Global Climate Impacts of Agriculture: A Meta-regression Analysis of Food Production

Abstract Good management requires proper measurement, yet little is known about anthropogenic climate effects of agriculture. To remedy this, a precise measurement of negative externalities is urgently needed. Therefore, the authors of this article describe the heterogeneity of results from previous studies on climate effects and – focussing on the agricultural sector – identify reasons for this phenomenon. The authors conduct a meta-regression analysis, based on 53 primary studies that cover the period between 1951 and 2015. All countries or country groups are included in the 1,345 reported results on emitted amounts of CO2e and SO2e. Our findings confirm the well-known result that an increase in livestock quantities corresponds with a significant increase in emission levels. By integrating culture-related country data, the authors conclude that the level of “humane orientation” and the amounts of emissions follow opposite courses. Furthermore, studies conducted while the first author of this study was working for an NGO, report significantly higher emissions. Based on an adaptation of a meta-regression analysis to the field of environmental performance measurement, we are able to provide new insights about the influence of the change of individual drivers on the emission level. Examples of these insights include a one-third increase in cattle stock is associated with an increase in emissions of 29.45 t/km2. We also find that publications where the first author works for an NGO reported an emission level 87.04 t/km2 higher than other publications. These findings enable the identification of the main drivers of emissions, while helping to explain the heterogeneity of existing studies. Based on the findings of this study, companies can take reliable measures to reduce the external climate effects of their products.