Impact of agronomic uncertainty in biomass production and endogenous commodity prices on cellulosic biofuel feedstock composition

This study evaluates the effect of agronomic uncertainty on bioenergy crop production as well as endogenous commodity and biomass prices on the feedstock composition of cellulosic biofuels under a binding mandate in the United States. The county‐level simulation model focuses on both field crops (corn, soybean, and wheat) and biomass feedstocks (corn stover, wheat straw, switchgrass, and Miscanthus). In addition, pasture serves as a potential area for bioenergy crop production. The economic model is calibrated to 2022 in terms of yield, crop demand, and baseline prices and allocates land optimally among the alternative crops given the binding cellulosic biofuel mandate. The simulation scenarios differ in terms of bioenergy crop type (switchgrass and Miscanthus) and yield, biomass production inputs, and pasture availability. The cellulosic biofuel mandates range from 15 to 60 billion L. The results indicate that the 15 and 30 billion L mandates in the high production input scenarios for switchgrass and Miscanthus are covered entirely by agricultural residues. With the exception of the low production input for Miscanthus scenario, the share of agricultural residues is always over 50% for all other scenarios including the 60 billion L mandate. The largest proportion of agricultural land dedicated to either switchgrass or Miscanthus is found in the southern Plains and the southeast. Almost no bioenergy crops are grown in the Midwest across all scenarios. Changes in the prices for the three commodities are negligible for cellulosic ethanol mandates because most of the mandate is met with agricultural residues. The lessons learned are that (1) the share of agricultural residue in the feedstock mix is higher than previously estimated and (2) for a given mandate, the feedstock composition is relatively stable with the exception of one scenario.     

Identifying potential areas for biofuel production and evaluating the environmental effects: a case study of the James River Basin in the Midwestern United States

Biofuels are now an important resource in the United States because of the Energy Independence and Security Act of 2007. Both increased corn growth for ethanol production and perennial dedicated energy crop growth for cellulosic feedstocks are potential sources to meet the rising demand for biofuels. However, these measures may cause adverse environmental consequences that are not yet fully understood. This study 1) evaluates the long‐term impacts of increased frequency of corn in the crop rotation system on water quantity and quality as well as soil fertility in the James River Basin and 2) identifies potential grasslands for cultivating bioenergy crops (e.g. switchgrass), estimating the water quality impacts. We selected the soil and water assessment tool, a physically based multidisciplinary model, as the modeling approach to simulate a series of biofuel production scenarios involving crop rotation and land cover changes. The model simulations with different crop rotation scenarios indicate that decreases in water yield and soil nitrate nitrogen (NO₃‐N) concentration along with an increase in NO₃‐N load to stream water could justify serious concerns regarding increased corn rotations in this basin. Simulations with land cover change scenarios helped us spatially classify the grasslands in terms of biomass productivity and nitrogen loads, and we further derived the relationship of biomass production targets and the resulting nitrogen loads against switchgrass planting acreages. The suggested economically efficient (planting acreage) and environmentally friendly (water quality) planting locations and acreages can be a valuable guide for cultivating switchgrass in this basin. This information, along with the projected environmental costs (i.e. reduced water yield and increased nitrogen load), can contribute to decision support tools for land managers to seek the sustainability of biofuel development in this region.     

Bioenergy crop models: descriptions,data requirements,and future challenges

Field studies that address the production of lignocellulosic biomass as a source of renewable energy provide critical data for the development of bioenergy crop models. A literature survey revealed that 14 models have been used for simulating bioenergy crops including herbaceous and woody bioenergy crops, and for crassulacean acid metabolism (CAM) crops. These models simulate field‐scale production of biomass for switchgrass (ALMANAC, EPIC, and Agro‐BGC), miscanthus (MISCANFOR, MISCANMOD, and WIMOVAC), sugarcane (APSIM, AUSCANE, and CANEGRO), and poplar and willow (SECRETS and 3PG). Two models are adaptations of dynamic global vegetation models and simulate biomass yields of miscanthus and sugarcane at regional scales (Agro‐IBIS and LPJmL). Although it lacks the complexity of other bioenergy crop models, the environmental productivity index (EPI) is the only model used to estimate biomass production of CAM (Agave and Opuntia) plants. Except for the EPI model, all models include representations of leaf area dynamics, phenology, radiation interception and utilization, biomass production, and partitioning of biomass to roots and shoots. A few models simulate soil water, nutrient, and carbon cycle dynamics, making them especially useful for assessing the environmental consequences (e.g., erosion and nutrient losses) associated with the large‐scale deployment of bioenergy crops. The rapid increase in use of models for energy crop simulation is encouraging; however, detailed information on the influence of climate, soils, and crop management practices on biomass production is scarce. Thus considerable work remains regarding the parameterization and validation of process‐based models for bioenergy crops; generation and distribution of high‐quality field data for model development and validation; and implementation of an integrated framework for efficient, high‐resolution simulations of biomass production for use in planning sustainable bioenergy systems.     

Modeling biogeochemical impacts of bioenergy buffers with perennial grasses for a row‐crop field in Illinois

Current research on the environmental sustainability of bioenergy has largely focused on the potential of bioenergy crops to sequester carbon and mitigate greenhouse gas emissions and possible impacts on water quality and quantity. A key assumption in these studies is that bioenergy crops will be grown in a manner similar to current agricultural crops such as corn and hence would affect the environment similarly. In this study, we investigate an alternative cropping system where bioenergy crops are grown in buffer strips adjacent to current agricultural crops such that nutrients present in runoff and leachate from the traditional row‐crops are reused by the bioenergy crops (switchgrass, miscanthus and native prairie grasses) in the buffer strips, thus providing environmental services and meeting economic needs of farmers. The process‐based biogeochemical model Denitrification‐Decomposition (DNDC) was used to simulate crop yield, nitrous oxide production and nitrate concentrations in leachate for a typical agricultural field in Illinois. Model parameters have been developed for the first time for miscanthus and switchgrass in DNDC. Results from model simulations indicated that growing bioenergy crops in buffer strips mitigated nutrient runoff, reduced nitrate concentrations in leachate by 60–70% and resulted in a reduction of 50–90% in nitrous oxide emissions compared with traditional cropping systems. While all the bioenergy crop buffers had significant positive environmental benefits, switchgrass performed the best with respect to minimizing nutrient runoff and nitrous oxide emissions, while miscanthus had the highest yield. Overall, our model results indicated that the bioenergy crops grown in these buffer strips achieved yields that are comparable to those obtained for traditional agricultural systems while simultaneously providing environmental services and could be used to design sustainable agricultural landscapes.     

Watershed‐scale impacts of bioenergy crops on hydrology and water quality using improved SWAT model

Cellulosic bioenergy feedstock such as perennial grasses and crop residues are expected to play a significant role in meeting US biofuel production targets. We used an improved version of the Soil and Water Assessment Tool (SWAT) to forecast impacts on watershed hydrology and water quality by implementing an array of plausible land‐use changes associated with commercial bioenergy crop production for two watersheds in the Midwest USA. Watershed‐scale impacts were estimated for 13 bioenergy crop production scenarios, including: production of Miscanthus × giganteus and upland Shawnee switchgrass on highly erodible landscape positions, agricultural marginal land areas and pastures, removal of corn stover and combinations of these options. Water quality, measured as erosion and sediment loading, was forecasted to improve compared to baseline when perennial grasses were used for bioenergy production, but not with stover removal scenarios. Erosion reduction with perennial energy crop production scenarios ranged between 0.2% and 59%. Stream flow at the watershed outlet was reduced between 0 and 8% across these bioenergy crop production scenarios compared to baseline across the study watersheds. Results indicate that bioenergy production scenarios that incorporate perennial grasses reduced the nonpoint source pollutant load at the watershed outlet compared to the baseline conditions (0–20% for nitrate‐nitrogen and 3–56% for mineral phosphorus); however, the reduction rates were specific to site characteristics and management practices.     

Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains,United States

Growing cellulosic feedstock crops (e.g., switchgrass) for biofuel is more environmentally sustainable than corn‐based ethanol. Specifically, this practice can reduce soil erosion and water quality impairment from pesticides and fertilizer, improve ecosystem services and sustainability (e.g., serve as carbon sinks), and minimize impacts on global food supplies. The main goal of this study was to identify high‐risk marginal croplands that are potentially suitable for growing cellulosic feedstock crops (e.g., switchgrass) in the US Great Plains (GP). Satellite‐derived growing season Normalized Difference Vegetation Index, a switchgrass biomass productivity map obtained from a previous study, US Geological Survey (USGS) irrigation and crop masks, and US Department of Agriculture (USDA) crop indemnity maps for the GP were used in this study. Our hypothesis was that croplands with relatively low crop yield but high productivity potential for switchgrass may be suitable for converting to switchgrass. Areas with relatively low crop indemnity (crop indemnity <$2 157 068) were excluded from the suitable areas based on low probability of crop failures. Results show that approximately 650 000 ha of marginal croplands in the GP are potentially suitable for switchgrass development. The total estimated switchgrass biomass productivity gain from these suitable areas is about 5.9 million metric tons. Switchgrass can be cultivated in either lowland or upland regions in the GP depending on the local soil and environmental conditions. This study improves our understanding of ecosystem services and the sustainability of cropland systems in the GP. Results from this study provide useful information to land managers for making informed decisions regarding switchgrass development in the GP.     

Crassulacean acid metabolism (CAM) offers sustainable bioenergy production and resilience to climate change

Biomass production on low‐grade land is needed to meet future energy demands and minimize resource conflicts. This, however, requires improvements in plant water‐use efficiency (WUE) that are beyond conventional C3 and C4 dedicated bioenergy crops. Here we present the first global‐scale geographic information system (GIS)‐based productivity model of two highly water‐efficient crassulacean acid metabolism (CAM) candidates: Agave tequilana and Opuntia ficus‐indica. Features of these plants that translate to WUE advantages over C3 and C4 bioenergy crops include nocturnal stomatal opening, rapid rectifier‐like root hydraulic conductivity responses to fluctuating soil water potential and the capacity to buffer against periods of drought. Yield simulations for the year 2070 were performed under the four representative concentration pathway (RCPs) scenarios presented in the IPCC's 5th Assessment Report. Simulations on low‐grade land suggest that O. ficus‐indica alone has the capacity to meet ‘extreme’ bioenergy demand scenarios (>600 EJ yr^?1) and is highly resilient to climate change (?1%). Agave tequilana is moderately impacted (?11%). These results are significant because bioenergy demand scenarios >600 EJ yr^?1 could be met without significantly increasing conflicts with food production and contributing to deforestation. Both CAM candidates outperformed the C4 bioenergy crop, Panicum virgatum L. (switchgrass) in arid zones in the latitudinal range 30°S–30°N.     

Investigating the Efficacy of Integrating Energy Crops into Non-Profitable Subfields in Iowa

Within-field spatial variability reduces growers’ return on investment and overall productivity while potentially increasing negative environmental impacts through increased soil erosion, nutrient runoff, and leaching. The hypothesis that integrating energy crops into non-profitable segments of agricultural fields could potentially increase grain yield and biomass feedstock production was tested in this study using a statewide analysis of predominantly corn- and soy-producing counties in Iowa. Basic and rigorous controls on permissible soil and soil-carbon losses were imposed on harvest of crop residues to enhance year-to-year sustainability of crop and residue production. Additional criteria limiting harvesting costs and focus on large-area subfields for biomass production were imposed to reduce the impacts of energy crop integration on grain production. Model simulations were conducted using 4 years (2013–2016) of soil, weather, crop yield, and management practice data on all counties in Iowa. Miscanthus (Miscanthus x giganteus), switchgrass (Panicum virgatum), and crop-residue-based bioenergy feedstock systems were evaluated as biomass. Average energy crop and plant residue harvesting efficiencies were estimated at 50 and 60%, respectively. Because of higher potential yields, average logistics costs for miscanthus-based biomass production were 15 and 23% lower than switchgrass-based and crop residue-based biomass productions, respectively, under basic sustainability controls, and 17 and 26% lower under rigorous sustainability controls. Subfield shape, size, area, and harvest equipment size were the dominant factors influencing harvesting cost and efficiency suggesting that in areas where subfields are predominantly profitable or harvesting efficiencies low, other options such as prairie strips, buffer zones around fields, and riparian areas should be investigated for more profitable biomass production and sustainable farming systems.     

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (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 nitrous oxide emissions were estimated in a spatially explicit manner. We found that, cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 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 in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. However, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop‐specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.     

Where can switchgrass production be more profitable than corn and soybean? An integrated subfield assessment in Iowa,USA

Perennial bioenergy crops are considered an important feedstock for a growing bioeconomy. However, in the USA, production of biofuel from these dedicated, nonfood crops is lagging behind federal mandates and markets have yet to develop. Most studies on the economic potential of perennial biofuel crops have concluded that even high‐yielding bioenergy grasses are unprofitable compared to corn/soybeans, the prevailing crops in the United States Corn Belt. However, they did not account for opportunities precision agriculture presents to integrate perennials into agronomically and economically underperforming parts of corn/soybean fields. Using publicly available subfield data and market projections, we identified an upper bound to the areas in Iowa, United States, where the conversion from corn/soybean cropland to an herbaceous bioenergy crop, switchgrass, could be economically viable under different price, land tenancy, and yield scenarios. Assuming owned land, medium crop prices, and a biomass price of US$ 55 Mg^?1, we showed that 4.3% of corn/soybean cropland could break even when converted to switchgrass yielding up to 10.08 Mg ha^?1. The annualized change in net present value on each converted subfield patch ranged from just above US$ 0 ha^?1 to 692 ha^?1. In the three counties of highest economic opportunity, total annualized producer benefits from converting corn/soybean to switchgrass summed to US$ 2.6 million, 3.4 million, and 7.6 million, respectively. This is the first study to quantify an upper bound to the potential private economic benefits from targeted conversion of unfavorable corn/soybean cropland to switchgrass, leaving arable land already under perennial cover unchanged. Broadly, we conclude that areas with high within‐field yield variation provide highest economic opportunities for switchgrass conversion. Our results are relevant for policy design intended to improve the sustainability of agricultural production. While focused on Iowa, this approach is applicable to other intensively farmed regions globally with similar data availability.     

A realistic meteorological assessment of perennial biofuel crop deployment: a Southern Great Plains perspective

Utility of perennial bioenergy crops (e.g., switchgrass and miscanthus) offers unique opportunities to transition toward a more sustainable energy pathway due to their reduced carbon footprint, averted competition with food crops, and ability to grow on abandoned and degraded farmlands. Studies that have examined biogeophysical impacts of these crops noted a positive feedback between near‐surface cooling and enhanced evapotranspiration (ET), but also potential unintended consequences of soil moisture and groundwater depletion. To better understand hydrometeorological effects of perennial bioenergy crop expansion, this study conducted high‐resolution (2‐km grid spacing) simulations with a state‐of‐the‐art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model. We applied the modeling system over the Southern Plains of the United States during a normal precipitation year (2007) and a drought year (2011). By focusing the deployment of bioenergy cropping systems on marginal and abandoned farmland areas (to reduce the potential conflict with food systems), the research presented here is the first realistic examination of hydrometeorological impacts associated with perennial bioenergy crop expansion. Our results illustrate that the deployment of perennial bioenergy crops leads to widespread cooling (1–2 °C) that is largely driven by an enhanced reflection of shortwave radiation and, secondarily, due to an enhanced ET. Bioenergy crop deployment was shown to reduce the impacts of drought through simultaneous moistening and cooling of the near‐surface environment. However, simulated impacts on near‐surface cooling and ET were reduced during the drought relative to a normal precipitation year, revealing differential effects based on background environmental conditions. This study serves as a key step toward the assessment of hydroclimatic sustainability associated with perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.     

21st‐century biogeochemical modeling: Challenges for Century‐based models and where do we go from here?

21st‐century modeling of greenhouse gas (GHG) emissions from bioenergy crops is necessary to quantify the extent to which bioenergy production can mitigate climate change. For over 30 years, the Century‐based biogeochemical models have provided the preeminent framework for belowground carbon and nitrogen cycling in ecosystem and earth system models. While monthly Century and the daily time‐step version of Century (DayCent) have advanced our ability to predict the sustainability of bioenergy crop production, new advances in feedstock generation, and our empirical understanding of sources and sinks of GHGs in soils call for a re‐visitation of DayCent's core model structures. Here, we evaluate current challenges with modeling soil carbon dynamics, trace gas fluxes, and drought and age‐related impacts on bioenergy crop productivity. We propose coupling a microbial process‐based soil organic carbon and nitrogen model with DayCent to improve soil carbon dynamics. We describe recent improvements to DayCent for simulating unique plant structural and physiological attributes of perennial bioenergy grasses. Finally, we propose a method for using machine learning to identify key parameters for simulating N₂O emissions. Our efforts are focused on meeting the needs for modeling bioenergy crops; however, many updates reviewed and suggested to DayCent will be broadly applicable to other systems.     

Hydrological responses of land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops in the Southern High Plains of Texas,USA

The Southern High Plains (SHP) region of Texas in the United States, where cotton is grown in a vast acreage, has the potential to grow cellulosic bioenergy crops such as perennial grasses and biomass sorghum (Sorghum bicolor). Evaluation of hydrological responses and biofuel production potential of hypothetical land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops enables better understanding of the associated key agroecosystem processes and provides for the feasibility assessment of the targeted land use change in the SHP. The Soil and Water Assessment Tool (SWAT) was used to assess the impacts of replacing cotton with perennial Alamo switchgrass (Panicum virgatum L.), Miscanthus × giganteus (Miscanthus sinensis Anderss. [Poaceae]), big bluestem (Andropogon gerardii) and annual biomass sorghum on water balances, water use efficiency and biofuel production potential in the Double Mountain Fork Brazos watershed. Under perennial grass scenarios, the average (1994–2009) annual surface runoff from the entire watershed decreased by 6–8% relative to the baseline cotton scenario. In contrast, surface runoff increased by about 5% under the biomass sorghum scenario. Perennial grass land use change scenarios suggested an increase in average annual percolation within a range of 3–22% and maintenance of a higher soil water content during August to April compared to the baseline cotton scenario. About 19.1, 11.1, 3.2 and 8.8 Mg ha^?1 of biomass could potentially be produced if cotton area in the watershed would hypothetically be replaced by Miscanthus, switchgrass, big bluestem and biomass sorghum, respectively. Finally, Miscanthus and switchgrass were found to be ideal bioenergy crops for the dryland and irrigated systems, respectively, in the study watershed due to their higher water use efficiency, better water conservation effects, greater biomass and biofuel production potential, and minimum crop management requirements.     

Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States

This paper investigates the spatial heterogeneity of landowners’ willingness to supply three bioenergy crops: switchgrass, Miscanthus, and willow, in the northeastern United States. Spatial heterogeneity might arise for several reasons. For example, landowners closer to bioenergy processing plants might be more likely to be willing to supply bioenergy crops, and landowners who are more willing to supply bioenergy crops may be spatially clustered because they share similar land attributes, demographics, experiences, and/or values. Using high‐resolution GIS data related to the location of pellet plants utilizing bioenergy crops and survey data related to landowners’ characteristics including spatial location, we estimate a spatial probit model to explain the variation in individual‐specific reservation prices (RPs)—the feedstock price at which landowners become willing to supply a bioenergy crop. We find that respondents’ RP is lower the closer they live to their nearest pellet plant and spatial dependency is only present for switchgrass supply. We also identify three economic hotspots (areas with high potential supply and low RPs) for each bioenergy crop. We believe that bioenergy supply chains could be developed around these hotspots.     

Land‐use legacies regulate decomposition dynamics following bioenergy crop conversion

Land‐use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land‐use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land‐use legacies with current management and litter quality. To evaluate how land‐use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape‐scale litterbag decomposition experiment. We proposed land‐use legacies regulate decomposition, but their effects are weakened under higher quality litter and when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.     

Valuation of ecosystem services in alternative bioenergy landscape scenarios

Agricultural land in the Midwest is a source of food and fuel, as well as biodiversity. It is also a cause of excess nutrients that make their way to the Mississippi River and the Gulf of Mexico. To address unsustainable changes to biogeochemical cycles and ecosystem functions, a multidisciplinary approach involving social science, natural science, and engineering is often effective. Given the potential of second‐generation biofuels, and capitalizing on the deep‐rooted perennial bioenergy crops capable of thriving in poor soils, we demonstrated an integrated socio‐environmental analysis of the impacts of growing switchgrass within row‐crop landscapes in Illinois. In this study, we model land use scenarios that incorporate switchgrass as a biofuel crop in a Midwest corn‐belt watershed using the Soil Water Assessment Tool coupled with an economic analysis for the Vermilion Basin in Illinois. We estimated the values of ecosystem services under an alternative bioenergy landscape, including commodity and bioenergy crops, changes in biogeochemistry, and recreational services. The estimated annual values of nitrate and sediment reduction attributed to bioenergy crops range from $38 million to $97 million and $16,000 to $197,000, respectively. The annual value of carbon dioxide emission reduction ranges from $1.8 million to $6.1 million based on the initial crop rotation pattern. Estimated average annual values for wildlife viewing, water‐based recreation, and pheasant hunting are $1.24 million, $0.17 million, and $0.3 million, respectively. To our knowledge, this study represents the first effort to comprehensively quantify ecosystem services using a process‐based model, and estimate their value in an alternative bioenergy landscape. The information we generate could aid in understanding the potential for biomass production from marginal land and the total economic value of the landscape at various spatial scales. The framework is useful in fostering alternative bioenergy landscapes with synergies in a food, energy, and conservation nexus.     

Consequential life cycle assessment of biogas,biofuel and biomass energy options within an arable crop rotation

Feed in tariffs (FiTs) and renewable heat incentives (RHIs) are driving a rapid expansion in anaerobic digestion (AD) coupled with combined heat and power (CHP) plants in the UK. Farm models were combined with consequential life cycle assessment (CLCA) to assess the net environmental balance of representative biogas, biofuel and biomass scenarios on a large arable farm, capturing crop rotation and digestate nutrient cycling effects. All bioenergy options led to avoided fossil resource depletion. Global warming potential (GWP) balances ranged from ?1732 kg CO₂e Mg^?1 dry matter (DM) for pig slurry AD feedstock after accounting for avoided slurry storage to +2251 kg CO₂e Mg^?1 DM for oilseed rape biodiesel feedstock after attributing indirect land use change (iLUC) to displaced food production. Maize monoculture for AD led to net GWP increases via iLUC, but optimized integration of maize into an arable rotation resulted in negligible food crop displacement and iLUC. However, even under best‐case assumptions such as full use of heat output from AD‐CHP, crop–biogas achieved low GWP reductions per hectare compared with Miscanthus heating pellets under default estimates of iLUC. Ecosystem services (ES) assessment highlighted soil and water quality risks for maize cultivation. All bioenergy crop options led to net increases in eutrophication after displaced food production was accounted for. The environmental balance of AD is sensitive to design and management factors such as digestate storage and application techniques, which are not well regulated in the UK. Currently, FiT payments are not dependent on compliance with sustainability criteria. We conclude that CLCA and ES effects should be integrated into sustainability criteria for FiTs and RHIs, to direct public money towards resource‐efficient renewable energy options that achieve genuine climate protection without degrading soil, air or water quality.     

Targeted subfield switchgrass integration could improve the farm economy,water quality,and bioenergy feedstock production

Progress on reducing nutrient loss from annual croplands has been hampered by perceived conflicts between short‐term profitability and long‐term stewardship, but these may be overcome through strategic integration of perennial crops. Perennial biomass crops like switchgrass can mitigate nitrate‐nitrogen (NO₃‐N) leaching, address bioenergy feedstock targets, and – as a lower‐cost management alternative to annual crops (i.e., corn, soybeans) – may also improve farm profitability. We analyzed publicly available environmental, agronomic, and economic data with two integrated models: a subfield agroecosystem management model, Landscape Environmental Assessment Framework (LEAF), and a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC). We constructed a factorial combination of profitability and NO₃‐N leaching thresholds and simulated targeted switchgrass integration into corn/soybean cropland in the agricultural state of Iowa, USA. For each combination, we modeled (i) area converted to switchgrass, (ii) switchgrass biomass production, and (iii) NO₃‐N leaching reduction. We spatially analyzed two scenarios: converting to switchgrass corn/soybean cropland losing >US$ 100 ha^?1 and leaching >50 kg ha^?1 (‘conservative’ scenario) or losing >US$ 0 ha^?1 and leaching >20 kg ha^?1 (‘nutrient reduction’ scenario). Compared to baseline, the ‘conservative’ scenario resulted in 12% of cropland converted to switchgrass, which produced 11 million Mg of biomass and reduced leached NO₃‐N 18% statewide. The ‘nutrient reduction’ scenario converted 37% of cropland to switchgrass, producing 34 million Mg biomass and reducing leached NO₃‐N 38% statewide. The opportunity to meet joint goals was greatest within watersheds with undulating topography and lower corn/soybean productivity. Our approach bridges the scales at which NO₃‐N loss and profitability are usually considered, and is informed by both mechanistic and empirical understanding. Though approximated, our analysis supports development of farm‐level tools that can identify locations where both farm profitability and water quality improvement can be achieved through the strategic integration of perennial vegetation.     

An integrated biogeochemical and economic analysis of bioenergy crops in the Midwestern United States

This study integrates a biophysical model with a county‐specific economic analysis of breakeven prices of bioenergy crop production to assess the biophysical and economic potential of biofuel production in the Midwestern United States. The bioenergy crops considered in this study include a genotype of Miscanthus, Miscanthus×giganteus, and the Cave‐in‐Rock breed of switchgrass (Panicum virgatum). The estimated average peak biomass yield for miscanthus in the Midwestern states ranges between 7 and 48 metric tons dry matter per hectare per year ( t DM ha^?1 yr^?1), while that for switchgrass is between 10 and 16 t DM ha^?1 yr^?1. With the exception of Minnesota and Wisconsin, where miscanthus yields are likely to be low due to cold soil temperatures, the yield of miscanthus is on average more than two times higher than yield of switchgrass. We find that the breakeven price, which includes the cost of producing the crop and the opportunity cost of land, of producing miscanthus ranges from $53 t^?1 DM in Missouri to $153 t^?1 DM in Minnesota in the low‐cost scenario. Corresponding costs for switchgrass are $88 t^?1 DM in Missouri to $144 t^?1 DM in Minnesota. In the high‐cost scenario, the lowest cost for miscanthus is $85 t^?1 DM and for switchgrass is $118 t^?1 DM, both in Missouri. These two scenarios differ in their assumptions about ease of establishing the perennial crops, nutrient requirements and harvesting costs and losses. The differences in the breakeven prices across states and across crops are mainly driven by bioenergy and row crop yields per hectare. Our results suggest that while high yields per unit of land of bioenergy crops are critical for the competitiveness of bioenergy feedstocks, the yields of the row crops they seek to displace are also an important consideration. Even high yielding crops, such as miscanthus, are likely to be economically attractive only in some locations in the Midwest given the high yields of corn and soybean in the region.     

Environmental limitation mapping of potential biomass resources across the conterminous United States

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM‐ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long‐term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low‐temperature response, summer high‐temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.