Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch...

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Assessing Impact of Biofuel Production on Regional Water Resource Use and Availability May Wu Ph.D. Principal Environmental System Analyst Argonne National Laboratory Department of Energy Webinar Office of Biomass Program, EERE, DOE Aug 15, 2012

Transcript of Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch...

Page 1: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

Assessing Impact of Biofuel Production on Regional Water Resource Use and Availability

May Wu Ph.D.

Principal Environmental System Analyst

Argonne National Laboratory

Department of Energy Webinar

Office of Biomass Program, EERE, DOE

Aug 15, 2012

Page 2: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

Biofuel Is a Key Component in

Water–Energy Nexus

1 2

Page 3: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

Potential Cellulosic Biomass

Resources for Biofuel Production Biofuel feedstock types

− Starch

Corn, wheat, sorghum, cassava

− Oil crops

Soybean, rapeseed, palm oil, algae, Jatropha, waste oil

− Sugar

Sugar cane, sugar beet, sweet sorghum

− Cellulosic

Crop residue, perennial grass, short- rotation woody crop, forest wood residue, municipal solid waste

• Billion-Ton Resource Update (DOE)

− Cellulosic biomass feedstock of nearly 1.1 billion dry tons potentially available for biofuel production by 2030

− Replace approximately 30% of the nation’s current petroleum consumption

Source: US DOE 2011 3

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Questions

Biofuel life cycle

How does the choice of feedstock affect water usage in producing

one gallon of biofuel?

How does the choice of different regions for growing feedstock

affect the types of water needed as well as the water availability?

How does the choice of refinery siting affect water sustainability?

How does the choice of feedstock and location impact down

stream water quality?

Page 5: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

Major Considerations of Water

Use in Biofuel Production

Spatial variability − Climate, water resource, soil, feedstock

Feedstock type − Annual crop, perennial grass, forest wood residue − Yield, water requirement

Management and practices − Chemical input, irrigation, harvest

Biofuel production pathway − Type of conversion process, process water use efficiency,

co-product Indirect inputs

− Energy, chemicals

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Irrigation

Base flow

Evapotranspiration (ET)

Rainfall

Evaporation

Percolation Ground water

Water resource input: Primarily rainfall Consumptive water use: Water loss by evaporation from soil and water surfaces, and by transpiration from plants

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Blue water – Surface and ground water use by crops and biorefinery

Green water – Rainfall use by crops

Grey water – Volume-equivalent water required to dilute chemicals to acceptable level

Biofuel Water Footprint Accounting

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Grey

water

Cooling, Process water,

Steam

Green

water

Blue

water

Production of electricity and other

fuels and chemicals

Irrigation

Co-product

Biofuel life cycle

Page 8: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

Spatial Distribution of Water Footprint:

Corn Stover Ethanol

Blue Water

Grey Water

Green Water

Requirement: 401 billion gallons of blue water to produce 4.9 billion gallons of biofuel annually

– 24% stover removal

8 Sources: Chiu and Wu 2012

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Projected Perennial Feedstock Production

Source: USDOE 2006 (https://public.ornl.gov/site/gallery/detail.cfm?id=138&topic=&citation=8&general=&restsection=)

Scenario: 2022 Feedstock: perennial Source: USDOE (2011)

Miscanthus Switchgrass

Areas suitable to grow perennials

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Spatial Heterogeneity in Types of Water Used

Sources: Chiu and Wu 2012

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Water Use in Biorefinery Varies with

Feedstock and Conversion Process

Cooling

Tower

53%

Boiler

3%

Dryer

42%

DDGS

2%

5.8

4.7 4.2 4.0 3.0

2.7

0.0

2.0

4.0

6.0

8.0

Dry mills(NREL)

USDAsurvey

MN drymills

MN drymills

RFAsurvey

UICsurvey

1998 2003 2005 2006 2007 2010

Co

nsu

mp

tive

Wat

er U

se

(Lit

er w

ater

/Lit

er f

uel

eth

ano

l)

Conventional biofuel - Corn dry mill Cellulosic biofuel - Biorefinery

0 2 4 6

Biochemical

Gasification

Pyrolysis

Gal of water per gal of ethanol

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Source: Wu et al. 2009; Humbird et al. 2011; Jones et al. 2009

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Multiple Products Produced from

Biorefinery

Biofuel Bio-electricity

Biogas

Animal feed

Fertilizer Chemicals

Agricultural residue,

grain starch, oil seeds,

forest wood residue, perennial

grass, Municipal

waste, algae, other

biomass…

Water use in producing displaced products

contributes to water credit.

Bio

chem

ical

th

erm

oche

mic

al

phys

ical

/che

mic

al

Conversion process

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0

10

20

30

40

50

AK AL

AR

AZ

CA

CO CT

DC

DE FL GA HI

IA ID IL IN KS

KY

LA MA

MD

ME

MI

MN

MO

MS

MT

NC

ND

NE

NH NJ

NM NV

NY

OH

OK

OR

PA RI

SC SD TN TX UT

VA VT

WA

WI

WV

WY

State withdrawal factor (gal/kwh)

Water Intensity in Electricity Generation

0 5 10 15 20 25 30 35 40 45 50

Once through

Recirculating

Cooling pond

Dry cooling

Once through

Recirculating

Cooling pond

Dry cooling

Once through

Recirculating

Cooling pond

Dry cooling

Once through

Recirculating

Cooling pond

Co

nve

nti

on

alco

alN

ucl

ear

NG

CC

*N

G a

nd

oil

Water withdrawal factor (gallons/kwh)

About 3% of the water withdrawn

is consumed

Sources: Wu and Peng, 2011

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Water Use for Energy Production from

Petroleum Oil

Sources: Wu et al. 2009

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• Corn ethanol: 0.7–10.4 gal Midwest regions • Cellulosic ethanol: 0.1–0.3 gal Non-irrigated perennial grass • Algal biodiesel: 3.7–53 gal Open-pond algal biodiesel, with MWW,

southern states • Petroleum gasoline : 0.1–0.3 gal United States, Saudi Arabia, Canadian

oil sand

Life-Cycle Water Footprint of Biofuels

Blue water consumed to drive a passenger car for a mile

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Sources: Wu et al. 2009

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Impact on Water Resource:

Annual Appropriation

Sources: Chiu and Wu 2012

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Change of Total Phosphorus (TP)

Water Quality and Quantity Changes in Upper Mississippi

River Basin under a Selected Billion Ton Scenario

Change of Nitrate (NO3)

Nitrogen, Phosphorus

Sediment

Flow

Evapotranspiration

Soil moisture content

Per ha

Scenario: $50 per dry ton, 2022, with sustainable agricultural residue harvest, USDA baseline

Study demonstrated reduced nutrient loss by growing perennial grass to produce cellulosic biofuel

SWAT modeling

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Sources: Demissie et al. 2012

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Case Study: Corn Stover Scenario

Biofuel Produced from Corn Stover in Iowa Counties

Corn stover based cellulosic ethanol production via hydrolysis and fermentation

Portions of stover removal based on soil sustainability requirement

Sources: Wu et al. under review with WRR

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Blue Water Footprint Affected by Irrigation,

Process Water, and Biorefinery Co-product

Sources: Wu et al. under review with WRR

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Water-biofuel nexus must be examined on regional basis to account for land availability, climate, soil, and water resource factors.

Development of a region-specific biofuel feedstock mix (starch, cellulosic, sugar, and oil crops) is essential for a water-sustainable biofuel production.

Biorefinery site selection should incorporate local water resource constraints, in addition to economic and infrastructure considerations.

Using perennial grass as feedstock can assist soil runoff control and reduce nutrient loss to water body while producing additional biofuels.

Develop Water Sustainable Biofuel Production

through Multiple Resource Planning

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Source: Chiu and Wu 2012

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Thank you !

Contact: [email protected]

Contributors

Argonne National Laboratory

Yi-wen Chiu

Marianne Mintz

Michael Wang

Yonas Demissie

Eugene Yan

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Sponsors

Department of Energy

EERE

Office of Biomass Program

Page 22: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.

Thank you !

Collaborators

National Renewable Energy Laboratory

Andrew Argo

Eric Tan

Danny Inman

Dutta Abhijit

Pacific Northwestern National Laboratory

Corinne Valkenburg

Army Corp Engineers

Zhonglong Zhang

Oak Ridge National Laboratory

Robin Graham (currently ANL)

Matthew Langholtz

Laurence Eaton

Idaho National Laboratory

Dave Muth

Jacob Jacobson

Erin Searcy

Page 23: Assessing Impact of Biofuel Production on Regional Water … · Biofuel feedstock types − Starch Corn, wheat, sorghum, cassava − Oil crops Soybean, rapeseed, palm oil, algae,

References

Arora, S., M. Wu, M. Wang, 2010. Estimated displaced products and ratio of distillers’ co-products from corn ethanol plants and the implications of lifecycle analysis, Biofuels (2010) 1 (6), p.911-922. Demissie, Y., E. Yan, M. Wu. 2012. Assessing Regional Hydrology and Water Quality Implications of Producing One Billion Tons of Feedstock for Biofuel in the United States, Environ. Sci. Technol. http://pubs.acs.org; DOI:10.1021/es300769K. Chiu, Y., M. Wu. 2012. Assessing County-Level Water Footprints of Different Cellulosic-Biofuel Feedstock Pathways, Environ.

Sci. Technol. Accepted. Humbird, D., R. Davis, L. Tao, C. Kinchin, D. Hsu, A. Aden, P. Schoen, J. Lukas, B. Olthof, M. Worley, D. Sexton, D. Dudgeon. 2011. Process Design and Economics for Biochemical Conversion of Lignocellulosic Biomass to Ethanol, Technical Report NREL/TP-5100-47764, Golden, CO. 136P. Jones, S.B., C. Valkenburg, C. Walton, D.C. Elliott, J.E. Holladay, D. J. Stevens, C. Kinchin, S. Czernik, 2009. Production of Gasoline and Diesel from Biomass via Fast Pyrolysis, Hydrotreating and Hydrocracking: A Design Case. Technical Report PNNL-18284 Rev.1. Pacific Northwest National Laboratory, WA. 76P. Miguez, F. E., M. Maughan, G. Bollero, S. P. Long, 2011. Modeling spatial and dynamic variation in growth, yield, and yield stability of the bioenergy crops Miscanthus × giganteus and Panicum virgatum across the conterminous United States, GCB Biology, 4 (5). P. 509-520. US DOE 2011. U.S. Billion Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. R.D. Perlack and B.J. Stokes (Leads), ORNL/TM-2011/224. Oak Ridge National Laboratory, Oak Ridge, TN. 227p. Wu, M. ,Y. Chiu., Y. Demissie. Quantifying the regional water footprint of biofuel production by incorporating hydrologic modeling, under review with Water Resource Research.

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References

Wu, M., Y. Demissie, E. Yan. 2012. Simulated Impact of Future Biofuel Production on Water Quality and Water Cycle Dynamics in the Upper Mississippi River Basin, Biomass and Bioenergy, 41(2012) 44-56. Wu, M., M. Mintz, M. Wang, S. Arora, Y. Chiu. 2011. Consumptive Water Use in the Production of Ethanol and Petroleum Gasoline – 2011 Update, Technical Report ANL/ESD/09-1-Update, Argonne National Laboratory, Argonne, IL. 75P. Wu, M. and J. Peng, 2010. Developing a tool to estimate water use in electric power generation in the United States, Technical Report, ANL/ESD/11-2-Update, Argonne National Laboratory, IL. 51p. Wu, M., Mintz, M. Wang, S. Arora. 2009. Water Consumption in the Production of Ethanol and Petroleum Gasoline, Environmental Management (2009) 44:981-997.