Skip to main content

Advertisement

SpringerLink
Log in

Land cover change from cotton to corn in the USA relieves freshwater ecotoxicity impact but may aggravate other regional environmental impacts

  • LAND USE IN LCA
  • Published:
The International Journal of Life Cycle Assessment Aims and scope Submit manuscript

Abstract

Purpose

Rising corn prices in the USA due partly to increasing ethanol demands have led to a significant expansion of corn areas displacing natural vegetation and crops including cotton. From 2005 to 2009, cotton area harvested in the USA nearly halved with a reduction of 2.5 million hectares, while that of corn increased by 1.8 million hectares. However, environmental impacts of land shifts from cotton and corn have been largely neglected in literature.

Methods

In this study, we evaluate the environmental properties of US corn and cotton production and implications of land cover change from cotton to corn using state-specific data and life cycle impact assessment. Focusing on regional environmental issues, we cover both on-farm direct emissions such as different types of volatile organic compounds and pesticides and indirect emissions embodied in input materials such as fertilizers. TRACI 2.0 is used to evaluate the environmental impacts of these emissions.

Results and discussion

The results show that US cotton and corn productions per hectare on average generate roughly similar impacts for most impact categories such as eutrophication and smog formation. For water use and freshwater ecotoxicity, corn shows a smaller impact. When land shifts from cotton to corn in cotton-growing states, however, the process may aggravate most of the regional environmental impacts while relieving freshwater ecotoxicity impact. The differences in the two estimates are due mainly to underlying regional disparities in crop suitability that affects input structure and environmental emissions.

Conclusions

Our results highlight the importance of potential, unintended environmental impacts that cannot be adequately captured when average data are employed. Understanding the actual mechanisms under which certain policy induces marginal changes at a regional and local level is crucial for evaluating its net impact. Further, our study calls for an attention to biofuel-induced land cover change between crops and associated regional environmental impacts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Andrade de Sá S, Palmer C, Di Falco S (2013) Dynamics of indirect land-use change: empirical evidence from Brazil. J Environ Econ Manag 65:377–393

    Article  Google Scholar 

  • Arima EY, Richards P, Walker R, Caldas MM (2011) Statistical confirmation of indirect land use change in the Brazilian Amazon. Environ Res Lett 6:024010

    Article  Google Scholar 

  • Babcock B (2009) Measuring unmeasurable land-use changes from biofuels. Iowa Ag Rev 15:3

    Google Scholar 

  • Bare J (2011) TRACI 2.0: the tool for the reduction and assessment of chemical and other environmental impacts 2.0. Clean Technol Environ Policy 13:687–696. doi:10.1007/s10098-010-0338-9

    Article  CAS  Google Scholar 

  • Bare J, Norris G, Pennington D, McKone T (2003) The tool for the reduction and assessment of chemical and other environmental impacts. J Ind Ecol 6:49–78

    Article  Google Scholar 

  • Berthoud A, Maupu P, Huet C, Poupart A (2011) Assessing freshwater ecotoxicity of agricultural products in life cycle assessment (LCA): a case study of wheat using French agricultural practices databases and USEtox model. Int J Life Cycle Assess 16:841–847

    Article  CAS  Google Scholar 

  • Brandão M, Clift R, Cowie A, Greenhalgh S (2014) The use of life cycle assessment in the support of robust (climate) policy making: comment on “Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation”. J Ind Ecol 18:461–463

    Article  Google Scholar 

  • Chiu Y, Walseth B, Suh S (2009) Water embodied in bioethanol in the United States. Environ Sci Technol 43:2688–2692

    Article  CAS  Google Scholar 

  • Claassen R, Carriazo F, Cooper JC et al (2011) Grassland to cropland conversion in the Northern Plains. Economic Research Service, U.S. Department of Agriculture, Washington DC

  • Dale BE, Kim S (2014) Can the predictions of consequential life cycle assessment be tested in the real world? comment on “Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation”. J Ind Ecol 18:466–467

    Article  Google Scholar 

  • Ecoinvent (2014) Database. In: Ecoinvent Database V22. http://www.ecoinvent.org/database

  • EPA (1999) Background report on fertilizer use, contaminants and regulations. National Program Chemicals Division, Office of Pollution Provention and Toxics, U.S. Environmental protection Agency, Colombus, OH, USA

  • EPA (1995) Emissions Factors & AP 42, Compilation of Air Pollutant Emission Factors, Chapter 9: Food and Agricultural Industries. United States Environmental Protection Agency, Washington, DC, USA

  • Fanin JM, Paxon KM, Barreca JD (2008) Evaluating the Shift from Cotton to Corn: Impacts on the Louisiana Economy. Agricultural Center, Louisiana State University, Baton Rouge LA

  • Fargione J, Hill J, Tilman D et al (2008) Land clearing and the biofuel carbon debt. Science 319:1235–1238

    Article  CAS  Google Scholar 

  • Gelfand I, Zenone T, Jasrotia P et al (2011) Carbon debt of conservation reserve program (CRP) grasslands converted to bioenergy production. Proc Natl Acad Sci U S A 108:13864–13869

    Article  CAS  Google Scholar 

  • Goebes MD, Strader R, Davidson C (2003) An ammonia emission inventory for fertilizer application in the United States. Atmos Environ 37:2539–2550

    Article  CAS  Google Scholar 

  • Goedkoop MJ, Heijungs R, Huijbregts M et al (2009) ReCiPe 2008, A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level; First edition Report I: Characterization. http://www.lcia-recipe.net/

  • Guinee JB, Gorree M, Heijungs R et al (2002) Handbook on life cycle assessment: operational guide to the ISO standards. Kluwer Academic Pubisher, Dordrecht, the Netherlands

  • Herner AE (1992) The USDA-ARS pesticide properties database: a consensus data set for modelers. Weed Technol 6:749–752

    CAS  Google Scholar 

  • Hertel TW, Golub AA, Jones AD et al (2010) Effects of US maize ethanol on global land use and greenhouse gas emissions: estimating market-mediated responses. Bioscience 60:223–231

    Article  Google Scholar 

  • Hertwich E (2014) Understanding the climate mitigation benefits of product systems: comment on “Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation”. J Ind Ecol 18:464–465

    Article  Google Scholar 

  • Hill J, Nelson E, Tilman D et al (2006) Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. Proc Natl Acad Sci U S A 103:11206–11210

    Article  CAS  Google Scholar 

  • Hill J, Polasky S, Nelson E et al (2009) Climate change and health costs of air emissions from biofuels and gasoline. Proc Natl Acad Sci U S A 106:2077–2082

    Article  CAS  Google Scholar 

  • ISO (2006) ISO 14042, environmental management-life cycle assessment-life cycle impact assessment. International Organization for Standardization, Geneve

    Google Scholar 

  • Jackson RB, Jobbágy EG, Avissar R et al (2005) Trading water for carbon with biological carbon sequestration. Science 310:1944–1947

    Article  CAS  Google Scholar 

  • Keeney D (2008) Ethanol USA. Environ Sci Technol 43:8–11

    Article  Google Scholar 

  • Keeney R (2010) Yield response and biofuels: issues and evidence on the extensive margin. World Congress of Environmental and Resource Economists

  • Krauter C, Goorahoo D, Potter C, Klooster S (2002) Ammonia emissions and fertilizer applications in California’ s Central Valley

  • Liska A, Yang H, Bremer V et al (2009) Improvements in life cycle energy efficiency and greenhouse gas emissions of corn ethanol. J Ind Ecol 13:58–74

    Article  CAS  Google Scholar 

  • Malcolm S, Claassen R, Nickerson C (2009) Ethanol and a changing agricultural landscape. Economic Research Service, US Department of Agriculture, Washington, DC, USA

  • Mathiesen BV, Münster M, Fruergaard T (2009) Uncertainties related to the identification of the marginal energy technology in consequential life cycle assessments. J Clean Prod 17:1331–1338

    Article  Google Scholar 

  • Miller S, Landis A, Theis T (2006) Use of Monte Carlo analysis to characterize nitrogen fluxes in agroecosystems. Environ Sci Technol 40:2324–2332

    Article  CAS  Google Scholar 

  • Mortvedt J (1995) Heavy metal contaminants in inorganic and organic fertilizers. Nutr Cycl Agroecosyst 43:55–61

    CAS  Google Scholar 

  • Plevin RJ, Delucchi MA, Creutzig F (2014) Using attributional life cycle assessment to estimate climate-change mitigation benefits misleads policy makers. J Ind Ecol 18:73–83

    Article  Google Scholar 

  • Plevin R, Jones A, Torn M, Gibbs H (2010) Greenhouse gas emissions from biofuels’ indirect land use change are uncertain but may be much greater than previously estimated. Environ Sci Technol 44:8015–8021

    Article  CAS  Google Scholar 

  • RFA (2013) Industry Statistics. http://www.ethanolrfa.org/pages/statistics. Accessed 18 Dec 2013

  • Rosenbaum RK, Bachmann TM, Gold LS et al (2008) USEtox—the UNEP-SETAC toxicity model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int J Life Cycle Assess 13:532–546

    Article  CAS  Google Scholar 

  • Runge F, Johnson R (2008) The browning of biofuels: environment and food security at risk. Woodrow Wilson International Center for Scholars, Washington, DC, USA

  • Sanchez ST, Woods J, Akhurst M et al (2012) Accounting for indirect land-use change in the life cycle assessment of biofuel supply chains. J R Soc Interface R Soc 9:1105–1119

    Article  Google Scholar 

  • Searchinger T, Heimlich R, Houghton R et al (2008) Use of US croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319:1238–1240

    Article  CAS  Google Scholar 

  • Secchi S, Gassman PW, Jha M et al (2010) Potential water quality changes due to corn expansion in the Upper Mississippi River Basin. Ecol Appl 21:1068–1084

    Article  Google Scholar 

  • Shapouri H, Gallagher PW, Nefstead W et al (2010) 2008 Energy balance for the corn-ethanol industry. U.S. Department of Agriculture, Washington, DC, USA

  • Schmidt JH, Weidema BP (2008) Shift in the marginal supply of vegetable oil. Int J Life Cycle Assess 13:235–239

    Article  Google Scholar 

  • Socolow RH (1999) Nitrogen management and the future of food: lessons from the management of energy and carbon. Proc Natl Acad Sci U S A 96:6001–6008

    Article  CAS  Google Scholar 

  • Suh S, Yang Y (2014) On the uncanny capabilities of consequential LCA. Int J Life Cycle Assess 19:1179–1184

    Article  Google Scholar 

  • Tessum CW, Marshall JD, Hill JD (2012) A spatially and temporally explicit life cycle inventory of air pollutants from gasoline and ethanol in the United States. Environ Sci Technol 46(20):11408–11417

    Article  CAS  Google Scholar 

  • Tsao C-C, Campbell JE, Mena-Carrasco M et al (2012) Biofuels that cause land-use change may have much larger non-GHG air quality emissions than fossil fuels. Environ Sci Technol 46:10835–10841

    Article  CAS  Google Scholar 

  • USDA (2014a) Cropland data layer metadata. http://www.nass.usda.gov/research/Cropland/SARS1a.htm. Accessed 13 Mar 2014

  • USDA (2014b) Quick Stats. http://www.nass.usda.gov/Quick_Stats/. Accessed 13 Mar 2014

  • USDA (2004) Energy use on major field crops in surveyed states. Economic Research Service, US Department of Agriculture, Washington, DC, USA

  • USDA (2014c) Farm and Ranch Irrigation Survey 2008 and 2003. http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Farm_and_Ranch_Irrigation_Survey/index.php. Accessed 13 Mar 2014

  • USDA (2006) Model simulation of soil loss, nutrient loss, and change in soil organic carbon associated with crop production. Natural Resource Concervation Service, US Department of Agriculture, USA

  • USDA (2000) Environmental indicators of pesticides leaching and runoff from farm fields. Natural Resource Conservation Service, US Department of Agriculture, USA

  • Wallander S, Claassen R, Nickerson C (2011) The ethanol decade: an expansion of US corn production, 2000-09. US Department of Agriculture, Economic Research Service, Washington, DC, USA

  • Wang M (2013) The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Model, 2012

  • Wang MQ, Han J, Haq Z et al (2011) Energy and greenhouse gas emission effects of corn and cellulosic ethanol with technology improvements and land use changes. Biomass Bioenergy 35:1885–1896

    Article  CAS  Google Scholar 

  • Weidema BP, Frees N, Nielsen AM (1999) Marginal production technologies for life cycle inventories. Int J Life Cycle Assess 4:48–56

    Article  Google Scholar 

  • Wright CK, Wimberly MC (2013) Recent land use change in the Western Corn Belt threatens grasslands and wetlands. Proc Natl Acad Sci U S A 110:4134–4139

    Article  CAS  Google Scholar 

  • Yang Y (2013) Life cycle freshwater ecotoxicity, human health cancer, and noncancer impacts of corn ethanol and gasoline in the US. J Clean Prod 53:149–157

    Article  CAS  Google Scholar 

  • Yang Y, Bae J, Kim J, Suh S (2012) Replacing gasoline with corn ethanol results in significant environmental problem-shifting. Environ Sci Technol 46:3671–3678

    Article  CAS  Google Scholar 

  • Yienger JJ, Levy H (1995) Empirical model of global soil-biogenic NOχ emissions 1984–2012. J Geophys Res Atmospheres 100:11447–11464

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, 93106-5131, USA

    Yi Yang & Sangwon Suh

Authors
  1. Yi Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sangwon Suh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sangwon Suh.

Additional information

Responsible editor: Greg Thoma

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 2305 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Y., Suh, S. Land cover change from cotton to corn in the USA relieves freshwater ecotoxicity impact but may aggravate other regional environmental impacts. Int J Life Cycle Assess 20, 196–203 (2015). https://doi.org/10.1007/s11367-014-0817-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11367-014-0817-z

Keywords

Search

Navigation