Regression modeling of field emissions in wheat production using a LCA approach

Abstract

In this study, field emissions of Iran wheat production were investigated. Data were collected from 260 farms in Fereydonshahr city in Esfahan province . Life cycle assessment (LCA) methodology was developed to assess all the environmental impacts associated with the production of wheat in the studied region. Global warming potential (GWP), eutrophication potential (EP), human toxicity potential (HTP), terrestrial ecotoxicity potential (TEP), oxidant formation potential (OFP) and acidification potential (AP) were calculated as 2620.86 kg CO 2 eq.t -1 (tonne of grain), 14.25 kg PO 4 -2 eq.t -1 , 1111.7 kg 1,4-DCB eq.t -1 , 10.59 kg 1,4-DCB eq.t -1 , 0.0073 kg ethylene eq.t -1 and 19.07 kg SO 2 eq.t -1 , respectively. In order to specify a relationship between input materials and field emissions (direct and indirect emission), Cobb-Douglass production function was applied. The impacts of farm area, N, P 2 O 5 , K 2 O, diesel fuel and biocides were entered as independent variables and different impact categories as dependent variables. RMSE of models for GWP, EP, HTP, TEP, OFP and AP was 0.07, 0.19, 0.17, 0.34, 0.49 and 0.26, respectively. Accordingly with a rise in farm size level, the emissions per tonne of grain produced decreased. Accordingly, the large farms are more environmentally friendly due to more yields and less emissions per tonne of grains.