Use of Monte Carlo analysis to characterize nitrogen fluxes in agroecosystems

Intensive agricultural systems are largely responsible for the increase in global reactive nitrogen compounds, which are associated with significant environmental impacts. The nitrogen cycle in agricultural systems is complex and highly variable, which complicates characterization in environmental assessments. Appropriately representing nitrogen inputs into an ecosystem is essential to better understand and predict environmental impacts, such as the extent of seasonally occurring hypoxic zones. Many impacts associated with reactive nitrogen are directly related to annual nitrogen loads, and are not adequately represented by average values that de-emphasize extreme years. To capture the inherent variability in agricultural systems, this paper employs Monte Carlo analysis (MCA) to model major nitrogen exports during crop production, focusing on corn-soybean rotations within the U.S. Corn Belt. This approach yields distributions of possible emission values and is the first step in incorporating variable nutrient fluxes into life cycle assessments (LCA) and environmental impact assessments. Monte Carlo simulations generate distributions of nitrate emissions showing that 80% of values range between 15 and 90 kg NO39-) N/ha (mean 38.5 kg NO3(-) N/ha; median 35.7 kg NO3(-) N/ha) for corn fields and 5-60 kg NO3(-) N/ha (mean 20.8 kg NO3(-) N/ha; median 16.4 kg NO3(-) N/ha) for soybean fields. Data were also generated for grain and residue nitrogen, N2O, NO(x), and NH3. Results indicate model distributions are in agreement with available measured emissions.