National Renewable Energy Laboratory Innovation for Our Energy Future

Margaret K MannNational Renewable Energy Laboratory

Ethan WarnerGarvin Heath

Biomass Life Cycle Assessment Challenges

LCA Complexity

LCA isn’t just a mass and energy balance• ESPECIALLY for bioenergy systems• Feedstock variability• Technology variability and interactions• Policies• Avoided emissions• Interaction with fossil fuels• Point of views

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Biomass is spatial and varied in nature

Agricultural Residues

Forest Residues Mill Residues

Urban Wood Residues

Farm & WWT Anaerobic Digestion

Dedicated Energy Crops

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+ algae, landfill gas, oil seeds…..

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Ag Residues

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Primary Mill Residues

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Forest Residues

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Biomass is Full of Choices

Multiple energy feedstocks• Ag residues• Forest residues• Mill residues• Urban residues• Dairy and wastewater

Multiple products• Fuels• Power• Chemicals• Consumer goods

Multiple fuels• Ethanol• Jet fuel• Green diesel• DME• Methanol• Mixed OH’s

Multiple processes• Thermochem• Biochem• Combustion• Cofiring• Gasification• Fischer-Tropsch

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Biomass Policies and Policy Creation

48 states have biomass-related financial incentives, many local– Of these, 12 have utility-directed biomass-related incentives

47 states have rules/regulations/policies addressing biomass energy– Of these, 38 are utility-directed

Federal financial incentives with biomass provisions– Depreciation– Corporate tax credit– Federal grant program– Federal loan program– Performance-based incentive

Also federal green power purchasing rules Individual states reviewing eligibility of biomass in RPS (most

notably Massachusetts) EPA evaluating carbon closure of bioenergy systems

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State Renewable Portfolio Standards

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Biomass Deployment and Other Renewables

NREL BioEnergy Atlas

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http://maps.nrel.gov/bioenergyatlas

• Built into Google Maps• Geographically-rich• Data download capable• Zoom and layer• BioFuels Atlas

• State transportation energy use and infrastructure

• Current biofuels facilities• Biofuels potential by region

• BioPower Atlas• Current power consumption

and electric rates• Wind and solar CSP

resource potential• Biopower potential by region

LCA Literature Harmonization

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Context:– Considerable previous work in assessing life

cycle GHG emissions of energy technologies.– But lack of holistic, rigorous evaluation of this

work, especially across technologies in a consistent manner.

– Methodological inconsistency has hampered cross-study comparisons and the usefulness of LCA results in other applications.

– Also, results in the impression amongst policymakers that the state of the science is inconclusive.

Goal and Principle:– Reduce the variability and inconsistency around

estimates of environmental impacts– Make the information useful to decision-makers

in the near term.

Methods (I): Literature Screening

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1. Municipal solid waste, landfill gas, and anaerobic digestion related papers and estimates were collected, but not processed.

2. The 1st (relevance) screen eliminated articles that were:– not a life cycle assessments (LCA) of electricity generation– references that were abstracts, posters, PowerPoint presentations,

conference papers less than five single-spaced pages, and trade journal articles less than three single-spaced pages

– published prior to 1980– not in English.– combined heat and power papers, unless impacts were allocated (or

it was possible to easily allocate) among heat and electricity. 3. Criterion for passing the 2nd (quality) screen:

– Criterion 1: quality methods– Criterion 2: completeness of reporting– Criterion 3: technology of modern relevance

Methods (II): GHG Figure Construction

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Criteria for biopower papers used in figure construction:– Results must be reported in a usable functional unit (e.g. g

CO2e/kWh) or easily converted to a useable functional unit.– Results must be numerically reported.– Results must be non-duplicative.

Life cycle GHG emission data distribution figures:– Initial harmonization steps:

• conversion to a common functional unit• where possible the application of common IPCC 2007 100-year

global warming potentials.• removal of coal portion of biomass co-firing estimates

– Three box and whisker plots• All exclude LUC• Two exclude the coal portion of biomass co-firing estimates

Literature Review Statistics

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Note: Some double counting is inherent in the Totals given that some references investigate more than one technology.

technology category

number of references reviewed

number of references passing the first screen

number of references passing the second screen

number of references providing life cycle GHG emissions estimates

biopower 362 162 84 53coal 273 195 111 59concentrating solar power 114 37 21 18geothermal 45 15 8 6natural gas 220 127 66 49nuclear 241 190 63 34ocean energy 64 30 6 5photovoltaics 400 235 72 23wind 246 171 71 48TOTALS 1965 1162 502 295Biopower - % of total reviewed 45% 23% 15%Biopower - % of those passing 1st screen 52% 33%Biopower - % of those passing 2nd screen 63%

Life Cycle GHG Emissions of Biopower Technologies w/ Coal and Natural Gas Portion of Co-firing (Draft)

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Life Cycle GHG Emissions of Biopower Technologies w/o coal (Draft)

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Life Cycle GHG Emissions of Biopower Feedstock Types w/o Coal, CO2 Mitigation Technology, and AEC (Draft)

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Lessons Learned – Biopower GHGs

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Significant set of existing literature (50+ passing screens)

Considerable variability within pool of studies analyzed– Variability across technologies can be significant– Variability within technologies can also be

significant– Variability across feedstock categories

Method and contextual inconsistency is prevalent– Many dimensions of inconsistency can be

harmonized– Other dimensions are more difficult (e.g. co-

product credits and geography)

Literature reporting

Literature coverage

Next Harmonization Steps

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Already complete:– Global warming potential– Coal contribution to co-firing

Potential simple options:– LCA scope (system boundary)– Facility parameters (lifetime, capacity factor, etc.)

Some potential complex options could include:– Location/yields and/or feedstocks (interlinked)– Co-product allocation methods and/or avoided

emission credits– Technology (at a higher resolution)

Movement into the complex options requires construction of meta-models that incorporate multiple assumptions and scenarios, to better understand drivers of inconsistency.

IMPORTANT: There is not one answer, as there is not one biomass system

Thank you!

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Margaret MannNational Renewable Energy LaboratoryGolden, ColoradoMargaret.mann@nrel.gov303-275-2921