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Title: US major crops’ uncertain climate change risks and greenhouse gas mitigation benefits

In this study, we estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops' yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. Uncontrolled warming's economic effects on major crops are slightly positive—annual benefits <$4 B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17 B under moderate mitigation, but only $7 B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18 B, generating benefits to moderate (stringent) mitigation as large as $26 B ($20 B).
 [1] ;  [2] ;  [3] ;  [4]
  1. Boston Univ., Boston, MA (United States)
  2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  3. NMR Group, Somerville, MA (United States)
  4. Univ. of Maryland, College Park, MD (United States
Publication Date:
OSTI Identifier:
Grant/Contract Number:
FG02-94ER61937; SC005171; DEFG02- 94ER61937
Published Article
Journal Name:
Environmental Research Letters
Additional Journal Information:
Journal Volume: 10; Journal Issue: 11; Journal ID: ISSN 1748-9326
IOP Publishing
Research Org:
Boston Univ., MA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
agriculture; climate change impacts; error-correction model; integrated assessment; econometric modeling