Quantifying Crop Yield Bioenergy Production And Greenhouse Gas Emissions From Cropland And Marginal Land Using A Model Data Fusion Approach

Bioenergy is becoming increasingly attractive to many countries, but has sparked an intensive debate regarding energy, economy, society and environment. Biofuels provide alternative energy to conventional fossil fuels. However, the environmental impact of producing and using biofuel is a major concern to our society. This study is dedicated to quantifying and evaluating biofuel production and potential climate change mitigation due to potential large-scale bioenergy expansion in the conterminous United States, using model-data fusion approaches.

Biofuel made from conventional (e.g., maize ("Zea mays" L.)) and cellulosic crops (e.g., switchgrass ("Panicum virgatum" L.) and "Miscanthus" ("Miscanthus x giganteus")) provides alternative energy to fossil fuels and has been considered to mitigate greenhouse gas emissions. To estimate the large-scale carbon and nitrogen dynamics of these biofuel ecosystems, process-based models are needed. Here, we developed an agroecosystem model (AgTEM) based on the Terrestrial Ecosystem Model for these ecosystems. The model incorporated biogeochemical and ecophysiological processes including crop phenology, biomass allocation, nitrification and denitrification as well as agronomic management of irrigation and fertilization. It was used to estimate crop yield, biomass, net carbon exchange, and nitrous oxide (N2O) emissions at an ecosystem level. We found that AgTEM reproduces the observed annual net primary production and N2O emissions of most sites, with over 85% of total

variations explained by the model. Local sensitivity analysis indicated that the model sensitivity varies among different ecosystems. Net primary production of maize is sensitive to temperature, precipitation, cloudiness, fertilizer and irrigation and less sensitive to atmospheric carbon dioxide (CO2) concentrations. In contrast, the net primary production of switchgrass and "Miscanthus" is most sensitive to temperature among all factors. The N2O emissions are sensitive to management in maize ecosystems, and sensitive to climate factors in cellulosic ecosystems. The developed model should help advance our understanding of carbon and nitrogen dynamics of these biofuel ecosystems at both field and regional scales.

Next, we estimated the potential emissions of greenhouse gases from bioenergy ecosystems with AgTEM, assuming maize, switchgrass and "Miscanthus" will be grown on the current maize-producing areas in the conterminous United States. The modeling experiments suggested that, the maize ecosystem acts as a mild net carbon source while cellulosic ecosystems (i.e., switchgrass and "Miscanthus") act as mild sinks. Nitrogen fertilizer use is an important factor affecting biomass production and N2O emissions, especially in the maize ecosystem. To maintain high biomass productivity, the maize ecosystem emits much more greenhouse gases, including CO2 and N2O, than switchgrass and "Miscanthus" cosystems, when high-rate nitrogen fertilizers are applied. For maize, the global warming potential amounts to 1-2 Mg CO2eq ha-1 yr-1, with a dominant contribution of over 90% from N2O emissions. Cellulosic crops contribute to the global warming potential of less than 0.3 Mg CO2eq ha-1 yr-1. Among all three bioenergy crops, "Miscanthus" is the most biofuel productive and the least GHG intensive at a given cropland. Regional model simulations suggested that, substituting "Miscanthus" for maize to produce biofuel could potentially save land and reduce GHG emissions.

Since growing biomass from marginal lands is becoming an increasingly attractive choice for producing biofuel, we looked further into bioenergy potential and possible GHG emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass and "Miscanthus", were assumed to be grown on the abandoned land and mixed crop-vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and N2O emissions were estimated in a spatially explicit manner, using AgTEM. Modeling experiments showed that, cellulosic crops, especially "Miscanthus", could produce a considerable amount of biomass and thus ethanol. For every hectare of marginal land, switchgrass and "Miscanthus" could produce 1.4-2.3 kL and 4.1-6.9 kL ethanol, respectively. The actual amount of ethanol production depends on nitrogen fertilization rate and biofuel conversion efficiency. Switchgrass has high global warming intensity (100-190 g CO2eq L-1 ethanol), in terms of GHG emissions per unit ethanol produced. "Miscanthus", however, emits only 21-36 g CO2eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target of 21 billion gallons by 2022 in the United States, growing "Miscanthus" on the marginal lands could save a large amount of land and reduce GHG emissions in comparison to growing switchgrass.

It should be noted that, ecosystem modeling may be useful for evaluating ecosystem services and environmental impacts, and the results could be informative for policy making concerning energy, food security and sustainability. However, the modeling results are limited in terms of advising agricultural management practices, land use change and energy system analysis, due to modeling uncertainties, data unavailability, and simulation scale and boundary limitations. High-accuracy data assimilation, model improvement and life cycle assessment still await future study.