Cited by 169Bioenergy crop production and managementBiofuel production and bioconversionEnvironmental Impact and Sustainability

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index; 1 of the 14 sources its claims cite were checked for support.

Land-use change and greenhouse gas emissions from corn and cellulosic ethanol

Open access
Dunn, Jennifer B, Mueller, Steffen, Kwon, Ho-young, Wang, Michael Q·2013·Biotechnology for Biofuels

Abstract

BACKGROUND: The greenhouse gas (GHG) emissions that may accompany land-use change (LUC) from increased biofuel feedstock production are a source of debate in the discussion of drawbacks and advantages of biofuels. Estimates of LUC GHG emissions focus mainly on corn ethanol and vary widely. Increasing the understanding of LUC GHG impacts associated with both corn and cellulosic ethanol will inform the on-going debate concerning their magnitudes and sources of variability. RESULTS: In our study, we estimate LUC GHG emissions for ethanol from four feedstocks: corn, corn stover, switchgrass, and miscanthus. We use new computable general equilibrium (CGE) results for worldwide LUC. U.S. domestic carbon emission factors are from state-level modelling with a surrogate CENTURY model and U.S. Forest Service data. This paper investigates the effect of several key domestic lands carbon content modelling parameters on LUC GHG emissions. International carbon emission factors are from the Woods Hole Research Center. LUC GHG emissions are calculated from these LUCs and carbon content data with Argonne National Laboratory's Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) model. Our results indicate that miscanthus and corn ethanol have the lowest (-10 g CO2e/MJ) and highest (7.6 g CO2e/MJ) LUC GHG emissions under base case modelling assumptions. The results for corn ethanol are lower than corresponding results from previous studies. Switchgrass ethanol base case results (2.8 g CO2e/MJ) were the most influenced by assumptions regarding converted forestlands and the fate of carbon in harvested wood products. They are greater than miscanthus LUC GHG emissions because switchgrass is a lower-yielding crop. Finally, LUC GHG emissions for corn stover are essentially negligible and insensitive to changes in model assumptions. CONCLUSIONS: This research provides new insight into the influence of key carbon content modelling variables on LUC GHG emissions associated with the four bioethanol pathways we examined. Our results indicate that LUC GHG emissions may have a smaller contribution to the overall biofuel life cycle than previously thought. Additionally, they highlight the need for future advances in LUC GHG emissions estimation including improvements to CGE models and aboveground and belowground carbon content data.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This study estimates land-use change (LUC) greenhouse gas (GHG) emissions for ethanol from corn, corn stover, switchgrass, and miscanthus using GTAP CGE results and Argonne’s CCLUB/GREET models. It finds corn ethanol has the highest base-case LUC GHG emissions (7.6 g CO2e/MJ), miscanthus the lowest (−10 g CO2e/MJ), and corn stover essentially negligible.

Key findings

  • Base-case LUC GHG emissions were 7.6 g CO2e/MJ for corn ethanol, 2.8 g CO2e/MJ for switchgrass ethanol, −10 g CO2e/MJ for miscanthus ethanol, and essentially negligible for corn stover.
  • Across all modelled parameter combinations, LUC GHG emissions ranged from 4.7 to 11 g CO2e/MJ for corn, 2.7 to 19 g CO2e/MJ for switchgrass, −10 to −2.1 g CO2e/MJ for miscanthus, and −1.21 g CO2e/MJ for corn stover.
  • Switchgrass results were most sensitive to assumptions about converted forestlands and harvested wood product (HWP) carbon fate; accounting for HWP sequestration reduced switchgrass LUC GHG emissions by 3–4 g CO2e/MJ, and applying the forest proration factor (FPF) reduced them by 2–3 g CO2e/MJ.
  • Corn ethanol LUC GHG emissions were lower than in previous studies, and at most contributed 20% of life-cycle GHG emissions for corn ethanol.

Methods

  • Used worldwide LUC results from Purdue University’s GTAP computable general equilibrium model for four scenarios: corn ethanol expansion to 57 BL, plus corn stover (+35 BL), miscanthus (+27 BL), or switchgrass (+27 BL).
  • Combined GTAP land transitions with domestic state-level soil organic carbon emission factors from a surrogate CENTURY model and U.S. Forest Service data, international carbon emission factors from Woods Hole Research Center, and aboveground forest carbon data from USDA Forest Service/NCASI COLE.
  • Calculated LUC GHG emissions with Argonne National Laboratory’s CCLUB model and placed results in a life-cycle context using GREET; sensitivity analyses varied surrogate CENTURY parameters (soil cultivation coefficient, crop yield increase, erosion) and CCLUB parameters (HWP fate, FPF, tillage).

Limitations

  • The paper states that addressing CGE model assumptions and their impact on LUC GHG emissions is outside its scope, and it used only one set of GTAP results; it notes that uncertainty associated with GTAP and similar models is large and difficult to estimate.
  • The paper states that future advances are needed in CGE models and aboveground/belowground carbon content data, including global SOC data and further calibration of CENTURY parameters.
  • The text makes evident that direct and indirect LUC could not be distinguished in GTAP results, and the forest proration factor was applied to reconcile forest land area differences among GTAP, the National Land Cover Dataset, and U.S. Forest Service data.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/1754-6834-6-51

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Figure 1 Distribution of AEZs in the United States.
Figure 1 Distribution of AEZs in the United States.CC BY · PubMed Central
Figure 2 Domestic LUC for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Negative values indicate a decrease in land area.
Figure 2 Domestic LUC for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Negative values indicate a decrease in land area.CC BY · PubMed Central
Figure 3 International LUC for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Negative and positive values indicate a decrease and increase, respectively, in land area.
Figure 3 International LUC for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Negative and positive values indicate a decrease and increase, respectively, in land area.CC BY · PubMed Central
Figure 4 Soil organic carbon content changes from domestic land-use transitions. Legend: Solid and hollow markers denote transitions in AEZs 7 and 10, respectively. Forest, grassland, and cropland-pasture transitions are denoted by circles, squares, and triangles, respectively. Orange, red, green, and blue markers reflect transitions to corn, corn stover, miscanthus, and switchgrass production, respectively. These results were generated from surrogate CENTURY modelling runs with calibrated soil cultivation effect coefficients, feedstock yields that increase with time, and with erosion effects.
Figure 4 Soil organic carbon content changes from domestic land-use transitions. Legend: Solid and hollow markers denote transitions in AEZs 7 and 10, respectively. Forest, grassland, and cropland-pasture transitions are denoted by circles, squares, and triangles, respectively. Orange, red, green, and blue markers reflect transitions to corn, corn stover, miscanthus, and switchgrass production, respectively. These results were generated from surrogate CENTURY modelling runs with calibrated soil cultivation effect coefficients, feedstock yields that increase with time, and with erosion effects.CC BY · PubMed Central
Figure 5 Forest carbon emission factor for four feedstocks in AEZs 7 and 10. Legend: SOC values were calculated with modelling option “sd” in Table 4.
Figure 5 Forest carbon emission factor for four feedstocks in AEZs 7 and 10. Legend: SOC values were calculated with modelling option “sd” in Table 4.CC BY · PubMed Central
Figure 6 Base case LUC GHG emissions (g CO2e/MJ) for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Domestic LUC GHG emissions were calculated with modelling option “sd” in Table 4, adopting the FPF, and assuming sequestration of 42% of aboveground live and dead tree carbon in HWP.
Figure 6 Base case LUC GHG emissions (g CO2e/MJ) for switchgrass, miscanthus, corn stover, and corn ethanol. Legend: Domestic LUC GHG emissions were calculated with modelling option “sd” in Table 4, adopting the FPF, and assuming sequestration of 42% of aboveground live and dead tree carbon in HWP.CC BY · PubMed Central
Figure 7 LUC (ha/MJ × 106) and LUC GHG emissions (g CO2e/MJ) from selected land conversions. Legend: Solid and hollow bars represent LUC amounts and LUC GHG emissions, respectively. Orange, red, blue, and green bars indicate feedstocks of corn, corn stover, switchgrass, and miscanthus, respectively. Results reflect base case modelling conditions.
Figure 7 LUC (ha/MJ × 106) and LUC GHG emissions (g CO2e/MJ) from selected land conversions. Legend: Solid and hollow bars represent LUC amounts and LUC GHG emissions, respectively. Orange, red, blue, and green bars indicate feedstocks of corn, corn stover, switchgrass, and miscanthus, respectively. Results reflect base case modelling conditions.CC BY · PubMed Central
Figure 8 Surrogate CENTURY parameters’ impact on domestic ethanol LUC GHG emissions for (a) conventionally-tilled corn (b) switchgrass and miscanthus. Legend: Solid and hollow shapes indicated surrogate CENTURY modelling with default and calibrated soil cultivation effect coefficients, respectively. Shapes with solid and dashed outlines represent surrogate CENTURY runs with constant and increasing yields, respectively. Diamond markers represent switchgrass results; square markers represent miscanthus results. All results except those indicated include erosion effects. In all cases, HWP sequesters 42% of aboveground live and dead tree carbon and the FPF is applied.
Figure 8 Surrogate CENTURY parameters’ impact on domestic ethanol LUC GHG emissions for (a) conventionally-tilled corn (b) switchgrass and miscanthus. Legend: Solid and hollow shapes indicated surrogate CENTURY modelling with default and calibrated soil cultivation effect coefficients, respectively. Shapes with solid and dashed outlines represent surrogate CENTURY runs with constant and increasing yields, respectively. Diamond markers represent switchgrass results; square markers represent miscanthus results. All results except those indicated include erosion effects. In all cases, HWP sequesters 42% of aboveground live and dead tree carbon and the FPF is applied.CC BY · PubMed Central
Figure 9 HWP and FPF impact on domestic ethanol LUC GHG emissions for (a) switchgrass and (b) corn. Legend: In Figures 9a and 9b, solid circles represents results calculated with the FPF applied. Hollow circles represent results using default GTAP results for area of converted forests. In Figure 9b, solid bordered circles represent results that account for some carbon sequestration in HWP. Circles with dashed borders are used for results that assume no carbon is sequestered in HWP.
Figure 9 HWP and FPF impact on domestic ethanol LUC GHG emissions for (a) switchgrass and (b) corn. Legend: In Figures 9a and 9b, solid circles represents results calculated with the FPF applied. Hollow circles represent results using default GTAP results for area of converted forests. In Figure 9b, solid bordered circles represent results that account for some carbon sequestration in HWP. Circles with dashed borders are used for results that assume no carbon is sequestered in HWP.CC BY · PubMed Central

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  • The authors state this as an assumption.

    Corn stover is treated as a waste product of corn production rather than a co-product.

    “this result is unsurprising because stover is modelled as a “waste” product of corn production (as opposed to a co-product).”
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Metadata

Authors
Dunn, J. B., Mueller, S., Kwon, H.-Y., & Wang, M. Q.
Affiliations
  • Argonne National Laboratory (US)
  • University of Illinois Chicago (US)
Corresponding author
Dunn, Jennifer B
Venue
Biotechnology for Biofuels
Published
2013
Volume
6
Issue
1
Pages
51
ISSN
1754-6834 (ISSN-L)
OpenAlex
W2152396357
Cited by
167
References
29
Citations by year
2026: 4 · 2025: 10 · 2024: 8 · 2023: 9 · 2022: 10 · 2021: 18 · 2020: 15 · 2019: 4 · 2018: 16 · 2017: 18 · 2016: 15 · 2015: 13 · 2014: 15 · 2013: 11
FWCI
38.25
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Biotechnology for Biofuels (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • U.S. Department of Energy (DE‐ AC02‐06CH11357, Contract No. DE-AC02-06CH11357., AC02‐06CH11357, 06CH11357, No. DE-AC02-06CH11357, DE-AC02-)
  • Purdue University
  • University of Chicago (DE-AC02-06CH11357)
  • University of Illinois at Urbana-Champaign
  • Biomass Program (DE-AC02-06CH11357)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Bioenergy crop production and management
  • Physical Sciences › Engineering › Biomedical Engineering › Biofuel production and bioconversion
  • Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
Keywords
land use change, greenhouse gas emissions, bioethanol, corn ethanol, cellulosic ethanol, corn stover, switchgrass, Miscanthus, biofuel feedstock, computable general equilibrium model, harvested wood products

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