Kendrick Killian

Energy and Environmental Aspects of Using Corn Stover for Fuel Ethanol

Summary Corn stover is the residue that is left behind after corn grain harvest. We have constructed a life-cycle model that describes collecting corn stover in the state of Iowa, in the Midwest of the United States, for the production and use of a fuel mixture consisting of 85% ethanol/15% gasoline (known as “E85”) in a flexible-fuel light-duty vehicle. The model incorporates results from individual models for soil carbon dynamics, soil erosion, agronomics of stover collection and transport, and biocon-version of stover to ethanol. Limitations in available data forced us to focus on a scenario that assumes all farmers in the state of Iowa switch from their current cropping and tilling practices to continuous production of corn and “no-till” practices. Under these conditions, which maximize the amount of collectible stover, Iowa alone could produce almost 8 billion liters per year of pure stover-derived ethanol (E100) at prices competitive with todays corn-starch-derived fuel ethanol. Soil organic matter, an important indicator of soil health, drops slightly in the early years of stover collection but remains stable over the 90-year time frame studied. Soil erosion is controlled at levels within tolerable soil-loss limits established for each county in Iowa by the U.S. Department of Agriculture. We find that, for each kilometer fueled by the ethanol portion of E85, the vehicle uses 95% less petroleum compared to a kilometer driven in the same vehicle on gasoline. Total fossil energy use (coal, oil, and natural gas) and greenhouse gas emissions (fossil CO2, N2O, and CH4) on a life-cycle basis are 102% and 113% lower, respectively. Air quality impacts are mixed, with emissions of CO, NOx, and SOx increasing, whereas hydrocarbon ozone precursors are reduced. This model can serve as a platform for future discussion and analysis of possible scenarios for the sustainable production of transportation fuels from corn stover and other agricultural residues.

Modelling climate, CO2 and management impacts on soil carbon in semi-arid agroecosystems

In agroecosystems, there is likely to be a strong interaction between global change and management that will determine whether soil will be a source or sink for atmospheric C. We conducted a simulation study of changes in soil C as a function of climate and CO2 change, for a suite of different management systems, at four locations representing a climate sequence in the central Great Plains of the US.Climate, CO2 and management interactions were analyzed for three agroecosystems: a conventional winter wheat-summer fallow rotation, a wheat-corn-fallow rotation and continuous cropping with wheat. Model analyses included soil C responses to changes in the amount and distribution of precipitation and responses to changes in temperature, precipitation and CO2 as projected by a general circulation model for a 2 × CO2 scenario.Overall, differences between management systems at all the sites were greater than those induced by perturbations of climate and/or CO2. Crop residue production was increased by CO2 enrichment and by a changed climate. Where the frequency of summer fallowing was reduced (wheat-corn-fallow) or eliminated (continuous wheat), soil C increased under all conditions, particularly with increased (640 μL L−1) CO2. For wheat-fallow management, the model predicted declines in soil C under both ambient conditions and with climate change alone. Increased CO2 with wheat-fallow management yielded small gains in soil C at three of the sites and reduced losses at the fourth site.Our results illustrate the importance of considering the role of management in determining potential responses of agroecosystems to global change. Changes in climate will determine changes in management as farmers strive to maximize profitability. Therefore, changes in soil C may be a complex function of climate driving management and management driving soil C levels and not be a simple direct effect of either climate or management.

Counting carbon on the farm: Reaping the benefits of carbon offset programs

Reducing anthropogenic greenhouse gas (GHG) emissions is the greatest environmental challenge facing society over the coming decades (NAS 2005). Although the largest global source of emission stems from the use of fossil fuels, land use, including agriculture, is the second greatest contributor to increasing GHG concentrations in the atmosphere, accounting for about 30% of total net emissions (IPCC 2007). The majority of these land use emissions are associated with deforestation and land conversion, mainly in the tropics; however, in the United States, agriculture contributes around 7% of total emissions (EPA 2007). The three main GHGs of concern—carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)—are all emitted through various agricultural activities, with the CH4 and N2O dominating agricultural emissions in the United States. However, agriculture has the capacity to not only significantly reduce its own emissions, but also to offset CO2 emissions from other sectors of the economy via carbon sequestration (CAST 2004; Paustian et al. 2006). By employing practices that increase organic matter content (about half of which is carbon) of soils, it is estimated that as much as 50 to 200 million t C per year of carbon offsets could be produced by US agriculture (Lal et al.…

Sustainable Land Management Through Soil Organic Carbon Management and Sequestration — The GEFSOC Modelling System

Soil organic carbon (SOC) is vital for ecosystem and agro-ecosystem function. Any sustainable land management strategy should, therefore, include a consideration of long-term effects on SOC. In the future, we have the opportunity to adopt land management strategies that lead to greater C storage in the soil. However, to do so, we need consistent estimates of SOC stocks and changes under varying land use and climate change scenarios. A Global Environment Facility (GEF) project developed a generically applicable system (the GEFSOC Modelling System) for making such estimates. The system links two dynamic SOC models, designed for site scale applications (Century and RothC) and an empirical method, to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. The system was developed using data from four contrasting eco-regions (The Brazilian Amazon, Jordan, Kenya and the Indian part of the Indo-Gangetic Plains). These areas were chosen, as they are located in regions previously underrepresented by soil C models. The system was then used to estimates SOC stocks and changes between 1990 and 2030 under likely land use change scenarios in each of the four regions. Losses in SOC of between 5 and 16 % were projected for each of the four areas over a 30-year period (2000–2030), driven by a range of factors including deforestation, overgrazing and conversion of grazing land to agriculture. Implications for sustainable land management and future land use policy are discussed for The Brazilian Amazon, Jordan, Kenya and the Indian Indo-Gangetic Plains.

Chapter 15 – COMET2.0—Decision Support System for Agricultural Greenhouse Gas Accounting

Improved agricultural practices have a significant potential to mitigate greenhouse gas (GHG) emissions. A key issue for implementing mitigation options is quantifying emissions practically and cost effectively. Web-based systems using process-based models provide a promising approach.