A Longitudinal U.S. State-Level Analysis of Organic Food Production and Greenhouse Gas Emissions

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A Longitudinal U.S. State-Level Analysis of Organic Food Production and Greenhouse Gas Emissions

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Title: A Longitudinal U.S. State-Level Analysis of Organic Food Production and Greenhouse Gas Emissions
Author: Squalli, Jay J. ORCID  0000-0002-3638-382X
Citation: Squalli, Jay J. 2016. A Longitudinal U.S. State-Level Analysis of Organic Food Production and Greenhouse Gas Emissions. Master's thesis, Harvard Extension School.
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Abstract: The question of whether organic farming is environmentally beneficial is not only contentious but also not well understood. Organic farming, which has been centered on the idea that increased soil health and vitality would result in more nutritious food and pest resistant crops, can also represent a significant means to tackle climate change. My research addresses the following question: Controlling for other sources of greenhouse gas (GHG) emissions, how do GHG emissions vary across U.S. states and over time with the proportion of total farmland devoted to organic cropland? This research question leads to three testable hypotheses. The first hypothesis, denoted as the Neutrality Hypothesis, posits that there exists no statistically significant relationship between organic cropland acreage and GHG emissions. The second hypothesis, denoted as the Mitigating Effect Hypothesis, is that increased organic cropland acreage is associated with lower GHG emissions. The final hypothesis, denoted as the Polluting Hypothesis, is that more organic cropland acreage is associated with higher GHG emissions. Most previous research has relied on lifecycle analysis (LCA) and has yielded estimation results that varied across products, product groups, locations, methodology, data, and even across studies assessing the same products. On the other hand, a recent study using multiple regression analysis presented questionable evidence contending a negative environmental impact for organic farming.

My research deviates from LCA by making use of U.S. state-level data over the 1997-2010 period excluding the years 1998, 1999, and 2009, multiple regression analysis, and a model consistent with the Stochastic Impacts by Regression on Population, Affluence, and Technology approach. Overall, there is evidence supporting the Mitigating Effect Hypothesis. Indeed, after controlling for other sources of GHG emissions, a one percent growth in organic farming is estimated to lower GHG emissions by 0.06% across U.S. states. This suggests that at the current rate of growth in organic farming, GHG emissions could decrease by about 7.7% by 2030 and by 12.8% by 2050 relative to the current level of emissions. In addition, in an assessment of the interaction between organic farming and the transportation sector, I find that the effect of organic farming on CH4 and N2O emissions depends on a state’s transportation output share (% of total state GDP). More specifically, at the current levels of transportation output, growth in organic farming is expected to mitigate CH4 and N2O emissions across most U.S. states. This would suggest that the environmental harm that transportation output contributes to organic food production might be too negligible to outweigh the environmental benefits of organic farming practices. A cluster analysis confirms these findings by showing that the environmental impact of organic farming is below the country average for most U.S. states and across three measures of emissions.

Although organic farming practices are already environmentally beneficial, further improvements can be achieved through the adoption of regenerative organic farming and by replacing the current competitive environment between conventional and organic farming with a more symbiotic coexistence. The current study reveals GHG mitigation benefits associated with organic food production. Policymakers and scientists can build on these results to further develop the evidence base and policies needed to maximize the benefits of adopting organic farming practices.
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Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:33797399
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