Xuesong Zhang

Sustainable bioenergy production from marginal lands in the US Midwest

Legislation on biofuels production in the USA and Europe is directing food crops towards the production of grain-based ethanol, which can have detrimental consequences for soil carbon sequestration, nitrous oxide emissions, nitrate pollution, biodiversity and human health. An alternative is to grow lignocellulosic (cellulosic) crops on ‘marginal’ lands. Cellulosic feedstocks can have positive environmental outcomes and could make up a substantial proportion of future energy portfolios. However, the availability of marginal lands for cellulosic feedstock production, and the resulting greenhouse gas (GHG) emissions, remains uncertain. Here we evaluate the potential for marginal lands in ten Midwestern US states to produce sizeable amounts of biomass and concurrently mitigate GHG emissions. In a comparative assessment of six alternative cropping systems over 20 years, we found that successional herbaceous vegetation, once well established, has a direct GHG emissions mitigation capacity that rivals that of purpose-grown crops (−851u2009±u200946 grams of CO2 equivalent emissions per square metre per year (gCO2eu2009m−2u2009yr−1)). If fertilized, these communities have the capacity to produce about 63u2009±u20095 gigajoules of ethanol energy per hectare per year. By contrast, an adjacent, no-till corn–soybean–wheat rotation produces on average 41u2009±u20091 gigajoules of biofuel energy per hectare per year and has a net direct mitigation capacity of −397u2009±u200932u2009gCO2eu2009m−2u2009yr−1; a continuous corn rotation would probably produce about 62u2009±u20097 gigajoules of biofuel energy per hectare per year, with 13% less mitigation. We also perform quantitative modelling of successional vegetation on marginal lands in the region at a resolution of 0.4 hectares, constrained by the requirement that each modelled location be within 80 kilometres of a potential biorefinery. Our results suggest that such vegetation could produce about 21 gigalitres of ethanol per year from around 11 million hectares, or approximately 25 per cent of the 2022 target for cellulosic biofuel mandated by the US Energy Independence and Security Act of 2007, with no initial carbon debt nor the indirect land-use costs associated with food-based biofuels. Other regional-scale aspects of biofuel sustainability, such as water quality and biodiversity, await future study.

Cellulosic feedstock production on Conservation Reserve Program land: potential yields and environmental effects

Producing biofuel feedstocks on current agricultural land raises questions of a ‘food‐vs.‐fuel’ trade‐off. The use of current or former Conservation Reserve Program (CRP) land offers an alternative; yet the volumes of ethanol that could be produced and the potential environmental impacts of such a policy are unclear. Here, we applied the Environmental Policy Integrated Climate model to a US Department of Agriculture database of over 200 000 CRP polygons in Iowa, USA, as a case study. We simulated yields and environmental impacts of growing three cellulosic biofuel feedstocks on CRP land: (i) an Alamo‐variety switchgrass (Panicum virgatum L.); (ii) a generalized mixture of C4 and C3 grasses; (iii) and no‐till corn (Zea mays L.) with residue removal. We simulated yields, soil erosion, and soil carbon (C) and nitrogen (N) stocks and fluxes. We found that although no‐till corn with residue removal produced approximately 2.6–4.4 times more ethanol per area compared to switchgrass and the grass mixture, it also led to 3.9–4.5 times more erosion, 4.4–5.2 times more cumulative N loss, and a 10% reduction in total soil carbon as opposed to a 6–11% increase. Switchgrass resulted in the best environmental outcomes even when expressed on a per liter ethanol basis. Our results suggest planting no‐till corn with residue removal should only be done on low slope soils to minimize environmental concerns. Overall, this analysis provides additional information to policy makers on the potential outcome and effects of producing biofuel feedstocks on current or former conservation lands.

Life cycle assessment of switchgrass cellulosic ethanol production in the Wisconsin and Michigan agricultural contexts.

Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combined with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.

Spatially Explicit Life Cycle Analysis of Cellulosic Ethanol Production Scenarios in Southwestern Michigan

Modeling the life cycle of fuel pathways for cellulosic ethanol (CE) can help identify logistical barriers and anticipated impacts for the emerging commercial CE industry. Such models contain high amounts of variability, primarily due to the varying nature of agricultural production but also because of limitations in the availability of data at the local scale, resulting in the typical practice of using average values. In this study, 12 spatially explicit, cradle-to-refinery gate CE pathways were developed that vary by feedstock (corn stover, switchgrass, and Miscanthus), nitrogen application rate (higher, lower), pretreatment method (ammonia fiber expansion [AFEX], dilute acid), and co-product treatment method (mass allocation, sub-division), in which feedstock production was modeled at the watershed scale over a nine-county area in Southwestern Michigan. When comparing feedstocks, the model showed that corn stover yielded higher global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) than the perennial feedstocks of switchgrass and Miscanthus, on an average per area basis. Full life cycle results per MJ of produced ethanol demonstrated more mixed results, with corn stover-derived CE scenarios that use sub-division as a co-product treatment method yielding similarly favorable outcomes as switchgrass- and Miscanthus-derived CE scenarios. Variability was found to be greater between feedstocks than watersheds. Additionally, scenarios using dilute acid pretreatment had more favorable results than those using AFEX pretreatment.

National Geo-Database for Biofuel Simulations and Regional Analysis of Biorefinery Siting Based on Cellulosic Feedstock Grown on Marginal Lands

The goal of this project undertaken by GLBRC (Great Lakes Bioenergy Research Center) Area 4 (Sustainability) modelers is to develop a national capability to model feedstock supply, ethanol production, and biogeochemical impacts of cellulosic biofuels. The results of this project contribute to sustainability goals of the GLBRC; i.e. to contribute to developing a sustainable bioenergy economy: one that is profitable to farmers and refiners, acceptable to society, and environmentally sound. A sustainable bioenergy economy will also contribute, in a fundamental way, to meeting national objectives on energy security and climate mitigation. The specific objectives of this study are to: (1) develop a spatially explicit national geodatabase for conducting biofuel simulation studies and (4) locate possible sites for the establishment of cellulosic ethanol biorefineries. To address the first objective, we developed SENGBEM (Spatially Explicit National Geodatabase for Biofuel and Environmental Modeling), a 60-m resolution geodatabase of the conterminous USA containing data on: (1) climate, (2) soils, (3) topography, (4) hydrography, (5) land cover/ land use (LCLU), and (6) ancillary data (e.g., road networks, federal and state lands, national and state parks, etc.). A unique feature of SENGBEM is its 2008-2010 crop rotation data, a crucially important component for simulating productivity andmorexa0» biogeochemical cycles as well as land-use changes associated with biofuel cropping. ARRA support for this project and to the PNNL Joint Global Change Research Institute enabled us to create an advanced computing infrastructure to execute millions of simulations, conduct post-processing calculations, store input and output data, and visualize results. These computing resources included two components installed at the Research Data Center of the University of Maryland. The first resource was deltac: an 8-core Linux server, dedicated to county-level and state-level simulations and PostgreSQL database hosting. The second resource was the DOE-JGCRI Evergreen cluster, capable of executing millions of simulations in relatively short periods. ARRA funding also supported a PhD student from UMD who worked on creating the geodatabases and executing some of the simulations in this study. Using a physically based classification of marginal lands, we simulated production of cellulosic feedstocks from perennial mixtures grown on these lands in the US Midwest. Marginal lands in the western states of the US Midwest appear to have significant potential to supply feedstocks to a cellulosic biofuel industry. Similar results were obtained with simulations of N-fertilized perennial mixtures. A detailed spatial analysis allowed for the identification of possible locations for the establishment of 34 cellulosic ethanol biorefineries with an annual production capacity of 5.6 billion gallons. In summary, we have reported on the development of a spatially explicit national geodatabase to conduct biofuel simulation studies and provided simulation results on the potential of perennial cropping systems to serve as feedstocks for the production of cellulosic ethanol. To accomplish this, we have employed sophisticated spatial analysis methods in combination with the process-based biogeochemical model EPIC. The results of this study will be submitted to the USDOE Bioenergy Knowledge Discovery Framework as a way to contribute to the development of a sustainable bioenergy industry. This work provided the opportunity to test the hypothesis that marginal lands can serve as sources of cellulosic feedstocks and thus contribute to avoid potential conflicts between bioenergy and food production systems. This work, we believe, opens the door for further analysis on the characteristics of cellulosic feedstocks as major contributors to the development of a sustainable bioenergy economy.«xa0less