent a construction
which is designed not only to help control and manage systems
and processes, but also to provide for an intellectual
understanding that can be made practically effective.
2. Scope and outline
Unfortunately, in the energy context, the value and role ofefficiency remain less than modest in current efforts to bringabout a behavior change towards cost-effective andenvironmental-conscious energy consumption and to accelerate
the adoption of efficient energy services along with the
production of clean renewable energy. Compelling evidence of
this situation is provided by numerous mostly disciplinary
studies and reports on what have been identified as energy
market imperfections, innovation market barriers, consumer
behavior failures, information campaign failures andknowledge problems (cf. [1,2]). The last, considering current
efforts to develop information and knowledge-oriented
technologies, economies, and social constructs, not only
deserve, but rather require, more serious attention and thoroughanalysis than is currently the case. In this second part of a twopart paper, an interdisciplinary study on energy efficiency isoffered. This study relates to investment in producing energy
services and behavior change-induced energy conservation. It
takes a life-cycle approach with a focus on informational
strategies and knowledge generation, as well as on organization.
The theoretical foundation presented in the first part of thepaper [3] is employed to analyze current technical, social, andeconomic implications and shortcomings.
3. Curent models and approaches
In traditional models and approaches, technology andbehavior are somewhat separated when they are being related toenergy-efficient machinery / equipment, and conservation ofenergy, with the latter primarily seen as actions of management,with curtailment aimed at reducing either energy usage or costsin general. Such a scenario is not structured to gain insight on
how members of society, whether they be individuals,
households or organizations, perceive energy, plan and actuallypurchase energy and energy-producing equipment, or how they
perceive energy use per se. By sub-dividing the socio-technicaland economic contexts, it is also impossible to account forexternal parameters, such as indirect energy use, geographic
location, and size of dwellings, which impact both the processof energy consumption or power generation and actual
outcomes achieved. Models and approaches that define andstudy energy efficiency employing economic concepts related
to costs, benefits, and economic agents are usually chosen due
to their analytical simplicity and usefulness in addressing
empirical problems. In particular, adjusted models taking into
account bounded rationality of people and market imperfections
helped to conceptualize so-called market barrier models.
Although these approaches are capable of partially integratingsome aspects of the technical, social, and economic dimensions,they are still quite limited when it comes to answering
questions related to understanding the perception, purchase anduse of energy (see also discussion in [4]).
4. Summary and concluding remarks
The study provides some insight into the structural andconceptual limits and shortcomings of models and approaches
in the fields of energy analysis and energy consumption
research in respect to information provision strategies andprograms. In particular, attention has been given to newly
emerging phenomena and structures related to currently
evolving information societies and to the rise of knowledge
economies in industrial nations and how this relates to thesubject of the study. Results obtained offer pointers on how tobetter integrate and connect disciplinary knowledge and thefindings of empirical studies, which remain still rather
fragmented, and how to formulate new concepts andapproaches that help to answer questions regarding theunderstanding of energy use and consumption within a sociotechnical and economic context. These are preconditions thatmust be attained in order to enable the design of better andmore effective energy efficiency measures and interventions.
They will also contribute to the advancement of knowledge andto technical as well as social innovation within the larger scopeof sustainable development.
References[1] Abrahamse, W., Steg, L., Vlek, C. and Rothengatter, T. The
Effect of Tailored Information, Goal Setting, and Tailored
Feedback on Household Energy Use, Energy-Related
Behaviors, and Behavioral Antecedents. Journal ofEnvironmental Psychology, 27(4): 265-276, 2007.
[2] Gillingham, K, Newell, R.G. and Palmer, K. Energy
Efficiency Economics and Policy. Washingthon D.C., USA:
Resources for the Future, 2009.
[3] Otto, H.E. The Concept of Efficiency in the Context of
Sustainable
EnergyConsumption:
Theoretical
Considerations and Legacy. in: Proc. of the International
Conference on EcoBalance, Tsukuba, Japan, 2014.
[4] Crosbie, T. Household Energy Studies: The Gap between
Theory and Method. Energy and Environment, 17(5): 735753, 2006.

�������������������������������������������������

P-082

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan219

Evaluating the Greenhouse Gas Emissions and the Life Cycle Cost of Thermoelectric
Generators for Passenger Automobiles
Yusuke Kishita,*1 Yuji Ohishi,1 Michinori Uwasu,1 Masashi Kuroda,1 Hiroyuki Takeda,1 and Keishiro Hara1
1

Osaka University, Japan*Corresponding author: kishita@ceids.osaka-u.ac.jp
1. Introduction
With the aim to realize a low-carbon society, athermoelectric generator (TEG) is a potential energy harvesting
technology by generating electricity from waste heat. One of
the strengths of TEGs is to retrieve electric energy from waste
heat whose temperature is as low as 200-300 degrees Celsius.
Yet, the conversion efficiency of the current thermoelectricmaterials remains low at the level of 5-10%, which makes it
difficult to diffuse TEGs in society. Much effort is thus being
devoted to improving the conversion efficiency by inventing
new thermoelectric materials. However, few studies have been
conducted to clarify to what extent TEGs can contribute torealizing a low-carbon society.
In order to clarify required performances of TEGs todiffuse them in the future, this paper assesses the life cycle CO2
emissions (LCCO2) and life cycle cost (LCC) of TEGs basedon several lifecycle scenarios. A case study of bismuth telluride(BiTe) TEGS for passenger automobiles is illustrated, where
the region of interest is Suita City, Osaka, Japan.
2. A method for life cycle evaluation of TEGs for passenger
automobiles
We evaluate lifecycle scenarios of TEGs from theviewpoints of LCCO2 and LCC by modeling each scenario as a
combination of processes. We define five types of processes,that is, (i) material production, (ii) product assembly, (iii)transportation, (iv) use, and (v) end-of-life. Notably, in the use
process, we evaluate the reductions of cost and CO2 emissions
because of gasoline savings as the effect of using TEGs.
Detailed formulae of the processes are described in our
preceding study [1]. In each of lifecycle scenarios, specificconditions surrounding individual processes are assumed, suchas usage conditions (e.g., when people use TEGs) and theperformances of TEGs (e.g., conversion efficiency).
3. Case study
We carried out a case study of installing TEGs inpassenger automobiles in Suita City, Osaka, Japan. In the casestudy, we focused on BiTe TEGs since they are suitable for theexhaust gas of passenger automobiles, whose temperature isaround 300 degrees Celsius. The evaluation boundary was set
from the material extraction to the landfill of TEGs. We
assumed that TEGs are used along with the life span ofpassenger automobiles (i.e., 12 years) and then landfilled.
We assumed two lifecycle scenarios according to theconversion efficiency of TEGs – (A) Baseline Scenario and (B)Technology Innovation Scenario. The conversion efficiency in
Scenario (A) was set at 2013 is 7.2% by assuming the current
level [2], whereas that in Scenario (B) was set at 17.7% basedon the technology roadmap in 2030 [3].
For evaluating the two scenarios, we collected as muchinventory data relevant to BiTe TEGs as possible throughliterature reviews and interviews. Also, we conducted aquestionnaire survey in collaboration with Suita City in orderto obtain detailed data on passenger automobiles in Suita City,
including the distribution of annual driving distance.
Figure 1 shows the mean LCCO2 and LCC of TEGs per

automobile. The mean LCCO2 in Scenarios A and B are -161
kgCO2 and -713 kgCO2, respectively. It is also shown that the
TEG price needs to decrease by 90% to make the LCC zero.
As described in Figure 2, the gas savings in Scenarios (A)and (B) amount to 1.9-2.3%/year and 5.4-5.5%/year of the gas
consumption of an automobile. If all the gasoline vehicles in
Suita City are equipped with TEGs, the annual gasoline savingsin the city reach 934kL/year (Scenario A) or 2,440kL/year(Scenario B). As the result, the CO2 reduction amounts to
0.07% (Scenario A) - 0.30% (Scenario B) compared to thewhole CO2 emissions of the City (1,499 thousand tCO2).
4. Summary
This paper assessed the life cycle CO2 emissions (LCCO2)
and life cycle cost (LCC) of TEGs for passenger automobiles.
Future work includes further sensitivity analysis to clarify
critical factors to the LCCO2 and LCC of TEGs.
Acknowledgments
We are grateful to Suita City of Osaka Prefecture, Japan,
for providing necessary dataset to carry out this research.
References[1] Kishita, Y., et al. Proceedings of the ASME IDETC/CIE
2014, DETC2014-34483, 2014.
[2] Kaibe, H., et al. Komatsu Technical Report 57(164):26-30, 2011.
[3] Funahashi, R. Fundamentals and Applications ofThermoelectrics - Guidepost to Green Society. Tokyo:
CMC Publishing Co., Ltd., 2011.
(A) Baseline Scenario(B) Technology Innovation Scenario(B') Drastic decrease in TEG price in (B)

0
-200
-400

When TEG price is decreased from
600,000 to 60,300 JPY/automobile

-600
-800

0

200,000

400,000

600,000

Figure 1. Mean LCCO2 and LCC of TEGs per automobile
Use(A) Baseline
Scenario(η=7.2%)(B) Technology
Innovation Scenario(η=17.7%)

Material production

Gas savings:
1.9-2.3%/year-161kgCO2

Gas savings:
5.4-5.5%/year-713kgCO2

-1200
-800
-400
0
400
Mean LCCO2 per automobile (kgCO2/automobile)

Figure 2. Breakdown of LCCO2 by scenario�������������������������������������������������

P-083

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan220

An proposal of the eco-efficiency of the Fuel Cell co-generation System of “Ene-Farm”
in consideration of the CO2 emission and metal resources depletion
Yusuke Jinno,*1 Kenji Koido,1 and Kiyoshi Dowaki1
1Tokyo University of Science, Japan*7414615@ed.tus.ac.jp

3.1 Definition of the Improved Eco-efficiency
In this study, we conducted an inventory analysis on energy
intensity and CO2 emission in use of the Embodied Energy andEmission Intensity Data for Japan Using Input-Output
Tables(3EID). In general, the validity of all inputs would be
required in this methodology. However, on the highly
confidential system like PEFC, we cannot collect all inputs so as
to analyze the environmental indexes. Thus, we need to examine
to somewhat extent this variability effect on the result. Because
the factor of energy consumption is various, and our purpose is
to find out the advantages. Also, we have to consider thecommunication index so that the end-users judge the eco-burden
and the performance to some extent. Here, for the purpose, we
defined the following environmental efficiency which wasprovided by the product performance and the eco-burden of LCCO2 emission or metal resource depletion. With respect to theenvironmental efficiency of LC-CO2 emission, we considered
the deviation on the specific data on the items which are
categorized in IO-table. We argued the following two scenarios:(1) weight saving of iron material (Scenario 1), and platinum
consumption of one tenth in comparison to the conventional unit
(Scenario 2).
Finally, we evaluated the value due to the consumptionchange of platinum and iron. Here, on the unit price of Ene-Farm,
we refferd to the date of NEDO. Also, we defined the value of
Ene-Farm from the viewpoint of metal resources consumption
as follows:
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝛼𝛼(1)
𝑅𝑅𝑅𝑅𝑅𝑅𝛼𝛼 =𝐴𝐴𝐴𝐴𝐴𝐴 × 𝑃𝑃𝑃𝑃𝛼𝛼

4. Results
The result of eco-efficiency shows in Fig.1. As a result, on
the eco-efficiency on CO2 emission basis, 4.22×10-2 to 4.81×102 MWh/kg-CO eq/kW in scenario 1 and 4.52×10-2 to 4.88×10-2
2
MWh/kg-CO2eq/kW in scenario 2 were obtained, and on thatmetal resource depletion, 31.3 MWh/kg-Sb/kW in scenario 1
and 27.3 MWh/kg-Sb/kW in scenario 2 were estimated,
respectively. We would be able to find the differences on basisof each scenario in spite of somewhat deviation.
6.0E-02

35.0

30.0

5.5E-0225.0
5.0E-02

20.0

15.0

4.5E-02

10.0
4.0E-025.0

3.5E-02referencescenario1

scenario2

0.0

Eco-efficiency(resource depletion base)[MWh/kg-Sb/kW rated

2. Analysis Condition
In this study, we targeted Ene-Farm of the co-generation
system on basis of Polymer electrolyte fuel cells (PEFC). We
basically utilized the report at Mizuho Information & ResearchInstitute, Inc as the reference specification date [1]. We defined
the system boundary including the range from mining process to
product one. Note that we ignored the eco-burden of fabricatingprocess, which is smaller in comparison to the total influence.
The direct intensities, which are corresponding to the energy
consumption for operating this system, were out of range.
Because the factor of energy consumption is various, and our
purpose is to find out the advantages of the product.

Where, α, RVjα, PEneα, AUj, and Pjα are the target periods (2015～2030), the resource value of j-material (P: platinum, F: iron)[-],the unit price of Ene-Farm in α-year [yen/unit], and the pricevalue of j-material [g/unit], respectively. Based on ourinvestigation, we assumed that the price values in 2014 were
5,010 yen/g of platinum and 320,000 yen/t of iron, and that thereserves (Dj) were 7.1×104 t of platinum and 7.9×1010 t of iron.
At the present, the annual consumptions were 445 t-platinum/yr
and 858×106 t-iron/yr, respectively. If the each resource value
corresponding to platinum or iron consumption by introducing
Ene-Farm in the future is defined as Cjα, Pjα is shown as thefollowing equision.
445(𝛼𝛼−2014)+∑𝛼𝛼 𝐶𝐶𝐶𝐶𝛼𝛼(2)
𝑃𝑃𝑃𝑃𝛼𝛼 = 𝑃𝑃𝑃𝑃2014 ⁄(1 −) 2015≤α≤2030
𝐷𝐷𝐷𝐷

Eco-efficiency(CO2 base)[MWh/kg-CO2eq/kW rated output]

1. Introduction
Recently, the household fuel cell cogeneration system
known as “End-Farm” has been promoted in Japan. However,on the technological advantages including the authorizedenvironmental effects seem to be not so many examples yet. In
the Japanese manufacturer group, as a first step, they began toestablish the inventory analysis based on the conventional LCA
methodology and propose the eco-efficiency in consideration of
the life cycle CO2 (LC-CO2) emission and metal resources
depletion. That is, they try to confirm the significance of EneFarm due to the environmental appropriateness. Based on thisactivity, we propose the improved eco-efficiency on theadvantage of technology from sustainable aspect. For theindicated indexes, we discussed about the uncertainties inemissions database and/or the validity of indexes.

Figure1. Eco-efficiency
On the result of resource value, for instance, in the platinum
case, the value would be approximately 1.93 times against thatin 2015. Based on the scenario 2, the deference would be 10.0
point in comparison to the conventional one.
5. Conclusions
We defined the eco-efficiencies on CO2 emission and metal
resource depletion and we analyzed the influences of Ene-farmpromotion on basis of some scenarios. Through our research, theindex of eco-efficiency, which we proposed, would become
extremely important.
References[1]Mizuho Information & Research Institute, Inc., the study
about life cycle assessment of the household fuel cellcogeneration system and fuel-cell car, 2008�������������������������������������������������

P-084

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

221

Cost, CO2 Emission and Energy Consumption of Bioethanol Production from a
Lignocellulosic Energy Crop, Erianthus sp. by SRB-CaCCO process
Takahiro Orikasa*1, Ken Tokuyasu2, Masakazu Ike2, Rui Zhao2, Mitsuru Gau3, Shoji Koide1, and Takeo Shiina4
1

Iwate University, Japan; 2National Food Research Institute, NARO, Japan;
Kyushu Okinawa Agricultural Research Center, NARO, Japan; 4Chiba University, Japan*Corresponding author: orikasa@iwate-u.ac.jp

3

2. Methods
The process of bioethanol production from Erianthus(Erianthus arundinaceus) by SRB-CaCCO process wasevaluated in terms of the total cost, CO2 emission, and energy
ratio. The system boundary included collection of biomass,
distribution of biomass and ethanol production process. The
LCI analyses have been done based on three scenarios (basecase, innovative case, and futuristic case) established for theprocess evaluation (Table 1).
The total CO2 emissions were calculated by multiplying
the coefficients of CO2 emissions for fossil fuel, electricity and(if any) utilities (including the bioethanol plant construction
process) by the respective values of consumption from each ofthese sources and then summing the results. The coefficients of
the CO2 emissions for fossil fuel, electricity and utilities(including direct energy use and indirect energy use) [3] and forbioethanol plant construction [4] were obtained from theliterature. The total CO2 emissions and energy consumption
were allocated to produced bioethanol and by-products(p-coumaric acid, ferulic acid and silica) by price value basis.
3. Result and discussion
The total cost of bioethanol production by SRB-CaCCO
process was estimated to be 84-128 Yens/ L-ethanol (Fig.1). A
gain on sale of by-product, such as p-coumaric acid and ferulic
acid, had an effect for reducing the total cost of bioethanol
production. The CO2 emission and energy consumption were
estimated to be 1.12-1.71 kg-CO2/ L-ethanol and 12.2-18.9MJ/
L-ethanol, respectively. The lower expected energy
consumption of by-product production process in SRB-CaCCO
could result in reduction in both the CO2 emission and theenergy consumption. These results suggested that the
SRB-CaCCO process could be an environmentally-friendly
technique for producing bioethanol from lignocellulosic
biomass.
Acknowledgments
This work was supported by a grant from the Ministry ofAgriculture, Forestry and Fisheries of Japan (Rural Biofuel

Research Project; 310, 311).
References[1] Galbe, M., and G. Zacchi. Pretreatment of lignocellulosic
materials for efficient bioethanol production, Advances inbiochemical engineering/ biotechnology 108: 41-65,
2007.
[2] Zhao, R., Yun, M.S., Shiroma R., Ike, M., Guan, D., andTokuyasu, K. Integration of a phenolic-acid recovery stepin the CaCCO process for efficient fermentable-sugar
recovery from rice straw, Bioresource Technology 148:
422-427, 2013.
[3] MOE (Ministry of Environment of Japan), The Guide
Line of Calculation Method for Green House Gas
Emission from Companies (Ver. 1.6). Tokyo, Japan: MOE,
2003 (In Japanese).
[4] Nansai, K. et al. Embodied energy and emission intensity
data for Japan using input-output tables (3EID). Ibaraki,
Japan: National Institute for Environmental Studies, 2002.
Table 1

Parameters of bioethanol production conditions

Pretreatment
Electricity of milling [kWh/kg-BM]
Heating time [h]Heating temperature [°C]
Boiler efficiency [%]Heat loss[%]
Solid content of pretreated sample [%]Biomass input [t/day]
Lime concentration [%]BaseInnovative

Futuristic

0.039
1
120
80
20
20
215
10

0.039
1
100
80
20
22.6
186
10

0.039
1
95
80
20
22.6
180
10

Saccharification and fermentation
Enzyme protain loading [mg/g-cellulose]
Protain production efficiency [kg-protein/kg-C]
Enzime production rate [g-protein/L/hr]
Enzime production time [h]Fermentation time [h]

15
0.22
0.15
168
78

15
0.22
0.15
168
78

2.5
0.24
0.3
168
60

Distillation and purification
Ethanol concentration [%]Ethanol yield [L/kg-dry]

5
0.212

5.5
0.213

5.5
0.252

Methane fermentation
Amount of waste liquid after distillation [t/day]

200

200

200

By-products
Materials
Recovery of p CA [g/kg-BM]
Recovery of FA [g/kg-BM]
Ratio of Silica [%]Electricity [kWh/kg-BM]

9.7
2.8
17.3
1.64

p CA, FA, Silica
9.7
9.7
2.8
2.8
17.3
17.3
1.64
1.64

*p CA means p -coumaric acid. FA means ferulic acid.

240

Costs [Yens/L-EtOH]

1. Introduction
The interest in bioethanol as an alternative to fossil fuel fortransportation has been increasing, and lignocellulosic biomass,
such as agricultural waste, woody biomass, and lignocellulosic
energy crops (such as Erianthus and Miscanthus), is expected
to be the new second-generation bioethanol resource [1]. The
SRB-CaCCO (Simultaneous Recovery of By-products andCalcium Capturing by Carbonation) process was recently
reported as an integrated process for phenolic acid recovery as
valuables in addition to fuel ethanol (bioethanol) production
from herbaceous feedstock [2]. In order to promote an action
for the construction of commercial bioethanol plant by
SRB-CaCCO process, the costs, CO2 emissions, and energy
ratios for bioethanol production should be evaluated. However,these have not yet been reported. In this study, cost, CO2
emission and energy consumption of bioethanol production
from Erianthus sp. were analyzed.

200

Waste management

160

Disttilation

120

Fermentation
Saccharification

80

Pretreatment

40

Feedstock

0-40

Valuable resouces

Base

Innovative

Futuristic

Methan fermentation-80

Fig.1 Breakdown of the total costs of the production ofbioethanol from rice straw�������������������������������������������������

P-086

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

222

Evaluation of Power Interchange Potential and Supply-demand Balance of Distributed
Generation in Kinki
Daisuke Fukuhara,*1 Naoki Yoshikawa, 1 Koji Amano, 1 and Koji Shimada1
1 Ritsumeikan University, Japan*Corresponding author: rv006078@ed.ritsumei.ac.jp
1. Introduction
In order to reduce the risk that depends on only thelarge-scale centralized generation, power supply by distributed
generation is attracting attention. However, the stability of the
supply-demand balance has become an issue because power
generation amount of renewable energy and power demand
have variation by district and time. When introducing a mass
renewable energy, to stabilize supply-demand balance, thecharge-discharge of the battery and power interchange arenecessary to alleviate the variation with district and time.
There are research using Geographic Information System(GIS), to evaluate the potential of new energy [1, 2], and there
are also studies of smart grid [3]. However, there is not muchresearch to evaluate the supply and demand balance and powerinterchange potential using GIS.
This study evaluated the reduction of dependence onlarge-scale centralized power generation and the stability ofsystem for charging-discharging power and power interchangeof surplus power generated by distributed generation in Kinki
region, Japan. We have estimated power generation potential
and demand of power by time period in each district by using
GIS. In addition, we evaluated the effect of the powerinterchange with supply-demand balance in consideration ofvariation with time or district.

grid power to storage to prepare for power shortage of nightand early morning from surplus power during the day or, tointerchange to urban areas where electric power is insufficientfrom the mountains in the same time.

2. Methods
In this study, in order to estimate the supply and demandbalance of power that targets the Kinki region, from weather
observations [4] and statistical data [5], we estimated theavailable supply of natural renewable energy and power
demand by using the GIS. By using the estimation results ofthe supply-demand balance, this study evaluated the local area
and Kinki whole power self-sufficiency rate, power supply
configuration ratio, the amount of power interchange, thecumulative amount of storage, and supply and efficiency.

Figure 1. Power self-sufficiency rate of the day (May)

3. Results
As shown in Figure 1, this study revealed difference ofcommon supply-demand balance through the year between themountainous area and urban area, and it became clear the
power storage and power interchange of efficacy for power
supply exceeds the demand power in the middle and summer
season. As shown in Figure 2, because the excess power by
distributed generation is large, it is possible to effectively
utilize the surplus electricity by the power interchange and thepower storage in interim period. However, power storage andpower interchange was less efficacious because power demanddoes not exceed supply throughout the day in the winter.
4. Conclusion
This study revealed that it can afford to supply power tothe residential sector as much surplus power is generated
during the day in the interim and summer period and that themore supply is required from the grid power in the earlymorning and evening.
This study also revealed that it can be increase morealternative power amount to the distributed generation from

Figure 2. Evaluation of power supply efficiency
Acknowledgments
We would like to acknowledge Nippon Life Insurance
Foundation for financial support.
References[1] Olufemi A. Omitaomu, et al. Applied Energy 96: 292-301,
August 2012[2] Wakeyama, et al. Journal of the Japan Institute of Energy
88: 58-69, 2009[3] Pertti Ja¨rventausta, et al. Annual Reviews in Control 34:
277-286, 2010[4] Japan Meteorological Business Support Center, weather
database AMeDAS, full set edition, 2011[5] Statistics Bureau, Ministry of Internal Affairs andCommunications.
Statistics
listoftables.
http://www.stat.go.jp/data/guide/download/index.htm(Accessed 18.06.2014)�������������������������������������������������

P-087

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan223

A Framework to Assess Impacts of Grid Mix Changes in Japan Using Input-Output Tables
Shunichi Hienuki,*1 Yuki Kudoh,1,2 and Hiroki Hondo1
Yokohama National University, Japan; 2 National Institute of Advanced Industrial Science and Technology, Japan*Corresponding author: hienuki-shunichi-sh@ynu.jp

1. Introduction
In the aftermath of the Great East Japan Earthquake that
occurred in March 2011, the entire energy demand and supply
system in Japan is facing its turning point. The current
Strategic Energy Plan [1] does not specify the exact power mix
in the future and some factors remains uncertain such as thecontribution of nuclear and renewables.
Since the impact associated with future grid mix is not
limited to the environment but should affect to socio-economic
aspects, a comprehensive approach that could assess thepotential impacts should help decision makers select the best
choices from the grid mix options. One of the effective toolsthat are used for this subject is the input-output (IO) table.
Using an IO table for future analysis is limited because theindustrial structure is fixed to the IO table benchmark year and
it is thus not possible to reflect any potential inter-sectortransaction changes that may arise from technological progress.
However, it is valuable in estimating the future potential
impacts that might arise from the current industrial structure
and technology level.
This study aims at establishing a framework for evaluating
the environmental and socio-economic impacts by power
generation technology using the IO table. A case study isconducted using the framework on the potential impacts ofJapan’s future grid mix scenarios.
2. Socio-Economic and Environmental Impacts Estimation
Employment generation as socio-economic impact and
GHG emissions as environmental impact is evaluated by usinga hybrid of bottom-up and IO approaches for life cycle
inventory analysis (Equations (1)–(2)).
𝐿𝐿𝐿𝐿 = 𝐿𝐿𝐿𝐿𝑑𝑑𝑑𝑑 + 𝑙𝑙𝑙𝑙̂・(𝐼𝐼𝐼𝐼 − 𝐴𝐴𝐴𝐴)−1 ・𝑓𝑓𝑓𝑓

𝐺𝐺𝐺𝐺 = 𝐺𝐺𝐺𝐺𝑑𝑑𝑑𝑑 + 𝑔𝑔𝑔𝑔�・(𝐼𝐼𝐼𝐼 − 𝐴𝐴𝐴𝐴)−1 ・𝑓𝑓𝑓𝑓

(1)
(2)

Electric energy output [TWh]

1

1,000
800

84

60
120
40
110

474

600
400

204

200

308

0

16

355
63

60
30
30
110

60
75
35
110

260

290

42

42

219

239

252

150
0
Scenario 1 Scenario 2

2012

Photovoltaic
Wind
Geothermal
Hydro
LNG
Oil
Coal
Nuclear250
Scenario 3

2030

Figure 1. Grid mix scenarios
130%
120%
110%
100%
90%
80%
70%
60%
50%
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Scenario 1: Employment

Scenario 2: Employment

Scenario 3: Employment

Scenario 1: GHG emissions

Scenario 2: GHG emissions

Scenario 3: GHG emissions

Figure 2. Employment and GHG emissions transitions
electricity supply is assumed to decrease by approximately
10% in 2030 from 2012.
The amount of power generation from three renewables
towards the future is estimated using logistic equations. Since
the scenarios assume preferential electricity supply from
nuclear and three renewables, fossil fuel powers play roles tofill the gaps between total electricity demand and supply from
nuclear and three renewables. Replacements of threerenewables and fossil fuel powers are considered according totheir durable years, whereas large-scale hydro only considers
operation stage due to its difficulty for their
newly-constructions in the current Japanese situation.

Where, 𝐿𝐿𝐿𝐿 is the direct and indirect employment, 𝐺𝐺𝐺𝐺 is the
direct and indirect GHG emissions, 𝐿𝐿𝐿𝐿𝑑𝑑𝑑𝑑 is the direct
employment, 𝐺𝐺𝐺𝐺𝑑𝑑𝑑𝑑 is the direct GHG emissions, 𝑙𝑙𝑙𝑙̂ is the
diagonal matrix of employment coefficient, 𝑔𝑔𝑔𝑔𝑔 is the diagonal
matrix of GHG emissions, 𝐼𝐼𝐼𝐼 is the unit matrix, 𝐴𝐴𝐴𝐴 is the input
coefficient matrix, 𝑓𝑓𝑓𝑓 is the final demand, 𝑙𝑙𝑙𝑙̂ is the number of
employees per unit of production, and 𝑔𝑔𝑔𝑔𝑔 is the embodied
GHG emissions per unit of production. The Japanese 2005 IO
table and GHG emissions are used for the calculation [2, 3].
In order to reflect the quality of employment generated interms of continuous and temporary jobs to the socio-economic
impact estimates, the framework considers the differences in
lead-times and durable years by power generation technology.

4. Case Study Results
Figure 2 shows employment and GHG emissions
transitions from 2012 until 2030. The employment generation
changes by +11%, -2% and -6% respectively for each scenario
in 2030 compared with 1.3 million person years in 2012. All
the scenarios show the maximum in 2027 (+20, +5 and +3%)
but will gradually balance out because of a decrease inelectricity demand. On the other hand, continuous GHG
reduction is observed in each scenario.

3. Case Study Assumptions and Scenarios
The target power generation technologies are nuclear,
three renewables (geothermal, wind and photovoltaic), fossil
fuels (coal, oil and LNG) and large-scale hydro. Four life cycle
stages of manufacturing and construction, operation andmaintenance, safe storage (for nuclear only) anddecommissioning are considered for the estimation.
Figure 1 shows the grid mix in 2012 and its futurescenarios in 2030 applied to in this case study. The total

References[1] Ministry of Economy, Trade and Industry (METI).
Strategic Energy Plan (April 2014).
[2] Ministry of International Affairs and Communications(MIC) (2011) 2005 Input-Output Tables for Japan.
[3] Nansai K, Moriguchi Y (2012) Embodied energy andemission intensity data for Japan using input–output
tables (3EID): For 2005 IO table, CGER, National
Institute for Environmental Studies, Japan.

�������������������������������������������������

P-088

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

224

Analysis of environmental loads and benefits of a bio-coke production factory:a case study in Osaka
1)

Yukari Fuchigami, 1) Keishiro Hara, 2) Takeo Kita, 1) Michinori Uwasu, 1,2) Shuji Kurimoto
1) Center for Environmental Innovation Design for Sustainability, Osaka University, Japan2) Osaka Prefecture Forest Owners Association*Corresponding author: fuchigami@ceids.osaka-u.ac.jp

1. Introduction
In Japan, due to a decrease in the demand for timber andthe availability of inexpensive foreign lumber, domestic timber
prices have been low. Currently, the domestic forestry industry
could not keep operation to sustain itself without subsidies
from the central and local governments. These subsidies are
insufficient due to the financial constraints and the budget forbasic management practices, such as pruning and thinning, islimited. As a result, the forest industry tends to ignore
environmental aspects while focusing primarily on the
profitability of operations. Moreover, though some practices,such as bio-coke production, have been promoted from theviewpoint of carbon-neutral biomass utilization, actual
environmental benefits of such practices have been hardly
understood from life cycle perspectives. Against thisbackground, it is necessary to first understand potential
environmental loads and benefits in a set of operation
processes and to develop sustainable forest management
practices that are rational, efficient, and environmentallyfriendly.
2. Research objectives and methods
In this study, we evaluated the environmental loads
associated with bio-coke production processes from woody
biomass, particularly focusing on energy consumption and CO2
emissions. We conducted a case study at Takatsuki Biomass
factory of Osaka Prefecture Forest Owners Association. Basedon interviews in the factory and field surveys, we obtained dataon electricity and fuel consumptions in the manufacturing
process along with data on the amount of products based onthese data from June 2012 to February 2014. These bio-cokes
are used as an alternative fuel for coke in an enterprise. So, we
also estimated reductions of CO2 emission by the alternativeuse.
We represented bio-coke production flow of Takatsuki
Biomass factory in Figure 1. System boundary of thispresentation is from raw material production process to using
process. The disposal and recycling processes aren’t includedin the boundary, nor are the waste water treatment of product
Process of raising raw material

Logging

Forestremainder
material

Process of manufacturing Product
Processing①

LoadingDryingGrinding

Process ofProcess ofProcess ofuse
distribution and saledisposal and recycling

Light oil
Gasoline
Mixed oil
Etc.

Input ones or products
Foreground data

Woody chip

Back ground data
Processing②
Grinding

Process boundary

Processing

System boundary
DryingPelletPressurizing

Electricity
Light oil
Kerosene
Etc.

Heating

Loading

Use

Drainage
Waste water treatment

Figure. 1

3. Result
The amount of CO2 emissions in the production andtransportation of bio-coke was 1.28t-CO2. Figure 2 shows theclassification of CO2 emissions in each step. It reveals that the
majority of the emission is due to the manufacturing process.
The largest emission source in manufacturing process waselectricity consumption.

Figure.2 Classification of CO2 emissions
in the bio-coke production
Comparing the amount of heat between bio-coke and coke,
1.7t bio-cokes is required to substitute for 1t coke. CO2
emissions from use of cokes minus CO2 emissions of the
production and transport bio-coke, it was 0.62t-CO2 / t. This is
the capable amount of reducing CO2 by an alternative use of
bio-coke.
4. Conclusion
Even taking into account the environmental impact during
production and transport, bio-coke was concluded to be theecological fuel. We argued that it is reasonable to anticipate
environmental benefit, though more and continuing utilizationis necessary by such company. In future study, we aim topropose a comprehensive model of sustainable forest
management by looking into other aspects such as cost
performances.
Acknowledgments
We are grateful to Osaka Prefecture Forest Owners
Association for their help.
References

Cooling
Bio-Cokemanufacturing process. In addition, we use the backgrounddata for the process for procurement of raw materials [1].

Life cycle flow of bio-cokeWaste
matter

[1] Tsuda, K., et al. Study on life cycle assessment of sustainablebuildings (Part 1) Inventory analysis of local woods based onfield survey. Technical papers of Architectural Institute of Japan.
[2] Ministry of the Environment Japan. The calculation methods
and emission factor list. (Accessed 20.8.2014)
http://ghg-santeikohyo.env.go.jp/files/calc/itiran.pdf.

�������������������������������������������������

P-089

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

225

Input-output analysis of introducing smart grid systems in Japan
Satoshi Nakano1 and Ayu Washizu*2
1

The Japan Institute for Labour Policy and Training, Japan; 2Waseda University, Japan*Corresponding author: washizu@waseda.jp

1. Introduction
Since the Great East Japan Earthquake, attention in Japan
has been focused on the construction of an energy system thatis more dependent on renewable energies. Construction of new
smart grid systems is indispensable to the introduction ofrenewable energies. Renewable energies are small anddistributed, and both photovoltaics (PV) and wind power
generation are variable. Consequently, mass introduction ofrenewable energies can destabilize power flow. The 2006
European blackout is thought to have been partially caused by
the broad introduction of wind power, which shows how
difficult the introduction of renewable energies can be(Yokoyama [1]). Smart grid technologies are capable of rapidly
detecting, analyzing and responding to various perturbations in
the network by integrating advanced control methods andequipment (Hidayatullah et al. [2]).
In fact, some engineers are offering alternative smart gridconfigurations. Because the grid is one of the most basic pieces
of infrastructure in a society, the decision-making should bebased on social economic considerations. This is the motivation
behind our study.
2. Alternative engineering scenarios
The Central Research Institute of Electric Power Industry(CRIEPI) report [3] looked at the effect of the mass
introduction of PV and wind power, and the assumptions madecan be seen in Table 1. It is assumed that new, efficient thermal
and pumped hydro power plants will be constructed to stabilize
power systems. Proper power control operation of thermal andpumped hydro power plants can play a positive role inelectrical power storage. Case 8b assumed that renewableenergy capacity would be the same as Case 8, but energy
generated by renewable sources in Case 8b is larger than inCase 8. Introduction of smart grids makes this possible. By
comparing these cases, we can analyze the comprehensive
effect of introducing smart grids. In comparison, METI's report[4] looked at the effect of introducing 28,000 MW of PV andconstructing a large number of batteries. It is assumed thatpower system stabilization will require the large-scale
introduction of batteries (See Table 2). Two kinds of batteries
were considered. Scenarios 4 and 5 have almost the same
conditions, but the latter assumed that interface control units
would be introduced. Interface control units are the most basic
elements of smart grid systems.
Table 1. Assumptions made in CRIEPI’s report (May 2013)
Generation of
Capacity ofPercentage ofphotovoltaics Percentage of photovoltaics
total+ wind power total capacity* + wind power Generation*MW
GWh
Case 1Case 5
Case 8
Case 8b

3,568
34,52460,41860,4184.12%
30.62%
44.51%
44.76%

4,522
37,89754,21473,7901.26%
10.16%
14.25%
20.19%*Total amount in east Japan

3.Results
As the existing Japanese input-output table doesn't include
renewable energy and smart grid activities, we constructed an
extended input-output table for the analysis of next generationenergy systems. Using this table, we calculated economic andenvironmental effects from constructing and operating thefacilities considered in the studies which provided the data in

Table 1 and Table 2. (Nakano and Washizu [5]). The results canbe seen in Table 3 and 4.
Table 2. Assumptions made in the METI report (April 2010)
PV power

Battery

Smart grid

control

Scenario 1

NaS (Largest)

No

Scenario 1'

Li-ion (Largest)

No

Scenario 2

NaS (Medium)

MediumScenario 3

NaS (Larger)

Small

Scenario 4

NaS (Small)

Large

Scenario 5

NaS (Small)

Large

Interfacecontrol unit

(NaS: Sodium-sulfur battery ，Li-ion： Lithium-ion battery )Table 3. Annual induced amount per GWh（from construction and operation of new power plants）
Service life of facilities = 20 years

32.9
33.7
37.6
47.7

EnergyCO2 emission
consumpiton（t-CO2)
（GJ）
1.2
8,288
481
1.2
8,772
561
1.4
10,313805
1.8
13,681
1,212

77.4
87.6
72.7
32.9
60.8
80.5
71.1

2.3
2.7
2.1
1.2
1.9
2.5
2.1

output（million JPY）
Case 1
thermal and Case 5
pumped hydro Case 8
Case 8bCase 1
Photovoltaics Case 5
and windCase 8power
Case 8bCase 1Case 5
Total
Case 8
Case 8blabor（person）

1,355
1,432
1,311
8,288
4,176
2,693
2,094

52
61
47
481
246
167
121

Table 4. Annual induced amount per GWh（from construction and operation of new PV）
241.43

EnergyCO2 emission
consumpiton（t-CO2)
（GJ）
9.01
4,163
223.5

265.72

11.23

4,213

114.06

2.86

1,681

80.3

147.26

4.47

2,324

117.6

100.79

2.22

1,421

65.4

99.53

2.17

1,387

63.8

Output（million JPY）

Scenario 1
Scenario 1'
Scenario 2
Scenario 3
Scenario 4
Scenario 5

Labor（person）

251.4

4. Discussions
Comparing the results of case 8 to case 8b in Table 3, andscenario 4 to scenario 5 in Table 4, we can see that the
introduction of smart grid systems has economic andenvironmental merit. Furthermore, comparing the results ofTable 3 to Table 4, we see the advantage of introducing not
only PV but also wind power, and that power systems can bestabilized through power control operation in thermal power
plants, and by operation of pumped hydro plants.
Acknowledgments
This study was supported by a Grant-in-Aid for Scientific
Research (B) (KAKENHI), 2011–2014, (No. 23310033 to Ayu
Washizu).
References[1] Yokoyama, A., IEEJ Journal, 129(5): 299-302, 2009.
[2] Hidayatullah, N.A., Stojcevski, B., Kalam, A., Smart Gridand Renewable Energy 2(3), 216-229, 2011.
[3] Yamamoto, H., Bando, S., Sugiyama, M., CRIEPI
Socio-economic Research Center Pep. No. Y10030, 2013
[4] Agency of Natural Resources and Energy (METI), The
report of next-generation electric-power-distribution
network study group, 2010.
[5] Nakano, S., Washizu, A., Proceedings of Society forenvironmental Economics and Policy Studies 2014.

�������������������������������������������������

P-090

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

226

Benefits of biogas projects from local and global perspectives
Aya HEIHO,* Hiroki HONDO, and Yue MORIIZUMIYokohama National University, Japan*Corresponding author: heiho-aya-gm@ynu.jp
1. Introduction
Many biomass projects based on local initiatives havebeen recently planned or implemented in Japan. However, few
studies have been conducted to evaluate their environmental
and socio-economic performance from a life cycle perspective.
The objective of the present study is to propose a method toassess sustainable development benefits of biomass projects
focusing on where benefits accrue.
2. Method
The method proposed consists of the following three steps:(i) definition of system boundary and functional unit, andselection of indicators, (ii) inventory analysis, (iii) evaluationof the benefits of a local biomass project.
First, the two project systems that describe the situations“before” and “after” implementing a project are defined. A
functional unit is set for the two project systems to provide thesame amount of goods and services for a year. The present
study chooses greenhouse gas (GHG) emissions, fossil fuelconsumption and employment as indicators.
Second, the values of indicators for each project system(𝐸𝐸𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 and 𝐸𝐸𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 ) are estimated using a hybrid method thatcombines both merits of process and input-output analysis froma life cycle perspective. Since the present study identifies
where the benefits of a project accrue, 𝐸𝐸𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 or 𝐸𝐸𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 arecalculated by region according to the following equation (1):𝑒𝑒
𝐸𝐸𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝐸𝐸 𝑜𝑜𝑜𝑜 𝐸𝐸
𝐸𝐸 𝑡𝑡𝑡𝑡𝑡𝑡𝑡 (1)𝐸𝐸𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏
The present study divides Japan into three regions, namely, theproject spot (i.e. the place where a biomass project is actuallydone), inside of the local area, and outside of the local area tocalculate the values of indicators for the three regions (𝐸𝐸 𝑜𝑜𝑜𝑜 ,𝑒𝑒, and 𝐸𝐸 𝑡𝑡𝑡𝑡𝑡𝑡𝑡 ). For the calculation, the present study
𝐸𝐸
uses national and regional input-output tables together withprimary data from a local government and companies andsecondary data from literature.
Finally, the benefits of the project (𝐸𝐸) are assessed bycomparing 𝐸𝐸𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 and 𝐸𝐸𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 as shown in equation (2):𝐸𝐸 𝐸 𝐸𝐸𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 − 𝐸𝐸𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏  (2)3. Case study
The method proposed is applied to assess the benefits of asmall-scale biogas project in Hokkaido, Japan. Figure 1 shows
the project system before implementing the project. In the
before system, livestock waste from milk cows is used formaking compost on each farm. The compost is used as afertilizer for feed crops. Electricity is supplied from
Livestock waste

Table 1. Environmental and socio-economic
consequences of a local biogas project*+*HPLVVLRQV>W&2HT\HDU@
3URMHFWVSRW>*-\HDU@(PSOR\PHQW>PDQ GD\V\HDU@▲ 15,496





,QVLGH+RNNDLGR▲ 282▲ 1,916

2XWVLGH+RNNDLGR







▲ 15,623





7RWDO

conventional power plants in the local electric power company.
Figure 2 indicates the project system after implementing the
project. In the after system, power and heat are generated withbiogas that is produced from livestock waste. Digested slurrythat generates in the biogas generation process is delivered tofarms as a fertilizer.
4. Results
Table 1 shows the changes in GHG emissions, fossil fuelconsumption and employment resulting from the project
implementation. A black triangle indicates decrease.
The bioenergy utilization is effective for the GHG
reduction. In particular, the GHG reduction in the project spot
is considerable, because CH4 and N2O are substantiallyreduced due to the absence of the compost making process inthe after system.
On the other hand, fossil fuel consumption increases byimplementing the biogas project. The breakdown by region
reveals that although it decreases inside Hokkaido, it increases
in the project spot and outside Hokkaido. Biogas power
generation reduces the use of fossil fuels for conventional
power generation inside Hokkaido. Conversely, diesel
consumption increases in the project spot because of thetransportation of livestock waste and digested slurry. Outside
Hokkaido, indirect fossil fuel consumption increases associatedwith the production of materials, equipment, fuels etc.
Employment increases in all the three regions. In the
project spot, new employment related to livestock waste
collection, plant operation and digested slurry delivery iscreated. Inside and outside Hokkaido, indirect employment
increases due to the demand of manufacturing, maintenanceand repair of equipment of the biogas plant.
Acknowledgments
We thank Shikaoi town environmental conservation centerfor providing valuable data. This work was partly funded byEnvironment Research and Technology Development Fund of
the Ministry of the Environment, Japan (Grant No. 2-1302).
Livestock waste

Composting facility
replacement

Biogas plant construction

Material transport

Compost production
Chemical fertilizer
production)RVVLOIXHOFRQVXPSWLRQ

Power generation

Digested slurry storage

Compost fertilization

Conventional
power generation

Fertilizer（N, P, K）

Electricity

Figure 1. Before system

Biogas generation

Chemical fertilizer
production

Digested slurry fertilization
Fertilizer（N, P, K）

Electricity

Figure 2. After system�������������������������������������������������

P-091

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

227

Carbon footprint labelling certification of railway operating service in Korea
Jae-Young Lee*1, Woo-Sung Jung1, Cheul-Kyu Lee1 and Hee-Man Kim2
Korea Railroad Research Institute (KRRI), Republic of Korea; 2Korea Railroad cooperation (KORAIL), Republic of Korea*Corresponding author: iyoung@krri.re.kr

1

1. Introduction
In Korea, the carbon footprint labelling certification
system for a product and service has been introduced from2009. The aim of this study was to certify the carbon footprintlabelling of railway operating service. Figure 1 shows national
railway line in Korea. In this study, the targets of railway
operating service for the carbon footprint labelling certification
were selected as KTX (Korea Train eXpress) from Seoul to
Busan as a long-distance travel and Nooriro (electric multipleunit) from Seoul to Sinchang as a short-distance travel.

Seoul to Busan was 10.21kg CO2/passenger-line and Nooriro
service from Seoul to Sinchang was 2.47kg CO2/passenger-line.
Most of carbon footprints were resulted from the manufacturephase containing 97% of KTX service and 99.6% of Nooriro
service.
Table 1. The amount of carbon emission with the life-cycle of
KTX and Nooriro service
TargetPreManufacture Use Waste Total(Unit : kgCO2) manufacture
KTX
0.17
10.04
- 10.21(Seoul-Busan)
Nooriro
0.01
2.46
2.47
(Seoul-Sinchang)

Figure 2. Contribution ratio of carbon emission with thelife-cycle of KTX and Nooriro service

Figure 1. National railway line in Korea
2. Methodology
The calculation criteria of carbon footprint in this study
was one-way per one passenger for the travel route of railway
operating service. The system boundaries were from thepre-manufacture to the manufacture phase including themaintenance and the operating service of railcar except for theuse and the waste phase. The CO2 emission of pre-manufacturephase for KTX and Nooriro service was calculated to multiply
the carbon footprint labelling coefficient by the amount of theexchange components at the railcar inspection and water use[1]. At the manufacture phase, the CO2 emission was predictedusing the amount of electrical energy consumed during theoperation of KTX and Nooriro at the selected travel route [2].
Finally, the carbon footprint of railway operating service wasconfirmed by Korea Environmental Industry & Technology
Institute (KEITI).

Acknowledgments
This work was financially supported by R&D program
through the basic research of Korea by the Ministry of Science,
ICT & Future Planning (grant number PK14003B).

3. Results and Discussions
Table 1 summarizes the amount of carbon emission withthe life-cycle of KTX and Nooriro service. Figure 2 describes
the contribution ratio of carbon emission with the life-cycle of
KTX and Nooriro service and Figure 3 shows the carbon
footprint labelling certified by KEITI for KTX and Nooriro
service.
As a result, the carbon footprint of KTX service from

References[1] Korea Environmental Industry & Technology Institute,
Guideline for carbon footprint labelling certification,
404-420, 2014.
[2] J.Y. Lee, et al. A study on the calculation of GHG
emission for domestic railroad transport based on IPCC
guideline, Journal of The Korean Society for Railway
15(4): 408-412, 2012.

(a)(b)
Figure 3. Cabon footprint labelling for (a) KTX and (b)Nooriro service
4. Conclusions
The carbon footprint labelling for two railway operating
service has been applied to inform the advantage of railway as
a low carbon emission source compared with other transportmodes in Korea.

�������������������������������������������������

P-092

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

228

A Review of the Life Cycle Assessment of Nearly Zero-Energy Residential Buildings
Markus Weißenberger,*1 Werner Jensch,1 and Werner Lang2
1

2. LCA of building services engineering
The final findings highlight that despite the wide range ofstandards (i.e., ISO 14040, ISO 14044, EN 15978) someelements within some standards are simplified or even neglected(Table 1). If the production of the HVAC (heating, ventilation,
air-conditioning) system is considered, usually only the main
components are assessed. As Table 1 indicates, only heating isevaluated in all case studies; all other use phase categories are
only occasionally considered.
Table 1. Consideration of building services engineering(+ included; - disregard; o nonspecific; n/a not applicable)
No.
Prod.
Use
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]

+
o
+
+
+
+
+
+
+

Heating

+
+
+
+
+
+
+
+
+
+
+
+

Hot
water

+
+
o
+
+
+
+
+
o
+
+

Ventil.

+
+
+
+
o
+
o
+
o
o
+
+

Cooling

+
n/a
+
+
+
n/a
+
n/a
n/a
+
+
+

Electr.

+
+
+
+
+
+
o
+
+

3. Energy and environmental impacts
Different inputs and outputs are described in the 12 casestudies [2-13]. The input of energy consumption is mentioned inall studies. Furthermore, the most applied measurement ofenvironmental impact (75%) is the Global Warming Potential(GWP). Acidification Potential (AP) as well as Eutrophication
Potential (EP) are applied by 58%. ½ of the case studies used
Photochemical Ozone Creation Potential (POCP) and 42%
Ozone Depletion Potential (ODP); the other environmental
impacts are insignificant. Moreover, all case studies assess the
production and use phase of buildings; however, the end-of-life
is inconsistent and not considered in 25%. As Figure 1 shows,by reducing the operational energy, embodied energy increases,
but the primary energy over the whole life cycle decreases.

300

120%

250

100%

200

80%

150

60%

100

40%

50

20%

0
-50

-100

Embodied energy [%](Production+Disposal)/Life cycle

1. Introduction
Given that the field of life cycle assessment (LCA) ofbuildings is vast, the aim of this paper is to clarify this area by
analyzing LCA case studies of nearly zero-energy residentialbuildings. As final energy demand during the operation phasehas fallen constantly over time, the impact of production anddisposal increases in terms of the total life cycle. In addition to
the European Union guidelines (2010/31/EU), it is requiredthat only nearly zero-energy buildings can be built after 2020.
These buildings will have a very low operational energy
demand and a very high total energy performance. Therefore, itis essential to analyze the life cycle of buildings [1].
This article focuses on a meta-analysis of peer-reviewed
papers in order to identify the state-of-the-art of basic
parameters and reference values from LCAs of nearly zeroenergy residential buildings.

Primary energy [kWh/(m² a)]

Munich University of Applied Sciences, Germany; 2Technical University Munich, Germany*Corresponding author: markus.weissenberger@hm.edu

0%
[2]

[3]

[4]

[5]

Production

[6]
Use

[7]

[8]

[9] [10] [10] [10] [11] [12] [13]Disposal

Embodied energy

-20%

-40%

Figure 1. Primary and embodied energy over the life cycle
4. Discussion
There are no case studies which could be compared one-toone. Every case study applies different system boundaries (e.g.,
the maintenance is sometimes either neglected or included in the
production or use phase). However, compared to conventionalbuildings the embodied energy shifts from 10-20% [14] and2-38% [15], respectively, to 17-96% (average 51%). That means
8-100kWh/(m2 a) is the reference value of embodied energy innearly zero-energy residential buildings. Due to that, themaintenance (also embodied energy) is mostly included in theuse phase, the value is conservative.
5. Conclusion
The results indicate the need to research the substructures(e.g., the HVAC system) to enhance a standardized, practical
approach that includes firm and definite general requirements
in order to assess the life cycle of nearly zero-energy buildings.
Acknowledgments
The authors would like to thank the German Bavarian
State Ministry of Education, Science and the Arts for theirfinancial support.
References[1] Weißenberger, M., et al. Energy Build. 76(2014): 551–557,
2014.
[2] Passer, A., et al. Int J Life Cycle Assess 17(9): 1116–1130,
2012.
[3] Gustavsson, L., et al. Energy Build. 42(2): 230–242, 2010.
[4] Cellura, M., et al. Energy Build. 72(2014): 371–381, 2014.
[5] Mosteiro-Romero, M., et al. Energy Build. 68(2014): 620–
631, 2014.
[6] Bribián, I. Z., et al. Build. Environ. 44(12): 2510–2520,
2009.
[7] Thormark, C. Build. Environ. 37(2002): 429–435, 2002.
[8] Paleari, M., et al. in Lang, W. (ed.) PLEA 2013 Munich.
Stuttgart: Fraunhofer IRB: 314–319, 2013.
[9] Blengini, G. A., et al. Energy Build. 42(6): 869–880, 2010.
[10] Verbeeck, G., et al. Build. Environ. 45(4): 964–967, 2010.
[11] Monteiro, H., et al. Energy Build. 47(2012): 572–583,
2012.
[12] Thiers, S., et al. Build. Environ. 51(2012): 276–284, 2012.
[13] Proietti, S., et al. Energy Build. 64(2013): 463–472, 2013.
[14] Ramesh, T., et al. Energy Build. 42(10): 1592–1600, 2010.
[15] Sartori, I., et al. Energy Build. 39(3): 249–257, 2007.

�������������������������������������������������

P-093

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

229

An Aggregative Assessment of Environmental Impacts on Reservoir Catchments Imposedby Public Construction Projects – A Case Study on Feitsui Reservoir
Yu-An Lin and Yuh-Ming Lee*
National Taipei University, Taiwan*Corresponding author: yml@mail.ntpu.edu.tw
1. Introduction
Taiwan belongs to subtropical climate, and the averageannual rainfall is almost to 2500 mm, but due to the
non-uniformly distributed precipitation and the steep-sloped
rivers, reservoirs has been widely constructed manage thewater supplies in Taiwan.[1] However, it’s still many problems
about the water resource management and distribution.
Reservoirs are the major water supply facilities in Taiwan,
and keeping good status of reservoirs operation is has been thegreat object for Taiwan.

help regional, state, and local agencies evaluate more
efficiently water-bodies and watershed that are not meeting
water quality standards.
WinHSPF is designed to interact with the BASINS
utilities and data sets to facilitate the extraction of appropriate
information and the preparation of model input files. The input
files can be modified and adapted to site−specific conditions
through the use of WinHSPF and supporting information
provided by the BASINS utilities and reporting functions, aswell as locally derived data sources. [4-5]2. Methodology
Environmental impact assessment (EIA) can be definedas the systematic identification and evaluation of the potential
impacts (effects) of proposed programs or legislative actions,relative to the physical–chemical, biological, cultural, andsocioeconomic components of the environment. [2]Taiwan government promulgated the environmental
impact assessment in 1994. The purpose of the assessment is toensure that decision-makers consider environmental impacts
before deciding whether to proceed with new projects. To
achieve the goal of environmental protection and sustainable
development, those who don’t follow the assessment won’t
allow implementing the development activity.
3. Case Description
Feitsui Reservoir, with Xindian River as primary flow andBeishi River as secondary flow, serves as the greatest reservoir
and is the primary resource of drinking water for Taipei
metropolitan area. The functions of Feitsui Reservoir which ismultiple targets operational are water supplying, electricity
generation and flood prevention.
In order to shorten the time of communication between
Taipei and Yilan as well as solve the surrounding traffic
congestion problem, Ministry of Transportation andCommunications R.O.C. proposed a project called“Taipei-Yilan Straight Railway Project” that includes threeroutes in 2013. According to the environmental protection law,
the project requires to hold an environmental impact
assessment in advance. Yet, part of the planning routes whichpass through Feitsui Reservoir catchments, could cause
different extent of effects to the water source protection areas
and other environmentally sensitive areas. [3]4. Assessment Results and Discussion
To understand more about the extent of effect by thedevelopment actions of Feitsui Reservoir catchments, thisstudy used BASINS/HSPF model and reviewed the impact of
the flow, sedimentation volume and water quality pollutants ofthe catchments that are affected by the construction.
Better Assessment Science Integrating Point and Nonpoint
Sources (BASINS) is a geographic information system based
tool developed by USEPA's Office of Water. It’s a multipurpose
environmental analysis system designed to bring together dataon water quality and quantity, land uses, point source loadings,
and other related spatial data with supporting nonpoint andwater quality model at a quicker and more effective pace. It canFigure 1. Screen image of analysis in BASINS
5. Summary and Conclusion
Because of the environmental influence which is by traffic
constructions development activities through collecting,compiling the monitoring information about the quality ofwater, water quantity, and sedimentation volume through thechanging of time, by analyzing and judging the direct andpotential impact factors of influential possibility to Feitsui
Reservoir catchments. At the same time, we also assessed theenvironmental hazards comprehensively by using concept
mapping with the viewpoint is from the "receptor" (theaffected).
References[1] Wen-Li Yu. Feitsui reservoir watershed hydrologic
analysis. Graduate Institute of Hydrological and Oceanic
Science, National Central University, 2005.
[2] Canter, L. Environmental Impact Assessment. Second
edition. McGraw Hill, 1996.
[3] Taipei Feitsui Reservoir Administration. Environmental
Impact Assessment on Reservoir Catchment Imposed byImportant Transportation Project. 2014.
[4] USEPA. BASINS(Better Assessment Science Integrating
Point and Nonpoint Sources).
http://water.epa.gov/scitech/datait/models/basins/index.cfm (Accessed 09.09.2014).
[5] A. Saleh and B. Du. Evaluation of SWAT and HSPF
within BASINS for the Upper North Bosque River
Watershed in Central Texas. American Society ofAgricultural Engineers. Vol. 47(4):1039-1049, 2004.

�������������������������������������������������

P-094

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

230

Environmental impacts of portland cement manufacturing and developed process withalternative technologies in Thailand
Unchalee Suwanmanee, 1 Suthida Authayanun,1 Worayut Saibuatrongand,2Viganda Varabuntoonvit2 and Thumrongrut Mungcharoen, *2

1

Department of Chemical Engineering, Faculty of Engineering, Srinakharinwirot University,
Nakhon-nayok 26120 Thailand
2
Department of Chemical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900 Thailand,*Corresponding author: fengtrm@ku.ac.th

Fuels
Chemicals

Transportation

Electricity
Clay and Fly Ash

Transportation

Electricity

Transportation

Raw Meal
Preparation

Electricity, Lignite
Coal, and
Alternative Fuels

Transportation

Clinker
Production

Electricity
GypsumTransportation

Iron Ore

Limestone &Shale Mining

Crushing

Production
CementPortland Cement
1 tonsFigure 1. System boundary of portland cement production.
3. Results and Discussion
3.1 Life Cycle Impact Assessment or LCIA (part i)
It is found that the EI and CI of cement production were
3.26 GJ per ton cement and 0.74 ton CO2 equivalent per ton
cement respectively as shown in Figure 2. The largest
contribution was from fossil fuels (coal and lignite) used forthe limestone calcination in clinker production of 2.75 GJ per
ton cement or 88 percent of total EI and 0.70 ton CO2

2.00

Cementproduction

Transportation

Cementproduction

Transportation

Clinker

production

Clinker

production

Rawmealpreparation

Crushing

0.00

shale mining

1.00

Limestone &GJ/ton cement

3.00

(a)
0.75

0.50

Rawmealpreparation

Crushing

0.00

shale mining

0.25

Limestone &2.1 Goal and scope of the study
The goals of this study are to assess the EI and CI from
cradle to production gate of cement production. The scope ofthe study includes the extraction of limestone and shale frommining process, crushing, raw meal preparation, clinker
production, cement grinding, and transportation of intermediate
product as shown in Figure 1. The functional unit was set as
1 tons of portland cement.

equivalent per ton cement 95 percent of total CI.

ton CO2 eq./ton cemen

1. Introduction
Global strategic management 2007 reported that the
average annual of cement production and consumption has
been continuous increasing from 2,283 million tons per year in2005 to 2,836 million tons per year in 2010 or about 4.7%
globally [1]. Office of natural resources and environmental
policy and planning reported that Thai industry sector
generated greenhouse gas (GHG) emissions accounted for 16.4
million tons CO2 equivalent or 7.2 percent of the total GHG
emissions in 2000. Majority of GHG emissions in the Thai
economy was dominant from Thai cement industry of 12.7
million tons CO2 equivalent or 79.3 percent of the total GHG
emissions in Thai industry sector. In this study was analyzed
and evaluated two environmental impacts, energy (EI) andcarbon (CI), of cement industry over the period from 2012 byusing Life Cycle Assessment (LCA) technique. The second
objective of this work was to evaluate and assess the
hypothesis for the improvements in cement production.

(b)

Figure 2. a) EI and b) CI of portland cement production.
3.2 Life Cycle Impact Assessment or LCIA (part ii)
The second objective is to improve cement production
which is described as follows: (i) replacing high carbon fuelsby using low carbon fuels; (ii) increasing the alternative fuels
to fossil fuels ratio (replacing high carbon fuels by using
alternative fuels); (iii) increasing the pozzolan to cement ratio(blended cements). It was found that using low carbon fuels
can reduce the CI by 16.96 percent of total CI. Using
alternative fuels and increasing the pozzolan to cement ratio,
the total EI were reduced by 17.65 and 10.06 percent of total
EI, respectively and the total CI are reduced by 3.77 and 5.21
percent of total CI, respectively.
4. Conclusion
It was found that the EI and CI of cement production
were 3.26 GJ per ton cement and 0.74 ton CO2 equivalent per
ton cement respectively. Using low carbon fuels can reduce the
CI by 16.96 percent of total CI. Using alternative fuels andincreasing the pozzolan to cement ratio, the total EI werereduced by 17.65 and 10.06 percent of total EI, respectively
and the total CI were reduced by 3.77 and 5.21 percent of total
CI, respectively.
Acknowledgments
This work has been supported by Srinakharinwirot
University fund, Department of Chemical Engineering,
Srinakharinwirot University and Kasetsart University.
References[1] Philippe Lasserre. Global Strategic Management Mini
Cases Series. (Accessed 18.01.2013).

�������������������������������������������������

P-095

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan231

Eco-benefit analysis of multifunctional building products
Michael JÄGER,*1 Johannes GANTNER,1 Sarah HOMOLKA,2 and Hannes KRIEG1
1

University of Stuttgart, Chair for Building Physics (LBP), Dept. Life Cycle Engineering (GaBi), Germany,
2
Fraunhofer Institute for Building Physics IBP, Germany*Corresponding author: michael.jaeger@lbp.uni-stuttgart.de

1. Introduction
One of the most important political goals of the European
Union is the energy turnaround. For the construction sector
especially the energy efficiency of the buildings has to be
increased significantly. The implementation of the Energy
Performance of Buildings Directive (EBPD) is an important
initiative that shall lead to energy efficient and in parallel tomore air tight buildings [1]. In this context especially building
products have to play a major role. Building products such as
wall panels usually provide a multitude of different (building
physical) functions. Hence in current environmental andeconomic analysis usually only the main function is addressed.
In a multifunctional context this is a methodological challenge.
When several products are compared via Life Cycle
Assessment a single, but complex functional unit or functional
equivalent has to be defined. With regards to the comparability
and applicability this definition cannot be easily done due tothe fact that building are complex systems with a multitude ofneeded, different functions one product can contribute.
2. The European research project ECO-SEE
The European project ECO-SEE (with funding from theEU) aims to improve the indoor environmental quality ofenergy efficient buildings. In the project different innovative
eco-building materials are developed, that shall improve not
only the energy consumption, but also improve further building
physical properties. Both an LCA and an LCC study are
conducted for these products to identify both moreenvironmentally friendly and cost-efficient solutions. [2]3. Multifunctional building products
In this context a method has been developed that addresses
the multifunctional building physical properties in order todefine comparable scenarios. The functions shall improve theenergy efficiency of the building on the one side (e.g.
insulation effect) and improve the indoor environmental quality(e.g. air borne chemicals, particulates, microbiologicalpollutants and allergens) on the other side.
Therefore modular, dynamic reference scenarios arecompiled to cope with different functions that are provided byseveral products. Instead of analyzing only a main function socalled functional bundles are defined. The required functions
can be provided by a single product (e.g. innovative
eco-building material) or by a bundle of different products.
4. Eco-benefit approach
The described approach introduces an eco-benefit method
to identify the most advantageous solution in order to provide afunctional bundle. In addition to an LCA the method includes
an innovative LCC-approach. Generally Life cycle costing
analysis is a method to estimate the total costs that occur
during the whole lifetime of a product. [3]A “forward LCC”-analysis is used to calculate the life
cycle costs of the examined products in a first step. Thisbottom-up approach shall answer the question regarding actual
costs of the product. In a second step a “backwards LCC”
based on currently available products/ product bundles in orderto estimate the competitiveness of the innovative product andidentify optimization potential.
5. Target Costing approach
As different functions are defined, a target costing
approach is used to identify those cost elements which have themajor influence on the end products and on the final price. The
basis for determining the target costs is the intended or
expected price for the final product, which is the building
product in the context of the presented method.
6. Conjoint analysis
Cost optimization also derives from the willingness to pay(WTP) of the customer. As the customers WTP mainly depends
on the functions that a product provides, in a further step theconjoint analysis [4] is used to identify the most important
attributes from an end-user perspective. The conjoint analysis
is a method in the area of market research with the aim to
predict achievable market prices. The method is often used formarketing or product management issues and is based on statedbuying preferences of possible customers.
Within the eco-benefit approach both environmental andeconomic advantageous solutions can be identified.
7. Conclusion and Outlook
All in all the method enables the user to improve theproducts from an economic perspective, but as consistency to
LCA is ensured, also from an environmental perspective.
Furthermore the maximum final price of the product is
identified from an end-user perspective.
The method is a decision-support instrument to develop
more sustainable products. Its application is shown on the basisof building products that are developed in an ongoing
European research project.
Acknowledgments
The research leading to these results has received funding
from the European Union’s Seventh Framework Programme
FP7-EeB.NMP.2013-2 under grant agreement no. 609234. The
information given in this publication does not necessarily
represent the view of the European Commission (EC).
References[1] Directive 2010/31/EU of the European Parliament and of
the Council on the energy performance of buildings(EPBD). 2010.
[2] ECO-SEE. ECO-innovative, Safe and Energy Efficientwall panels and materials for a healthier indoor
environment. EU-Project with funding from the European
Union’sSeventhFramework
Programme
FP7-EeB.NMP.2013-2 under grant agreement no. 609234.
2013.
[3] Jäger, M., et al.. Life Cycle Costing of energy storage
technologies for building integration. Conference
contribution SB 13, Munich, 2013.
[4] Backhaus, K. et al.. Multivariate Analysemethoden.
Berlin, 2000.

�������������������������������������������������

P-096

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan232

Development of a combined LCA and LCC tool for refurbishment measures of districts
Rafael Horn,*1 Johannes Gantner,2 and Michael Baumann2
1

Fraunhofer IBP, Germany; 2University of Stuttgart, Germany; 3*Corresponding author: rafael.horn@ibp.fraunhofer.de

3. Software Tool
In this context an analysis tool is developed to reduce theefforts for comparative environmental and economic analysisof refurbishment measures for existing districts. The tool aims
at enabling comparisons of different refurbishment scenarioswith minimal user effort wherefore the user input data iscompleted by typological data and generic databases. It is notaiming at detailed modelling but giving guidance todecision-makers in situations of potential refurbishments. Thus
a contribution to the acceleration of the refurbishment ratio andto the sustainable development in the building sector ispossible.
4. Approach
The model is realised within a two-stage methodology, inwhich the buildings are assessed initially before they are
regarded in district context. Each of the stages contains an
LCA-module based on the recommendations of the EeBGuide[1] and an LCC-module, which is implemented based on [2]and [3]. For the whole model only energy-saving refurbishment
measures that differ between the scenarios are considered due
to its focus on comparative analysis. At building level, thescenarios “conventional refurbishment”, “future-oriented
refurbishment” (low-energy building standard) and “partial
refurbishment” are compared to the reference scenario, that
only takes conservation measures into account. With regard toseveral system configurations and boundary conditions the best
scenario for each building can be identified. All buildings are
combined on district level (see figure 1), where they are
analysed summatively.
User input

Typology data

Description of theexisting building
Description of therefurbishment

Building level

ModuleEnergyLCAModule
LCCModule

Typology data

User input

1
2
…
i

Description of
district-widemeasures
Building profil 1
toBuilding profil iModuleEnergyLCAModule
LCCModule

Eco-portfolio

District level
Generic data

Generic data

Figure 1. Connection building and district level
The criteria and methodology developed on building level canalso be used on district level as well. Further optimisation
potentials can be identified by taking into account several
measures on district level like district heating systems

including cogeneration or integration of renewable energy
systems. To aggregate the results to be conveyed at a glance aneco-portfolio (see figure 2) is developed including directcomparison of ecological and economic efficiency of thechosen scenarios.
Eco-portfolio City district
MinimalConventional

Total environmental emissions

1. Introduction
The refurbishment of the building stock in terms of energy
supply and efficiency is a significant part of the German
turnaround in energy policy, as the building sector accounts for
40% of Germany’s total energy demand. Thus the required
refurbishment ratio of at least 2% is not yet achieved. The main
reasons are high investment costs and uncertainties in both
economic and environmental benefits. Moreover, synergy
effects of decentralised energy supply and their saving
potentials are usually not considered.

PartialFuture-oriented

Single building
District
District incl.
combined heatand power
production

LCC

Figure 2. Example Eco-portfolio of a city districtThus the best district refurbishment concept from the user’s
point of view can be generated. Due to the generic database themodel holds potentially significant uncertainties. These wereanalysed quantitatively on both building and district level. On
building level a high consistency has been proven bycomparing the results to several available tools with similar
methodology. For validation on district level a comparison withan already conducted district refurbishment has been carriedout. Again, a high correlation between the outcome of thedeveloped model and the measured data could be stated. In
contrast to current approaches the model takes a complete life
cycle approach into account and is not restricted to CO2emissions within the use phase.
4. Conclusion
In summary, the LCA and LCC tool for districts enables
architects and urban planners already in early design stages toassess the different economic and ecologic impacts of different
refurbishment strategies and optimize those.
References[1] EeBGuide Project (2012a) Operational guidance for life
cycle assessment studies of energy efficient buildings
initiative, InfoHub available online: www.eebguide.eu.
Accessed 12 September 2014[2] EN 15978: Sustainability of construction works –Sustainability as-sessment of buildings – calculation
method.
CEN–European
Com-mittee
forStandardization. Brussels: CEN – CENELEC 2010[3] VDI 2067: Wirtschaftlichkeit gebäudetechnischer
Anlagen. Beuth Verlag, Berlin (2012).

�������������������������������������������������

P-098

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

233

Macro Analysis of Life Cycle CO2 from Urban Passenger Transport Systems
in Asian Developing Countries
Kei ITO*1, Naoki SHIBAHARA2, Hirokazu KATO3, Koh KANAI3
1

Nagoya City Hall, 2Japan Environmental Management Association for Industry, 3Nagoya University, Japan*Corresponding author: k.ito@urban.env.nagoya-u.ac.jp

1. Introduction
This research estimates a macro-estimate of the CO2
emissions from urban passenger transport systems in Asiandeveloping countries using the life cycle assessment
framework. The transport mode with the lowest CO2 emissions
were determined for each city by reflecting in the estimates foreach transport mode the energy efficiency of each country,
whose electric power source configuration and combination offuels differ greatly. In addition, estimates were carried out
taking into consideration future trends in energy and emission
technology in each country, and the differences in CO2emissions among urban transport system development
scenarios were evaluated.
2. Method of Estimating Life Cycle CO2 for Passenger
Transport Modes
The assessed mode is BRT, LRT, and railway, for whichdevelopment is proceeding in Asian developing countries(Table 1). In order to evaluate the quantity of emissions inaccordance with transport demand, the evaluation index “lifecycle CO2 emissions per passenger-km transported (transportdemand)” was used. CO2 emissions were estimated for each of
the activities of vehicle operation, infrastructure construction,
maintenance and repair, and vehicle manufacture, bymultiplying the vehicle distance traveled, the route length, andthe number of vehicles manufactured by their respective CO2
emission factors. The life cycle of the transport system was set
to 60 years. Local differences in energy efficiency and futurechanges were reflected in the factors.
It is considered that the actual railway and bus operators
determine the level of service for the aspects of both transportcapacity (number of vehicle trips × capacity of each vehicle)
and number of trips. This relationship between transport
intensity and transport capacity was approximated as an
exponential function, and the transport capacity was set inaccordance with the transport intensity. The number ofjourneys is calculated by dividing the transport capacity by thevehicle capacity.

4. Results and Discussion
Fig. 1 shows the relationship between transport intensity
and life cycle CO2 per passenger for China and Vietnam, whichhave the largest difference in electricity generation coefficient.
It can be seen that as the transport intensity increases theemissions per person decrease, and the transport mode with thesmallest emissions changes. In China, even if BRT is
introduced on a route with high transport demand, its emissions
are lowest. On the other hand, in Vietnam where the electricity
generation coefficient is less, it can be seen that the transportmode with the smallest emissions changes from LRT to railway
at a transport intensity of about 10,000 [passengers/day].
From the above, it is important to consider the differencesin electricity generation coefficient, etc., among countries whenevaluating the introduction of an urban transport system fromthe point of view of low carbon properties.
200

Rail

※2

Capacity
85
130
85※3
[passengers/vehicle]
Vehicles in a train
1
1
Variable[vehicles/train]
Energy consumption
0.65
2.5
2.0
efficiency[l/km][kWh/km] [kWh/km]*1:Set based on articulated bus*2:Set based on values for tramcars for LRT and values forurban railway for rail systems, by reference to the Railway
Statistical yearbook.
*3:The safe capacity (128 passengers) based on the Road
Trucking Vehicle Act, converted to the capacity of rail
commuter vehicles in accordance with JIS E 7103.
3. Setting emission factors
This research analyses the differences in emission factors

Life cycle CO2emission / passenger[g-CO2/passenger-km]

Table 1 Transport mode
BRT ※1
LRT ※2for electricity generation coefficients, infrastructure
construction, and vehicle manufacture, whose characteristics
are different among countries. The LCA software MiLCA1) wasused for setting the factors for each area, and the values foreach country in the inventory database IDEA contained in
MiLCA were used for the electricity generation coefficients.
For each emission factor of infrastructure construction,
maintenance and repair, and vehicle manufacture, theestimation values for Japan2) were corrected using the ratios ofCO2 emission in each country for rail track construction, andvehicle manufacture obtained from MiLCA.
Future changes in energy efficiency are anticipated in theoperational stage, where the effect of technological advances iseasily reflected. In Japan it has been reported that an
improvement in fuel consumption of bus vehicle isapproximately 10% by 2020. In this research an improvementin fuel consumption of 2% every 10 years as vehicles are
renewed was set, envisaging a final improvement in fuelconsumption of 10%. For energy efficiency in the energy
generation stage, an improvement of 30% in 20 years isenvisaged for fossil-fired power generation only, where major
improvements are anticipated.

China：Rail

160
China：LRT

120

China：BRT （solid line）
Vietnam：BRT （dash line）

80
Vietnam：LRT

40

Vietnam：Rail00

10,000 20,000 30,000 40,000 50,000
Transport intensity[passenger/day]Fig. 1 Sectional transport demand intensity and life cycle CO2
per passenger-km
References[1] Japan Environmental Management Association for
Industry Guinée, MiLCA v.1.1,2012.
[2] Motohiro O, et al. Infrastructure Planning Review (Japan
Society of Civil Engineers), Vol.23(2): 355-363, 2006.

�������������������������������������������������

P-099

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

234

Estimation Method of the Change in Life Cycle CO2 from Mass Transit System
Applying Micro-scopic Traffic Flow Simulation
Naoki Shibahara*1, Ryoko Morimoto, Nozomi Kudo2 and Hirokazu Kato3
1

Japan Environmental Management Association for Industry;
National Traffic Safety and Environment Laboratory, Japan; 3Nagoya University, Japan*shibahara@jemai.or.jp

3. Results
The estimated results of life cycle CO2 emissions indicatedthat it was necessary to shift transportation demand fromautomobiles to LRT in order to reduce the CO2 withintroducing LRT. Sensitivity analyses were carried out for thechanges in CO2, which were due to changes automobile
operations, when there was a change in demand. This research
focuses on the road conditions, to determine how the sensitivity
to transportation demand shift differs in the direction towards
the central station, where there was congestion, and the
direction away from the central station, where there was nocongestion.
The hourly CO2 emissions were estimated for a case inwhich 10 to 50% automobiles traveling on the road alongside
the LRT shifted to the LRT.
Figure 1 showed the analysis results in the direction
towards the central station. If 20% of the automobiletransportation demand was shifted to the LRT, the CO2
emission reduction was greater than the dotted line whichshowed the reduction of CO2 emissions in proportion to
demand shift line. It is considered that this was because ofcongestion at the crossroads contributing predominantly todeterioration of the vehicle driving environment.
On the other hand, in the analysis results for the direction
away from the central station in the same area (See Figure 2),

250

Average traveling speed
CO2 emissions

200

Change in CO2 emissions
due to reduction in
vehicle traffic

150

30
25
20
15

100

10

50

5

0

0
0%

10%

20%

30%

40%

50%

平均旅行速度[km/h] [km/h]
Averagetraveling speed

300

Demand shift
rate from automobiles
自動車からの転換率

Figure 1. Sensitivity analysis of demand shift from automobiles(towards central station)

300
250

Average traveling speed
CO2 emissions

200

30
25
20

Change in CO2 emissions
due to reduction in
vehicle traffic

150
100
50

15
10
5

0

0
0%

10%
20%
30%
40%
50%
自動車からの転換率
Demand shift
rate from automobiles

Average 平均旅行速度
traveling speed[km/h][km/h]

2. Method of Estimating CO2 Emissions
As a case study, the life cycle CO2 emissions were
estimated for a project to replace a part of the conventional bus
route (14.5km) with a new LRT 5km section. The conventionalbus, LRT system and automobiles in the area were included inthis evaluation.
The method of "rough LCA", which was generally used tofind the emission factors, on the standard structure
supposition[1], was used to estimate CO2 emissions fromvehicle manufacturing, infrastructure construction andmaintenance stages.
An urban traffic simulator developed by the National
Traffic Safety and Environment Laboratory was used to obtain
the CO2 emissions by the operations of route buses,
automobiles, and the LRT. For automobiles, this simulator wasable to reproduce running modes such as accelerating,decelerating, and stopping (idling) to obtain positional data foreach vehicle every 0.5 second with calculations of CO2
emissions.

the reduction in the CO2 emissions was less than that of thedirection towards the central station. This was because of nocongestion in the direction away from the central station
originally. Therefore, even though the traffic volume was
reduced by this shift, there was no great change in vehicle
behavior. In addition, the road traffic is also greatly affected thesensitivity analysis results for this transportation demand shift.

[kg/時間]CO
2排出量
CO
2 emissions [kg/h]

1. Introduction
The purpose of this research is to develop a method of
estimating the total life cycle CO2 emissions from a masstransit system by taking account of vehicle traveling,
infrastructure construction and production of vehicles in order
to comprehensively evaluate the change in CO2 emissions
associated with system introduction. In particular, congestionof roads due to crossings, traffic signals and the driving
behavior of vehicles with mixed traffic of light rail transit(LRT) were analyzed by micro-simulation of traffic flow.

CO22 排出量[kg/ 時間]CO
emissions[kg/h]

2

Figure 2. Sensitivity analysis of demand shift from automobiles(away from central station)
4. Conclusion
As a result of micro-scopic traffic flow simulation, it was
found out that the changes of driving behavior were possible toreflect the CO2 estimates. Therefore, it was possible to evaluate,
environmental aspects of measures in more detail, such as theintroduction of public transport priority signals or eliminationof congestion by improvement of crossroads, which change thelocal driving environment.
References[1] Watanabe, Y., Osada, M. and Kato, H.: Environmental
Assessment of Introducing LRT (Light Rail Transit)
system -Comparison with Alternative Modes and an
Application of Eco-efficiency-, Journal of Life cycle
assessment 2(3), pp.246-254, 2006. [in Japanese]�������������������������������������������������

P-100

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan235

Net CO2 emissions by the change of consumption in consequential LCA
Kotaro Kawajiri,*1 Masaharu Motoshita1,2, Tomohiko Ihara3, Hiroki Hatayama1, and Kiyotaka Tahara1
1

National Institute of Advanced Industrial Science and Technology, Japan; 2UniversityTechnische Universität Berlin, Germany;
3
The University of Tokyo, Japan*Corresponding author: kotaro-kawajiri@aist.go.jp

1. Introduction
Sustainable consumption is one of the main issues in anenvironmental science. While nearly 20% of CO2 emissions
come from the residential section in Japan, the other CO2
emissions from the other sectors would be also attributed to theconsumer behavior because the final objectives of the activitiesof the other sectors are the benefits of consumers. Therefore,
the effects of consumer behavior on the CO2 emissions inJapan would be large.
The effect of consumer behavior would be the matter atthe usage stage. The most of foregoing studies employ thesimple assumptions for the consumer behavior, such as aconsumer buys a new product, use and waste it, and any otherchange happens in his/her life. However, if they buy the
product, the substitution or complement of consumption would
happen.
There are few studies investigating such a consequential
effect by consumer behavior in LCA field. Dowaki et al [1]investigated the rebound effect by the policy in Japanesetransportation sector. Tiesen et al [2] investigated the reboundeffect caused by buying a luxurious product. However, there
are a few studies investigating the analytical framework to
estimate the environmental impacts of such a consequential
consumer behavior.
The objective of this study is to propose thecomprehensive analytical framework to estimate theenvironmental
impactofsubstitutional/complemental
consumption by the change of consumption pattern for all
items of their daily lives.
2. Method
This study employs the second largest classification with
63 items of daily expenditure in a national survey by theStatistics Bureau and the Director-General for Policy Planningof Japan (2005) [3]. The number of classification is 63. The
CO2 intensity of each item ci is estimated using the 3EID
database [4] and methods proposed by the previous study [5].
The analytical method is composed of the following threecalculation steps.
Firstly, the total expenditure of each respondent isnormalized by the average total expenditure of all respondents.
Secondly, the correlation coefficient mij is obtained by thesingle regression analysis between the item i and the item j.
The correlation coefficients are summarized into the matrix M.
Here, the sum of each row of matrix M is zero due to theconstraint that the total expenditure does not change by thechange of consumption pattern.
Finally, the net CO2 emissions cnet by changing thespending considering the change of consumption pattern by
substitution and complement is estimated by multiplying thematrix M and the CO2 intensities c as,

cnet  cT M

3. Result
The 63 x 63 matrix M is obtained by the method in theprevious section. The values of matrix are negative andpositive; where the negative value means the substitutional

relationship and the positive value means the complemental
relationship.
Highlighting the cells relating to a food in the matrix, foodmaterials are in the complemental relationship each other. For
example, increase in the spending for the meat leads to increasein the spending for the rice. On the other hand, theconsumption of food material and some items, such as dining
out, boarding, and rent for house, are in the substitutional
relationship.
The net CO2 emissions per Yen of the following three
items, (1) oil and seasoning, (2) milk, egg, and daily products,(3) and waterworks, are larger than those of electricity. A large
amount of the net CO2 emissions of those items is caused by
the complemental spending for electricity. The increase in
spending for the former two items would be due to the increasein energy consumption by cooking devices and refrigerator.
The increase in spending for waterworks would be due to theenergy consumption to heat water. Therefore, it seems
reasonable that those items have large net CO2 emissions.
These results imply the importance of the effects of substitution
and complement on the total CO2 emissions for such items,
which have small CO2 intensity but large net CO2 emissions.
4. Conclusion
In this study, we proposed the analytical framework using
matrix to estimate the net CO2 emissions of consumption
considering the change of consumption pattern by substitution
and complement.
The matrix shows the substitutional and complemental
relationship between the each consumption. The following
prominent characteristics were found in the matrix. The foodmaterials are in complemental relationship each other. The foodmaterials and some items, such as dining out, boarding, andrent for house, are in substitutional relationshipSome items, such as oil and seasoning, milk, egg, anddaily products, and waterworks, have the large net CO2
emissions. These large emissions come from the complemental
consumption of electricity.
This study sheds light on the large hidden impacts ofconsumption by substitution and complement, which have notbeen clarified so far. The proposed analytical framework would
be useful to investigate such a hidden impact of consequential
consumer behavior.
References[1] Dowaki K., et al. J. Japan Soc. Energy and Resources, 31(6): 16-23, 2010.
[2] Thiesen J., et al. Int. J. LCA, 13(2): 104-114, 2008.
[3] The Statistics Bureau and the Director-General for Policy
Planning of Japan,
http://www.stat.go.jp/data/zensho/2009/index.htm[4] Nansai K., et al. Env. Sci. Technol., 46(16): 9146-9154,
2012.
http://www.cger.nies.go.jp/publications/report/d031/eng/i
ndex_e.htm[5] Ihara T., et al. Proc. 4th Int. Conf. Life Cycle
Management, Capetown, 2009, in USB.

�������������������������������������������������

P-101

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

236

Modeling Consumer's Choice and its GHG Implication under Simultaneous Considerationof Available Income and Time
Koji Takase*1 and Yasushi Kondo 2
1Shizuoka University, Japan; 2Waseda University, Japan, Japan*Corresponding author: jktakas@ipc.shizuoka.ac.jp

1. Introduction
Consumers face the time constraint in addition to themonetary budget in their daily life. Accordingly, consumer’s
choice for a particular purpose greatly influences otheractivities through those constraints. For example, driving a
private car is generally less time consuming, more expensive
and less environmentally-friendly than public transportation. If
consumers shift their transportation modes aiming for reducing
environmental loads, their action will cause a time shortage anda budget surplus. The difference in the total time and budget
must be compensated by adjusting other activities, such as
reducing home laundry and making them done by professional
cleaners instead. These adjustments might end up with moreenvironmental loads as a whole, which is a source of therebound effects. In this manner, some choices, which are
regarded as environmentally-friendly under a particularsituation, constitute only a portion of consumers’ lifestyle.
Therefore, a holistic approach is indispensable to evaluate thetotal environmental loads associated with consumer’s choices.
With this background, we propose a new method forevaluating environmental loads induced by consumption
patterns which meet both time and budget constraints. In otherwords, our method provides a systematic way to deal with thetime and income rebound effects simultaneously. Although thetime rebound effect has been considered in Jalas [1, 2] andDruckman et al. [3], the income rebound effect is not explicitly
taken into account in their analysis.
2. ModelIn our model, consumers are assumed to choose theiroperation levels of the consumption “technologies” (CT). A
CT is expressed as a set of products and time that are necessary
to achieve some purpose as in Becker [4]. For example, the CT“home laundry” needs several inputs such as a washingmachine, detergent, utility charges and time for washing anddrying to produce output (laundry activity). Likewise, the CT“laundry service” needs cleaning charges, time for stopping incleaning shops, and time for pick-up. As mentioned above,
there are a few mode of transportation which are regarded as
CTs for transportation activity. Because there are many
activities and modes in our daily life, consumer have toallocate there resources (income and time) among those CTs.
With the basic idea of the CTs, we can write down thehousehold consumption vector y as the linear form.
y = Bz + y0
(1)
In equation (1), the vector z represents operation levels of CTs.
The matrix B is the converter matrix that connects CTs andproducts. The vector y0 is the fixed consumption, such as afridge and clothes that cannot be sorted to a particular CT.
In addition, budget and time constraints are employed toour consumer model,
py = M(2)(3)
btz = T
where p, M and T represent price vector, income and total time,
respectively. The vector bt represents time required for CTs.
Note that variety of CTs is described by the fixed matrix B andthe fixed vector bt in equations (1) and (3).

With this consumer model and an environmentallyextended input-output model such as Nansai, et al. [5, 6], we
evaluate the GHG emission induced directly and indirectly by
consumers,(4){ d (I-A)-1 + c }ywhere d and c represent the direct GHG emission by industry
and consumer, respectively, while A represents the input
coefficient matrix.
To find the optimal operation levels of CTs (the vector z),
we have constructed a linear program (LP) to minimize the
GHG emission (4) subject to the monetary budget (2) and thetime constraint (3). An optimal solution to the LP can be
regarded as a social outlook for an environmentally-friendly
lifestyle.
3. Empirical example and concluding remarks
In our empirical example of Japanese household, we haveclassified products and time into 37 CTs. There are somealternative CTs for laundry, leisure, eating and travel activities.
Therefore, consumers can choose their optimal operation levelsof those alternatives. In addition to the time and budget
constraints, other technical restrictions have been introduced.
The total laundry weight, the total food intake and the total
travel distance are fixed; operation levels of some activities(sleep, personal care, work, etc.) are fixed; upper and lower
bounds are set for the change rate of each CT to avoid
unrealistic solutions.
To sum up, this paper provides a holistic framework toevaluate consumer’s choice in terms of the GHG emission. The
basic concept of CTs is illustrated. The income and time
rebound effects are incorporated into our model because budget
and time are used up through those constraints.
References[1] Jalas, M. A time use perspective on the materials intensityof consumption. Ecological Economics 41: 109–123,
2002.
[2] Jalas, M. The everyday life context of increasing energy
demands: Time use survey data in a decomposition
analysis. Journal of Industrial Ecology 9(1-2): 129–145,
2005.
[3] Druckman, A., et al. Time, gender and carbon: A study ofthe carbon implications of British adults' use of time.
Ecological Economics 84: 153–163, 2012.
[4] Becker, G. S. A theory of the allocation of time. Economic
Journal 75: 493–517, 1965.
[5] Nansai, K., et al. Improving the completeness of productcarbon footprints using a global link input–output model:
The case of Japan. Economic Systems Research 21:
267–290, 2009.
[6] Nansai, K., et al. Estimates of embodied global energy
and air-emission intensities of Japanese products forbuilding a Japanese input–output life cycle assessment
database with a global system boundary. Environmental
Science and Technology 46: 9146–9154, 2012.

�������������������������������������������������

P-102

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

237

Determinants of Environment-conscious Behavior in Eating Habits
Tomohiko Ihara*1, Wakana Zaima1, and Hideaki Kurishima2
1The University of Tokyo; 2Shibaura Institute of Technology*Corresponding author: ihara-t@k.u-tokyo.ac.jp

1. Introduction
Resolution of today’s environmental issues requires not
only the implementation of large-scale environment-conscious
policies by governments and corporations but also theconsumers’ daily practice of environment-conscious behaviors.
Eating habits are related to various environmental issues andchosen by consumers’ decisions. This study aims to clarify what
factor affects consumers’ decisions in environment-conscious
behaviors in eating habits and what personal attribution isrelated to their decisions in order to extract the elements
encouraging environment-conscious behaviors.
2. Method
Previous studies on determinants of environment-conscious
behaviors have been conducted based on Factor association
model (FAM) [1], Collective protection motivation model(CPMM) [2], or Psychological processes model [3]. The study
adopted FAM and CPMM because these two models haverelatively high explanation effects.
The survey results are analyzed based on FAM and CPMM
using path analysis by a free statistical computing software R.
First, their explanation effects are compared. After thecomparison, the relationship between personal attributes, thetype of environment-conscious behaviors, and the degree ofpractice of environment-conscious behaviors are evaluatedusing the model which had higher explanation effects.
3. Data
A survey via the Internet is conducted for 500 Japanese
adults in their 20s or 30s living urban areas (Tokyo or the cities
which have more than 300,000 residents) (100 male students, 96
female students, 150 male no student adults, and 154 female nostudent adults). The questionnaire includes the degrees ofconsciousness of four environmental issues (drought, global
warming, waste, and water pollution) and practice of 28
environment-conscious behaviors related eating habits.
4. Comparison between FAM and CPMM
Akaike’s information criteria (AIC) was adopted for
goodness of fit of the models. FAM had lower AICs in all the
behaviors (see Figure 1). FAM was adopted for the following
analysis.
1600
1400

6. Difference of practices by personal attributes
The survey results were compared by the personal attributes.
Female subjects have significantly larger values in thegeneral goal intention, the perceived seriousness ofenvironmental problems, the ascription of responsibility forenvironmental problems, and the belief in the effectiveness of apro-environmental lifestyle. No student subjects do not have any
significantly larger values compared to student subjects.
Subjects who do grocery shopping or cook frequently has
significantly larger values in the general goal intention, theperceived seriousness of environmental problems, the ascriptionof responsibility for environmental problems, and the belief inthe effectiveness of a pro-environmental lifestyle.
7. Behavior intention and practice
Practice of the specific environment-conscious behaviors
were also surveyed at the same time in the study. Regression
analysis between behavior intention and practice showed that thecoefficients of determination were 0.196 to 0.507 and all the
relationships were significant (p  0.05). It is considered that the
behavior intentions affect the behavior practices certainly butother factors for the behavior practices would exist.
8. Conclusion
The previous studies have showed that FAM and CPMM
had similar explanation effects. However, this study showed that
FAM has larger explanation effects.
Our analysis found that the perceived seriousness ofenvironmental problems and the feasibility evaluation give thelargest impacts on the intention. Therefore, appeal onseriousness of environment problems and institution/education
on environment-conscious behaviors can be effective forencouraging practice of environment-conscious behaviors.
Sex, occupation, the degree of grocery shopping, and thedegree of cooking also affected the consciousness ofenvironmental issues and the practice of environment-conscious
behaviors. Promoting grocery shopping and cooking may
encourage the practice of environment-conscious behaviors.
Acknowledgments
This study was supported by MEXT/JSPS KAKENHI
Grant Number 25740052.

1200
1000
800
600
400

Behavior 28

Behavior 27

Behavior 25

CPMM

Behavior 24

Behavior 23

Behavior 22

Behavior 21

Behavior 20

Behavior 19

Behavior 18

Behavior 17

Behavior 16

Behavior 15

Behavior 14

Behavior 13

Behavior 12

Behavior 11

Behavior 9

Behavior 10

Behavior 8

Behavior 7

Behavior 6

Behavior 5

Behavior 4

Behavior 3

Behavior 2

Behavior 1

FAM

Behavior 26

200
0

problems had the largest path to the general goal intention of apro-environmental lifestyle and the feasibility evaluation had thelargest path to the behavior intention of environment-in
conscious behavior all the subject groups.

Figure 1. Comparison of AIC between FAM and CPMM
5. Difference of determinants by personal attributes
The model was constructed for each subject group. The
models showed that the perceived seriousness of environmental

References[1] Hirose, Y. Determinants of environment-conscious
behavior. Japanese Journal of Social Psychology 10(1):44–55, 1994.
[2] Tozuka, T., and H. Fukada. A test of collective protection
motivation theory in threat appeal persuasion. Japanese
Journal of Experimental Social Psychology 44(1): 54–61,
2005.
[3] Koike, T., et al. Basic study on psychological processes
and activities related to environmental problems.
Proceedings of Hydraulic Engineering 47: 361-366, 2003.

�������������������������������������������������

P-103

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

238

Product differentiation and eco-behavior by using carbon footprint
Kenju Akai,*1 Haruaki Tamura,1 and Nariaki Nishino1
1
The University of Tokyo, Japan*Corresponding author: akai@css.t.u-tokyo.ac.jp

1. Introduction
It is required that each citizen tries to reduce Green House
Gases (GHGs) to mitigate the impact of global warming.
However, each person tends to set a high value on convenienceand economical reasonableness, disregarding eco-friendliness.
This tendency is generally called social dilemma [1].
To remove this social dilemma, carbon footprint is thought
to be attractive. Carbon footprint is a kind of eco-label, whichis to be attached to each product. Since the carbon footprintshows the total emission of CO2 in whole process of
production, it enables to grasp how much CO2 is emitted ineach action of process of production.
The aim of this study is to analyze the effect of the spreadof carbon footprint and influence of the carbon tax to the social
dilemma. To this end, this study constructs the game-theoretic
models for trading goods with carbon footprint between
producers and consumers, and then analyzes their actions in thelaboratory experiment by employing real human subjects.
2. Model description
This study considers the situation in which producers
decide whether to produce eco-friendly products or not andconsumers whether to purchase them or not. The eco-friendly
products have three levels of the CO2 emissions, highest
amounts, defined as ߮௔ , middle amounts, ߮௕ , and lowest
amounts, ߮௖ . The costs of these products are ܿ௔ ൐ ܿ௕ ൐ ܿ௖ .
The producers choose one of these three products.
The environmental damages are assumed to be calculated
as some relation to the cumulative CO2 emissions caused by
the products. Some amounts of CO2 emissions are sunknaturally in the long life. All products are sold in the market
until Period T. The cumulative CO2 at period ‫ ܶ א ݐ‬is definedas ߮ത௧ . Thus, the damage function ݂ሺ߮ത௧ ሻ from the emissions
is defined as follows:ߛ݂ሺ߮ത௧ ሻ ൌ(1)݊ሺͳ ൅ ሺെߙ߮௧ ൅ ߚሻሻ

3. Human subject experimentThis study employs the experimental economics method toanalyze the decision making for human subjects. The principleof this method is the induced value theory [2]. This theory
suggests providing monetary incentives for subjects as areward relative to the profit they earn in the laboratory. Thismethod is useful for breaking the hypothetical bias that isdefined as the overestimation when subjects have no monetary
incentive and hypothetically make their decisions [3].
This study conducts the two treatments. One is the tax
treatment in which consumers need to pay tax for the
proportion to the amount of CO2 emission of each product theybuy. The other one is no-tax treatment which is the benchmark
control session. There are two producers and three consumers
in each group. We recruit 4 groups. One session includes morethan 20 periods. Same subjects join the both treatments.
Average payments are about 3,000 yen in 2 hours.
4. Results
The highest eco-friendly product is more frequently
produced and purchased in all groups in the tax treatment thanthat in non-tax treatment. This result suggests that the tax
system succeeds in promoting to purchase and produce
eco-friendly products. However, there are two groups which
produced and purchased the lowest eco-friendly products more
frequently in the tax treatment than the no-tax treatment. This
result implies that the tax system also has a risk to promote
some consumers to become free riders, that is, to purchase lesseco-friendly products because damages from the pollution
become less. In total, the net amount of CO2 emission in the
tax treatment is 30% less than that in the non-tax treatment,
which implies that the tax system succeeds in enhancing
incentives for consumers and producers to reduce CO2.

where߮ത௧ ൌ ෍ሺ෍ ‫ܯ‬௜௧ ߮௜ െ ‫ݏ‬ሻǡ݅ ൌ ܽǡ ܾǡ ܿ
௧

‫ݐ‬

௜

(2)

Notice that ‫ ݅ܯ‬is the number of purchasing product atperiod ‫ݐ‬. ‫ ݏ‬is the CO2 sinks. ߙǡ ߚǡ ݊ are the parameters
for environmental damages, respectively.
There are k producers. They obtain profits defined as themultiplication of the number of products they sold, ݉௧௟ , andthe profits from the one unit of each product, ܵ. The, theprofits for producer l is defined as follows:ߨ ௟ ൌ ݉௧௟ ܵǡ ݈ ൌ ͳǡ ǥ Ǥ ǡ ݇,(3)‫ݑ‬௠ ൌ ‫ ݎ‬െ ‫݌‬௜ െ ݂ሺ߮ത௧ ሻǡ ݉ ൌ ͳǡ ǥ Ǥ Ǥ ǡ ݆ǡ ݅ ൌ ܽǡ ܾǡ ܿ

(4)There are j consumers. They obtain net benefits defined as
the difference between benefits from the purchased product andenvironmental damages. The prices of the three products aredefined as ‫݌‬௔ ǡ ‫݌‬௕ ‫݌‬௖ , respectively. The reservation price ofconsumers is defined as r. The net benefit for consumer m isdefined as follows:

Figure 1. Fraction of eco-products in non-tax vs. tax treatments
References[1] Dawes RM. Formal models of dilemmas in social decision
making. Human judgement and decision process. NewYork:
Academic Press; 1975.
[2] Smith V. Experimental Economics - Induced Value Theory.
American Economic Review 1976; 66: 274-279.
[3] Glenn W, Harrison E, Rutström E. Experimental evidence
on the existence of hypothetical bias in value elicitation
methods. In: Plott CR, Smith VL, editors. Handbook ofExperimental Economics Results, Volume 1. 2008. P.
752-767.

�������������������������������������������������

P-104

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

239

Effect on CO2 Emissions of Low-Carbon-Technology Considering Residents’ Activity
Schedule
Chika Ishida,*1 Hiroyoshi Morita,2 Yoshimi Kanaoka,3 and Hirokazu Kato1
1

Nagoya University, Japan; 2Nippon engineering consultants company, Japan; 3Urban Renaissance Agency, Japan*Corresponding author: cishida@urban.env.nagoya-u.ac.jp

1. Introduction
Smart City projects are currently in progress all over theworld, owing to concerns over the exhaustion of petroleum
resources and global warming. These projects are largely using
information and communication technology (ICT)[1]. Some
major trial examples are 1) decreasing CO2 emissions ofdomestic housing, buildings, and transportation; 2)visualization of the energy supply and demand in each district
and area-wide energy system (Micro Grid)[2].
The energy consumption and peak characteristics of thedomestic energy sector are dependent on the lifestyle of theindividual household; this includes the way of life, means oftransportation, and location. Moreover, development of ICT
instigates telework and shared housing. These kinds of lifestylechanges are predicted to influence energy demand.
This research aims to investigate low-carbon sectors fromtwo perspectives; the introduction of low-carbon technology
and space construction. A model was constructed, which cancalculate the energy demand and CO2 emissions from theactivity schedule of each household. Furthermore, theinfluences of new lifestyles on the reduction of CO2 emissions
are analyzed.
2. Composition of CO2 emission model
The model for estimating CO2 emission is shown in Figure
1. Firstly, household composition is set up and a schedule iscreated for each member with SCHEDULE v2.0 using
statistical research[3]. Secondly, the energy demand of light,
electrical appliances, air-conditioning, hot-water supply, andtransport is calculated. Thirdly, energy consumption is
calculated depending on the assumed energy system. Finally,
the CO2 emissions from domestic sources in the entire area are
estimated based on the household composition and land use.
In this study, the energy system, which is assumed to be
introduced in the future, has four types. One is that the energyof each house and building is controlled individually. The otheris that area energy is operated cooperatively, accommodated,and controlled. The systems are divided as decentralized,
semi-centralized, and centralized.
Housing TypeHousehold Type

Location ofhome

Floor space

Individual
activity schedule

Trip distance andModal share

Energy consumption
schedule from domestic

House facilities
performance

Energy consumption
Light and
electricalappliance

airconditioning

hot water
supplytransport

CO2 emission from domestic

Figure 1. CO2 emission estimate model
3. Case study in the Nagoya metropolitan area
Evaluation of the introduction of each energy system tothree areas (inner, suburbs, outer) in the Nagoya metropolitan
area is conducted. The changes set for household composition

coincided with the problems in each area. The changes
introduced shared housing in inner areas, relocation from a
detached house to an apartment in the suburbs, and telework
was proposed in outer areas.
CO2 emissions are reduced compared to the current
situation by changing household composition. Introducing theenergy system lowers area-wide CO2 emissions in the order ofdecentralized, semi-decentralized, and centralized.
In the inner area, a reduction rate of 24% is observed, inthe current system, by introducing shared housing. Additional
reductions are expected by introducing the energy system.
In the suburbs, a reduction rate of 4% in the current
situation is achieved by house relocation. Furthermore, CO2
emissions per capita become negative when area-wide energy
is introduced. This is because the amount of power generationfrom housing is balanced with commercial and business energy
consumption.
In the outer area, CO2 emissions are slightly reduced, inthe current system, by introducing telework. However, whenthe energy system is introduced, the emissions increase. This isbecause the energy used to power a car is generated byphotovoltaics. The CO2 emissions are not influenced by shorter
trips, while CO2 emissions from houses increase because
time-at-home is increased through telework.
4. Conclusion
In this study, a CO2 emission model, which is influenced
by area characteristics, space composition, and activity
schedules, is constructed. The different effects of introducing
low-carbon technology are analyzed based on land use,household composition, and activity schedules.
This study reveals the following: 1) The effect of
introducing area-wide energy is greater in the suburbs becauseload leveling is achieved. 2) In the case of introducing telework,
CO2 emission is lower in the current energy system. However,if the public transport share increases and the CO2 emission
basic unit of electric vehicles decreases, then CO2 emissions
from housing could increase.
Acknowledgments
This study was supported by the Environment Research &Technology Development Fund, Ministry of Environment,
under permission No. 2-1404, for the study titled “Planningand Evaluation Model for Green Growth Centers based on
Spatial Inventory Analysis”. We appreciate this support andexpress our heartfelt thanks.
References[1] New energy Promotion Council (NEPC), Japan Smart
City Portal HP, 2013.
http://jscp.nepc.or.jp/index.shtml(Accessed 26.08.2014).
[2] T. Kashiwagi, Smart Kakumei, Nikkei BP, 2010.
[3] The society of Heating, Air-Conditioning, and SanitaryEngineers of Japan, SCHEDULE v2.0, 2000.

�������������������������������������������������

P-106

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan240

Evaluation of relationship between agricultural workers and agricultural residues:
A case study of Hyogo prefecture
Tomohiro Tabata,*1 and Yukako Sakon,1

1Kobe University, Japan*Corresponding author: tabata@people.kobe-u.ac.jp䢳䢸䢲䢲䢲䢲

䢳䢴䢲䢲䢲䢲
䣃䣩䣴䣫䣥䣷䣮䣶䣷䣴䣣䣮䢢䣹䣱䣴䣭䣧䣴䣵

1. Introduction
Technical, economic, and social issues for energy
utilization of agricultural residues exist even though such
utilization of such residues is quite important from theviewpoint of global warming. However, stable supply ofagricultural residues might be difficult in the future because
there are few younger agricultural workers in Japan and aging
ones have increased. In this study, we develop a model toestimate production of agricultural residues taking into accountpopulation of agricultural workers and cultivated acreage.

䢺䢲䢲䢲䢲

䢶䢲䢲䢲䢲

䢲

3. Results and Discussion
The following regression formula is introduced.

S 60.85LM  10.33LF  0.46 AA  123.24 AL  7,084(10.08)(3.09)( 4.31)(15.67)( 1.37)(1)

where, S are sales of agricultural products, LM are maleagricultural workers，LF are female agricultural workers，AA iscultivated acreage for rice, vegetables, and fruits (are)，and AL:
is cultivated acreage for feed grains and crops (are).
There are about 150,000 agricultural workers in FY2010[1]. Based on the cohort-change rate method, the result in
FY2030 is reduced to approximately 63,000 people (Figure 1).
According to the results of agricultural workers, production ofagricultural residues is 7.8 million tonnes in FY2010 (Figure 2).
On the other hand, the result in FY2030 is reduced to 3.5
million tonnes. Energy of agricultural residues in FY2010
corresponded to 595 GJ and the result in FY2030 is reduced to
278 GJ. These values take into account utilization ofagricultural residues, such as compost. If all agriculturalresidues are utilized as energy, 5,928 GJ can be utilized in

䢴䢲䢳䢲

䢴䢲䢳䢷

䢴䢲䢴䢲

䢴䢲䢴䢷

䢴䢲䢵䢲

䣣䣤䣱䣸䣧䢢䢸䢷䢢䢪䣈䣧䣯䣣䣮䣧䢫䢳䢷䢯䢴䢻䢢䢪䣈䣧䣯䣣䣮䣧䢫䢵䢲䢯䢶䢶䢢䢪䣏䣣䣮䣧䢫䢶䢷䢯䢸䢶䢢䢪䣈䣧䣯䣣䣮䣧䢫䣣䣤䣱䣸䣧䢢䢸䢷䢢䢪䣏䣣䣮䣧䢫䢳䢷䢯䢴䢻䢢䢪䣏䣣䣮䣧䢫䢵䢲䢯䢶䢶䢢䢪䣈䣧䣯䣣䣮䣧䢫䢶䢷䢯䢸䢶䢢䢪䣏䣣䣮䣧䢫

Figure 1. Future outlook of agricultural workers䢺䢲䢲䢲䣃䣴䣫䣥䣷䣮䣶䣷䣴䣣䣮䢢䣴䣧䣵䣫䣦䣷䣧䣵䢢䣝䣶䣪䣱䣷䣵䣣䣰䣦䢢䣶䣱䣰䣰䣧䣟

2. Methods
This model consists of five modules, aiming to (1) estimate
sales of agricultural products using a regression model, (2)convert each agricultural residue from sales of each agricultural
product, (3) estimate CO2 reduction effect if the agriculturalresidue is utilized for heat and electricity, (4) estimate future
outlook of population of agricultural workers, and (5) estimate
future agricultural residues.
First, an agricultural census in Japan from FY2000 to
FY2010 [1] is utilized to construct the regression model (FYmeans fiscal year. FY2000, which ends in March 2001). Salesof agricultural products are extracted as the explained variable;
and 18 variables, such as agricultural workers and cultivatedacreage, are extracted as explanatory variables from this census.
Second, residue to product ratio of each agricultural product is
examined via a literature survey and interview. Third, heat andelectricity made from agricultural residues are assumed to
substitute for heating oil and system power of major powercompanies. Fourth, future outlook of population of agricultural
workers is estimated using the cohort-change rate method.
Finally, future outlook of agricultural residue is estimated bymultiplying agricultural residue and the future outlook of the
population of agricultural workers.
This model is applied to Hyogo prefecture as a case study.
The future outlook of production of agricultural residues from
FY2010 to FY2030 is estimated.

䢸䢲䢲䢲

䢶䢲䢲䢲

䢴䢲䢲䢲

䢲
䢴䢲䢳䢲

䢴䢲䢳䢷

䢴䢲䢴䢲

䢴䢲䢴䢷

䢴䢲䢵䢲

䣃䣹䣣䣬䣫

䣐䣫䣵䣪䣫䢯䣪䣣䣴䣫䣯䣣䣊䣫䣩䣣䣵䣪䣫䢯䣪䣣䣴䣫䣯䣣䣊䣣䣰䣵䣪䣫䣰䢯䣯䣫䣰䣣䣯䣫䣖䣣䣰䣤䣣䣐䣣䣭䣣䢯䣪䣣䣴䣫䣯䣣䣊䣣䣰䣵䣪䣫䣰䢯䣭䣫䣶䣣

䣍䣱䣤䣧

䣕䣱䣷䣯䣣

䣍䣫䣶䣣䢯䣪䣣䣴䣫䣯䣣

Figure 2. Future production of agricultural residues
FY2010. The CO2 reduction effect is also 1.9 million tonnes in
FY2010, and the result in FY2030 is reduced to 0.8 million
tonnes. If the population of agricultural workers aged 14–44
years is raised quinquennial until 20%, then for our outlook
between FY2010 and FY2030, production of agriculturalresidues may increase 2.1 million tonnes in FY2030.
4. Conclusion
Although local governments estimate the renewable energy
potential of agricultural residues for their future biomass
utilization plans, they do not consider the decline of
agricultural works. The model we developed is able tointerrogate and assess their plans taking into account actual
farming.
Acknowledgments
This research was partly supported by the Sumitomo
Foundation. The residue to product ratio of vegetables andfruits for each agricultural product was provided from Chiba
Prefectural Agriculture and Forestry Research Center.
References[1] Ministry of Agriculture, Forestry and Fisheries. 2000,
2005 and 2010 Census of Agriculture and Forestry inJapan. http://www.maff.go.jp/j/tokei/census/afc(Accessed 02.07.2014).

�������������������������������������������������

P-107

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

241

Land constraints associated with future food and biofuel demands
Kento Tamura,*1 Naoki Yoshikawa,1 Koji Amano, 1 and Seiji Hashimoto1
1
Ritsumeikan University, Japan*Corresponding author: rv0013ir@ed.ritsumei.ac.jp

1. Introduction
Demand for food has been increasing while biofuels haveattracted attention as carbon-neutral energy resources.
Increased demand for these agricultural products is expected toaffect some planetary boundaries such as global land use,biodiversity loss, freshwater use, nitrogen and phosphorus
flows, and climate change. An estimate shows 62 countries will
not be self-sufficient in the future because of their land
constraints [1]. Furthermore, cropland requirements are
estimated to be a maximum of 2,669 million ha by 2100 [2].
Therefore, assessing land constraints associated with both foodand biofuel demands are important. Nevertheless, such land
constraints have not been well examined. This study estimatedthe following: (1) demand for crops for food and biofuels under
new IPCC scenarios (SSPs) and (2) required agricultural land.
We then briefly discuss gaps and potential to satisfy thenecessary areas devoted to crop production.
2. Method and data
This study examined 187 countries and regions all over
the world. Shared Socioeconomic Pathways (SSPs) developedby the Intergovernmental Panel on Climate Change (IPCC)
were used to get future population and GDP data of 2010–2100.
We estimated the demand for food of 96 items in Food Balance
Sheets of Food and Agriculture Organization (FAO) of theUnited Nations using the methods based on [3] and estimatedthe demand for crops for bioethanol for vehicles using methods
based on [4]. Figure 1 presents a flowchart of this study.
3. Results and discussion
As a result, food crop demand might reach 16.3 Gt, or 2.4
times the present level, through 2100. Although most crop
requirements are expected to decrease in association withdepopulation after 2050, wheat and maize must increase until
2100 because of increased per-capita intake of meat andincreased demand for feed. Biofuel crop demand will reach10.0 Gt, about half of which is sugar cane.
This result also demonstrates that land requirements canreach 1.3 times larger than the present land harvested (1.6 Gha)at most because of expected increases in per-capita GDP and
population. Land demand for biofuels was expected to be
10-20% of the total at most under this scenario. Economic
growth had greater influence on its increase than that of land
for food crops.
In Figure 2, the maximum value of agricultural landdemand through 2100 for each region (Rmax) is shown with theactual area harvested in 2010 (2010act). Most regions must
expand agricultural land. Especially in Eastern and Southern
Asia and Eastern and Western Africa, they had large difference
between 2010act and Rmax.
Moreover, land demand for biofuel was expected to be
30% of the total at most. Halving meat consumption could
reduce about 15% of total land requirement at most.
4. Conclusion
This study estimated the demand for crops for food andbiofuel under new IPCC scenarios (SSPs) and required
agricultural land. Results shows 1.3 times the present
agricultural land might be needed through 2100 because of

Figure 1. Flowchart of this study

Figure 2. Actual area harvested and estimated agricultural land
requirements
expected increases in per-capita GDP and population. Most
regions must expand agricultural land. Especially, Eastern andSouthern Asia and Eastern and Western Africa must greatly
expand their land area from present levels. Moreover, halving
meat consumption could reduce about 15% of total land
requirement at most.
Acknowledgement: This research is supported by theEnvironment Research and Technology Development Fund
(S-11-2) of the Ministry of the Environment, Japan.
References[1] Fader, M. et al. Spatial decoupling of agricultural
production and consumption: quantifying dependences ofcountries on food imports due to domestic land and water
constraints, Environmental Research Letters 8: 014046,
2013.
[2] Munesue, Y. and Masui, T. Variation factor of global
cropland requirements from the IPCC Special Report on
Emissions Scenarios (SRES). Environmental Science22(2): 73-90, 2009. (in Japanese)[3] Munesue, Y. and Masui, T. Long-term projections ofglobal food requirements from the IPCC Special Reporton Emissions Scenarios (SRES). Environmental Science21(1): 63-88, 2008. (in Japanese)[4] Yoshimoto, K. et al. A study of food supply–demand
structure and change of land use in the world considering
increase of the demand for bioethanol, Environmental
Systems Research 36: 255-263, 2009. (in Japanese)�������������������������������������������������

P-108

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

242

Web-Based system Development for GHG emission from Livestock Sector
Geun-young Lee ,*1 Sung-mo Yeon1, and Kun-mo Lee2
1
WECOS, Korea; 2 Ajou University, Korea*Corresponding author: gylee1011@wecos.co.kr

1. Introduction
As the global GHG emissions increase, Korea
governments have enforced a National/Sectoral GHG
Mitigation Target system for GHG emission management in all
sectors. Each company including this system has conductedvarious activities for GHG reductions.
Ministry of Agriculture, Food and Rural Affairs (MAFRA)
have studied diverse researches for GHG management inlivestock sector. But up to now, there is not almost the GHG
emissions management system in national low lever local
government. Therefore the need to manage and calculate GHG
emission in national level is required increasingly.
2. Research and result
2. 1. Goal and scope definition
2. 1.1. Goal
In Korea, researchers have studied diverse researches for
GHG emissions in livestock sector. But there is not almost the
GHG emissions management system in national local
government. Therefore the goal of this study has developed
Web-based system in order to manage GHG emissions in local
government for milk cow, Korean beef/beef cattle and pig.
2.1.2. Scope
Geographical scope is 227 local governments andlivestock studied are milk cow, Korean beef/beef cattle and pig.
In addition, we separated GHG emissions into 4 steps,
namely feedstuff production, enteric fermentation, electricity
for farm, manure management
2.2 Activity data
2.2.1 Number of heads
But we need the number of heads of each growth phase formilk cow, Korean beef/beef cattle and pig, there is not relevant
data in Korea.
Therefore we calculated the number of heads using local
government’s statistics annual report and national statisticaldata.
2.2.2 Feeding
We estimated the amount of the feed fed in the eachgrowth phase utilizing feeding standard of Korean National
Institute of Animal Science (NIAS) and relevant associationdata.
And we classified feedings as 3 categories, namelyroughage feed, concentrated feed and TMR. For TMR, we
assumed “0” because there is no data in feeding standard andstatistical data.
2.2.3 Energy consumption
There is no standard farm’s operation data for energy
consumption in Korea. Korea Energy Economics Institute(KEEI) has published the national energy consumption data
about agriculture sector every 3 years. But that data is notsuitable for this study.
Therefore we calculated energy intensity (energy
consumption/head) from the GHG emission of farm operation
including “Development of carbon tracing system for livestock
agriculture” by performed MAFRA.

2.2.4. GHG emission factors
Emission factors provided by Greenhouse Gas Inventory& Research Center of Korea (GIR), Korea Environment
Corporation and Ajou university’ s farm model are used.
2.3. Result
We developed web-based GHG emission management
system which we can use the above-mentioned activity dataand emission factors.
Main characteristic of this system is that we are able easily
to enter raw data and calculate GHG emissions to local
government level.

.
Figure 1. The main screen of web-based system
The total of 3 livestock’s GHG emissions is 929,377 tCO2
in 2001 and 1,402,192 tCO2 in 2012. The highest GHG
emission area is Gyeonggi-do province for milk cow,
Gyeongsangbuk-do Province for Korean beef/beef cattle andGyeonggi-do province for pig.
3. Conclusion
To manage GHG emissions in livestock sector consistently,
we need to introduce new national scheme. Also we have to
study the research for detailed activity data and emission
factors.
Acknowledgment
This research has been development within the frame
work of “The method development of calculation and medium
for CH4 and N2O emission” and supported by Korean National
Institute of Animal Science (NIAS).
References[1] Kun-mo Lee, “ Quantification and control of thegreenhouse gas emissions from a dairy cow system”,
Journal of Cleaner Production 70: 50∼60, 2014[2] Kyu-hyun Park, “Development of carbon tracing system
for livestock agriculture”, research report, National
Institute of Animal Science of the Republic of Korea,
2013[3] “2013 National Greenhouse inventory Report of Korea”,
Greenhouse Gas Inventory & Research Center of Korea,
2014[4] Korean Statistical Information Service. http://kosis.kr�������������������������������������������������

P-109

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

243

Greenhouse Gas Emission of Rice Production System in the Philippines Based on Life
Cycle Inventory Analysis
Elmer G. Bautista1 and Masanori Saito2*
1

Philippine Rice Research Institute, Philippines; 2 Tohoku University, Japan*Corresponding author: msaito@bios.tohoku.ac.jp

1. Introduction
In the Philippines, agriculture was 3% of GDP and
employing 35% (12.9 million) of the total labor force [1]. Rice
cultivation is 34% of its total agricultural area [2]. The national
inventory in agricultural has been 1994 data. It is important toquantify the GHG emission from rice production.
Most rice fields are cultivated twice a year. Methane, theGHGs emitted through anaerobic decomposition of organic
matter in the field, is less in rainfed than irrigated rice. With
low mechanization status, carabao is still widely used as draft
animal for plowing and harrowing. Rice straw burning is mostpractice (95%) because it is the fastest, economical, and easiest
way but cause environmental and health hazards.
Climate change has been the biggest threat to humanity.
The Philippines has been severely experiencing naturalcalamities such as floods, typhoons, and droughts as it is moredevastating in the tropics than other climatic zones.
This paper assessed the GHG emissions of rice production
based on lifecycle inventory analysis. It is vital to help
identify potential mitigation processes.
2. Methods
This study classified rice production into irrigated (2.9Mha) or rainfed (0.13M ha) area with ave. 4.21 and 2.93 t ha-1 in
2006-2007, respectively. The system boundary included
seedbed preparation, land preparation, transplanting, crop care,harvesting, and threshing. In the Philippines, harvested rice isusually preserved as grain and was milled immediately before
consumption.
The GHG emissions from fertilizer, pesticide, fuel andcarabao; and methane (CH4) and nitrous oxide (N2O) emissions
from soil were estimated based on 2006 IPCC guideline. The
difference in rice straw management (burning or incorporation)
was also accounted. Data and GHG emission factors weregathered from the Philippine surveys of 2006-2007 [1] andreferences [2]. GWP used were 21 and 310 for CH4 and N2O,
respectively. The total GHG emission of rice production was
calculated using the following formula:
GHGr = ∑(GHGrc +GHGf+GHGcm+GHGfuel+GHGrs+ GHGp+ GHGmach)
Where: GHGr = the total GHG emission of rice
GHGrc = the GHG emission during rice cultivation
GHGf = the GHG emission of fertilizer
GHGcm = the GHG emission of carabao
GHGfuel = the GHG emission of fuelGHGrs = the GHG emission of rice
GHGP = the GHG emission of pesticides
GHGmach= the GHG emission of machine

3. Results and Discussions
The total GHG emission of rice production in thePhilippines was 13.3 Tg CO2 eq. yr-1.
Table 3. GHG emission of rice in the Philippines.
Irrigated area
Rainfed area
Total

Total kg CO2 eq. yr-1
1.14E+10
1.87E+09
1.33E+10

kg CO2 ha-1 yr-1
3.92E+03
1.38E+03
3.11E+03

Rice yields from irrigated and rainfed areas were 74% &26% of the total rice production while GHG emission were11.4 Tg CO2 eq. yr-1 (86%) and 1.87 Tg CO2 eq. yr-1 (14%).
The GHG emission of rice in the Philippines was lower
than other temperate countries. Lower GHG emission was due
to lower use of fertilizer, agro-chemicals, fuel, and other inputs.
Increasing rice productivity will increase inputs but also
increase GHG emission. However, if the increase in yield iscomparable with the increase in inputs from fossil sources, theGHG emission per rice grain might be kept at the same level.
Table 2. GHG emission of rice in the Philippines
CH4 emission from soil
CH4,
N2O
from
carabaoN2O from N applied
Fertilizer
Pesticides
Fuel
Threshing
Handtractor
Total

kg CO2 eq. ha-1
irrigated rainfed
3,625
1,141

kgCO2eq kg grain-1
irrigated rainfed
0.861
0.389

50

50

0.012

0.017

105
99
5
6
13
17
3,922

79
74
2
5
13
17
1,381

0.025
0.024
0.01
0.01
0.03
0.04
0.931

0.027
0.025
0.01
0.02
0.04
0.06
0.471

Several mitigation processes could be adapted such as use ofalternate wetting and drying and midseason drainage; replacing
carabao with handtractor; and good straw management.
4. Conclusion
The major GHGs emitted were CH4 and N2O from soil andfertilizer. Mitigation for these processes should be prioritized.
Also, it was noted that GHG emission from rainfed was muchsmaller than irrigated rice’s. The Philippines needs to produce
more rice by expansion of irrigation and use of advance rice
farming but inevitable increase GHG emission. Therefore, itwill be more important to satisfy both increasing riceproductivity and mitigating GHG emission.
5. Acknowledgment
The authors are grateful to the JSPS RONPAKU
fellowship program. The fellowship was given to E.G.B.
6. References[1] CountrySTAT Philippines. (2007). Palay and Corn: Volume
of production by ecosystem/crop type, geolocation, year
andperiod. http://countrystat.bas.gov.ph/selection.asp(Accessed on April 2, 2014)[2]FAOSTAT(2012).
FAO
Statistic
database.
http://www.fao.org. (Accessed on June2012)[3] Wassmann, R., et al. (1994). Temporal patterns of methane
emissions from wetland rice fields treated by different
modes of N application. J. Geophys. Res.: Atmospheres 99(D8), 16457-16462.
[4] Yoshida S. 1981. Growth and development of rice plant. In:
Fundamental of rice crop science. International Rice
Research Institute, Philippines. Chap 1. pp1

�������������������������������������������������

P-110

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

244

A proposal of the CF index of rice in consideration of consumer’s health condition.
Takashi Oi,*1 Kenta Shiokawa,1 Kenji Koido,1 and Kiyoshi Dowaki1
1

Tokyo University of Science, Japan*7414604@ed.tus.ac.jp

1. Introduction
Recently, the demand of rice is decreasing due to a changeof the food culture in Japan. Accordingly, the number of rice
farmer has been declined slightly. On the other hand, Japan
government announced to join in Trans-Pacific Partnership(TPP) in the future. TPP is a Free Trade Agreement (FTA) witha high-level liberalization goal so as to reduce all trade tariffs
to zero. So far, Japanese rice was protected by high tariff rate.
However, based on the scheme, the government seems to get agood chance to enlarge the number of rice farmers. That is, thecharacteristics of eco-friendliness and/or high quality etc.
would be remarkable.
In this paper, we focus on the Japanese rice production
from the viewpoint of LCA thinking and product quality. Thismeans that the agricultural product can take a good strategy so
as to enlarge the market. Also, the product can be exported bymaking differences on the eco-friendliness and the quality,
even if TPP scheme would be promoted.
2. Estimation Conditions
Here, we considered the following two scenarios: (1) the
product is the rice exported after the brown rice cultivated inJapan is polished, and (2) that is the rice exported after thebrown rice cultivated in Japan is unpolished. Both of products
are assumed to be stored in foreign countries before shipment,
for instance, Asian countries which would be promising area.
We adopted the model country of Indonesia. Thus, weinvestigated the influences of not only agricultural activity but
also transportation and storage.
3. Calculation method
Based on the system boundary, we calculated the LCCO2
emission and DALY. In the calculation of above indexes, thespecific energy consumption was due to sub-processes ofagricultural activities or transportation. Also, this time, we
involved the effect of quality change of product. On the ricecultivation, we executed the site investigation in Yamagata,Japan, that is, we used the bottom-up methodology.
The index on the food security was considered by themeasurement data. Using the measurement result of heavy
metal content of rice, we calculate DALY per polished rice 1
kg. Here, our estimation was estimated by LIME2. DALY is
calculated by the product of chronic damage function andamount of daily intake per kilogram of body weight. Also,
chronic damage function is as follows:
chronic = PDI × DR × DALYs(1)
DR = 0.1⁄�ED10h − THr�ED10h = 1.6 × NOAEL = 0.3 × LOAEL

(2)
(3)

where, chronic, PDI, DR, DALYs, ED10h, THr and NOAEL
are chronic damage function, daily ingestion predictive
quantity [mg/kg/day], dose-response factor, DALY of chronic[risk/(mg/kg/day)], 10% of quantity which influences a person,
threshold, and no observed adverse effect level, respectively.
Also, we considered quality of rice. Here, the quality ispalatability. That is, the quality means the inclusion of heavy
metal, protein, amylose, moisture, consistency and stickiness,by which the preference is extermenly affected. Thus, as a friststape, we focused on the influecne for quality change due to thecold storage. Compared the case of cold storage at 12 deg.C tothat of ambient storage at room temperature, we investigatedthe quality change of target rices with the passage of time of amonth and fourth month. Then, the effect was calculated by thefollowing equations of rate of deterioration (See (4)).
������� �� ����� �������
�
(4)
RD =
, balance =������� �� ������ �������

��Where, RD, H and –H are rate of deterioration, consistency[kgf] and -H is stickiness [kgf].

4. Estimation Results
First, we discussed the CO2 emissions and DALYs for thedifferences of harvesting area and the product of rice. On theCO2 emission, that was 1.46 kg-CO2eq/kg of polished ricewhich was exported from Tokyo, Japan to Jakarta, Indonesia.
Varying the harvesting area, for instance, California, US fromwhich the product was delivered to Jakarta, Indonesia, that was
3.21kg-CO2eq/kg. In this estimation, the specific CO2 emissionof rice would be affected by the cultivation method. Especially,
the emission of US was 2.75 kg-CO2eq/kg [1].
Next, we investigated the health influence due to the toxic
substances in rice. Using the chronic damage function of
cadmium and arsenic, we obtained 0.0343 DALYs/kg-Cd and0.149 DALYs/kg-As. Also, from the measurement results, Thus,
the DALYs of the following cases: brown rice with storage,
polished one with storage, polished one with exportation andbrown one with exportation, were 0.00684, 0.00180, 0.00702
and 0.00478 DALYs/kg, respectively.
On the quality change, RD and taste score were shown in
Table 1. In general, it is said that brown rice or the rice withcold storage can keep better quality. However, the RD of ricewith ordinary storage at room temperature in this study would
be better. That is, there would be little influence about the riceof short-term storage without cold storage.
Table1. Change of quality
Kind of rice(day of analysis)
Brown rice storage(28. 5.2014)
Ordinary temperature storage(8.7.2014)
Refrigerated storage(8.7.2014)
Polished rice storage(28. 5.2014)
Ordinary temperature storage(8.7.2014)
Refrigerated storage(8.7.2014)
Polished rice exportation(28. 5.2014)
Ordinary temperature storage (8.7.2014)
Refrigerated storage(8.7.2014)
Brown rice exportation(28. 5.2014)
Ordinary temperature storage(8.7.2014)
Refrigerated storage(8.7.2014)

RD
1.09
1.14
1.14
1.17
1.39
1.23
1.09
1.16

Taste score
74
71
73
72
67
70
75
74
75
76
74
75

5. Conclusions
From the above results, probably, there is a good potential toexport Japanese rice with better quality to Asian countries,
even if the delivery method is the system without any cold
storage.
References[1] Myclimate, The Climate Protection Partnership, LCA of
rice: Confidence intervals for avoiding wrong conclusions.
http://eventi.ict.uniba.it/lcafood2010/presentations/thursday-23/parallel-2b/kagi.pdf(Accessed 18. 08.2014)�������������������������������������������������

P-112

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

245

Influence of management practices on life cycle greenhouse gas emissions
from rice production in Yamagata Prefecture, Japan
Katsushi Yokoyama *1 and Kiyotada Hayashi 2
1

Yamagata Integrated Agricultural Research Center, Japan; 2National Agriculture and Food Research Organization, Japan*Corresponding author: yokoyamakats@pref.yamagata.jp

2. Methodology
GHG emissions in rice production between 1990 and 2001
were compared by conducting life cycle assessment analysis
according to the size of each business in Yamagata Prefecture(Figure 1). The data used for the assessment are based on
representative farm management records from 1990 and 2011that were associated with prefectural agricultural extension
services, as well as data obtained from the World Census of
Agriculture and Forestry in Japan. GHG emissions from riceproduction were estimated according to a simplified
assessment method developed by the National Agriculture andFood Research Organization.
GHG emission estimates were subjected to various
assumptions. The assumed size of a business was determinedbased on five categories: 1 ha, 3 ha, 5 ha, 10 ha, and 30 ha. One
type of paddy rice cultivar was considered for 1990, and three
types were considered for 2011. Moreover, the estimationconsidered the paddy rice cultivar cropping ratio,
environmentally friendly rice cultivation attestation area,
agricultural-work commission ratio, mean pest control area,
seedling raising management method, and the preparative
method used for crop drying, among other factors.
GHG emissions were divided into direct emissions frompaddy fields and indirect emissions resulting from theconsumption of energy, materials, and chemicals in thecultivation and harvesting processes. Then, emissions were
estimated with respect to carbon dioxide (CO2), methane (CH4),
and nitrous oxide (N2O), and converted into the amount ofemission relative to CO2.
3. Results
As compared with 1990, a decrease in GHG emissions per
cropping area and per kilogram of product was observed in
2011. In both 1990 and 2011, there were fewer GHG emissions
per cropping area and per kilogram of product when the size ofthe farm was large (Figure 2).
Environmentally friendly cultivation resulted in a low
amount of GHG emissions per cropping area, but high GHG
emissions per kilogram of products, as compared withconventional cultivation in 2011. However, in 1990, as

compared with conventional cultivation, environmentallyfriendly cultivation resulted in reduced GHG emissions per
kilogram of products (Figure 3).
4. Conclusion
In order to win the battle against the negative effects ofglobal warming for rice production, it is essential to increase
the efficiency of production while still enabling expansion of abusiness. Therefore, it is important to secure yield while
practicing environmentally friendly cultivation to improve
manufacturing efficiency.

2010

1990

< 1 ha> 5 ha< 1 ha> 10 ha1 - 3 ha3 - 5 ha5 - 10 ha

1 - 3 ha3 - 5 haFigure 1. Farm sizes (paddy field) in 1990 and 2010
In Yamagata prefecture, Japan
12000
GHG emissions （kg CO2 eq./ha）

1. Introduction
One of the primary agricultural policy objectives in
Yamagata Prefecture is to mitigate greenhouse gas (GHG)
emissions from rice production while decreasing riceproduction costs. These factors are considered be mutuallydependent, and therefore their relationship requires
clarification for each factor to be effectively promoted.
However, knowledge on the relationship between management
practices and their environmental impacts is limited.
In this study, life cycle GHG emissions from riceproduction in Yamagata Prefecture in 1990 and 2011 were
estimated. These two years were chosen for comparison
because there were less farmers associated with a large-sizedbusiness and fewer measures implemented for achieving
environmentally friendly rice cultivation practices in 1990 thanin 2011.

Environmentally friendly practices (2011)

Conventional practices (2011)

11000

Conventional practices (1990)

10000
9000
8000
7000
㻜

㻡

㻝㻜

㻝㻡

㻞㻜

㻞㻡

㻟㻜

farm size （ha）

Figure 2. GHG emissions in farms of different size
Environmentally friendly cultivation

Conventional cultivation

Haenuki (2011)
Hitomebore (2011)

Koshihikari.etc.(2011)
Sasanishiki (1990)

0

2000

4000

6000

8000

GHG emissions (kg CO2 eq./ ha)

10000

Figure 3. GHG emissions for each farm size and ricecultivar (Haenuki, Hitomebore, Koshihikari, and Sasanisiki:
paddy rice cultivar)�������������������������������������������������

P-113

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

246

Potential reductions in life-cycle greenhouse gas emissions from paddy rice production:
assessing the influence of puddling, transplanting density, and irrigation depth
Motoko Shimura,*1 Hidehiro Takahashi,1 Chiharu Ito,2 Makoto Shibuya,2 Kiyotada Hayashi,3and Kenji Matsumori1
1NARO Western Region Agricultural Research Center, Japan; 2Akita Prefectural Agricultural Experiment Station, Japan;
3NARO Agricultural Research Center, Japan*Corresponding author: shimura@affrc.go.jp

1. Introduction
When water is stored in paddy fields for long periods, thesoil becomes reducing and methane (a greenhouse gas; GHG) is
produced. In rice cultivation, low-cost and labor-saving methods
have been emphasized in the past. Recently, approaches that
integrate multiple functions, such as ecosystem preservation andwater quality conservation, have been introduced. However,there have been few studies examining the effects that
introduction of these technologies has had on generation of
GHG. In this study, a life-cycle assessment of these newly
applied technologies and approaches was carried out.
2. Study area and Cultivation techniques
We evaluated reclaimed land in Hachirogata in the Akita
Prefecture of Japan (Figure 1). Non-puddling cultivation is atechnique for planting rice without standing water. A rotary plow
is used to plant the rice in finely crushed soil. Turbid water is
produced when puddling is used, but not with this method,effectively improving water quality. Furthermore, it is possible
to delay irrigation. Thus, the soil is less likely to become reduced
and a smaller amount of methane gas is produced. Sparse
planting is a technique in which the density of the planting stock
is reduced by 30% (21 stock/m2 to 15 stock/m2), reducing thematerial costs of producing seedlings. In deep-water
management, because the amount of water stored in the paddy
field and the number of days of storage is increased, water
purification occurs through denitrification and sedimentation ofsuspended solids.
3. Results and Discussion
We found that with use of non-puddling technology,
methane emissions were reduced to 64% compared to with useof puddling (Figure 2). Furthermore, since turbid water outflow
is suppressed, the eutrophication impact had a negative value, as
the non-puddling approach improves the aquatic environment.
For sparse planting, the amount of methane emissions was
equivalent (97%) with conventional planting (Figure 3).
Furthermore, we evaluated the global warming andeutrophication impact. We used the JLCA database that has beendeveloped using the SimaPro.
As a result, GHG emissions using non-puddling technology
was reduced to 69% compared to with puddling. GHG emissions
using sparse planting was reduced only a small amount to 93%
of that for full planting and the eutrophication impact was nearly
the same (Figure 4).
For deep-water management, GHG emissions did notchange, but the eutrophication impact also had a negative value
due to its water purification effects.
Therefore, non-puddling cultivation is appropriate tosuppress GHG emissions. In addition, from a viewpoint of water
quality conservation, both deep-water management and nonpuddling cultivation are effective.

50km

Figure 1. Study area

Figure 2. Methane gas emissions of rice paddy field: the influence of puddling

Figure 3. Methane gas emissions of rice paddy field: the influence of transplanting density (21, 15 stock/m2)

conventional planting
puddlingsparse planting
puddlingsparse planting
non-puddling
GHG (kg-CO2 eq/kg)

Figure 4. Greenhouse gas emissions of rice paddy field�������������������������������������������������

P-114

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

247

Life cycle CO2 emission of konjac production via an overwintering methodology in Gunma, Japan
Kenji Koido,*1 Yusuke Akaike,1 Yousuke Isshi,1 Keisuke Ide,1 Shou Ushikubo,1Masanori Kou,1 Kenta Komiya,1 Katsuya Shimizu,1 Takumi Minami,1 and Kiyoshi Dowaki1
1Tokyo University of Science, Japan*Corresponding author: koido@rs.tus.ac.jp

2. Scopes and system boundary
The system boundary of konjac production is shown in Fig.
1. The cultivation system comprises field operations, fieldprocesses, energy consumption and storage including
agrochemicals
production, fertiliser
production
andtransportation. Input to the system consists of raw materials
and small corm, while output has konjac and CO2. The
functional unit is kilo gram of konjac.
cultivationRawmaterials

Agrochemicals
production

Fertiliser
production

Energy carriers&
transportation

KonjacStorage

CO2

Field operations

Small corm

Field
processes

Energyconsumption

Fig. 1: System boundary of konjac cultivation
3. Inventory analysis
Inventory data for the cultivation was obtained frominterviews with a farmer in Gunma, Japan. The konjac is aperennial crop as shown in Fig. 2, and it takes two or three
years to produce large-sized corm available for sale inconventional cultivation, where the growing-area ratio for the

first-year, second-year and third-year konjac is 3:6:1. On theother hand, all of the konjac grown with the overwintering
method are harvested after two years cultivation in
overwintering method. For the conventional cultivation,
fertiliser fed to the field has the amounts of 140 kg-N/ha, 140
kg-P/ha and 140 kg-K/ha, while those for the overwintering
one is 120 kg-N/ha, 120 kg-P/ha and 120 kg-K/ha in first year
and 80 kg-N/ha, 80 kg-P/ha and 80 kg-K/ha in second year.
First year

Small
corm

Second-year
product
cormSecond year

First-year
harvested
corm

Second-year
seededcorm

Second-year
harvested
corm

Third year

Third-year
seededcorm

Corm

Third-year
harvested
corm

Third-year
product
corm

Corm

Fig. 2: Cultivation of perennial konjac
4. Results and discussion
CO2 emission for the conventional cultivation is 112
g-CO2/kg-konjac, whereas that for overwintering is 57
g-CO2/kg-konjac, which is half of the conventional CO2 release.
Such small amount of emission was caused by no storage inwinter season for the overwintering. Moreover, fertilisation
process has large amount of CO2 emission for bothconventional and overwintering cultivations in comparison
with other processes as shown in Fig. 3.
CO₂ emission [g-CO₂/kg-konjac]

1. Introduction
Agricultural crops cultivation selling in global chain may
require not only consumer’s health benefits but also ecologicalfriendliness. Especially, konjac is becoming popular inwestern countries as a food and nutraceutical products because
it is effective for dietary food and relieving intestinal ailments[1,2]. The konjac production will be promoted when it isproved that its health benefits and eco-friendliness are high.
Konjac is a perennial crop, which takes two or three years
for production of grown-up corms from planting to harvest andrequires frequent transportation by trucks and much fuels forstorage [3,4]. About 90% of konjac corm annually produced
in Japan is cultivated at Gunma prefecture. To reduce carbon
dioxide (CO2) emission in transportation and drying for storage
and diminish excessive work hours, an overwintering
methodology is a promising cultivation method in comparison
with the conventional one. For conventional methodology,
more transportation and drying for storage of the corms are
required after the cultivation perennially. The overwintering
methodology can omit such a process and drastically reduce
CO2 emission and useful for large-scale cultivation of konjac.
Efficiency in konjac production system is proportional tothe productivity and inverse of the input energy. The higher
efficiency requires either higher productivity or lower input
energy. The latter is reasonable because the former has alimitation in producing konjac with a certain level of nutrient
values. In this study, calculation of a case-based CO2
emission in the overwintering konjac production system isestimated by means of buildup approach to reveal the reduction
effect of CO2 emission for the future promotion of theoverwintering cultivation.

120
100

Planting

80

Plowing
Harvesting

60

Disinfection

40

Fertilising

20

Transportation

0

Storing

Conventional

Overwintering

Fig. 3: Comparison of CO2 emission between conventional andoverwintering cultivation of konjac
5. Conclusion
The results showed that the CO2 emission in overwintering
production was 112 g-CO2/kg, while that in conventional
That indicated the highproduction was 57 g-CO2/kg.
possibility of overwintering konjac corms cultivation to reduce
CO2 emission and excessive work hours for labours.
References[1] Kraemer, W.J. et al. Metab. Clin. Exp. 56, 1149–1158, 2007.
[2] Japan Konjac Association, Research on creation offoreign demand for konjac and expansivity of konjac
export, Research report of MAFF in Japan, March 2007.
[3] Uchida, S. et al. Konjac, from cultivation to processing/selling, Ed: Specialty cultivation technology researchsociety, Rural Culture Association, Tokyo, 2011.
[4] Chua, M. et al. J. Ethnopharmacology 128, 268–278, 2010.

�������������������������������������������������

P-116

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

248

Life Cycle Cost Analysis of Willow Production on Small-Scale Fields
Hidetsugu Morimoto*1, Shigeru Satoh2, Kimiharu Ishizawa3 and Takeshi Arai1
1Tokyo University of Science, Japan; 2Kyoto Prefectural University, Japan; 3Miyagi University of Education, Japan*Corresponding author: m0r1m0t0@rs.tus.ac.jp

1. Introduction
Energy security is one of the most important issues
worldwide. In particular, regions like Japan that have a lower
rate of self-sufficiency should urgently consider sustainableenergy production systems. In this country, the abandoned fieldarea is about 400,000 ha (MAFF, 2012). This issue has been
discussed in recent decades. In May 2014, the Japanese
government proposed the introduction of coordinated renewableenergy production in regional land use in its Act for Renewable
Energy Production in Rural Areas.
This paper addresses renewable energy production on
small-scale fields, such as the use of abandoned fields for thepreservation of agricultural lands. Willow (KKD; Salix spp.)
grown as short rotation coppice, cultivation in three different
places, has superior woody biomass for use in combination withfossil fuels.
2. Methodology
The analysis area is shown Figure 1. The analysis period isover two growing seasons. Three test fields, in Ibaraki (F1),
Kyoto (F2) and Miyagi (F3) prefectures, are in humid
subtropical climates, or Cfa according to the Köppen climateclassification. The respective field areas are 49.22 a (F1), 25 a(F2) and 46.8 a (F3). Since all infrastructure was already in place,calculation began at the leveling stage.
3. Yields and Production Costs
Table 1 shows results for yields and willow production costsof the three fields. All fields had yields per unit area more than
1.0 dry-t/10 a. Sara et al. (2012) reported yields of 0.3–0.79 dryt/10 a in commercially advanced Sweden. In our case, yield was
the same among all test fields and did not depend on planting
density or maintenance times. Weeding two to four times in thefirst season and about twice in the second season was sufficient.
Costs depended on harvesting. When the cost of the firstseason was considered the initial cost, the field with the highest
operation cost was F2 (Table 1). Although field F1 wasmaintained (weeding, herbicide and pesticide application) 12–
14 times per season, its cost was the highest; however, its
operation cost was lowest. The reason is that the harvest cost for
F1 was lower than for the other fields. For the test cultivation, it
was necessary to consider not harvest cost per field unit but pertree unit, because the density varied among the fields. Costs(JPY/tree) were 7.5 (F1), 79 (F2), and 74 (F3). Maintenance ofF3 was the lowest. To keep operation costs low, it was necessary
1st season

Infrastructure

Leveling

Brush
Disposal

Soil
improvement

Weedung

Cutting
Stumping
Collecting
Shipping

Spreading
Plowing

Planting
Planting

MaintenanceWeeding

Spread pesticide/herbicide

System boundary

Plowing

Mulching

Harvesting
HarvestCutting
Collecting
Shipping
Chipping

2nd season

Figure 1. Flow chart of willow production and systemboundary for LCC

to control the harvest.
4. Comparing production costs with other crops
Willow cultivation can be considered one use forabandoned fields. Some willow production costs were lower
than those of rice and sugar cane cultivation in Japan. Willow ismore costly than extensive production of food crops such as
rapeseed and buckwheat, which are cultivated to control
increases in unutilized farmland in Japanese rural areas.
However, given the Optimal Case (OC), which is the lowest
processing (leveling, planting, maintenance and harvesting in
Fig. 1) cost among the willow production fields, willow
cultivation becomes a feasible use of abandoned fields.
5. Comparing cost unit per unit heat value with otherresources
The cost per unit heat value (CHV) of willow is similar tothat of fossil fuel energy but lower than that of woody biomass
given the OC. The CHVOC was 1.88 JPY/MJ, in which heatvalue is 18.8 MJ/dry-t (Satoh et al., 2012) and OC operation cost
is 35,315 JPY/dry-t. Heat values of woody biomass, kerosene
and heavy oil were 0.67, 3.02 and 1.99 JPY/MJ, respectively.
The price of natural gas is lowering because of the shale gas
revolution, and the CHV of willow is inferior to it. However,considering that gas is finite, willow production might be asuperior resource.
6. Conclusion
It is possible to produce willow on small unused andabandoned fields in Japan. The yield is about 1.0 dry-t/10 a,similar to or greater than commercially advanced countries. If
the production process cost can be controlled, the CHV ofwillow would be superior to fossil fuel energy.
References[1] MAFF (2012): REPORT ON RESULTS OF 2010 WORLDCENSUS OF AGRICULTURE AND FORESTRY IN JAPAN[2] Sara G.G. et al. (2012): Environmental assessment of energy
production based on long term commercial willow plantation in
Sweden, Science of the Total Environment, 421-422, pp. 210-219.
[3] S. Satoh et al. (2012): Growth and above-ground biomass
production of a willow clone with high productivity, Salix pet-susu
clone KKD, Journal of the Japan Institute of Energy, 91, 948-953.

Table 1 Amount and cost of production
F1
F2
F3
Field Area [a]
50.0
11.6
46.8
2011. Mar. 2012. Mar. 2012. Apr.
Production period- 2012. Dec. - 2013. Dec. - 2013. Dec.
Plant density [tree/10 a]
900
1,379
751
Weight [wet-kg/tree]
5.21
2.27
5.24
Moisture content [%]
43.0
42.2
45.0
Annual average
1.32
1.34
1.08
[dry-t/10 a]
Operation Cost [JPY/10 a]
79,251
171,998
93,264(60,039)(128,357)(86,356)(JPY/dry-t)
Maintenance content
Weeding rotary tiling
14 times
5 times－brush cutter
12 times－
2 times
Herbicide
12 times
7 times－
Pesticide
2 times
2 times
1 time�������������������������������������������������

P-117

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

249

Life Cycle Inventory Analysis for Small Scale Trawl Fishery in Sendai Bay
Kazuhito Watanabe*1 and Kiyotaka Tahara2
Kwsennuma Regional Promotion Office, Japan; 2Advanced Industrial Science and Technology, Japan*Corresponding author: watanabe-ka825@pref.miyagi.jp

2. Method
System boundary: the inputs are each item of fishing gears,
fishing boat, and fuel oil. The outputs, on the other hand, arelandings and environmental burden. The manufacturing
processes of fishing gears, fishing boat, and fuel oil areconsidered in addition to an immediate operation of the fisheryin this system. However, the abandonment stage of the fishingequipment was excluded from the investigation.
Data collection: Data were basically gathered by aninterview with the WATARI Fisheries Cooperative Association.
The researchers also gathered data through the questionnaires
given to the fishermen.
Inventory analysis: In this research, the researchers took
up CO2 as an index of the environmental burden in the point of
global warming prevention. CO2 emission functional unit ofeach item are calculated by AIST-LCAver5. In addition, theresearchers summed up the amount of CO2 emission by taking
the sum total of CO2 of each item emission in fishery system.
Each of the landings (weight) and the amount of money was
requested in conversion into the CO2 emission functional unit.
Moreover, the researchers calculated the differences of eachfishing boat and monthly changes of CO2 emissions.
3. Results and Discussion
Table 1 shows the amount of CO2 emission of the small
scale trawl fishery and calculation results of the CO2 emissions
as functional unit. The total amount of CO2 emission by thesmall scale trawl fishery (11 boats) was 1,009t per year.
Expressed in ton, the value becomes 4.7t. Moreover, expressedin million JPY, the value becomes 8.2t. Moreover, the ratio of
the CO2 emission in the small scale trawl fishery is calculated.
The influence by the fishing boat and the fishing gear was
small ratios (totally 3%) while the emission by the fuelconsumption was 97% of the whole, and occupied big ratios.
Therefore, in order to reduce the CO2 emissions of small scale
trawl fishery, the policy for reducing direct fuel consumption
Table 1 CO2 emission caused by small scale trawl fishery
Fishing method

Cumulative CO2 emission
t-CO2/ fish catches
t-CO2/t-products/ fish catches
t-CO2/million yen

Small Scale
Trawl Fishery
11 boats total

1,009

4.7

8.2

must be devised. Thus circumstanced, the use of fishing gear
which expanded mesh of fishing net was suggested one of theways to reduce CO2 emission. However, the trade-off between
fish landings and CO2 emissions needs to be considered.
The difference in the CO2 emissions of each fishing boat
was computed (Figure 1). The CO2 emissions of each fishingboat are in the ranges from 6.6 to 12.1t-CO2/million yen
respectively, and the difference of 1.8 times was observed
between maximum value and minimum value. These results
indicated that the difference of information as to fisheryformation in ocean and/or the know-how based on thefishermen’s experiences besides trim parts (engine ability, GPSand fishing gear, etc.). Secondly, monthly changes of CO2
emissions were investigated (Figure 2). The lowest value was
6.5t-CO2/million yen in the August. On the other hand, thehighest value was 10.1 t-CO2/million in May and October. The
difference of 1.5 times was observed between maximum monthand minimum month. When the fish in season was obtained at
the time of its season, it was indicated that CO2 emissions also
tend to become low.
These results were also compared with I-O table analysis
results (2005 edition). It was 9.1 t-CO2/million yen as averagevalue of the whole sea surface fishery. Since the value of thesmall scale trawl fishery was 8.2 t-CO2/million yen, it turned
out to be lower value than that of average value based on I-O
analysis.
LCI analysis was performed for the small scale trawl
fishery in this study. As a result, CO2 emission was cleared.
Moreover, changes of CO2 emission from small scale trawl
fishery was shown in the view point of individual boats andmonthly. Continued case study is required to develop fishery
LCI database in the future.
CO2 emission t-CO2 /million yen

1. Introduction
Small scale trawl fishery is done around the coastal areasof Japan. This is one of the large amounts of fish catchingfishery as well as purse seine fishery and offshore trawl fisheryin Japan. As to the application of LCA for fisheries, thediscussion of functional units is remained. In order to construct
the fisheries and marine products LCI data corresponding tocatch variability, we need dynamic analysis associated with theamount of fishing effort and catches to comprehend thedispersion of data as a reality. Therefore, in this study, we
performed LCI analysis for small scale trawl fishery in
Sendai-bay using multi-year data, and clarified the impact for
the result by the difference of annual fishing catch. In addition,
we considered the suitable indicator for fisheries and marine
products.

14
12
10
8
6
4
2
0
A

B

C

D

E

F

G

H

I

J

K

Names of fishing boats

Figure 1 CO2 emissions of each fishing boat
12

CO2 emission t-CO2/million yen

1

10
8
6
4

Closed fishingseason

2
0
J

F

M

A

M

J

J

A

S

O

N

D

Figure 2 Monthly changes of CO2 emissions�������������������������������������������������

P-118

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

250

Improving the Environmental efficiency of woody biomass utilization: Focusing on the
manufacturing of High Value-added Products in Maniwa, Japan
Dami MOON*1, Naomi KITAGAWA1, Masayuki SAGISAKA1, and Yutaka GENCHI1
1National Institute of Advanced Industrial Science and Technology, Japan*Corresponding author: dami.moon@aist.go.jp

1. Introduction
Generally, woody biomass is often used to produce
bio-energy for converting electricity, heat, or biofuel.
Meanwhile, Okayama prefecture is suggesting thepossibility of material production from woody biomass inorder to enhance the value of woody biomass as a resource.
Maniwa city, which is located in western part of Japan, hasbuilt integrated woody biomass station (IWBS) for a
purpose to produce woody products, such as wood chips,
barks, and chip dust, to promote logging residues utilization
which are collected from forests in rural district.
Furthermore, Okayama prefecture, a large administrative
unit of Maniwa, is to support the planning for producing
high value-added (HVA) products using logging residues
and mill residues in Maniwa, called Master batch of
Cellulose Nanofiber (CNF-MB), and High standard chip
dust (HSD) as a possible alternative to plastic composites.
This study quantified the effects of financial benefits
and Greehouse Gas (GHG) emissions and its efficiency by
the production of HVA products in Maniwa. Overall, thepurpose of this study was to find a better understanding theenvironmental and economic effect of business model for
manufacturing high value-added products.
2. Methodology
There are 6 types of woody products that are
manufactured or planned in IWBS, Maniwa. 4 products ofchip for paper, chip for fuel, bark, and chip dust are
currently being produced, and other 2 products of HSD and
CNF-MB are planned to produce in the near future. For thisstudy, the process for manufacturing woody products cangenerally be divided into five stages : harvest, transport to
the IWBS, sawmilling, manufacturing, and transport to theconsumer. Among these, the process using logging residues
go through only 4 stages except for sawmilling stage.
In order to examine the effects of financial benefits
and Greehouse Gas (GHG) emissions by introduction of
HVA products, two scenarios were proposed : onedescribes the current situation for producing 4 types ofexisting woody products (BAU scenario), and the otherscenario describes the planning situation in which the
production of HVA products such as HSD and CNF-MB
are added from the current situation (HVA scenario).
Quantitative information related to supply and demandof woody biomass has been collected through in-depth
interview by executives of Maniwa lumber cooperation and
the Maniwa city hall during 2011-2013. And specificinformation about manufacturing of CNF and HSD was
obtained by the result of the internal experiment bycooperating with Okayama prefecture. Based on
information, financial expenditure, income and benefit
could be calculated. Total amount of GHG emissions also
could be estimated using the value of amount of woody
biomass input of each product and the value of GHG
emissions per tonnes of woody biomass as shown inequation (1).

GHGt=∑n i=1(A×GHGui)(1)

Here, GHGt is total amount of GHG emissions(kg-CO2eq); A
is amount of woody biomass input of each products (inputton/year); i indicates 5 stages of the process (n=1~5). Where, 1:
harvest stage, 2: sarmilling stage, 3: transport to the IWBS, 4:
manufacturing stage, and 5: transprot to the consumer stage ;GHGu is GHG emissions per unit tonnes of woody biomass.

3. Results
As results, 1,195 JPY/input-ton of benefit can beobtained in HVA scenario, which is increased by up to 100%
compared to BAU scenario of -1,195 JPY/input-ton.
In GHG emissions terms, it was estimated thatapproximately 51 kg-CO2eq/t of GHG are emitted in HVA
scenario, while about 37 kg-CO2eq/t of GHG are emitted in
BAU scenario.
Income-expenditure ratio of 4 types of existing products,
chip for paper, chip for fuel, bark, and chip dust, was 0.8, 1.1,
0.6, 0.8 respectively in BAU scenario. Meanwhile, incomeexpenditure ratio for 4 types of existing products and 2 typesof HVA products of HSD and CNF-MB was 0.8, 1.1, 0.6, 0.8,
1.2, 1.2 respectively. And total income-expenditure ratio for
all products was changed to 1.2 in HVA scenario from 0.9 in
BAU scenario by the effects of the production of HVA
products.
The effect of benefit compared to its GHG emissions ofeach products was calculated, based on the results offinancial benefit and GHG emissions. In BAU scenario,
benefit for GHG emissions for chip for paper, chip for fuel,bark, and chip dust was -0.03, 0.05, -0.03, -0.01 respectively.
Whereas, in HVA scenario, the value for 4 types of existingproducts and 2 types of HVA products of HSD and CNF-MB
was -0.06, 0.02, -0.06, -0.05, 0.02, 0.11 respectively. And thevalue for total products in HVA scenario was turned to 0.02
from -0.03 in BAU scenario by adding the HVA products.
4. Conclusions
This study examined to clarify the meaning of the
production of high value-added (HVA) products which areproduced of woody biomass. The results of this study showthat adding the production of HVA products can improvethe cost efficiency and also be increased the amount ofbenefit compared to GHG emissions to the region.
Through this study, we figured out that production of HVA
products can stimulate economic and environmental
effective than existing products. The next task will involve
in-depth analysis linking substitution effect of woody
products that may guide woody biomass to transition to
useful resources for material production that promoteeconomically and environmentally sound and less carbon
development in rural regions.
Acknowledgement
This work is funded by Japan Science and Technology
Agency (JST) and The Environment Research andTechnology Development Fund (K2364).

�������������������������������������������������

P-119

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

251

Potential for energy saving of dairy farming system dependent upon land utilization
Tatsuo Hishinuma*1
1
Utsunomiya University, Japan*Corresponding author: thishinuma@cc.utsunomiya-u.ac.jp

1. Introduction
Dairy production is an important agricultural sector inJapan, placed second in agricultural production value in 2012.
1.4 million dairy cows produced milk at 18 thousand dairy
farmers, in Japan. Energy from fossil fuels is used at several
processes of milk production system; forage production,
feeding process, milking process, manure handling.
We applied life cycle inventory analysis to dairy farming
system dependent upon land utilization, to reveal amount ofenergy consumption. We discussed potential for energy saving
at the total system.
2. Materials and methods
We investigated a dairy farming system at the Utsunomiya
University (UU) as in Table 1. The dairy farming system at the
UU has 15 hectare roughage production fields. Amount ofroughage production was plenty to feed dairy cows, it was a
type of dairy farming dependent upon land utilization. The
dairy barn has facing out tie stall barn, tunnel ventilation with 6fans, ridge roof. The manure treatment systems were utilizedcomposting process for solid waste treatment and activatedsludge process for liquid waste treatment.
Table 1. Dairy farming at the Utsunomiya University
Parameters
ValuesNumber of heads (dairy cow)
16 headMilking times per day
2 times
Milk production per cow
1,300-5,400 kg/yr
Forage production lands
1,526 aHay fields, 621 aCorn fields (for corn silage), 505 aPasture fields, 400 aPeriod of pasturage
from Apr to Nov
The objective processes to assess the dairy farming systemat the UU were feed production processes (concentrate feed
and roughage), livestock management process, and manure
treatment processes excludes liquid waste treatment, in thisstudy.
The data of fossil fuels consumption and other materials
consumption (fertilizer, pesticide, concentrate feed, medicine,and other chemicals) were collected annual report from thedairy farming system at UU. in 2009. The amounts ofelectricity consumption on equipment at livestock housing andmanure treatment process were measured with an electric
power meter (KW1M-H Eco-Power Meter, Panasonic). The
functional unit was set to 1 L milk production, 4 %fat-corrected milk. The energy consumption factor of materials
were collected LCA software (JEMAI-LCA pro), and articles
and reports.
3. Results and discussion
The total amount of energy consumption was 630 GJ/yr,
10.7 MJ/L-milk. The roughage production process (pasture,rapped corn silage and hay) represented 45% of the totalenergy consumption, which was derived from diesel fuel. Theenergy consumption from concentrate feed (import grains)production process and electricity consumption from dairy

equipment were contributed 23% and 18% of total energy
consumption. From the amount of energy consumption at
monthly variation, energy consumption during Jul to Nov waslarge (Figure1).

Figure 1. Energy consumption of dairy farm at UU
Energy consumption at a rapping corn silage production
process was 8.0-15.0 MJ/TDN-kg, which was large value
compared with the energy consumption at a hay production anda pasture management. Total energy consumption ofself-sufficient roughage was lower than energy consumption ofutilizing imported hay (from Australia).
The large electricity consumption of dairy equipment wasdue to ventilation fan and pump for pipe line milking system.
Especially, electricity consumption of ventilation fan at the
livestock management process varied with seasons, because theventilation fan was run in summer more than in winter, for heat
management. On the other hand, electricity consumption frommilking pump and barn (lightning, electric fences and other)were flat through the whole years (Figure 2).

Figure 2. Electricity consumption of dairy farm at UU
4. Conclusion
Energy consumption from the dairy farming systemdependent upon land utilization was low, compared with thedairy farming system utilizing imported hay. For energy saving,
improvement ventilation system inclding effective heat
management in summer is required, from results of LCI
analysis at dairy farming system at the UU.

�������������������������������������������������

P-120

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

252

Substance Flow Analysis on Agricultural Nutrients focusing Nitrogen and Phosphorus
Takashi Yamamoto*1, Masafumi Mizoguchi1, Kazuyo Matsubae1, Kenichi Nakajima2, Keisuke Nansai2, Tetsuya Nagasaka1
1

Tohoku University, Japan 2National Institute of Environmental Studies, Japan*Corresponding author: b4tm5022@s.tohoku.ac.jp

1.

Introduction
Agricultural nutrient such as phosphorus, potassium andnitrogen are essential elements for food production. Theseelements are called three major elements of fertilizer and thedemand of them has been increasing not only for agricultural
industry but also for other industries, including chemical
(N,P), galvanizing (P), and automobile industry (P).
In 2050, the world population will reach more than 9 billion
and stable food supply is one of the most important issues.
Furthermore, amount of bioethanol production has increased
about three times in the past ten years. From these reasons, thedemand of the three elements will increase as well as that of
fertilizer. [1]The aims of this study were the following three, (1) to grasp
supply and demand of nitrogen and phosphorus using material
flow analysis; (2) to estimate global phosphorus and nitrogen
flows associated with export and import of various
commodities; and (3) to analyze phosphorus and nitrogenconsumption between the Japanese domestic economy and theglobal supply chain using the GLIO model. Furthermore, wehave quantitatively clarified agricultural nutrients consumption
for various countries and discussed the possibilities andbottlenecks of recovery and recycling of N and P from thewaste streams.
2. Method
The method of this study was threefold:(1) Material flow analysis of nitrogen and phosphorus subject
to 2005 in Japan. [2](2) The estimation of nitrogen and phosphorus accompaniedwith each item traded among 231 countries and regions basis of
BACI. [3] 423 types of N and 281 types for P contained
products were chosen from HS code (the number indicating theclassification of international trade items unified worldwide).
(3) The agricultural nutrient flows into the 2005 input-output
model of the Japanese economy, and integrates international
trade statistics on the basis of Global Linkage Input Output(GLIO) model. [3]3. Result and Conclusion
Our results show that domestic flows of nitrogen andphosphorus. (Figure 1, 2) These elements flow in fromoverseas and flow out into soil (374kt-N, 273kt-P) used as
fertilizer and feed. Table1 and 2 show top five countries about
the amount of movement, import, and export of nitrogen andphosphorus accompanied with international trade. Figure 3 and4 show the balance of nitrogen and phosphorus. Regarding
nitrogen, North America and China are the key stakeholders,which have large amount of excess balance of nitrogen.
Looking at phosphorus, extracted phosphate ore in Morocco
was mostly exported, and consumed in Asian countries,
including India and China. North and South America and China
have large amount of excess balance of phosphorus, while mostAfrican countries, even P ore mining countries, face on the lowbalance of P.
From the estimated results, nitrogen and phosphorus are flowin as fertilizer and feed, and mostly ended up to flow out theenvironment in the developed countries. It is expected that theconsumption of nitrogen and phosphorus will increase as the
economic development in BRICS and VISTA. The more

effective utilization of these nutrients and the geopolitical andenvironmental governances are strongly required in coming
decades.

Figure 1 Domestic flowsof nitrogen

Figure 2 Domestic flowsof phosphorus

Table 1 Major international nitrogen flows
Top 5 flows㻌
From
CanadaTrinidad and Tobago
Australia
USA
USA

To
USA
USA
Japan
Mexico
China

kt-N
4,034
2,958
1,873
1,239
1,095

Top 5 exporter㻌Top 5 importer㻌
Share [%]
3.4
2.5
1.6
1.0
0.9

USA
Japan
China
India
Germany

kt-N
17,086
6,531
5,308
5,164
4,777

Share [%]
14.5
5.5
4.5
4.4
4.0

RussiaUSA
Australia
CanadaUkrainekt-N
13,161
9,398
5,462
5,324
4,429

Share [%]
11.2
8.0
4.6
4.5
3.8

Table 2 Major international phosphorus flows
Top 5 flows㻌
From
JordanUSA
MoroccoMorocco
USA

To
India
China
India
USA
Canada

kt-P
438
426
415
366
314

Top 5 importer㻌
Share [%]
2.3
2.3
2.2
1.9
1.7

India
China
BrazilGermany
USA

kt-P
1,961
1,033
899
739
712

Share [%]
10.4
5.5
4.8
3.9
3.8

Top 5 exporter㻌MoroccoUSA
RussiaChina
Jordan

kt-P
3,219
2,834
2,032
1,208
858

Share [%]
16.7
13.3
11.1
9.9
9.3

Figure 3 Estimated nitrogen balance

Figure 4 Estimated phosohorus balance
4. Reference[1] F.O.Licht, “World Ethanol Markets”, 2006
[2] Matsubae, K., et al., Chemosphere, 84, 767-772, 2011[3] Nansai, K., et al., Environ. Sci. Technol. 46, 155-163, 2012�������������������������������������������������

P-122

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

253

Water Security and Socio-Economic Metabolism in China: Toward an Integrated Assessment
Tao Wang* and Seiji Hashimoto
Ritsumeikan University, Japan*Corresponding author: a.t.wang@gmail.com
1. Introduction
An adequate and secured supply of clean water is criticalto human health, economic development, and environmental
conservation. In China, per capita freshwater availability isbarely a quarter of the world’s average [1]. Water security thus
poses a serious challenge to the planet’s largest population andthe second largest economy. The effects could spill over to theentire globe by shaking food supply and prosperity.
Material resources, with numerous interwoven relations towater, constitute another pillar for human development.
Socio-economic metabolism and material flow accounting
offer a framework to compile a great variety of biomass, fossil
fuels, minerals, and material commodities [2]. Their methods
and theories are promising to be employed to investigate thewater-material nexus. By combining water use assessment withmaterial flow analysis, this present research attempts to explore
the material-driven water demand in China and vice versa.
2. Water demand and socio-economic metabolism
The consumptive water demand maintained a moderate
upward trend in China in the past three decades, growing from
480 giga-m3 (Gm3) in 1990 to 610 Gm3 in 2012. The directmaterial input, a measurement of the country’s socioeconomic
metabolism, more than quadrupled in the same period [3], andthe gross domestic product (GDP) increased by a factor of nine[4]. The fact suggests that to a certain degree water
consumption has been decoupled from material resource
demand and economic growth in China.

transmission and treatment, 45 Gm3 of tap water was
distributed to the industries, service sectors, and households. 36
Gm3 of post-use wastewater flows were collected and cleaned
in municipal wastewater treatment plants, and merely 3.2 Gm3of treated water was reclaimed and recycled (without counting
onsite and internal recycling). The present water cycle in China
is basically linear and open to environmental sources and sinks.
About 40% of the raw water intake may be evaporated, leaked
away, or dissipatedly used throughout the cycle.
Vast capital and materials have been devoted toconstruction of municipal water infrastructure. A material stock
accounting has been conducted to compute the quantity of
specific infrastructure (e.g., length of pipes and capacity oftreatment plants) and the intensity of typical construction
materials per infrastructure. It shows that some 2.8 gigatonnes(Gt) of materials were embodied in the infrastructure stock asof 2012, including 1.8 Gt in drainage and sewage pipes, 0.52
Gt in water supply pipes, 0.30 Gt in water facilities and 0.12 inwastewater facilities. In terms of material composition, about
66% of the stocks are sand and gravels, 30% are cement, and4.1% are cast iron and steel tubes and components.

Figure 2. Municipal water cycle in China, 2012,
in giga-m3/a. Data source: [6].

Figure 1. Consumptive water demand in China, ca. 1970–2012.
Agriculture claims nearly two-thirds of China’s water
demand (Figure 1). Most of this consumption is connected tohuman demand for biomass materials, including staple foods
and livestock [4, 5]. Industrial sectors account for another 20%
of total water consumption. >60% of the industrial water has
been consumed by production of minerals and basic materials(e.g., pulp and paper, metals, plastics, and chemicals) [5]. For
the country as whole, approximately three-fourths of its water
consumption is directly driven by demand for materials(including biomass and minerals).
3. Municipal water system and material stocks
Municipal water comprises no more than 10% of China’s
water demand (Figure 1), nonetheless it needs water in better
quality, usually meeting drinking standards. The municipal
water cycle in China has been characterized and quantified in
Figure 2. In 2012, approximately 57 Gm3 of raw water was
drawn from surface and underground water bodies. After

4. Summary
This research examines water use and its connection withthe demand for material resources in China. It also assesses themunicipal water cycle and material stocks in the water
infrastructure. The study may help pay the way toward an
integrated assessment of water and material resources insocio-economic metabolism.
Acknowledgments
This study is supported by Ritsumeikan Global Innovation
Research Organization (R-GIRO) under the research of water
reclamation and recycling in Asia.
References[1] Cheng, H., et al. Environ. Sci. Technol. 43(2): 240–244, 2009.
[2] Eurostat. Economy-wide Material Flow Accounting: A Compilation
Guide. Luxembourg: Statistical Office of the European Union, 2007.
[3] Wang, H., et al. J. Ind. Ecol. 16(4): 481–492, 2012.
[4] National Bureau of Statistics of China (NBSC). China Statistical
Yearbook 2013. Beijing: China Statistics Press, 2013.
[5] NBSC. China Statistical Yearbook on Environment 2013. Beijing:
China Statistics Press, 2013.
[6] Ministry of Housing and Urban-Rural Development of China. China
Urban Construction Statistical Yearbook 2012. Beijing: China
Planning Press, 2013.

�������������������������������������������������

P-123

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

254

Water Footprint Assessment of Machine Tool
Jahau Lewis Chen,*1 Yen-Bou Chen,1 and Hua-Chih Huang2
1

National Cheng Kung University, Taiwan; 2ITRI, Taiwan*Corresponding author: jlchen@mail.ncku.edu.tw

1. Introduction
Water is critically important to human life. However, thedemands for fresh water in many regions are much more thanthose can load. The concept of water footprint came fromvirtual water which can help us roughly understand the water
consuming of a product manufacturing process and after
services. Hoekstra and his student published water footprint
manual in 2011[1]. Berger and his coauthors [2] studied thewater footprint of three Volkswagen passenger cars. The
research team of professor Bras [3-4] estimated the water
footprint of a 2011 Ford Focus vehicle. Zhao and his coauthors[5] analyzed the water footprint of three machining processes.
This paper presents a methodology for assessing water
footprint of machine tools. Detail assessment steps andcalculation process for life cycle of machine tools is describedin this paper. The difficulty in inventory process
and data selection during water footprint assessment will bepresented. A case study is used to explain the capabilities of the
proposed methodology.
2. Water footprint
The definition of water footprint [1] is classified into threekinds of water that are green water footprint, blue water
footprint and grey water footprint. Green water means raining
water stored in ground or plants then evaporates in growth ortransfer into products. Blue water footprint indicates the water
use from groundwater or surface water. Grey water footprint is
the amount of water use in diluting wastewater emission toachieve discharge standards. Water footprint of machine tools
only has blue and grey water.
3. Water footprint inventory and data selection
The system boundary for water footprint inventory is the
direct water consumptions in machine tool life cycle, such as
production of materials, manufacture processes of eachcomponent, use of electricity and lubrication oil, andtransportation. The calculation of water footprint and data
selection is in accordance with different life cycle stages. In
material stage, the mass and specification of every componentof machine tools are investigated. The SimaPro 7 database wasselected in material stage for water footprint calculation.
During manufacture process stage, the inventory information
includes the kind of machining processes and the remove mass
or volume in each process for each component. The Ecoinvent
database and information in literature [5] were selected in
manufacture process stage for water footprint calculation andcomparison. In transportation stage, Ecoinvent database is used
for calculating water footprint. In use stage, the life of machine
tools assumed to be 7 years old. Data of water footprint forelectricity consumption in Taiwan is calculated based on the
structure ratio of different electricity generation source in
Taiwan. The coefficient of water footprint for electricity
consumption in Taiwan is 574.78 gal/MWh.
4. Water footprint of machine tool
The EMVC machine tool designed by ITRI is selected as
design example to demonstrate the capabilities of proposed
method. The specification of EMVC machine tool is shown in
Table 1. The processes of water footprint calculation of EMVC

machine tool can be divided into four stages, such as material,
manufacture processes, use and transportation stages. Thismachine tool is transported 180 km by using the 16 tons truck.
The value of water footprint of EMVC machine tool is shownin Table 2. It is obvious that the water footprint of machine tool
is dominated by the use stage.
Table 1. Specification of EMVC machine tool
EMVC machine toolSpecification
Weight10242.299 kg
Maximum Output Power
11 kW
Operation Rate of Spindle
70 %Life of Spindle
7 years
Electricity Consumption of Peripheral
1 kW
Equipments
Transportation
180 kmTable 2. Water footprint of the EMVC machine tool
Water footprint
Life cycle stage(ton)
Material
17.877
Manufacture process
21.541
Transportation
2.081
Use
1162.581
5. Conclusions
This paper presented the calculation result for water
footprint assessment of machine tool. The EMVC machine toolcase demonstrated the capability of the proposed method.
Acknowledgments
This Study is supported by The Intelligent Machinery
Technology Division, Mechanical and Systems ResearchLaboratories, ITRI (Industrial Technology Research Institute)of Taiwan.
References[1] Hoekstra, A.Y., A.K. Chapagain, M.M. Aldaya and M.M.
Mekonnen. The Water Footprint Assessment Manual:
Setting the Global Standard. Earthscan, 2011.
[2] Berger, M., J. Warsen, S. Krinke, V. Bach and M.
Finkbeiner. Water Footprint of European Cars: Potential
Impacts of Water Consumption along Automobile Life
Cycles. Environmental Science & Technology 46:
4091-4099, 2012.
[3] Semmens, J., B. Bras and T. Guldberg. Vehicle
Manufacturing Water Use and Consumption: An Analysis
Based on Data in Automotive Manufacturers’
Sustainability Reports. Journal of Life Cycle Assessment
19(1): 246-256, 2013.
[4] Kim, H.C., T.J. Wallington, S.A. Muller, D. Berdish, B.
Bras, F. Tejada and T. Guldberg. Water Use in the Life
Cycle of Light-Duty Vehicles. Proceedings of theInternational Conference on EcoBalance 2012, C1-08,
Yokohama, Japan, November 20-23, 2012.
[5] Zhao, F., J. Ogaldez and J.W. Sutherland. Quantifying in
Water Inventory of Machining Processes. CIRP Annals
Manufacturing Technology 61(1): 67-70, 2012�������������������������������������������������

P-124

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

255

Evaluation of Water Use in Paddy-Rice Production
on the Basis of Differential Water Footprint
Susumu Uchida*1
1

Ibaraki University, Japan*Corresponding author: uchida@mx.ibaraki.ac.jp
1. Introduction
Water use in paddy-rice production was evaluated on thebasis of a differential water footprint (DWF) that had beendeveloped for analyses of water resource. Previous studies
have proposed various water flow indicators that can be used toanalyze water resources [1-4], and some have proposed waterflow indices comparable with carrying capacity, taking into
account the subject area of water supply [5, 6].
However, essential water use flow is difficult to define andevaluate. In a previous study [7], we introduced a new concept
of “acceptable delay” for the continuous evaluation of thewater resource burden and its sustainability. This is the time
period within which water is consumed without problems, andis defined for each type of water use. We assumed the amountof water consumed throughout this period, and regarded its rate
as the essential water use flow. The ratio of this water use flow
to total supply flow in an objective basin is defined as water
stress. Furthermore, we defined the area as DWF on the basisof acceptable delay, in which the water use flow is met by
precipitation. By integrating DWF with respect to time, thetotal water resource burden is obtained corresponding to eachwater use as stock. The unit of area multiplied by time wasdefined as the integral water footprint (IWF).
Agriculture, in particular paddy-rice production, is themost important water-consuming sector in Japan. In this study,
we evaluated water resource consumption of paddy-riceproduction, using the Ibaraki prefecture as a case study.

the amount of precipitation. The effect of considering
acceptable delay is shown around point A in Figure 1. This part
corresponds to irrigation with the same amount of water as thesubsequent irrigations, indicated as peaks to the right. However,this irrigation has seven days of acceptable delay in contrast toother irrigations having a shorter acceptable delay. This caused
lower water stress on the days indicated, shown as broader
peaks of DWF.
A DWF exceeding 1 indicates that more area is required toprovide water for irrigation than the actual cultivation area.
Figure 1 shows the maximum DWF reached is 60, however,this does not necessarily represent a lack of water. If the excess
is time related, farmers can share water resources with eachother by shifting the timing of irrigation, or by storing water inponds. To analyze the total water balance, annual integration to
IWF is needed. They were 1.11 ha/ha-a for 1998 and 2.01 for
2001, which proves that paddy-rice production is based on thedebt of water from other neighboring areas.

2. Methodology
In the analysis, we constructed scenarios of riceproduction on the basis of the standard schedule recommended
by the Ibaraki prefecture, meteorological data, andphenological model. Daily water use was estimated bysimulation on the basis of the scenario, in which water demandis met first by precipitation, irrigation water only being used in
the case of shortage. Data on precipitation at Tsuchiura and theflow of the Seimeigawa River was used. From this estimation,water use and its sustainability were evaluated throughderivation of DWFs and IWFs.

Acknowledgments
This work was supported by JSPS KAKENHI Grant
Number 25550045.

3. Result and discussion
Figure 1 shows the obtained DWFs per cultivation area for1998 and 2001. For both years, the DWF showed higher values
in the latter half of the cultivated period, when pulsed irrigation
with much water was needed. The DWF in 2001 is greater thanin 1998. This difference is thought to reflect the difference in

4. Conclusion
In this study, the effect of introducing the concept ofacceptable delay was restricted because the schedule of water
use in the scenario was assumed to be tight. However, this newconcept will be more useful in the evaluation of various
controls in water-resource consumption by considering thedependency of water stress on acceptable delay, together with
DWF and IWF.

References[1] Vanham, D., and G. Bidoglio. Ecol. Indicators, 26: 61–75,
2013.
[2] Ridoutt, B. G., et.al. J. Clean. Prod., 28: 127–133, 2012.
[3] Federal Office for the Environment FOEN. The
Ecological Scarcity Method – Eco-Factors 2006, Bern,
Switzerland: FOEN, 2009.
[4] Pfister, S., et al. Environ. Sci. Technol., 43 (11):4098–4104, 2009.
[5] Stoeglehner, G., et al. J. Clean. Prod. 19: 1677–1686,
2011.
[6] Gleeson, T., et al. Nature, 488: 197–200, 2012.
[7] Uchida, S., and K. Hayashi. J. Life Cycle Assess. Jpn.,10(1): 40–48, 2014.

Diffential water footprint(ha/ha)

60
50
40

1998

A

30
20

2001

10
0
27-Apr 4-May 11-May 18-May 25-May 1-Jun

8-Jun 15-Jun 22-Jun 29-Jun

6-Jul

13-Jul 20-Jul 27-Jul 3-Aug 10-Aug 17-Aug 24-Aug 31-Aug 7-Sep

Figure 1. Differential water footprint of paddy-rice production in Ibaraki, Japan�������������������������������������������������

P-125

EcoBalance 2014

The 11th International Conference on EcoBalance
27–30 October 2014, Tsukuba, Japan

256

Development of Water Footprint Inventory Database of Asian Countries
Soya Iida,*1 Yuya Ono,1 and Norihiro Itsubo1
1
Tokyo City University, Japan*Corresponding author: g1383101@tcu.ac.jp

1. Introduction
The scarcity and the ubiquity of water resources havebeen increasing all over the world. These problems are causedby the sudden population growth and the improvement ofquality of life in the developing country. Additionally, disease
and malnutrition are widespread due to the insufficient of foodfrom water shortage. Water Footprint (WF) is an evaluation
method measuring environmental impacts related with water
use through the entire life cycle of products and service.
China’s economy has developed rapidly, but serious water
problems have emerged because of the increases in water
demands and wastewater. It is concerned that water problem
may restrict the sustainable growth in Asian country.
2. Purpose
The purpose of this research is to develop water footprint
inventory database which enables us to account consumed
water amount with the differentiation in types of water resourcein China by province. We adopted input-output tables andstatistical tables of China to develop water footprint database in
China. Applying input-output table make it possible toaggregate direct water consumption and indirect water
consumption in upstream of the supply chain. Development of
the water footprint inventory database of China classified toprovince is carried out. We will conduct case studies withJapanese companies that have factories in China using thisdatabase to verify the quality of our output.
3. Method
The database on water considering the type of water
resource (rain water, irrigation water and ground water) and theform of water (water use and water consumption) was
developed in this study. We have estimated 135 sectors of
direct water use and consumption of the Chinese input-output
table in agriculture, forestry, fishery, industry and other service
industries in this study [1, 2]. In addition, we use statistics dataof 2007 to cope with age targeted for the input-output tables [3,4]. We have applied statistics of “China statistical yearbook
2007” in the agricultural, fishery, industry and other service
industries sectors, “China forestry statistical yearbook 2008” inthe forestry sector [5]. At this time, we divided into sevenregions in China and estimated the water consumption
considering the type of water resource in the agricultural
production of each (Figure 1). The seven regions divided are
the northeast (Heilongjiang, Jilin, Liaoning), east (Shandong,
Jiangsu, Shanghai, Anhui, Zhejiang, Jiangxi), south (Fujian,Guangdong, Hong Kong, Macao, Hainan, Guangxi Zhuang
Autonomous Region), west (Henan, Hubei, Hunan), southwest(Chongqing, Guizhou, Sichuan, Yunnan, Tibet Autonomous
Region), north (Beijing, Tianjin, Hebei, Shanxi, Inner
Mongolia Autonomous Region), and northwest (Qinghai,
Gansu, Shaanxi, Xinjiang Uygur Autonomous Region, Ningxia
Hui Autonomous Region).

Figure 1. LCI DB development method
estimated that 8.6E+11m3 direct water consumption in the
agricultural sector of China's total, it can be said to be valid theresults of this study. In the northwestern and northern regions,
it was found that they supplement most by irrigation because
there is little precipitation. In the south region, it is a thriving
industrial region in the country, direct water consumption in the
agricultural sector was less than the other regions. In the future,
we will estimate direct water use and consumption in othersectors, and develop database of China.
References[1] Food and Agriculture Organization(FAO). Chapter 6 ETc
Singlecrop
coefficient.
http://www.fao.org/docrep/X0490E/x0490e0b.htm(Accessed 25.04.2014)[2] National Institute for Agro-Environmental Sciences(NIAES).
Meteo
Crop
DB.
http://meteocrop.dc.affrc.go.jp/(Accessed 21.05.2014)[3] Jing Huang, Hai-Lin Zhang, Wen-Jie Tong, and Fu Chen:
The impact of local crops consumption on the water
resources in Beijing. Journal of Cleaner Production 21:
45-50, 2012.
[4] Zhuoying Zhang, Hong Yang, and Minjun Shi: Analyses
of water footprint of Beijing in an interregional
input-output flamework. Ecological Economics 70:
2494-2502, 2011[5] National Bureau of Statistics of China: China Statistics
Press, 2009.
[6] Liqiang Ge, Gaodi Xie, Caixia Zhang, Shimei Li, Yue Qi,
Shuyan Cao, and Tingting He: An Evaluation of China’s
Water Footprint. Water Resource Manage 25: 2633-2647,
2011.

4. Result & Conclusion
In this study, direct water consumption in the agricultural
sector whole of China became 9.2E+11m3. As a comparison
with existing research, Liqiang Ge et al. [6] have been�������������������������������������������������