Sustainability Analysis: Hydrogen 

Regional Sustainability (HyReS)

Elizabeth B. Connelly

National Renewable Energy Laboratory

June 13, 2018

DOE Hydrogen and Fuel Cells Program 

2018 Annual Merit Review and Peer Evaluation Meeting

This presentation does not contain any proprietary, confidential, or otherwise restricted information.

Project ID SA059 NREL/PR-5400-71334
NREL | 2

Overview

Timeline Barriers

Start: September, 2015

End: September, 2018

80% complete

4.5 A. Future Market Behavior

• Consumer preferences for green hydrogen

4.5 B. Stove-piped/Siloed Analytical Capability • Integration of metrics from internal (DOE) and external 

models

4.5 D. Insufficient Suite of Models and Tools

• More complete analytics across all aspects of 

sustainability 

Budget Partners

Total Project Funding: $500k

• FY15: $200K

• FY16: $200k

• FY17: $100k

Total DOE funds received to 

date: $500k

Argonne National Laboratory (GREET)

Collaborative Reviewers

• Ford

• Louis Berger

• E4Tech

• LBST (Ludwig-Bölkow-Systemtechnik)
NREL | 3

FCTO Systems Analysis Framework

Relevance 1

HyReS integrates with systems analysis 

framework:

• Expansion of existing systems analysis 

models that address costs and 

environmental impacts

• Additional sustainability metrics and a 

general regionalization of all inputs and 

results, given available data.

Analysis 

Framework

• Cost estimation

• Supply chain 

efficiencies

• Energy resource and 

water utilization

• GHG and criteria 

emissions

Models & Tools

• H2A production and 

delivery models

• GREET

• H2FAST

• SERA

Studies & 

Analysis • Sustainability 

metrics

• Framework 

implementation

Outputs & 

Deliverables

• Reports

• Workshops

• Public framework

• FCTO Program 

Targets

• BETO Sustainability 

Framework & 

Billion-Ton Report

• H2@Scale 

• Sustainability science 

and green business 

communities

• Other frameworks

• Fuel Cell 

Technologies Office

• Sustainable energy 

analysis community 

Acronyms

BETO: Bioenergy Technologies Office

GHG: Greenhouse gas

GREET: Greenhouse Gases, Regulated Emissions, and 

Energy Use in Transportation model

H2FAST: Hydrogen Financial Analysis Scenario Tool

SERA: Scenario Evaluation and Regionalization Analysis 

models
NREL | 4

HyReS Objectives

Overall Objectives:

– To provide industry, government, and non-government 

stakeholders with readily accessible and transparent analytic tools 

needed to make informed investments with respect to hydrogen 

supply, fuel cell systems, and sustainable development 

– To examine environmental burdens in an integrated regional 

assessment approach that also takes into account the economic

and social aspects of hydrogen supply chains and the FCEV life 

cycle 

FY18 Objectives:

– Model various future scenarios of hydrogen infrastructure build- out based on uncertain political, technological, and economic

conditions

– Develop and publish online visualization tool of scenario results

Relevance 2

The Hydrogen Regional Sustainability (HyReS) framework will 

integrate existing sustainability metrics and indicators to examine 

environmental, economic and social impacts of hydrogen supply 

chains and FCEVs
NREL | 5

Modeling Approach Builds on SERA 

Framework

• The Scenario Evaluation and 

Regionalization Analysis 

(SERA) modeling framework 

develops optimized hydrogen 

supply networks in response to 

hydrogen demands

• Spatially explicit: accounts for 

the geography of resource 

availability, supply chain costs, 

and HyReS will include supply 

chain sustainability

• Identifies optimal supply chain 

configuration (least-cost or 

most-sustainable) options both 

temporally and regionally

Approach 1

The HyReS/SERA framework will identify optimal hydrogen supply 

chains considering spatially- and temporally-based constraints and 

aspects of sustainability
NREL | 6

Metrics for Comparison of Alternative 

Hydrogen Supply Pathways

• Business perspective: focus on 

issues that are material to the 

company’s long-term value 

– System energy efficiency

– Water management

– Emissions

• Government perspective: 

– Energy security

– Resource conservation

– Human health

– Cost to consumers

Approach 2

The HyReS framework will track information related to 

selected sustainability indicators, maintaining 

compatibility with existing frameworks to guide a broad 

range of decision makers

Framework Alignment

Sustainability Accounting Standards Board 

(SASB) – material sustainability metrics

Global Reporting Initiative (GRI) –

comprehensive sustainability reporting 

standards

MSCI – ESG factors related to UN Principles for 

Responsible Investment

ENVISION – certification for sustainable 

infrastructure 

Natural Capital Coalition – protocol for 

business managers and decision makers

Bioenergy Technologies Office (BETO) 

sustainability program (social, economic, 

environmental)
NREL | 7

Modeling Approach Leverages GREET2017 

and FASTSim Models Approach 3

Feedstocks Delivery Outputs

Natural Gas Gaseous or 

Liquid Energy Consumption

Coal Tube Trailer Water Consumption

Nuclear Pipeline Emissions

Solar Barge

Biomass Rail ... 

Incorporating GREET 2017 data:

• Updated water consumption factors

• Updated the emission factors of criteria air 

pollutant (combustion and non-combustion 

emissions) for SMR hydrogen

• Updated U.S. electricity generation mix

The HyReS analysis combines GREET 

environmental impacts with FASTSim 

modeling of future vehicle attributes

FASTSim is used to model 

future vehicles with 

comparable driving ranges 

(400 miles) and, when 

possible, acceleration.

Inputs to GREET include 

vehicle weight, battery size, 

and fuel economy.

Vehicle	

Cycle

GREET2

Material	

recovery	and	

production

Vehicle	

component	

fabrication

Vehicle	

Assembly

Vehicle	

Disposal	and	

Recycling

Fuel	Cycle

GREET1

Feedstock

Production	&	

Transportation Vehicle	Operation:	PTW

Fuel

Production	&	

Transportation

Well-to-Pump	(WTP)
NREL | 8

Health Impact Assessment with EASIUR

As opposed to BenMAP or COBRA, the 

Estimating Air pollution Social Impact 

Using Regression (EASIUR) (Carnegie 

Mellon, 2016) model will be used for 

monetizing health benefits from changes 

in air pollution emissions

– More straightforward integration 

with SERA/HyReS model

– Chemical transport model as 

opposed to Gaussian dispersion 

model

– Marginal benefits calculations similar 

to EPA models (see figure)

– Applied to GREET emissions factors 

by year

Approach 4

ANALYSIS 

a 

c 

0

2

4

6

8

10

12

14

16

18

20

2007 2008 2009 2010 2011 2012 2013 2014 2015 

Avoided air pollution damages

(billion 2015 US$)

Central estimate

COBRA high

EPA high

EASIUR high

COBRA low

EPA low

EASIUR low

AP2

Penn et al. (2017)

Central estimate

COBRA high

EPA high

EASIUR high

COBRA low

EPA low

EASIUR low

AP2

Penn et al. (2017)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

2007 2008 2009 2010 2011 2012 2013 2014 2015

Avoided air pollution damages

(billion 2015 US$)

Year 

The HyReS framework will assess social 

sustainability, such as health benefits from 

changes in air pollutants using existing tools

Reprinted	by	permission	from	Springer:	Nature	

Energy,	“The	Climate	and	Air-Quality	Benefits	of	Wind	

and	Solar	Power	in	the	United	States,	”Millstein,	D.,	R.	

Wiser,	M.	Bolinger,	and	G.	Barbose.	2017	

https://doi.org/10.1038/nenergy.2017.134.

Benefits from wind power Benefits from solar power
NREL | 9

Scenario and Sensitivity Analysis

Scenarios varying based on:

• Future grid mix –

– GREET /EIA projections

– NREL Renewable 

Electricity Futures Study

• H2@Scale and H2USA 

demand scenarios

• FCTO program goals

– Electrolyzer efficiency

– Biomass gasification 

efficiency

Approach 5

The HyReS framework will consider a number of scenarios related to 

political, technological, and economic conditions

Source: NREL - https://www.nrel.gov/analysis/re_futures/data_viewer/
NREL | 10

Modified GREET System Boundaries for 

Energy Accounting Accomplishments 1

System boundaries adjusted to: (1) avoid double counting between 

WTP and PTW stages; (2) consider biomass as being generated and 

used within the system

Biomass 

Gasification to 

Hydrogen

Poplar Farming Transportation of 

Poplar

Transportation via 

Pipeline

Compression at 

Refueling Station

Vehicle Operation

0.035 mmBtu Diesel

0.56 lb Nitrogen

0.17 lb Phosphoric Acid

0.15 lb Potassium Oxide

0.02 lb Herbicides

6.73 lb Calcium Carbonate

0.004 lb Insecticides

2.09 mmBtu 

Poplar

2.09 mmBtu 

Poplar

0.09 mmBtu Diesel

0.052 mmBtu Natural Gas

0.029 mmBtu Electricity

1 mmBtu 

G. H2

1 mmBtu 

G. H2

0.037 mmBtu Electricity 0.1 mmBtu Electricity

1 mmBtu 

G. H2

Feedstock

Fuel

Vehicle Operation

WTP

- PTW

Fuel Cycle

Example: Hydrogen from Poplar 

Pathway is adjusted so that the poplar 

biomass is not counted as part of the 

fuel cycle energy use

Boundary Description Feedstock Fuel Vehicle 

Operation

Total Fuel 

Cycle

Total Energy Consumption (Btu/mmBtu) – FCEV: G. H2 from Poplar Biomass

GREET Default 

(Solid Background Blocks) 41,000 1,557,000 1,000,000 2,598,000

Adjusted 

(Dotted Line) 41,000 424,000 0 465,000

COORDINATING MODIFICATIONS WITH 

AMGAD ELGOWAINY (ANL, GREET)
NREL | 11

Vehicle-Fuel System / Model Source

BEV100 BEV300 BEV400 FCEV ICEV HEV - E10

GREET FASTSim

with

GREET

GREET FASTSim

with

GREET

FASTSim

with

GREET

GREET FASTSim

with

GREET

GREET FASTSim

with

GREET

GREET FASTSim

with

GREET

0

20

40

60

80

100

120

140

160

180

V

e

hicle

C

y

cle

E

n

erg

y

C

o

n

s

u

m

ptio

n

[m

m

Btu

/

v

e

h]

Modeled 400-Mile Range Vehicles in FASTSim 

Vehicle Cycle Results

FASTSim was used to model vehicle 

specifications for MY2025 vehicles 

with a 400-mile range

• Adjustments to existing 

vehicles made with respect to 

vehicle weight and fuel storage 

to result in 400-mile range

• GPRA targets used to adjust 

glider weight, motor power, 

and battery energy density for 

MY2025 vehicles

• Resulting vehicles lighter than 

GREET vehicles and thus have 

lower vehicle cycle impacts

• BEV400 is not modeled by 

GREET; BEV400 vehicle cycle 

energy intensity is 13% higher 

than GREET BEV300 

Accomplishments 2

FASTSim-modeled 

vehicles tend to have 

lower vehicle cycle 

energy impacts than the 

GREET lightweight default 

vehicles

-20%

-14%

-14%

-20% -20%

BEVs, FCEVs, and HEVs shown above are assumed to have li-ion batteries

BEV100 BEV300 BEV400 FCEV ICEV HEV -

E10

Total Vehicle 

Weight (lbs)

GREET 2700 3500 2900 2700 2800

FASTSim 2100 2900 3700 2400 2100 2100

Fuel 

Economy 

(mpgge)

GREET 140 120 80 40 60

FASTSim 140 120 110 80 50 50
NREL | 12

Wind

FCEV BEV

Natural

Gas

FCEV

Avg.

Grid Mix

BEV

Corn

HEV ICEV

Corn Stover

HEV ICEV

Poplar

FCEV HEV ICEV

Petroleum

HEV ICEV

FC

E

V

B

E

V

4

0

0

FC

E

V

B

E

V

4

0

0

H

E

V - E

8

5

FFV - E

8

5

H

E

V - E

8

5

FFV - E

8

5

FC

E

V

H

E

V - E

8

5

FFV - E

8

5

H

E

V

IC

E

V

P

e

trole

u

m

C

o

n

s

u

m

p

tio

n (M

M

B

t

u

/

v

e

h)

0

100

200

300

400

500

0

100

200

300

400

500

20.2 23.0 21.6 26.5

122.7

141.3 134.9

155.5

33.9

135.4

156.1

385.0

446.8

Life Cycle Petroleum Consumption

per vehicle lifetime

Analyzed Life Cycle Petroleum Consumption 

of FASTSim-Based Vehicles Accomplishments 3

Over the vehicle lifetime, wind- and natural gas-based 

FCEVs result in the lowest petroleum consumption, a 95% 

reduction from conventional gasoline vehicles

Fuel Cycle

Vehicle Cycle

PRELIMINARY RESULTS - COORDINATING WITH AMGAD ELGOWAINY (ANL, GREET)

-75%

-95% -95%
NREL | 13

Vehicle / Vehicle-Fuel System

BEV FCEV HEV

BEV100 BEV100+ BEV300 BEV300+ BEV400 BEV400+ FCEV FCEV+ HEV HEV+

0

50

100

150

200

V

e

hicle

C

ycle

E

n

erg

y

C

o

nsu

m

ptio

n

[m

m

Btu

/

v

e

h]

160.0

kWh

160.0

kWh

238.0

kWh

238.0

kWh

48.0

kWh

48.0

kWh

3.6

kWh

3.6

kWh

2.8

kWh

2.8

kWh

Revised Energy Intensity of Li-Ion Batteries

Peters and Weil (2018) review the existing literature on the LCA of Li-Ion batteries (LIBs), unifying 

assumptions across studies. 

HyReS analysis considers both GREET default values and higher energy intensity of LIB 

manufacturing.

Accomplishments 4

Electricity for LIB 

manufacturing (kWh/kg)

Heat for LIB manufacturing 

(MJ/kg)

Peters and Weil (2018) unified assumptions 9.0 20.0

GREET2017 default assumptions 1.1 18.7

Due to large LIB size, 

BEV400 vehicle cycle 

energy intensity 

increases by 25% 

using unified 

manufacturing 

assumptions

Considering FCEVs and HEVs with 

LIBs based on reviewer feedback

Reference:	Peters,	Jens	F.,	and	Marcel	Weil.	2018.	“Providing	a	Common	Base	for	Life	Cycle	Assessments	of	Li-Ion	Batteries.”	Journal	of	Cleaner	

Production 171	(Supplement	C):	704–13.	https://doi.org/10.1016/j.jclepro.2017.10.016.

9%

24%

25%
NREL | 14

NOx Marginal Benefits PM2.5 Marginal Benefits

Marginal NOx Benefit

($/tonne)

0

500,000

1,000,000

1,300,000

Marginal PM2.5 Benefit

($/tonne)

0

500,000

1,000,000

1,300,000

Integrated EASIUR into HyReS Framework 

Extracted marginal benefits of reducing NOx and PM2.5 emissions 

from EASIUR (Carnegie Mellon, 2016) for network of over 600 nodes 

used in SERA

Accomplishments 5

Lat-Longs

Urban area network based on H2USA LDV 

demand for hydrogen and existing electrolysis, 

SMR, and nuclear facilities (H2@Scale) $/tonne of 

NOx/PM2.5

NOx PM2.5

Minimum Marginal Benefit 

(2010$/tonne & location)

$654

Alamogordo, NM

$18,477

Roswell, NM

Maximum Marginal Benefit 

(2010$/tonne & location)

$205,866

New York, NY

$1,250,410 

New York, NY

Areas with higher 

population density 

have greater marginal 

benefits from air 

pollution reductions; 

PM2.5 marginal 

benefits are greater 

than those for NOx
NREL | 15

Monetized Benefits Air Pollution Emissions 

Reductions for H2USA Scenarios

The National 

Expansion scenario 

has greatest FCEV 

adoption (hydrogen 

consumption), yet 

33% lower 

cumulative air 

pollution benefits 

than in the State 

Success scenario.

The Urban Markets 

scenario requires 

only 40% of the 

hydrogen consumed 

in the National 

Expansion scenario, 

but results in 85% of 

the air pollution 

benefits.

Accomplishments 6

Scenario analysis highlights that spatial pattern of FCEV adoption 

determines magnitude of monetized air pollution benefits

Cumulative (2015 to 2050) Results

National

Expansion

State

Success

Urban

Markets

0B

50B

100B

H

y

dro

g

e

n

C

o

n

s

u

m

ptio

n

(k

g) 200K

400K

600K

N

O

x

R

e

d

uctio

n

(to

n

n

e

s)

0K

10K

20K

P

M

2.5

R

e

d

uctio

n

(to

n

n

e

s)

$0B

$5B

$10B

T

otal B

e

n

e

fits

($)
NREL | 16

Responses to Reviewers’ Comments: 

Pathways and Costs

Comment 1: Biomass gasification is not relevant (not being developed 

by DOE), would be more appropriate to use pyrolysis or hydrothermal 

liquefaction

Response: For consistency with DOE models, we base our pathways on 

those from the H2A production models. At this time, biomass 

gasification is the only biomass pathway modeled. 

Comment 2: The project is using the Hydrogen Analysis (H2A) model for 

the hydrogen levelized cost. This hydrogen cost is not a price. Price is set 

by the market. 

Response: SERA calculates the cost of producing hydrogen based on the 

H2A capital costs and resource efficiency. SERA also uses energy and 

other resource prices (mainly from EIA). Transportation and distribution 

costs are based on the HDSAM model. Thus, the outputs include the 

cost of hydrogen from individual units with a 10% IRR (minimum 

required selling price). Future work will implement the H2FAST 

approach for cost analysis. A market-based pricing strategy is outside 

the scope of this project.

Responses 1
NREL | 17

Responses to Reviewers’ Comments: Model 

Inputs and Outputs

Comment 3: It is not clear what the final model will look like when 

the project is done, and what possible inputs and outputs would 

be. 

Source:

H2A

HDSAM

EIA 

(and Billion Ton Study)

H2USA and H2@Scale

H2USA

Geospatial

Analysis

Responses 2

Process 

Efficiency 

Process Emissions 

(GREET-based/ 

HyReS module)

Feedstock 

Upstream Impacts 

(HyReS module)

Environmental 

Impacts (HyReS 

module)
NREL | 18

Collaboration and Coordination

• Argonne National Laboratory – Modeling

– GREET Model

• Collaborative Reviewers – Metric Visualization

– Ford

– Louis Berger

– E4Tech

– LBST (Ludwig-Bölkow-Systemtechnik)

– Academic institutions

• H2@Scale Project Team – Scenario Analysis
NREL | 19

Remaining Challenges and Barriers

Finalizing Model

• Implementation of resource supply curves in SERA model

• Modeling impacts from existing production facilities (used 

in H2@Scale scenarios)

• Calculating H2 prices

Relevance to Stakeholders

• Additional stakeholder input from hydrogen producers 

and/or fueling station owners

• Limited mapping capabilities with Tableau Public
NREL | 20

Future Work

Model Updates

• Implement supply curves for hydrogen feedstocks to 

reflect actual resource availability

– Biomass – prepared using Billion Ton Study (✓)

– Solar – NREL maps (see Hydrogen Resource Report)

– Wind – NREL maps (see Hydrogen Resource Report)

• Expand production pathways outside of those in H2A

• Compare sustainability of vehicle technologies across 

non-LDV market segments

Visualizations 

Finalize and publish Tableau public visualizations of future 

scenarios

– Based on iterative stakeholder feedback

Project Coordination

Continue coordination with H2@Scale team to understand 

sustainability implications of H2@Scale scenarios

– Requires additional inputs/model restructuring to 

account for existing production infrastructure

Any proposed future work is subject to change based on funding levels.

Some proposed work (in orange) is outside the current project scope.

Project Plan

Year One

• Subject Review

• Steering Team

• Expand Framework

Year Two

• Additional Expansion

• Framework Application

• Corporate-Level Alignment

• Beta Version

Year Three

• Reviewer Feedback

• Refine Framework

• Implement Framework

þ







þ

þ

þ

þ

þ

þ

Ongoing iterative process
NREL | 21

Technology Transfer Activities

• Licensing of SERA model is being considered

• Presently publically available:

– FASTSim: https://www.nrel.gov/transportation/fastsim.html

– GREET: https://greet.es.anl.gov/

– H2A Case Studies: 

https://www.hydrogen.energy.gov/h2a_prod_studies.html

– HDSAM Model: 

https://hdsam.es.anl.gov/index.php?content=hdsam

– EASIUR: http://barney.ce.cmu.edu/~jinhyok/easiur/online/
NREL | 22

Summary

Relevance

• Expansion of existing systems analysis models that address costs and environmental 

impacts

• Addresses industry and other stakeholder preferences

Approach

• Modifying GREET fuel system boundary for energy accounting, coordinating with ANL

• Comparing vehicles with 400-mile range

Accomplishments and Progress

• FASTSim-based vehicle cycle results show BEV400 vehicle cycle with 15% higher energy 

consumption than FCEV with 400-mile range

• FCEVs can reduce life cycle petroleum consumption by 95% compared to conventional 

gasoline vehicles

• H2USA “State Success” scenario results in the largest monetized benefits due to air 

pollution reductions concentrated in densely populated areas

Collaboration

• GREET model developers; H2@Scale project team; Steering committee

Proposed Future Research

• Final refinements of model and implementation to analyze H2@Scale and other 

sensitivity scenarios

• Tableau Public for visualization of results
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency 

and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

www.nrel.gov

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency 

and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency

and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

NREL/PR-5400-71334

Thank You