Oxidant and acid precipitation effects on soybean yield: Cross-sectional model development

Regression models have been constructed to examine effects of oxidant and acid precipitation air pollutants and regional factors on soybean yield. Although regional factors provide most of the explanatory power, effects of oxidants and acid precipitation are statistically significant. These regressions suggest that controlling oxidant air pollution may produce greater benefit than controlling acid precipitation. Specifically, controlling pH to 5.2 or 5.6 would result in a national-level increase in soybean yield of ～ 1%. In comparison, if oxidant concentrations were controlled to 40 or 25 ppb (nL/L), a national-level increase of 4%–9% is predicted. Simultaneous control of both pollutants (i.e., pH = 5.6, oxidant = 25 ppb (nL/L) would result in a national-level benefit of ～ 10%. Regression models and field generated dose-response functions predict similar results. Before the methods developed in this paper can be used for policy analysis, data and sources of estimate uncertainty need to be more closely examined.