Estimation of the variability in global warming potential of worldwide crop production using a modular extrapolation approach

The agri-food sector, and specifically agricultural production, is a major contributor to climate change. In order to manage the impact on the climate, a better understanding of the variability of global warming potential in agriculture is needed. This study assesses the variability in global warming potential of 27 crops using the modular extrapolation of agricultural life cycle assessment (MEXALCA) method, a modular, geographical extrapolation method for crop life cycle assessment. The global warming potential results, excluding land use change, were validated with crop data from the ecoinvent database and from the literature. oduction weighted worldwide mean values of global warming potential for the 27 crops varied in a wide range (factor of 20 in impact per ha; factor of 100 in impact per kg). The global warming potential values per kg of fresh mass were lowest for sugar crops (<0.05 kg CO2-eq kg−1), followed by root crops (<0.15 kg CO2-eq kg−1), vegetables and fruits (<0.35 kg CO2-eq kg−1), and oil palm. Cereals (except rice), pulses, rapeseed and soybean had medium values (<0.6 kg CO2-eq kg−1). Highest values were found for treenuts, other oil crops (linseed, cotton, peanuts), and rice (1.2–2.4 kg CO2-eq kg−1). obal warming potential per kg fresh mass was negatively correlated with the mean yield of the different crops, but not in the case of the same crop produced in different countries. The farming intensity in different countries, the yields and the selection of producing countries were important contributory factors in determining the variability of global warming potential.