Cited by 1,128Agriculture Sustainability and Environmental ImpactClimate change impacts on agricultureClimate Change Policy and Economics

The DOI matches its Crossref record; 52 of the 53 references it cites were found in a registry or an index; none of the 45 sources its claims cite is checked for support yet.

Greenhouse gas mitigation by agricultural intensification

Open access
Burney, Jennifer A., Davis, Steven J., Lobell, David B.·2010·Proceedings of the National Academy of Sciences

Abstract

As efforts to mitigate climate change increase, there is a need to identify cost-effective ways to avoid emissions of greenhouse gases (GHGs). Agriculture is rightly recognized as a source of considerable emissions, with concomitant opportunities for mitigation. Although future agricultural productivity is critical, as it will shape emissions from conversion of native landscapes to food and biofuel crops, investment in agricultural research is rarely mentioned as a mitigation strategy. Here we estimate the net effect on GHG emissions of historical agricultural intensification between 1961 and 2005. We find that while emissions from factors such as fertilizer production and application have increased, the net effect of higher yields has avoided emissions of up to 161 gigatons of carbon (GtC) (590 GtCO 2 e) since 1961. We estimate that each dollar invested in agricultural yields has resulted in 68 fewer kgC (249 kgCO 2 e) emissions relative to 1961 technology ($14.74/tC, or ∼$4/tCO 2 e), avoiding 3.6 GtC (13.1 GtCO 2 e) per year. Our analysis indicates that investment in yield improvements compares favorably with other commonly proposed mitigation strategies. Further yield improvements should therefore be prominent among efforts to reduce future GHG emissions.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper estimates that historical agricultural intensification from 1961 to 2005 avoided large greenhouse gas emissions by sparing land conversion, with an upper estimate of 161 GtC (590 GtCO2e) and a lower-bound estimate of 86.5 GtC. It concludes that investment in yield improvements compares favorably with other mitigation strategies and should be prominent in efforts to reduce future emissions.

Key findings

  • Yield gains since 1961 avoided 161 GtC (+104.2/−41.9 GtC) in the AW1 scenario, averaging 3.6 GtC/yr (+2.3/−0.9 GtC/yr), equal to 34% of the 478 GtC emitted by humans between 1850 and 2005. The lower-bound AW2 scenario avoided 86.5 GtC (±24.7 GtC), averaging 1.9 GtC/yr (±0.5 GtC/yr), or 18% of that total.
  • AW1 would have required an additional 1,761 Mha of cropland (1,514 Mha more than the real world); AW2 would have required an additional 1,111 Mha (864 Mha more than the real world). Land conversion dominated emissions, with a global average of 105 ±21 tC/ha lost in conversion of land to cropland.
  • Each dollar invested in agricultural yields resulted in 68 fewer kgC (249 kgCO2e) emissions relative to 1961 technology, at $14.74/tC (∼$4/tCO2e) in AW1 and $27.43/tC in AW2 under the refined estimate; simple estimates were $7.16/tC and $13.32/tC. This compares favorably with other options available at <$73/tC: buildings (1.49 GtC/yr), energy supply (0.49 GtC/yr), transportation (0.46 GtC/yr), and industry (0.30 GtC/yr).
  • Context: between 1961 and 2005 population rose 111% (3.08 to 6.51 billion), crop production rose 162% (1.8 to 4.8 billion tons), cropland grew 27% (960 to 1,208 Mha), and total crop yield increased 135% (1.84 to 3.96 t/ha). In 2005 agricultural production accounted for 1.4–1.7 GtC emissions (10–12% of anthropogenic GHG emissions), with land use change adding 1.5 GtC.

Methods

  • The authors calculated agricultural GHG emissions for 1961–2005 and two counterfactual “alternative world” scenarios: AW1 held 1961 yields and fertilizer application rates while meeting real-world production and living standards; AW2 maintained 1961 per capita production using population projections based on 1950–1955 fertility and mortality rates.
  • Emissions included N2O from agricultural soils, CH4 from rice cultivation, carbon released from biomass and soil during conversion of forest, shrub, and grassland to cropland, and N2O, CH4, and CO2 from production and use of nitrogenous, phosphate, and potash fertilizers. The analysis used FAO production and yield data, IPCC Tier 1 guidelines, GREET emissions factors, biome carbon values, and cropland-only accounting.
  • Cost-effectiveness was assessed using public and private agricultural research spending from 1961 to 2005, with assumptions about the fraction of research relevant to yield improvements and the share of productivity growth attributable to agricultural R&D.

Limitations

  • Stated: the counterfactual scenarios are not dynamic; AW1 assumes demand for agricultural products would have been identical without yield improvements, ignoring food-price effects (real prices fell by ∼40% between 1965 and 2000), and AW2 is a lower bound with a more dire lower-bound scenario acknowledged.
  • Stated: the analysis excludes livestock, burning of agricultural residues, pesticides, fuel use, agricultural machinery, irrigation, transport, pastureland, and biofuels, and neglects projected increases in meat demand as per capita GDP grows; land carbon values carry ±20% uncertainty.
  • Evident: results depend on scenario assumptions and broad cost-effectiveness ranges, and the paper notes difficulty identifying hypothetical expansion regions and the portions of agricultural investment relevant to yield improvements.

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Integrity signals

Registry

Crossref · 10.1073/pnas.0914216107

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

31 Not checked yet · 11 Own method · 8 Own result · 5 No basis given · 4 Own interpretation

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Show all 21 claims

  • It may state two separate claims as one. 20
  • Probably not a substantial claim. 28
38 of 38
  • The authors state this as an assumption.

    The AW1 scenario exogenously specifies that demand for agricultural products over time would have been identical without yield improvements.

    “for example, the AW1 scenario exogenously specifies that demand for agricultural products over time would have been identical without yield improvements, thus ignoring the role of food prices (which fell in real terms by ∼40% between 1965 and 2000)”
  • The authors state this as an assumption.

    Even without increased agricultural productivity, income growth from productivity gains in other sectors, as well as higher crop demand for nonfood uses, would nevertheless have kept per capita demand at 1961 levels despite any price increases.

    “However, we assume that even without increased agricultural productivity, income growth from productivity gains in other sectors, as well as higher crop demand for nonfood uses, would nevertheless have kept per capita demand at 1961 levels despite any price increases”
  • The authors state this as an assumption.

    Yield advancements are directly related to research funding.

    “Assuming that yield advancements are directly related to research funding, we assess the cost-effectiveness of mitigation through yield improvements using the ratio of public and private spending on agricultural research since 1961”
  • The authors state this as an assumption.

    A slightly more conservative assumption that 70% of all public and private research was relevant to yield improvements.

    “For the global case, a slightly more conservative assumption that 70% of all public and private research was relevant to yield improvements gives a cumulative 45-year total of $806 billion in agricultural investments.”
  • The authors state this as an assumption.

    A conservative estimate that the AW2 scenario included no intensive livestock operations.

    “thus, a conservative estimate that the AW2 scenario included no intensive livestock operations results in a savings of up to ∼0.58 GtC/yr (∼2.1 GtCO2e/yr) in the livestock sector compared with the RW.”
  • The authors state this as an assumption.

    Emissions due to burning of agricultural residues can be conservatively assumed to be 15% lower in AW2 than the real world.

    “Emissions due to burning of agricultural residues can be conservatively assumed to be 15% lower in AW2 than RW (the difference in total production), although we do not calculate burning emissions for the RW.”
  • The authors state this as an assumption.

    An assumption of constant intensity for machinery and irrigation results in 5% more irrigated land and 17% fewer agricultural tractors in the AW2 scenario compared with the real world.

    “An assumption of constant intensity for machinery and irrigation results in 5% more irrigated land and 17% fewer agricultural tractors in the AW2 scenario compared with the RW.”
  • The authors state this as an assumption.

    Fertilizer application rates remain at 1961 levels in both AW scenarios.

    “We assume fertilizer application rates remain at 1961 levels in both AW scenarios, and scale fertilizer consumption and associated production emissions accordingly.”
  • The authors state this as an assumption.

    For both AW expansion scenarios, the percentages of rain-fed and irrigated rice systems are the same as in the RW, and drainage practices and organic amendments are the same in each scenario.

    “For both AW expansion scenarios, we assume that the percentages of rain-fed and irrigated systems are the same as in the RW, and that drainage practices and organic amendments are the same in each scenario.”
  • The authors state this as an assumption.

    The same public funding percentage applies to developing and developed world when estimating total agricultural spending in each time period.

    “We use the values for public research spending in 1981, 1991, and 2000, and use the same public funding percentage for developing and developed world to estimate total spending in each time period.”
  • The authors state this as an assumption.

    Agricultural investment spending grew at a rate of 4.5% between 1961 and 1981.

    “We assume a growth rate of 4.5% in spending between 1961–1981, and use the 1981 value to extrapolate back in time”
  • The authors state this as an assumption.

    Agricultural investment increased linearly from 1981 to 2000.

    “we assume a linear increase from 1981 to 2000”
  • The authors state this as an assumption.

    Agricultural investment grew at 2.1% annually from 2001 to 2005.

    “we estimate the values for 2001–2005 assuming a 2.1% annual growth in agricultural investment ([30](#r30)).”
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Citations

Cites

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Research works printed but not linked: 3

  1. ; U.S. Environmental Protection Agency Global Anthropogenic Non-CO2 Greenhouse Gas Emissions, 1990–2020. EPA Report 430-R-06-003. (U.S. Environmental Protection Agency, Washington, DC, 2006).
  2. 10.1079/sum2005291 · DOI
  3. RE Evenson, C Pray, MW Rosegrant Agricultural Research and Productivity Growth in India (International Food Policy Research Institute, Washington, DC, 1998).

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Metadata

Authors
Burney, J. A., Davis, S. J., & Lobell, D. B.
Affiliations
  • Stanford University (US)
  • Carnegie Institution for Science (US)
Venue
Proceedings of the National Academy of Sciences
Published
2010-06-15
Volume
107
Issue
26
Pages
12052-12057
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2149362589
Cited by
1,128
References
53
Citations by year
2026: 59 · 2025: 53 · 2024: 62 · 2023: 69 · 2022: 76 · 2021: 99 · 2020: 74 · 2019: 87 · 2018: 72 · 2017: 56 · 2016: 57 · 2015: 66 · 2014: 73 · 2013: 76 · 2012: 80
FWCI
65.01
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Aeronautics and Space Administration (NNX08AV25G)
  • Carnegie Institution of Washington
Topics
  • Physical Sciences › Environmental Science › Ecology › Agriculture Sustainability and Environmental Impact
  • Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Climate change impacts on agriculture
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
Keywords
greenhouse gas emissions reduction, agricultural intensification, agricultural emissions, crop yield improvement, fertilizer emissions, CO2 emissions, agricultural research investment, land use change, energy crops

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