ISSN 1880-8468
Technical Report ofInternational Development Engineering
国際開発工学報告

TRIDE-2013-01

February 14, 2013

Abstracts of Master Theses
Presented in February 2013

Department of International Development Engineering,
Graduate School of Science and Engineering,Tokyo Institute of Technology
http://www.ide.titech.ac.jp/TR

Preface

Master theses of Department of International Development Engineering, Tokyo Institute ofTechnology were presented successfully on August 3, 2012 and February 14, 2013. This
technical report consists of the abstracts of those theses.

ⅰTechnical Report of International Development Engineering
TRIDE-2013-03m
Table of Contents(Completing in September 2012)
Application of Knowledge Management System in Development Project:
A Case of World Heritage Site in Luang Prabang, Lao P.D.R.......................................................................................................... Tetsuro OKUMURA

1

Antenna Pattern Reconstruction Using Spherical Harmonics and Its
Application to Double-Directional Channel Modeling...................................................................................................................... Yang MIAO

5

Decomposition of Gas-phase Benzene using Ag/TiO2 Packed Nonthermal
Plasma Catalyst Reactor.................................................................................................. Christian PANGILINAN

9Study of Private Participation Influence on the Efficiency Performance ofMunicipal Water Supply Management in Indonesia................................................................................................. Nirmala HAILINAWATI

13

Contact-less Heartbeat Detection Method by using Microwave....................................................................................................................... Yanran LIU

17(Completing in March 2013)
Numerical

Study

on

Localized

Heavy

Rain

using

LatestUrban

Parameterizations and High-Resolution Sea-surface Temperature........................................................................................................... Kumiko NAKANO

21The Decomposition of Methyl Orange over Titania Coated Magnetic
Activated Carbon.
...................................................................................................... Takuro HARAGUCHI

25

Selective Catalytic Reduction of Nitrogen Oxides with Propene over Ag/CeO2TiO2 Catalyst.................................................................................................................... Yang YANG

29

Estimation of Co2 Emission from Urban Freight Transport in Khon Kaen,
Thailand............................................................................................................... Shinsuke MOGIⅱ

33

Which Factors Influence the Relief Goods Convergence in Humanitarian
Logistics?
.......................................................................................................... Tsunenori ANDO

37

Economic Operation of Large-Scale Photovoltaic Power Plants under
Uncertainty.............................................................................................................. Junichirou ISHIO

41

Lifetime Prediction of Concrete Mixed with Seawater against Chloride Attack
and Carbonation................................................................................................................. Hiroki OHARA

45

Effect of Temperature, Oxygen Concentration and Solution on the
Degradation of Paint on Steel in Marine Exposure Tests and Accelerated Test................................................................................................................... Yu KAMIYA

49

Synthesis of Zeolites from Lake Sludge as Ammonium Adsorbent Materials
Estimating CO2 Emissions of an Automobile Company in Global Supply
Chain: Case Study of Locational Conditions in Thailand........................................................................................................ Yuhki KAWAHARA

53

Microbial Community Analysis of the Methane Fermentation Process Treating
Glycerol.................................................................................................................. Kohei HATTA

57

Moral Hazard Issues Contractor and Subcontractor in Construction Overseas
Project............................................................................................................... Shotaro FUKAO

61

An Analysis on Consumers’ Preferences for the Residential Photovoltaic
System Focused on Its Long-Term Operation........................................................................................................ Toshiya MORIZUMI

65

Quantitative Analysis of the Atmospheric Boundary Layer Flow Field using
Doppler Lidar...................................................................................................................... Ayako YAGI

69

Application of Virtual Reality(VR) Panorama for Townscape Monitoring in
the World Heritage Site of Luang Prabang , Lao P.D.R.
................................................................................................................... Kenta YOKOI

73

Equilibrium Extraction of Light Rare Earth Metals with PC-88A as
Extractant......................................................................................................... Naoto YOSHIMURA

ⅲ

77

Optimal Design and Control of a Buck Converter Used for Energy Harvesting................................................................................................................... Jiawei WANG

81

Preparation of Acidic Activated Carbon from Bagasse Fly Ash.................................................................................................................... Zhaoxia GAN

85

Bioethanol Concentration Process using Solvent Extraction....................................................................................................................... Haihao HU

89Image Based Real-time Vehicle Classification for ETC...................................................................................................................... Cong GENG

93

Outdoor Experiments on Human Bio-Meteorology at the Hottest City Tajimi
Using a New Wearable Measurement System.............................................................................................................................. Rui SHI

97

Distributed Video Coding By Selective Line Pruning andMulti-frame based Interpolation..................................................................................................................Phan Tuan TAI

101

Determinants of Mobile Learning Acceptance in Luang Prabang:
Towards World Heritage Site Preservation Awareness Promotion.......................................................................................................... Yew Siang POONG

ⅳ

105

APPLICATION OF KNOWLEDGE MANAGEMENT SYSTEM IN DEVELOPMENT PROJECT:A CASE OF WORLD HERITAGE SITE IN LUANG PRABANG, LAO P.D.R.
Student Number: 10M18022

Name:

Tetsuro OKUMURA

Supervisor: Shinobu YAMAGUCHI
Jun-ichi TAKADA

開発プロジェクトへの知識管理システムの活用：ラオス人民民主共和国ルアンパバーン世界遺産地域のケース
奧村 哲郎
本研究は、ラオス・ルアンパバーン世界遺産地域における情報システムに関する重要な知識や情報を継承するための知識管理システムを構築し評価することを目的とする。提案された 3 種類のシステムの中から、クラウドコンピュー
ティングサービスを用いた方法が最適であると判断され試行した。有効性、必要性、持続可能性の側面から評価を行った結果、導入したシステムは知識を継承するのに効果的なツールであることが判明した。同時に、情報が管理共有されることで業務効率が高まることが示唆された。

1

Introduction

Tech have been working with the local ICT team since2003 have changed over time. Each student had worked
on specific tasks reflecting local needs and their own
skills. From 2005 to 2008, web log was existed built on
Zope. ICT team recorded acquired knowledge and daily
activities in the log daily. However, due to broken harddisk drive, all the data were lost. So the project keeps
limited information such as web application and several
design documents such as database structure diagram.
With this incident, a keen need to manage project data inmore effective manner came into attention.
AccordingtoGorelick,projectknowledge
management is “basically, systematic approach to
optimize access appropriate and feasible advice,knowledge, and experience located in somewhere in theorganization for individuals or team in organization”[4].
Milton proposed knowledge management model, andthere are two methods of knowledge succession fromtrained person to beginners [5]. Connection approachsucceeds knowledge in direct way. This is the mosteffective method if succeeding person and succeeded
person located at same place on the same time.
Collection approach proposes knowledge bank whichaccumulates explicit knowledge, and collect knowledge
from skilled person, then knowledge bank transfer
knowledge to beginners. This method is considered as
possible solution under high human mobility because it
does not require people staying at the same place at thesame time.
Reflecting these literature review, to hand over skills
and knowledge to new team members both for local ICTteam and Tokyo Tech team, appropriate knowledge
management system has become urgent requirement toavoid project knowledge and skill from losing.

Information and Communication Technology (ICT) has adramatic impact on achieving specific social andeconomic development goals as well as playing a keyrole in broader national development strategies [1].
However, it is said that 85% of e-government project waspartially or completely failed in developing countries due
to big gap between design and local situation [2].
Luang Prabang, Lao PDR was inscribed as UNESCO
world heritage site in 1995. As a part of tri-partite
cooperation among Tokyo Tech, the Department ofWorld Heritage Luang Prabang (DPL) of Laogovernment and UNESCO, the significant collaboration
started with development and operation of a databasemanagement system (DBMS) at DPL in 2003 [3].
During the course of its operation, the local team faced
the difficulty of updating its database for more than one
year in 2010. Field survey identified three aspects which
are contributing to the situation: 1) Technical aspect, 2)
human resources aspect and 3) external aspect.

2 Problem Analysis and Research Objectives
2.1 Problem Analysis
The field survey took place between February and Marchin 2011 to analyze the conditions at local site. As a result,it was identified that the project was facing difficult
situation of not being able to succeed project knowledge
and skills. Among multiple factors, one of the significant
reasons was the high human mobility of the teammembers, both at local ICT team and Tokyo Tech team.
Since DPL was upgraded to the department from local
office in 2009, tasks and duties were expanded.
Therefore, due to lack of training time for new teammembers who joined after 2008, they were experiencing
difficulties in getting previously trained skills fromexperienced members who had been working since thevery beginning of the project.
On the other hand, a number of students from Tokyo

2.2 Research Objectives
This study aims to build and evaluate a system toeffectively transfer project knowledge and skills for1heritage management in Luang Prabang, Lao P.D.R.
Specifically, the study took three steps: First, local
environment and users’ needs were carefully analyzed.
Second, feasible and sustainable knowledge management
system was studied using comparative analysis of several
potential methods. Third, usability, effectiveness andsustainability of introduced system were evaluated.

editable.
4) Easy to search contents: It is preferable to have afunction to obtain necessary contents easily fromhundreds of accumulated information. Also user will
be changed as time advances, system are required toobtain necessary contents in simple way for
beginners.
Considering two preconditions and four local needs,
three knowledge management system solutions weresuggested.
1) In-house system: Local team members can build
their own knowledge management system byutilizing PHP with PostgreSQL. PHP is a script
language to build web application. PostgreSQL is adatabase server. Both are widely used around theworld.
2) Free and open source software: Free software named
MediaWiki, which is a wiki package written in PHP
and is originally developed for Wikipedia, has all therequired functionalities [6]. “Wiki is a website thatallows the creation and editing of any number ofinterlinked web pages via a web browser using asimplified markup language or a text editor”(Wikipedia).
3) Cloud computing: Internet services to share thedocuments, such as Google Drive, Evernote [7] andDropbox, can also fulfill all the requirements.
As the local team has already been introduced PHP
and PostgreSQL for the database development andmanagement [8], they can implement the knowledge
management system with the flexibility to match theirown needs. In contrast, the technical succession of thissystem itself in the future is an additional burden to the
local team. Considering software development, PHP and
PostgreSQL would be possible to update for long term
because they has large number of users and developers.
Therefore, sustainability of this solution depends onfitting design with local needs.
MediaWiki requires PHP and PostgreSQL, but theteam does not need to launch a new server. MediaWiki isequipped with full-text searching functionality.
MediaWiki can handle text, graphics and data files, anduser can edit the contents easily. Although it is free
software, customization to respond to specific local
needs is difficult.
Cloud computing does not need any local server.
Instead, everything can be accessed via Internet. Amongthe cloud computing services, software as a service(SaaS) is the most suitable service to the end users.
Users can run the application via Web browser and data
files are stored on cloud servers. There are free services

3 Methodology
Method to build knowledge management system follows
three steps based on the Milton’s model [5]: 1)
Comparative study for knowledge management system,2) training of building and using knowledge management
system and 3) building of knowledge management
system.
3.1 Comparative

Study
Management SystemforKnowledge

Field observation and brainstorming with local ICT team
identified two preconditions for applying local situationand four local requirements for knowledge management
system.
There are three preconditions to be carefully
considered for introducing the system: 1) Low speed
Internet access, 2) unstable power supply, 3) expected
number of users. DPL has ADSL Internet connection
which can download up to 1 M bps (bit per second).
However, there are around 30 computers sharing theconnection. Also, the connection is unstable. Powersupply is not stable especially in rainy season from April
to October. Because of that, hard disk drives in PC crash
two or three times a year. As the number of users forknowledge management system is around 10, the system
can be designed for relatively smaller scale.
System requirements were discussed in DPL in
October 2011. Following are the four requirements
identified to build appropriate knowledge management
system.
1) Accessibility: Accessibility means that project
information and knowledge need to be easily shared
between ICT team and Tokyo Tech team members aswell as among the internal members of DPL.
2) Ability to store various kinds of file formats:
Because project information and knowledge wererecorded in various kinds of file formats, the system
is required to store information in different format.
For example, design document for database system
was created by Excel format, and teleconference
minutes were recorded as text file.
3) Data modifiability: Project activities have possibility
to be modified according to local needs andfunctionality of the system after first development.
Thus, created contents in the system should be2

Table 1: Identified contents (as of June 2012)that satisfy the requirements. In developed countries, theintroduction of cloud computing is massive as they candrastically save the cost for system administration.
However, it is not necessarily feasible solution in the
project site due to very slow Internet connection.
Although, it is considered that this solution is asustainable way to keep data.
As a result of discussion with local ICT team,Evernote was selected as a knowledge management
system. Three reasons were raised for the introduction ofEvernote: 1) Easiness to introduce the system, 2)
maintenance-free and 3) ability to share contents
between Tokyo Tech and local ICT team members.
First, Evernote does not have complicated installationon the server because it has client software for PCs as
well as web interface. Users including local ICT teamand Tokyo Tech team can concentrate in contents
management. Second, Evernote does not require internal
administrator to maintain the system. Evernote corp.
provide system maintenance and software updates. Third,
Evernote enables to share all contents between local ICTteam and Tokyo Tech team because contents are stored in
the server on the Internet. Synchronization is performed
using client software on PC.

3.2 Training for Building andKnowledge Management System

Category
Technical document
Project report
Presentation to public
Minutes
Knowledge management instruction
Administrative document
Total

Number ofcontents
133
44
88
75
9
5
355

Source: created by author, July 2012

Fig. 1 An example of operational manual
Source:Using

Evernote created by ICT team, 2010conference between local ICT team and Tokyo Tech team.
Knowledge management instruction refers to documents
for building and introduction training of knowledge
management system. Administrative document includes
contents which are not categorized as above such as listof members, useful address list.
Local ICT team members conducted input activity
after introductory training. Input activity follows thestandard template which require an individual to fill title,
author, tag (keyword) for all the contents. Evernote canaccept text form, so text files were typed directly. Other
file formats were uploaded as an attachment.

The next step of introducing Evernote as knowledge
management system was the provision of training on theuse of client software and method of knowledge
management. Seven training components for knowledge
management were developed as followings: 1)
Installation of Evernote client software; 2) input method
for contents; 3) search necessary contents; 4) backup andrestore; 5) get previous updating data; 6) clipping web
page to Evernote; and 7) practice of inputting materials.
In order to conduct training, relevant knowledge
management system manuals were prepared. The
training was conducted at ICT center in mid-December
in 2011.
3.3 Building
Knowledge
Management

4 Evaluation Analysis
To evaluate usefulness, effectiveness, and sustainabilityof introduced knowledge management system using
Evernote, two evaluation methods (case trials andinterviews) were conducted.
4.1 Case Trials
Case trial simulates the situation where users arerequested to use knowledge management system toretrieve necessary information. It has two objectives.
First, advantages and problems of using Evernote are
expected to be identified. Second, users can experienceand become familiar with Evernote. Four cases areprepared simulating past activities: 1) Creating map ofbuilding usage using ArcGIS, 2) how to transmit GIS
skills from experienced member to the beginner, 3)

SystemPast project information was retrieved from hard disks inTokyo Tech and local ICT team. In total, 355 contents
were identified.
Table 1 lists the identified contents. Technicaldocuments mainly include system design documents,
training materials, and software operational manual (Fig.
1). Project report was composed of activity report createdby students. Presentation to public refers presentationmaterials shared at local workshop and symposium.
Minutes includes records of regular weekly tele-3

building environment for database application and 4)
fixing bug in PHP script. Ten members, four from local
ICT team and six from Tokyo Tech team, participated incase trials from January to April, 2012. Case trials wereconducted in pairs and one member observed
participant’s behavior such as referring manual andhaving question to other members, and recorded themwith time.
The case trials identified three major findings. First,
GIS manuals effectively assisted beginners’ operation.
Further, GIS manual/video can be a supportive tool to
explain specific skills and knowledge for both beginners
and skilled members. Second, screen shot is useful tocope with language barrier. Users can understandprocesses in the manual easily with visualization.
Additionally, videos are especially useful for beginners
to understand operations of software with step-by-step
explanations. Third, manuals for PHP application need tocater for different level of users. Members who did notjoin the application development need specification
document to understand basic of the system. Because
members involved in the development have alreadyknown system’s specification, they need only script
diagram or log of bug fix to remind system schema.
4.2 Interviews
To supplement case trials analysis, interviews wereconducted to participants to obtain their feedbacks on thefollowing three aspects: 1) Usability of the introduced
knowledge management system, 2) necessity of theintroduced knowledge management system, 3)
sustainability of the introduced knowledge management
system. In addition, participants were asked to provide
their opinion on individual case trials. Interview
conducted to all participants of case trials. Interview
illustrated three major findings.
1. Evernote functioned as a tool to avoid knowledge
loss: Evernote provided a platform to accumulate
and share knowledge and information between
Tokyo Tech and local ICT team. Evernote also
contributed to efficient work by reducing frequencyof asking help from others.
2. Evernote cannot fully replace implicit knowledge:
implicit knowledge, such as technical tips or“know-hows” was accumulated through user’s
experience. Data stored in Evernote are not as
intuitive as human experience, but remain as a goodsource of information repository.
3. Updating contents in efficient manner isimportantforsustainableknowledge
management: Updating contents is needed forlong-term use of Evernote. This research identified

four principles to record technical documents inEvernote efficiently: 1) table of contents should becreated to facilitate overview to each project, 2)high resolution screen shots is recommended to be
used, 3) captions should be written in each screen
shot to give supplemental explanation, 4) reviewing
manual with colleagues is important to checkmistake and to promote understandings.

5 Conclusions
In the world heritage town of Luang Prabang in Lao
P.D.R., various activities using information technology
have been introduced since 2003. Valuable knowledge
and skills related to heritage management accumulated
over time were not successfully shared nor utilized byproject members due to high human mobility. To copewith such condition, knowledge management system wasintroduced following the model proposed by Milton.
Evernote was selected as a most feasible method ofknowledge management system, reflecting local
condition. A total of 355 contents were covered inEvernote, including technical documents, project
documents, workshop information as well as local
training manuals.
Evaluation of established knowledge management
system was carried out using four case trials andinterviews for the users. Evaluation analysis revealed
that Evernote can serve as a potential tool to avoid
knowledge loss. In addition, Evernote was found toeffectively function to improve work efficiently.
However, it is also important to note that Evernote
cannot replace implicit knowledge through experience.
Finally, continuous updating of contents was found vitalfor sustainable knowledge management.
Acknowledgement
This work was supported by JSPS KAKENHI Grant Number 21404001.

References[1] Digital Opportunity Initiative, “Creating a Development Dynamic; Finalreport of the Digital Opportunity Initiative,” Accenture, Markle Foundation,
UNDP, 2001.
[2] Heeks R. B., “Most eGovernment-for-Development Projects Fail: How Can
Risks be Reduced?,” iGovernment Working Paper Series, Paper No. 14, IDPM,
University of Manchester, 2003.
[3] Yamaguchi, S. Y., Takada, J., Ooka, N., Kawaguchi, Y., (2006) “Application ofInformation Communication Technology to Promote Sustainable Development– Case Study: Luang Prabang, Lao PDR,” 42nd Congress of International
Society of City and Regional Planners (ISOCaRP), Istanbul, Turkey.
[4] Gorelick, C., April K., and Milton, N., 2004, “Performance Through Learning:
Knowledge
Managementin
Practice,”
Burlington,
MA:
Butterworth-Heinemann.
[5] Milton, N., 2009, Project knowledge management, Cincom systems Japan,
pp.7-11. (in Japanese)[6] Wikipedia, [online] http://en.wikipedia.org/wiki/Wiki, (accessed on Oct. 20,
2011)[7] Evernote. [online] http://evernote.com (accessed on July 2, 2012)[8] Okumura, T., Leong, C., Takada, J., and Yamaguchi, S. Y. , “Analysis on
Sustainability of Free and Open Source Software (FOSS) Application~Database Management of World Heritage Site of Luang Prabang, Lao
P.D.R.~,” JASID 12th spring conference, Tokyo, pp. 137-138.

4

Antenna Pattern Reconstruction Using Spherical Harmonics and
Its Application to Double-Directional Channel Modelling
Student Number: 10M51605

Name: Yang MIAO Supervisor: Jun-ichi TAKADA

To characterize antenna, the acquisition of its three-dimensional radiation pattern is very important. Spherical antenna
measurement is a practical approach to measure antenna pattern in spherical geometry. However, due to the limitationof measurement range and measurement time, the measured samples may either be incomplete on scanning sphere, or
be inadequate in sampling interval; there is a need to extrapolate and interpolate the measured samples. Spherical wave
expansion provides a good approach to reconstruct antenna pattern in spherical geometry, and its cut-off (band-limited)property makes it possible to be analysed by the sampling theorem. This research identifies the limitation of patternreconstruction by conventional algorithm, and proposes a novel approach to virtually deviate the antenna position by thephase shift of measured data. Numerical investigations are conducted to validate the proposed algorithm for both complete
and incomplete data.

1

Introduction

2 Spherical Wave Expansion Technique
The major concerns for wireless propagation channels
recently are the measurement and modelling of directional properties of channel. The introduction of doubledirectional channel model enables to evaluate the performances of different antennas in certain propagation environment. To study the double-directional channel, the acquisition of full antenna pattern, the complex polarimetricantenna response in angular domain, is very important.
This thesis focuses on analytic and continuous antenna
pattern reconstruction from measured samples. Sphericalantenna measurement is a practical approach to measure thepattern of antenna under test (AUT), through scanning overa spherical surface in both azimuthal and elevation dimensions. However, due to the limitation of measurement time,coarse sampling interval is not sufficient, and there is a needto interpolate the measured pattern. On the other hand, due
to the limitation of measurement set-up, the scanning may
not be conducted on the whole sphere but only on somepart of it, therefore the measured samples are incomplete
and there is a need to extrapolate the incomplete data.
A review of antenna pattern extrapolation together withinterpolation has been done and the related work are generally concluded as the iterative Fourier transform approach[1][2][3], the iterative spherical wave expansion approach[4][5][6], and the equivalent current approach [7][8]. The
first two approaches utilize the plane wave representationand the spherical wave representation of antenna radiatedfield, respectively. While plane wave model has infinite
angular resolution regardless of antenna size, the sphericalwave model has finite angular resolution determined by antenna size. In this research, spherical wave function is utilized as the tool to reconstruct the antenna pattern.
The main objective of this research is to systematicallystudy the antenna pattern reconstruction for both complete
and incomplete spherical measurement by using sphericalwave functions, and to investigate the effect of samplinginterval and measurement range on the reconstruction accuracy.

Spherical wave functions (SWF) [9], are homogeneous solutions to vector Helmholtz equation in the spherical coordinates. The radiation pattern outside the minimum sphereof antenna can be expanded into a weighted sum of spherical wave functions, i.e. spherical wave expansion (SWE)[9] :√ ∑∑ ∑
Qsmn Fsmn (r, θ, ϕ) (1)E(r, θ, ϕ) = k η2Nn

s=1 n=1 m=−nwhere:
m: mode indices for ϕ direction
n: mode indices for θ direction
Fsmn (r, θ, ϕ): SWF, TE (s = 1) and TM (s = 2)
mode SWF compose of a complete orthogonal set
Qsmn : spherical wave coefficient (SWC)√k η: coefficient to ensure the normalization condi1tion that unit SWC corresponds to 1 W 2 , k is thewavenumber
N : truncation number
The minimum sphere of an antenna is defined as thesmallest possible spherical surface, which is centred at thecoordinate origin and could enclose the antenna completely.
In this thesis, truncation number is determined by the minimum sphere radius r0 as N ≥ [kr0 ], where the square
brackets indicate the largest integer smaller than or equal
to kr0 . The highest spatial frequency for a radiating fieldis 1/λ, according to the sampling theorem, the minimum
sampling interval should be λ/2, thus the sampling number
is no more than [2kr0 ] per circumference of the minimum
sphere. To represent the radiation field, the spherical wave
5

Continuous flow-type experiments were carried out
using a single-stage plasma driven catalysis system.

gas detection tube system was used to monitor
ozone concentration. Carbon balance, CO2 yield andselectivity were calculated as follows:[CO2 ] + [CO ] + n [ by-products ] + 6 [C6 H 6 ] x100
6 [C6 H 6 ]0
[CO2 ]YCO , % =x100
6 ([C6 H 6 ]0 − [C6 H 6 ] )CB =2

SCO2 , % =[CO2 ] x100
[CO2 ] + [CO]High-voltage supplied to the reactor was
generated by connecting the reactor to a neontransformer, (LECIP Co. Ltd., 100-A-15HCS)
connected to a volt slider and a 50 Hz, 100 V AC
power supply. The applied voltage, V, was measured
with a 1000:1 high-voltage probe (Agilent
Technologies, N2771B) and the charge, Q, wasdetermined by measuring the voltage across a 10 nF
capacitor connected in series with the ground line of
the reactor. The signals were recorded by an
oscilloscope (GW Instek, GDS-1072A-U) by
averaging 64 scans. Waveform data obtained fromthe oscilloscope were processed to produce V-Q
diagrams. The discharge power, Pdis, and the specificinput energy, SIE, to the reactor were calculatedusing the V-Q Lissajous method. From the V-Q
diagram, the area was calculated corresponding to
the electric energy consumed per voltage cycle andthen was multiplied to the frequency of the feeding
voltage to obtain discharge power. The specificinput energy was calculated by dividing thedischarge power with the gas flow rate.

Figure 2. Flow chart of experimental set-up

The nonthermal plasma reactor is made ofquartz tube with (OD=15 mm, L=200 mm, t=1 mm).
Stainless steel rod with D=9 mm was fixed inside
the center of the quartz tube as a high-voltage
electrode and silver paint was coated outside thereactor as the ground electrode. The silver paint wascoated to make a length of 50 mm around theoutside body of the quartz tube to make the effective
length of the reactor. Catalysts were placed within
the effective length of the reactor and the plasma
was generated by passing low-current high-voltage
across the electrodes of the reactor.

2.3. Activity Experiments
Preliminary experiments involved initialozone concentration generated by the plasma, effectof plasma on benzene concentration, and effect of
the catalyst on ozone concentration. Initial ozone
concentration at specified voltages were determinedby allowing the feed gas to pass through the plasma
reactor without benzene and the catalysts. The effectof plasma on benzene concentration was tested byallowing the pollutant to go through the reactor
while the plasma was turned on and testing its
concentration afterwards. Finally, the effect of thepresence of the catalyst on ozone concentration wastested by placing the catalysts within the plasma
region and turning on the plasma then testing theresulting ozone concentration.
Before doing activity tests, the catalysts in
the reactor were saturated with gas-phase benzene
until adsorption equilibrium was reached. An initialconcentration of 200 ppm of benzene was used forthe experiments. After adsorption equilibrium,
activity tests were performed by varying the applied
voltage to the reactor and effluent composition andconcentrations were monitored.

3. Catalyst Characterization
TG-DTA was performed on the base TiO2 todetermine the effect of temperature on the catalyst.
During the calcination step for IP method,
depending on the temperature used, the resulting
TiO2 phase may either be anatase, rutile or a mixtureof both. Based from the TG-DTA results, only an
exotherm for the evaporation of water at ~100oC
was present
indicating no other physical orchemical transformations occurred on the catalyst.
For the IP method, a calcination temperature of
500oC was chosen.
The bulk crystal structure and crystal size ofthe prepared catalysts were analyzed by XRD(Figure 3). Results show that all prepared catalysts
retained its anatase crystal structure with a crystal
size of ~20 nm. With increasing Ag loading, theintensity of the anatase peak at 2θ = 25o slightly
decreases. Although silver was deposited on the
catalyst, no peaks relating to silver or any of its
oxides were detected by XRD due to the small
amount of the loaded metal on TiO2.

2.4. Chemical and Electrical Analysis
Benzene concentration and its by products
were analyzed by using GC-MS equipped with andEquity-5 column. GC-TCD was used to monitor
CO2 and CO concentration of the effluent gas and a6
dP̄n|m| (cos θ1 ) −jmϕ1
number should be no less than [2kr0 ], therefore the bande
sin θ1 · · ·dθwidth (truncation number) should be at least [kr0 ]; by in..


.


creasing the bandwidth, the evanescent components of the(9)
XB =  dP̄ |m| (cos θ )

l1
n
−jmϕ

l2
field can be retained.
esin θl1 · · ·


dθ
..
For the application of SWE, generally SWC are un.
known; measured field samples at certain sphere areachieved to calculate SWC, once the SWC have been Achievable pseudo-inverse problem for complex matrix
solved, the field can be calculated at anywhere outside the must satisfying:antenna minimum sphere. Generally, there are two apπ2π(+ 1) × () ≥ N (N + 2)
(10)proaches to achieve SWC: inner product method and least∆θ∆ϕsquare solution method.
where ∆θ and ∆ϕ are the sample interval for θ and ϕ di1) Inner product method:
mensions respectively.
m
1(−1)
Q1mn = (2)(2)√(hn (kr))2 k η∫ 2π ∫ π
3 Antenna Pattern Reconstruction(4)[Eθ (r, θ, ϕ) · F1,−m,n (r, θ, ϕ) · θ̂
ϕ=0

for Complete Spherical Measurement

θ=0
(4)

+ Eϕ (r, θ, ϕ) · F1,−m,n (r, θ, ϕ) · ϕ̂] sin θdθdϕ

Through complete spherical antenna measurement, complete field samples over the whole scanning sphere are
(2)
1
d
2
{ kr
)2
achieved: E(θl1 , ϕl2 ), θl1 ∈ [0 : ∆θ : π], ϕl2 ∈ [0 : ∆ϕ :d(kr) (krhn (kr))} + n(n + 1)(
kr(3) (2π−∆ϕ)]. Therefore, the main task for antenna pattern re∫∫construction should be interpolation. Conventionally, SWC(−1)m 2π π
(4)[Eθ (r, θ, ϕ) · F2,−m,n (r, θ, ϕ)· can be calculated from measured complete samples, and in√k η ϕ=0 θ=0terpolation can be conducted with the reconstruction of an(4)θ̂ + Eϕ (r, θ, ϕ) · F2,−m,n (r, θ, ϕ) · ϕ̂] sin θdθdϕtenna pattern by SWE.
According to the sampling theorem and the bandThis method has a strict requirement that the electric
limited property of SWE, the sampling number per circumfield should be given over the whole scanning sphere.
ference should be at least twice the truncation number 2N ,2) Least square solution method:that is, the sampling interval in measurement should be less2π
than 2N. In practical measurement, AUT is not necessar1
1
m m
√ (2)
ily
locatedin the center of global coordinate. For the sameamn = k ηhn (kr) √ √) Q1mn(−2π n(n + 1) |m|
AUT, the minimum sphere radius when it is deviated from(4) coordinate center is obviously bigger than the radius when
it is centred, therefore, the required sampling number per√ 1 d(5) circumference (sampling interval) for deviated case should
bmn =k η(krh(2)n (kr))
kr d(kr)
be bigger (smaller) than that of the centred case.
m m
1
1
√ √
(−
) Q2mnTaken open-ended rectangular waveguide (OERW) as
2π n(n + 1) |m|an example of AUT for illustration, the following figure
shows the reconstruction error for both deviated case and




a11
Eθ (θ1 , ϕ1 ) sin θ1
centred case with the change of sampling number per cir..
 .. 
cumference.
 . 


.




amn 
 Eθ (θl1 , ϕl2 ) sin θl1  .. 
..
Nyquist . Case1: Deviated AUT.
 = (X H X)−1 X H  (6)sampling
Case2: Centered AUT
 b11  Eϕ (θ1 , ϕ1 ) sin θ1 
Nyquist0.25 condition
when sampling
 . 


.
..
 .. 
N=2 condition




0.2
when
 bmn Eϕ (θl , ϕl ) sin θl 
1
2
1
N=6



..
..
0.15
N=6
.
.
N=7
1

Q2mn =Error(2)hn (kr)where,

(
X=


XA
−XB

XB
XA

N=2
N=3
N=4

0.1

)
(7)

0.05



−jmP̄n|m| (cos θ1 ) −jmϕ1esin θ1 · · ·sin θ1



..




.


XA =  −jmP̄ |m| (cos θl )n−jmϕl2
1
e
sin
θ
·
·
·


l
1
sin θl1


..
.

0

(8)

5

N=8

10
15
20
Sampling number per circumference

25

Figure 1: Error of reconstructed pattern by conventional
interpolation approach for both deviated AUT andcentred AUT

7pore volume slightly decreased from 0.2809 cm3/g
to around ~0.2557 cm3/g indicating that the pores
might have been blocked by the silver as it wentinside the pores of the catalyst. DPN and DPH
catalysts showed no significant change in surface
area, pore volume and pore diameter.

Surface morphologies and active metal
dispersion on the catalyst surface was imaged using
SEM-EDS. Figure 4 shows the different SEM
images of the prepared catalysts and the base TiO2
and Figure 5, its Ag metal dispersion. The images
show that IP catalysts formed small aggregate
structures covering the catalyst surface due to its
calcination where as for DP catalysts, did not havethese aggregate structures. Digital mapping of Ag
on the catalyst surface show that with increasing Ag
loading, the Ag density on the surface also increases.
DP catalysts showed very good Ag dispersion on the
catalyst surface as compared to IP catalysts. This is
attributed to the long aging time of 24 h in the IP
method, as compared to only 2 h for DPN and 30
mins for DPH. This allowed the silver salt to enter
into the pores of the catalyst by capillary forces
instead of retaining it on the surface.

Figure 4. SEM images of Ag/TiO2 catalysts

Figure 5. SEM-EDS Ag digital mapping of Ag/TiO2 catalysts
Table 1. Summary of ICP-AES and BET results

Catalyst
Figure 3. XRD patterns of prepared catalysts

TiO

Table 1 shows the characterization results of
ICP-AES and N2 adsorption by BET method of the
prepared catalysts. Actual Ag concentration of
Ag/TiO2 catalysts were determined using ICP-AES.
For IP catalysts, 3% and 5% showed only ~13%difference from the theoretical value but around
45% for the 1% Ag. For DPN catalysts, 21%~23%
difference was observed, consistent for all Ag
loading amounts. However for DPH catalysts, thedifference reached up to 87%~95%. Even after 24hof sample digestion, DPH samples still contained aresidue that was not dissolved within the solution.
This was not observed from the other preparation
methods. It is speculated that this residue contains
the silver metal.
Surface area, pore volume and pore
diameter of the prepared catalysts were analyzed by
BET method using Autosorb 1 (Quantachrome). For
IP catalysts, with increasing Ag loading, surface
area decreased from 64.95 m2/g of the base TiO2 to49.00 m2/g in the 5% Ag loaded catalyst. The pore
diameter increased with Ag loading, 17.30 nm fromthe base TiO2 to 20.88 nm in 5% Ag/TiO2, the total

2

IP1
IP3
IP5
DPN1
DPN3
DPN5
DPH1
DPH3
DPH5

Theo Actual%Diff
wt% wt%

-

-

-

1.02
3.04
5.02
1.00
3.01
5.04
1.00
3.00
5.02

0.56
2.63
4.34
0.77
2.34
3.93
0.12
0.15
0.24

45.19
13.38
13.56
23.49
22.13
21.93
87.95
94.85
95.13

Surface PorePoreArea, Vol., Diameter,nmm2/g cm3/g
64.95 0.2809 17.30
61.64
53.54
49.00
64.73
64.60
63.28
65.54
65.14
64.94

0.27000.25400.25570.28430.2717
0.26640.27830.27820.2767

17.52
18.98
20.88
17.56
16.80
16.82
17.03
17.14
17.04

4. Activity Results
The results of the effect of catalysts on ozone
concentration are presented in Figure 6. It showsthat ozone generation is directly proportional to theapplied SIE to the reactor with the initialconcentration reaching up to ~1940 ppm at thehighest voltage setting. Placing catalysts inside thereactor decreased the discharge gap resulting in theformation of ozone at lower SIE values. A decreasein ozone concentration was also observed due to thecatalytic decomposition of ozone to oxygen gas andits reaction with silver or silver oxide to form silver(II) oxide.
8

DECOMPOSITION OF GAS-PHASE BENZENE USING Ag/TiO2
PACKED NONTHERMAL PLASMA CATALYSIS REACTOR
Student Number: 10M51611

Name: Christian PANGILINAN

Supervisor: Hirofumi HINODE

This research describes the decomposition of gas-phase benzene using Ag/TiO2 catalysts in a plasma driven
catalysis system. Ag/TiO2 catalysts were prepared using three methods: IP, DPN and DPH with varying Ag
loading amount and were characterized by TG-DTA, XRD, SEM-EDS, ICP-AES and N2 adsorption (BET).
Benzene decomposition, by-product formation, carbon balance, carbon dioxide yield and selectivity andozone utilization were used to measure catalytic performance of the prepared catalysts.
dioxide and carbon monoxide yield and selectivity,and ozone utilization.

1. Introduction
Recently, raising environmental awarenessand promoting environmental protection is
becoming an issue of growing concern as our worldis becoming more and more polluted.
Industrialization has led to the emission of various
substances in our atmosphere that pose significant
threat to both human and ecological life.
One major group of these pollutants arevolatile organic compounds (VOCs) and theemissions by industrial, commercial and agriculturalprocesses are a major source of air pollution and is aconcern for human health and the environment.
Depending on their structure and concentration,
VOCs together with nitrogen oxides and sulfur
containing compounds reacts in a series of complex
chemical reactions once released in the troposphere.
These leads to the formation of secondary pollutants
such as photochemical smog, secondary aerosol andsuspended particulate matter and tropospheric ozone,
acid deposition, and formation of organosulfuric
compounds. Prolonged exposure to these chemicals
are detrimental to human health and to theenvironment. [1-4].
In this research, treatment of gas-phasebenzene as a representative VOC with silver ontitanium dioxide catalysts using a nonthermal
plasma driven catalysis (PDC) system wasinvestigated. Benzene is commonly used in
manufacturing processes of materials such as
polymers, plastics, resins and adhesives. Improper
use and storage of this chemical leads to its
vaporization and exposure increases the risk ofcancer and other illnesses.
The specific objectives of this research are as
follows: (1) preparation of Ag/TiO2 catalysts using
three different methods and characterization of the
prepared catalysts, (2) nonthermal plasma reactor
system assembly, (3) determination of catalytic
activity of the prepared catalysts, and (4) evaluationof catalytic performance through pollutant
decomposition, by-product formation, carbon

2. Methodology
2.1. Catalyst Preparation andCharacterization
Catalysts were prepared by three methods:
impregnation method (IP), deposition-precipitation
with NaOH[5] (DPN) and deposition-precipitation by
H2O2[6] (DPH) with varying Ag loading of 1%, 3%
and 5% by weight. A summary of the methods ispresented in Figure 1. Anatase type TiO2 was
obtained commercially from Sakai Chemical
Industry Co., Ltd., Japan and was used as the basecatalyst. The catalysts were characterized by TGDTA, XRD, SEM-EDS, ICP-AES and BET.

Figure 1. Catalyst preparation methods

Conventional IP method was compared todeposition-precipitation methods to determine theeffect of metal dispersion on catalyst performance in
PDC system. In the DP methods, slow addition of
the precipitating agent facilitates the precipitation ofsilver on the catalyst surface as compared to aging
in IP method.

2.2. Experimental Set-up
Figure 2 shows the flow chart of theexperimental set-up and the reactor used.
90.2

Table 1: OERW simulation environment

Aperture location

Observing distance

27.3mm0.84λ × 0.37λ1) deviated case: move along
x-axis by λ from center(N=6)2) center-located (N=2)
45.5λReconstruction Error

Wavelength
Aperture size (a× b)

Deviated AUT
Centered AUT

0.15

0.1

Acceptablemeasurement
range when N=2

0.05

Acceptablemeasurement
range when N=6
N=6

N=2
N=3

N=7
N=8

N=4
0
110

It is not difficult to find the following points. Firstly, foreach case, the reconstruction accuracy will stay the samewith adequate sampling numbers, and the bigger the truncation number is, the higher the reconstruction accuracy willbe. Secondly, the Nyquist sampled, 2N points per circumference, is not sufficient to completely reconstruct the pattern; 2(N + 1) points per circumference is enough, therefore the sampling interval should be no more than 2(N2π+1) .
Thirdly, comparing between both cases when truncated at
N = [kr0 ] respectively, the reconstruction accuracy for thedeviated AUT case from measured samples with adequate
sampling interval is lower than that for the centred case; therequired sampling interval for the deviated case is smaller
than the centred case. In conclusion, the antenna patternreconstruction by conventional approach is limited by the
AUT location in global coordinate.

4

120

130

140 150
θscan

160

170

180

Figure 2: Error of reconstructed pattern with different
measurement range for both deviated and centred AUT
case

Obviously, the reconstruction accuracy will stay thesame with adequate measurement range; for each case, thebigger the truncation number is, the higher the reconstruction accuracy. However, when truncated at N = [kr0 ]respectively, the reconstruction accuracy for deviated caseis lower than the reconstruction accuracy for the centredcase. According to sampling theorem, the un-measured
range on scanning sphere should be less than the biggest allowable sampling interval 2(N2π+1) . Therefore, the measurement range for elevation and azimuthal dimension should
be no less than π(1 − N1+1 ) and 2π(1 − 2(N1+1) ) respectively. Obviously, the bigger the minimum sphere is, thelarger the measurement range should be. In conclusion, thereconstruction accuracy and the requirement for measurement range are limited by the AUT minimum sphere, furthermore limited by AUT location in global coordinate ofmeasurement set-up.

Antenna Pattern Reconstruction
for Incomplete Spherical Measurement

Through incomplete spherical antenna measurement, incomplete samples on some part of the scanning sphere areachieved. Here is a typical incomplete measured data set: 5 Proposed
Algorithm Applying
E(θl1 , ϕl2 ), θl1 ∈ [0 : ∆θ : θscan ], ϕl2 ∈ [0 : ∆ϕ :Translational Phase Shift Tech(2π − ∆ϕ)]. The main task for antenna pattern reconstruction of the incomplete measured samples should be extrapniqueolation as well as interpolation.
Conventional iterative SWE algorithm [4] [5] could ex- A novel approach is proposed to virtually transfer the AUT
trapolate and interpolate the incomplete measured samples: position by the translational phase shift of measured samples, assuming the scanning sphere radius is much bigger
1. extend samples by zero-padding to cover entire than the shifted distance. Through shifting the deviatedsphere
AUT pattern to coordinate center, the minimum sphere radius will always be minimized; both the requirement for
2. calculate SWC using extrapolated data
sampling interval and measurement range will be lower, at
3. calculate new field samples by SWE using SWC in the same time the reconstruction accuracy will be increased
correspondingly. The proposed algorithm guarantees thestep 2same requirement of both sampling interval and measure4. updated data in step 3 are replaced by the measured ment range for the same AUT, and the antenna pattern reconstruction will not be limited by AUT location any more.
samples within the scanned area
Given the incomplete measured samples distributed as
11ππ
Steps 2 to step 4 are repeated iteratively.
0 : π6 : 2π
3 in θ dimension and 0 : 6 : 6 in ϕ dimension,
For practical measurement, AUT is not necessarily lo- for the deviated OERW case in Table 1, Figure 4 and Figcated in the center of global coordinate system. Considering ure 5 shows the E-plane amplitude of reconstructed pattern
the deviated and centred OERW in Table 1 again, given ab- by conventional algorithm and proposed algorithm respecπ, the tively; obviously, the proposed algorithm could well reconsolutely sufficient sampling interval ∆θ = ∆ϕ = 60
effect of measurement range on reconstruction accuracy for struct the incomplete samples while the conventional algoboth cases are investigated as in Figure 2.
rithm could not.
10

Catalytic activity was tested on benzene
decomposition using PDC treatment. Results(Figure 7) show that DP catalysts were able to fully
decompose benzene at low SIE values while IP
catalysts were only able to reach ~20%
decomposition. The low efficiency of IP catalysts is
attributed to the decrease in its surface area from
calcination.

no other carbon containing compounds in theeffluent after treatment giving 100% selectivity tocarbon dioxide. Carbon balance (Figure 8) andcarbon dioxide yield (Figure 9), however, were notable to reach 100% which indicates the formation ofintermediates such as carbon peroxy radicals or
plasma polymerization of the pollutant which were
deposited on the catalyst surface.
Ozone concentration after the treatment(Figure 10) was also monitored and results show adecrease in ozone concentration (from Figure 6)
which indicates a synergetic effect of the system inthe decomposition of benzene as well as ozone by
PDC, with DPN5 catalyst fully decomposing theozone produced.

Figure 6. Effect of catalysts on ozone generation

Figure 10. Ozone concentration after PDC treatment

5. Conclusions and Future Work
Prepared DP Ag/TiO2 catalysts were able tofully decompose benzene at low SIE compared to IP
catalysts which only reached ~20% with DPN
catalysts also able to decompose the ozone
generated in the system. Although benzene was
fully decomposed, carbon balance and carbon
dioxide yield was not able to reach 100%. Further
increase in applied SIE is expected to give better
results.
Future work includes the following:
decomposition kinetics; use of different reactor
configurations; use of different types of catalysts;
and modification of process parameters such asvoltage frequency and background gas.

Figure 7. Benzene decomposition

Figure 8. Carbon balance

References
[1]

[2]

[3]
[4]
Figure 9. Carbon dioxide yield[5]

Benzene decomposition is not the only factor
considered in catalyst performance. GC-MS only
detected benzene, oxygen and carbon dioxide with

[6]

11

Chen, H. L., Lee, H. M., Chen, S. H., Chang, M. B.,
Yu, S. J., Li, S. N. Environmental Science
Technology, 43 (2009) 2216-2227.
Dewulf, J., Van Durme, J., Leys, C., Van
Langenhove,H.
AppliedCatalysis
B:
Environmental, 78 (2007) 324-333.
Whitehead, J. C. Pure Applied Chemistry, 82, 6,(2010) 1329-1336.
Passant, N.R. Retrieved from http://pubs.rsc.org,
doi: 10.1039/9781847552310, published October 31,
2007.
Sandoval, A., Aguilar, A., Louis C., Traverse, A.,
Zanella, R. Journal of Catalysis 281 (2011) 40-49
You, X., Chen, F., Zhang, J. Anpo, M. Catalysis(2005)
Letters,
Vol.
102,
Nos.
3-4

possible to be analysed by the sampling theorem, and both
sampling interval and measurement range can be decided by
the minimum sphere of AUT in global coordinate system.
The limitations of pattern reconstruction by conventionalalgorithms are identified, and algorithms applying translational phase shift are proposed and validated by numericalresults for both complete and incomplete measured data.
In the end, the theoretical modelling of doubledirectional channel by spherical harmonics is studied
through the equivalent circuit model, and the antenna complex amplitude can be extracted from the model. Therefore,to evaluate the performance of different antennas in certain
propagation environment, the antenna pattern reconstruction is one of the important parts.
In future, channel sounding will be conducted, andchannel parameter will be estimated according to the dataof both channel sounding and antenna measurement. The
double-directional channel modelling by spherical harmonics will be testified by comparison with the plane wave
channel model.

measured samples

Check if AUT
is located at the center of global
coordinate

No(Case 1)

Yes(Case 2)

Virtually transfer the AUT position to coordinate
center by translational phase shift of themeasured pattern samples

Reconstruction of centered AUT by
spherical wave
(Case 1)(Case 2)

Virtually transfer the AUT position back toinitial location by translational phase shiftof the reconstructed pattern

Reconstructed PatternFigure 3: Proposed algorithm for both complete and incomplete
spherical measurement

−3

5

x 10

Acknowledgement
This work is supported by ”The research and development
project for expansion of radio spectrum resources” of the
Ministry of Internal Affairs and Communications, Japan.

Eplane Pattern

Amplitude,N/C

4

References

3[1] R.W. Schafer, R.M. Mersereau, and M.A. Richards,”Constrained iterative restoration algorithm,” Proc.
1
IEEE, vol.69, pp.432-450, Apr. 1981.
Reconstructed field
Reference field[2] A. Papoulis, ”A new algorithm in spectral analysis and0band-limited extrapolation,” IEEE Trans. Circuits Syst.,
0
45
90
135
180
θ, deg.
vol. CAS-22, pp. 735-742, 1975.
[3] M.D. Sacchi, T.J. Ulrych, and C.J. Walker, ”InterpolaFigure 4: E-plane of reconstructed pattern by conventionaltion and extrapolation using a high-resolution discretealgorithm
Fourier transform,” IEEE Trans. Signal Processing, vol.
46, pp. 31-38, 1998.
[4] W.Zhang, R.A Kennedy, and T.D. Abhayapala. ”Iter−3
EplanePatternx 10
ative extrapolation algorithm for data reconstruction
5
over sphere”, in Proc. IEEE ICASS 2008, Las Vegas,
4
Nevada, Mar. 2008, pp.3733-3736.
[5] E. Martini, S.Maci, and L.J. Foged, ”Spherical near
3
field measurement with truncated scan area”, in processing of the European Conference on Antenna and2
Propagation, pp.3412-3414, Rome, Italy, April 2004.
[6] R.C. Wittmann, C. F. Stubenrauch, M.H. Francis, ”Us1
ing truncated data sets in spherical scanning antenna
Reconstructed fieldmeasurements”, International Journal of Antenna andReference field0
Propagation Volume 2012.
0
45
90
135
180
θ, deg.
[7] J.R. Perez and J. Basterrechea, ”Antenna far-field pattern reconstruction using equivalent currents and geFigure 5: E-plane of reconstructed pattern by proposed algorithm
netic algorithms”, Microwave Opt. Technol. Lett., vol.
42, no. 1, pp. 21-25, 2004.
[8] L.J. Foged, L. Scialacqua, F. Saccardi, and F. Mioc,”Comparative investigation of methods to reduce trun6 Conclusion and Future Workcation errors in partial spherical near field antenna meaThis research systematically studied the antenna pattern resurements”, EuCAP 2012.
construction for both complete and incomplete spherical [9] J.E. Hansen, editor. Spherical Near-Field Antenna Measurement. London, U.K., Peter Peregrinus, 1988.
measurement, by means of spherical wave functions. The
band-limited property of spherical wave expansion make it
Amplitude,N/C

2

12

Study of Private Participation Influence on the Efficiency Performance ofMunicipal Water Supply Management in Indonesia
Student number: 10M51628

Name: Nirmala Hailinawati

Supervisor: Naoya Abe

Increasing demand for safe and affordable water supply to people in developing countries shall be satisfied by goodpractices of water utilities. In year 2010, 58% of public-managed water utilities in Indonesia were showing low
performance in various aspects. Thus, with expectation to turn around this condition, private participation has being
initiated and growing diversely in many forms of contract, while also raised doubt of its implementation since several
partnerships were performing under agreed target. This study aims to figure out the efficiency performance of municipal
water utilities in Indonesia and examines whether the private participation is influencing the overall efficiency
performance of water utilities based on the Data Envelopment Analysis.
contracts in Latin America, Sub-Saharan Africa, andAsia, with increasing trend until now.
However, several cases of water PPPs contract
terminations and failures to reach the targeted
performance were noted, such as in Argentina (thecountry with the largest contract termination), SubSaharan countries, and in Malaysia[3]. This issue has
considerably raising doubts of the PPPs implementation.

1. Introduction
Increasing demand for safe and affordable water supply
has become more and more essential in the developingworld. A partnership between public and private entity
has become one of alternative choices to answer a vast
water demand and to turn around poor performance of
publicly managed utilities.
Private participation was introduced in 1990’s inIndonesia with the absence of national regulatory
framework[1]. After more than two decades, while moreprivate participation has been initiated in Indonesia, thepro and counter discussions on it have continued. The
existing studies on this subject are mainly utilizing a
direct comparison on net achievement of water utility.
This study impartially observes the relative efficiency
performance of municipal water utility in Indonesia
based on Data Envelopment Analysis (DEA). DEA able
to identify “frontier” that is used to evaluate observation
representing the performance of all the entities that are
to be evaluated[2]. The term “efficiency performance” inthis study is trying to explain how efficient a water
utility utilizes its available resources (inputs) to obtainan optimal overall performance (outputs). This study
comprehensively
embracedentireperformance
dimensions: technical, financial, organizational, andservice. The objective of this study is divides into two
main streamlines: 1) to uncover the efficiency profile ofwater utility in Indonesia, which include identifying bestpractices and classifying the group characteristics, and2) to observe private participation influence on theefficiency performance, which include confirming thedifference between water utilities with and without
private participation and understanding the ownership
structure of water utility with private participation.

2.2. Water supply in Indonesia and private
participation
The nature of water utilities in Indonesia is publicly
managed, generally under municipality government.
Performance evaluation released by government showsthat until 2010 only around 41.94% of water utilities
were performed healthy.
Bear by the Asian financial crisis in 1998, theconditions of most of the public water utilities inIndonesia have deteriorated. The Indonesian
government reform after the crisis affected the directionof water supply management. With Law No.22/1999 on
Local Autonomy, which transferred some infrastructure
function to local government, more private participation
on infrastructure sectors were encouraged.
The pro and counter discussions on private participationin water supply management were going on and getting
sharper when taking utility’s performance as point ofview. The issue sparks when highlighted performance ofthe private sector concessionaires in Jakarta indicatesthat key original performance targets have been
dramatically scaled back[4], and the part privatization ofBali’s piped water supply has led to increased inequality
and restricted access for the poorest sectors of society[5].
Meanwhile, public water utilities still could not comeout from unfavorable performance condition, as 58% ofwater utilities in year 2010 are in less satisfactory andcritical condition. In this circumstances, many disputes
whether ones’ performances are better than others’.

2. Overview of private participation inwater supply sector
2.1. Private participation in water supply sector
In early 1990s many governments implemented reformon their water supply and sanitation services, which
often included delegating the management of utilities toprivateoperators
undervariouscontractual
arrangements[3], noticeably in European countries likeFrance and UK.
In developing countries, the initial contracts of private
participation in water sector were the concession in
Corrientes in Argentina and Buenos Aires in Brazil.
These contracts then quickly followed by other

3. Efficiency performance of water utility
What most evaluation method widely used bygovernment, regulatory body, and scholars is the directcomparison of water utilities net achievement orcomparison with the previous situation. This is a verystraightforward method and easy to understand,however this method is letting us to imagine the similar
size of water utilities being observed.
The evaluation by DEA approach has started the use
frequently these days to assess the efficiency
13

right hand side (2.) since, otherwise, θ* could beenlarged. Let the set of such j ∈ {1,…,n} be:performance of water utilities, with case study in UK,
Italy, Japan, Portugal, and Australia.
3.1. Data envelopment analysis (DEA)
DEA is a non-parametric mathematical programming
technique to assess the efficiency of homogenous units.
The unit under study is called a decision making unit
(DMU). The basic concept of DEA is rooted from acommon efficiency ratio: output/input unit.

H

E

Output

I

G
D

F
C

10
A
B

0
0

10

Input

20

$

*,"

-,"

…(eq.6)3.2. Model construction
A model for analysis for this study is constructed by
depicted the main activities of water utility in Indonesia.
The model concept is trying to embrace how waterproduction activity explains the distribution andaccessibility achievement. With regard to DEA, we
describe three variables as “input” and eight variables as“output”. Table 1 shows the input and output variables
and the comparison with the variables used in previous
studies. In previous ones, the “production activities”
tried to be represented by operating cost, while in thisstudy represented directly by production capacity,
production hours, and number of staff. More input andoutput variables are included in current study with aim
to do the evaluation more comprehensive.

Sales 30
(Ten thousand Yen) DEA frontier line

20'/+0 = 1: 3 *∗ *4 = 3 -∗ -4 530
Staff (person)

Figure 1. Frontier line where a single input and a single
output model is applied

Table 1. Variables evaluated as input and output inwater utility’s efficiency performance evaluation
No

In a single input and a single output model, DMU withthe highest slope (output/input) sets the “benchmark” toother DMUs. DEA frontier line designates theperformance of the best DMU (point E) and measuresthe efficiency of other DMUs by deviations from E
Here, we move from the output/input ratio for each
DMU to the “ratio of ratios”. Thus, the efficiency scores
gained are relative within a specific dataset.
In this study, we are employing the basic DEA model
namely CCR, input oriented, which named afterCharnes, Cooper and Rhodes in 1978. The first step is todetermine the weights of input (vi) and output (ur) of
DMUk (k = 1,2,…,n) using linier programming so as tomaximize the ratio:+  …  

≤1

+⋯ +

max,  =  1 1 + 2 2 +⋯+  
1 1Subject to:  ⋯ " , # , … , $ ≥ 0
" , # , … , ' ≥ 0

2 2

 

( = 1, … , )Input
1
Operating cost2
Production capacity
3
Production hours
4
Number of staff
Output1
Total connection
2
Distribution capacity
3
Pipe length
4
Burst repair cost5
Coverage area
6
Number of people perconnection
7
Service hours
8
Idle capacity rate
9
Non revenue water
10
Average tariff…(eq.1)Case study:
Italy[6]Case study:
UK[7]This study:
Indonesia

O
X
X
X

O
X
X
X

X
O
O
O

X
O
X
X
X

O
O
O
O
X

O
O
X
X
O

X

X

O

X
X
X
X

X
X
X
X

O
O
O
O

3.3. Datasets
The study evaluates 236 water utilities, treated as DMU,
which considered representing around 60% of water
utilities in Indonesia. Equal footing based on population
size is applied for fair comparison among DMUs.
Larger population size means higher responsibility“pressure” and complexity to the municipality
government to provide safe water to the people.
Population size in Indonesia is very varied andundeniably created huge gap between municipalities(from the population database in this study minimum
value is 30,653; median is 326,636; and maximum is9,583,247). This concern becomes our main
consideration to split the database into two groups by
one million population threshold: high (nH = 39) andlow (nL = 197) populated municipality. Figure 2 shows
the standard range of datasets in both groups.
Private participation being reviewed is located in 22
municipalities, in both high and low populated groups,
which include 37 contracts. All of the private
participation located in the relative urbanized area,
compare to other areas in the same province, and have
population more than 100 thousand people.

…(eq.2)…(eq.3)…(eq.4)The (v*, u*) obtained as an optimal solution for linier
programming results in a set of optimal weights for
DMUk. The ratio scale is evaluated by:∑'*," *∗ *+…(eq.5)∗ =Variable∗∑$-," - -+vi* is the optimal weight for the input item i and its
magnitude expresses how highly the item is evaluated.
Similar for ur* which is the optimal weight for output
item r.
Reference set is the efficient DMU which its
performance is referred by other inefficient DMU(s). In
the case where DMUk has θ* < 1 (CCR-inefficient), theweights (v*, u*) produces equality between the left and14

Further, we identified the efficiency score of “withprivate participation” water utilities from both high (11DMUs) and low (11 DMUs) populated groups. In
Section 5 we will tests whether private participation
does influencing those efficiency scores or not.

Nine types of contract discusses are: concession, build
own operate (BOO), build operate transfer (BOT),
managerial contract, rehab operate transfer (ROT), joint
venture (JV), leasing contract, rehab upgrade operatetransfer (RUOT), and rehab expand operate transfer(REOT).

4. Characteristics of water utility inIndonesia

6

We identified the characteristics of inefficient andefficient DMUs, in high and low populated municipality,
based on its weighted value obtained from DEA. The
methodology used is cluster analysis by agglomerative
hierarchical clustering with Ward’s algorithm.
For inefficient DMUs we give recommendation to each
DMU and identify to which efficient cluster it isprojected. Figure 3 is showing the clusters of efficient
DMUs in high populated group, and Table 1 is showing
one example of recommendation for an inefficient
DMU in high populated group.

4
2
0
-2

0.30

Average tariff

NRW

Index of similarity

0.25

3.4. Relative efficiency performance
Figure 3 shows the summary results of efficiency
scores by DEA in high and low populated groups.

Cluster
EH1

Cluster
EH2

With private
participation

0.20

Figure 4. Clusters of efficient DMUs in high populated
municipality
Table 2. Suggested input variables changes for DMU#126 of high populated municipality(efficiency score: 0.939, main referred to cluster EH3)

Figure 3. Summary of efficiency scores percentages
From the results we can see that high populated groupis having higher magnitude and median of efficiency
score. Also, we can infer that low populated group is
having a wide range of efficiency performance.

Variables

Unit

Production capacity
Production hours
Number of staff

l/s
Hour
PersonProjection
900.368
22.556342.767

Changes-6.02%-6.02%-26.29%Blue dots: efficient DMUs in more developed municipalities
Red dots: efficient DMUs in less developed municipalities

JakartaPopulation scale:
9 million people

Figure 5. Geographical distribution of best practice water utilities in Indonesia
15

96

23

74

83

40.91%

121

21.83%

77

53.85%

1231

75

45.45%

134

9.09%

35.03%

106

25.38%

33.33%- medium density & lessdeveloped area
- dominant variables:
production & service hours

Cluster
EH3

13112.82%

0.90-0.99

132

0

128

11.68%

98

00.80-0.89

127

0.70-0.79

86

4.55%

73

0

4.57%

89

1.52%

0

29

0

0.60-0.69

112

0.50-0.59

103

Low-populated
municipality

inertia gain

0.05

High-populated
municipality

0.10- medium to highdensity & moredeveloped areas- dominantvariables:
connection/people,
number of staff &billed water

0.00- medium to highdensity & moredeveloped areas- dominantvariables: total
connection &production cap.

0.10

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

0.00

Percentage of efficiency scores

Click to cut the tree
Hierarchicalclustering

0.35
0.30

Figure 2. Standard range of datasets (mean = 0)

0.20

Idle capacity rate

Low populated

Distribution capacity

High populated

Service hours

People/connection

Coverage area

Total connection

Number of staff

Production hours

Production capacity

-4

0.15

Standardized value of datasets

8become majority shareholder in the contracts analyzed
in this study
100%

Besides, we also plotted the efficient DMUs in
Indonesia map in Figure 6. From the map, we canconclude that the distribution of best practice water
utilities with efficient performance is well-dispersed. It
is a good sign that the inefficient water utilities could“learn” from their nearest neighbors, where social andeconomic condition are assumed as relatively similar, of
how they efficiently utilizing available resources.

20%

Local-private

Population
Density

RegionDevelopment
statusz
pvalue (zcrit=1.96)0%Type of contract

7. Conclusion
This study confirmed following results: 1) water utilities
in high populated municipality is tend to perform more
efficient than the ones in low populated municipality; 2)53.85% and 21.83% of water utilities in high and low
populated municipality, respectively, are showing anefficient performance. Also, geographical distribution ofbest practice water utilities is well-dispersed inIndonesia; 3) clusters of inefficient and efficient water
utilities, along with their characteristics have been
identified in this study; 4) efficiency performance ofwith and without private participation are notstatistically different; and 5) foreign private shares ismajority in concession, JV, leasing contract, REOT,
ROT and RUOT, while local private shares is majority
in BOO and BOT type of contract, in other hand, thegovernment has never become majority shareholder.

Remarks

U

Ucrit

high
low
high
middlelowwest
centraleast
moredeveloped

145
1271
247
288
74
893
106
14

-

90 0.759
0.175
0.433
0.927
0.869
0.103
0.697
1 0.695

Fail to reject Ho
1.350 Fail to reject Ho
0.773 Fail to reject Ho
0.087 Fail to reject Ho
0.152 Fail to reject Ho
1.603 Fail to reject Ho
0.354 Fail to reject HoFail to reject Ho

1217

-

0.120

1.524 Fail to reject Holess developed

65.5

-

0.821

0.219 Fail to reject Ho

Government

Figure 6. Plot of means and standard error ofgovernment, local-private, and foreign-private share foreach type of contract

Table 3. Summary of Mann-Whitney statistical test
Category

60%

80%

The statistics test conducted to confirm whether there isdifference of efficiency performance between water
utilities with and without private participation using
non-parametric statistical Mann-Whitney U test.
The results from high (Mann–Whitney UH = 145, NH1 =11, NH2 = 28, p > 0.05) and low populated (Mann–
Whitney UL = 1271, NL1 = 11, NL2 = 186, zL = 1.350, p >0.05) groups shows that the distributions of efficiency
scores in with and without private participation groups
are not significantly different.
Moreover, to be more convinced, we stepped back anddo equal footing by density, region, and development
status, and repeated the analysis. All of the results
confirmed that we fail to reject null hypothesis by 5%
significance level, which consistent with the previous
finding.

40%

Ownership percentage

5. Performance different of water utilities
with and without private participation

Footing byForeign-private

References[1] National Working Group of the Water Dialogues
Indonesia (WDI), 2009, Final Technical Report, IDRC
[2] Cooper, W. H., et al., 2006, Introduction to Data
Envelopment Analysis and its uses, Springer[3] Marin, P., 2009, Public-Private Partnership for
Urban Water Utilities, The World Bank Report[4] Bakker, K., 2007, Trickle down? Private sector
participation and the pro-poor water supply debate in
Jakarta, Indonesia, Geoforum 38 (2007) 855-868[5] Cole, S., 2012, A political ecology of water equity
and tourism: a case study from Bali, Annals of Tourism
Research, Vol.39, No.2, pp. 1221-1241[6] Romano, G., and Guerrini, A., 2011, Measuring andcomparing the efficiency of water utility companies: adata envelopment analysis approach, Journal of
Utilities Policy, 19, 202-209[7] Thanassoulis, E., 2000, The use of data envelopment
analysis in the regulation of UK water utilities: water
distribution, European Journal of Operational Research,
126, 436-453

6. Ownership structure of water utilities
with private participation
The private participation is letting a private ownershipto some extends. A majority shareholder is somehow
dominating the direction of management. Given the
results in Section 5, we would like to see the majority
ownership profile of private participation in water utility
in Indonesia. Here, we summarize the ownership
percentage of local-private partners, foreign-private
partners, and government for each type of contract.
From the results we can infer that foreign private sharesis found higher in concession, JV, leasing contract,
REOT, ROT and RUOT type of contract. Those typesof contract are mainly involved in water treatment plant(WTP) operational and all operational activities thatdelegated to private partner. While, local private share isfound higher in BOO and BOT type of contract, which
involved WTP and distribution network to supply
residential and industrial areas. In other hand, thoughhaving shares in some contracts, government has never16

Contact-less Heartbeat Detection Methodby using Microwave
Student ID : 10M51634

Name : Yanran LIU Superviser : Jun-ichi TAKADA

マイクロ波を用いた非接触心拍検出方法
劉妍然

本論文では、マイクロ波を用いた、心拍の変動の検出に関する実験結果を報告する。心拍変動の変化は居眠り状態のひとつ重要なサインとなる。マイクロ波の透過係数の振幅または位相の変化によって、心臓の動きを直接とらえて、電波変化を検知することから、人体や車体の大きな振動にも耐性があるとが考えられる。４名の被験者対して、周波数、偏波、アンテナ位置、アンテナ距離などをパラメータとして、従来法である透過係数の測定による検出法と比較を行った。その結果、提案法がより安定して心拍を検出できることを示すとともに、より確実に検出できる条件を明らかにした。

I. I NTRODUCTION

oximeter sensor.Therefore, we proposed a contact-less heartbeat detection method by using microwave. The sleepinessdetection system using this method is very simple and low
cost, so it can be used widely.
Doppler radar has been considered for the detection ofheartbeat [4]. It can be used to measure the chest displacement due to heartbeat and respiration by the reflected signal.
The variation of displacement due to respiration is between 4
and 12 mm, and the chest displacement caused by heartbeat
alone is between 0.2 and 0.5 mm [5]. Heart Rate Variability(HRV) can be extracted from temporal variation of the phaseof the reflection signal. But the detection is quite difficult
when the motion of the body exceeds the order of the
wavelength [6]. Another approach is using ultra-wideband(UWB) pulse radar. It can detect the small motion of the
body surface and also is robust to the large motion of the
body [7]. However, the use of microwave UWB is prohibitedin the vehicle in Japan, while quasi millimeter wave UWB
has the potential interference as it is used for inter-vehicularradar [8].

Nowadays, the demand for contact-less heartbeat detection
has increased, especially for sleepiness detection in vehicles.
Driver’s sleepiness is one of the most dangerous causes
for the traffic accidents which may end with fatal death.
Several techniques to prevent driver from falling asleep at
the wheel have been developed. One well known approachis using imaging sensors to count eye blinks while driving[1]. However, it is necessary to predict sleepiness early
before drivers show signs of sleepiness so that preventing
steps can be applied before accident is almost inevitable.
We focused on heartbeat because the change of the patternof heartbeat is a significant sign of sleep. It is influenced
by posture, state of mind, surrounding temperature and soon [2]. But except for mental condition, if other factors
are almost constant during driving, sleepiness becomes the
major factor. Therefore, detecting the change of the patternof heartbeat is very useful for preventing traffic accidents.
Heart Rate Variability (HRV) is a physiological phenomenon where the time interval between heartbeats varies.
It is measured by the beat-to-beat variation of heart rate.
The level of sleepiness can be estimated from the decreasein heart rate and the increase in high frequency componentof heartbeat intervals [3]. Therefore, as long as we obtain theheartbeat interval in time domain, sleepiness can be judged.
The activity of heartbeat can be recorded by using electrocardiogram (ECG). It needs electrodes attached to thesurface of skin and records ECG wave by an external device.
Since measurement is done in a long term, extra mental
stress may be applied to the driver. So sleepiness is difficult
to evaluate accurately. Microwave radiation, however, canbe transmitted to other dielectric medium, and information
inside the body can be obtained from transmissive wave.
Using this characteristic, heartbeat can be measured without
the mental stress of the driver due to the attachment of

II. M EASUREMENT
Chest Cross sectional viewPrinciple of the proposed method is to detect the changeof the permittivity in biological issues including heartbeat,arterial pulsation, and breathing. These motions are almost
concentrated in the thorax, but also some include the abdomen. Figure 1 shows the chest cross sectional view. Twothirds of the heart is at the left of the body center. Heartdrives blood into the arteries and the size of heart changes.
So the motion caused can be detected at the skin surface.
When each ventricle contracts, the heart ejects a surge ofblood into the aorta, leading to pressure wave through the
body [9]. Therefore, this motion does not occur at the sametime as the chest wall motion due to the heartbeat. The
delay from the chest to the pulse points could cause some17FrontLeft ventricle

Right ventricle

Thoracic aortic

Sf : 0, -3, -6.5 [cm]#1

Esophagus

Tx

VNA

Sf
#2

Left lungdf : 3, 50, 100 [cm]front

Right lung

Spinal cord

Back

Fig. 1.

db : 3 [cm]SbRx

Chest cross sectional view

Sb : -6.5 [cm]Antenna- 0 +Top view

PC

VNA
Fig. 3.

Human
Heart

Antenna locations

TABLE IM EASUREMENT SPECIFICATIONS

Antenna

Equipment

Data
LoggerVNA (Agilent)
Data logger (NI USB−6221BNC)
Pulse Oximeter
Frequency
950 MHz, 10.5 GHz
Car speed
0 m/s
Specimen
Body 1 (female), Body 2 (male)
Body 3 (female), Body 4 (male)
Vector Network Analyzer:
No. of points
1200
Sweep time
60 s
Sample rate
20 Hz
Pulse Oximeter:
No. of points
60000
Sweep time
60 s
Sample rate
1000 Hz
Antenna polarization:
950 MHz
Horizontal, Circular10.5 GHz
Horizontal, Vertical
Antenna location:df
3 / 50 / 100 [cm]db
3 [cm]sf
0 / −3 / −6.5 [cm]sb
−6.5 [cm]Pulse Oximeter
Fig. 2.

Measurement setup

spreading in time of the signal during the measurement. The
lungs are located in cavities on either side of the heart. In themeasurement using microwave, transmission wave throughbody measures the permittivity of heart, aorta and lungs.
As a comparison, measurements are also done using thereflection wave. Reflection wave in front of body mainly
measures the motion of heart, and at back mainly measuresthe motion of lungs.
Measurement setup
To demonstrate the feasibility of heartbeat detection by
microwave, Measurement are performed by using a vector
network analyzer (VNA) and two antennas at 950 MHz
and 10.5 GHz. Fig.2 shows the schematic experimental
setup. VNA measures full 2-port S-matrix to compare thedetection performances between transmission and reflection
properties. One antenna is set in front as well as backside of the body. Two male and two female specimen were
examined to check the gender dependency. Moreover, a pulse
oximeter measures the pulse of blood flow of the specimen
as reference for comparison. The VNA measurement and theoximeter measurement are done at same time.
Fig. 3 shows the locations of transmitter and receiverantennas. We assumed that the possible locations of thesensors are in the back of the seat for one side, seat belt,
steering wheel or instrument panel for the other side in
vehicle. The front antenna was connected to Port 1. The
separation between body and front df is varied from 3 to
100 cm. The horizontal offset at driver’s front sf is varied
from 0 to −6.5 cm (’−’ means left side distance from body

center). The back antenna was connected to Port 2, andthe separation between body and back db is 3 cm. The
horizontal offset at driver’s back sb is −6.5 cm. In thenext section, the performance of heartbeat detection will be
investigated in terms of these antenna locations and also themost suitable locations for the sensors will be determined.
The measurement specifications are shown in Table 1.
III. S IGNAL PROCESSING
HRV Extraction
To extract HRV, detect the peaks of signal takes an importantrole because an irregularity of heart beat can be determinedthrough heartbeat interval. heartbeat interval has the largest
amplitude among. Since we have the measurement datafrom VNA, and the pulse oximeter data as reference, the
18

x 10

-4

Amplitude5

1.2

VNA data

correlation coefficient

0
-5
0

10

20

30
Time [s]40

Amplitude

1

50

60

Oximeter data

0.5
0Cross-covariance1

LagLag=1853ms= 1853 ms

0.8
0.6
0.4
0.2
0
-0.2
-0.4

-0.5
0

10

Fig. 4.

20

30Time [s]

40

50

60

-6

-2

0

2

4

Time [ms]Raw data: VNA and oximeter

Fig. 6.

1

Heartbeat interval [s]

0.8

0.7

0.6

0.5

False Alarm

6
4
x 10

Time lag between VNA data and oximeter data

1.2

VNA
0.9

Heartbeat interval [s]-4

VNA data
Oximeter data

1.1
1
0.9
0.8
0.7
0.6
0.5

0.4

0.4
0

10

20

30

40

50

0

60

1

Fig. 5.

2

3

4

5

Time [ms]Time [s]Fig. 7.

Heartbeat interval (VNA data)

6
4
x 10

synchronized Heartbeat interval data

As explained above, the oximeter data does not occur
synchronized with VNA data. There is a time lag exist.
To obtain the time lag between these two data, correlation
coefficient is calculated and defined by:signal processing is divided into two steps. The first stepis to determine whether heartbeat can be detected using the
proposed method. The next step is to estimate the detection
error.
Fig. 4 shows an example of raw data at 950 MHz. In
the VNA data, it includes the information of heartbeat,
respiration and noise. The oximeter data includes the pulse
wave of specimen. According to the previous study, the peakamong 1 ∼ 2 Hz in frequency domain is the component ofheartbeat. Therefore, band pass filter is applied for all data.
Pass band frequency is chosen to be 1 ∼ 2 Hz.
The sampling rate of VNA data is 20 Hz, for oximeterdata it is 1000 Hz. Before detecting the peaks, VNA data areinterpolated to the same sampling rate as oximeter data. The
time difference between two consecutive peaks corresponds
to the heartbeat interval.
Fig. 5 shows the heartbeat interval extracted from VNA
data. Since the normal heart rate is from 60 to 120 bpm, thethreshold of false alarm is determined within 0.5 s ∼ 1.0 s.
If heartbeat interval out of this range is detected, false alarm
occurs and the value is changed to the average of heartbeat
intervals so that it will not affect the detection.

CXY (n)=E[(Xp+n − µX )(Yp − µY )]p(1)
E[(Xp+n − µX )2 ]E[(Yp − µY )2 ]where X and Y are heartbeat intervals of VNA data andoximeter data, µX and µY are the mean values of X and
Y . Before calculating, heartbeat intervals are resampled tomillisecond unit to improve the accuracy. Therefore, here
p = 1, 2, ...60000, CXY (n) obtained the interdependenceof X and Y by observing these two variables at times nmilliseconds apart. Fig. 6 shows the result of correlation
coefficient. For this case, the time lag is 1853 ms.
Fig. 7 shows the synchronized heartbeat intervals after
shifting lag time. The solid line is VNA data, and the dashedline is oximeter data. If the difference time between two datais less than five percent of oximeter data, we assume thatheartbeat is detected. Otherwise, heartbeat is misdetected.
Miss detection rate is calculated for evaluation. For the data
which heartbeat is detected successful, root-mean-square19error (RMSE) is used to estimate the detection error anddefined as follow:p
E [(RVNA (i) − Roxi (i))2 ]RMSE =
(2)

1
0.9
0.8
0.7
0.6

R

0.5
0.4

IV. R ESULTS= 13.580 4%

isRmis RM=m13.5804%
SE =0.0 1630 9
RMSE = 0.0163

0

1

2

3
4
Tim e [m s]5

VNA data
Oximeter data

1.2

Heartbeat interval [s]By calculating RMSE and misdetection rate of extracted
heartbeat intervals, frequency dependency, microwave type,antenna conditions, and signal feature are evaluated. We
can observe that the detection performance at 950 MHz ismuch better than 10.5 GHz. Misdetection rate at 950 MHz
is about 18 %, but more than 80 % heartbeat detection
is failed at 10.5 GHz. Since the mechanism of proposed
method is to measure the permittivity of heart, the electricalcharacteristics of biological tissue and cells have the frequency dependence. Permittivity decreases as the frequency
increases. Therefore, heartbeat could be detected better atlower frequency.
The permittivity of heart, aorta, and lungs are measured
using the transmission type of microwave. Reflection wave
is also measured as comparison. As expected, from the raw
data waveform, the displacement of heartbeat and respiration
can be observed clearly from the transmission wave, but very
difficult seen from reflection at back. Misdetection rate oftransmission wave is smaller than reflection in front.
The orientation of the antenna influences to the heartbeat
detection performance. At same measurement condition, we
can observed that there is a very big difference depend on
antenna polarization. Heartbeat could be detected only using
horizontally polarized wave. From the results at different
antenna positions, heartbeat could be detected best when df
is 3 cm and sf is −6.5 cm. Therefore, antennas can beinstalled in the seatbelt at left side of driver in vehicle.
Moreover, the VNA data is complex number. From the results, phase component shows better detection performance
than amplitude component. Using the best measurement
condition above, Fig. 8 shows the results of heartbeat
interval of four specimens. Because microwave measured
the transmission through body, gender dependency is notseen obviously. But individual deference exists. Cardiac
arrhythmia is found from specimen Body 2.
Therefore, the results can be summarized as follow:• Heartbeat could be detected using phase component
utilizing transmission property of microwave at 950
MHz.
• The orientation of the antenna influences to the heartbeat detection performance. Horizontal polarization
showed better performance.
• Antenna should be placed at left side of body.
• Closer the sensor located to the body, the better heartbeat detected.
• Gender dependency was not observed using transmission wave, but individual patterns varied. Detection
results are influenced by the health condition.

1.1

Body 3 (F.)

1
0.9
0.8
0.7
0.6

R mis=3.7938%
RmisRMSE=0.01495= 3.7938%
RMSE = 0.0150

0.5

1 .2
1
0 .9
0 .8
0 .7
0 .6

m is =3 6.04 17 %Rmis =RRM
36.0417%
SE =0.0 17 363
RMSE = 0.0174

0 .5
0

1

2

1

2

3

4

5

Time [ms]Fig. 8.

6
4
x 10

5

6
x 10 4

VNA data
Oximeter data

1.1

Body 4 (M.)

1
0.9
0.8
0.7
0.6

R

mis =34.75 1%

0.0185 2
RmisRM=SE=
19.4022%
RMSE = 0.0195

0.4

0

3
4
T im e [m s ]

1.2

0.5

0.4

V NA da ta
O xim e te r da ta

Body 2 (M.)

1 .1

0 .4

6
x 104

Heartbeat interval [s]Heartbe at interval [s ]where RVNA is heartbeat interval of VNA data, and Roxi isheartbeat interval of oximeter data.

VNA da ta
O xim ete r da ta

Body 1 (F.)

1.1

H eartb eat in te rval [s ]Freq. 950 MHz, Type S21, Antenna : H., Sf = -6.5 cm, df= 3 cm, phase
1.2

0

1

2

3

Time [ms]

4

5

6
4
x 10

Sample dependency

V. C ONCLUSION
A new contact-less heartbeat detection method by using
microwave was proposed in order to detect the sleepinessof drivers. Measurements were performed with different
antenna positions at 950 MHz and 10.5 GHz. Heartbeat
intervals are extracted from S−parameters measured by
VNA and compared to the waveform measured by pulse
oximeter.
For healthy specimens, extracted heartbeat intervals of
proposed method are matched well with the oximeter data.
87.7 % of heartbeats are detected successfully. Since thelevel of sleepiness can be judged from the change of thepattern of heartbeat. It is expected that this study is very
useful to predict driver from falling asleep while driving
and reduce traffic accidents.
R EFERENCES[1] S. Furugori, Y. Miura, N. Yoshizawa and C. Iname, “Analysis of
Driver’s Behavioral Change for a Long Term Driving,” JSAE Annual
Congress, no. 55-02, pp. 1-4, 2002.
[2] M. Yanagidaira and M. Yasushi, “Method for Predicting Drowsiness,”
PIONEER R&D, Vol. 17, no. 1, 2007.
[3] M. Yasushi and M. Yanagidaira, “Estimating Sleepiness during Expressway Driving,” J. Int. Soc. Life Inf. Sci., vol.21, no.2, pp.442-448,
2003.
[4] D. Obeid, S. Sadek, G. Zaharia, and G. E. Zein, “Non-contact Heartbeat
Detection at 2.4, 5.8 and 60 GHz: A Comparative Study,” Microwave
Opt. Techol. Lett., vol. 51, no. 3, pp. 666-669, 2009.
[5] G. Ramachandran and M. Singh, “Three-dimensional reconstruction ofcardiac displacement patterns on the chest wall during the P, QRS, andT-segments of the ECG by laser speckle interferometry,” Med. Bio.
Eng. Comput., vol. 27, no. 5, pp. 525-530, 1989.
[6] H. J. Kim, K. H. Kim, Y. S. Hong and J. J. Choi, “Measurement of
human heartbeat and respiration signals using phase detection radar,”
Review of Scientific Instruments, vol. 78, no. 10 pp. 104703-104703-3,
2007.
[7] E. M. Staderini, “ UWB radars in medicine,” IEEE Aerosp. Electron.
Syst. Mag., vol. 17, no. 1, pp. 13-18, 2002.
[8] Japan Ministry of Internal Affairs and Communications website. Available : http://www.tele.soumu.go.jp/j/adm/freq/search/share/index.htm[9] A. Owen, ”Effect of increasing age on diastolic motion of the left
ventricular atrioventricular plane in normal subjects,” International
Journal of Cardiology, vol. 19, no. 1, pp. 203-212, 1998.

20

NUMERICAL STUDY ON LOCALIZED HEAVY RAIN
USING LATEST URBAN PARAMETERIZATIONSAND HIGH-RESOLUTION SEA-SURFACE TEMPERATURE
Student Number: 10M18128

Name: Kumiko NAKANOSupervisor : Manabu KANDA

高精度の都市地表面パラメータ・海表面温度を導入した都市型集中豪雨シミュレーション

仲野

久美子

高解像度の海表面温度（SST）と東京都心の詳細な修正粗度・運動量粗度・熱粗度を含む最新の都市パラメータを導入した「NEW」と，都市影響を考慮しない「OLD」の条件を設定し，メ
ソ気象モデルWRFを用いた都市型豪雨シミュレーションを行い解析値の比較を行った．その結果，主に以下の事が明らかになった．①NEWの条件における都市上空での雨の強化と実況降雨の再現性の向上，②都市域の熱・水蒸気の滞留と，それに伴う海風侵入の影響による豪雨発生
メカニズム，③東京都心の詳細な運動量・熱粗度による都心上空の風速場の再現性の向上
the surface boundary condition since the weather of Kanto
region tends to be influenced by SST [3]. Therefore, the urbansea interaction in Kanto region should be taken into accountmore carefully by improving the boundary condition.
In this research, to evaluate the urban effect on LHR withmore detailed parameterizations, high special-resolution SST
and aerodynamic parameters considering actual urban
geometries of expanded area were incorporated into WRF forthe better representation of the urban area and the sea character.

1. Introduction
Urban localized heavy rainfall (LHR) has become a serious
issue especially during summer in the Tokyo metropolitan area.
Although it has been still difficult to predict LHR due to theuncertainties of weather forecasting, urbanization is suspected
to be one of the key factors to generate LHR. In the previous
researches, urban effects on LHR have been studied using
Weather Research and Forecasting (WRF) model, where someurban characters were parameterized, i.e. anthropogenic heatand moisture emission (AHE・AME) and urban canopy model(UCM) incorporating actual displacement height (d) of Tokyo[1]. UCM, coupled with WRF, is a model used to calculate
fluxes from each building facet by assuming uniform andinfinitely-long street canyons. Although these parameters
improved the reproductivity of LHR, they remain to be
insufficient in terms of representing aerodynamic parameters of
realistic building configurations and sea surface temperature.
The former problems are summarized as follows;
1. Previous researches considered only actual d and treatedthe actual roughness length of momentum and heat (and) constant, for urban areas.
andareimportant parameters for drag effect of buildings.
2. The d was calculated from old-fashioned Macdonald’s
equation with building GIS information.
3. The area of d was previously available only within Tokyo.
By default, UCM assigns constant surface roughness
parameters in all urban areas. Kanda et al.[2] showed that
Macdonald’s equation largely underestimated d andfromhighly detailed large eddy simulations (LES) incorporated withreal urban morphologies of Tokyo.
Secondly, the representation of the sea surface temperature(SST) is also important factor for LHR occurrence in terms of

2. Improvement of parameters for WRF
d andwere calculated with a new parameterization
obtained from LES [2], using average building height (Have),maximum building height (Hmax), height variance (σH ), plane(λp) and frontal area indices (λf), estimated from real urban
morphologies of Kanto region. Those parameters with 1-km
resolution in Tokyo were calculated with building GIS
information with 1-m. resolution provided by CADCENTER
and those of the other areas of Kanto region were estimated byincorporating four datasets:, Google Maps, the Advanced
Spaceborned Thermal Emission and Reflection Radiometer
Global Digital Elevation Map of Ministry of Economy, Trade,and Industry of Japan and NASA, and a free high resolution
digital elevation model and land use data from the Geospatial
Information Authority of Japan. The previous d values by
Shimoju et al. [1] calculated from McDonald's equation aremuch lower in Tokyo (Fig. 2-1): maximum difference is 50-m.
Also, roughness length for heat ( ) was estimated in UCM byeq. (1)[4],
( )

(1)

where
) is roughness Reynolds number andis plane area vegetation ratio. is the friction velocity andis the molecular diffusivity of air(=1.46×10-5(m2s-1)).

21

Table 3-1 Simulation cases
Name

SST

UCM

AHE・AME

OLD

TSK

NO

NO

Const.

NEW

MODIS

YES

YES

New parameterization

OLD+SST

MODIS

NO

NO

Const.

STANDARD

MODIS

YES

YES

Const.

d, Z0, ZT

Table 3-2 Additional cases for OLD and NEW
Name

Fig.2-1 Displacement height (a: previous one , b: new one)

IBC

NCEP

NCEP

NCEP_1w
ECMWF

ECMWF

ECMWF_1w
JMA

JMA

JMA_1w

1-A

2-A

3-A

1-C

2-C

3-C

Spin-up time
1 day
1 week
1day
1week
1day
1 week

Fig. 4-1 Computational domains
Table 4-1 Grid Information of each domain (for NCEP and ECMWF)

Domain
Domain1
Domain2
Domain3

Fig. 2-2 Spatial distribution of SST at 13:00 of(A)29th July 2007 and (C)21th August 2008.

Grid number
62×56×58
171×171×58
201×181×58

Grid size
30 km
6 km
1.2km

Table 4-2 Grid Information of each domain (for JMA)

1,2 and 3 :TSK, MODIS SST, Observation respectively.

Domain
Domain1
Domain2

Sea Surface Temperature (SST) acquired from NASA
Moderate Resolution Imaging Spectroradiometer (MODIS)
was prepared for the simulation using monthly day and nighttime SST data linearly interpolated to the desired simulation
date with 4-km resolution which is a significant improvementfrom the 25-km SST resolution commonly used for WRF
models, named TSK. MODIS SST agrees well with theobserved SST provided by the agricultural institute of
Kanagawa (Fig. 2-2). Also, this figure shows that TSK
overestimates actual SST. Maximum differences between
MODIS SST and TSK range from 3 to 4 deg C during daytime.

Grid number
171×171×58
201×181×58

Grid size
4.8km
1.2 kmTo increase reliability of results, each day has six different
setting of two kinds of spin-up period, one day or seven days,
and three types of initial boundary conditions (IBC): Global
Final Analyses from National Center for Atmospheric Research(NCEP), Global Atmospheric Reanalysis Interim by European
Centre for Medium-Range Weather Forecasts (ECMWF) andMeso Scale Model Grid Point Value of Japan Meteorological
Agency (JMA) (Table 3-2). Furthermore, sensitivity analysis
for SST and the aerodynamic parameters was also conductedby incorporating MODIS SST into OLD_NCEP and changing
the new aerodynamic parameters of NEW_NCEP to constantvalue in urban areas (Table 3-1).

3. Simulation Date and Cases
In order to investigate urban effects on LHR, the MODIS SST
and the latest urban parameterizations, including AHE・AME
and the new aerodynamic parameters of Kanto region, wereapplied to WRF using the improved UCM. Three analysis
dates, 29th of July 2007, 16th and 21st of August 2008, wereselected for the simulations, where an intense localized heavy
rain occurred by the urban effect [1]. The simulation results
were compared with those without MODIS SST and the urban
parameterizations, named OLD (Table 3-1).

4. Numerical settings
Simulation was conducted with three nests when using IBC of
NCEP and ECMWF, and with two nests in case of using that of
JMA (Fig.4-1). All of the smallest domains have the same gridsize, 1.2-km. To validate the model, rainfall data from radar(AMESH) are also shown.

22

Fig.4-1 Spatial distribution of total rainfall of AMESH and simulations from 12:00 to 24:00 of each analysis date
(The area bounded by broken lines is the radar’s coverage for 2007)(i)Fig. 4-2 Results of OLD_NCEP and NEW_NCEP in 29 July 2007 comparing with observation. (a)~(f):25-m. wind velocity
and hourly precipitation snapshots at 13:00 and 17:00 JST, (g),(h): 1st atmospheric level water mixing ratio at 15:0 JST0, (i):Time-series of 2-m. temperature and hourly precipitation AMeDAS and AMESH observationmeans that IBC of JMA has low accuracy and IBC has asignificant impact on the accuracy of LHR simulation.
b) Mechanism of LHR
The mechanism of LHR can be represented well when using
IBC of NCEP. In 29th July 2007, strong convergence occurred
over the city by the sea breeze from Sagami bay and Kashimanada. Water vapor advected by sea breeze increased rainfall
around Tokyo in NEW, not simulated in OLD (Fig,4-2g,h).
Even though onset of rain is delayed by around 4 hours in allcases of NEW (Fig 4-2a-f), NEW realized more accurate
rainfall than OLD. Temperature of NEW above Tokyo
becomes higher than that of OLD and close toobservation(Fig4-2i) This improvement of NEW

4. Resultsa) Precipitation
Fig 4-1 shows the total amount of rainfall from 12:00 to 24:00.
NEW is likely to increase rainfall around Tokyo (Fig 4-1).
Especially with IBC of NCEP, spatial distribution of rainfall
agrees well with that of AMESH in all of the analysis dates
although the amount of rainfall in the simulation isoverestimated in the case of 16th August 2008. However, in 21
August 2008, the cases of NEW which used IBC of JMA did
not show increase of rainfall around city. Potential temperature
at the first level (Ta) also tended to be lower than observationin using IBC of JMA for all analysis dates (not shown). This23b) Aerodynamic parameter (d, , )NEW_NCEP largely its simulated wind velocity andtemperature from STANDARD. New roughness length of city
delayed seabreeze from Kashima-nada especially above Tokyo.
Fig.5-2 shows that the north-easterly seabreeze whose windspeed is more than 2.5m/s at 25m height from ground isdelayed when entering Tokyo in NEW_NCEP whereas one of
STANDARD keeps its speed while passing over Tokyo. Thismeans that new rouhness length significantly drags wind speed
over city. Fig.5-3 shows that 25-m wind speed of Tokyo of
NEW_NCEP agrees better with observation than that of
STANDARD which is overestimated in 21 August 2008. Thisdrag of wind over city can be found in all analysis dates.
Furthermore, the new roughness length also has an impact tostagnate heat and moisture,which increase temerature andrainfall in city. Fig.5-1 shows that 2-m temperature of Nerimaof NEW_NCEP keeps higher than that of STANDARD from11:00 to 13:00 of 29 July 2007 because of the stagnation ofheat of NEW_NCEP.

Fig.5-1 Temperature at 2m. above Nerima in 29 July 2007

Fig.5-2 Wind velocity at 25m. at 11:00 in 29 July 2007
（Red point：Nerima，Red line; drawn where sea breeze
speed becomes less than 2.5m/s ）6. Conclusion
The conclusions of this study are summarized as follows:a. Results, applying the new urban parameterization,tended to realize a more accurate simulation of
localized heavy rainfall and also simulate more rainfall
in city than those without it.
b. Big improvement of temperature of Kanto region
could be found by the change of SST especially whenprevious SST was too overestimated orunderestimated.
c. The new aerodynamic parameter delayed sea breeze
and increased the stagnation of heat and water vapor
around city because the new roughness length worked
as the drag of urban geometry for wind velocity.

Fig.5-3 Wind velocity at 25m. above Tokyo in 21 August
2008 (per 10 min.)made temperature gap between the sea and the land larger
thereby enhancing seabreeze penetration
noon. The
penetration of sea breeze can obviously be found around
Sagami bay(Fig 4-2b).

References[1] Shimoju R., M. Nakayoshi, and M. Kanda, (2010). Case
analyses of localized heavy rain in kanto considering urban

5. Sensitivity Analysis

parameters. Annual Journal of Hydraulic Engineering., JSCE, 54.,a) SST
The impact of MODIS SST can be seen in the temperature
distribution. With MODIS SST, spatial distribution oftemperature improved (not shown). Especially default SST
caused under/overestimation of air temperature over the land
depending on its bias; underestimated SST in 29 July2007
caused lower Ta or overestimated one of 21st August 2008
contributed to higher Ta. Fig.5-1 shows that the 2-mtemperature of OLD_NCEP of 29th July 2007 keeps lower
than that of OLD+SST above Nerima in the morning becauseof the underestimation of default SST of OLD_NCEP.

pp.349-354. (in Japanese)[2] Kanda, M. et al: New Aerodynamic Parameterization for RealUrban Surfaces derived from LES. Proceedings of the 8thinternational conference for urban climate, 118, 2012.
[3] Oda, R. et al. : Impact of the actual sea surface temperature ofTokyo bay of urban air temperature. Annual Journal of HydraulicEngineering., JSCE, 52., pp.283-288, 2008. (in Japanese)[4] Kawai, T et al.: Evaluation of the Simple Urban Energy Balance
Model Using Selected Data from 1-yr Flux Observations at Two
Cities.Preview, Journal of Applied Meteorology and Cimatology, Vol
8, No4, 693-715, 200924

The Decomposition of Methyl Orange over Titania Coated Magnetic Activated Carbon.
Student number: 10M18163 Name: Takuro Haraguchi

Supervisor: Hirofumi HINODE

磁性 TiO₂/AC 光触媒による染料の分解
原口拓郎
本研究では、2 つの異なる粒子径の活性炭担持酸化チタン光触媒と磁性 TiO₂/AC 光触媒を調製し、メチル
オレンジの分解に対する触媒活性を評価した。活性炭担持酸化チタン光触媒では、酸化チタンと活性炭の割合が 66 : 33 かつ大きい粒子径の触媒が再利用後も酸化チタンより高活性を示した。磁性 TiO₂/AC 光触媒は活性炭担持酸化チタン光触媒よりも活性が下がり、また粒子径の小さい触媒の方が触媒活性低下が大きいことが分かった。

1 Introduction

Thirdly, TMAC or TAC was prepared by adding MAC or AC

Titania photocatalytic oxidation offers potentially a facile andinto titania sol. Then, the solution was ultrasonicated for 30

cheap method for removing organic pollutants frommin and placed in an oven maintained at 70˚C for 12 hours for

wastewaters. Typically, a photocatalytic reaction is conductedaging process. The resulting gel was then dried at 100˚C andin a suspension of submicrometer-sized titania. However,calcined in a furnace at 500 ˚C for 5 hours.

removing such fine particles from large volumes of water
involves further expense [1]. To solve this problem, Beydoun

et al prepared titania coated magnetic particles that can beeasily separated and collected by magnet [1]. However,photocatalytic activity was reduced significantly due to thephenomenon of photodissolution. Ao et al prepared Titania
coated magnetic activated carbon (TMAC) which exhibit highphotocatalytic activity and magnetic property [2]. It is also
reported that the property of Activated Carbon (AC) strongly
affect the photocatalytic activity of catalyst [3].
In this study, TMAC with different particle size of AC weredeveloped for treatment of dye pollutant (Methyl Orange,MO) in water. The effect of AC particle size on photocatalytic
activity and magnetic property were evaluated.
TAC preparation route (TAC is prepared by adding pure AC)

2 Experimental
2.1 Catalyst preparation

Figure 1 Sample preparation of TAC and TMAC

The preparations of TAC (Titania coated AC) and TMAC was

Table 1 Identification of photocatalyst

shown in Fig1. Firstly, magnetic activated carbon (MAC) was

Size of AC

prepared using two types of AC with two sizes (50 - 125μm

Big size
125-425μm

and 125 – 425μm). Each AC was modified by HNO3 andSmall size
50-125μm

mixed with solution containing iron nitrate. MAC containing

Weight ratio

TAC5B

TAC5S

Fe was prepared after 3 hours calcinations at 750˚C in N2(TiO2 : AC)

TAC5B1, TAC5B2

TAC5B1,TAC5B2

condition. Secondly, Titania sol was prepared by TTIP

of TAC and-TMAC5S(Titanium Tetra isopropoxide ), glacial acetic acid and water

TMAC

50 : 50

TAC6B

TAC6S

with molar ratio of 1:10:350. The weight ratio of TiO2 and AC

TAC6B1, TAC6B2

TAC5B1,TAC5B2

is shown in Table 1. TTIP was hydrolyzed using glacial acetic

TMAC6B-acid at 0˚C. Water was added to this solution dropwise under

66 : 33

75 : 25

vigorous stirring for 1hour, subsequently the solution was
ultrasonicated for 30 minutes and stirred further 5 hours.
1
25

TAC7B

TAC7S

TAC7B1, TAC7B2

TAC5B1,TAC5B2

2.2 Photocatalytic activity test
For photocatalytic activity test, 100W ultraviolet lamp (with a

Table 2 Surface area of samples with different particle size

wavelength from 250-600 nm) covered by a Pyrex glass
sleeve was placed at the center of the reactor. Before UV

Big size

irradiation, 0.25 g sample was added into 900 ml solution

2(m /g)

containing 50 ppm of Methyl Orange and the mixture was

Small size

maintained in dark condition for 7 hours to reach adsorption

2

AC

TAC5

TAC6

TAC7

TMAC

991.4

545.3

439.2

306.4

351.3

1032

818.5

449.9

368.8

521.6

(m /g)

equilibrium. After that, the UV irradiation was carried out,
and sampling (5 ml) was done at regular intervals of 1 hour

3.3 SEM-EDS

for analysis by UV-vis spectrometry. Recycling of used

The SEM images of TMAC6B and TMAC5S were shown insample of TAC was also carried out to observe the change in

Fig. 3. Small particles of Titania could be observed. The EDS

photocatalytic activity after use. Reused sample was by

was shown in Fig4 indicated a heterogeneous distribution ofcollected new catalyst through filtration and drying after

Fe and Ti on the surface of AC. On the other hand, TMAC5S

photocatalytic activity test.

showed a uniform distribution of Fe and Ti.

3. Catalyst characterization
3.1 XRD(a)

XRD patterns of TMAC6B and TMAC5S were presented inFig. 2. TMAC6B showed anatase phase of TiO2 , magnetite
phase of iron oxide and composite oxide of Ti and Fe

15kV× 2,000(Ilmenite), while TMAC5S showed not only anatase,

10μm

magnetite and Ilmenite but also composite oxide of Ti and Fe(Pseudobrookite).

(b)

15kV×2,000

10μm

Figure.3 SEM images of (a)TMAC6B and (b)TMAC5S(a)Figure 2 XRD patterns of TMAC6B and TMAC5S

3.2 Surface area measurements
Table 2 shows the results of surface area measurements of AC,(b)

TAC and TMAC by BET method. As mass ratio of Titania
increased, surface area decreased. This is probably due toblockage of AC pores by titania[4]. The decrease of surface
are of TMAC could be attributed to the blockage of AC poresby magnetite [5].

Figure 4 EDS results of (a) TMAC6B and (b) TMAC5S
226

4. Results and discussion
4.1 Photocatalytic activity of TAC.

Table.3 Degradation of amount of MO by TAC and TiO2

The result of photocatalytic activity of new sample of TAC(TAC1) and reused sample of TAC(TAC2) were shown in Fig
5 and Table 3.The photocatalytic activity of TiO2 was alsomeasured for comparison. Here, the photocatalytic activity ofsmall size of TAC1 (TACS1) was much higher than big sizeof TAC1 (TACB1) and TiO2. However, TACS2 showedsignificant drop in photocatalytic acitivity compared to
TACB2. The drop in photocatalytic activity could be

4.2 Photocatalytic activity of TMAC

attributed to the detachment of TiO2 from TACS during the

The result of photocatalytic activity test of TMAC was shown

photocatalytic activity test and/or the covering of TACS by

in Fig. 6 and Table 4. TMAC showed a very low

the byproducts from MO photodegradation. On the other hand,

photocatalytic

TAC6B showed comparable performance to pure TiO2

photocatalytic activity of TMAC5S is much lower than that ofalthough the amount of TiO2 was only about 2/3 of pure one.

TMAC6B. This low activity could be attributed to heat

And this sample also showed insignificant dropped intreatment and photodissolution during UV irradiation.

acitivity

comparedto

TAC.

Moreover,photocatalytic activity after reuse. Previous study explained
about the synergy effect between TiO2 and AC which
improves the photocatalytic activity of the composite material
[3].

(a)

Dark adsorption

Figure.6 Photocatalytic activity of TMAC

Dark adsorption

Table.4 Degradation of amount of MO by TAC and TMAC(b)

4.2.1 Heat treatment
Three causalities can be considered concerning the decrease in

Dark adsorption

photocatalytic activity of TMAC, the phase transformation of
TiO2 from anatasae to rutile [7], Formation of Pseudobrookite,
Fe2TiO5 [7], and the diffusion of Fe ions into the layer of TiO2
coated on the surface of AC[8]. The first issue of phase

Fig.5 photocatalytic activity of (a) TAC1 and (b) TAC2transformation could be removed since XRD analysis show norutile phase. For the second issue, TMAC5S showed phase of327

Fe2TiO5 that could act as recombination site for electron and

The photocatalytic activity of TAC decreased after reused.

hole, thus reducing the photocatalytic activity of the catalyst.

Especially, decrease of photocatalytic activity of TACS is

For the third issue, Beydoun et al[1] showed that Fe diffusedhigher than that of TACB. The decrease of photocatalytic

into TiO2 during the heat treatment could also act as

activity could be attributed to the detachment of TiO2 fromrecombination site for electron and hole. It is possible that the

TACS during the photocatalytic activity test and/or thesecond and the third causalities mentioned above caused thecovering

decrease in photocatalytic activity of TMAC.

photodegradation.

of

TACS

by

the

byproducts

from

MO

4.2.2 Photodissolution

The decrease of TMACS photocatalytic activity could be

Photodissolution of Fe in titanium/iron oxides system during

attributed to the formation of composite oxide of Ti and Fe,

UV irradiation has been reported in previous study [1]. Thisand the diffusion of Fe into TiO2 during heat treatment

phenomenon occurs due to electronic interactions between
TiO2 coating and iron oxide where the photogenerated

All prepared catalysts showed magnetic property due to theelectrons in TiO2 phase are transferred into iron oxide phase.

presence of magnetite phase in them.

This causes the formation of Fe ions that could migrate to thesolution through the pores of TiO2 coating. However, in thiswhile in the previous study, the TiO2 was coated directly on

6. Future plans
In order to develop TMAC as a practice photocatalyst,
additional researches are needed to increase photocatalytic
activity of TMAC. The two ways of ehance photocatalytic
activity could be considered. The first way is to develop amethod that calcinations temperature is decreased until
diffusion of Fe ions can be inhibited and anatase phase ofiron oxide core [1]. The interaction between TiO2 and ironTiO2 is prepared. The second way is to introduce of anoxide in this study is thought to be minimal.

intermediate passive SiO2 layer between the titanium
dioxide phase and Activated Carbon inhibited the directcontact.

study, ICP-AES analysis of Fe ions after UV irradiation
showed no Fe element detected meaning that photodissolution
of Fe did not occur in the system. This could be explained
from the preparation procedure where in this study, firstly, theiron oxide introduced into the AC before coating by TiO2,

4.3 Magnetic property of TMAC
XRD analysis result showed magnetite phase in TMAC. The
test of magnetic property was carried out by applying
commercial neodymium magnet on the samples and weighting

7. References

the amount left (not attached to the magnet). The result is[1] D. Beydoun, J. Phys. Chem, B 104 (2000) 4387–4396.

showed in Table 5. Magnetic force of TMACB was stronger[2] Y. Ao et al, Separation and Purification Technology , 61

than that of TMACS. The formation of Fe2TiO5 reduced the(2008) 436–441

amount of magnetite phase in TMACS, thus decreasing the[3] J. Matos et al, Applied Catalysis B: Environmental , 18

magnetic force of TMACS.

(1998) 281-291[4] X. Wang et al, Journal of Hazardous Materials, 169 (2009)
1061–1067

Table.5 Comparison test of magnetic force[5] J. Araña et al, Applied Catalysis B: Environmental, 44(2003) 161–172[6] Y. Ao et al, C A R B ON, 4 6 ( 2 0 0 8 ) 5 9 6 –6 0 3[7] F.X. Ye et al, Materials Science and Engineering B,148(2008) 154–16[8] Jimmy C et al, Environmental Science andTechnology, VOL. 37. NO. 10, 2003 /5. Conclusions
TAC and TMAC were successfully prepared. All preparedcatalysts

showedphotocatalytic

activity

towardMOdegradation under UV irradiation.

428

Selective Catalytic Reduction of Nitrogen Oxides with Propene
over Ag/CeO2-TiO2 Catalyst
Student Number: 10M18298 Name: Yang YANG Supervisor: Hirofumi HINODE

プロペンを還元剤とした Ag/CeO2-TiO2 触媒による NO 選択還元楊 洋
本研究では、過剰酸素存在下でプロピレンを還元剤とする NO 選択還元 (HC-SCR) を目的とした触媒の開発を行った。Ag/CeO2-TiO2 触媒を用い、焼成温度、Ag 担持量、C3H6 濃度影響及び酸素有無影響を検討した。
550℃は最適な焼成温度であり、この温度で焼成した 3wt%Ag/CeO2-TiO2 触媒が最大活性を示し、400℃で約63%の NO 分解が達成できた。また、HC-SCR において C3H6 と酸素の存在は不可欠であることを確認した。

1

Introduction
Air pollution by nitrogen oxides (NOx)effective redox Ce4+/Ce3+ sites and their ability

emitted from mobile and stationary sources is

to exchange oxygen[1]. The presence of ceria

one of serious environmental problems to beenhanced the oxidation of NO to NO2, thereby

solved because NOx contribute to the formation

increasing the activity of NO reduction[2]. Inof acid rain and photochemical smog, global

our laboratory, activity of various TiO2 support

warming, depletion of ozone layer.

metal catalysts had been investigated[3-5]. In

Nowadays, three-way catalysts (TWC) arereaction mechanism suggested, NO reduction

generally used to reduce NOx in automobiles.

possibly occurred via the formation of NO2.

This method can reduce NOx with highSomeefficiency at specific air to fuel (A/F) ratio.

CeO2-TiO2 mixed oxide which has a high

Recently, lean-burn gasoline or diesel engines

surface area in enhancing the oxidation of NO

have highly attracted attention due to theirto NO2[2,6]. On the other hand, silver plays anfuel efficiency. However, the presence of excess

important role as the active species andO2enhance the catalytic activity of Ag/TiO2-ZrO2

inexhaust

gas

from

these

engines

suppresses NO reduction activity. Therefore,studiesalso

reported

the

role

of

in HC-SCR of NO using C3H6[7].

catalyst that can efficiently convert NO to N2 in

Therefore,

in

this

study,

theuniquethe presence of O2 is desirable. Among several

properties of CeO2-TiO2 support and theapplicable

methods,

reductionwithselective

catalytic

activity of Ag were combined to develop ahydrocarbons(HC-SCR)

CeO2-TiO2 supported Ag catalyst effective forcontained in the exhaust is currently the most

HC-SCR of NO using C3H6 in the presence of O2.

studied technology for NO reduction.

The effects of calcination temperature, Ag

Ceria (CeO2) is an important rare earth oxideloading levels, C3H6 concentrations and oxygenand has been widely investigated in thepresence on catalytic activity of prepared

automotive exhaust purification related tocatalysts have been investigated.

oxygenstorageandreleasecatalysis.

Aremarkable property of CeO2 is the number of
1

29

2

to 550℃.

Experimental

2.1 Materials

NO and NO2 concentration were analyzed by

CeO2-TiO2 catalysts were preparedby

NOx analyzer (Shimadzu, NOA-7000). N2O andco-precipitation method using TiO2 precursor of

CO2 were analyzed by gas chromatographs[(CH3)2CHO]4Ti (Wako) and CeO2 precursor of(GC-323W for N2O; GC-390 for CO2). Catalysts

Ce(NO3)3・6H2O (Wako) with the same molar

were characterized by TG-DTA, XRD, N2

ratio for Ce and Ti. Firstly, Ce(NO3)3・6H2O wasadsorption (BET method) and SEM-EDS.

dissolved in 35ml of deionized water with
continuous stirring and the pH was maintained

3 Results and Discussion

between 0.5-1.0 by addition of HNO3. Then

3.1 Characterization of Prepared Catalysts
Figure[(CH3)2CHO]4Ti was added to the solution and1 shows the XRD patternsofthe pH was adjusted to between 9-11 by

3wt%Ag/CeO2-TiO2 catalysts with different

addition of NH3 solution. The resulting mixture

calcination temperature. Ag metal phase was

was filtered, dried at 100℃ for 8hours andconfirmed at calcinations temperature higher

calcined at 550℃for 4hours under air flow.

than 550℃. Starting from 700℃, the rutile

Ag/CeO2-TiO2 catalysts were prepared byphase of TiO2 was observed indicating theimpregnation method. Firstly, Ag precursor ofphase transformation of TiO2 from anatase toAgNO3 (Wako) was dissolved in 50ml ofrutile.
Figuredeionized water and mixed with CeO2-TiO2.
Then

the

mixturewasstirredat

2 shows the XRD patterns

of

room

temperature for 12hours and dried at 80℃ for
12hours and calcined at 400, 550, 700 or 800℃
for 4 hours under air flow. Using this method,
Ag/CeO2-TiO2 catalysts with Ag loading of 0.5,
1, 2, 3, 5wt% were prepared.
All catalysts were pelletized, crushed, andsieved to 0.71-1.00 mm prior to catalytic
activity test.

2.2 Catalytic Activity Test
The catalytic activity test was carried out
with a fixed-bed flow reactor by passing areactant gas containing 1500ppm of NO, 10% of

Ag/CeO2-TiO2

O2, 1500ppm of C3H6, and helium as balanceloading levels. Ag phase was confirmed in allgas. 1.0 g of catalyst was used with acatalysts prepared. Ag loading of more thancorresponding space velocity of 13000 h-1 and a

3wt% showed an effect on TiO2 phase formed.

total gas flow rate of about 4 ml/s. The

At 5wt% of Ag loading level, both anatase andtemperature was changed stepwise from 150℃

brookite phase of TiO2 were observed.

230

catalysts

withdifferentAgdecrease of specific surface area and the
reduction in anatase phase of TiO2. To confirm
the latter possibility, the comparison between
the catalytic activity of anatase and rutile
phase of TiO2 in Ag/CeO2-TiO2 catalyst isnecessary. One previous study reported thatthe dispersion of active sites was better inanatase phase than rutile phase leading to abetter catalytic activity[8].

Table 1 shows the specific surface area ofseveral samples. It can be seen that highcalcination temperature could significantly
decreased the surface area of the catalysts. It
was generally known that due to the sintering
effect on particles, bigger particles with lower
surface area will be formed at high calcination
temperature.

3.3 The Effect of Ag Loading Levels
Figure 4 shows the conversion of NO to N2
over Ag/CeO2-TiO2 catalysts with different Ag
loading levels (0.5, 1, 2, 3, 5 wt%). Ag loadinglevel of 1wt% led to an improved activity of thecatalyst. Previous study proposed a reaction

3.2 The Effect of Calcination Temperature

mechanism where Ag promotes the conversion

Figure 3 shows the conversion of NO to N2
over

3wt%Ag/CeO2-TiO2

with(-NCO) species with NO2 on Ag active sites[7].

temperature

However, Ag loading level higher than 3wt%

(400,550,700,800℃). The catalyst calcined atshowed a decrease in the activity of the

550 ℃ showed the maximum activity. This

catalysts. This could be attributed to theresultpatterns

formation of brookite phase of TiO2 whichsuggested that calcination temperature of

reduced the amount of anatase phase of TiO2.

400℃ was not enough to provide the catalyst

Again, the comparison of activity of anatasewith catalytically active phase of Ag metal. On

and brookite phase of TiO2 in Ag/CeO2-TiO2

the other hand, the decrease of activity on

catalyst is necessary to confirm this.

different

calcination

together

with

the

catalysts

of NO to N2 through the reaction of isocyanate

XRD

catalysts prepared at calcination temperature
higher than 700℃could be attributed to the3313.4 The Effect of C3H6 Concentrations

4 Conclusions

Figure 5 shows the conversion of NO to N2

Ag/CeO2-TiO2 catalyst active for selective

over 3wt%Ag/CeO2-TiO2 catalyst with different

catalytic reduction of NO using C3H6 wasC3H6 concentrations (0, 500, 1000, 1500 ppm).

successfully prepared in this study.

Without C3H6 (0 ppm), NO could not be

The catalyst calcined at 550℃ showed thedecomposed. When C3H6 was added to thehighest activity (maximum NO conversion tosystem, there was a significant increase in NO

N2 63% at 400 ℃ ). Calcination temperature

conversion to N2, while the conversion of NO toaffected

NO2

These

activity of catalyst, the specific surface area ofconfirmed the role of C3H6 as reducing agent in

catalyst, the type of TiO2 phase and the amount

HC-SCR of NO and that NO2 was one of theof Ag metal formed in the catalyst.

decreased

(data

not

shown).

intermediates during NO conversion to N2.

severalfactors

determining

theCatalyst with Ag loading level of 3wt%
showed the highest activity (maximum NO
conversion to N2 63% at 400℃). Ag loading up
to a certain amount enhanced the catalytic
activity. However, a high Ag loading level could
lead to formation of TiO2 phase that could
decrease the activity.
C3H6 roleas

reducing

agent

and

the

importance of O2 presence in HC-SCR of NO
has been confirmed.

3.5 The Effect of O2 Presence

References

Figure 6 shows the conversion of NO to N2[1] Proceedings of the 11th ECERS Conference, Krakow, 2009

over 3wt%Ag/CeO2-TiO2 catalyst with 10%O2or[2] R.Q.Long,R.T.Yang Appl.Catal.B 27 (2000) 87-95

without O2. In the presence of O2, NO[3] J.Mitadera; Master Thesis, Tokyo Institute of Technology (2003)

decomposition[4] H. Kawai; Master Thesis, Tokyo Institute of Technology (2004)

activity

shiftedtolower

temperature range compared to that without[5] C.Tang; Master Thesis, Tokyo Institute of Technology (2006)

O2. This shows that the presence of O2 could[6] Journal of Hazardous Materials 174(2010) 734-739

improve the activity of prepared catalyst on[7] Catalysis Today 42(1998) 127-135

HC-SCR of NO.

[8] M.Makii; Master Thesis, Tokyo Institute of Technology (2008)

4

32

ESTIMATION OF CO2 EMISSION FROM URBAN FREIGHT TRANSPORT IN KHON KAEN, THAILAND
Student Number: 10M18217

Name: Shinsuke Mogi

Supervisor: Shinya HANAOKA

タイ国コンケン市における都市内物流部門からの CO2 排出量推定茂木慎祐
本論文では、タイ国コンケン市を対象に、都市内物流部門からの CO2 排出量を推定した。現地で物流調査を実施し、現状維持、公共交通整備に伴う駅周辺商業地域発展、大型貨物車通行規制、電気ピックアップ普及という 4 つのシナリオで、2012 年から 2050 年まで走行貨物車による CO2 排出量の将来推定を行った。その結果、公共交通整備に伴う駅周辺商業地域発展及び電気ピックアップ普及を組み合わせた場合、最も CO2
排出量抑制効果があることを示した。
1.

Subregion’s East West Corridor, Khon Kaen is planned to develop

Introduction

traffic and transportation system. In fact, Khon Kaen has a plan to

It is imperative to reduce CO2 emission from transport

construct 5 lines of bus rapid transport (BRT) by 2022.

sector in terms of global warming. However, due to increasing
motorization rate in cities of developing countries, it is difficult to
reduce CO2 emission by around 20 to 50 percent with general

2.2 Selection of Methodology

CO2 cut policies. Therefore, Low-Carbon Asia Research Project,

Four-step model is a general method applied to forecast

which is funded by the Ministry of the Environment, Japan, aims

traffic volume in road network. In this research, the first two steps

at identifying policy roadmaps including land use policy toward aof four-step model are applied to estimate truck OD. The whole

2050 vision of low carbon society in Asia. However, many cities

estimation steps are shown in Figure1.

in developing countries have no existing data on logistics so thatthey face difficulties to make effective CO2 reduction policy onlogistics. Consequently, it is necessary to estimate CO2 emission
from urban trucks in order to assess physical distribution policies
in cities of developing countries.
Research objectives are as follows.
1)

To estimate truck trip origin-destination (OD) at a base yearof 2012 by conducting an interview survey in Khon Kaen2)

To compare 2050 estimated CO2 emission from urban trucks
between four scenarios: 1) Business-as-usual (BAU), 2)
Transit-oriented development (TOD), 3) Heavy truck ban
Figure1. Flowchart to estimate CO2 emission

and 4) Electric vehicle pickup dissemination (i.e. EV
pickup)Transit-oriented development (TOD) is an approach to city

2.2.1 Zoning of the study area

development with public transportation focusing on land use

Khon Kaen is divided into 45 zones, while outside of it isaround stations of the public transportation. In this research, TOD

divided into 5 zones, totally 50 zones (See Figure2).

is applied to both passenger and freight transport sectors, so TOD
also indicates that a public transport network is constructed ontruck routes and more offices are condensed near the stations.

2.

Research Methodology

2.1 Selection of Study Area
The study area is an urban area of Mueang Khon KaenDistrict in Khon Kaen province, Thailand (hereinafter referred toas “Khon Kaen”). Since Khon Kaen is located on Greater Mekong

Figure2. Zoning map of Khon Kaen

33

urban trucks. Heavy truck ban scenario has two major setups: the2.2.2 Estimation of truck trip generation/attraction
Truck trip generation (i.e. G) and attraction (i.e. A) are

first one is that the number of pickup trips increases at much

estimated in equation (1).
𝐺 = 𝛼𝑔 𝑁𝑜, 𝐴 = 𝛼𝑎 𝑁𝑜
𝑡𝑎
𝑡𝑔
(1)
=
𝑁
=
𝑁 ,
𝑛𝑜 𝑜
𝑛𝑜 𝑜
Here, trip generation/attraction per office unit: 𝛼𝑔 , 𝛼𝑎 , thehigher rate than one of 6 and 10 wheel trips year by year. The

zone: 𝑛𝑜 , truck trip sample generation/attraction: 𝑡𝑔 , 𝑡𝑎

Ring Road.

estimated with a regression model equation (2) which has two

EV pickups are expected to be used in the future. EV pickup

independent variables: the number of employees (i.e. 𝑁𝑒 ) and

scenario means that newly registered EV pickups increase every

second one is that the distribution of truck trips in 2050 becomes
the same as the distribution of registered trucks in Bangkok
Metropolitan Region in 2002 when heavy trucks with 10 wheels

number of offices by zone: 𝑁𝑜 , the number of office samples byor more had been restricted to entry and park within the Middle

The number of offices by zone (i.e. 𝑁𝑜 ) in equation (1) is

Since pickup trips are largest of three in 2012 (See Table1),

population (i.e. 𝑁𝑝 ).

𝑁𝑜 = 𝛽0 + 𝛽1 𝑁𝑒 + 𝛽2 𝑁𝑝

year among the total newly registered pickups in Khon Kaen.

(2)
Table1. Distribution of trips by vehicle types

In addition, truck trip production (i.e. 𝑇) is set up by

equation (3) as control total of the amount of truck trips in Khon
Kaen.

T

𝑎𝑒 𝑁𝑒𝑇𝑡𝑔 + 𝑡𝑎 𝑇
=
𝑁𝑒
2𝑛𝑒
=

(3)

Here, truck trip production per employee: 𝑎𝑒 , the total number of
employees in Khon Kaen: 𝑁𝑒𝑇 , the number of employee samples:3.

Data Collection

𝑛𝑒 , truck trip sample generation/attraction: 𝑡𝑔 , 𝑡𝑎

3.1 Outputs of interview survey

2.2.3 Estimation of truck trip OD

sample generation/attraction per office unit and 2) truck trip

This interview survey has the two outputs: 1) truck trip

sample OD.

Frater method is used to estimate truck trip OD by vehicle
type based on tuck trip sample OD and estimated truck trip

3.2 Steps of the interview survey

generation/attraction in 2012. However, since the truck trip
sample OD has the value of 0 at many cells, 50-zone sample OD

A surveyor visits a target office and conduct interview to amatrices are consolidated into 7-zone sample OD matrices at first

shopkeeper of the office. Totally 24 surveyors and 3 directors

by following 7 zones in Figure2. After estimation, truck trips inworked on the survey for 15 days (i.e. from 16 to 30 November

7-zone OD matrices are divided into each cell of 50-zone OD2012).

matrices by using the number of employees by zone.
3.3 Survey items
Survey items used to this research are showed in Table2.

2.3 Scenario Setting
Based on a concept of TOD, Khon Kaen is planned to open

When an interviewee answers to vehicle type, he or she selects

5 BRT lines by 2022. Therefore, newly commercial area is

one of four vehicle types: pickup truck, 6 wheel truck, 10 wheel

expected to develop near BRT stations. TOD scenario means thattruck and more than 10 wheel truck.

the number of offices near BRT stations increases year by year
Table2. Survey items of Interview Survey

while those far from the stations decrease year by year.
Table1 indicates that in 2012 more than half of the total
truck trips in Khon Kaen are 6 and 10 wheel truck trips (heavy
truck trips), even if Khon Kaen is an urban area. Therefore,
Heavy truck ban may be effective in terms of CO2 reduction from34

4.

Results and Discussion

4.1 Results
4.1.1 Analysis on survey data
As the result of the survey, the number of effective officesamples is 127 (i.e. 8.26% of the total number of offices in Khon
Kaen) and 330 truck trip effective samples. In the interview
survey, office samples in each zone were collected, but somezones had 0 effective office samples as shown in Figure3.
Since the number of more than 10 wheel truck trip samples
Figure4. Location distribution of truck trip generation in 2012is only 4 of the total number of truck trip samples of 330, thistruck trip’s sample OD matrix cannot be used to estimate trip OD
matrix in 2012 with Frater method. Thus, a more than 10 wheel
truck

is

not

consideredwhenestimating

truck

trip

generation/attraction in 2012.

Figure5. Truck trip OD in 2012

Figure3. Location distribution of offices in 2012

4.1.3 2050 estimated truck trip generation/attraction
TOD scenario indicates that the number of offices near
BRT stations increase while those far from the stations decrease.

4.1.2 Truck trip generation/attraction and OD in 2012
Figure4 illustrates where truck trip samples and estimated

Ito at el. (2011) represents population distribution as an urban

truck trips in 2012 are generated. Truck trip sample generation

structure to minimize CO2 emission from passenger transport intends to be high when office samples are located in suburb ofKhon Kean in 2022. Since such the population distribution is used

Khon Kaen and have greater than or equal to 50 employees.

in the TOD scenario, more offices are located near BRT lines in

However, it cannot not be judged whether the truck trip sample

2050 as shown in Figure6. Additionally, Figure7 shows the samegeneration reflects realistic situation on logistics in Khon Kaen

trend in case of truck trip generation at the year of 2050.

because commercial area and residential area exist in the samezone in Khon Kaen. Therefore, when truck trip generation in 2012is estimated, it is assumed that the number of offices by zone is
proportional to the number of truck trips by zone.
Figure5 shows that truck trip sample OD from/to outside andsuburb of Khon Kaen is relatively large, when office samples arelocated in suburb and have greater than or equal to 50 employees.
The fact that there are more empty lots in suburb than in center ofKhon Kaen may lead to build offices which have large number of
employees.

Figure6. Location distribution of offices in 2050

35

percent compared with BAU scenario, because the estimated CO2
emission is influenced by downward trend of CO2 emission frompower sector in Thailand Power Development Plan.

Figure7. Location distribution of truck trip generation in 2050

Figure8. Comparison of estimated vehicle-kilometers toward 2050

4.2 Discussion
Estimated results from 2012 to 2050 in not only 4 scenarios
but also combined TOD and EV pickup scenario are shown in
Figure8 and Figure9.

4.2.1 Comparison of 2050 estimated vehicle-kilometers
Compared

with

in

BAU

scenario, 2050

estimated

vehicle-kilometers in TOD scenario are reduced by 27 percent(See Figure 8). This is because more truck trip OD has shorter

Figure9. Comparison of estimated CO2 emission toward 2050

distance between zones since more truck trip generation isconcentrated near the BRT stations.

5.

Conclusions

Heavy truck ban and EV pickup scenario increase 2050

Based on the interview survey, characteristics of truck trip

estimated vehicle kilometers by 155 and 27 percent compared

generation/attraction in Khon Kaen are clarified. For example,

with BAU scenario. This is because 4 and 6 pickup trips areheavy trucks easily enter Khon Kaen and truck flow from/to

generated when a 6 and a10 wheel truck trip are converted, and 2

outside and suburb of Khon Kaen is relatively large.

EV pickup trips are generated when a pickup trip is converted.

As the result of comparison between 4 scenarios, TOD has

Trip conversion ratios are decided based on ratios between

big impact on reducing 2050 CO2 emission. Heavy truck ban has

payloads of 2 different vehicles.

big impact on increasing 2050 CO2 emission. EV pickup
dissemination has small impact on reducing 2050 CO2 emission.
Consequently, combined TOD in freight transport and EV pickup

4.2.2 Comparison of 2050 estimated CO2 emissions

dissemination is the most effective for CO2 reduction.

Figure9 shows that 2050 CO2 emission in TOD scenario is
reduced by 26 percent compared with in BAU scenario due to thehuge reduction of 2050 vehicle kilometers.

References

Heavy truck ban scenario increases 2050 CO2 emission by

1)

Y. Ito et al. (2011): Study on the Model for Developing the64 percent compared with BAU scenario due to huge growth in

Urban Structure to Minimize CO2 Emission –Case of Khon

2050 vehicle kilometers.

Kaen City, Thailand-, Master Thesis at Nihon University (inEV pickup scenario reduces 2050 CO2 emission by 6

Japanese)36Which factors influence the relief goods convergencein humanitarian logistics?
Student Number: 11M18019

Name: Tsunenori ANDO

Supervisor: Shinya HANAOKA

人道援助ロジスティクスにおける物資滞留問題の解析安藤 恒徳	
  東日本大震災のような大規模災害時には，被災者支援を目的とした人道援助ロジスティクスが必要であり，支援物資輸送はその中心に位置づけられる．しかし，過去の災害も含め，集積所における物資の滞留が問題点として指摘されてきた．そこで本研究では，東日本大震災を対象に物資滞留に影響を与える要因を明らかにした．また，支援物資輸送の滞留現象を再現するシミュレーションモデルを構築し，物資滞留発生現象の主要因を解明した．
humanitarian logistics, and it is often observed in

1. IN TRODU CTION

the Tohoku Earthquake. Fig.2 shows the amountof inventories in warehouse. It turns out thatvolumeofinventories

wasdramaticallyincreasing on 16 March, but after that there were
few amounts of goods leaving the warehouse andmany goods remained as stock. This is aphenomenon of goods convergence.

Fig.2. Amount of relief supplies[water] in Miyagi
1st warehouse	  Source: NRI[1]100 150 200 250 300 350 400 450 500 550

For solving this problem, this study proposes tobuild a simple model to express relief goods
convergence in humanitarian logistics based on
the Asymmetric Simple Exclusion Process(ASEP). The objectives of this study aresummarized as the following:i.) To identify the causes of relief goods
convergence.
ii.) To build humanitarian logistics flow model.
iii.) To analyze the simulate results.

50

2. IDENTIFYING CAUSES OF
RELIEF GOODS CON VERGEN CE

0

Number of disasters reported

In recent years, natural disasters, such as anearthquake, a flood, and a typhoon, areincreasing globally as shown in Fig.1. When theearthquake and tsunami in the coast of Sumatrathat occurred in 2004, that supplies thenecessary support to victims have not received
enough is actualized, is globally recognized as"Logistics is a concern issue". Since then, theneed to build appropriate humanitarian logistics(HL) has been pointed out in many places.
In the Haiti earthquake in 2010, although thesupport goods from each country had arrived to
the large-scale warehouse, even the disastervictim of the end was not prudent and it exposed
insufficient logistics management. In addition,
due to the frequent occurrence of large-scale
natural disasters, there is a growing interest in
the HL also in international organizations. The
World Food Program (WFP) manages United
Nations
Humanitarian
Response
Depot(UNHRD), which owns 40 vessels, 60 airplanes,
and 5,000 tracks Natural
directly,and is carrying out HLdisasters reported 1900 − 2011itself.

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

2010

Year

Fig.1. Natural disasters reported 1975-2011

EM−DAT: The OFDA/CRED International Disaster Database − www.emdat.be − Université Catholique de Louvain, Brussels − Belgium

Source: EM-DAT

Relief goods convergence is a big issue of
37

Several reports describes the problem of relief
goods convergence of Tohoku Earthquake [2][3]Based on these report, there are six causes forthis problem, as follows:i.) Operation by inexperienced officersii.) Unregulated and uncontrolled operation

iii.) Lack of warehouse facilitiesiv.) The difficulty in sharing informationv.) Frequent demand changevi.) Many suppliersThis study focuses on the problems of vi.) many
suppliers. Other causes are not subjects of thisstudy because they are possible for solving bystandardization of the operation method andtechnological development.

Fig.4. Production plant model

After that, they are transported to 1st warehouseplaced in the prefecture. In 1st warehouse, theunloaded relief goods are sorted for 2nd
warehouse placed in the municipality andtransported to 2nd warehouse. In 2nd warehouse,
the unloaded relief goods are again sorted for
shelter and transported to shelter. This flow isused as a reference to make a model.

3. ASEP M ODELASEP is a non-equilibrium statisticalmechanics model, called the one-dimensional
asymmetric simple exclusion process. ASEP isreferred to as an open system that the system asshown in Fig.3. Particles are inserted into theline with the inflow probability α and move tonext box in probability p. After that, they
removed at the end with the outflow probability
β.
Fig.3.

4.2 M odeling hum anitarian logistics
by ASEP
Humanitarian logistics flow is generally
characterized by a complex network structure
where many processes join and diverge eachother. In order to simplify things, we consider aone-dimensional model with a strictly linear
structure as shown in Fig.5. Let us assume thathumanitarian logistics delivers N relief goods.
The N relief goods move downstream to theshelters. Relief goods leave DP by the supply
probability Sp, and move a transportation cell by
the transportation probability Tp, and in this cell,
the concept of ASEP is used. In a warehouse cell,
there is no effect of ASEP. So two or more goods
can put into one cell by the input volume
probability Ip, and come out of here by Output
volume probability Op.

ASEP
model	
 Source:[4]Source: [4]ASEP model is used to represent traffic stream.
ASEP figured out principle of traffic congestionand proposed a solution. And, it was applied theresults to improvement of production efficiency inplant by considering products as cars. So, thismodel can represent relief goods convergence inhumanitarian logistics in a similar way.
Minemura, et al[4] developed a simple model ofa production plant based on the ASEP andsimulate the dependence of the lead time T on
the lot size r. Then, they derived an analyticaldescription of the simulation results based on
exact results for the single-species ASEP.
Furthermore, they determined the optimum lot
size and investigate dependence of it on several
parameters used in the simulations. A production
plant is in general characterized by a complex
network structure where many processes join
and diverge each other. In order to simplify
things, they first consider a one-dimensionalmodel with a strictly linear structure (Fig.4).

Fig.5. Humanitarian logistics model(1) Setting the cell
Some cells in this model are two of the cells andcell transport depot. First, a transportation cell
expresses the process of transportation and thenumber of cells expresses the length of the time
concerning the transportation. Moreover, awarehouse cell expresses a warehouse and the

4. M ODEL DEVELOPM EN T
4.1 Concept of H um anitarian logistics
Collected relief goods are loaded in trucks andother means of transport in distribution point.

38

5.3 Sim ulation conditions

number of balls that are in this cell is in stock.
(2) Setting the transition probability function
Input and output volume probabilities are
estimated from the actual data. And transport
probability and supply probability are given
arbitrarily.
(3) Setting the time
Let the concept of the time in this model be thenumber of times of calculation of a simulation.
Calculation times are when the probability
calculation was performed in all spheres locatedon the cell. And it considers that this one
calculation is 1 hour, and regards it as one day in
24 hours.
(4) Simulation calculation
Simulation is performed 10 times. Java is used
for the calculation of the simulation.

The simulation using Humanitarian logistics
model and estimated Input volume probability
and Output volume probability is performed. The
performed simulations are four cases of Iwate
water, Miyagi water, Iwate clothing, and Miyagi
clothing. As a virtual value, the number of goods,
the number of cells, etc. see volume of inventories
and a lead time how change from change ofprobability. The parameters used in thesimulations are summarized in Table1.
Table.1 Simulation condition
!# #! &# !#$!
""$##"$ ' !#'
!" !# !#'
 $#%$ !#'
$# $#%$ !#'

5. SIM ULATION
5.1 Aggregate calculation of actual
data

#"      """#!$#(    """#!$#(  

5.4 Results	  Fig.7 shows simulation result of water in Iwate
prefecture to follow Poisson distribution based on
Table.1. These graphs are the change of entering(left) and dispatching (right). The horizontal axis
shows date and the vertical axis shows number ofgoods.

Aggregate calculation of database received fromTohoku University Logistics Research Groupshows entering and dispatching goods are
conducted randomly. This can be regarded as
Poisson process with random transport by many
suppliers.

5.2 Param eter estim ation of Ip and Op
Estimate Input volume probability and output
volume probability of the Poisson distribution
from the actual data. It is calculated as thefollowing equation (1):Fig.7 Simulation result
There are 3 patterns of change of inventory
volume of water in Iwate prefecture as shown in
Fig 8, 9 and 10 .
(1) Happening the goods convergence (Fig.8):
There are more than 5 days that more than 12
inventory volume. 12 is the max dispatching in aday.
(2) Maintaining inventories (Fig.9): There is no
goods convergence and out of inventory.
(3) Out of inventory (Fig.10): There is a day thatout of inventory.

(1)

Fig.6. Estimation result
Fig.6 shows expected frequency from estimation
result (blue line) and observed frequency of
database (red line) of water in Iwate prefecture.
X-axis shows the number of occurrences k andy-axis shows the probability of it.	
 Fig.8 Happening the goods convergence39

to be reduced sharply. It can be said that it is aneffective measures to perform controlled logistics
for the goods convergence in humanitarian
logistics from this result.

Fig.9 Maintaining inventories

Fig.11 Change of inventory
Fig.10 Out of inventory

Table.3 Improvement result

Table.2 Simulation results

$& "&%!)&#$&'$

( **("%-*'(*+(%'+*,&#+$'(&"#"*.
'&"))&%")*("+*"&%/
+*'+*,&#+$'(&"#"*. '&"))&%")*("+*"&%/
)+#*
&&)&%,( %"%*"%"% "%,%*&(")+*&"%,%*&(.

*"$)
*"$)
*"$

( **("%". "'(*+(%'+*,&#+$'(&"#"*.
'&"))&%")*("+*"&%/
+*'+*,&#+$'(&"#"*. '&"))&%")*("+*"&%/

)+#*
*"$)
*"$)

( *#&*!)"%". "'(*+(%'+*,&#+$'(&"#"*.
'&"))&%")*("+*"&%/
+*'+*,&#+$'(&"#"*. '&"))&%")*("+*"&%/
*"$)"%*"%"% "%,%*&(")*"$)

& 
& %

that goods may be stuck in the warehouse due to)+#*
&&)&%,( %""%"!($!!&!!!(!&"$%This paper showed the 6 causes of the goods
convergence identified by literature review. In
Humanitarian logistics model using ASEP withestimating parameters regarded Poisson process,the goods convergence was expressed anduncontrolled logistics due to many suppliers is
identified the cause of the goods convergence.
The results show that there is a high possibility

*"$)
*"$)

( *#&*!)"%-*'(*+(%'+*,&#+$'(&"#"*.
'&"))&%")*("+*"&%/
+*'+*,&#+$'(&"#"*. '&"))&%")*("+*"&%/ &&)&%,( %"%*"%"% "%,%*&(")#  $&$$*
# "%%"!%&$'&"!+  

6. CON CLU SION

)+#*
&&)&%,( %"%*"%"% "%,%*&(")!#'&("' #$"&*'&#'&("' #$"&*%'&

random transporting by many suppliers.

Reference

Table 2 shows results of all cases. As a result,the goods convergence can be shown in all cases.
The goods convergence is demonstrated due tomany suppliers as actual date.

[1]野村総合研究所: 経済産業省委託調査報告書 平成２３年度サプライチェーンを支える高度な物流システムの構築事業災害時等における緊	  急支援物資供給の効率化事業報告書,2012.
[2]桑原雅夫，和田健太郎:東日本大震災における緊急支援物資ロ
ジスティクス定量的評価:一次集積所における搬入/搬出記録の5.5 Discussion

分析, 第 45 回土木計画研究発表会, 2012.

Simulation results of change of inventory
volume expressed relief goods convergence. For
controlling input volume, the other simulation
supposing controlled logistics was performed byusing fixed Input volume probability (Table.3).
Target of this simulation is the clothes of Iwate
Prefecture. The result of this simulation showsthat it is able to maintain less inventory volume
as shown in Fig.11. The goods convergence is able

[3]峯猛:東日本大震災における救援物資供給停滞の発生とその要因，物流問題研究，No.56,pp16-21,2011[4]Takumi Minemura, Katsuhiro Nishinari, and Andreas
Schadschneider: Productivity Enhancement through Lot Size
Optimization, Cellular Automata Lecture Notes in Computer
Science Volume 6350, 2010, pp 593-599

40

Economic Operation of Large-Scale Photovoltaic power Plants under Uncertainty
Student number: 11M18031

Name: Junichirou Ishio

Supervisor: Naoya Abe

不確実性を考慮した大規模太陽光発電システムの経済的運用に関する研究
石尾 淳一郎本研究では，大規模太陽光発電システム（大規模 PV システム）の効率的な維持管理計画を策定するうえで必要となる基礎的要件を明らかにすることを目的とし，構成機器の劣化・故障の動態の分析，動的計画法による PV モジュールとパワーコンディショナ（PC）の交換計画の最適化，以上から想定される維持管理計画の経済性の評価・分析を行った．その結果，モジュールや PC の交換は経済的に効率的ではないことが明らかとなった．

probability of occurrence, probability of progress, and effect to the
output decline were considered. The function of time-related dynamics
of a PV module output is expressed as:

1. Introduction
Following the introduction of Feed-in Tariffs (FIT) for large scalecommercial photovoltaic (PV) power plants (mega-solar plants), thenumber of such plant has been substantially increasing in Japan. In
order to gain revenue from their plant, operators need to keep the highlevel of output from the systems during the project. To accomplish thispoint, the operators have to manage the uncertainties related to failure
occurrence. The failures occur at random but random operation andmaintenance (O&M) are not so efficient. Well-designed plans for goodO&M are necessary for the PV system operators.

 1  DRh t  1  DRt t (eq. 2)where, P(t) is the annual amount of output from a module at year t(kWh)，Pmax is the annual amount of output of initial year of the project(202 kWh)，and DR is the degradation rate. Each four failure occurs byfollowing each failure occurrence probability. To get the probabilities,
we calculated the reliability of a PV module against these failures. The
reliability is given by equation (eq. 3) (Fukui 2008).

2. Objectives
1. To simulate the dynamics of time-related deterioration of PV
modules, the failure occurrence of power conditioners, and the
dynamics of output change of large scale PV systems.
2. To clarify the basic characteristics of well-designed O&M plans
which maximize the profit from large-scale PV system.

Rt  nt 
N(eq. 3)R(t) is the reliability of PV module at year t，n(t) is the number ofactive items at year t (“active” means “never failed”) and, N is thenumber of total items in the targeting systems. According to Realini(2003) and Hasegawa (2011), who analyzed Realini’s data by FTA(Fault Tree Analysis), for 21 years old PV modules, the reliability
against yellowing: 2.4%, delamination: 9.0%, hot spot: 75.1%, terminal
oxidation: 56.6%. De Lia (2003) demonstrated that, the degradation
rate of a PV module is fixed. Therefore we assumed that the probabilityof every failure occurrence follow the exponential distribution because
the failure rate is independent from time if we assume exponential
distribution (eq. 4).

3. Output decline of a mega-solar plantTo simulate the dynamics of large-scale PV system, we simulated thetime-related PV module deterioration by considering four types offailure modes, and failure occurrence of power conditioner (PC). We
also considered the mismatch losses in PV arrays.
3.1. The dynamics of power decline of a PV module

First, we tried to determine the amount of annual output from apristine PV module. Japanese Industrial Standards (JIS C 8907, 2005)
gives the definition to estimate the output of it.
The output depends on nominal battery capacity, quantity of solar
radiation, and power losses caused by various factors. We postulated
the use of a 200Wp mono crystalline silicon module in Tokyo. It isfacing south and the angle of elevation is 30°. Then the amount ofannual output from a pristine PV module is given by:
E p  H  K  P  365  1

Pt   E p  1  DR y t   1  DRd t 

ht   

( : fixed)(eq.4)

Then the reliability function R(t) is expressed by eq. 5.
tRt   exp  dt   exp t 
 0 



(eq.5)

Subsequently the failure occurrence probability is given by eq. 6.

(eq. 1)

where, Ep is the amount of annual output from a module (kWh/year), H
is the amount of solar radiation on the panel per a day in Tokyo (3.74
kWh/m2/day)，K is the factors of losses (74%), [K is composed of loss
by heat (15%)，loss in PC (6%), and loss of circuit (7%)], P is thenominal PV capacity (200Wp)，365 is the number of days in a year and，
1 is the general solar irradiance (1kW/ m2). The resulting amount ofannual output from a pristine PV module in Tokyo is 202kWh. This
number was then used to simulate the time-related deterioration of PV
modules. In this research, we considered four types of failure modes
and simulated their occurrence and progress on PV modules.
3.1 Output simulation from a PV module
A number of reports on the cause of PV module degradation (i.e.,
Kato 2010，Ferrara 2012) were studied, but we adopted the report“Mean Time Before Failure of Photovoltaic modules” by Realini(2003). Realini reported not only the factors which cause degradation
but also their numerical information such as the frequency ofoccurrence in 10kW PV modules and the output decline of 21 years old
PV modules. We focused on four degradation failures modes what
Realini depicted in the report, i.e., “Yellowing”, “Delamination”, “Hotspot”, and “Terminal oxidation”. In this research, these four factors’

41

 

ln Rt t(eq.6)

We can calculate the failure occurrence probability of each failuremode by eq. 6 and the data given by Realini. The failure occurrence
probabilities are: yellowing: λy=0.178，delamination: λd=0.115, hot
spot:λh=0.014, terminal oxidation: λt=0.027. These factors remain
constant through time.
Once these failures occur, they progress by following certain
progress probability and make the module worse. Hasegawa (2011)
calculated these progress probability and how much the each failure
progress decrease the output from a module by attaching FTA and ETA
to the data of Realini (2003).
In this research, we adopted the result from Hasegawa and we
simulated the time-related dynamics of a PV module output. In thesimulation, we generated random numbers which follow normal
distribution and conducted a Bernoulli trial by attaching the failure
occurrence probabilities as thresholds.
Figure 1 shows the time-related dynamics of a PV module
degradation caused by four types of degradation failure modes. And theresult is the average of 1,000 trials of Monte-Carlo simulation. The blue

become 0 substantially.
Kato (2010) investigated 483 residential PV systems and checked therecords of their components’ trouble and failure histories. As a result,
Kato clarified that 101 PC experienced failures and some of them are
replaced in 12 years operation. Many of them failed in early years of
their operation. We used Kato’s data to simulate PC failure occurrence.
The state of PC is defined as two patterns “normal” or “fail”. We gave a
failure occurrence probability as a threshold to conduct Bernoulli trial.
To consider the characteristics of PC failure, we renewed the threshold
every year.
To get the PC failure occurrence probability, we assumed thetime-related dynamics of probability follows exponential distribution.
Also we assumed the percentage of failed PC in 483 PCs as a PC
failure occurrence probability and the total number of failure
experienced PCs by year 12 follows the probability density function ofan exponential distribution F(τ) to get probability distribution function,
we considered the probability distribution function as a function of
failure occurrence probability at year t. Figure 5 shows the result of
failure occurrence simulation of PC. We simulated 10,000 PCs
operations in 20 years. 2,141 PCs failed in the simulation but the PCs
which experienced two or more failures were only about 3% of all. The
results about the percentages are similar to Kato’s actual investigations.
However Kato considered PC only for residential use because of data
deficiency about the large scale PCs for commercial use.

line shows the effect of yellowing, the green line is delamination, thered line is hot spot, and the sky blue line shows the effect of terminal
oxidation. We multiplied the effects by the four failures and got Figure
2 as a result of the dynamics simulation of a PV module output (1,000
trials). The average degradation rate was 0.8%/year and it was almost
constant (Fig. 3). This result is similar to the result of Jordan (2011)
given by real field observation.
Figure 4 shows the distribution of PV module output at year 20. The
distribution is bimodal. The mean output is 171.7kWh/year, the median
output is 178.6kWh/year and the standard deviation of the distribution
is 14.8.
3.2 Output from a PV array
One of the he characteristics of large-scale PV systems is that theoutput from the system is not equal to the amount of output from all PV
modules in the system. The reasons are the mismatch losses in PV
arrays and the failure of PCs. We discuss the mismatch losses here.
In the general PV systems, PV modules are connected in series andparallel to adjust the output (current and voltage) for use, and the groupof PV modules are called “PV array”. The actual number of PV
modules in a PV array is about 10 to 50. However the output dispersionof each module causes mismatch losses in PV arrays. The lower output
modules become the bottleneck of an array and the output from anarray is limited by the low output modules even if the other modules
are keeping high performance. The loss is generally called mismatch
loss. The loss depends on each module’s I-V curve and the circuit
structure of an array but we assumed that “The output from anarray” = “the lowest output of a module in an array” times “thenumber of modules in an array” to simplify the simulation
model.

3.4 The output from a mega-solar
To clarify the time-related output dynamics of large-scale PV
systems, we considered the degradation of one module, the effect of
mismatch losses in arrays, and PC failure occurrence.
Based on these considerations, we simulated the output from 1MW
large-scale PV power plant. We assumed 5 PCs whose maximum
capacity are 200kW and each of them are controlling the output from
1,000 PV modules.
The result is shown on Fig. 6. The blue line shows the result of no
mismatch losses case. The green line shows the result of a case that one

3.3 Failure of power conditioners
As we mentioned, we need to consider the state of PC when we
simulate the output from PV systems. Because of the function as an
AC/DC converter, once PC fails the output (AC) from the system will
the average degradation of each1

The average output from 1000 modules

205

x 10

8

0.99

4

7

200
0.98

6
195

0.97

5

0.95
0.94

190

Frequency

kWh/yearP(t)/Pmax

0.96

185

4

3

0.93

180
2

0.92
175

1

0.91
0.9

0

5

10

15
year

20

25

170

30

0

2

4

6

8

10
year

12

14

16

18

Year

Year

Fig. 1 The dynamics of time-relateddegradation of a PV module

Fig. 3 The average output decline of
1,000 trials

Output from 1000 modules

220

0

20

0

1

2
3
4
5
6
7
8
9
The number of times of PC failure occurrence

10

Fig. 5 The frequency of PC failure occurrence

400

10

x 10

5

The average output from mega solar (No mismatch, mismatch 1 and 2)

350
200

9

300

160

140

8

250
kWh/year

The number of modules

kWh

180

200

7

150
6

100
120

5

50

100

0

5

10

15

20

25

year
Year
Fig. 2 The dynamics of time-relateddegradation of a PV module (1,000 trials)

30

0
120

130

140

150

160
kWh/year

170

180

190

th

200

Fig. 4 The power distribution on year 20 (1,000 trials)

42

4

0

2

4

6

8

10
year

0

2

4

6

8

10 12

12

14

16

18

20

14

16

18

20

Year
Fig. 6 Output dynamics of a mega-solar plant4.1 A PV module replacement
We optimized the PV module replacement plan by using dynamic
programming. We assumed 20 years as the project duration andassumed 100,000 yen as a replacement cost of one PV module(200Wp). The revenue function of a PV module is given by equation 13.
The action variables for operators are shown on eq. 14. The statetransition function is eq. 15. The reward function is eq.16. The Bellman
equation is eq. 17.

array is constructed by 10 modules. The red line shows the result of acase that one array is constructed by 50 modules. Through thissimulation we clarified that the effect of failure occurrence andmismatch loss because the output from a degraded PV system goes
down to 48% ~ 62% of initial output in 20 years if the operators did nottake O&M actions.
4. Dynamic programming
The frequent treatment for the components keeps the performance ofa mega-solar high but too frequent treatment increase the operational
cost of the mega-solar project. To maximize the profit from themega-solar project, the operators have to develop the plan whichbalances the revenue and O&M cost. To clarify the basic characteristicsof the optimal O&M plan, we applied dynamic programming. In short,
dynamic programming is the method to find the discrete action
variables which maximized or minimized the target function withconsidering the option of actions of the discrete states changed by theaction.
Let’s consider the maximizing program of f x1,, xn  (eq. 7). A
matrix of state variables x i a set of countable discrete values
a1 ,, a N  . Then we try to find the optimal set of xi which
maximizes f x1,, xn  . If we consider choosing xi as making
decision, this problem can be recognized as a multistage
decision problem (eq. 8). Through the process of eq. 9 to 12, we
can consider f x1,, xn  as a maximization of f n xn  . If weassume x n* as a set of numbers which maximize f n xn  ,x n1 is decided by the function xn*1  xˆn 1 xn* . And we candecide the optimal x1 which follows x1*  xˆ1 x2*
withrepeating backward the same processes. The way to find the
optimal set of state variables by this way is called backward
recursion. We apply backward recursion to solve theoptimization problems.
In this research, to find the best replacement plan which
maximizes the profit from the system, we assume certain action
variables，state transition functions, reward function, and Bellman
equation. We solved the Bellman equations by backward recursion.

 pa   42  202  1  0.008a 1(eq.7)

J  f1x1  h1x1, x2     hn1xn1, xn  max(eq. 8)f 2 x2   max f1 x1   h1 x1, x2 (eq. 9)J  f2 x2   h2 x2 , x3     hn1xn1, xn  max(eq. 10)f n xn   max f n 1 xn 1   hn 1 xn 1, xn (eq. 11)J  f n xn   max(eq. 12)

x1

x n1

(eq. 13)x  keep, replacea  1,g a, x   
 1,(eq. 14)x  keep(eq. 15)x  replace x  keep
42  202  1  0.008a 1 ,f a, x    91516,(eq. 16)x  replaceV a   max8484  0.992a -1  0.9V a  1,91516  0.9V 1

(eq. 17)

We solved the Bellman equation by backward recursion, and got the
optimal set of action variables and state transition function which
maximize the profit from a PV module operation. Figure 7 shows the
optimal state path of a module operation. The vertical axis means theage of the module and the horizontal axis means the year of the project.
The age of a PV module is increasing monotonously. It means that no
replacement is the best choice which maximizes the profit of a PV
module operation.
The opportunity loss caused by conducting no replacement is far
smaller than the replacement, it indicates that the degradation rate of
PV module is small, or the replacement cost is too high to replace a
module. To know the relation of the replacement cost and the decisionof replacement, we calculated the maximum costs of replacement thatallow operators to replace a module (Fig. 8). The result shows that the
replacement cost per a module should be lower than 1,1440yen to allow
the operators to replace the degraded module.

 J  f x1,, xn   max



4.2 A Power conditioner replacement
We can apply dynamic programming only if the reward function is
known, so we cannot apply the method to the case of PC replacement
because the occurrence of PC failure is stochastic and sporadic. In
contrast to PV modules failures, PC failures are easy to find because of
the function of PCs and their failure occurrence frequency is relatively
low. According to the result shown by Fig. 5, 70% of PCs never fail in
20 years operation and the PCs fail over two times is only 2% of all
PCs in use. So we assumed that PCs fail once in 20 years operation andaimed to give the information for making decision whether or not toreplace PCs after they fail. The patterns of failure occurrence are only
20.

Optimal State Path

20

11.44

6.8

18
16

Age of PV module

14
12
10
8
6
4
2
2

4

6

8

10
year

12

14

16

18

20

Fig. 7 Optimal state path of a PV module

0.6

1.21
Fig. 8 A module degradation and replacement cost

43

Fig. 9 Opportunity loss caused by no action

So we calculated the opportunity loss of no replacement for eachpattern.
We assumed the capacity of PC is 200kW, one PC is controlling
1,000 modules, the array is constructed by 10 modules. S pc a  isthe state of PC on age a. If the PC fails S pc a  becomes 0.
Then the system output is eq. 18.
 100




Psystem a   
Pmodule,i, j a    S pc a 
10  mini1,2,,10 j 1 








Table 1 Parameters of mega-solar cost (1MW)
Cost

Capital cost

Construction

System price0.473 B yen

cost(350,000 yen/kW)

・1MW

Land price (100yen/m2)

・25,000m2

Voltage up (15 M yen)(0.38 B yen)Line price (12 M yen)

Real estate tax (370M yen/year)(eq.18)

Scrapping cost of facilities (19 M yen)

We calculated the opportunity loss and the result is shownon the Figure 9. If the replacement cost is higher than theopportunity loss of no replacement, it is more profitable for theoperators not to replace the failed PC. If the replacement costis lower than the opportunity loss, the replacement becomes
more profitable. The highest opportunity loss was 6.76 million
yen at year 1. The actual replacement cost of large scale PC(200kW) is about 10 million yen (GS Yuasa, telephone survey,
2012.12.26) so it is better for the operators not to replace but
to maintain to prevent failures with paying maintenance costlower than the values of curve on Figure 9.

Revenue

Maintenance cost

cost

Other costs (7.25 M yen/ year)(replacement cost)

Sales of electricity (42yen/kWh)

x 10

0.5

Operating

8

The cash flow of mega-solar (1MW, bottom up, mismatch, pc)

0-0.5

Yen/year-1

5. The Evaluation of mega-solar projects
We assumed some O&M plans with considering the results bysection 4 and evaluated their economic efficiency by calculating NPVof mega-solar plant project under each O&M plan. We assumed 1MW
mega-solar plant project and the actual number of its cost and revenue
are given by the report from the National Policy Unit of Japan (コスト等検証委員会 2011) (Table 1).
To calculate NPV for each O&M patterns, we need to know the cash
flow of the project. According to the numbers on table 1, we simulated
the cash flow in case the operators don’t conduct any O&M actions(Fig. 10). High initial cost, the revenue decline because of degradationof the components, and scrapping cost on the last year of operation are
shown in the figure. We calculated NPV of the project for each O&M
pattern and summarized the result on Table 2 but we assumed 5% as a
discount rate here.
We assumed 7 patterns of O&M. To validate the result of section 4.1
we assumed no replacement for modules and replacement caseconducting module replacement with referring the preventive exchange
thresholds (80%, 75%, 70%). To validate the result of section 4.2, we
assumed O&M pattern 1, 5, and 7.
According to the results shown on table 2, The O&M patterns which
don’t replace PV module were more efficient, and not to do any
treatment to PC causes similar effect on NPV to pay 4.8 million yen for
PC maintenance every year.
However the every pattern of NPV was negative. It is mainly causedby high construction cost so even if the operators manage well themega-solar plant, the profitability of the project is still low. To improve
the profitability, not only O&M
but also construction cost should be
improved.

-1.5
-2
-2.5
-3
-3.5
-4

0

2

4

6

8

10
year

12

14

16

18

20

Fig. 10 Cash flow of mega-solar operation (No action case)

Table 2 NPV on each maintenance pattern

1

PC

PV module

Rank of profitability

No action

No action

3 (NPV:-0.123 B¥)

2Preventive replacement (80%)

7 (-0.132)

3

Preventive replacement (75%)

6 (-0.126)

4

Preventive replacement (70%)

3 (-0.123)

5

MaintenanceNo action

1 (- 0.064)

6

0.1Myen/year

Preventive replacement (75%)

2 (- 0.065)

7

MaintenanceNo action

3 (-0.12)

4.8Myen/year

Reference[1] 加藤和彦，太陽光発電システムの不具合事例ファイル，日刊工業新聞社，2010 年[2] Claudio Ferrara and Daniel Philipp, Why Do PV Modules Fail?, 2012, Energy Procedia 15[3] Ayumu Hasegawa, et al., Evaluation of Reliability Considering Degradation and sudden
Failure of Photovoltaic Module, 2011
[4] Antonella Realini, Mean Time Before Failure of Photovoltaic modules, 2003, Final report
BBW 99.0579[5] 福井泰好, 入門 信頼性工学, 2006，森北出版株式会社[6] Francesco De Lia, Salvatore Castello Luigi Abenate, Efficiency degradation of c-silicon
photovoltaic modules after 22-year continuous field exposure, 2003, 3rd World Conference on

6. Conclusion
For the first objective, we simulated the time-related dynamics of PV
module output and the failure occurrence of power conditioner. Withconsidering the influence of mismatch loss, we simulated the dynamics
of the output from a mega-solar (Fig.6). If the operators don’t conduct
O&M actions, the output from a mega-solar declines to 48% ~ 62% in
20 years.
For the second objective, we clarified that no actions towarddegrading PV modules is economical choice for the operators. And
maintenances for PCs may be the more efficient action than the full
replacement of them because the opportunity loss caused by no
replacement of a PC is lower than the replacement cost.

Photovoltaic Energy Conversion[7] D. C. Jordan，S. R. Kurtz, Photovoltaic Degradation Rates – an Analytical review, 2011,
DOI: 10.1002/pip. 1182
[8] M. Vazquez, Photovoltaic Module Reliability Model Based on Field Degradation Studies,
2008, Wiley InterScience DOI: 10.1002/pip.825[9] 大友政吉，太陽光発電システムにおける経年モジュールの影響評価と信頼性モデルの検討，2011[10] 国家戦略室 コスト検証委員会，コスト等検証委員会報告書， 201144

Lifetime Prediction of Concrete Mixed with Seawater
against Chloride Attack and Carbonation
Student Number: 11M18054

Name: Hiroki OHARA

Supervisor: Nobuaki OTSUKI

塩害および中性化における海水練りコンクリートの寿命予測
小原 弘毅
本論文では，将来的な淡水不足から，練混ぜ水に海水を使用したコンクリートの物質透過性や内部鋼材の腐食挙動を明らかにし，塩害および中性化に対する寿命（潜伏期および進展期）を定量的に評価した．その結果，塩害環境下の潜伏期は，練混ぜ水として海水を用いた場合の方が淡水の場合より短くなった．しかしながら，進展期は前者の方が長くなり，両者を足し合わせた寿命は同程度となった．特に置換率 55%の高炉セメントを用いた場合，両者の差は最も小さくなり，寿命は約 40 年となった．一方，中性化環境下の寿命は練混ぜ水が与える影響は小さく，セメント種類による影響が大きいことが分かった．

1. Introduction
World Meteorological Organization (WMO)
reports that two-third of world population isgoing to suffer from water shortage until 2025.
At that time, it is necessary to use seawater as
concrete material. However, seawater usages
as concrete material have not been investigatedenough. So considering this background, to use
seawater as concrete material, objectives of thisthesis are set as below;
1. To clarify material properties and corrosion
behavior of concrete mixed with seawater
2. To predict quantitative lifetime of concrete
mixed with seawater against chloride attackand carbonation

diffusivity, and carbonation rate for chapter 2.
The mix proportion have 2 parameters of
mixing water (freshwater, seawater), 2
parameters of Water cement ratio (0.5, 0.7),
and 4 parameters of BFS (Blast Furnace Slag:
By-product from steel industry) replacement
ratio (0(Ordinary Portland Cement), 40, 55,70%). Totally, 16 patterns of concrete areprepared. Additionally, unit water content is
171kg/m3 (W/C: 0.5), and 174 kg/m3 (W/C: 0.7).
Initial chloride content in concrete induced byseawater is about 3.0kg/m3. And s/a is 42%(W/C: 0.5), and 46 %( W/C: 0.7). Target slump
and air content are 8±4 ㎝, and 3±2％. Curingcondition is in moist air. Additionally, OPC
have been cured for 5 days, and BFS have been
done for 7days.Second one is mortar withembedded steel to clarify oxygen permeability
and corrosion behavior for Chapter 2 and 3.
The mortar specimen embedded steel (φ13×100mm), mix proportions are similar toconcrete. But in case of mortar, curingcondition is submerged condition in thosemixing water for 7 days. And S/C is equal to
2.0.
2.2 Chloride ion diffusivity coefficient
To clarify chloride ion diffusivity, concrete
specimen which has been exposed in artificial
seawater for 4 months is used. The way toevaluation is conform to Japan Society of Civil
Engineers (JSCE)-G 572-2010. And theequation is used Fick’s diffusion equation asshown equation 1.
Eq.1(c: amount of chloride content (kg/m3), t:
exposure time (year), D: chloride ion diffusivity(cm2/year))Fig.1 Lifetime
In this research, lifetime of concrete isclassified as shown in figure 1. To predict theselifetime, material properties and corrosion
behavior such as chloride ion diffusivity,
corrosion threshold chloride ion contents,
carbonation rate for incubation period, andoxygen permeability for propagation period areinvestigated.
2. Materials property of concrete mixed withseawater
2.1 Specimens
In this thesis, two types of specimen are used.
First one is concrete to clarify chloride ion
45As shown in figure 2, chloride ion diffusivityof concrete mixed with seawater is lower thanthat mixed with freshwater. It might be that
initial chloride content induced by seawater as
concrete material degreases chloride ion
concentration difference between concrete andexposed seawater. Additionally, chloride ion
diffusivity is decreased with increasing of slag
replacement ratio.

permeability than that mixed with freshwater.
Additionally, this value is decreased withincreasing of BFS replacement ratio, because
BFS have reduction ability on oxygen supplies.

Fig.4 Oxygen permeability
3. Corrosion behavior
In this chapter, corrosion behaviors which
are corrosion current density and corrosion
threshold chloride ion content are investigated.
3.1 Corrosion current density
To clarify corrosion threshold chloride ioncontent, time-dependent change of corrosion
current density is needed. This value canillustrate a phenomenon of corrosion. For
understanding corrosion current density,
AC-impedance method is used. The specimen
which is mortar embedded reinforcement isalso exposed to 50℃ and 3%NaCl spray zone
after 7 days submerged curing. The result isshown in figure 5 using W/C=0.5 specimen. And,
this figure have red dashed line at 0.2 µA/cm2,
this is the corrosion threshold current density
defined by International Federation for
Structural Concrete (FIB). As shown in figure 5,
if corrosion current density is higher than thisvalue, embedded steel is corroded.

Fig. 2 Chloride ion diffusivity
2.3 Carbonation rate coefficient
To clarify carbonation rate coefficient using
concrete specimen, the evaluation method isconform to JIS A 1153. The result is shown infigure 3.

Fig. 3 Carbonation rate coefficient under air
As can be seen, the difference between
freshwater and seawater as concrete material
is small. So the effect of seawater is very low.
However, using BFS the carbonation rate isincreased with increasing of replacement ratio.
Because high BFS replaced cement have low
pH in its cement matrix.
2.4 Oxygen permeability
To clarify oxygen permeability, limit current
density obtained from cathodic polarization
curve with mortar specimen is substituted inequation 2.
Eq.2(: Oxygen permeability (mol・cm2/sec),
ilim: limit current density (A/cm2), n: atomic
value (=4), F: Faraday constant (96500c/mol)).
The result is shown in figure 4. As a result,Fig.5 Time dependent of Corrosion current
density (In case of W/C=0.5)
The result in figure 5 shows, as can be seen,
the duration to reach corrosion thresholdcurrent density is steadily increased withincreasing of BFS replacement because of
decreasing of chloride ion diffusivity. Besides,
in case of OPC and BFS 40% replaced pattern,
duration of the mortar mixed with seawater to

The figure indicate that the difference between
freshwater and seawater as concrete material
is small for OPC, while BFS cement mortar
mixed with seawater have lower oxygen

46

has shorter incubation period than that mixed
with freshwater. Because seawater as concretematerial induces initial chloride content, theduration to reach corrosion threshold chloride
ion content is shortened. So, only consideringincubation period, concrete mixed withseawater is difficult to use.

reach corrosion threshold current density isshorter than that mixed with freshwater,
because initial chloride content induced byseawater as concrete material decrease theduration to reach corrosion threshold chloride
ion content. On the other hand, BFS55%
replaced mortar mixed with seawater has
almost same resistance against corrosion thanthat mixed with freshwater because of long
duration to reach corrosion threshold current
density and its chloride ion diffusivity are
lower than that mixed with freshwater.
3.2 Corrosion threshold chloride ion content
In this section, using specimens whichreached corrosion threshold current density
detected by AC-impedance method in section
3.1, corrosion threshold chloride ion contents
are determined. The evaluation method isconformed to JCI-SC45. The result is shown infigure 6. Additionally, the result of chloride ioncontents analyzed from mortar specimen isconverted into chloride ion content in concrete.

Fig. 7 Duration of incubation period against
chloride attack (In case of 70mm cover depth)
4.2 Duration of incubation period against
carbonation
To clarify this period, carbonation rate
coefficient obtained from section 2.3 is used.
The result is shown in figure 8 and table1.

Fig. 6 Corrosion threshold chloride ion content

Fig. 8 Duration of incubation period against

As it can be seen, BFS pattern have lower
corrosion threshold chloride ion content than
OPC pattern. It is highly possible that Cl-/OH(In general, when the value rises above 0.6,
corrosion start.) is increased with increasingof BFS replacement ratio. Because high BFS
replaced cement have low pH. Additionally, thevalue of BFS 70 % replacement (in case of W/C=
0.7) is less than initial chloride contents(dashed horizontal line shown in figure.6)
induced by concrete mixed with seawater. It
means BFS 70% replaced concrete mixed withseawater induce corrosion at the initial stage.
As a result, in case of OPC pattern, corrosion
threshold chloride content is about 5 to 6kg/m3
and in cases of BFS pattern, the value is about
3 to 4 kg/m3.
4 Lifetime prediction
4.1 Duration of incubation period against
chloride attack
To clarify this period, chloride ion diffusivity
and corrosion threshold chloride ion content
are used. As illustrated in figure 7, all mix
proportions of concrete mixed with seawatercarbonation (In case of 30mm cover depth)
From this result, the difference between
lifetime of concrete mixed with seawater andfreshwater is so small. But lifetime against
carbonation is decreased with increasing of slag
replacement ratio. Because high BFS replaced
concrete have low pH. Thus the effect of
seawater on lifetime against carbonation is low,
but high BFS concrete can not apply to severe
carbonation condition. Additionally, OPC
concrete is better than BFS as shown table 1.
4.3 Duration of propagation period against
chloride attack
To clarify propagation period, amount ofcorrosion product proposed by Yokozeki1) andcorrosion rate during propagation period whichis calculated by oxygen permeability obtained
from section 2.4, and the relationship2) between
oxygen permeability and corrosion rate areneeded. Then, using calculated corrosion ratefrom oxygen permeability and amount ofcorrosion product around reinforcement during
propagation period (The value is about
54mg/cm2 in case of 70mm cover depth and φ47

5 Conclusions
In this thesis, the effects of seawater onmaterial properties and corrosion behavior
have been clarified. And using these results
quantitative lifetime of concrete mixed withseawater also has been investigated. From thisinvestigation, conclusions are obtained asfollows;

13mm
of carbon steel), duration of
propagation period is predicted as figure 9.
From this result, concrete mixed with seawater
have longer duration than that mixed withfreshwater, because of its low corrosion rateduring this period. Particularly, 55% BFS
replaced concrete (0.5B55) mixed withseawater has longer duration than other type ofconcrete mixed with freshwater as shown intable 1.

1. Chloride ion diffusivity of concrete mixed
with seawater is lower than that mixed withfreshwater. In case of carbonation rate, thedifference of value between concrete mixed
with seawater and freshwater is small. In
case of oxygen permeability, using OPC the
difference of value between freshwater andseawater as concrete material is small, butusing BFS the value of concrete mixed withseawater is lower than that mixed withfreshwater.

Fig. 9 Duration of propagation period against
chloride attack (In case of 70mm cover depth)
4.4 Lifetime including incubation andpropagation against chloride attack
Using results of section 4.1 and 4.3, in thissection, lifetime included incubation andpropagation is investigated as figure 10, andtable 1.

2. In the case of chloride attack, the durationof concrete mixed with seawater is almost
same duration as that mixed withfreshwater. Especially, in case of BFS 55%,
the difference is smallest. And the duration
is 40 years.
In the case of carbonation, the difference of
lifetime between concrete mixed withfreshwater and seawater is so small. But
using BFS, regardless of mixing water, theresistance against carbonation is too low.

Fig. 10 Duration of Lifetime against chloride

References
attack (70mm cover depth)
1) K. Yokozeki et al., (1997). "A Rational Model to
From this result, only considering incubation
Predict Service Life of RC Structures in Marine
period, concrete mixed with seawater isEnvironment", Forth CANMET/ACI Internationaldifficult to use. But considering incubation and
Conference on Durability of Concrete 1
propagation as lifetime, concrete mixed withseawater is slightly shorter than that mixed
2) S. Maruyama, (2004), "Influence of Temperature
with freshwater. Especially, the difference
and Cement on Corrosion Rate of Steel Bar under
between BFS 55% concrete (0.5B55) mixed with
Carbonation", Master thesis of Tokyo Institute ofseawater and freshwater is minimum value.
Technology (in Japanese)
And the lifetime of concrete mixed withseawater is 40 years. This is enough long to use
practically as shown table 1.
Table 1 Comparison of average incubation and propagation period depending on mixing water
Deterioration
factorChloride
AttackMixing
water
Fresh
Sea
Fresh

Carbonation
Sea

Ave.
13.8
Ave.
4.5
Ave.
396.3
Ave.
145.2

Incubation period
Year
Max.
26.2
Min.
6.0
Max.
16.3
Min.
0.0
Max.
2759.0
Min.
12.9
Max.
842.7
Min.
11.0

Best mix
0.5B55
0.5B55

Ave.
8.4
Ave.
12.8

0.5OPC
0.5OPC48

Propagation period
Year
Max.
14.1
Min.
2.5
Max.
23.5
Min.
2.4

Best mix
0.5B55
0.5B55

Ave.
22.3
Ave.
17.3
Ave.
396.3
Ave.
145.2

Lifetime(Total)
Year
Max.
40.1
Min.
8.9
Max.
39.9
Min.
5.9
Max.
2759.0
Min.
12.9
Max.
842.7
Min.
11.0

Best mix
0.5B55
0.5B55
0.5OPC
0.5OPCEffect of temperature, oxygen concentration and solution on the
degradation of paint on steel in marine exposure tests and accelerated test
Student Number : 11M18077

Name : Yu KAMIYASupervisor : Nobuaki OTSUKI

促進試験と海洋曝露試験における塗装鋼板の劣化に及ぼす温度， 酸素濃度，溶液の影響
神谷 悠
長期に亘る塗装鋼材の劣化過程を把握することは従来からの課題であり、関連した曝露実験も行われてきたが、その詳細な劣化過程は不明確である．また、試験期間を短縮するための促進試験も提案されているが，温度や酸素、溶液種類等の条件が劣化進行に及ぼす影響は明らかではない．そこで、本論文では屋外曝露試験および既往の実曝露実験から、海中上部での塗装の劣化過程を明らかにした．また、促進試験と屋外曝露試験から塗装に膨れが生じる期間の促進倍率を算定した．さらに個々の促進条件が塗装の劣化進行速度に及ぼす影響を明らかにし，実環境での塗装に膨れが生じる期間を推定した．

1.Introduction
Recently the importance of maintenance toactual structures increases. Many offshore
structures consist of paint coated steel for
protection against corrosion. In these cases, it
is important to estimate the life time of thesestructures for maintenance. While exposure
tests have been conducted in actual
environment, it is insufficient to clarify
deterioration process of paint and still needs
more data. In addition, to shorten thelong-term process of deterioration of paint on
steel, accelerated test have also been conducted.
However, conditions for acceleration were
determined by knowledge or experience inmany cases. And the effect of each condition to
the deterioration of paint is not quantitatively
evaluated yet. When paint deterioration
process is estimated, two types of corrosion
should be considered. These are microcell
corrosion and macrocell corrosion distinguishedby the distance of anode and cathode. And
deterioration process and rate also depends onthe environment.
From above background, the objectives of thisresearch were shown as follows; (1) to clarify
the paint deterioration process and period
considering macrocell corrosion in submergedzone. (2) to evaluate quantitatively effects oftemperature, solution type, paint thickness,paint type and dissolved oxygen by accelerated
test and its magnification.(3) to estimate thedeterioration period in actual environment bymagnification.

through seabed, submerged zone, tidal zone
and splash zone. Test was conducted for
20years. And observation was conducted at 1,
12 and 20 years. Steel pipe was coated with Tar
epoxy(800μm). In submerged zone, blister andripping appeared by 12 years. After 20years
exposure, serious degradation occurred insubmerged zone. Many defects and corroded
areas
were
observed.
Somecorrosion
progressed deeply, vertically (Fig.1). These
penetrated 4.5mm of steel thickness. It seems
the effect of macrocell corrosion.

Fig.1 Relation between square root of corroded area andmaximum corrosion depth for submerged zone
2.2 Exposure test in artificial water tank withseawaterTo
clarify
deterioration
process
anddeterioration period of paint on steel especiallyfor submerged zone more precisely, outside
exposure test was conducted. Test site was
Futtsu city, Chiba Prefecture.
(1)Experimental procedureSpecimens were exposed in artificial watertank with natural sea water. Water levelchanged every 6hours between low water level
and high water level. Water temperature was

2. Clarification of deterioration process andperiod
2.1Summary of the previous test [1]Exposure test had been conducted in actual
environment in Miyako Island, Okinawa
prefecture. Paint coated steel pipe were settled
49

about 20℃ and Dissolved oxygen was about
5.0mg/L. Specimens were settled directly inatmosphere, tidal zone, and submerged zone.
Phthalic resin paint was applied in this test.
Paint thickness was 150μm. States of specimen
are shown in Table.1. Test duration was
11months.
Table.1 specimen

pitting

defect5cm

5cm

Defect on surface

Pitting under the defectFig.3 Defect on paint and pitting under the defect

12cm

12cm

1. Embedded in Epoxy

2. Paint on surface

2.3. Summary of accelerated tests(1)Experimental procedure
This test followed the form proposed by JSCE[3]assuming submerged zone. As accelerated
conditions, 1)temperature 2)solution type3)paint thickness 4) paint type 5) dissolved
oxygen (air contact)were selected. Tested
combinations of these conditions and duration
before blistered are shown in Table.2. Dissolved
oxygen was measured by air contact. It means
air bubbles hit the paint 1)directly or2)indirectly. When it was direct, dissolved
oxygen was 5.1mg/L, it was indirect, dissolved
oxygen was 4.1mg/L at 50℃.

(2)Visual observation
Visual observation was conducted every month
during test period. After the test, paint was
peeled and observation of steel surface wasconducted.
Inatmosphere,
remarkabletransform did not been observed by the end of
the test. In tidal zone, rust appeared at
5months, ripping occurred at 8months, thenpaint tore completely at 9months. In
submerged zone, rust appeared at 3months,
blister appeared at 5months then ripping
occurred at 10months. Secular change ofappearance in submerged zone is shown Fig.2.
After the exposure test, remarkable transform
did not been observed on steel surface inatmosphere. In tidal zone, steel surface wastotally corroded because of steel surface
appearance by paint tearing. In submergedzone, pitting under the defect (rust) and blackrust were observed. Defect on paint and pitting
under the defect are shown Fig.3. It seems theinitiation of deep, vertical corrosion.

rust

blister

5cm

5cm

Rust(3months)

Blister (5months)(2) Visual observation
Visual observation was conducted. From theobservation, it was confirmed that eachspecimen followed the deterioration processthat of outside exposure test. That is firstly,
rust appeared on surface then, blister
generated. Only on one specimen in condition
4) which had 225μm paint thickness, rust andblister occurred simultaneously. It seems theeffect of thickness. In other words, it needed
longer time to rust achieving the surface
because the paint was thick. After peeling paint,
pitting was also observed under the defect oncondition 3) same as outside exposure test.
(3)Effect of macrocell corossion
pH inside blister was measured. It was 10~12
at tar epoxy paint. That was alkalinized. It wasconsidered by accumulation of hydroxide ionsin blister caused by macrocell corrosion current.
That is, macrocell corrosion was formed then,blister became cathodic part and defect became
anodic part.

ripping
5cm
Ripping(10months)

Fig.2 Secular change of appearance in upper
underwater

Table.2 Tested conditions and duration in accelerated test
1)
2)
3)
4)
5)
6)

1)Temperature
50℃
50℃
50℃
50℃
50℃
50℃

2)Solution
NaCl3%
NaCl3%
NaCl3%
NaCl3%
Artificial seawater
NaCl3%

3)Paint thickness
150μm
150μm
100μm
225μm
150μm
150μm

.

50

4)Paint type
OA
OA
OA
OA
OA
TE

5)Dissolved oxygen

5.1mg/L
4.1mg/L
5.1mg/L
5.1mg/L
5.1mg/L
5.1mg/L

Duration
9days
11days
7days
21days
27days50-70days

2.4Proposal of paint deterioration process
From the two exposure tests, accelerated test
and Funke’s model [2] deterioration process insubmerged zone which differs corrosion rateand distribution could be proposed as follows;

3. Evaluation of quantitative effects on
accelerated conditions and magnification
3.1 Evaluation of accelerated conditions
The effect of each accelerated condition wasquantitatively evaluated by comparing theduration before blistered in different conditionsof accelerated test
(1) Effect of temperature
In general, reaction velocity depends on
temperature. And it follows Arrhenius’equation. Therefore, the apparent activationenergy was calculated with the otherexperimental results in the group. Its value
approached to the activation energy of oxygen
diffusion (11kcal/mol). So it seems oxygen
diffusion dominated the reaction in this process.
Therefore,
accelerated
coefficientbytemperature was estimated by equation.1. It
was 5.8times. This value was relatively close tomeasured one.

Step.1 is initiation stage of deterioration.
Corrosion occurs under weak paint point andrust is formed. Then, macrocell corrosion cell isformed. Defect part becomes anode and certain
paint coated parts turn cathode. (Fig.2.1)
Step.2 is propagation stage. Blister is formedon paint by accumulation of hydroxide ions on
cathodic area. And macrocell corrosion current
increases. Defect areas progresses in horizontal
and vertical direction against the painted
surface. (Fig.2.2)
Step.3 is acceleration stage. Blister breaks
and it turns into ripping. That is, new defect.
And macrocell corrosion distribution changes
that leads new blister generation. (Fig2.3)

𝑉𝑇2
𝑉𝑇1

= exp⁡[

∆𝐸𝑎

1

1

1

2

( − 𝑇 )]𝑅 𝑇

(1)

Where; VTn=corrosion current density（µA/cm2）
at temperature Tn, Δ E= activation energy(cal/mol), R=gas constant=1.99 (cal/K/mol) ,T=kelvin(K)From the clarification of deterioration, theduration before blistered was applied as thedeterioration period.

(2) Effect of solution
When artificial seawater solution was
replaced by NaCl3%, duration accelerated
3times by comparing accelerated test
condition1) and 5). It seems Ca2+ and Mg2+ inseawater prevented chemical reaction morethan Na+..
(3) Effect of paint thickness
It was confirmed that while paint thickness
increased, contribution to the sum of resistance
was slight. And it seems that paint thickness
divided by duration would get smaller.
Therefore, from accelerated test condition1), 3)
and 4), logarithm approximation was applied.
It was shown in equation.2.
Y = 17.264ln(X) - 74.171(2)
Where; Y = duration, X = paint thickness

Fig.2.1 Step.1 initiation stage(4) Effect of paint typeTar epoxy paint was approximately 6.7 times
stronger than Phthalic resin paint bycomparing condition1) and 6). In this study,
this value was applied as the effect of painttype.

Fig.2.2 Step.2 propagation stage(5) Effect of dissolved oxygen
When dissolved oxygen increased 1.24times(4.1mg/L to 5.1mg/L), duration accelerated
1.22times by comparing conditions 1) and 2).
From the result of the effect of temperature,
the relation between corrosion rate (duration

Fig.2.3 step.3 Acceleration stage

51

Table 3 Magnification of each and total factors andcomparison of estimated and actual value of the duration of incubation periods
Futtsu(Outside exposure)

Miyako1)(In situ exposure)

Conditions for setting eachmagnification or duration

Laboratory
Lab data

Site Data

Magnification

Site Data

Magnification

Temperature E  1 1  
V1 exp  a    V2
 R  T2 T1  

50˚C
(T2)

20˚C
(T1)

×5.8

26˚C
(T1)

×4.0

Solution

3%NaCl: ×1.0, Seawater: ×3.0

NaCl3%

Seawater×3.0

Seawater

×3.0

150μm
(X1)

×1.0

800μm
(X1)

×4.6

Factors

Y1 17.26 ln( X 1 )  74.17

Y2 17.26 ln( X 2 )  74.17

Paint
thickness

Y:duration, X:Thickness

150μm
(X2)

Paint typePhthalic: ×1.0, Tar epoxy: ×6.7

Phthalic

Phthalic

×1.0

Tar epoxy×6.7

Y1  2 X 1  19.2
Y2  2 X 2  19.2

5.1mg/L

5.0mg/L

×1.0

6.4mg/L

×0.7

Dissolved
oxygenY:duration, X: Dissolved oxygen

Total
Magnification

Multiply all magnification

Estimated
duration

Multiply total magnificationfrom 9days

Actualduration

From observation

×1

9days

before blistered) and dissolved oxygen had a
proportional relation. Therefore, the relation
between duration and dissolved oxygen could
be described as follows;
Y =- 2X+19.2(3)
Where; Y = duration, X = dissolved oxygen

×17

×259

153days( =9days×17)

6.6years(=9×258/365)

150days

Several years(1~12years)

shortened
0.7times.
Therefore,
magnification was 259times.

total

4. Estimation of the duration before blistered
Duration before blistered was estimated bymultiplying actual duration of accelerated test
condition 1) and total magnification.
So, estimated durations were 153days in
Futtsu and about 6.6years in Miyako Island.
These values were appropriated with actual
duration in exposure tests. Therefore, durationin actual environments could be estimated.

3.2 Magnification for exposure test in Futtsu
Duration before blistered on exposure test in
Futtsu was 6.7times extended compared to theaccelerated test condition 1). Estimation
process was as follows;
1) Effect of temperature was estimated by
3.1(1). Equation.1 was applied and duration
was 5.8times extended compare to acceleration
test, condition 1). 2) Effect of solution was
estimated by 3.1(2). Duration was 3times
extended 3) Paint thickness was same asacceleration test. 4) Paint type was same asacceleration test. 5) Effect of dissolved oxygen
was quite small. Therefore, total magnification
was 17times.

5. Conclusions(1) Deterioration process considering the effectof macrocell corrosion was clarified from theappearance of paint deterioration.
(2) Effects of temperature, solution, oxygen
concentration, paint thickness and paint typewere quantitatively evaluated. Magnificationsof acceleration of each factor from accelerated
test to two exposure tests were evaluated.
(3) Duration before blistered (Deterioration
period) in actual environments could be
estimated by accelerated tests.

3.3 Magnification for exposure test in Miyako
Duration before blistered on exposure test in
Miyako Island was 258times extended
compared to accelerated test. And estimation
process was same as 3.2. Temperature anddissolved oxygen were approximate values.
1) Effect of temperature was estimated to
4.0times. 2) Effect of solution was estimated to
3times. 3) Effect of paint thickness wasestimated to 4.6times. 4) Effect of paint typewas estimated to by 4.1(4). And duration was
extended about 6.7times 5) Effect of dissolved
oxygen was estimated by 4.1(5). Duration was

References[1] Masahiro YAMAMOTO et al., “Durability of organic
coat steel exposed in the marine environment for
20years”, Materials and Environments, Vol.55，239-244(2006)[2] Funke, W., Ind. Eng. Chem. Prod. Res. Dev.，17 [1],50-53 (1978)[3] Japan society of civil engineers., “Guideline for
evaluation of durability and load carrying performanceof steel structures in the marine environment” (2009)52

Estimating CO2 emissions of an automobile company
in global supply chain: Case study of locational conditions in Thailand
Student Number: 11M18090 Name: Yuhki KAWAHARA Supervisor: Shinya HANAOKA
タイ製造業の立地条件を考慮したグローバルサプライチェーンにおけるCO2排出量算定川原	
  優輝
本研究では、タイの日系自動車メーカーの一台あたりの生産におけるCO2排出量を、グローバルサプラ
イチェーンを考慮して算定した。排出量算定にあたり、今後の自動車市場の動向や企業の立地条件を考慮して2030年の自動車市場を対象としたシナリオを作成した。この結果から、市場に近い場所で生産することが、環境的にも経済的にも有益であり、輸送距離と生産場所の電力源によってCO2排出量が大きく異なる
ことが明らかになった。

comprehensive supply chain and transportation, regarding
manufacturing industry[3].

1. Introduction
1-1. Background1-2. Objectives of the Study

CO2 emissions reduction is one of the biggest issues in
the world; logistics sector also has same issue. Spreadingwith the globalization of industry, we should consider acomprehensive way of CO2 emissions reduction in a
global supply chain.

The objectives of this study are the following.

(1) Estimate total CO2 emissions within inclusive global
supply chain and total production per one vehicle tofocus on one Japanese automobile company (company A).

A number of Japanese manufacturing companies,
which are active in Asia, reconsider of the plant location
or establishment of the new plant due to recent situations
such as insurgency, disaster and wage increase. Additionally, free cross-border movement between people, goods,
capital and information is even more accelerated by AEC.
Especially automobile is a very broad base industry; generally speaking, one automobile needs about 20 or 30
thousands parts. Therefore, automobile manufactures
have enormous economic influence. Most automobile
manufacturers have assembly plants in Thailand. Fig.1
shows that productivity of automobile industry inThailand is the fifth in Asia and exportation of automobile is over 50%.

(2) Estimate the change of CO2 emissions per one vehicle on scenarios, which consider automobile market
and locational conditions in 2030.
According to environmental report of company A, they
already figured out their portion of CO2 emissions. Fig.2,
pink area is company A and red line is this research area.

The flood in Thailand charged a heavy toll on Japanesecompanies in 2011. Moreover, because of wage increase,some companies are considering plants relocation.
Some researchers have already studied CO2 emissionsof inclusive supply chain. Their studies mostly focus on
primary products[1][2]. However, there are a few studies on
Total annual automobile
production (thousands cars)

2000#

2. Methodology
2-1. Data

60%#

1800#

50%#

1600#
1400#

This study mainly uses two types of data. One is to estimate CO2 emissions per one vehicle. Second is to build
the scenarios to project the plant locations and the automobile market in 2030.

40%#

1200#
1000#

30%#

800#

20%#

600#
400#

2-1-1. Data for Calculation of CO2 emissions
Estimation of CO2 emissions needs distance data,
weight of parts data, emission factors and input energy ofelectricity to make parts. Distance data, which is distanceof supplier to supplier and suppliers and company A, iscalculated by Google Maps. Distance of overseas is from

10%#

200#
0#

Fig. 2 Research area (red line)

2009#

2010#

Japan

USA

China

2011#

0%#

ThailandFig.1 Automobile production and export ratio

53

calculation tool5). Weight of parts and electricity ofmaking parts are also from JLCA database. Emission
factors are from calculation tool[4]. Tab.1 and Tab.2 arethis research target.

F is emission coefficient (t-C/GL)
Ft is emission factor (t-CO2 /tkm).
u is number of unit and q is number of vehicles.

2-2-2. Production Process

Tab.1 Target parts and suppliers
Number of parts

Number of suppliers

Transportation

75+(engine, body)

88

Production

31

31

CO2 emissions from suppliers are calculated by using
JLCA database. CO2 emissions from assembly plant arefrom environmental report of company A and emission
factor. Equations for calculation are the following.

Tab.2 Specification of target automobile
Type

𝐸! = ! 𝑔! 𝑓 ⁄1,000,000

Pickup truck 4WD M/T 4 door

Weight [kg]1,825

Dimension [mm]5,135 x 1,835 x 1,860

Displacement [cc]2,494Engine weight [kg]207

𝐸! = 𝑔 𝑓 ⁄1,000,000

Building scenario data is based on GDP, car ownership,
investment cost. Investment cost is from open souse by
JETRO.

3. Results
3-1. Present Plant Location

2-2. Estimation Method
2-2-1. Transportation Process

Fig.3 presents plant locations of suppliers and locationof company A. Large portion of suppliers located aroundseaside area. Fig.3 also illustrates the flood impact area
which if denoted by blue color.

Calculation of this study is divided to transportation
process and production process. Land transportation is
calculated by improved tonnage method. Maritime transportation is calculated by tonnage method. These calculations are calculated by estimation tool form PRILT[4].
Calculation equations are the following.
𝑊! ×𝑑!" ×𝐶× 1⁄1000 ×𝐻×𝐹× 44⁄12
𝑢(1)

𝑊×𝑑!" ×𝐹! × 1⁄1,000,000
𝑞

(2)

𝐸! =

Where:
Ei is CO2 emission of transportation on the truck (t-CO2).
Em is CO2 emission of maritime transportation (t-CO2).
Wi and W are total parts weight and total vehicles weight.
d is distance (km).
C is fuel usage basic unit (l/tkm).
H is heat generation per unit (GL/kl).
Tab.3 Comparison of investment cost
ThailandLabor wage
Total wages
Total annually land cost

$286/month$15,444,000$1,731,053(4)

Where:Ep is CO2 emissions of production process on suppliers(t-CO2).
Ea is CO2 emissions of production process on assemblyplant (t-CO2).
gn and g are electricity usage (kWh).
F is emission factor (g-CO2/kWh).

2-1-2. Data for Scenario Building

𝐸! =

(3)

!

Malaysia

Fig. 3 Present plant locations

3-2. Scenario Building
Before the scenario building, this study needs to consider the tendency of company A behavior. This study

Indonesia$344/month$18,576,000$1,491,033$209/month$11,286,000$3,168,555

Vietnam

Cambodia$130 /month$7,020,000$1,309,200$82/month$4,428,000$956,589

Myanmar$68/month$3,672,000$1,335,384

Total electricity cost

$10,581$9,006$5,978$4,633$16,291$8,968

Total water rate cost

$191,861$331,038$657,097$187,031$172,169$422,019$17,377,495$20,407,077$15,117,630$8,520,864$5,573,049$5,438,370

Total cost54

builds 4 scenarios according to investment cost and automobile market.

Myanmar have a good advantage of investment cost especially labor wage. Consequently, Cambodia and Myanmar were decided to build scenarios.

3-2-1. Impact of flood in Thailand

3-3. Estimation Results

The total amount of suffering the flood created in
Thailand is 1.4trillion dollars which was estimated byWorld Bank. This flood affected 800 companies, including 450 Japanese companies. Some companies that produce parts to company A were included among 450.
Therefore, company A was affected by flood impact indirectly.

Tab.4 indicates scenario purpose, plant locations, andtarget market of each scenario. Fig 5 shows this research
scenarios.

3-3-1. East Region Scenario
Purpose of this scenario is to avoid the flood risk. In
this scenario, some countries and company A which haveflood risk are relocated to east region. From the result of
estimation, transportation CO2 emissions of supplier was
reduced because of shortens distance.

3-2-2. Projection of Automobile Market
This study built 4 scenarios based on the projection
study of the automobile market[5]. According to this projection, relationship between car ownership and GDP is
illustrated in Fig.4.

3-3-2. Cambodia Production Base Scenario
This scenario aims to Vietnam market. In this scenario,
company A establishes its new assembly plant in Phnom
Penh. All transportation process is used by truck and carrier car.
From result of this scenario, CO2 emissions of suppliers were increases by five times compare to present case.
CO2 emissions of production process were decreased
because CO2 emissions factor in Cambodia is higher thanThailand one.

3-3-3. Myanmar Portion of Suppliers Relocation Scenario
This scenario, some suppliers which have flood risk arerelocated to Dawei in Myanmar. This scenario has two
purposes. One is to avoid flood effect and the other is tocompare the CO2 emissions if some suppliers change
their plant location.
In transportation process, CO2 emissions of supplierFig.4 Projection of automobile market in 2030

3-2-3. Comparison of Investment
This study compiled investment cost and comparedwith some countries around Thailand. The result from
Table3 suggests that Cambodia andTab.4 Target parts and suppliers
Scenario Name

PurposeAssembly Plant

Suppliers Plant(1)East Region Scenario

Disaster countermeasure type

ThailandThailand

ASEAN(2)Cambodia Production Base ScenarioMarket adapted

Cambodia(Phnom Penh)

Thailand

Vietnam,
Cambodia(3)Myanmar Portionof suppliers Relocation Scenario

Disaster countermeasure type

ThailandMyanmar(Dawei),land(4)Myanmar Production Base ScenarioMarket adapted

Myanmar(Dawei)ThailandFig.5 Scenarios

55

Thai-

Market

ASEAN

India

increased due to extended distance.
In production process, CO2 emissions were decreased
because CO2 emission factor in Myanmar is lower thanThailand.

emissions depends on the electrical resource. When referring from Fig.6 about comparison of transportation cost[6]in Myanmar base scenario,. However, Cambodia basescenario indicated that production process of CO2 emissions depended on country electricity issue. Therefore,
manufactures should consider their plants locations whereis beneficial plant location for environment and economic.
Efforts of companies and researchers will trigger ofinnovation of the new technology to develop new
eco-friendly automobile. However, if they cannot reduce
emissions on the supply chain, they would not be able toreduce CO2 emissions in automobile industries.

3-3-4. Myanmar Production Base Scenario
This scenario aims to automobile market in India. This
scenario establishes a new assembly plant at Dawei in
Myanmar.
CO2 emissions of supplier’s transportation were increased, but CO2 emissions on maritime transportation
were decreased. Total CO2 emissions of transportation
was decreased.	
 CO2 emission factor is lower than Thailand. Therefore,
CO2 emissions of production process were decreased.
Total CO2 emissions were reduced by approximately 34%
compared to present case.

References[1] Christophe Rizet et al.: Assessing carbon footprint and energy
efficiency in competing supply chains: Review – Case studies and4. Conclusions and Discussion

benchmarking, Transportation Research D17, pp.293-300, 2012.
[2] Brendan O’Donnell et al.: The relative contribution of transporta-

This study focused on one automobile company andestimated inclusive global supply chain CO2 emissions
and clarifies the change of CO2 emissions result fromthese comparisons.
In the case of transportation process, CO2 emissions ofsuppliers are not effective for whole emissions. In maritime generated a quite little CO2 emissions, which accounts of the majority of total CO2 emissions. This result
was not only long because of distance but also automobile transport ship issue. It is likely that containership isavailable to carry much more freights than car carrier.
Regarding to the production process, amount of CO2

tion to supply chain greenhouse gas emissions: A case study ofAmerican wheat, Transportation Research D14, pp.487-492, 2009.
[3] Ki-Hoo Lee: Integrating carbon footprint into supply chain management: the case of Hyundai Motor Company (HMC) in the automobile industry, Journal of Clearner Production 19, pp.1216-1223,
2011.
[4] 国土交通政策研究所：物流から生じる CO2 排出量に関する手引き，2012．
[5] Joyce Dargay et al.:Vehicle Ownership and Income Growth,Worldwide: 1960-2030, The Energy Journal Vol. 28, pp. 143-170,
2007.
[6] JETRO: ASEAN Logistics Network Map 2nd Edition, JETRO,

Transportation cost (US$)

CO2 emissions per vehicle (t-CO 2/vehicle)

2009.

-

Fig.6 CO2 emissions results-(S: Suppler, A: Assembly Plant, D: Distributor)
56

MICROBIAL COMMUNITY ANALYSIS OF
THE METHANE FERMENTATION PROCESS TREATING GLYCEROL
Student Number: 11M18120 Name: Kohei Hatta Supervisor: Kiyohiko Nakasaki

グリセリンを原料としたメタン発酵プロセスにおける微生物叢の解析
八田 恒平
効率的なメタン発酵を可能にするためには，処理しようとしている基質に適したグラニュールを生成することが重要である．以前より，グリセリンを基質としたメタン発酵は効率化が困難であることが知られていた．本研究では食品工場の廃水処理過程で生成したグラニュールを 104
日間かけて馴致することで，2.5 gCOD/L/d の高負荷グリセリンの処理が可能な微生物群集を得ることに成功した．また，馴致にともなってグラニュール中の微生物叢が変化し，これまでに主要な構成微生物としては知られていなかった属の細菌が優勢になることを分子生物学的手法を用いて明らかにした．

microbial community for each kind of substrate.
Many microorganisms are able to metabolize
glycerol in the presence of external electron
acceptors (respiratory metabolism), however, few
are able to metabolize glycerol in the absence ofelectron acceptors [1]. Therefore, the start-up of
methane fermentation from glycerol requires longtime for those few kinds of microorganisms, whose
specific growth rate is low, to grow up to theconcentration that can show the decomposition
activity against glycerol.
In this study, the microbial community on theacclimation process was analyzed to find themicroorganisms that can decompose glycerol.

1 Introduction
Extensive researches have been carried out
worldwide to address the environmental problems
associated with the depletion of fossil fuels, and theemission of greenhouse gases that contribute to theglobal climate change. Above all, biodiesel fuel(BDF) is in spotlight and has been produced atindustrial scale in the world through base-catalyzed
transesterification of vegetable oil, animal fats andwaste oil. The increase of BDF production brings
about the massive by-product of waste glycerol thatis usually incinerated.
One of the solutions to treat this waste glycerol
is methane fermentation from glycerol. The
methane fermentation is conducted as the anaerobic
digestion of the organic wastewater by the varietyof microorganisms. Besides the production of themethane, the advantages of the methane
fermentation include energy savings, generation of
low quantities of sludge and excellent waste
stabilization. The methane fermentation process
occurs with different groups of bacteria in four
steps of reaction: hydrolysis, acidogenesis,
acetogenesis, and methanogenesis.
Several research groups have focused on thepossibility of anaerobic treatment of glycerol
recently and most of these studies have aimed atusing the glycerol as a co-substrate for processingof other substrates like pig manure etc. However,
BDF plants are not always constructed near themethane fermentation reactor treating other kinds ofsubstrate. Hence, the anaerobic processing ofglycerol as a single substrate should be established.
Generally, the start-up of methane fermentationneeds acclimation period to propagate adequate

2 Materials & methods
2.1 Acclimation of granule to glycerol
using semi-continuous stirred tank reactor(semi-CSTR)
The microbial community in the granuleobtained from a food factory was acclimated toglycerol. Fig. 1 shows the schematic diagram of theexperimental set-up. The 300 mL of seed granule
was inoculated to 2.7 L of water in the sterilized
reactor. A carbon source mixture designated as GAL
consisted of 5 g of glucose, 2.5 g sodium acetateand 2.08 g lactic acid per litter of distilled water
was prepared and the mixture of glycerol and GAL
was used as substrate.
Six kinds of the glycerol-GAL mixture
designated as S, G0, G25, G50, G75 and G100 wereprepared by changing the mixing ratio as shown in
Table 1. These substrates were supplied in a
stepwise manner: 0-1 days with 100% GAL

57

(substrate S), 2-21 days with 100% GAL (substrateG0), 22-37 days with 75% GAL and 25% glycerol(substrate G25), 38-49 days with 50% GAL 50%
glycerol (substrate G50), 50-61 days with 25%
GAL 75% glycerol (substrate G75), and 62-104
days with 100% glycerol (substrate G100). Other
inorganic substances were prepared according to thepaper of Ghangrekar et al. [2]. Every day, 750 mLof substrate was fed to the reactor after draining 750
mL of supernatant. The reactor was fed withconstant organic loading rate (OLR), i.e., 2.5
gCOD/L/d. The pH in the reactor was kept at 7.5 by
the addition of 0.1M NaOH solution every day. The
reactor was kept at 39°C and stirred at 100 rpm
except the feeding period.
The samples withdrawn at adequate timeinterval were subjected to the analyses of pH,
Oxidation-reduction
Potential(ORP),
concentrations of Volatile fatty acids (VFAs) andlactic acid, PCR-DGGE and DNA sequencing of
16s rRNA gene fragment. The gas samples wereanalyzed by GC-MS.

column oven was set at 40°C.
Methane and carbon dioxcide quantities were
determinedbygaschromatography-mass
spectrometry (GC-MS). A GC (GC-17A, Shimadzu,
Kyoto, Japan) was equipped with a 25m×0.25mm
ID CP-Porabond-Q fused silica column, film
thickness 5 mm (Chrompack, Varian DeutschlandGmbH, Darmstadt). Helium was used as carrier gas(head pressure 7 kPa). 0.5 ml of gas samples were
injected in split mode (split ratio: 90, injector
temperature: 50°C, column oven temperature:40°C).

2.3 Microbial community analyses
The granules samples were taken from thegranule sampling pipe that has 250 mm height fromthe bottom on day 17, 19, 28, 37, 45, 49, 55, 61, 67,
77 and 84 in fermentation period of the reactor. A
DNA extraction kit, ISOIL for Beads Beating(Nippon Gene Co., Ltd., Toyama, Japan), was used
for the extraction of DNA from the granules
samples. Samples weighing 0.3 g (wet weight) weredirectly put into a tube in the beads beating kit.
About 950 μL of the Lysis solution BB and 50 μLof the Lysis solution 20S were added to the tube,
which was then bead-beaten vigorously for 45 s at a
rate of 5500 rpm on a bead-beater (Micro Smash
MS-100; Tomy Medico, Ltd., Tokyo, Japan). Afterincubation at 65°C for 1 h, the samples were
centrifuged at 11,000 rpm for 1 min at room
temperature by using a microcentrifuge (MX-105
High Speed Refrigerated Micro Centrifuge; Tomy
Tech INC., Tokyo, Japan). The wash solution and
70% ethanol containing ethachinmate were used towash and purify the DNA pellet, which was thenvacuum-dried for 20 min. The DNA pellet was thendissolved in TE solution (Tris-HCl, 10 mM; EDTA,
1 mM; pH 8.0).
PCR ampliﬁcation was conducted with TaKaRa
Ex Taq Hot Start Version (Takara Bio INC., Shiga,
Japan) using TaKaRa PCR Thermal Cycler Dice
(TP600, Takara Bio INC., Shiga, Japan). The
primers were as follows: 357F, 5-CGC CCG CCG
CGC GCG GCG GGC GGG GCG GGG GCACGG GGG GCC TAC GGG AGG CAG CAG-3,
and 517R, 5-ATT ACC GCG GCT GCT GG-3 [3].
The PCR program was set for initial denaturation at
94°C for 7 min, followed by 35 cycles of 60-s
denaturation at 94°C and 60-s annealing at 65°C
(ﬁrst 7 cycles), then at 60°C (second 7 cycles), andﬁnally at 55°C (last 21 cycles). Each annealing step
was followed by a 120-s extension except for theﬁnal extension (at 72°C for 10 min). For Archaea,
the nested PCR amplification was applied. In the

Table 1 Compositions of the substrates
Organic
components
GlycerolGlucoseAcetic acid
Lactic acid

S
0
13.9
15.2
8.5

Concentrations (mmol/L)
G0
G25 G50 G75
012.7 25.5 38.2
27.8 20.8 13.9
6.9
30.5 22.9 15.2
7.6
16.9 12.7
8.5
4.2

G100
50.9
0
0
0

1. Substrate bottle
2. Pump for feeding
3. Jar fermenter in water bath
4. Pump for withdrawing
5. Output bottle
6. pH electrode
7. Gas sampling bag

Fig. 1 Semi-CSTR set-up

2.2 Chemical analyses
The pH and the ORP of the supernatant
withdrawn from Runs A and B were measured withelectrodes (PH-3P, Mettler Toledo, Tokyo, Japan).
The concentration of VFAs (acetic acid,propionic acid, butyric acid and iso-butyric acid)and lactic acid was measured with a HPLC system(JASCO, Tokyo, Japan) with a Shodex Sugar
SH1011 column (Showa Denko K.K., Tokyo,
Japan) and a refractive index detector (Hitach,Tokyo, Japan). Mobile phase was 5 mM H2SO4,
flow rate was 0.9 ml/min and the temperature in the58

first step, primers PRA46f and PREA1100r wereused in order to achieve the 1,072bp fragment, thePCR product from the first step were diluted andused as a template to produce the 179 bp fragment
by using PARCH340f and PARCH519r primers [4].
DGGE was performed using the Dcode DGGE
Complete System (BioRad Laboratories, CA,
USA). Prior to loading onto 10% (w/v)
polyacrylamide gel in 1x TAE buffer (40 mM Trisacetate; pH 7.4; 20 mM acetate, 1 mM Na 2 EDTA)
with a denaturing gradient ranging from 30% to60%, the PCR products were mixed with an equalvolume of 2x gel loading dye (10 mM Tris-HCl (pH8.0), 20 mM EDTA (pH 8.0), 0.05% (w/v)
bromophenol blue, and 70% glycerol). The ‘‘100%
denaturant’’ corresponded to 7 M urea and 40%(w/v) deionized formamide. Electrophoresis wasundertaken at a constant voltage of 200 V at 60°C.
After 3.5 h of electrophoresis, the gels were stainedwith 1x TAE buffer and ethidium bromide for 30
min, and then rinsed with distilled water before
imaging using a UV illuminator (Epi-Light UV
FA500; AISIN, Saitama, Japan).
Using the DGGE image as a reference, thebands of interest were excised from the gel on a
Dual Intensity Ultraviolet Transilluminator (Model
TDS-20; UVP, CA, USA). The extracted bands
were then re-ampliﬁed and subjected to cloning byusing the TOPO TA Cloning Kit (Invitrogen,
Carlsbad, CA, USA) in order to purify the DNA
bands. Sequencing reactions for the puriﬁed DNA
bands were carried out with a BigDye Terminatorv3.1 Cycle Sequencing Kit (Applied Biosystems,
CA, USA), while sequencing was performed using
an ABI PRISM 310 Genetic Analyzer (Applied
Biosystems, CA, USA).The results of sequencing
were compared to the sequences of the 16S rRNA
genes available in the databases (DDBJ, EMBL and
GenBank) and the afﬁliation including the relative
strains of the sequences were determined using
sequence match analysis in the ribosomal databaseproject II (RDP-II) data and analysis services.

anaerobic digestion. Firstly, the bacterial grouphydrolyses and produces acetic acid through VFAs.
Then, acetic acid are further digested to methane byarchaea. Under the conditions of stable methane
fermentation, VFAs are consumed and thenconverted to methane immediately after they are
produced; therefore VFAs concentration in thereactor is kept at low level in the liquid sample.
Acetic acid, propionic acid, butyric acid, and isobutyric acid were the common acidogenic productsin this experiment. Among them, Acetic acid andpropionic acid were the ﬁrst and second mostabundant intermediates and their low concentrations
were signiﬁcant and demonstrated the performanceof the reactor.
Gas production rate (mol/d)

0.1
CH4
CO2

0.08
0.06
0.04
0.02
0
0

20

40

60
Time (d)

80

100

120

Fig. 2 The courses of biogas production rate during
the granule acclimation to glycerol
0.8
Acetic acid
Propionic acidIso-butyric acid
Butyric acid
Total VFAs
Lactic acid

Concentration (g/L)

0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0

3 Results & discussion

20

40

60
Time (d)

80

100

120

Fig. 3 The courses of VFAs and lactic acidconcentration in the supernatantFig. 2 shows the courses of biogas production
rate during the granule acclimation to glycerol.
From the start-up to around Day 14, theconcentration of methane was low suggesting thatthe microorganisms had not adapted to the new
substrate. After the day 14, the production rate ofmethane was stable at around 0.065 mol/d except
the day just after the change of the glycerol ratio in
the substrate.
VFAs are intermediates produced during the

The VFAs concentration in the liquid sample isshown in Fig. 3. After the start of the experiment,
other easily degradable compounds than glycerol,such as sodium acetate and lactic acid are includedin the substrate thus the VFAs concentration in thereactor become rather high. Afterward, VFAs were
getting decrease when glycerol was gradually
increased in synthetic wastewater component. From
day 61 of the operation period, the reactor was fed

59methane fermentation. At the beginning of themethane fermentation, the initial ORP value was 80 mV and then it decreased rapidly to -400 mV. It
meant the anaerobic condition was retained in thewhole of the acclimation process.
Fig. 5 shows the DGGE fingerprints of bacteria
in the samples from acclimation process of granule
to glycerol. At the early stage of acclimation,
various kinds of bacteria were detected in thereactor. Then, the bacteria that correspond to theband number B7, B8 and B10 became dominant in
the later stage of the acclimation process. The
differences between DNA sequences corresponding
to these three bands were only 1 or 2 bp. No
previous studies show that this genus becomesdominant in the methane fermentation fromglycerol. Previously, it was reported that this genus
can convert glycerol to 1,3-propanediol (mainproduct), lactic acid, acetic acid, and formic acid.
The result that 3 strains that correspond to Band B7,
B8 and B10 became dominant in our acclimation
process supports the hypothesis that these 3 strainsthat correspond to Band B7, B8 and B10 in the
granule decomposed glycerol efficiently.
The results of DGGE fingerprints and DNA
sequencing of 16s rRNA gene fragment of archaea
confirmed that a strains that correspond to Band A8
and A13 became dominant in the Archaeal
microbial community (data not shown). These
genera are often observed in the granule sample
from the methane fermentation process. Therefore it
was suggested that these genera produced methane
in this experiment.

by 100% glycerol as carbon source; the VFA
concentration was lower than 0.2 g/L and stable
until the end of the experiment. This indicated thatthe activity of the microorganisms in the granularsludge was kept at high level. These results indicatethatthebalanceofacinogenesis
andmethanogenesis was achieved.
The low pH has the adverse effects on theperformance of anaerobic processes. Thisphenomenon was explained by that themethanogens tend to lose their activities under the
low pH conditions. The pH value between 6.4 and
7.8 is considered necessary to maintain highperformance of the methane fermentation.
8

0
pH
ORP

-100

7.6

-200

7.4

-300

7.2

-400

7

0

20

40

60
80
Time (d)100

ORP (mV)

pH (-)

7.8

-500
120

Fig 4 Change of pH and ORP during the operational
period

4 Conclusions
In the acclimation process of granule toglycerol, the stable production rate of methane, lowconcentrations of VFAs and lactic acid insupernatant and characteristic microbial community
were observed, which indicated the successful
production of the acclimated granule that have theability to treat 2.5 gCOD/L/d of glycerol.
It was revealed that 3 strains that correspond toBand B7, B8 and B10 become the dominant in theacclimated granule by the molecular biologicalanalysis.

Fig. 5 The DGGE fingerprints of bacteria in thesample from acclimation process of granule toglycerolFig. 4 illustrates the time courses of pH andoxidation-reduction potential (ORP) during theacclimation process of the granular sludge. At theearly stage, pH value slightly fluctuated from 7.3 to
7.6. Afterward, it was maintained at around 7.5 toachieve the good performance of anaerobic
digestion. The ORP indicates whether the reaction
condition is kept at the aerobic or the anaerobic. A
negative value of ORP represents anaerobic
condition and ORP < -200 mV is good condition for

References[1] Yazdani SS. et al., Curr. Opin. Biotechnol., 18, 213-9(2007)[2] Ghangrekar MM. et al., Water Res., 39, 1123-33 (2005)[3] Muyzer G. et al., Appl. Environ. Microbiol., 59, 695-700(1993)[4] Keyser M. et al., Syst. Appl. Microbiol., 29, 77-84 (2006)60

Moral hazard issues contractor and subcontractor in construction overseas projectStudent Number: 11M18137

Name: Shotaro FUKAO

Supervisor: Shinya HANAOKA, Keisuke MATSUKAWA,

契約理論から見た海外プロジェクトにおけるプライムコントラクターとサブコントラクターの関係性

深尾 翔太郎本研究では，海外プロジェクトにおける日系建設会社と現地サブコントラクターとの間で起こるモラルハザード発生メカニズムを契約理論の観点からモラルハザードモデルとして定式化し，分析する．日系建設会社の立場から，現地サブコントラクターとの間で発生するモラルハザードを抑制し，プロジェクトを効率良く進めるために望ましい問題対応スキームに関して理論的アプロー
チを試みる．そして，今後海外進出を試みる製造業や建設業の意思決定支援に資することを目的とする．

1. Introduction
1-1. Background
These days, the fact that construction industries and manufacturing is
encountering many challenges is gotten attention since domestic new
business is different from foreign new business in terms of various
conditions in especially developing country. One of those challenges
is moral hazard which occurs with local subcontractor in new
construction project Japanese construction and manufacturingindustries[1]Some researchers have already studied regarding how occur overseas
conflicts. They actually conducted questionnaire and interview
survey but their solution of survey result is descriptive and isn’t used
contract theory. Furthermore, study concern about constructionindustries by using contract theory is conducted but contract theorymodel isn’t based on actual condition through questionnaire andinterview survey.

Fig1: Questionnaire for Company A and B

1-2. Objective
This study of objectives is the following.
i.

Examine relationship between contractor and subcontractorii.

The contract schemes for moral hazard between Japanesethrough questionnaire and interview survey.
Construction Company and subcontractor in the developing
countries are formulated in the form of a moral hazard model,
whereby the moral hazard issues caused by subcontractor are
investigated. Furthermore, the optimal compliant moral hazards
issues enhance the project efficiency, are theoreticallyinvestigated.

2.

Research Design2-1. Research Method
In this research, questionnaire and interview survey is conducted toJapanese Construction Company A who is familiar with overseas
construction project firstly to comprehend actual condition of conflictin overseas construction project (Fig.1). Furthermore, verification

Fig.2 Framework of this research

survey is conducted to confirm the case treating is as to whether
occur frequently or not. After survey, narrowing frequent case to
many cases and describing theoretically.

3. Results

Build a model based on a scenario of using a moral hazard model of

3-1. Questionnaire and Interview survey result

contract theory was build based on specific conflict in overseas.

Questionnaire is distributed to 28 employee of company A.
and interview survey was conducted and these survey
results as following Fig3. Fig3 shows the number of conflictin each stakeholder. As following Fig3, it is found that thebiggest number of conflict is between contractor andsubcontractor.

(Fig2)

2-2. What is Moral Hazard?
By the way, what is moral hazard? Moral hazard can be present any
time two parties come into agreement with one another. Each party in

Therefore, this result can be assumed that conflict between
contractor and subcontractor is happened frequently inoverseas construction project. It is found that these conflicts

a contract may have the opportunity to gain from acting contrary to
the principles laid out by the agreement.

61

behind. When contractor and subcontractor executed
contract, subcontractor concealed real spec to get job.
E：Subcontractor wouldn’t make the deadline for contractor
but they already got all payment from contractor. Therefore,
they got done with work in spite of they hadn’t confirmed
check enough. After that, contractor found a mistake aboutcertain parts from subcontractor but Contractor had tomodify them due to pay all money to Subcontractor alreadyfrom contractor.
F ： Case of that subcontractor submit product, since
subcontractor was pursed due date, although subcontractor
hasn’t prepared yet, subcontractor reported as fake that I
am ready for Vendor FAT (Factory Acceptance Test, shipping
confirmation examination of attendance at proceeding by
clients).But since preparation for Vendor FAT wasn’t
finished yet, subcontractor couldn’t pass this examination byclients. Then contractor had to start again.
G： Ladder which is for Air Fin Cooler wasn’t made as
required. Ladder is not importance compare other parts.
That’s why Subcontractor designed it without asking
Contractor.
H：Workers of subcontractor often dare to happen strike
intentionally since they don’t want to work. They take aholiday.
I：Worker of subcontractor sometimes dare to jump off fromhigh height with no scaffold since they want to solarium(payment for pain and suffering) .
J：Welder of subcontractor make fake welding product whichapparently can be seen as a completed product.
K：The number of trip by hauler of earth and sand is at gate
during construction stage. Hauler sometimes tries to cheat
the number of trip by giving extra money to a worker at thegate.
L： In hot site, ice provider sometimes try to cheat the
number of how many times they provided an ice by putting
ice at outside (it means that they dare to make ice melt)
M：Worker of subcontractor sometimes do sabotage to stay
more at site during test session. They tried to get allowanceat site.
Next, classify the case A~M as each case is caused bysubcontractor(company) or (worker) and where each case iscaused country overseas project experience not enough orcountry overseas project experience enough (Fig5)．From
Fig5，Case A can be assumed as that case can occur thehighest frequency because case A can occur at everywhere
and can be caused by both subcontractor company andworker. Case B~G would be happened all over the worldexcept Japan and these can be said general case in overseas．
Therefore, from framework of case, the most general case iscase A, B and these would be used as model case and proceed
theoretically analysis. But case C~G is same as case B inmany point, these case can be described generally by usingcase B. Finally case A and B is decided as representativecase

are case of preventing efficiency.

Fig3. The number of conflict between each stakeholder inoversea projects for Company A
3-2. Verification survey result
This verification survey also was conducted as questionnaire
and interview survey. Furthermore, this survey result is
Fig4. Conflict between contractor and subcontractor in eachstakeholder is the most frequency in overseas project.

Fig4. The number of conflict between each stakeholder inoversea projects for Company B
3-3. Narrowing the all case to typical case in overseas
From the above survey, many moral hazard cases wereextracted. It can be assumed that one of these research
objectives is achieved through above survey. Next, moral
hazard cases are narrowed to clarify what can moral hazard
cases occur the highest frequency.
Then introduce the case of moral hazard that obtained byprevious surveys after narrowing.
3-4. introduction narrowed typical 9 cases and classification
A：Contractor often proposes contract of incentive payment
to subcontractor. If subcontractor can submit product earlier
than due date, subcontractor can get incentive fee fromcontractor. Incentive bonus depends on how early thesubmission can be made. But if subcontractor can’t submit
by due date (at behind due date), subcontractor has to pay
penalty fee. This way of the contract usually gives incentive
in keeping due date of subcontractor.
B ： Subcontractor sometimes doesn’t acknowledge their
mistake despite they didn’t make an effort and can’t meetdue date. It blames other company for the mistake.
It means that Subcontractor tries to cheat to avoid penalty
fee.
C：Schedule had been behind since subcontractors hasn’t
skill enough for piling block. It occurred because
subcontractor had cheated real skill at accepting contract
with contractor.
D：Due to lack of subcontractor’s skills, schedule had been62

Fig5: Framework of caseIn case of that no incentive (𝒂𝒊 = 𝒂𝑳 ) and no
confirmation(𝑲𝒊 = 𝑲𝑳 )𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐿 )(𝐾𝐿 ) = 𝑅
𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐻 )(𝐾𝐿 ) = 𝑅 − 𝜓′
R > 𝑅 − 𝜓′ Therefore,𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐿 )(𝐾𝐿 ) > 𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐻 )(𝐾𝐿 )In case of that no confirmation, subcontractor had better tonot make an effort to get more payoff.
Incentive compatibility condition(Condition of that subcontractor makes an effort for making ontime)𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐻 ) − 𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐿 )= {R − 𝜓 ′ − (1 − 𝑝)𝑡2 𝑃} − {(𝑅 − 𝑡1𝑃 )} ≥ 0
𝜓 ′ ≤ {(𝑡1 − 𝑡2 ) + 𝑝𝑡2 }𝑃 ⋯ ⋯ ⋯①
In case of that incentive(𝒂𝒊 = 𝒂𝑯 ) and receiving confirmation(𝑲𝒊 = 𝑲𝑯 )𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐿 )(𝐾𝐻 ) = (1 − 𝑡3 )𝑅 + 𝑡3 (𝑅 − 𝑃) = 𝑅 − 𝑡3 𝑃
𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐻 )(𝐾𝐻 )= R − 𝜓 + 𝑞𝐹 − (1 − 𝑞)(1 − 𝑟)𝑡4 𝑃
In case of that no incentive (𝒂𝒊 = 𝒂𝑯 ) and no
confirmation(𝑲𝒊 = 𝑲𝑳 )𝐶2𝑒𝐿 : 𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐿 )(𝐾𝐿 ) = 𝑅
𝐶2𝑒𝐻 : 𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐻 )(𝐾𝐿 ) = 𝑅 − 𝜓
𝑅 > 𝑅 − 𝜓より
𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐿 )(𝐾𝐿 ) > 𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐻 )(𝐾𝐿 )In case of that no confirmation, subcontractor had better tonot make an effort to get more payoff.
Incentive compatibility condition(Condition of that subcontractor makes an effort for making ontime)
𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐻 ) − 𝛱𝐻𝐴 (𝑎𝐻 )(𝑒𝐿 )= {R − 𝜓 + 𝑞𝐹 − (1 − 𝑞)(1 − 𝑟)𝑡4 𝑃 − ( 𝑅 − 𝑡3 𝑃)} ≥ 0𝜓 ≤ 𝑞𝐹 + {(𝑡3 − 𝑡4 ) + (𝑞 + 𝑟 − 𝑞𝑟)}𝑃 ⋯ ⋯ ⋯②

4. Formulation
4-1. Model Overview
Build a model based on case A and B.
Incentive contract is the contract which subcontractor getsbonus depending on how early the submission can be made(The faster they submit, the more bonuses they get.) If
subcontractor submits before the deadline, contractor also
has benefit in terms of time and cost because time can beused for other work and time can link cost.
In case of subcontractor not meeting the deadline, it insiststhat there are other reasons for delay such as othersubcontractor’s delay. Subcontractor tries to avoid penalty
by behaving like this.
In case of it, contractor claims subcontractor to pay penalty.
Payoff of subcontractors by the incentive contract is also thefollowing three.
I.
They submit earlier than due date and get bonus
II. They make due date just in time and get reward ascontracted
III. They try to submit earlier than due date but they can’t
do it furthermore they can’t submit by due date. Thenthey probably was forced pay penalty fee．
Moral hazard is caused by subcontractor shifting blame andwill not occur if both get a maximum the payoff.
4-2. Parameter Distribution
Fig6 shows the game tree of game in extensive form. Payoff
𝜋 𝑃 , 𝜋 𝐴 is contractor and subcontractor respectively.
Game tree is proceeded as order below
1. Subcontractor chooses as to whether accept contract ornot. If not game will be end（node a）
2. Contractor chooses effort level 𝑎𝑖 (𝑖 = 𝐻, 𝐿) ． If theychoose 𝑎𝐻 and contract type is incentive. If case of𝑎𝐿 contract is normal．(no incentive)（node b）
3. In this move, subcontractor choose make an effort as𝑒𝐻 or not make an effort as 𝑒𝐿 and if its choice is inincentive, proceed node c2, and also if its choice in no
incentive as well, then proceed c1. In case of that not
make an effort，subcontractor can’t meet due date, andthen if it is in incentive, proceed e3. And if it is in no
incentive, proceed e1．(node c1,c2)
4. This move is nature. Subcontractor can be successes by
probability q in incentive and will get reward R andincentive bonus. If subcontractor is fail with probability
1-q, subcontractor has still chance as probability r to
submit product. In no incentive, subcontractor submit
with probability p by due date and can get reward ascontracted (node d1,d2,d3)
5. In case of that subcontractor doesn’t make an effort oris fail, they certainly try to shift blame to avoid paying
penalty. At the same time, contractor have to make aneffort to force them to pay with effort level𝜔𝑖 (𝑖 = 𝐻, 𝐿)(node 1~e4)
6. In case of that in 5, contractor choose make an effort,
success probability for forcing them to pay penalty
with 𝑡1 , 𝑡2 , 𝑡3 , 𝑡4 (node f1~f4)

Optimal Strategy

Subcontractor generally has no choice in contract type.
Therefore, all they can do is follow contractor’s decision ofcontract type. Function ① and ② is result of making aneffort. That’s why subcontractor should make an effort formeeting due date if subcontractor want to get profit more.
4-3. Contractor’s Payoff (Expectation value)

4-3. Subcontractor’s Payoff (Expectation value)

In case of that no incentive(𝒂𝒊 = 𝒂𝑳 ) and receiving
confirmation(𝑲𝒊 = 𝑲𝑯 )𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐿 )(𝐾𝐻 ) = (1 − 𝑡1 )𝑅 + 𝑡1 (𝑅 − 𝑃) = 𝑅 − 𝑡1 𝑃
𝛱𝐿𝐴 (𝑎𝐿 )(𝑒 ′ 𝐻 )(𝐾𝐻 ) = R − 𝜓 ′ − (1 − 𝑝)𝑡2 𝑃

63

At node t1~t4, as to whether Contractor should collect fromsubcontractor or not. Case of that subcontractor cannot
make due date is most of same. Therefore, t1 is used as
representative case.
In case of that making an effort for collecting𝛱𝐿𝑃 (𝑎𝐿 )(𝑒 ′ 𝐿 )(𝐾𝐻 ) = 𝑊 − ℎ − 𝜔 + 𝑡1 𝑃 ⋯ ⋯ ⋯ (∗)
In case of that not making an effort for collecting𝛱𝐿𝑃 (𝑎𝐿 )(𝑒 ′ 𝐿 )(𝐾𝐻 ) = 𝑊 − ℎ ⋯ ⋯ ⋯ (∗∗)(∗) − (∗∗) = (𝑊 − ℎ − 𝜔 + 𝑡1 𝑃) − (𝑊 − ℎ) = 𝑡1 𝑃 − 𝜔 > 0
Then contractor should make an effort to collect as thiscondition. Next, for being easy to build function, no consider
confirmation (remove node e below).At this same time,
contractor don’t know whether subcontractor make an effort
or not. Therefore, if contract is incentive, subcontractor
make an effort with d and if no incentive, probability isd’.(Fig7)
In case of no incentive, contractor’s payoff𝛱𝐿𝑃 (𝑎𝐿 ) = (1 − 𝑑′ )(𝑊 − ℎ) + 𝑑′ {(1 − 𝑝)(𝑊 − ℎ) + 𝑝𝑊}= 𝑊 − ℎ + 𝑑′𝑝ℎ ⋯ ⋯ ⋯ (A)In case of incentive, contractor’s payoff
𝛱𝐻𝑃 (𝑎𝐻 )= (1 − 𝑑)(𝑊 − ℎ − 𝜑)+ 𝑑[(1 − 𝑞){(1 − 𝑟)(𝑊 − ℎ − 𝜑) + 𝑟(𝑊 − 𝜑)}+ 𝑞(𝑊 + 𝐸 − 𝐹 − 𝜑)]Fig6: Fundamental model of game tree
= 𝑊 − 𝜑 − (1 − 𝑑)ℎ + 𝑑{−(1 − 𝑞)(1 − 𝑟)ℎ + 𝑞(𝐸 − 𝐹)}= 𝑊 − 𝜑 − ℎ{1 − (𝑞 + 𝑟 − 𝑞𝑟)𝑑} + 𝑑𝑞(𝐸 − 𝐹) ⋯ ⋯ ⋯ (𝐵)Optimal Strategy
Which incentive and no incentive contract would be betterfor subcontractor?
(𝐵) − (𝐴) = 𝛱𝐻𝑃 (𝑎𝐻 ) − 𝛱𝐿𝑃 (𝑎𝐿 ) > 0, Incentive contract isbetter than no incentive= 𝑊 − 𝜑 − ℎ{1 − (𝑞 + 𝑟 − 𝑞𝑟)𝑑} + 𝑑𝑞(𝐸 − 𝐹)
− (𝑊 − ℎ + 𝑑′ 𝑝ℎ) > 0
𝑑𝑞𝐸 + {(𝑞 + 𝑟 − 𝑞𝑟)𝑑 − 𝑝𝑑′ }ℎ − 𝜑 > 𝑑𝑞𝐹

5. Conclusion

This study focused on 2research which one is survey andother is contract theory. Survey’s and model’s finding asfollow

In advance, contractor has prepares contingency andman-hour to deal with some risk which can occur
simultaneously.

From model, some finding as follow
 If contractor save incentive bonus as small,utility of contractor will be higher.
 If ahead of schedule thanks to subcontractor isbig, utility of contractor will be higher.
 If suffer a loss from delay is big, contractor must
give incentive to subcontractor as submitting
earlier.
 If probability of that subcontractor can meet due
date is big, it means that contract type would be
no incentive.

Fig7: In case of no action for collecting penalty
Thus, Contractor should propose Incentive contract to
subcontractor. Furthermore, it is found that subcontractor
certainly make an effort to meet due date from ① and ②.
d and d’ can be d=d’=1．Therefore,
𝑞𝐸 + {𝑞 + (1 − 𝑞)𝑟 − 𝑝}ℎ − 𝜑 > 𝑞𝐹 ⋯ ⋯ ⋯ ③.
At this time, condition of subcontractor’s optimal payoff inincentive contract is𝜓 ≤ 𝑞𝐹 + {(𝑡3 − 𝑡4 ) + (𝑞 + 𝑟 − 𝑞𝑟)}𝑃 ⋯ ⋯ ⋯②
From ②, ③ we can get𝝍 ≤ 𝒒𝑭 ≤ 𝒒𝑬 + 𝒉{−𝒑 + 𝒒 + (𝟏 − 𝒒)𝒓} − 𝝋 ⋯ ⋯ ⋯ ④(But, member of P can be ignored since effect as against
function② is small).
④ is important to get maximum utility each other.
Interpretation ④

If F is small, incentive contract can be easy to be
adopted for contractor

If E is big(ahead of schedule is big), incentive contract
can be easy to be adopted for contractor
If 𝒉 is big(suffer a loss from delay), incentive contract
can be easy to be adopted for contractor
If 𝒑 is big(even in no incentive, when probability ofthat subcontractor can meet due date is big)𝒒 + (𝟏 − 𝒒)𝒓 − 𝒑 would be small. It means that
contract type would be chosen no incentive.

6. References
[1]
[2]
[3]
[4]

64

山本明男：日系建設会社のグローバル戦略－リスクマネジ
メントから見た事例研究, 2007
石磊・小林潔司：建設契約におけるダブルモラルハザード,
2010
Joel S.Demski et al.: Resolving double moral hazard
problems with buyout agreements, 1991
Russel Cooper et al.: Product Warranties and Double
Moral Hazard, 1985

An Analysis on Consumers’ Preferences for the Residential Photovoltaic System
Focused on Its Long-Term Operation
Student Number: 11M18150

Name: Toshiya MORIZUMISupervisor: Naoya ABE

住宅用太陽光発電システムの長期運用に着目した消費者選好の分析
森住 俊哉
本研究では、普及が進むにつれ近年増加している住宅用太陽光発電システム（以下、住宅用 PV）に係わる消費者トラブルの改善、また消費者に対する故障や保守管理に関する適切な情報提供の重要性とこれらの情報が住宅用 PV の購買行動に与える影響を明らかにすることを目的しアンケート調査を行った。同調査によるデータを分析し、住宅用 PV の保守管理制度に対して高い消費者選好を持つ消費者群の特徴を情報収集の観点から明らかにした。分析結果を基に、消費者が保守管理の重要性を認知し購買意思決定を下すために必要な情報提供の在り方を提言した。
recognized among policymakers. For example, areport by the Ministry of Economic, Trade, andIndustry (METI), Japan (2009a) on the expected
initial cost recovery period of residential PV
systems under the feed-in tariff, effective from2012, did not include the aspect of additionalcosts for user support.
Changes in consumers’ behavior in gathering
information could be one of the key tools toprovide adequate information on PV systems.
METI (2009b) surveyed the status of consumers’
behavior in gathering product information. The
survey results showed that word-of-mouthcommunications (WOMCs) significantly influence
consumers’ purchase decisions. In the case ofresidential PV systems, consumers’ behavior ingathering information including WOMCs has
become more multifaceted. If consumers’ behavior
in gathering information on PV systems
influences their purchasing decisions, thendifferences in gathering approaches could affecttheir preferences for selected attributes ofresidential PV systems, such as price andperformance.

1. Introduction
In recent years, electricity output fromphotovoltaic (PV) systems has been increasing
considerably. Specifically, residential PV systems
have made a particularly large impact in theJapanese PV market. However, as the number ofresidential PV system installations increases, thenumber of consumer problems with PV systems
also rises (Figure 1). Consumer problems with PV
systems are of great concern because they not
only impose financial risks on consumers but also
prevent the PV market from developing soundly.
Based on this development, Cabinet Office, Japan(2012) proposed solutions from three perspectives:
law enforcement, the importance of the quality ofmaintenance services, and adequate information
provision.
Number of consumer problems

3500
3000
2500

2000
1500
1000

2. Objectives
This study suggests solutions to the problems of
information provision and the quality ofmaintenance services proposed by Cabinet Office,Japan (2012). To reduce consumers’ financial
risks when purchasing PV systems, adequate
information provision should not only improve
consumer problems with such systems but also
make consumers recognize the importance of thequality of maintenance services for theirlong-term operation. Hence, this study aims to:500
02001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Figure 1. Changes in the number of consumer
problems with PV systems (2001–2011)
Source: Cabinet Office, Japan (2012)
Under this proposal, Cabinet Office, Japan(2012) indicated the importance of the quality ofmaintenance services for PV systems. An increasein the quality of user support (e.g., warranty andmaintenance services) is expected to reducepurchasers’ financial risks (Shinp et al., 1982).
According to the survey by Kato (2010),
approximately 35% of residential PV systems
experience some problems within 10 years of
installation. In spite of this fact, the importanceof user support for PV systems has not been

1) Study the relationship between consumers’
preferences for residential PV systems andconsumers’ behavior in gathering information onsuch systems through data analysis.
2) Assess the proposal by Cabinet Office, Japan(2012) and propose more effective solutions
related to information provision on PV systems.

65

decrease the number of profiles and to effectively
observeconsumers’
preferencesforallalternatives in each attribute. In total, the 32
profiles generated by applying such an orthogonal
design were divided into eight choice sets
randomly. Table 4 presents an example of the
choice sets used in this survey. Four options werethen chosen from the 32 profiles and one
no-choice option. The no-choice option in choicesets is applied to avoid the overestimation of
consumers’ preferences (Vermeulen et al., 2008).

3. Data collection
This study conducted an online survey to collectdata on consumers’ behavior in gathering
information on PV systems and their preferences
for residential PV systems. Tables 1 and 2 show
the summary and content of this survey,
respectively.
Table 1. Summary of the online survey
Survey term

3 Oct, 2012～5 Oct, 2012

Respondents

Consumers who are plannning to install
residential PV systems within 3 years

Sample size

Table 4. Example of choice sets

Q: Which one of the following options would you
choose if you were purchasing a residential PV
system?

N=291

Table 2. Content of the online survey
Data
Definition
Demographic characteristics Age, households' income,occupation, education etc.
Behavior for gathering
1) Information sources which
information on PV systems respondents use or trust2) Contents of information which
respondents use or trust
Stated preference
Choice-based experimentson resdential PV systems

Option1

Option2

Option3

Option4

1.8 million JPY

2 million JPY

1.8 million JPY

2.2 million JPY

Initial cost recovery
period16 years

10 years

10years

17years

Peripheral warranty
period10 years

15 years

15 years

10 years

Module performance
warranty period

15 years

25 years

20 years

25 years

Price

Application fee for
peripheral warranty

free

10,000 JPY

free

Maintenance service(10 years)

Periodic check30,000JPY

Periodic check30,000JPY

none

□

□

□

ChoiceChoice-based experiments (shown in Table 2) are
generally used to collect stated preference datafor products. In experiments, the researcher
provides a number of choice sets to respondents
and asks them to choose the most desirable optionin each set. Choice sets are constructed fromcertain profiles including attributes such as priceand product quality. This study assumed that cost,benefit, and warranty and maintenance services
affect consumers’ decisions when purchasing PV
systems. In this survey, six attributes with two or
four alternatives were defined as the components
of profiles (Table 3).

Attributes

Alternative1

Alternative2

Alternative3

Alternative4

1.8 million JPY

2 million JPY

2.2 million JPY

2.4 million JPY

Initial cost recovery
period7 years

10 years

13 years

16 years

Peripheral warranty
period10 years

15 years

Module performance
warranty period

10 years

15 years

20 years

25 years

Application fee for
peripheral warranty

free

10,000 JPY

20,000 JPY

30,000 JPY

none

Periodic check30,000JPY

Maintenance service(10 years)

free
Monitoring service

30,000JPY□□

This study applied the latent class (LC) model toestimate the relationship between consumers’
preferences for PV systems and their behavior ingathering information on such systems. First, themethodology of standard conjoint analysis is
explained. It is assumed that respondents choose
options that possess the combination of attributes
that would provide them with the highest level ofutility. (Eq. 1) represents the utility level attained
from option (i) for individual (n):𝑈𝑛𝑖 = 𝐗 𝑛𝑖 𝛃′ + 𝜀𝑛𝑖(Eq. 1)
𝐗 𝑛𝑖 is the vector of observed attributes with
conformable parameter 𝛃′, while the error term
𝜀𝑖𝑗 is unobservable and assumed to follow a
Gumbel distribution. The probability that
individual (n) chooses option (i) is represented in(Eq. 2):𝑃𝑛𝑖 =exp⁡(𝐗 𝑛𝑖 𝛃′)∑𝑖 exp⁡(𝐗 𝑛𝑖 𝛃′)(Eq. 2)This model estimates 𝛃′, which maximizes the
log-likelihood function (Eq. 3):

Monitoring service Monitoring service

freeChoosenothing fromthese options

4. Data analysis

Table 3. List of attributes and alternatives
Price

Option5

30,000JPY

ln 𝐿 = ∑ ∑ 𝑑𝑛𝑖 ln 𝑃𝑛𝑖

Choice experiment design is concerned withcreating choice sets in an efficient way. Applying afull factorial design would generate too many
choice sets, which would be cumbersome forrespondents to answer. In the case of the design
shown in Table 3, the total number of
combinations would be 2,048. Therefore, anorthogonal design was adopted by this study to𝑛𝑖(Eq. 3)𝑑𝑛𝑖 is the choice result whether individual (n)chooses option (i) or not.
However, it is known that heterogeneity amongindividuals’ preferences makes them difficult to
examine in traditional conjoint models. The LC
model overcomes this issue by assuming that the
population consists of latent classes (Z) and that66

Table 5. Description of the variables used in the
LC modelthe unobserved heterogeneity among individuals
can be estimated by these classes throughestimating a parameter vector in the membershipfunction (Eq. 4):
𝑀𝑛𝑧 = 𝐖𝑛 𝝀′𝑧 + 𝜁𝑛𝑧(Eq. 4)

Variable
Description
Devendent valiable
Chosen1 if the option is chosen, 0 otherwise
Variables in utility function
PriceTotal price [million JPY]
(Price+Application fee for peripheral warranty)
Initial
Initial cost recovery period [year]
Peripheral
Peripheral warranty period [year]
ModuleModule performance warranty period [year]
Dum_Periodic
1 if the maintenance service is "Periodic check", 0otherwise
Dum_Monitor_free 1 if the maintenance service is "Monitoring service(free)", 0 otherwise
Dum_Monitor_paid 1 if the maintenance service is "Monitoring service(30,000JPY)", 0 otherwiseASC
1 if the option is "no-choice option", 0 otherwise
Variables in membership function 1:Experiences on gathering information
Dum_Basic
1 if a respondent has collected information about price,performance of PV systems, 0 otherwise
Dum_Governmental 1 if a respondent has collected information about
governmental supports for PV systems, 0 otherwise
Variables in membership function 2:Trustworthy information sources
Dum_e-WOM
1 if a respondent trusts information from
e-WOMCs , 0 otherwise
Dum_WOM
1 if a respondent trusts information from
WOMCs ,0 otherwise
Variables in membership function 3:Trustworthy conents of information
Dum_Governmental 1 if a respondent trusts information about governmental
supports for PV systems, 0 otherwise
Dum_Actual
1 if a respondent trusts information about actual PV
power generation or yield from PV systems, 0 otherwise

𝐖𝑛 is the vector of the characteristics ofindividuals with conformable parameter 𝝀′𝑧 and𝜁𝑛𝑧 is the unobservable error term. The
probability that individual (n) resides in thelatent class (z) is
𝜋𝑛𝑧 =exp⁡(𝐖𝑛 𝛌′𝑧 )∑𝑧 exp⁡(𝐖𝑛 𝛌′𝑧 )(Eq. 5)

By combining the choice equation (Eq. 2) with themembership equation (Eq. 5), the probability that
individual (n) chooses option (i) under theassumption of heterogeneity among individuals is
𝑃𝑛𝑖 = ∑ 𝑃|𝑛𝑖|𝑧 𝜋𝑛𝑧𝑐exp⁡(𝐗 𝑛𝑖 𝛃′𝑧 )exp⁡(𝐖𝑛 𝛌′𝑧 )
=∑ [
]×[
]
∑𝑧 exp⁡(𝐖𝑛 𝛌′𝑧 )𝑧 ∑𝑖 exp⁡(𝐗 𝑛𝑖 𝛃′𝑧 )(Eq. 6)

5. Results

The marginal willingness to pay (MWTP) is used
to compare consumers’ preferences for each
attribute. MWTP is calculated as (Eq. 7)
𝑀𝑊𝑇𝑃 = −𝛽𝑧𝛽𝑐𝑧

The variables are described in Table 5, while
Table 6 shows the results of the LC model. This
study classified respondents into three groups
based on the heterogeneity of their preferences forresidential PV systems. This result shows thatapproximately 29% of respondents (class 2) havethe highest preferences for initial cost recovery
period, module performance warranty period, andmaintenance service among all respondents. Thismeans that they would like to recover the initial(Eq. 7)𝛽𝑐𝑧 is the estimated parameter of cost in class (z)and 𝛽𝑧 is the estimated parameter of attributes
except price. The goal of the LC model is toestimate both the MWTP and a vector ofparameter 𝛌𝑧 in the membership function.

Table 6. Results of the LC model (N=291)

Class1
Class2Marginal Willingness to pay (MY: million JPY)
MWTP
t-valueMWTPt-value
Initial [MY/year]-0.027***-3.083-0.296***-4.363
Peripheral [MY/year]
0.028***
2.700
0.021
1.387
Module [MY/year]
0.022***
4.470
0.040***
3.391
Dum_Periodic [MY]0.305***
4.191
0.550***
2.813
Dum_Monitor_free [MY]0.820***
8.232
0.795***
3.498
Dum_Monitor_paid [MY]0.438***
5.316
0.660***
3.025
ASC [MY]-3.679***-8.868-4.344***-5.917
Membership function 1: Experiences on gathering information
lamda
t-valuelamda
t-value
Const
0.156
0.474
-0.579-1.439Dum_Basic
1.188***
3.014
0.936**
2.077
Dum_Governmental
0.234
0.633
0.713*
1.683
Membership function 2: Trustworthy information sources
lamda
t-valuelamda
t-value
Const
1.048***
5.158
0.178
0.735
Dum_e-WOM
0.061
0.158
0.942**
2.230
Dum_WOM
0.585
1.220
0.249
0.457
Membership function 3: Trustworthy conents of information
lamda
t-valuelamda
t-value
Const
0.920***
4.865
0.093
0.409
Dum_Governmental
0.695
1.611
1.250***
2.737
Dum_Actual
1.312
1.225
1.580
1.441
Class share
54%
29%

Class3MWTP-0.105
0.010
0.013
0.180
0.825
0.221
-1.019t-value-0.729
0.301
0.355
0.565
0.838
0.516
-0.816

Base outcome

Base outcome

Base outcome
17%***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively.
67

initial cost recovery.

cost in a shorter period and that they attach
importance to high-quality user support
compared with other respondents.
In addition, the LC model estimated consumers’
characteristics
thatmayinfluencetheheterogeneity of their preferences for PV systems.
The LC model defined class 3 as the base outcome.
Therefore, the parameters of the membershipfunctions for classes 1 and 2 are different fromthat of class 3. This study adopted three datasets,
as shown in Table 6. The results are explained asfollows.
First, it is observed that consumers who gather
information more positively have higher
preferences for initial cost recovery and user
support than others. The parameters ofmembership function 1 show that respondents inclass 1 tend to gather basic information such as
price and system performance, while respondents
in class 2 tend to gather both basic informationand information on governmental support such as
subsidies.
Second, there is a probability that consumers
who trust interactive communication with PV
users are categorized into class 2. The result ofmembership function 2 shows that the dummy
variable e-WOM in class 2 is statisticallysignificant at the 5% level. Information from PV
users includes information about their actual PV
power generation and actual yields from theirsystems. This finding implies that respondents inclass 2 like to gather more reliable information
related to initial cost recovery through e-WOMCs,
namely communication with PV users on theInternet.
The probability that consumers who have higher
preferences for initial cost recovery and user
support would like to gather more reliable
information is also observed through anothermembership function. Membership function 3(Table 6) was constructed with a dataset about
the information content respondents trust themost. The estimated parameter was notstatistically significant; however, respondents
who attach importance to information on actual
PV power generation and yield from PV systems
in addition to information on governmental
support would be classified under class 2.

2) Conclusion: Objective 2
Cabinet Office, Japan (2012) proposed that it isimportant for both consumers and the PV market
to provide more understandable and accessible
information on PV systems. The results of the LC
model support this proposal. If information on PV
systems, especially that related to initial cost
recovery, was more understandable and accessible
for consumers, consumers would attach a higher
importance of these information to the long-term
operation of PV systems.
3) Further study
The proposal by Cabinet Office, Japan (2012)
presented a future research avenue for theprovisionof
informationon
consumers’
profitability. In recent years, services for theestimation of PV power generation have been
provided to consumers by a number of PV
manufacturers. However, as mentioned in the
proposal by Cabinet Office, Japan (2012),
improvements in estimation accuracy arenecessary to provide more reliable information on
consumers’ profitability.
This
study
has
demonstrated that more reliable information on
consumers’ profitability is also necessary for the
long-term operation of PV systems; theassessment of the accuracy of output estimation
could thus be further studied. Another research
direction could be the re-examination of thecalculation of the initial cost recovery period
conducted by METI (2009a). As mentioned in the
introduction to this paper, the existing calculation
does not include the additional cost for user
support. To provide more reliable information on
consumers’ profitability, policymakers should
propose more realistic calculation results to
consumers.

References
Cabinet Office, Japan, 2012, Proposal for consumer
troubles on residential photovoltaic systems (inJapanese)
Kato, 2010, Collection of instances related to troubles
on photovoltaic systems, Nikkou Kogyou Shinbunsha(in Japanese)
METI, Japan, 2009a, Report on feed-in-tariff forphotovoltaic systems (in Japanese)
METI, Japan, 2009b, Survey on the consumers’purchasing behavior after Lehman shock (inJapanese)
Shinp et al., 1982, Warranty and other extrinsic cue
effects on consumers’ risk perceptions, Journal ofMarketing, Vol. 39, No. 2, pp. 36-43
Vermeulen, Goos and Vandebroek, 2008, Models andoptimal designs for conjoint choice experiments
including a no-choice option, International Journal of
Research in Marketing, Vol. 25, pp. 94-103

6. Conclusions
1) Conclusion: Objective 1
The LC model expressed the relationshipbetween consumers’ preferences for PV systems
and their behavior in gathering information onsuch systems. Consumers who have higher
preferences for initial cost recovery and user
support have the characteristic of gathering
information
more
positively
andattachimportance to information sources and content
that include more reliable information related to68Quantitative analysis of the atmospheric boundary layer flow fieldusing Doppler lidar
Student Number: 11M18166

Name: Ayako Yagi

Supervisor: Manabu Kanda

ドップラーライダーを用いた大気境界層流れ場の定量的解析手法の提案
八木綾子
本論文では，ドップラーライダーにより観測された視線方向風速分布から，都市上空の流れ場を定量的に解析する手法を提案する．各方位角の視線方向風速分布において算出した自己相関係数か
ら流れ場の代表的な長さスケールを抽出した．算出した代表長さは，支配的な構造の特徴，及びその日変化を捉えていた．

radial velocity distribution observed by Doppler
lidar. These researches contributed to understanding
ABL flow field.
Although some researches have shown the
span-wise width of streaky pattern of ABL flow,
their stream-wise scale was not precisely examined.
A considerable reason is because a range of usual
Doppler lidar observation is not enough to capture
the full scale of stream-wise length of streaky
structures. Another reason is from a difficulty in thephysical interpretation of the calculated stream-wiselength because of the meandering of streaky pattern.
The first reason is entirely follow the Doppler lidar
equipment. The second reason could be solved byadjusting the estimation procedure, which is a partof the aims of this study.
In addition, most of the previous researches
have focused on the streaky pattern and the otherpatterns are still not well examined since they aremuch less frequently observed compared to thestreaky structure during their limited observation
periods.
In this research, a method is proposed toestimate stream-wise representative length andspan-wise representative length. This method wasapplied not only to streaky pattern but also to otherflow patterns. Special aspects of this research area
as follows: (1) Stream-wise length scale isexamined together with the span-wise length scale.
(2) This method was applied to whole datasets
obtained for two weeks. Based on this analysis,
structures of various flow patterns (not only streaky
pattern) were analyzed quantitatively andcomprehensively.

1 Introduction
Local heavy rainfall and air pollution areatmospheric environmental problems which havestrongly influenced our daily life. These problems
are strongly coupled with momentum and scalartransport process within the atmospheric boundary
layer (ABL). Hence, the understanding of flow fieldwithin the ABL is important to solve or mitigate theatmospheric environmental problems.
It is commonly known that flow structure within
the ABL configure some characteristic patterns.
Woodcock [1] suggested that there are two types offlow structure within the ABL from observation ofHerring Gull flight above the sea: i.e. linear
structure (LS) and random structure (RS).
Grossman [2] estimated the spatial width of theflow structure based on the spectra of verticalvelocity observed above the sea.
Doppler lidar is the latest remote sensing system
which has been used to analyze ABL flow field inrecent years. Doppler lidar beams near infraredlaser (1.54 ) and receive the backscatter reflectedfrom aerosols floating in the atmosphere. Then,radial wind velocity can be measured by detecting
the Doppler shift of the backscatter. Doppler lidar
measurements
havealreadymadesomeachievements in the ABL research. Fujiyoshi [3]has observed streaky structure and thermal structure
within a field observation in Sapporo. Iwai [4] hasdetected the two-dimensional wind velocity
distribution using Doppler lidar observation and thewidth of convective rolls from frequency analysis
of vertical velocity observed by airplane
observation. Oda [5] calculated the width of streaky
structure from two-point correlation coefficient of69

2 Overview of Doppler lidar(1)Autocorrelation coefficient
was calculated
from measured radial wind velocity distribution oneach azimuth using eq. (4.1).

Table.1 shows specifications of Doppler lidar used
for this research. The measurement range in radial
direction is from 325 m to 4275 m which isresolved each 50 m. This Doppler lidar is installedon the roof top of West 8th building in Tokyo
institute of technology (sea level altitude is 78 m,height from ground is 42 m cf. Fig.1). It has
operated since August 2011. The measurement area
is represented by residential urban area. Outside themeasurement area, metropolitans, e.g. Shinjuku andShibuya, spread in the north east. Such a long term
observation in urban area has never been conductedso far.
The measurement was operated by Plane
Position Indicator (PPI) scan. In PPI scan, scanner
turns round with constant elevation. In this research,elevation angle was set 0 . This means that scanner
turns round parallel to the sea surface and thehorizontal radial velocity distribution wasmeasured.
Table.1: Specifics of Doppler lidar
Range resolution
Minimum/Maximum range
Range bin number
Scan speed,,

In this research,correlation.

was set as indication of(3) Two representative lengths, i.e.
and, were determined among the
integral length distribution in azimuth.
represents the longest integral length throughazimuth, which implies the stream-wise length scale,andis the shortest and has a meaning of
span-wise length scale. For the determination ofthese characteristic scales, data during one hour areused in which 10 scans of the data were included.
is determined at the azimuth where varianceofamong 10 scans of data is largest since
meandering of structure makes the variance largest
in stream-wise direction.
is determined at
the azimuth where variance ofis minimum sincevariance ofis less affected by meandering in the
span-wise direction.

Scanner

Height fromground is 42m.

4km

Fig.1: Observation site(a) Observation area of Doppler lidar, (b) Locationof Doppler lidar, (c) The scanner of Doppler lidar.

3 Analytical basis
Representative length scale of flow patterns are
estimated in the following procedures (cf. Fig.2).

(2)Calculation of integral lengthfrom autocorrelation coefficient.

(3)Extraction of representative lengthfrom integral length.

[m]

(4.2)
1.0

[m s-1]

0

0.5
-2
0.0

-4

0
-6
0

1000

2000

3000

4000

(4.1)

(2) Integral length
was calculated by integrating
the autocorrelation coefficients in radial direction
on each azimuth by eq.(4.2).
(4.2)
∫

(c)

(1)Calculation of autocorrelation coefficientfrom radial velocity distribution.

̅̅̅̅̅̅̅̅̅̅̅

Where, R is autocorrelation coefficient,isradial velocity, az is azimuth angle, r is radial
distance,is phase lag,is integral interval.
Over bar indicates spatial mean in radial direction.
The value of
was decided empirically withconsidering the precision of autocorrelation
coefficient and limitation of observation area. The
resolution of is 50 m, which is the same as theresolution of Doppler lidar.

(a)

(b)

̅̅̅̅̅̅̅̅̅̅̅

̅̅̅̅̅̅̅̅̅̅̅ √∑

√∑

50 m
325 m/4275 m
80
3.0 degree s-1

The installation site̅̅̅̅̅̅̅̅̅̅̅

√∑

250

500

750

1,000

1,250

1,500

-0.5

[m]

r[m]

Fig.2: Flow of analysis procedure70[]

4 Results
4.1 Comparison of integral lengths between
streak and fishnet cases.
Fig. 3 shows integral length through azimuth. In
Fig.3, left figures show radial velocity in which red(blue) means positive (negative) radial velocity
toward the observation point. The right figures in
Fig.3 show the integral lengths where the dottedlines and dot-dash lines show the span-wise andstream-wise direction, respectively. These winddirections were estimated from Velocity Azimuth
Display (VAD) method.
Fig.3 (a) and (b) distinguish the streak andfishnet events respectively. Streak event has thestreaky wind velocity pattern along stream-wise
direction. Fishnet event is cell-like patterns andisotropic horizontally. As in the Fig.3, the integral
length of streak event tends to be longer instream-wise and to be shorter in span-wise direction.
In a fishnet case, the integral length distribution wasalmost isotropic in azimuth. Therefore, the present
method could properly distinguish the two kinds ofevent adequately.
180°

90°

270°

0°

1,500
1,000
500
0
0

180°

270°

90°

0°

90
180
270
Azimuth [degree]

360

2,000

(b2)

Integral length [m](b1)

Fig.5 shows the estimated representative lengths(
and). The axis at
the right side is for, and that of left side isfor. The figure shows thatis longerin the night time, andis getting longer withapproaching noon. Fig.6 shows the extracted
azimuth (and) and stream-wise andspan-wise estimated from VAD method.
) is almost identical to stream-wise(span-wise) direction. Therefore the estimatedrepresentative lengths seem to correctly reflect thestream wise and span wise.

(a2)
Integral length [m](a1)

Fig.4: The daily change of radial velocity
distribution

600

1,500

1,500

400

1,000

1,000

500

500

0

200
0
0

4

90
180
270
Azimuth[degree]

12

16

20

24

Time [hour]

0
0

8

360

Fig.5: The daily change of representative length

Fig.3: Comparison integral length of streak caseAzimuth [degree]with fishnet case
4.2 The daily change of representative lengths
The representative lengths (and)
were calculated in a typical day. The radial velocity
pattern used for this analysis was shown in Fig.4. In
the night time, streak structure was dominant andthe structure was gradually transformed to fishnet
pattern with approaching 12:00.

360
270

180
90
0
0

4

8

12

Time[hour]

16

20

24

Fig.6: Comparison
andwithstream direction calculated by VAD method

71

4.3 Relationship of representative length withatmospheric stability
Validity of the integral lengths was evaluated in theprevious sections. Those integral lengths were usedas the index of flow structure in this section.
Fig.7 shows the correlation diagram ofatmospheric stability ( ⁄ ) with aspect ratio of⁄
stream- and span-wise lengths (). Theanalysis was conducted for the datasets obtained in
2012/10/1-2012/10/13 in which 170 cases areincluded. Figs.7a, b show the unstable ( ⁄)and stable ( ⁄) cases respectively.
Atmospheric stability was observed using asonic-anemometer which was installed within ameasurement area of the Doppler lidar. Colors ofplots in Fig. 7 correspond to the flow patterns
which were visually classified into 6 groups;“Streak”, “No streak”, “Mixed”, “Fishnet”, “Front”
and “The others”. In this classification, Mixed is amedium flow pattern between Streak and Fishnet.
⁄
In the unstable case, aspect ratio ()
tends to decrease with increasing ⁄ . The plots ofStreak are distributed at relatively large aspect ratio,
and it followed by Mixed and Fishnet. This order in
the aspect ratio is consistent with the visuallyclassification as Streak is more elongated andfishnet is more round. In the stable case, the aspectratio looks less sensitive to ⁄ .

(a)Unstable

1.Streak3.Mixed

2.0E-03

4.0E-02

4.Fishnet

5 Conclusions
Doppler lidar measurements have been mainly used
for only qualitative analysis of ABL flow. The
method proposed in this paper allows quantitative
analysis of ABL flow. The following findings wereobtained.
1) Representative lengths of flow pattern were
determined using radial velocity distribution
measured by Doppler lidar.
2) Integral length distribution through azimuth
showed a reasonable tendency for streak structuresand fishnet structures.
3) Diurnal variation of representative lengths
corresponds to that of the flow pattern.
4) The aspect ratio of representative lengths
decreases as the atmospheric stability ( ⁄ )increases in unstable case. The same tendency
cannot be seen in the stable case.

References[1] Woodcock, A. H.: 1975, Thermals Over the Sea
and Gull Flight Behavior,Boundary-Layer Meteorol.
9, 63-68.
[2] Grossman, R L. 1982: An analysis of verticalvelocity spectra obtained in the BOMEX
fair-weather, trade-wind boundary layer., Bound
Layer Meteor., 23, 323-357.
[3]Y. Fujiyoshi, K. Yamashita, C, Fujiwara:
Visualization of Streaks, Thermals and Waves in
the Atmospheric Boundary Layer, Journal of
Visualization, Volume 9, Issue 4, p 359, 2006.
[4] Hironori Iwai, Shoken Ishii, Nobumitsu
Tsunematsu, Kohei Mizutani,Yasuhiro Murayama,
Toshikazu
Itabe,
Izumi
Yamada,Naoki
Matayoshi,Dai Matsushima, Sha Weiming, Takeshi
Yamazaki,andToshikiIwasaki,2008:
Dual-Doppler lidar observation of horizontal
convective rolls and near-surface streaks,
GEOPHYSICAL RESEARCH LETTERS, VOL.
35.
[5] Ryoko Oda, Hironori Iwai, Yasuhiro Murayama,
Shoken Ishii, Kohei Mizutani, Toshikazu Itabe,
Nobumitsu Tsunematsu, Izumi Yamada, Naoki
Matayoshi, Dai Matsushima, Weiming Sha.
Takeshi Yamazaki and Toshiki Iwasaki: DOPPLER
LIDAR OBSERVATIONS OF THE COHERENTSTRUCTURESIN THE INTERNAL BOUNDARY
LAYER

6.The ohters

20

⁄

15
10
5
0
1.0E-04(b)Stable

1.Streak

8.0E-01⁄

2.No streak

1.6E+01

3.2E+02

3.Mixed

20

⁄

15
10
5
0
1.0E-04

2.0E-03

4.0E-028.0E-01

1.6E+01

3.2E+02⁄

Fig.7: Relationship atmospheric stability withaspect ratio of representative length(a) Unstable case, (b) Stable case.
72

APPLICATION OF VIRTUAL REALITY (VR) PANORAMA FOR TOWNSCAPE
MONITORING IN THE WORLD HERITAGE SITE OF LUANG PRABANG, LAO P.D.R.
Student Number: 11M18189

Name: Kenta YOKOISupervisor: Shinobu YAMAGUCHI, Jun-ichi TAKADA

ラオス，世界遺産地域ルアンパバーンにおける町並み景観モニタリングのための VR パノラマの応用
横井健太

本研究は，ラオス国の世界遺産地域ルアンパバーンにおける町並み景観の変化をモニタリングのための町並み景観表現技術を試行導入し評価すると同時に，その技術を用いたモニタリング手法の確立を目的とする．町並み景観表現技術の比較検討の結果，VR(バーチャルリアリティ)パノラマを用いた方法が最適であると判断された．そこで VR パノラマ技術を活用した Street-View(ストリートビュー)と名付けたバーチャルツアーを提案し，現地ルアンパバーンにおいて試行導入を行なった．有用性と持続可能性の側面から評価を行った
結果，導入した VR パノラマを用いた方法は町並み景観のモニタリングに有効活用できることが判明した．同時に，作成方法に関する研修を適切に行うことで持続的な活用が可能であることが示唆された．

maintenance knowledge are required.
As a result, considering feasibility and sustainability,
VR panorama was identified as the most applicabletechnology in Luang Prabang. There are three major
reasons for this selection. First, immersive scene can beexperienced as a virtual tour. This virtual tour is developed
from multiple VR panoramas. Immersion affects
understanding and image sharing of the townscapechanges. Second, VR panorama requires less knowledge
and training. Since VR panorama can be produced bydigital single-lens reflex (SLR) camera which is used by
DPL staff members daily, it takes less time to mastercreating skills. If producing VR panorama was easy forstaff members, more staff members can join monitoring
work using VR panorama. Third, its equipment for VR
panorama involves relatively low cost compared to 3D
computer graphics. This is important particularly for its
feasibility and sustainability.

1. Introduction
Luang Prabang of Lao P.D.R. was inscribed in the list ofWorld Heritage Site in 1995. Since its inscription, theheritage site has faced dramatic increase of tourists,changing along with rapid tourism development. The
UNESCO/ICOMOS monitoring mission noted that if “theLao traditional heritage continues its steady decline, theTown of Luang Prabang would be heading toward asituation that would justify World Heritage in Danger
Listing” [1].
The Department of World Heritage Luang Prabang(DPL) has a responsibility to monitor and manage
townscape, in Luang Prabang. Tokyo Tech has beencollaborating with DPL in introducing applicable ICT
tools for effective management of heritage site since 2003.
Local needs assessment identified that there are needs tointroduce townscape visualization technology formonitoring and to establish a townscape monitoringprocedure from a long-term viewpoint.
Responding to the needs assessment, this researchaims to introduce and evaluate applicable and sustainable
townscape visualization technology in Luang Prabang. It
also aims to establish a townscape monitoring procedureusing selected townscape visualization technology.

3. Overview of research
Fig. 1 shows the overview of this research, which consistsof five steps.
First, survey on current townscape monitoring method
was conducted to clarify the monitoring issues. Interviews
were conducted at Authorization Unit, Urban Planning
Unit as well as with local ICT team. In addition, the author
observed fieldwork of Authorization Unit and Urban
Planning Unit.
Second, Street-View prototype which is one kind of
virtual tour composed by multiple VR panoramas wasintroduced. This step was composed of four activities: 1)
selection of pilot site; 2) comparative analysis fortechnology of VR panorama; 3) training for creation ofStreet-View; and 4) development of the prototype.
Third, the townscape monitoring procedure using theprototype was developed. To establish the effective
townscape monitoring procedure, it is necessary to sharethe important townscape elements to preserve uniquetownscape of Luang Prabang among DPL staff members.
Therefore, important townscape elements were extractedusing the prototype. Extracted townscape elements wereused to lay out indicators for monitoring.
Forth, the case trials and the interviews wereconducted to evaluate the prototype as monitoring tool.
Case trial is one of evaluation method to identify theadvantages and issues of the produced Street-View
prototype. Participants were asked to perform the tasks

2. Selection of townscape visualization technology
Based on a field survey on existing technologies in DPL,
comparative analysis on applicable technologies was
conducted between Virtual Reality (VR) panorama andtwo types of 3D computer graphics, namely 3D modelingand 3D measurement.
VR panorama is panoramic images providing arealistic visualization to all angles from static viewpoints.
It establishes a virtual scene through real photos. It candisplay spherical panoramas format, which refers to 360°in the horizontal direction and 180° in the verticaldirection [2]. This technology is becoming quite popular
by Google Street View [3].
3D modeling is 3D models created by computer
graphics in virtual reality environment. Buildings andexist urban space can be visualized and stored in acomputer. Townscape simulation is available with featureof moving view point and editing 3D model [4].
3D measurement is 3D models created by laser range
sensor such as air-bone laser-profiler or laser range sensor[5] [6]. It is possible to create precise 3D models and large
quantities at one time. However, equipment cost and
73





1. Current situation survey
Interview with chiefso
ICT teamoAuthorization Unito
Urban Planning Unit
Observe fieldworksoAuthorization unitoUrban Planning unit

Cross-linked
VR Panorama

↓






Regular interval

2. Development of Street-View prototype
Select pilot site
Comparative analyze for technology of VR
panorama
Train local ICT team how to create Street-View
Develop Street-View prototype

Figure 2 Concept of Street-View
Source: created by author, 2012↓

3. Development of townscape monitoring procedureExtract townscape elements
Discuss with Deputy Director and Authorization
Unit Chief
Develop “Townscape monitoring indicators”
Develop “Indicator sheet”↓



4. Evaluation
Case trials and interviews↓

5. Discussion
Discuss with DPL staffs
Discuss and propose townscape monitoring
methodFigure 3 Shooting locations of the Street-View prototype
Source: Heritage Preservation and Development Master Plan,
2001, p.12

Conclusion
Figure 1 Overview of research
Source: created by author, 2012

Map

related to townscape monitoring with the prototype andthe author observed its process.
Fifth, based on the process of the prototype
development and evaluation results, townscape monitoringprocedure was discussed.

Hotspot

Panel buttons

4. Analysis on current townscape monitoring
methodThe issues of current townscape monitoring method in
DPL could be summarized in the following four points.
First, DPL does not have comprehensive townscapemonitoring method. Each unit conducts different fieldsurvey to monitor townscape independently. Second, thetownscape elements required to preserve the uniquetownscape of Luang Prabang are not shared among DPL
staff members. Points of focus are different for each unit
and not shared between DPL staff members. Third, there
are differences in the level of understanding of theheritage preservation master plan (PSMV). The PSMV is adocument that provides comprehensive guideline toregulatebuilding
constructionamongstaffs.
Understanding of the PSMV content is vital formonitoring. Forth, there is lack of staff members. All units
have multiple tasks at one time and all unit chiefs
complained about lack of staff members. This issue isimportant to be considered to develop effective townscapemonitoring procedure.

Figure 4 Interface of the Street-View prototype
Source: the Street-View prototype, created by local ICT team andauthor, Luang Prabang, 2012

VR panoramas created at a few meters intervals arecross-linked each other (Fig. 2).
The main road in the core heritage zone (1.5 km) was
selected for pilot site, since this area has many types ofarchitectures and plans to improve for better townscape(Fig. 3). A total number of 31 VR panorama photos weretaken at 50 meter intervals, covering 1.5 km of the mainroad.
Development of the prototype consists of three steps:
1) shooting four directions of photos with fish-eye lensand digital SLR camera; 2) stitching by software; and 3)
authoring by software. Hugin was used for stitching [7].
SaladoPlayer, SaladoConverter and SaladoConfigurator
were used for authoring [8] [9] [10]. All software usedwere free open source software. Training on how to create
Street-View was conducted for local DPL staff members.
Before developing the prototype, important functions
were discussed. Showing map to navigate desired VR
panorama was identified as one of the functions needed tomonitor townscape, and thus, the following functions were

5. Development of Street-View prototype
The author and local staff members developed a prototypeof Street-View, which enables users to take virtual tour inorder to examine its usability and sustainability. Multiple

74equipped: 1) control zoom in/out with mouse, panel button
and keyboard; 2) control viewing direction with mouse,panel button and keyboard; 3) select desired spot from
map; and 4) move to next spot with hotspot.
Fig. 4 shows interface of the prototype. Map of the
PSMV was used in the prototype. In this map,preservation level of buildings and regulations of land use
are shown by colors and symbols. These information areimportant for monitoring.

6. Developmentoftownscapemonitoringprocedure
6.1. Creating “Townscape monitoring indicators”
Using Street-View prototype, the important townscapeelements were extracted together with the Deputy Directorand Authorization Unit Chief. The townscape elements are
considered as indicators for townscape monitoring.
First, Authorization Unit Chief identified theimportant townscape elements from every spots byexamining the prototype, following rules and regulations
described in the PSMV. Then, the townscape monitoring
indicators were created through discussions. The“townscape monitoring indicators” provides 12 types oftownscape elements which should be checked whenmonitoring with Street-View. The indicators are classified
into five categories: 1) prescription on buildings andspaces; 2) plantations; 3) appearance of buildings; 4)
parking situation; and 5) service by networks.

Figure 5 Indicator Sheet on spot No. 1
Source: Indicator sheet, created by author, Luang Prabang, 2012

By using the procedures illustrated above, if themonitors encounter the gap between the conditions shownin Street-View and the PSMV, such gaps can be submitted
for discussion at DPL.

7. Evaluation analysis
To evaluate the Street-View prototype as a townscapemonitoring tool, case trials and interviews were conducted.
Further, the townscape monitoring procedure was also
examined through evaluations.
Case trial is an evaluation method to identify theadvantages and points of improvement of the prototype.
Participants were asked to perform the tasks of monitoringwith the prototype and the author observed its process.
Four tasks to check following important indicators wereprepared: 1) prescription of buildings; 2) external aspect;3) parking; and 4) electricity network. In addition,interviews were conducted after case trials to supplementcase trials observation. Five users were selected from each
unit in DPL: two members from Authorization Unit; twofrom Urban Planning Unit; and one from local ICT team.

6.2. Creating “Indicator sheet”
Following identification of townscape monitoring
indicators, the concrete indicator sheets were created forevery spots in the Street-View prototype.
Fig. 5 shows an example of spot No. 1. This spot is
the biggest traffic intersection and 13 kinds of indicators
were identified. This sheet has equirectangular image ofthe spot, a list of indicators, a map of the area and dates
that photos were taken. Map in the PSMV was used,following the Street-View prototype. The map shows,preservation level of buildings and regulations of land use
by colors and symbols.

6.3. Townscapemonitoring
indicators and Street-View

procedurewith

7.1. Positive findings of Street-View prototype
Based on the case trial and interview results, four positive
findings of Street-View prototype were identified.
First, user-friendly operation enables users withdifferent experiences and backgrounds to use theStreet-View. Participants were able to understand theprototype’s operation after a brief explanation of the
prototype given before the case trial and accomplishedtheir tasks without difficulty. User-friendly operation isimportant for different people to participate in townscapemonitoring work, especially in circumstances when humanresources are limited. This advantage allows theStreet-View to overcome the problem of a lack of humanresource in DPL.
Second, Street-View makes it possible to sharetownscape information among DPL and contribute to
analyze townscape changes. Street-View can store data ofvisualized townscape information. By comparing thestored data and PSMV, people can evaluate and analyze
the townscape. Furthermore, stored data enables DPL staff

Townscape monitoring procedure using the indicators andStreet-View was established. This procedure has threemajor steps as bellow:
1) Check indicators and regulations
1-.1. Check indicators at the desired spot to monitor
using the “Indicator sheet.”
1-.2. Check where the regulation is described in the
PSMV using the “Townscape monitoring
indicators” sheet.
1-.3. Check regulations referring to the PSMV.
2) Check townscape using Street-View
2-.1. Open the spot using Street-View.
2-.2. Check the situation through the visualized
townscape.
3) Evaluate the townscapeCompare the visualized townscape in Street-View and
the PSMV regulations to evaluate the townscape ofthe selected spot. If there are problems, think about aplan or direction to modify the issue.
75members to formulate a common understanding of
townscape information. In the future, a chronologicalanalysis of townscape changes would be possible byaccumulating data using Street- View.
Third, Street-View can be utilized as acommunication tool for relevant organizations and the
local residents. It was suggested in interviews that theStreet-View is useful to explain the need to preserve sites
with images of good quality and to build a consensus
among relevant organizations and the local residents. The
Street-View’s actual usage as a communication tool should
be investigated in the future.
Forth, Street-View meets the need for townscapemonitoring through its major functions. The major
functions of Street-View are as follows: 1) it can control
viewing direction; 2) it enables to zoom in/out; and 3) it
can provide virtual tours using hotspot links. The case trial
and interviews made it clear that these major functions
work effectively for townscape monitoring.

identified several issues regarding the townscapemonitoring procedure.
First, the indicator sheet should be accompanied with
explanation for the users to fully understand its procedure.
It is important that what and how to be monitored for eachmonitoring spot are clearly shared among staff members.
Therefore, the indicator sheet should contain descriptionsof the indicators at each spot and detailed the monitoringprocedures for those spots. Second, understanding level ofthe PSMV should be promoted. Indicators for monitoring
are based on the rules and regulations identified in PSMV.
Street-View cannot be utilized effectively without solid
knowledge of such rules and regulations. Third, training
on townscape monitoring procedures is necessary.
Participants were given a brief training on how to use thetownscape monitoring indicators, and it was found useful.
For implementing full monitoring of the townscapechanges, extended training for the users would become
vital.

7.2. Points of improvement of Street-View

7.4. Sustainability of Street-View as monitoring tool

Four aspects of Street-View prototype were identified forfurther improvement.
First, blind spots reduce the utility value of theStreet-View because they hide information that users want
to see. There are two factors that cause blind spots. The
first is unexpected obstacles, such as cars and motor bikes,
coming into the image when taking photos. The second is
the fact that the Street-View is unable to capture thebuildings and other objects as they exist between shootingintervals. The former factor can be solved by placing extra
attention on unexpected obstacles, while the latter can besolved by shortening photograph intervals; however, thistakes longer for shooting and stitching.
Second, low resolution images reduce the utility valueof Street-View more than expected. The prototype
includes several low resolution images and it was difficult
to confirm details even with zooming function forparticular objects and places. This is due to human error in
failing to check the resolution of an image when taking
photos. More training on photo taking with specificobjectives for townscape monitoring would help solve thisproblem.
Third, map function of the prototype was founddifficult to check building attributes. The prototype has a
map function with two objectives. The first is to move tothe desired spot for monitoring. The second is to check abuilding’s attributes as defined by the PSMV. The firstobjective functions effectively. However, the second
objective was not achieved because the prototype has asmall map size, preventing the users from checking thedetailed information on the maps. To utilize the mapfunction effectively, it is necessary to improve it with aproper size and better quality resolution.
Forth, despite user-friendly characteristics, interviews
revealed that the prototype does not have a specific user
guide. According to Nielsen [11], a user guide can reducethe burden of memorizing how to use a system from aninterface usability aspect.

Sustainability of Street-View was discussed from the
aspects of required skills and equipment costs. As for therequired skills, without advanced technical background, it
was found easy for staff members to create Street-View aslong as trainings were well-planned and properly
conducted. As for the equipment costs, it does not require
costly equipment to create/operate Street-View. For thesereasons, it can be said that Street-View has a high level ofsustainability in Luang Prabang.

8. Conclusion
This research developed a townscape monitoring tool
using Street-View prototype, which composed by multiple
VR panoramas as a townscape visualization technology.
Further, townscape monitoring procedure was developed.
Evaluation revealed that Street-View can be utilized tomonitor townscape changes and further to share important
information. Several improvements to avoid blind spots
and low resolution of photo were discussed for further
improvement. Street-View could be utilized in the future
for townscape monitoring in Luang Prabang as long as
trainings are well-planned and properly conducted.

References[1]

UNESCO, ICOMOS, “Reactive Monitoring Mission to the Town of Luang
Prabang World Heritage Property Lao People’s Democratic Republic”, 2007
[2] C Deng, et al., “Integration of Web2.0, Panorama Virtual Reality andGeological Information System”, Fourth International Conference on
Computer Sciences and Convergence Information Technology, pp.
1625-1628, 2009[3] Google Maps Street View, http://google.com/streetview/. (accessed on Oct.
21, 2012)[4] K Ono, et. al., “3DCG Reconstitution and Virtual Reality of UNESCO World
Heritage in Danger: the Citadel of Bam”, Progress in Informatics, No. 5, pp.
99-136, 2008
[5] K Yano, et. al., “Virtual Kyoto: 4DGIS Comprising Spatial and Temporal
Dimensions”, Journal of Geography, 117(2), pp. 464-478, 2008
[6] K Ikeuchi, et. al, “Flying Laser Range Sensor for Large-Scale Site-Modelingand Its Applications in Bayon Digital Archival Project”, International Journalof Computer Vision, 78, 2-3, pp. 207-222, 2008[7] Hugin–
Panorama
photosnitcher,
Online,Available:
http://hugin.sourceforge.net/ (accessed on Jan. 14, 2013)[8] SaladoPlayer, Online, Available: http://panozona.com/wiki/SaladoPlayer(accessed on Dec. 18, 2012)[9] SaladoConverter,
Online,Available:
http://panozona.com/wiki/SaladoConvertorn (accessed on Dec. 18, 2012)[10] SaladoConfigulator,
Online,Available:
http://panozona.com/wiki/SaladoConfigurator (accessed on Dec. 18, 2012)[11] J Nielsen, “Usability engineering”, Morgan Kaufaman, 1993

7.3. Analysis of townscape monitoring procedure
The monitoring steps illustrated in 6.3 were used in thecase trials. The results of the case trials and interviews76Equilibrium extraction of light rare earth metals with PC-88A as extractant
Student Number: 11M18195 Name: Naoto YOSHIMURA Supervisor: Ryuichi EGASHIRA
PC-88Aを抽出剤とした軽希土類金属の平衡抽出吉村 直人
軽希土類金属としてランタン及びセリウム，抽出剤としてPC-88A，希釈剤としてSolvesso150または灯
油を用い，金属濃度、原料水溶液相中のpHを変化させて液液平衡抽出を測定した。両金属イオンは溶媒相中に抽出され，ランタンに比較してセリウムの抽出率は高く，溶媒抽出によりセリウムとランタンを分離できることを確認した。水溶液相中のpHの増加および抽出溶媒相中の未反応の抽出剤濃度の増加とともに，金属の抽出溶媒相への分配比は増加した。Solvesso150に比較して灯油を溶媒とした場
合，両金属の分配比は大きかったが，分離係数は同程度であった。抽出溶媒相中の未反応抽出剤濃度が高い条件を除いて抽出平衡は報告されている反応式に従った。
effect of extractant concentration on extraction
equilibrium. [2] Mori et al. reported that in the regionof high extractant concentration, the extraction
reaction was quite different from those in the region ofrelatively low extractant concentration. [3]In this study, La and Ce were selected from the RE
metals. La is neighboring element of Ce in periodic
table and well-studied elements in solvent extraction of
RE metals. The extraction equilibrium of La and Ce
with PC-88A were studied under various conditions.

1. Introduction
Rare earth (RE) metals which possess physicallyand chemically specific properties are applied in many
fields of advanced technology such as magnets,
ceramics, electronics, nuclear technology and so on.
[1] It is difficult to separate RE metals, since RE
metals has the similar chemical nature because of same
electric configuration of outermost husks, and all RE
metals generally form trivalent cations.
In recent years, demand of RE metals is increasing
with development of a high-tech industry. However,supply of RE metals depends strongly on limited area,
it is difficult to maintain a stable RE metals supply andprice of RE metals are increasing. On the other hand,
RE metal deposits are very common, but mineraldeposits of RE metals in another area have not been
exploited. To maintain a stable RE metals supply, inthe present, the Japanese government pushed
exploitation of mineral deposits of RE metals in
another area and establishment of enrichment plant of
RE metals is estimeted.
Solvent extraction is presently one of the major
techniques on industrial scale for the separation of RE
metals. 2-ethylhexyl phosphonic acid mono-2ethylhexyl
ester(PC-88A)isanacidicorganophosphorus extractant and has been widely usedin solvent extraction of lanthanides industry for the
separation and purification of the metal ions.
In separation process of RE metals, most of the RE
metals are separated by solvent extraction and only
cerium (Ce) is recovered by precipitation. The
extraction equilibrium of Ce is not fully studied
relative to other RE metals.
A number of fundamental studies of RE solvent
extraction have been carried out under low metal
concentrations and relatively low extractant
concentration. However, practical metal extraction on
a commercial scale is usually conducted under highconcentrations of metal extractant. There are not manystudies on extraction equilibrium analysis of RE metals
in high metal concentration and high extractant
concentration. Nakamura used lanthanum (La)hydroxide, La(OH)3, as a solute and measured that the

2. Experimental
Table 1 shows the experimental conditions ofsolvent extraction of La and Ce by PC-88A. La(NO3)3,
La(OH)3 and Ce(NO3)3 were used as sources of metal
ions. Solvesso150 or kerosene was used as a diluent.
Solvesso150 is one of the petroleum fractions andcontains a high proportion of aromatic hydrocarbons.
Kerosene is one of the petroleum fractions andcontains a high proportion of alkane. To adjust the pH,
solutions of NaOH and HNO3 were added to theextraction system. The initial concentrations of metaland extractant were changed.
Same volumes (20ml) of the organic and aqueous
solution were poured into a 50ml conical flask withscrew cop, and stirred with magnetic stirrer for 24h at
298±3K to attain equilibrium. The two phases werethen separated by a separating funnel and RE metal
concentrations of the aqueous solutions were analyzed
by ICP-AES. The metal complex concentration oforganic solutions was calculated by material balance.
The pH values of the aqueous solutions were measured
by pH meter. In this study, the effect of ionic strengthof the aqueous solutions on the extraction equilibrium
was not considered.
3. Results and Discussion
3.1 Precipitation of solid phase and oxidization of
Ce
Figure 1 shows the photographs of the organic andaqueous solutions in separating funnels. When
La(OH)3 was used with relatively high metal77

( ) ][̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅

Table 1 Experimental condition of solvent extraction of La and
Ce by PC-88A
Aqueous feed phase
Aqueous solution of
La(NO3)3, La(OH)3, Ce(NO3)3
Volume of aqueous feed phaseVaq[m3]
2.0×10-5
Concentration of metal
in aqueous feed phase[M3+ ]0 [kmol･m-3] 2.5×10-4-0.215
Initial pH
pH0[-]
1 – 13(Adjusting by HNO3 or NaOH)
Organic solvent phase PC-88A diluted by Solvesso150 or
kerosene
Volume of organic solvent phase Vorg[m3]2.0×10-5
Concentration of PC-88A
̅̅̅̅̅̅̅̅2 ]0 [kmol･m-3]
in organic solvent phase [(𝑅𝐻)0.06-0.5
Stirring timet [h]24
Temperature
T [K]
298±3

[

(3)

]

Figures 2 and 3 show that the effect of pH on D of
La and Ce, respectively. RE metals were extracted tothe solvent phase and D of Ce was higher than that of
La. Ion radius decreases with an increase of atomic
number in lanthanide, and the metal ion of smaller ion
radius is easy to make a metal complex because ofincrease of charge density in the ion[6]. Then Ce wasmore preferably extracted than La. D of RE metal
increased with pH.
D was larger with kerosene than that with
Solvesso150. D with La(NO3)3 was approximately
equal to D with La(OH)3 except for the case that solid
phase was precipitated. When the system contained
both of Ce and La, D with binary metal system wasapproximately equal to that with single metal system.

concentration, the solid particles were precipitated in
the organic phase to be turbid. [4] When La(NO3)3 orCe(NO3)3 was used, the solid phase didn’t appeared in
all cases. When NaOH solution was used to adjust pH
in cases with Ce(NO3)3, the color of both phasechanged from colorless to yellow. Since the colors of
the solutions containing trivalent and tetravalent Ce arecolorless and yellow, respectively, increasing pH madeCe oxidized from trivalent to tetravalent. To prevent
oxidization of trivalent Ce, NaOH solution was added
to extraction system at contact of solvent phase andaqueous phase. Therefore, it was considered thatquantity of oxidized Ce was small and tetravalent Ce
wasn’t considered.

SoluteM(NO 3 ) 3
M(NO 3 ) 3
M(OH) 3
La(NO 3 ) 3 + Ce(NO 3 ) 3

Diluent
Solvesso150
Kerosene
Solvesso150
Solvesso150) ][(̅̅̅̅̅̅̅̅̅

La(NO3)3

La(OH)3

+]

[

[

]

[

]

Fig. 2 Effect of pH on the distribution ratio of La) ][(̅̅̅̅̅̅̅̅̅
[Fig. 1 Photographs of the organic and aqueous solutions inseparating funnel

[

]

[

]

Fig. 3 Effect of pH on the distribution ratio of Ce

3.2 Distribution ratio
In previous studies, the cation exchange reaction
has been reported by: [5] (M= RE metal)
+
(1)
M 3+
( )2 M 3 ( )3( ) ][ ][̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅) ][][(̅̅̅̅̅̅̅̅̅

+]From Eq. (2) and Eq. (3), D is expressed by:) ][(̅̅̅̅̅̅̅̅̅
[

]

(4)

Figures 4 and 5 show that the effects of pH on Ds of
La and Ce, respectively. D decreased with an increase
in initial metal concentration. With the results in which
the initial extractant concentrations were fixed as
0.5kmol·m3, the unreacted extractant concentration(2)

Distribution ratio, D, is defined by:78

decreased with the initial metal concentration at same
pH value. Accordingly D increased with the unreacted
extractant concentration, as expressed in Eq.(4).
SoluteM(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(OH) 3
La(NO 3 ) 3 + Ce(NO 3 ) 3[M 3+ ] 0 [kmol・m -3 ]2.5×10 -4
0.005
0.027
0.055
0.11
0.215
0.025
0.027(respectively)

Solute=NaNO3 or NaOH
Diluent=Solvesso150) ][(̅̅̅̅̅̅̅̅̅
[]Fig. 6 Effect of pH on the distribution ratio of Na

3.4 Effect of [(̅̅̅̅̅̅̅̅
) ] on) ][(̅̅̅̅̅̅̅̅̅

+]Eq. (2) is expressed as below:̅̅̅̅̅̅̅̅2 ]3(6)[𝐻 + ]3[(𝑅𝐻)
If the extraction reaction should follow the reaction of
Eq. (1),[𝐻 + ]3 is proportional to the third powerof unreacted extractant concentration. Figures 7 and 8
show that the effect of unreacted extractant
concentration on[𝐻 + ]3 of La and Ce,
respectively. Plots in relatively low unreacted
extractant concentration agreed with the line whose
slope was 3, but the plots in high unreacted extractant
concentration were deviated from the line. This
indicated that the extraction reaction should not follow
the reaction of Eq. (1) and the additional reaction
might occur. It has been reported that in the higher
range of extractant concentration, the reaction should
require the dimeric species of extractant more than 3 toform complex in the organic phase[3]. In this study,
the extraction reaction was not fully clarified in highextractant concentration region.

Diluent=Solvesso150[]

Fig. 4 Effect of pH on the distribution ratio of La[

Diluent=Solvesso150) ][(̅̅̅̅̅̅̅̅̅

[]SoluteM(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(NO 3 ) 3
M(OH) 3
La(NO 3 ) 3 + Ce(NO 3 ) 3
M(NO 3 ) 3

Fig. 5 Effect of pH on the distribution ratio of Ce

3.3 Effect of Na on the extraction of La and Ce

PC-88A makes metal complexes with wide variety
of metals. The effect of sodium (Na) on the extractionof La and Ce were investigated. The distribution ratioof sodium, D of Na, is defined by:[̅̅̅̅̅̅̅̅̅̅̅̅̅
( )]
[

]

[M 3+ ] 0 [kmol・m -3 ]2.5×10 -4
0.005
0.027
0.055
0.11
0.215
0.025
0.027(respectively)
0.055[(RH) 2 ] 0 [kmol・m -3 ]
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.06, 0.08, 0.1, 0.3(5)

Figure 6 shows that the effect of pH on D of Na.
Sodium formed metal complexes with PC-88A in the
pH range more than 5[7]. The extraction of La and Ce
were measured in the pH range from 1 to 2.5. D of Na
is very small in the pH range, and the effects of Na on
the extraction of La and Ce might to be small.

Diluent=Solvesso150)2 ] onFig. 7 Effect of [(̅̅̅̅̅̅̅̅

79[𝐻 + ]3 of La

industry corporation. .

D
(RH)2
[]
m-3]
K1

=extraction equilibrium constant[-]<Subscripts>
0=aqueous or organic feed solutionaq=aqueous phaseorg=organic phase
M=Rare earth metal
Na=Sodium
La=Lanthanum
Ce=Cerium<Superscripts>=organic phase species̅̅̅̅Diluent=Solvesso150)2 ] onFig. 8 Effect of [(̅̅̅̅̅̅̅̅

[𝐻 + ]3 of Ce

3.5 Extraction equilibrium constant
Table 2 shows the extraction equilibrium constantsof La and Ce. K1 could be obtained by the intercepts of
the line whose slopes were 3 in Fig. 7 and Fig. 8. K1 of
Ce was larger than that of La. K1 with kerosene waslarger than that of Solvesso150.
Diluent
Solvesso150
Kerosene

Table 2 K1 of La and Ce
La
5.0×10-5
4.7×10-4

References[1] S.Radhika,B.Nagaphani Kumar,M.Lakshmi Kantam,
B Ramachandra Reddy, Liquid-Liquid extraction andseparation possibilities of heavy and light rare-earths
from phosphoric acid solutions with acidicorganophosphorus reagents, Separation and Purification
Technology, 75(2010)295-302[2] Kazuma Nakamura, Effect of operating condition on
solvent extraction of La with PC-88A, Bachelor Thesis,
Tokyo Tech (2012)[3] Yasushige Mori, Hitoshi Ohya, Haruhiko Ono,
Wataru Eguchi ’Extraction equilibrium of Ce(Ⅲ),
Pr(Ⅲ) and Nd(Ⅲ) with acidic organophosphorus
extractants’ Journal of Chemical Engineering of Japan
Vol.21 No.1 (1988) 86-91[4] Yoshiyuki Hirashima, Hideaki Kodera, Jiro
Shiokawa, Extraction of Lanthanoids with Bis(2ethylhexyl) Hydrogenphosphate, The Chemical Societyof Japan 4(1982) 627-631[5] Fu Mian-xin, Sui Zhi-tong, Mikiya Tanaka,
Equilibium analysis of solvent extraction of yttrium andeuropium from hydrochloric acid with P 507, Transactionsof Nonferrous Metals Society of China 21(2011) 20932098[6] KazukoMatsumoto ‘kidoruigensonokagaku’
Asakurasyoten (2008) 53-57[7] Annual report of National Institute of Advanced
Industrial Science and Technology (2008) 557-558

Ce
4.0×10-4
3.5×10-3

3.6 Separation Factor

Separation Factor,, is defined by:(7)

is calculated
Table 3 shows the separation factor.
by using K1 of La and Ce.
with Solvesso150 was
approximately equal to that with kerosene.
Diluent
Solvesso150
Kerosene

Nomenclature=separation factor[-]=distribution ratio[-]=dimeric species of extractant[-]=molarity of the species in the bracket [kmol･Table 3 Separation factor,
Separation factor,
7.94
7.59

4

Conclusion
Rare earth metals were extracted to the solvent
phase and cerium was more preferable extracted thanlanthanum. The distribution ratio increased with pH
and unreacted extract concentration.
Effect of difference of diluent on the distribution
ratio was observed, but effect of difference of diluent
on the separation factor was not observed.
Effect of difference of anion ion of solute on the
distribution ratio was not observed.
In the distribution ratio of both rare earth metals,
the distribution ratio with binary metal system wasapproximately equal to distribution ratio with single
metal system.
The extraction equilibrium was followed thereaction reported in previous studies except in highextractant concentration.
Acknowledgement
PC-88A was supplied by daihachi chemical

80

Optimal Design and Control of a Buck Converter Used for Energy Harvesting
Student Number:11M18203

Name: Jiawei WANG

Supervisor : Kunio TAKAHASHI

エネルギーハーベスティング用降圧コンバータの最適な設計及び制御方法
王佳偉

エネルギーハーベスティングには、エネルギー効率の観点からキャパシタが蓄電デバイスとして検討されている。キャパシタを電源として使用する場合、一定電圧を供給するためには降圧コンバータ―が必要である。本論文では、線形近似回路を用いて降圧コンバータの電流挙動、効率について解析し、回路と制御パラメータの決め方を示した。理論的な検討を基づいて、
キャパシタに蓄えた電力で照明用 LED の点灯する検証実験を行った。

1 Introduction
Recently, Energy Harvesting has been widely
noticed in the world. Energy Harvesting is thetechnology of accumulating and storing someenergy which is not used surrounding us for later
use. In our lab, the energy which is too small to be
used directly is defined as tiny electric energy.
And in order to charge the tiny electric energy
into the capacitor efficiently, how to design andcontrol a boost converter has been studied [1],[2].
When a capacitor is used as power source, abuck converter is necessary. In this case, unlike
conventional buck converter, the output voltage isconstant and the input voltage is variable. There
are also some studies about buck converter withvariable input [3], [4]. But in their studies, energy
efficiency is not their main purpose. In the energy
harvesting, energy efficiency is very important.
In this paper, how to design and control a buckconverter when the capacitor is used as a powersource is studied. In section 2, a model circuit isused to analyze current behavior and the energy
efficiency for the buck converter. In section 3, amethod of determining the circuit and controllingparameters is introduced. In section 4,
experiment results are shown and in section 5
conclusions are presented.

Figure 1 Buck converter and equivalent circuit
Buck converter consists of three components:
FET, diode, inductor. The FET is controlled by
PWM regulation, and T is the switching period.
Duty ratio 𝑑 = 𝑇on⁄(𝑇on + 𝑇off ) = 𝑇on⁄𝑇 , where

𝑇on is the time for which the FET is on, and𝑇off is the time for which the FET is off. So thecircuit’s current behavior can be analyzed byconsidering two time intervals, 𝑇on and 𝑇off .
The assumptions made for the analysis is:①

The capacitance is large enough, and thevoltage of the capacitor can be regarded as
constant in one switching period, T.

②

Diode’s forward voltage can be considered
as 𝑣f = 𝑉D + 𝑅D 𝑖③

Load has no imaginary part of impedance.
(In the case of LED, 𝑣f = 𝑉R + 𝑅𝑖 )According to load, the output current and max

2 Theoretical analysis of buck converter

forward current can be considered as load

In the design of buck converter, an analytic
solution is useful. Here, an equivalent circuit as
figure1(b) is used to analyze the current behaviorof buck converter.

parameters. And duty ratio and switching period
can be considered as control parameters.

81With the Kirchoff ’s voltage law, we can set up

In this paper, the energy efficiency of theequations as:

buck converter is defined for one switching period𝑉at steady state:on

𝑉R = on 𝑅on +𝜂=
off(𝑉D + 𝑉R ) = off 𝑅off

𝑃on + 𝑃off
𝑃in

Where 𝑃on and 𝑃off is the energy consumption

Where, 𝑅on = 𝑅S + 𝑅L + 𝑅, and 𝑅off = 𝑅D + 𝑅L + 𝑅.

in resistance R when FET is on/off, 𝑃in is theWith the condition of continuous current and theenergy introduced from the capacitor to the buckinitial condition, the solution of equations can beconverter for one switching period. With theobtained.

analytic solution of the output current, energy
efficiency 𝜂 can be calculated. With this solution
and the example specifications as figure 3,
relationship between efficiency and switchingfrequency can be plotted like figure 4.

Figure 2 Output current of buck converter

Figure 3 Example specifications for buckAt the steady state, the peak output current isconverterandL, the average output

current is described as

o

.

=

̃

(

̃

)
( ( ̃

̃̃
L =

(
(

̃̃

̃

)

( ̃

̃̃

̃̃

(

)

0.92

)

)
̃̃

(
)

0.9
V0=10V d=0.3)

0.88
V0=15V d=0.2
V0=20V d=0.15
0.86
50

=

=

V0=5V d=0.6

)

and
o

Load R=10
Output Vout=3V

0.94

Efficiency

described as

𝑇̃

1

(
{∫(

1)
1)

on( ) 𝑑

̃

)(

{(

+ ∫(

1)

) + ( L + )(̃

+ 𝑇̃onoff( ) 𝑑 }̃

200

Figure 4 Relationship between energy
efficiency and switching frequency)

When the output and input voltage of the buckconverter is given, the duty ratio can bẽ 𝑇̃off }determined. So the relationship between energy

At here,efficiency and switching frequency should only bẽ=𝑇̃on =

100
150
Frequency 1/T [KHz]

𝑅on

𝑅off
𝑅on

𝑇̃ =

𝑇on = 𝑑𝑇̃ 𝑇̃off =
=

𝑉

𝑉R
𝑅on

=

𝑅on
𝑅on

considered.

𝑇

𝑇off = (From the figure 4, when input and output isgiven, the energy efficiency will be constant.

𝑑)𝑇̃

3 The method to determine control and(𝑉D + 𝑉R )𝑅offcircuit parameters823-1 Duty ratio’s determination

̃With the solution of current at steady state andtheexamplespecifications,

the

1
{(
̃

∆ =
relationship

With

̃

)(

)} + 𝑑this̃(solution1) + ̃ ( L + )(𝑑) = (𝑑 𝑇)

and

the

examplebetween average output current and control

specifications, the relationship between ripple

parameters can be plotted as figure 5.

current and switching frequency is showed as
100
Load R=21.3
Output Vout=3V

1/T=10KHz
1.5
80

Ripple current I [mA]

Average output current Iout [A]figure 7.

Input voltage V0=20V
Load R=10

2

1/T=40KHz
1/T=80KHz
1/T=100KHz

1

0.5

60

40

V0=7V d=0.43
V0=6V d=0.5

20

0

0.2

0.4

0.6
0.8
Duty ratio d

V0=5V d=0.6

1
V0=4V d=0.75

Figure 5 Relationship between output current

0

100

200
300
Frequency 1/T [KHz]

and control parameters

Figure 7 Relationship between ripple current

From the figure 5, at some switching frequency

and frequency

area, the average output current can be obtained

According to the output ripple, the necessary

only by input voltage and duty ratio. And thisswitching frequency range can be obtained withswitching frequency area is required for buckthis result. In the definition of energy, theconverter. So the duty ratio can be calculated asswitching is not considered. But the relationshipthe following formula:between switching loss and switching frequency𝑑=ois clear [2]. In the switching range calculated by

+ ̃
+ ̃

allowable ripple current, in order to reduce
switching loss, a lower switching frequency is

3-2 Switching frequency’s determination

should be selected.

In this section, how to determine the switching

3-3 Inductor’s choosing

frequency for buck converter is introduced. The
output current and the peak output current of

There are two modes of output current for buckload R is given, the allowable range of ripple canconverter: continuous mode and discontinuous

be determined. As figure 6, The ripple current formode. In this paper, continuous mode is only

buck converter can be defined as ∆ =considered. The critical condition for continuouso.

mode is that the current of inductor is zero( 𝐿 = 0).
When FET, inductor, diode are ideal parts, theenergy loss for them can be neglected. So the
output and input voltage can be calculated as
L =Figure 6 Output and ripple current
With the analytic solution of output current for

(𝑉

𝑉o )

𝑇on =

𝑉o

And

buck converter, the ripple current can be

𝑉o
𝑇on
=
=𝑑
𝑉
𝑇on + 𝑇off

calculated as

83

𝑇off

According to the critical condition, in order tooperating point for LED should be considered.

have the output at continuous mode, the output

For the next step, the condition for using thiscurrent should satisfy the following conditions:linear approximation should be clarified.

≥

𝑉o )

2

𝑇on (or𝑉o5

𝑇off )

Voltage V [V]o(𝑉With the relationship between input and output,

43

Output voltage Vout≥

Output current Iout [A]the critical condition can be calculated as
𝑇

Capacitor's voltage V0 (5V-4V)𝑉
8 o

When input voltage and output current is given,

2
0.01

60

20

60

0.008
0.006
0.004

With this formula, inductor can be determinedconsidering with the limit of switching frequency.

2040
Output current Iout

40
Tme [s]Figure 9 Result of the LED’s lighting experiment

4 Experiment result and discussion

In the modeling of circuit, turn on/off delay time

In the experiment, A capacitor power source forfor FET is very short comparing to the switching

LED lighting is used. With the dynamic input

period, so it’s not considered. But there is an

voltage of capacitor, a constant output current foreffect on the experiment result. For the next step,

LED lighting is obtained.

how does the voltage change at the delay time for
FET should be considered.

5 Conclusion
In this paper, the electric behavior for buckconverter is analyzed with a model circuit. With
the analytic solution, how to settle circuit andcontrol parameters is introduced. At last, acapacitor power source is used for LED lighting
Figure 8 Experimental specifications for

successfully. For the next step, LED’s I-Vexperimentcharacteristic

With the experimental specifications as figure 8,𝐹=ochangeableswitchingfrequency circuit should be considered.

References

the voltage for capacitor is from 5V to 4V, andoutput current

and[1] Keisuke Otome, “Effects of usage conditions onenergy efficiency of boost switching regulator”[2] Masanori Tanaka, “Optimization of circuit andcontrol parameters of a Boost Converter for
Energy Harvesting”.
[3] Marcelo Gradella Villalva , “Dynamic analysisof the input-controlled buck converter fed by aphotovoltaic array”, Revisra Control& Automacao/Vol.19 no.14/Outubro, Novembro e Dezembro
2008[4] M.G.Villalva, “Input-controlled buck converter
for photovoltaic applications: modeling anddesign”, PEMD 2008. 4th IET Conference on,
pp.505-509= 9mA, switching frequency

0KHz, the experiment for LED lighting is

conducted, And the result is obtained as figure 9.
From the result of the experiment, a constant
output voltage is obtained with a dynamic input
voltage. And the output voltage is consisted withthe theoretical value. But the output current isdifferent from the theoretical value. At here,
LED’s voltage is also considered with a linear
approximation as diode. in the case of LED, inorder to use this linear approximation, the84Preparation of acidic activated carbon from Bagasse Fly AshStudent Number:

11M18210

Name: Zhaoxia GANSupervisor: Hirofumi HINODE

バガスフライアッシュを用いた酸性活性炭の製造
甘 釗霞
本研究では、バガスの燃焼灰（バガスフライアッシュ：BFA）の有効利用を目的とし、吸着剤として広く利用されている活性炭の製造を研究した。BFAに酸処理と熱処理を同時に行うワンステップ処理を施し、酸性活性炭の製造を行った。製造した活性炭の重金属吸着実験を行い、吸着性能について検討した。その結果、製造した活性炭がPb2+およびCd2+に対して吸着容量はそれぞれ30.12mg/gと18.66mg/gであり、吸着剤としての利用が期待できる。
1. Introduction

adsorption capacity towards heavy metals. Here,the potential of using the produced activatedBagasse is a valuable solid fuel to be
combusted

in

steam

boilers.

In

carbon as adsorbent for heavy metals was studied

developing

countries, most of the industries take thisbyapplying

theactivatedcarbontotheadvantage and leave minimal excess of bagasse

adsorption of two model pollutants, Pb2+ and Cd2+.

during normal milling seasons. However, the

2. Experimental
2.1 Preparation of activated carbon from BFA

ashes from the combustion process in the form of
fly ash (BFA) have not yet being commercially
utilized causing disposal problems.

BFA was obtained from PT Madukismo, a

In terms of BFA, the supply is steady as longsugar

companyinYogyakarta

province,

as sugar industries still use bagasse for fuelingIndonesia. The methodology of one step treatment

their steam boiler. A sugar industry emits(acid treatment and thermal treatment) is shown

approximately 5.5 kg of fly ash per metric ton of

in Figure 1. The apparatus of thermal treatment

cane processed in the flue gases from the bagasse

is shown in Figure 2. Before being used for

combustion. In the case of Indonesia with around

activated carbon precursor, the fly ash has been

2.5 million tons of annual production of cane,sieved to obtain particle size from 0.7 to 1.4 mm

13,750 tons of BFA per year is produced

and underwent chemical impregnation using

nationwide [1].

sulfuric

acid

with

certainweightratiosSome researchers already made an attempt toH2SO4:BFA = 1,2,3 or 4 prior to heat treatments

utilize it as adsorbents by direct usage with

between 400 and 600oC. The acid treatment was

minimal pretreatment. It is very rare that BFA isdone at room temperature and then subjected tobeing upgraded to become advanced material

heat treatment by 15℃/min of heating rate in asuch as high porosity activated carbon before

horizontal tubular furnace (ISUZU, EPKR-12K)

being utilized. Previous study

showed that

under continuous nitrogen flow of 150 ml/min.

[1]

BFA can be converted into high surface area

After reaching final temperature, the condition

activated carbon by CO2 and KOH activation. The

was maintained for 1 hour before cooling to room

conversion of BFA into activated carbon withtemperature. After activation, all samples weremuch higher surface area could improve thesubjected to washing by deionized water until

adsorption capacity of the material.

neutral pH.

In this study, BFA was upgraded using H2SO4

The samples were labeled as STxRy for thechemical activation to produce acidic activatedactivated samples. Small letter x indicatescarbons. The use of activated carbon to adsorb

activation temperature in hundreds (℃) while yorganic compounds has been widely known andstates the weight ratio of H2SO4/BFA.

practiced. However, it is also generally known
that activated carbon showed only a minimal85

2.3 Adsorption in model solution
The activated carbon prepared from BFA wasused as an adsorbent in adsorption runs.
Adsorption runs were conducted by 0.05 g ofadsorbent and 50 ml of Pb2+ or Cd2+ aqueous
solution with the concentration of 10-50 mg/l inflask. This concentration range was selected foreasy comparison to results from other studies [6].
The flask was put in a constant temperature(30 ± 1℃) shaker bath with 100 rpm for 12 hours.
Afterreaching

adsorption

equilibrium,themixture was filtered and the filtrate was analyzed
by ICP. Table 1 shows the conditions ofadsorption experiment.
Table 1 Adsorption experimental conditions
Mass of solutions [ml]50
Initial concentration of solutions [mg/l]

Fig.1 Methodology of one step treatment (acidAdsorbent [-]treatment and thermal treatment)

10~50

activated carbon
from BFA

Weight of adsorbent [g]pH [-]

0.05
Pb2+:5.0±0.2
Cd2+:6.0±0.2

Temperature [℃]

30 ± 1 ℃

3. Results and discussion
3.1 Yield of activated carbon in one step
treatment
The yield of activated carbon obtained in one
step treatment (activated carbon/BFA weightratio) was about 0.5.

3.2 Activated carbon characterization
Fig.2 Apparatus of thermal treatment

Table 2 shows the characterization of activatedcarbons. Chemical activated carbon samples show
a general trend of enhancement of porosity by

2.2 CharacterizationThe

samples

texturalproperties

increasing activation temperature and chemical

wereratio. Surface areas of the activated samples,characterized using nitrogen adsorption at 77K

which represent the total porosity, have a positiveby Autosorb 1 from Quantachrome. Surface area
wascalculated

using

BET

method,correlation with Vmic data, but it is not always inwhileline with Vmes. Thus, the total surface area of the

micropore volume (Vmic) has been determinedsamples is mostly determined by the surface area

using DR method. Then, mesopore volume (Vmes)

in micropores range.

was calculated by subtraction of total volume

Table 2 Characteristics of activated carbons(Vtot) with micropore volume (Vmic).
The chemical property analyses were done bymeasuring point of zero charge pHZPC. The
method of determining pHZPC was based on themethod that was proposed by Noh and Schwarz
[2].

86

The acidity of activated carbon was determined

where Ce (mg/L) is the equilibrium concentration

by pHZPC measurement. Table 3 provides theof the adsorbate, qe (mg/g) is the amount adsorbed

results of pH measurement. The pHZPC of all

per unit weight of adsorbent at equilibrium, qmax

samples decreased after modification with H2SO4(mg/g) and KL (m3/mg) are the Langmuir constants

at different thermal temperatures. At the same

related to maximum adsorption capacity and thethermal temperature, the activated carbon withaffinity of binding sites or bonding energy forhigher weight ratio of H2SO4/BFA has lower

adsorption processes, respectively [4].

pHZPC. Lower value of pHZPC means stronger

3.4.1 Adsorption of Pb2+ with different C0

acidity of the sample.

Figure 5 shows the comparison of adsorption
Table 3 The acidity of solid

equilibrium of Pb2+ on several adsorbents withsample

pHZPC

different weight ratio of H2SO4/BFA ratio. Table 4

BFA

8.48

ST5R1

5.64

shows Langmuir constants. All the isotherms of

ST5R2

4.86

ST5R3

4.84

ST5R4

4.59

ST4R1

3.76

ST6R1

5.44

Langmuir model fit the experimental data
(coefficient of determination R2>0.96) meaningthat the adsorption process in this study is basedon monolayer coverage of Pb2+ on the surface ofactivated carbon. The activated carbon samples
prepared with higher weight ratio of H2SO4/BFA
have higher adsorption capacities towards Pb2+.

3.3 Removal ratio r
The removal ratio r was obtained by,

3.4.2 Adsorption of Cd2+ with different C0

V (c 0  c e )r
Vc 0Figure 6 shows the comparison of adsorption
equilibrium of Cd2+ on several adsorbents with

where C0 and Ce are the initial and equilibrium

different weight ratio of H2SO4/BFA ratio. Table 5

liquid phase concentrations. The r of Pb2+ andshows Langmuir constants. All the isotherms of

Cd2+ in aqueous solutions are shown in Figure 3

Langmuir model fit the experimental data

and Figure 4.

(coefficient of determination R2>0.95) meaning

The maximum r of Pb2+ on ST5R4 was aboutthat the adsorption process in this study is based

100%. The maximum r of Cd2+ on activatedon monolayer coverage of Cd2+ on the surface ofcarbon ST5R4 was about 25%. The acidic

activated carbon. The activated carbon samples

activated carbon could adsorb both Pb2+ and Cd2+.

prepared with higher weight ratio of H2SO4/BFA

The difference in the amount adsorbed could be

have higher adsorption capacities towards Cd2+.

attributed to the difference in the size of hydrated
form of each ion, that is, Pb2+ which has bigger
ionic size is less strongly hydrated (smaller1

hydrated form) compared to Cd2+ (bigger hydrated

ST5R1form) [3].
Removal ratior [-]3.4 Adsorption isotherms
Langmuir adsorption isotherm is most widelyused model for the adsorption. According toLangmuir theory, it has been assumed that
adsorption occurs at a specific homogenous site

ST5R2
ST5R3

0.5

ST5R4
ST4R1
ST6R1

within adsorbent, each site is occupied only a0adsorbate molecule, all sites are equivalent and0

there are no interactions between adsorbate

3060Concentration
C0[mg/l]molecules. The non-linear form of Langmuir
isotherm model can be represented byqe 

Fig.3 r of Pb2+ with different C0

qmax KCe
1  KCe87

15
Amount of adsorption q[mg/g-carbon]

1
ST5R1
Removal ratio
r[-]

ST5R2
ST5R3

0.5

ST5R4
ST4R1
ST6R1

0
0

30
Concentration
C0[mg/l]60

Fig.4 r of Cd2+ with different C

0Langmuiradsorption
isotherm

10

ST5R1
ST5R2
ST5R3
ST5R4

5

0
0

30

60

Concentration Ce[mg/l]

Fig.6 Comparison of adsorption equilibrium of
Cd2+ on several adsorbents of different chemical

Table 4 Langmuir constants of Pb2+

weight of H2SO4/BFA ratio

Pb2+

qmax[mg/g]

KL[m3/mg]

ST5R1

10.87

1.32

BFA was successfully converted into activated

ST5R2

13.40

0.05

carbon with yield of about 0.5. The acidity of

ST5R3

19.80

0.03

prepared activated carbons was confirmed by the

ST5R4

30.12

2.27

4. Conclusion

measurement of pHZPC. The porosity of prepared
activated

increasedwithincreasing

activation temperature and weight ratio of30
Amount of adsorption q[mg/g-carbon]

carbonH2SO4/BFA.
Langmuiradsorption
isotherm

20

BFA

activatedadsorption ability towards

carbonPb2+

showedand Cd2+. The

activated carbon samples of higher weight ratio of

ST5R1
ST5R2
ST5R3
ST5R4

H2SO4/BFA showed higher adsorption capacities.
The maximum adsorption capacity of Pb2+ andCd2+ on ST5R4 obtained from linear Langmuirmodel is 30.12 mg/g and 18.66 mg/g.

10

The maximum adsorption capacity of activatedcarbon prepared from BFA in this study iscomparable to other adsorbents (about 5 to 30

0mg/g). Therefore, the activated carbon prepared

025
50
Concentration Ce[mg/l]

from BFA in this study is applicable for theremoval of heavy metal pollutants in the water.

Fig.5 Comparison of adsorption equilibriumof Pb2+ on several adsorbents ofReferences

different chemical weight of H2SO4/BFA ratio[1] Chandra Wahyu Purnomo, Chris Salim, Hirofumi Hinode, Preparation and

Table 5 Langmuir constants of Cd2+

[2]
[3]

Cd2+

qmax[mg/g]

KL[m3/mg]

ST5R1

2.81

0.15

[4]

ST5R2

5.99

0.10

[5]

ST5R3

10.63

0.04

ST5R4

18.66

0.02

[6]

88

characterization of activated carbon from bagasse fly ash, Journal of
Analytical and Applied Pyrolysis, Volume 91, Issue 1, May 2011, Pages
257-262
J.S. Noh, J.A. Schwarz, J. Colloid Interface Sci,130, (1990)
U. Adie Gilbert, I. Unuabonah Emmanuel , A. Adeyemo Adebanjo, G, Adeyemi
Olalere, Biosorptive removal of Pb2+ and Cd2+ onto novel biosorbent: Defatted
Carica papaya seeds, Biomass and bioenergy 35 (2011)
A. Ozer, Removal of Pb( Ⅱ ) ions from aqueous solutions by sulphuric
acid-treated wheat bran, Journal of Hazardous Material 141 (2007)
Bian Jiaxing :“Preparation of solid acid catalysts from Bagasse Fly Ash”,
Tokyo Institute of Technology（2011）
H.Trevino-Cordero ,L.G.Juárez-Aguilar,D.I.Mendoza-Castillo, V.
Hernández-Montoya,A. Bonilla-Petriciolet,M.A. Montes-Morán, Synthesis andadsorption properties of activated carbons from biomass of Prunus domestica
and Jacaranda mimosifolia for the removal of heavy metals and dyesfrom
water Industrial Crops and Products 42 (2013) 315–323

Bioethanol concentration process using solvent extraction
Student Number: 11M18226 Name: Haihao HU Supervisor: Ryuichi EGASHIRA

溶媒抽出を用いたバイオエタノール濃縮プロセス
胡 海昊
エタノール水溶液を原料とし、キシレンおよびアルデヒド（フルフラールおよびベンズアルデヒド）を溶媒として回分平衡抽出を行った。水に比較してエタノールは選択的に溶媒相側に抽出され，エタノールが濃縮されることを確認した。比較的高いエタノールの分離の選択性を有しかつ分配係数の低い溶媒であるキシレンにアルデヒドを混合することにより、若干の選択性の低下のみで分配係数が向上した。また液液抽出と蒸留を組み合わせたプロセスを想定し、エタノール-水系の共沸点よりも低い範囲におけるエタノール濃縮を計算により検討した。製品中エタノール濃度の増加と共に所要エネル
ギーは増加し、また製品中エタノール濃度が高い範囲では蒸留のみに比較して液液抽出および蒸留を組み合せた場合の所要エネルギーは小さかった。

(thermal stability) and rapid phase separation. The
first 2 factors are considered as the most importantcriteria.
Bioethanol is very cheap and common. Therefore,
the solvent should be cheap, common and highly
available. These considerations suggested that thefavorable solvent would be a hydrocarbon. In thecase of the solvent of hydrocarbon, such as,
xylene, the distribution coefficient of ethanol was
low and the separation selectivity to water was
relatively high[1]. Among the xylene isomers,m-xylene was considered to be most favorable
because of the poor commercial potential inindustry and not expensive, so m-xylene wasselected. On the other hand, aldehyde had
relatively high solvency for ethanol. In this study,
we focus on aldehydes of furfural andbenzaldehyde, which are used as an extraction
solvent for refining lube oil and as a raw materialof chemical synthetic substance, respectively. And
the effects of the mixed solvents on the ethanol
concentration were also discussed.

1. Introduction
Bioethanol is considered to be the most promisingfuel of the future since it is obtained fromrenewable sources, and is environmental friendly.
The need of bioethanol is increasing quickly inrecent year. However the conventional processes
tend to be uneconomic because commodity ethanol
is cheap in spite of the great difficulty in theseparation of ethanol and water, because theethanol-water system forms azeotropic mixture at
96 % of ethanol concentration.
The technology of bioethanol concentration has
long been studied. The typical method of
purification is distillation, which requires muchenergy for ethanol recovery and dehydration.
Many ethanol recovery methods have been
proposed to replace the distillation method, such as
membraneseparation[4],adsorption[4] and[5]supercritical fluid extraction , etc. The solvent
extraction technique is regarded as one of theprospective concentration methods.
In this study, batch equilibrium extraction of
ethanol was conducted, and the concentration
process using solvent extraction was simulated
based on the experimental results.

2.2 Experimental
Table 1 shows the experimental conditions forbatch extraction. The specified amounts of the feedand solvent phases were contacted and shaken witheach other in conical flasks with screw cap in
isothermal bath for 24 h at 298 K to equilibrate.
After the equilibration, the raffinate and extract
were separated by a separating funnel. The
respective liquid phases were analyzed by gas
chromatography (GC17A, Shimadzu Ltd.) with a
30m× 0.25mm i.d. capillary column and a flame
ionization detector, in which the column
temperature was maintained at 333K for the initial
5min, and then increased at 5K/min up to 373K. A
Karl Fischer titration (758 KFD Titrino Metrohm

2. Batch Extraction
2.1 Solvent Selection
A large number of organic solvents have been
examined to measure the extraction of ethanol [2].
The properties of water and ethanol are quite
similar,makingsolvent
selection
morecomplicated. Many factors should be considered tochoose favorable solvents for ethanol extraction,such as distribution coefficient of ethanol,
separation selectivity of ethanol over water,
availability, solvent toxicity, chemical stability

89

Ltd.) was used with dehydrated methanol of
HYDRANAL methanol and titration solution of
HYDRANAL composite 5, purchased from
Sigma-Aldrich Ltd., to measure the water
concentration of each solution.

were lower than that in the azeotropic mixture ofethanol-water system.
The ethanol distribution coefficient andseparation selectivity at equilibrium were defined
as follows:
mi=yi/xi
βEtOH,W= mEtOH /mW

Table 1 Experimental conditions for LLE
Feed system Aqueous solution of ethanol(50g)
Furfural[2]where yi and xi are the concentrations ofcomponent i in the organic and aqueous phases atliquid-liquid equilibrium.
Figure 3 shows the relation between the ethanol
distribution coefficient and separation selectivity.
The selectivity decreased with increasing
distribution coefficient in all solvents. The
m-xylene solvent[1][2] showed a low distribution
coefficient, because ethanol has low solubility in
m-xylene solvent. However ethanol could bepartitioned more easily into the m-xylene phasethan the water, so the separation selectivity wasvery high for m-xylene solvent. The solvent
m-xylene-benzaldehyde maintained the separation
selectivity and significantly improved the ethanol
distribution coefficient. However, benzaldehyde iseasily oxidized to benzoic acid, and it is required
to care about extraction operation. Comparing withm-xylene-benzaldehyde mixed solvent, theselectivity with m-xylene-furfural mixed solvent
was in the same range and the distribution
coefficient was higher. Therefore the aldehydes offurfural and benzaldehyde enhanced the ethanol
distribution coefficient. And the distribution
coefficient increased by greater furfural content,
but the heterogeneous region and the ethanol
separation selectivity reduced. The addition of onlya small amount of furfural significantly improved
the distribution coefficient and maintained theseparation selectivity.
However, the favorable solvent for concentration
process should be selected depending on theprocess design and specifications.

m-Xylene

Solvent
systemBenzaldehyde

xF,EtOH
S/F ratioTime
Temperature

m-Xylene, Benzaldehyde(1:1)
m-Xylene, Furfural(1:1,7:3,9:1)
0.1~0.71
24h
298±1K2.3 Results and Discussion
Figure 1 shows the liquid-liquid phase diagraminwater-ethanol-solvent
system.
The
heterogeneous region was wider with the solventof m-xylene than those with the other solvents[1][2].
And it was the smallest in the case of furfuralsolvent, that is to say, furfural dissolved ethanol
most[2].

Fig.1 LLE for water-ethanol-solvent system
The ethanol concentrations in the extract phase on
solvent-free basis were plotted against the feedethanol concentrations in Figure 2. The
concentration of ethanol in the extract phase on
solvent-free basis was higher than the ethanol
concentration in feed for all runs, namely, ethanol
was concentrated by extraction. Although theethanol was concentrated to relatively highconcentration especially in the cases withm-xylene andthe mixed solvents ofm-xylene-furfural, the concentrations of ethanol in
the extract phase based on the solvent-free basis

Fig.2 The ethanol concentrations in the extract
phase on solvent-free basis at various feed ethanol
concentrations.

90

multistage extraction column and contracted withsolvent S. The extract phase E is obtained from the
top of the extraction column and sent into
distillation column 1 to recover solvent. And thedistillate D is sent into the distillation column 2 toconcentrate ethanol to a high level. The raffinate
phase R which comes out at bottom of theextraction column also sent into the distillation
column 2 to recover ethanol.

Fig.3 Relation between ethanol
coefficient and separation selectivity

distribution

Finally the experimental results calculated by
the Non-Random Two Liquid (NRTL) model,
which is an activity coefficient estimation model
can be applied to non-ideal solution.
The NRTL equation and interaction parameters
were defined as follows:

Fig.4 Process flow diagram of ethanol recovery by
combination of extraction and distillation

n=1mxn njGnjl=1mGljxl

3.2 Process calculation conditions
Aspen Hysys simulator (Aspen Japan, Inc.) wasused to simulate extraction process based on theexperimental results, which were calculated by the
Non-Random Two Liquid (NRTL) model. Table 4shows calculation conditions of process. The S/F
ratio was fixed at 0 to1. If the S/F ratio equal 0, it
means that this process consists only of the
distillation column2. The feed temperature was
298K, the operation pressure was one atm, and thepressure drop was zero in all runs.

where αij was the nonrandom parameter, τij
was the interaction parameter. For allcomponents, αij was fixed as 0.3.
Table3 shows the NRTL parameters
obtained by fitting the measured relationshipfor ethanol+water+m-xylene+furfural system.
Calculation result is shown in Figure 1 asdashed line.
Table2 NRTL Parameters (α
i
j
τ
Water
Water
Water
Ethanol
Ethanolm-Xylene

Ethanolm-Xylene
Furfuralm-Xylene
FurfuralFurfural

207.8
1527.2-3565.9
261.3
1119.62849.2

Table4 Calculation conditions of Process
Aqueous solution
Feed system
of ethanol
m-Xylene
Furfural
Solvent system
m-Xylene,Furfural(9:1)
Feed, F
1000 kg/h
xF,EtOH
0.1
S/F Ratio
0~1
Extraction Column Stages
3
Distillation Column 1 Stages
10
Distillation Column 2 Stages
20
xp,EtOH=0.85~0.95
Total Specification
Yp,Eth=0.98
Specification
xp,EtOH=0.6~0.75(Distillation Column 1)
Yp,Eth=0.99
Specification
xp,EtOH=0.85~0.95(Distillation Column 2)
Yp,Eth=0.99

)
τ
284.5
3073.6-2915.4
808.8-355.6456.3

3. Liquid-liquid extraction process
3.1 Process
In this study, the concentration process should befocused to recover ethanol the azeotropic mixtureof ethanol-water system.
The combination of extraction and distillation
was studied to evaluate the recovery of ethanol.
Process flow diagram is shown in Figure 4. In thisprocess, bioethanol feed F is supplied into91

Energy requirements increases with increasing
concentration of ethanol, and it was found that theincrease of energy requirements in the case of
S/F=0 was particularly noticeable. In the range
exceeding 92% of ethanol concentration in
product, the solvent extraction process could
reduce energy requirements significantly, andcould save energy for about 43% to the maximum.

3.3 Results and Discussion
Figure 6 and Figure 7 show the effects of S/Fratio on the energy requirements in different
distillation column and in different solvents,
respectively. The energy requirements indistillation for Process in Figure 6 and Figure 7
were estimated under the same specifications(xp,EtOH=0.92, Yp,EtOH=0.98).
In Figure 6, the calculation results show theincrease in S/F ratio resulted in the increase ofenergy requirements of distillation column1 for allcases. As much as solvents increased, energy
requirement for recover solvent became large. On
the hand, the energy requirements of distillation
column2 decreased with increasing S/F ratio incase of furfural solvent only. In Figure 7, thecalculation results show that furfural required
lower energy requirements than the other solvents.
And comparing with the case of S/F=0(Distillation
column2 only), the required energy with furfural
was also lower, if the S/F ratio was lower than 0.8.

Fig.8 Effects of ethanol concentrations in producton energy requirements
4

Conclusion

Firstly, Ethanol could be concentrated byextraction, and the distribution coefficient of
ethanol could be improved by the addition ofaldehyde, to the solvent of m-xylene, with little
decrease of the selectivity.
Secondly, simulation of the ethanol concentration
process shows the extraction process using furfuralsolvent is required lower energy than distillation
process.
The results above confirmed the feasibility ofbioethanol concentration process by solvent
extraction.
Fig.6 Effects of S/F Ratio on energy requirements
in different distillation column.

Nomenclatures
m: distribution coefficient, yi: mass fraction in
extract, xi: mass fraction in raffinate, β: separation
selectivity
EtOH: ethanol, W: water, Fur: furfural, X: m-xylene,
Ben: Benzaldehyde,<Subscript>0: initial, R: raffinate, E: extract, D:
distillate, P: product, W: bottom,

References[1] Habaki,H.,et.,J.of JPI, vol53,(3),135-143 (2010)[2] Hu.H., Habaki.H., Egashira.R.,SCEJ 43th Autumn
Meeting,J123[3] Daniel R. Arenson, A. Steen Kertes, C. Judson King,
Ind.Eng.Chem. vol 29,607-613(1990)[4] Richare D. Offeman.,et. Separation and Purification
Technology.vol72, 180-185(2010)[5] A.K.Frolkova V.M.Raeva Theoretical Foundations ofChemical Engineering,Vol.44(2010),No.4,545-556[6] Horizoe.H J.of JPI, vol53,(12),31-34 (2007)

Fig.7 Effects of S/F Ratio on total energy
requirements in different solvent.
Figure 8 shows the effects of ethanol
concentration in product on energy requirements.
The calculation of the energy requirements in
Figure 6 was done under same specification( xp,EtOH=0.85~0.95,Yp,EtOH=0.98).

92

Image based real-time vehicle classification for ETC
Student Number: 11M18232

Name: Cong Geng

Supervisor: Yukihiko Yamashita

ETC のための画像に基づくリアルタイム車両認識システム
コウソウ

従来の電波通信に基づく ETC(Electronic Toll Collection 電子料金収受システム) は，高価であるため，開発途上国における普及が進んでいない。本論文では，この問題を解決するために，車両画像情報の統計的学習に基づく ETC を提案する。その一環として，車両を自動分類できる試行ライブラリを構築した。まず，背景差分法で車両を背景から分離する。次に，車種分類に有用な画像情報を輪郭検出により獲得する。そして，学習データで訓練された統計モデルによって入力データの分類結果を出力する。さらに，コンパクトデ
ジタルカメラと市販のパソコンで実験を行い，安いコストで車両分類を実現できることを検証した。最後に，結論および将来の課題を述べる。

1

Introduction

Most staﬀs want spread use of ETC because they
feel the working condition in toll gate is suﬀering
because of exposure to emission gas and physicalexhaustion.

As a part of the Intelligent Transport Systems(ITS), ETC has been widely introduced in over 40
countries. ETC has achieved a considerably highutilization rate in developed countries and brought
about remarkable beneﬁts in both economy and environment.
However, due to the expensive starting cost of facilities and equipments, ETC has a comparatively
slow spreading speed in developing countries. Inspired by the idea of number-plate automatic reading software using video camera, I proposed an image based toll collection system. In my work, a
trial vehicle classiﬁcation library has been built ona normal notebook PC. It shows the possibility ofrealtime vehicle classiﬁcation and the potential of
the image based ETC on such cheap facilities.

2

Related work

2.1

Field work

2.2

Related researchesTraﬃc related research, such as traﬃc surveillance
and number-plate recognition has always been oneof the most focused ﬁelds. Morida et al. and Mohamed et al. have implemented a background subtraction method based on luminance accumulationof pixels [1] [2]. In their work, background is assumed to be the area with comparatively gradualluminance changing from frame to frame , while theforeground is assumed to be the area with drasticchanging. In my work, I adopt the above method
to erase the background area since it has a computational advantage among others such as opticalﬂow based method [3], and block matching method[4].
As for the step of Feature extraction, Chang et al.
implemented a component labeling algorithm [5].
In their work, each component is labeled using a
tracing technique. This method is based on theprinciple that a component is fully determined byits contours, just as a polygon is fully determinedby its vertices. This algorithm requires only one
pass over the image, which is faster than any othertraditional component-labeling algorithms.

To know how is ETC being used in developing
countries, I conducted a questionnaire on 25 tollgate staﬀs and an interview to a toll gate manager in Shandong province, China. According to
the results of the questionnaire and the interview,
the utilization rate of ETC in Shandong province
is still low due to the high cost of existing systems.

93

3

Proposed solution

4.1

Pre-processing

4.1.1

Background subtraction

I(x, y, t) refers to the luminance of pixel P (x, y) in
the frame t of an image sequence. The luminanceof background pixel can be modeled byI(x, y, T ) = I(x, y) + σ(x, y) sin(2πωt) + kζ(1)

in which I(x, y) and σ(x, y)(abbreviated into I andσ) refer to the average luminance and vibration at
P (x, y) up to frame t. ω indicates the frequencyof luminance, the bound ζ depends on the camera
and k is a coeﬃcient of (−1 ≤ k ≤ 1).
Thus, while the luminance I(x, y, t) satisﬁes

Figure 1: Image-recognition based ETC

I − σ − ζ ≤ I(x, y, t) ≤ I + σ + ζ,

The Figure 1 shows the proposed imagerecognition based ETC. The bank or credit cardcompany has the vehicle owner’s deposit information which is bonding to their numberplate. At thetoll station, two video camera is set up to take thephoto: one high-resolution camera is in the front
to take the scene with the numberplate. The otherone is at oﬀ the road to take the side view of a passing vehicle. Both number plate and vehicle classare recognized and sent to the bank, then the toll
fee is charged automatically. A numberplate reading library and a vehicle classiﬁcation library arenecessary to fulﬁll this transaction. Many numberplate reading libraries have been introduced into
practice use, such as the ”Intrada ALPR” libraryby Q-Free in Norway and the N-system by NEC in
Japan. Thus, we can get it from the market. Because vehicle classiﬁcation library is barely available on the market, so we tried to build a trial
library for this task.

P (x, y) is assigned to a background pixel and being
separated from foreground pixels.
As the frames go on, I and σ of the backgroundarea are updated by

40

I = (n − 1)/n × I + 1/n × I,√
σ 0 = (n − 1)/n × σ + 1/n × 2 × (I − I)2

(2)

(3)
(4)

For the foreground area, the average luminance I
is kept and only the vibration σ is updated by0

I = I,(5)√σ 0 = (m − 1)/m × σ + 1/m × 2 × (I − I)2 (6)in which m and n(n ≤ m) refer to the updating
parameters.

4.1.2

Smoothing filter

In the pre-processing, smoothing ﬁlter is applied
to blur the image and leave noise pixels out. In
my work, I applied the Gaussian ﬁlter to the original image to fulﬁll the noise reduction. For a 2-D
image, Gaussian distribution is deﬁned by the following function:

Algorithms

Object recognition using statistical method is athree-stage process which involves pre-processing
and feature extraction and classifying in a video
sequence. Through the pre-processing, the background and noise are removed, and the objects
are localized in the input. Then these objects
are described by a set of meaningful values (feature descriptors) in the feature extraction step. Finally the classiﬁcation requires building a knowledge base of all classes against which an input object is matched.

G(x, y) =1 − x2 +y2 2
e 2α
2πα2

(7)

in which x and y refers to the distance in 2-D coordinates and α indicates the standard deviation.
The closer the distance from the center pixel is, themore weight on the neighboring pixel is. This operation makes luminance of pixels become related
to their neighbors. Therefore, the gap of luminancebetween pixels is reduced and the input image becomes smoother.

94

4.2
4.2.1

3. Weight distribution in an N ×N rectangle partition: First, the entire blob is separated into
N × N rectangles. Then the weight of distribution of the blob is calculated by N × N
rectangle partition.(Fig 4)

Feature extraction
Blob labeling

Blob labeling is to label the connected pixels as anaggregated blob on a binary image. The blob labeling also has two phases: contour detection andcontour tracing.
First, a scanner scans the binary image pixel by
pixel from the top to the bottom, from the left
to the right. When the scanner detects the ﬁrst
foreground pixel, called initial point, the contour
tracing is conducted. In the step of tracing, acontour tracer traces the following connected foreground pixels by a prearranged direction (from 0to 7) shown in Fig 3.

Figure 3: distribute weight of 3×3 partition

4.3

Classifying

4.3.1

Criterion of classification

The criterion of classiﬁcation of a vehicle has agreat variety from country to country, from state tostate. To make the trial library ﬁt the general caseof on the road, I have set up the task to 3-classand 4-class classiﬁcations. The vehicle classiﬁcation chart is shown in Fig 5

Figure 2: Tracing orderWith the previous pixel which is positioned in
number d, the next tracing position is set to d + 2.
For example, since P in Fig 3 follows pixel 3, thenext trace position should be pixel 5. it is not necessary to trace pixel 4 since in previous step, if 4 is aforeground pixel, it should have been traced before
P. With this trick we can run the algorithm fasterthan the others. When the tracer came back to
the initial point, the tracer start from the ﬁrst stepagain, to scan a possible inner contour of this blobor of other blobs and trace them if necessary. By
doing this again and over again, I obtained pixellevel information such as area and perimeter of the
blob.

4.2.2

Figure 4: Vehicle classiﬁcation
4.3.2

Classifier

A number of classiﬁers are examined to deal withmy data. They are NaiveBayes, J48 decision tree,
Multilayer perceptron and Logistic. These classiﬁer are often used in machine learning and patternrecognition.

Feature selecting

After the blob labeling has been done, I have to
extract features appropriate for the task of vehicle
classiﬁcation. As our purpose is to classify vehicles
by their size, I decided to extract following featuresfrom blobs.
1. Number of pixels: indicates the ’size’ of theblob on camera.

5

Experiment

5.1

Implementation

The dataset consists video data of 346 vehicles.
The video was took on the E6 expressway, near to

2. Aspect ratio: calculated by length/height,

95

Trondheim, Norway. The video format is AVI, withsize of 320×240, 30 fps. A Canon compact digital
camera, IXY 910 IS, is used to take the video. The
whole program is implemented on a Macbook PC,
with 2.4GHz Intel Core 2 Duo CPU and 4GB memory. Above hardware cost less than one-thousand
dollar.
The code is implemented with C++ on Eclipse ver.
3.7, an open source integrated development environment provided by IBM. I conducted the above
image-processing using OpenCV ver. 2.2, an open
source library for computer vision mainly provided
by Intel. The training and test of data were accomplished on Weka ver 3-6-8, an open source data
mining tool.

5.2

a diﬃculty on discriminating a minicar and a normal passenger vehicle. In fact, a minicar is distinguished only by the measure of displacement volume. It does not have much diﬀerence with a normal passenger vehicle in their looking.

6

Conclusion&Future work

This trial library has proved that the image-based
vehicle classiﬁcation achieved about 80% accuracy
under simple 3-class and 4-class classiﬁcations. The
aﬀordability gives a strong advantage to the utilization in developing countries. However, the disadvantage of the image based system contains theshortage in accuracy and the need for regular cleaning of lens. Thus, it could be seen as a cheaper
option to fulﬁll non-stop toll gate for developing
countries which have abundant labor to do manual
operations such as re-labeling and regular cleaningof lens.
The future includes: to improve the accuracy of thevehicle classiﬁcation by using more reﬁned featureand classiﬁer, to combine with numberplate reading library and to convince the authorities to takea pilot test.

Results

I separated the video data to a training set with 225
vehicles and a testing set with 121 vehicles. Table
1 shows the accuracy of adaptation on both 3-classand 4-class models trained by diﬀerent classiﬁers.
The Decision tree achieved the best performance

Table 1: Accuracy of trained model
Classiﬁer name3-class 4-class
NaiveBayes
80.2% 76.4%
Decision tree
84.3% 81.0%
Multilayer Perceptron 82.6% 82.6%
Logistic
78.5% 79.3%

References[1] S.Morida, K.Yamazawa. ”Networked Remote
Surveillance System Using Omnidirectional Image Sensors”（D-II), Vol. J88-D-II, pp. 864-875,
May 2005 (in Japanese).

in the vehicle classiﬁcation task. Here, it’s detailed
results are shown in Tables 2 and 3.
According to Table 3, 4-class classiﬁcation has[2] Shahrizat Shaik Mohamed, Nooritawati Md
Tahir, Ramli Adnan ,”Background Modellingand Background Subtraction”, CSPA 2010 , pp
1-6, May 2005.

Table 2: Details of 3-class classiﬁcation
Class Accuracy F-Measure ROC Area
I
84.8%
0.912
0.924
II
72.2%
0.578
0.724
III
100%
0.846
0.982

[3] M.S. Kemouche,”A Gaussian Mixture Based
Optical Flow Modeling for Object Detection”,ICDP2009 3rd International Conference,
pp 1-6, 2009.
[4] Wu-Chih Hu, ”Adaptive Template Block-based
Block Matching for Object Tracking”, ISDA
’08. 8th International Conference, pp 61-64,
Nov 2008.

Table 3: Details of 4-class classiﬁcation
Class Accuracy F-Measure ROC Area
I
46.2%
0.545
0.803
II
88.6%
0.881
0.831
III
83.3%
0.732
0.885
IV
82.6%
0.900
0.994

[5] Fu Chang, Chun-Jen Chen, Chi-Jen Lu. ”ALinear-Time Component-Labeling Algorithm
Using Contour Tracing Technique”, Computer
Vision and Image Understanding vol 93, pp
206-220, 2004.

96

Outdoor Experiments on Human Bio-Meteorology at the Hottest City Tajimi
Using a New Wearable Measurement SystemStudent number: 11M18255

Name: Rui SHISupervisor: Manabu KANDA

人体装着型計測システムを用いた，多治見市における夏季の熱環境・生理評価実験
石蕊

人の動線に沿って連続的に変化する温熱環境とそれによる人体生理への影響を評価する目的で，日本で一番熱い町の１つである岐阜県多治見市において夏季の熱環境・生理評価実験を行った．実験には、気象因子（気温，湿度，風速，長波及び短波放射）と生理因子（表面皮膚温度，深部体温，脈拍，運動量，温熱感）を同時計測できる人体装着型温熱生理計測システムを用いた．都市の街区内の詳細な温熱・生理データの可視化を行い，熱環境と人体生理応答の関係，そして過渡現象における急激な熱環境変化に対する人体生理の応答特性を明らかにした．

1. Introduction

All indices relative to thermal environment were
measured. Here, wind velocity, short & long wave
radiation were measured using three compact globe
thermometers with different properties [3]. Those
three variables are identified from the heat balance
equations of globe thermometers. The sensors forambient temperature and relative humidity were
installed in the radiation shield to reduce the radiation
effect. Details are shown in Figure 1(1).

In recent years, the number of people suffering fromheat stroke has increased due to extreme hot weather
caused by urban heat island. To prevent heat strokeand evaluate its risk, the detailed understanding ofthermal environment in human living spaces and how
it’s effect to human health are needed.
Knowledge about the relationship between thermal
environment and health has been obtained but mostly
from laboratory experiments [1]. On the other hand,outdoor experiments [2] focusing on the thermal
environment and thermal sensation are plenty, but themeasurement of physiological factors are still very
limited. Comparing with laboratory, actual urban
micro climate, such as air temperature, radiation, windspeed and etc. are largely fluctuating. The evaluationof its impact on human physiology is important.

2. 2 Physiological part
Subject’s physiological responses to thermal
environment were also measured. Average skintemperature was estimated from Hardy& Dubois’s 7
points method [4]. The other sensor for pulse rate,
body motion, and thermal sensation can be seen in
Figure 1(2).

However, it is not easy to measure thermal
environment in urban areas with conventional
meteorological sensors due to their heavy and bulky
characteristics. To overcome the problem, a compact
and portable measurement system (Figure 1) was
developed, which can measure both meteorological(air temperature, humidity, long and short wave
radiation, wind velocity) and physiological (skintemperature, tympanic (core) temperature, pulsation,
rate of acceleration, thermal sensation) parameters.
Using this measurement system, two observations
along subjects’ pathways were conducted in thesummer of 2011 and 2012, at Tajimi City, Gifu
Prefecture, which is one of the hottest cities in Japan.

3. Observation Outline
3.1 2011 year’s observation
The first observation was focused on the thermal
environment in the urban living spaces. 26 subjects
wore the measurement system while walking aroundthe parking lot, commercial area, highly-reflective
painted area, biotope area, and green spots (route in
Figure 2), from August 22-24, 2011. Threeobservations (morning 8-10, noon 12:30-14:30,
evening 16-18) were held each day. The examinees
were classified three groups according age bracket;
30-40's subjects conducted the experiment on first day,20’s on second day, and 50-70's on third day.
3.2 2012 year’s observation
The second observation was focused on the transientphenomena, e.g., abrupt changes of environments (hotto cool) and changes of exercise states (walking torest). 4 subjects held the observation followed theprocedures shown in the Figure 3, on September 5-6,
2012.

2. Wearable Measurement System
The compact wearable measurement system, which
can measure both meteorological and physiologicalindices (Table 1), will be explained in this section.
2.1 Meteorological part97

Figure 1. The compact measurement system.
Table 1. Measurement items used in the observation
Meteorological Part
Variable

Instrumentation

Air temperature

K type,(Ta)

Thermocouple

Relative humidity

SHT75,(RH)

Sensirion

Wind velocity
Short wave radiation(S)Global anemoradiometerLong wave radiation (L)Physiological Part
Accuracy

Variable

Instrumentation

Skin temperature

Thermochron, SL type,(Tskin)KN Laboratories

Core temperature

MC-510, Omron (2011)(Tcore)LT-200, Gram (2012)

0.32 𝑚𝑠 −1

Pluse rate (PR)

Handmade

N/A

21.8 𝑊𝑚−2

Body motion

KXM52-1050，
Kionixinc

N/A

10.9 𝑊𝑚−2

Thermal sensation

Handmade

N/A±0.2 K±1.8 %

Accuracy±0.7 K±0.1 K

Figure 3. Detailed observation procedures in 2012.

4. Results and Discussion
4.1 Thermal environmental & physiological map
Thedetailed
thermalenvironmental
andphysiological maps were visualized along subjects’
pathways. Figure 4[a] shows that the urban canions
have higher temperature about 3 ℃ than the nearest

Figure 2. Observational route map

98

-0.3
-1.1

173

-1.9

86

130

43
0

35.7

49.8

35.4

47.3

35.1

44.8
42.2

34.8
34.5

39.7

34.2

37.1
34.6

33.9

[ ]

934

Japan Standard Time

1004

RP
MET

33.6

Figure 4. Thermal environment map on the morning ofthAugust 24 , [a]Ta anomaly from Tajimi city AMeDAS,[b] short wave radition, [c]SET*, [d]subject’s Tskin

10
8

METS

6
80

4
2
50
36.5

0
Tskin
Tear

36

36.7

35
34.5

37.1
36.9

35.5

33.4℃

1025

36.0

[d]

904

24.4 ℃

32.7 ℃

1040
1055
Japan Standard Time

27.5 ℃

Tear [Degree C]

216

52.4

[ ]

Body motion[ms-2]

0.5

Pulse Rate [BPM]

259

54.9

[c]

0.1

110

1.2

[Wm-2]

0.2

Figure 5. One of time series chart of 2011’s observation

303

-3.4

0.3

834

2.0

-2.7

[K]

1

0

346

[b]

2

0

Tskin [Degree C]

2.8

[a]

Wind Speed[m s-1]AMeDAS point (Automated Meteorological Data
Acquisition System) of JMA (Japan Meteorological
Agency); only biotope and green area (white circle
area) are cooler than AMeDAS data. Though theobservational area was not too large, just about 700
square meters, data showed spatially heterogeneity.
This locality may cause the difficulty of evaluation of
micro climate using AMeDAS data. From Figure 4[b],high-temperature area (red circle area) corresponded
well with short wave radiation. Figure 4[c] shows
SET* [5], which is an index of heat stress, [d] shows
subject’s skin temperture(Tskin). They are correlating
well each other. The relation between these two will
be discussed later.

36.5

1110

Figure 6. A part of ID3’s thermal physiology time series
chart of 2012. Enclosure pinky area means outdoor.

2) Time constant of human skin temperature
Tskin fell immediately by the abrupt change ofenvironment (hot to cold), and then gradually
approached constant. In order to characterize subject’s
responses for the abrupt change, time constant wasestimated by following equation:
(

)

(

)

( )

Where T0 is initial value, T0+a/b is the amplitude of
the change in Tskin, -b/a indicates the steady value.
is a time constant, which gives the time required toreach a 63% responses for T0+a/b. Linear
approximation was used to obtain a and b. The
average time constant of Tskin is 2.57 [min], for33.4 ℃ outdoor to 24.5 ℃ indoor. This value iscomparable as Nagano’s experiment (2.39 [min]) [6].
Time constant of Tskin is influenced by age andsubjects’ sweat rate (Figure is not shown).
3) Time delay of core temperature
When the environment abruptly changed, a timedelay was found in subjects’ core temperatures (Figure6). The average time delay is 17.4 [sec], when abrupt
environment changed from 33.4 ℃ to 24.5 ℃ .
Furthermore, the time delay became longer when thechange of subjects’ motion accompanied by thechange of environment. For the case into 24.5 ℃
indoor is 39.9 [sec], while into 28.0℃ indoor morethan 167.4 [sec].

4.2 Physiology during transient phenomena
1) Analysis of time series data
Here we focused on the relation between windvelocity and body motion in the first observation.
Figure 5 shows that wind velocity has the similar
behavior with body motion. Such cases wereconfirmed in 20 out of 26 subjects. Wind velocity inthe urban canyon was generally weak, and the subjects’
movements could increase relative wind velocity.
From the second observation: when the environment
abruptly changed (from outdoor to air-conditional
indoor), in response to the cold environment, a drop in
Tskin, Tcore and pulse rate can be seen from Figure 6.
This decrease is caused by physiologicalvasoconstriction. Furthermore subject’s metabolism isrelatively constant for the environments change, which
can be seen by the data of METS from 10:25 to 10:50.

99

300

300

38
36

200
34

100

32

Male

Female

0

34

38

42

46

Hourly SW[g m -2 h-1]

Hourly SW[g m-2 h-1]

4.3 Thermal effects to the human physiology
Here the relationship between thermal environmentand human physiology was focused. Figure 7 shows
the relation between hourly sweat rate and SET*. Herehourly sweat rate means sweating per unit surface area
per unit observation time. Figure 8 shows SET* has an
influence on average Tskin. Hourly sweat rate andTskin corresponds with SET*, however the plots havedispersion. Factors causing the dispersion are thedifferences of gender and BMI (body mass index).
First, considering the difference of gender, maleshows a tendency to a large hourly sweat rate thanfemale. Furthermore, the Tskin of female are higher
than the male. It can be considered that because of low
hourly sweat rate of female, efficient heat dissipationby the heat of vaporization is difficult, as result
leading to a high Tskin for female.
Second, the result of BMI differences goes well with
common intuition that obesity subjects are more
sweating than others. Due to the fat, a heat-insulating
layer formed between capillary and the atmosphere,
sensible heat dissipation is reduced. As in the case ofgender, sweatier obese subjects have confirmed asignificant decrease in Tskin.
Finally, significant effect to age difference was notconfirmed by this observation. One possible reason isthat 50s or older have a regular exercise habit.

References

R² = 0.5912

R² = 0.7161

200

R² = 0.7697

100

30

50

and conductive heat loss from their bodies was found.
Within urban canyons, since wind velocity was low,
subjects’ movements enhanced the convective heatexchange.
3) For abrupt changes of environments from 33.4℃
outside to 24.5℃ indoor, the average time constant of
human skin temperature is 2.57 minutes, which is
influenced by age and subjects’ sweat rate.
4) A time delay was found in subjects’ coretemperatures when the environment abruptly changed,
when temperature gap is smaller, the time delay was
found to be longer. Furthermore, the time delay was
longer when abrupt environment change isaccompanied by changes in the subjects’ motion.
5) Sweat rate had a correlation with the thermal load
(SET*). Some of deviations for their relation wereexplainable from the gender and BMI differences;male subjects generally sweated more than female
ones; overweight persons sweated more than normal
and underweight subjects. The subject with larger
amount of sweating showed lower skin temperature
due to the evaporative cooling.

ST
Over weight
OW
Under weightStandard weight
UW

0
30

34 40 38

SET* [degree C]

42 50 46

60
50

SET* [degree C]

Figure 7. Relation between hourly sweat SET*[Degree
rate and C]SET*.
38

36

Tskin [Degree C]

Tskin[Degree C]

38
R² = 0.7122

34

R² = 0.7489

32

Female
male

30
30

40

50

36

R² = 0.5912
R² = 0.7161

34

R² = 0.7697

32

Over weight
Under weightStandard weight

30

60

30

40

50

[4] Hardy J. D., DuBois E. F.: The Technique of
Measuring Radiation and Convection, Journal of
Nutrition, Vol.15, pp.461-475. 1938.

60

SET*[Degree C]

SET*[Degree C]

Figure 8. Relation between Tskin and SET*.

5.

[1] Niimi Y., Matsukawa T., Sugiyama Y.,
Shamsuzzaman A.S.M., Ito H., Sobue G., ManoT.: Effect of Heat Stress on Muscle
Sympathetic Nerve Activity in Humans,
Journal of the Autonomic Nervous System, pp.
61-67, 1997.
[2] Kanda M., Kinouchi T., Kobayashi H.:
Application of New Outdoor Thermal Sensation
Index to Evaluation of Thermal Environment
Around River, Annual Journal of HydraulicEngineering, Vol.40, pp.237-242, 1996. (InJapanese)[3] Nakayoshi M., Shi R., Kanda M.: Developmentof Radio-anemometer Using Three-compact
Globe Thermometers, Annual Journal of
Hydraulic Engineering, Vol.55, pp.349-354, 2011.
(In Japanese)[5] Gagge, A. P.: An Effective temperature scale
based on a simple model of human physiologicalregulatory response, ASHRAE Transactions
77(1), pp. 247-262, 1971.
[6] Nagano K., Takaki A., Hirakawa M., Tochihara
Y.: Effects of ambient temperature steps onthermal comfort requirements, International
Journal of Biometeorology, Vol. 50 (1), pp.33-9,
2005.

Conclusion

The conclusions of this study are summarized asfollows:
1) The detailed thermal environmental andphysiological maps were visualized along subjects’
pathways, which can detect localized hot and coolspots and their impacts for human health.
2) The close relation between subjects’ movements
100Distributed Video Coding By Selective Line Pruning andmulti-frame based Interpolation
Student Number: 11M18261

Name: Phan Tuan Tai Supervisor: Yukihiko Yamashita

選択的なライン抽出とマルチフレーム補間を利用した Distributed Video Coding
ファン トゥアン タイ
Distributed Video Coding（DVC）は, 符号化器では予測などを行わず, 計算量が少ない手法で画像を符号化し, 復号器では誤り訂正の技術を用いて復号器で予測した画像を補正するという特徴を持っている。そこで本論文では, 符号化器において選択的ライン抽出による空間的間引きを行い,復号器においてマルチフレーム補間により元の大きさの画像に復元することによって,DVC の符号化効率を向上することを提案する。さらに, 提案手法を実装し, 計算機実験によりその有効性を
確認する。

1

Introduction

and their interpolated ones. This method outperforms
the conventional DVC for video sequences containing alarge number of motions. However, this scheme uses the
single-frame based interpolation to reconstruct dropped
frames. Therefore, artifacts and flickering eﬀects arevisible in the interpolated frame because the temporal correlation between frames of video sequences are
ignored.
In this paper, I propose an improved SDP-DVC using
the multi-frame based interpolation which is based on
the high-order new edge-directed interpolation (NEDI).
This scheme uses not only the pixels of current frames
but also available pixels in the previous key frame forthe interpolation process at the decoder. I utilized motion vectors obtained by the motion estimation for deciding reference pixels in the key frame. This scheme
enables to generate interpolated pixels which are taking
into account the temporal correlation between frames.
This work is regarded as an evolution of work in [7].
The rest of this paper is presented as follows. Section 2 reviews SLP. In Section 3, my proposed DVC byselective line pruning and multi-frame based interpolation is presented. Experimental results are shown in
Section 4. Finally, Section 5 concludes the paper.

Distributed source coding (DSC) is based on two results of information theory: the theorems by Slepianand Wolf [1] and by Wyner and Ziv [2] for lossless andlossy codings of correlated source, respectively. Even
though, DVC algorithms do not outperform conventional video coding schemes in rate-distortion performance at present, DVC is a promising tool for creating
reversed complexity codecs for power-constrained devices. Currently, in conventional digital video coding
standards, the encoder typically has high complexity
mainly due to motion estimation for finding the bestinter picture prediction. On the other hand, DVC enables to reversed complexity codecs, i.e., a simple encoder and a complex decoder.
The common application of DVC is transformdomain Wyner-Ziv (TDWZ) codec [3], where key
frames are encoded by the intra mode and Wyner-Ziv(WZ) frames (non-key frames) are inserted between key
frames. The decoder uses the key frames for motion
estimation to create an estimation frame of the WZ
frames. Then WZ frames are corrected by error correcting codecs with using a low-density parity-check(LDPC) code. However, the decoder would require alarge amount of computation due to motion estimation.
Moreover, a mixed resolution framework was applied
to DVC [4] (MR-DVC), in order to adapt decoder complexity. In MR-DVC, WZ frames are downsampled before encoding. Key frames, which are used for estimating the missing information in WZ frames, are compressed at full resolution. At the decoder, key frames
and WZ frames are decoded and WZ frames are interpolated back to their original size. Then, TDWZ
decoder further corrects WZ frames by error correcting codecs. The MR-DVC is based on super-resolution
framework thus it requires a large amount of parity bits
to correct high-frequency region in WZ frames.
In my previous work, I proposed a video coding
scheme called selective data pruning based DVC (SDPDVC) [7] to improve SDP based video coding performance by using an error-correcting system of DVC. In
particular, I applied TDWZ coding for residual signals
which are diﬀerences between the pruned lines by SLP

2

Selective Line Pruning andmulti-frame based NEDI

2.1

Selective Line Pruning

SLP is a simple line-based image downsampling
method. It is described as follows: the target columns
to be pruned are somehow found in an image, and thenthey are pruned to reduce the width of the image. The
original paper [6] uses a metric based on the meansquare error to determine the columns to be pruned.

2.2

Multi-frame based NEDI

The NEDI method is based on the idea that the geometric duality between the low-resolution covarianceand the high-resolution covariance is useful for interpolating a high-resolution image from its lower resolution

101

counterpart. This method is originally used for interpolating an image to double the sizes of rows and columns.
However, the SLP usually changes aspect ratio of theimage. If some columns are pruned, only the horizontal resolution becomes low. To address this issue, thehigh-order NEDI was proposed to utilize the geometricduality after SLP.
In order to improve the quality of the interpolated
image, I try to use the multi-frame based interpolation
instead of the single-frame based interpolation in theinterpolation process at the decoder. This method can
reduce the spatial artifacts since the temporal correlation between frames in the video sequence are alsoutilized. Not only the quality of the interpolated image is improved, but also I can reduce the bits in theerror correction process for improving video coding performance of my scheme. In this paper, I use NEDI-9
with motion estimation (ME) and motion compensation (MC) to gain the best quality of the interpolated
image.
NEDI-9 is an extension of NEDI-6 for referencing
more pixels between frames in video sequences. LetP̂h6 (t) be the frame which is interpolated from the lowresolution frame I(t) by using NEDI-6. Assume thatthe previous interpolated frame is I(t − 1). In NEDI9, ME and MC are applied to align the current blockof pixels in P̂h6 (t) to its matched block in I(t − 1).
Then, six neighboring pixels in P̂h6 (t) and three pixels
in the matched block of I(t − 1) are used to interpolate
one high-resolution pixel in the current frame. Theinterpolated pixel is obtained by taking the weighted
average:P̂h9 (t, i, j +

1
)
2

=

1
1
∑
∑

Figure 1: Model parameters of 9th order edgedirected interpolation (NEDI-9).

terpolation process at the decoder. The architecture of
new SLP-MFI-DVC is shown in Fig. 2. It is based on
the original MR-DVC system [4], but diﬀerent from theoriginal SDP-DVC, where the motion estimation andmotion compensation are performed at the decoder.

3.1

Firstly, all frames are resized by SLP and the resizedframes are encoded with H.264/AVC. For all frames
within a group of pictures (GOP), the downsampled
positions by SLP are the same. In the next step, resized key frames are decoded by a local decoder andinterpolated back to their original size by using NEDI6. Then, the full resolution residues between the interpolated key frames and the corresponding originalframes, which are called the spatially scalable residue(SSR) hereafter, are also encoded with H.264. For WZ
frames, lines of pixels which locate at the pruned position are extracted by using pruned position indices.
After that, residual pruned lines (RPLs) are obtainedby taking the diﬀerence between the pruned lines of WZ
frames and those of the preceding key frames. RPLs are
encoded by TDWZ coder and will be used for correcting
interpolated lines at the decoder. During the TDWZ
encoding, the LDPC-accumulated (LDPCA) codec [8]is used as the error-correcting code since it is suitablefor DVC purpose.

h93l+k+1

k=−1 l=0×P̂h6 (t, i + k, j + l)
+

1
∑

h97+k

k=−1

×I(t − 1, i + k + m0 , j + 1 + n0 )=h9 · Ph9(1)where h9 is the vector of ninth-order model parameters,
Ph9 is the vector of 6-spatial neighboring pixels and 3spatio-temporal neighboring pixels of P̂h6 (t, i, j + 21 ),and (m0 ,n0 ) is the motion vector of the current block.
The model parameters of NEDI-9 is shown in Fig. 1,
where blue circles represent the available pixels in the
low resolution frames and black circles represent the
pixels need to be interpolated. The first term in equation (1) represents the spatial pixels in NEDI-6 andthe second term represents the spatio-temporal pixels
in I(t−1). The filter-like interpolation of NEDI-9 helps
reducing the artifact and flickering eﬀect that appear
by the intra frame based interpolation.

3

Encoder Architecture

3.2

Decoder Architecture

The decoder basically does the reverse operation of theencoder except the interpolation. For the interpolation, the single-frame based NEDI-6 is used for the
first key-frame while the multi-frame based NEDI-9 isemployed for the following frames in each GOP. Theinterpolation is performed as follows. First, decoded
low-resolution key frames are interpolated to the original size by NEDI-6 interpolation. The interpolated key

SLP-MFI-DVC

In this section, I present an improvement of my previous SDP-DVC scheme [7] by using NEDI-9 in the in-102

Figure 2: Architecture of proposed SLP-MFI-DVC.
frames are incorporated with SSR to reconstruct full
resolution key frames. For the WZ frames, block-based
motion estimation and motion compensation are applied to find the most similar block of pixels in the previous full-resolution key frame. Then, NEDI-9 whichuses three neighboring pixels in the matching block andsix surrounding pixels in the current frame are used
to interpolate each pixels in the current block. If theresult of the block matching is totally diﬀerent fromthe current block, the three spatio-temporal pixels are
discarded because the pixels in the matched block are
not related. Thus the artifact and flickering eﬀect are
reduced from interpolated frames. Moreover, for WZ
frames, the temporal residue is calculated to obtain theside information for TDWZ decoder. After TDWZ decoding, the reconstructed WZ frames are obtained byadding the corrected residue to previous reconstructed
key frames.

4

Comparing to NEDI-6, NEDI-9 achieves higher PSNR
for all frames. The interpolated sequence using NEDI-9
also has less flickering artifacts and higher quality consistent in the temporal direction than the single-frame
based interpolated sequence using NEDI-6. Especially,
for the fast moving sequence, NEDI-9 gained the muchlarger PSNR than NEDI-6. From this results, I can
expect the accuracy of the error correction process is
improved and thus the final reconstructed frames havehigher PSNR.

4.2

The rate-distortion performance of proposed SLP-MFIDVC is compared with original SDP-DVC, DISCOVER
DVC codec [9] at GOP of 4, and H.264/AVC intra coding. In SLP-MFI-DVC, the number of pruned lines inrow and column are fixed to 48, which means about
a half of pixels in each frame are removed. Besides, I
used the same condition with [7] for pruned indices andnonlinear quantization parameters.
Fig. 4 illustrates the R-D curves of various videocoding methods. The PSNR and bitrates are calculated for the luminance component of all frames andthe PSNR is the average over the sequences. Experimental results show that new SLP-MFI-DVC can outperform original SDP-DVC in all cases. It also outperforms DISCOVER for fast moving sequences, suchas Foreman and Soccer. Moreover, it also shows better performance than H.264/AVC intra coding in Hall
Monitor sequence. Note that by using multi-frame
based interpolation, SLP-MFI-DVC performance gradually reaches to H.264/AVC.
For fast motion video sequences, the conventional
DVC usually has problems in frame interpolation, re-Experiments

In this section, the experimental results are shown tovalidate the eﬀectiveness of the new SLP-MFI-DVC
method. I used luminance (Y) signal of 150 framesof popular video sequences, Foreman, Hall Monitor,
and Soccer with QCIF size and 15fps. As the core
codec used in the encoder, I used GOP=4 coding of
H.264/AVC.

4.1

Video Coding PerformanceEﬀect of using NEDI-9

Fig. 3 shows the PSNR comparison of the interpolation methods between NEDI-6 and NEDI-9. Here, I
only compared the PSNR of the WZ frames because
key frames are always reconstructed to full resolution.

103

40

PSNR [dB ]

38
36
34
NEDI-9NEDI-6

32
30
28
0

10

20

30

40

50

60

70

80

90

100

110

Number of frames(a) Foreman QCIF, 15fps
30.5

PSNR [dB]30

29.5
NEDI-929

NEDI-6

28.5

28
0

10

20

30

40

50

60

70

80

90

100

110

Number of frames(b) Hall QCIF, 15fps
40

PSNR [dB]383634
NEDI-9NEDI-6

32
30
28
0

10

20

30

40

50

60

70

80

90

100

110

Number of frames(c) Soccer QCIF, 15fps

Figure 3: PSNR comparison of the video interpolation methods.
Figure 4: Rate-distortion performance of various
coding methods.

sulting lower performance compared to H.264/AVC.
It can be observed in Foreman and Soccer sequences.
In my framework, the multi-frame based interpolation
is eﬀective to reduce the artifacts which are occurred
by SLP and the multi-frame interpolation process performs better than the single-frame based interpolation.

5[2] A. Wyner and J. Ziv, “The rate-distortion function forsource coding with side information at the decoder,”IEEE Trans. Inf. Theory, vol. 22, no. 1, pp. 1-10, 1976.
[3] A. Aaron, S. Rane, E. Setton, and B. Girod,“Transform-domain Wyner-Ziv codec for video,” inProc. SPIE VCIP’04, pp. 520-528, 2004.
[4] B. Macchiavello, F. Brandi, E. Peixoto, R. L.
de Queiroz, and D. Mukherjee, “Side-information generation for temporally and spatially scalable Wyner-Ziv
codecs,” EURASIP Journal on Image and Video Processing, vol. 2009, 2009.
[5] D. Liu, X. Sun, F. Wu, S. Li, and Y. Q. Zhang, “Imagecompression with edge-based inpainting,” IEEE Trans.
Circuits Syst. Video Technol., vol. 17, no. 10, pp. 12731287, 2007.
[6] D. T. Võ, J. Solé, P. Yin, C. Gomila, and T. Q. Nguyen,“Selective data pruning-based compression using highorder edge-directed interpolation,” IEEE Trans. Image
Process., vol. 19, no. 2, pp. 399-409, 2010.
[7] T. T. Phan, Y. Tanaka, M. Hasegawa, S. Kato, “MixedResolution Wyner-Ziv Video Coding Based on Selective
Data Pruning,” MMSP2011, pp. 2-6, Hangzhou, China,
Oct. 17-19, 2011.
[8] D. Varodayan, A. Aaron, and B. Girod, “Rate-adaptive
codes for distributed source coding,” Signal Processing,vol. 86, no. 11, pp. 3123-3130, 2006.
[9] X. Artigas, J. Ascenso, M. Dalai, S. Klomp, D. Kubasov,and M. Ouaret, “The DISCOVER codec: architecture,techniques and evaluation,” in Proc. 26th Picture Coding Symposium, Lisbon, Portugal, Nov. 2007.

Conclusions

In this paper, a new SLP-MFI-DVC using multi-frame
based interpolation has been proposed to improve
the SDP-DVC video coding performance. The ratedistortion performance of the proposed codec is better
than conventional ones and the DISCOVER for videos
with relatively many motions. Still, there is a room for
improvements in the interpolation. Future work also includes replacing the SLP with other resizing methods
such as a fast content aware retargeting.

6. References[1] D. Slepian and J. Wolf, “Noiseless coding of correlated
information sources,” IEEE Trans. Inf. Theory, vol. 19,
no. 4, pp. 471-480, 1973.

104

DETERMINANTS OF MOBILE LEARNING ACCEPTANCE IN LUANG PRABANG:TOWARDS WORLD HERITAGE SITE PRESERVATION AWARENESS PROMOTION
Student Number: 11M51436

Name: Yew Siang POONG

Supervisor: Shinobu YAMAGUCHI, Jun-ichi TAKADA

Mobile learning has been gaining attention in international development to promote knowledge among local community.
However, little is known about mobile learning acceptance in Luang Prabang, Lao PDR. Through the collaboration with
the Department of World Heritage of Luang Prabang, questionnaire survey based on the extended Technology
Acceptance Model was administered to 484 students in two local higher education institutions. Besides, face-to-faceinterview was conducted with eight faculty members to gain understanding on mobile learning implementation
perceptions and possibilities. Empirical data shows high degree of intention to use mobile learning, and multiple
regression analysis discovered six important mobile learning acceptance factors. Result from this study contributes toknowledge improvement from least developing country perspective and provides valuable guidelines for thedevelopment of mobile learning application to promote heritage site preservation awareness in Luang Prabang.
to use mobile learning
By understanding the acceptance of mobile learning, it isexpected that the findings would facilitate thedevelopment of effective mobile application to promote
World Heritage Site preservation awareness in the future.

1. Introduction and Objective
UNESCO recently issued an urgent call for preservationof Luang Prabang town as a World Heritage Site due torapid development after Luang Prabang has become apopular tourists spot. Although Lao PDR is identified asa least developed country, mobile subscription rate has
shown growing trend and has achieved 65% penetration
rate in 2011 [1]. As education is recognized to play animportant role in promoting awareness in preservationand protection, this research aims to introduce mobile
learning to promote World Heritage Site preservation
awareness in World Heritage Site.
Mobile learning is defined as “acquisition of any
knowledge and skill through the use of mobile
technology, anywhere, anytime that results in analteration in behavior” [2]. Recently, mobile learning isperceived as a tool to empower people in developing
countries in gaining access to information, which would
eventually promote sustainable development as well as
improving quality of life. This is evidenced from theinitiatives of mobile learning application on developing
countries by international development agencies, such as
UNESCO, World Bank, and Asian Development Bank.
However, in order to ensure sustainable use of ICT
implementation, user perception evaluation is vital prior
to its implementation, especially in developing countries[3]. Consistent with this view, this research intends toexamine mobile phone usage behavior and perceptions ofmobile learning to shed light on the actual status ofmobile learning readiness among the young generation in
Luang Prabang.

2.2 Theoretical framework
The original TAM proposes two important
antecedents of technology use intention, namely,
perceived usefulness and perceived ease of use.
Perceived usefulness is defined as “the degree to which aperson believes that using a particular system would
enhance his or her job performance” [4, p.320]. Past
research has found that intention to use a technology
would be enhanced when the technology is believed toprovide advantage to the potential users. Also, literatureshows that a technology that is easy to use would boost
the perception of usefulness, which in turn increases
intention to use a technology. This notion is captured byperceived ease of use, which is defined as “the degree towhich a person believes that using a particular system
would be free from effort” [4, p.320]. Therefore, thefollowing hypothesis is developed:
H1: Perceived usefulness is positively related tobehavioral intention to use mobile learning
among young adults in Luang Prabang.
H2: Perceived ease of use positively affects
behavioral intention to use mobile learning
among young adults in Luang Prabang,
mediated by perceived usefulness.
Literature indicates that social actors do play animportant role in influencing an individual to adopt
technology. In particular, the image value of the societyof which an individual is active in and the opinion fromthe close social actor of an individual are the key factors
in social influence [5]. Nevertheless, social influence
does not assert direct effect to intention to use. Rather,social influence increases perceived usefulness of atechnology, which in turn influences intention to use [6].
Thus, the following hypothesis is developed:
H3: Social influence positively affects behavioral
intention to use mobile learning among
young adults in Luang Prabang, mediatedby perceived usefulness.
Personal innovativeness is defined as “the willingnessof an individual to try out any new information
technology” [7, p.206]. Research shows that individual

2. Research Components
2.1 Problem statement
The study of mobile learning acceptance has just begunin the recent years. With many literatures focusing on
developed countries, there is lack of understanding of
end user mobile learning acceptance in least developed
countries. Hence, this gives rise to the following researchquestion: what are the factors affecting young adult’s
intention to adopt mobile learning in Luang Prabang?
Following this, three research objectives are developed:
i. To evaluate current mobile phone ownership profile
ii. To assess mobile phone usage behavioriii. To investigate factors affecting behavioral intention
105

who have high level of personal innovativeness will
demonstrate increased curiosity and courage to be thefirst adopter of new technology. This research intends totest whether there is relationship between personalinnovativeness and intention to use mobile learning.
Hence, the following hypothesis is developed:
H4: Personal innovativeness is positively
related to behavioral intention to use
mobile learning among young adults inLuang Prabang.
Based on the past findings, self-efficacy, which isdefined as “people’s judgments of their capabilities toorganize and execute courses of action required to attaindesignated types of performances” [8, p.391], influences
an individual’s behavioral intention to use technology.
When one has favourable judgment on his/her own
capability to handle a technology, intention will be
stimulated to use the technology. Therefore, thehypothesis is developed as:
H5: Self-efficacy is positively related tobehavioral intention to use mobile learning
among young adults in Luang Prabang
Motivation theorists have found that individual’s
perceived enjoyment plays an important role in theprocess of using technology. Perceived enjoyment isdefined as “the extent to which the activity of using thetechnology is perceived to be enjoyable in its own right,
apart from any performance consequences that may be
anticipated” [9, p.1113]. Given that mobile learning inthis study context is to be used in informal settings, thisstudy proposes the following hypothesis:
H6: Perceived enjoyment is positively related tobehavioral intention to use mobile learning
among young adults in Luang Prabang.
Potential consumers’ affordability has been found to
influence purchase in consumer research [10]. Perceived
price measures young adults’ perception on whether or
not the pricing structure offered by telecommunication
operators is reasonable for using advanced mobile
services [11]. The investigation of perceived price isimportant to clarify affordability issue since Lao PDR isa lower-middle income economy country. Therefore, thefollowing hypothesis is proposed:
H7: Perceived price is positively related tobehavioral intention to use mobile learning
among young adults in Luang Prabang.
Mathieson, Peacock and Chin [12] argue that anindividual may face limited resources in using
technology. Although an individual may perceive thathe/she has the ability to use technology, perceived
facilitating resources also plays an important role in use
intention. Taylor and Todd assert that “the absence offacilitating resources represents barriers to usage andmay inhibit the formation of intention to usage” [13, p.
153]. Given that Lao PDR is a least developed country,
this study intends to assess local people’s perception on
facilitating resources with respect to the use of mobile
learning. Thus, the following hypothesis is proposed:
H8: Perceived facilitating resources are positively
related to behavioral intention to use mobile
learning among young adults in Luang
Prabang.
Based on the literature review, the TAM model ismodified to suit the current research context, as shownin Figure 1. There are a total of eight independent
variables and one dependent variable. The dependent
variable is behavioral intention to use ML (ML shortfor “mobile learning”). Also, two types ofrelationships are modeled in theoretical framework,
namely direct and mediated relationships. In particular,
mediated relationship attempts to model the causal
chain of an independent-dependent variable
relationship, in which deeper insight could be obtainedwith the inclusion of a mediator variable.
SocialInfluence

Self-efficacy
H3

Perceived
Usefulness
Perceived
Ease of Use

Perceived
Enjoyment

H5

H6
Behavioral
intention touse ML

H1
H2

PersonalInnovativeness

H4

H8
Perceived
Facilitating
Resources

H7
Perceived
Price

Direct relationshipMediated relationship
Figure 1: Research model
2.3 Methodology
This study adopts questionnaire survey andinterview to acquire student perceptions on mobile
learning. The questionnaire consists of three sections: 1)
collecting of students’ demographic information, 2)
investigating mobile phone features and usage by
students; and 3) inquiring students’ perceptions towards
technology acceptance variables identified in thetheoretical framework. The questionnaire was translated
into Lao language with the assistance of local DPL staffs
and was verified by Souphanouvong University
personnel.
A total of 484 questionnaires were distributed toSouphanouvong University (SU) and to Northern Law
College (NLC) of Luang Prabang in March 2012. SU is
one of the four Lao national universities and NLC is a
law-focused college established directly under the
Ministry of Justice. There are a total of 4,700 and 4,000
students in SU and NLC respectively. The number of
distributed questionnaire compose of about 5% of thetotal campus population. A total of 443 questionnaires
were returned, yielding 91.53% response rate. Finally,
365 questionnaires were considered valid for data
analysis.
Descriptive analysis based on frequency result was
conducted on demographic and perception questions.
Next, inferential analysis using multiple regression was
conducted to test the proposed theoretical model. In
order to validate mediation effect, mediation procedure
based on Baron and Kenny [14] work was performed.
Finally, bootstrapping procedure was applied to assess
the mediation effect and whether or not the mediation
model is statistically significant.
In addition, interviews were conducted with faculty106

sites (n=203), playing game (n=178), and reading news
(n=134). On the other hand, mobile phone is used mainly
in chatting (n=230) and listening to music (n=213).
Meanwhile, school (n=159, 43.56%) and home (n=119,32.60%) are the top two places of access to the Internet.
Respondents who access to the Internet anywhere using
mobile phone comprise of 30.13% (n=110). Analysis
shows that Internet access mobility trend is observed
among the young adults in Luang Prabang.

members of the education institutions to supplement thestatistical data. Questions asked include student’s mobile
usage behavior from adult point of view, mobile learning
perceptions and development prospects in general, andimplementation suggestions for the development ofWorld Heritage Site preservation awareness mobile
application.

3. Findings
Male and female respondents comprise of 61.4%(n=224) and 34.5% (n=126) respectively. Fifteen
respondents did not state their gender. Majority of the
respondents (70.4%, n=257) are in the age around 20 to
24 years old. Mixed distribution is observed in
respondents’ income demographic, although the highest
income category (received >100,000 Lao Kip per month)records the responses (n=97, 26.6%), followed by those
who received income less than 19,999 Lao Kip permonth (n=81, 22.2%).

3.2 Hypotheses testing
Descriptive data analysis on the symmetricagree-disagree 5-point Likert scale revealed high degreeof agreement response on perceived usefulness,
perceived ease of use, perceived enjoyment, perceived
facilitating resources, personal innovativeness, social
influence and intention to use mobile learning. However,both self-efficacy and perceived price factors received
relatively higher disagreement responses on the scale.
In order to test the hypotheses, three sets ofregression models are developed as follows:

3.1 Mobile phone demographic and use behavior
The survey found the following three major
characteristics among university students in Luang
Prabang:
3.1.1 Most common device owned by student is mobile
phone, followed by laptop PC
Given the multiple response options of mobile phone,tablet, laptop personal computer (PC) and desktop PC, atotal of 587 (160.8%) cases were reported (n=365). Thismeans respondents own between 1 to 2 devices at thesame time. The device that most owned by respondents
is mobile phone (n=358), followed by laptop PC (n=188),
desktop PC (n=29) and tablet (n=12). The figures
conform to the trend of mobile phone ownership inseveral other developing countries and depict thepotential of using mobile phone as a tool to implement
innovative ICT application.

Equation (1) tests the direct effect of independent todependent variables (hypothesis 1, 4, 5, 6, 7, and 8).
Equation (2) and (3) forms the necessary conditions totest hypothesis 2, and 3 respectively.
Result of the regression model is as shown below:

3.1.2 Smartphone is popular among university students
Among those who owned a mobile phone (n=358),
data analysis shows 177 (49.44%) respondents state that
their device is a smartphone. With respect to connectivity
options, there are 516 cases reported (144.13% with
n=358), depicting one or more connectivity options
available in the mobile phone. Specifically, respondents
state that their mobile phones have Bluetooth (n=204),
3G (n=149), WiFi (n=76), and infrared (n=15). Internet
connectivity wise, 3G-enabled mobile phone appears to
be more common than WiFi-enabled mobile phone. The
high number of Internet-ready mobile phone owned by
the respondents suggests that more varieties ofinnovative applications could be developed.

All the hypotheses are supported except self-efficacy(H5) and perceived price (H7). Result of regression
model (4) shows that perceived enjoyment is thestrongest predictor for behavioral intention to use mobile
phone for learning, followed by perceived facilitating
resources. Overall explained variance for regression
model (4) is 35.2%. Equation (5) and (6) shows thatperceived ease of use and social influence would enhance
perceived usefulness of mobile learning, which in turninfluence behavioral intention. Effect of social influenceis reduced significantly after perceived usefulness is
included into equation (6a) (see equation (6c) for effectreduction of SI). Both the mediation equation (5) and (6)are statistically significant under bootstrap analysis at
95% confidence interval.

3.1.3 Laptop PC is the main device used for digital
activities followed by mobile phone, and the school is thecommon place to access Internet
A multiple response analysis shows that laptop PC is
the most used device (1749 cases), followed by mobile
phone (1195 cases). Specifically, laptop PC is reported
being used mainly for searching information (n=231),
learning new knowledge (n=231), e-mail (n=223),
watching video (n=220), engaging in social networking

3.3 Interview results
Feedback from faculty members shows that there istrend of mobile Internet use among students and that107

developing mobile learning application. Also, initiatives
to stimulate personal innovativeness among the young
adults and engage important social actors of Luang
Prabang community in promotion campaign, such asworkshops and demonstrations, would be essential toincrease mobile learning adoption.

mobile learning is in line with current students’ mobile
phone use behavior. In addition, the use of mobile
learning could increase accessibility to information,
given high mobile phone penetration rate in Luang
Prabang. With regard to application implementation
approach, faculty members commented that mobile
learning should be designed in a motivating, interesting,and enjoyable approach so as to be able to attract the
young adults to use. In addition, using mobile learning topromote World Heritage Site awareness is thought as aneffective approach, given limited accessibility to World
Heritage Site information. Faculty members suggest
providing hands-on demonstration, assignments, andworkshops to promote the application, in addition to
media announcement. Well-designed application is also
one of the important criteria to promote mobile learning
application, according to the interviewees.
Department of World Heritage (DPL) counterpart
comments that the introduction of mobile learning
application could supplement awareness promotion
campaign by providing easy access to heritage
information using mobile phone. The development ofsuch application could also contribute to the collection of
locally-oriented mobile applications, which is still scarcein number currently.

4.3 Limitation and future research
As an explorative study, current research draws fromstudent sample, which calls for caution on data
generalizability. Future studies with respectable
resources could increase the sample size and include
different target respondents to achieve a morecomprehensive coverage. Empirical testing research aresuggested to incorporate additional factors to increase theexplanatory power of the current model in this study. In
addition, future research could embark on determining
the implications of using mobile learning by analyzinguser performance on pre- and post- adoption of mobile
learning in promoting World Heritage Site preservation
awareness. A comparative study between users who
adopt mobile learning and those who do not could also
be conducted to determine whether mobile learning is aneffective solution to promote heritage site preservation
awareness in Luang Prabang.

4. Discussion

References

4.1 Data interpretation
Current investigation shows that the determinants ofmobile learning use intention among the young adult inLuang Prabang are perceived usefulness, perceived easeof use, personal innovativeness, perceived enjoyment,
perceived facilitating resources, and social influence. In
addition, relationships between social influence andperceived ease of use with behavioral intention to use
mobile learning are mediated by perceived usefulness.
This result suggests that 1) the effect of social influence
on intention to use mobile learning depends largely on
how the important social actors convey mobile learning
usefulness to the potential users; 2) mobile learning easeof use could enhance usefulness perception, which inturn increase use intention. As oppose to literature,
self-efficacy and perceived price did not appear to be thedeterminant of intention to use mobile learning. Mixed
responses on both of the perceptions suggest that some
respondents do concern about the skills they possess may
not be sufficient for them to use mobile learning.
Moreover, there are also relatively high responses of
disagreement on the acceptability of mobile pricing
structure offered by telecommunication operators to
support mobile learning.

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[5] Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention, andbehavior: An introduction to theory and research. Reading, MA:
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4.2 Implication for Research and PracticeThis study has validated the extended TAM in aleast developing country (LDC) context. TAM was
originally created in the United States by Davis [4].
However, there are limited studies conducted in Lao
PDR using TAM. The finding of this study has filled thegap of understanding mobile learning acceptance inLuang Prabang, which is an imminent research indeveloping countries.
Practitioners are suggested to look into theenjoyment, usefulness, and ease of use factors while108