A mathematical model to design a lignocellulosic biofuel supply chain system with a case study based on a region in Central Texas

This study formulates a model to maximize the profit of a lignocellulosic biofuel supply chain ranging from feedstock suppliers to biofuel customers. The model deals with a time-staged, multi-commodity, production/distribution system, prescribing facility locations and capacities, technologies, and material flows. A case study based on a region in Central Texas demonstrates application of the proposed model to design the most profitable biofuel supply chain under each of several scenarios. A sensitivity analysis identifies that ethanol (ETOH) price is the most significant factor in the economic viability of a lignocellulosic biofuel supply chain.     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

Cellulosic ethanol is widely believed to offer substantial environmental advantages over petroleum fuels and grain‐based ethanol, particularly in reducing greenhouse gas emissions from transportation. The environmental impacts of biofuels are largely caused by precombustion activities, feedstock production and conversion facility operations. Life cycle analysis (LCA) is required to understand these impacts. This article describes a field‐to‐blending terminal LCA of cellulosic ethanol produced by biochemical conversion (hydrolysis and fermentation) using corn stover or switchgrass as feedstock. This LCA develops unique models for most elements of the biofuel production process and assigns environmental impact to different phases of production. More than 30 scenarios are evaluated, reflecting a range of feedstock, technology and scale options for near‐term and future facilities. Cellulosic ethanol, as modeled here, has the potential to significantly reduce greenhouse gas (GHG) emissions compared to petroleum‐based liquid transportation fuels, though substantial uncertainty exists. Most of the conservative scenarios estimate GHG emissions of approximately 45–60 g carbon dioxide equivalent per MJ of delivered fuel (g CO₂e MJ^?1) without credit for coproducts, and 20–30 g CO₂e MJ^?1 when coproducts are considered. Under most scenarios, feedstock production, grinding and transport dominate the total GHG footprint. The most optimistic scenarios include sequestration of carbon in soil and have GHG emissions below zero g CO₂e MJ^?1, while the most pessimistic have life‐cycle GHG emissions higher than petroleum gasoline. Soil carbon changes are the greatest source of uncertainty, dominating all other sources of GHG emissions at the upper bound of their uncertainty. Many LCAs of biofuels are narrowly constrained to GHG emissions and energy; however, these narrow assessments may miss important environmental impacts. To ensure a more holistic assessment of environmental performance, a complete life cycle inventory, with over 1100 tracked material and energy flows for each scenario is provided in the online supplementary material for this article.     

Biomass feedstock preprocessing and long‐distance transportation logistics

Biomass‐based biofuels have gained attention because they are renewable energy sources that could facilitate energy independence and improve rural economic development. As biomass supply and biofuel demand areas are generally not geographically contiguous, the design of an efficient and effective biomass supply chain from biomass provision to biofuel distribution is critical to facilitate large‐scale biofuel development. This study compared the costs of supplying biomass using three alternative biomass preprocessing and densification technologies (pelletizing, briquetting, and grinding) and two alternative transportation modes (trucking and rail) for the design of a four‐stage biomass–biofuel supply chain in which biomass produced in Illinois is used to meet biofuel demands in either California or Illinois. The BioScope optimization model was applied to evaluate a four‐stage biomass–biofuel supply chain that includes biomass supply, centralized storage and preprocessing (CSP), biorefinery, and ethanol distribution. We examined the cost of 15 scenarios that included a combination of three biomass preprocessing technologies and five supply chain configurations. The findings suggested that the transportation costs for biomass would generally follow the pattern of coal transportation. Converting biomass to ethanol locally and shipping ethanol over long distances is most economical, similar to the existing grain‐based biofuel system. For the Illinois–California supply chain, moving ethanol is Biomass‐based biofuels have gained attention because they are renewable energy sources that could facilitate energy independence and improve rural economic development. As biomass supply and biofuel demand areas are generally not geographically contiguous, the design of an efficient and effective biomass supply chain from biomass provision to biofuel distribution is critical to facilitate large‐scale biofuel development. This study compared the costs of supplying biomass using three alternative biomass preprocessing and densification technologies (pelletizing, briquetting, and grinding) and two alternative transportation modes (trucking and rail) for the design of a four‐stage biomass–biofuel supply chain in which biomass produced in Illinois is used to meet biofuel demands in either California or Illinois. The BioScope optimization model was applied to evaluate a four‐stage biomass–biofuel supply chain that includes biomass supply, centralized storage and preprocessing (CSP), biorefinery, and ethanol distribution. We examined the cost of 15 scenarios that included a combination of three biomass preprocessing technologies and five supply chain configurations. The findings suggested that the transportation costs for biomass would generally follow the pattern of coal transportation. Converting biomass to ethanol locally and shipping ethanol over long distances is most economical, similar to the existing grain‐based biofuel system. For the Illinois–California supply chain, moving ethanol is $0.24 gal^?1 less costly than moving biomass even in densified form over long distances. The use of biomass pellets leads to lower overall costs of biofuel production for long‐distance transportation but to higher costs if used for short‐distance movement due to its high capital and processing costs. Supported by the supply chain optimization modeling, the cellulosic‐ethanol production and distribution costs of using Illinois feedstock to meet California demand are $0.08 gal^?1 higher than that for meeting local Illinois demand.     

Influence of spatially dependent,modeled soil carbon emission factors on life‐cycle greenhouse gas emissions of corn and cellulosic ethanol

Converting land to biofuel feedstock production incurs changes in soil organic carbon (SOC) that can influence biofuel life‐cycle greenhouse gas (GHG) emissions. Estimates of these land use change (LUC) and life‐cycle GHG emissions affect biofuels' attractiveness and eligibility under a number of renewable fuel policies in the USA and abroad. Modeling was used to refine the spatial resolution and depth extent of domestic estimates of SOC change for land (cropland, cropland pasture, grassland, and forest) conversion scenarios to biofuel crops (corn, corn stover, switchgrass, Miscanthus, poplar, and willow) at the county level in the USA. Results show that in most regions, conversions from cropland and cropland pasture to biofuel crops led to neutral or small levels of SOC sequestration, while conversion of grassland and forest generally caused net SOC loss. SOC change results were incorporated into the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model to assess their influence on life‐cycle GHG emissions of corn and cellulosic ethanol. Total LUC GHG emissions (g CO₂eq MJ^?1) were 2.1–9.3 for corn‐, ?0.7 for corn stover‐, ?3.4 to 12.9 for switchgrass‐, and ?20.1 to ?6.2 for Miscanthus ethanol; these varied with SOC modeling assumptions applied. Extending the soil depth from 30 to 100 cm affected spatially explicit SOC change and overall LUC GHG emissions; however, the influence on LUC GHG emission estimates was less significant in corn and corn stover than cellulosic feedstocks. Total life‐cycle GHG emissions (g CO₂eq MJ^?1, 100 cm) were estimated to be 59–66 for corn ethanol, 14 for stover ethanol, 18–26 for switchgrass ethanol, and ?7 to ?0.6 for Miscanthus ethanol. The LUC GHG emissions associated with poplar‐ and willow‐derived ethanol may be higher than that for switchgrass ethanol due to lower biomass yield.     

Wood pellets,what else? Greenhouse gas parity times of European electricity from wood pellets produced in the south‐eastern United States using different softwood feedstocks

Several EU countries import wood pellets from the south‐eastern United States. The imported wood pellets are (co‐)fired in power plants with the aim of reducing overall greenhouse gas (GHG) emissions from electricity and meeting EU renewable energy targets. To assess whether GHG emissions are reduced and on what timescale, we construct the GHG balance of wood‐pellet electricity. This GHG balance consists of supply chain and combustion GHG emissions, carbon sequestration during biomass growth and avoided GHG emissions through replacing fossil electricity. We investigate wood pellets from four softwood feedstock types: small roundwood, commercial thinnings, harvest residues and mill residues. Per feedstock, the GHG balance of wood‐pellet electricity is compared against those of alternative scenarios. Alternative scenarios are combinations of alternative fates of the feedstock materials, such as in‐forest decomposition, or the production of paper or wood panels like oriented strand board (OSB). Alternative scenario composition depends on feedstock type and local demand for this feedstock. Results indicate that the GHG balance of wood‐pellet electricity equals that of alternative scenarios within 0–21 years (the GHG parity time), after which wood‐pellet electricity has sustained climate benefits. Parity times increase by a maximum of 12 years when varying key variables (emissions associated with paper and panels, soil carbon increase via feedstock decomposition, wood‐pellet electricity supply chain emissions) within maximum plausible ranges. Using commercial thinnings, harvest residues or mill residues as feedstock leads to the shortest GHG parity times (0–6 years) and fastest GHG benefits from wood‐pellet electricity. We find shorter GHG parity times than previous studies, for we use a novel approach that differentiates feedstocks and considers alternative scenarios based on (combinations of) alternative feedstock fates, rather than on alternative land uses. This novel approach is relevant for bioenergy derived from low‐value feedstocks.     

Ecosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design

Renewable fuel standards in the US and elsewhere mandate the production of large quantities of cellulosic biofuels with low greenhouse gas (GHG) footprints, a requirement which will likely entail extensive cultivation of dedicated bioenergy feedstock crops on marginal agricultural lands. Performance data for such systems is sparse, and non‐linear interactions between the feedstock species, agronomic management intensity, and underlying soil and land characteristics complicate the development of sustainable landscape design strategies for low‐impact commercial‐scale feedstock production. Process‐based ecosystem models are valuable for extrapolating field trial results and making predictions of productivity and associated environmental impacts that integrate the effects of spatially variable environmental factors across diverse production landscapes. However, there are few examples of ecosystem model parameterization against field trials on both prime and marginal lands or of conducting landscape‐scale analyses at sufficient resolution to capture interactions between soil type, land use, and management intensity. In this work we used a data‐diverse, multi‐criteria approach to parameterize and validate the DayCent biogeochemistry model for upland and lowland switchgrass using data on yields, soil carbon changes, and soil nitrous oxide emissions from US field trials spanning a range of climates, soil types, and management conditions. We then conducted a high‐resolution case study analysis of a real‐world cellulosic biofuel landscape in Kansas in order to estimate feedstock production potential and associated direct biogenic GHG emissions footprint. Our results suggest that switchgrass yields and emissions balance can vary greatly across a landscape large enough to supply a biorefinery in response to variations in soil type and land‐use history, but that within a given land base both of these performance factors can be widely modulated by changing management intensity. This in turn implies a large sustainable cellulosic biofuel landscape design space within which a system can be optimized to meet economic or environmental objectives.     

The greenhouse gas intensity and potential biofuel production capacity of maize stover harvest in the US Midwest

Agricultural residues are important sources of feedstock for a cellulosic biofuels industry that is being developed to reduce greenhouse gas emissions and improve energy independence. While the US Midwest has been recognized as key to providing maize stover for meeting near‐term cellulosic biofuel production goals, there is uncertainty that such feedstocks can produce biofuels that meet federal cellulosic standards. Here, we conducted extensive site‐level calibration of the Environmental Policy Integrated Climate (EPIC) terrestrial ecosystems model and applied the model at high spatial resolution across the US Midwest to improve estimates of the maximum production potential and greenhouse gas emissions expected from continuous maize residue‐derived biofuels. A comparison of methodologies for calculating the soil carbon impacts of residue harvesting demonstrates the large impact of study duration, depth of soil considered, and inclusion of litter carbon in soil carbon change calculations on the estimated greenhouse gas intensity of maize stover‐derived biofuels. Using the most representative methodology for assessing long‐term residue harvesting impacts, we estimate that only 5.3 billion liters per year (bly) of ethanol, or 8.7% of the near‐term US cellulosic biofuel demand, could be met under common no‐till farming practices. However, appreciably more feedstock becomes available at modestly higher emissions levels, with potential for 89.0 bly of ethanol production meeting US advanced biofuel standards. Adjustments to management practices, such as adding cover crops to no‐till management, will be required to produce sufficient quantities of residue meeting the greenhouse gas emission reduction standard for cellulosic biofuels. Considering the rapid increase in residue availability with modest relaxations in GHG reduction level, it is expected that management practices with modest benefits to soil carbon would allow considerable expansion of potential cellulosic biofuel production.     

Implications of corn prices on water footprints of bioethanol

Previously reported water footprints (WFPs) of corn ethanol have been estimated based on the assumption that corn ethanol feedstock could be supplied by the same states where the corn is grown. However, ethanol conversion facilities may choose out-of-state feedstock suppliers depending on the total price of feedstock they have to pay including both the corn price and transportation costs. The purpose of this study is to evaluate the WFPs and total water use (TWU) of corn ethanol considering an optimal allocation of corn with heterogeneous corn feedstock prices across states. The results show that the WFPs of corn ethanol are less than 100 l of water per liter of ethanol (Lw/Le) for all ethanol-producing states based on both the 2008 corn price and transportation costs for rail and truck. Results also reveal that WFPs are very sensitive to the market price of corn and that additional greenhouse gas emissions due to corn trade between states are not significant.     

Life Cycle Performance of Cellulosic Ethanol and Corn Ethanol from a Retrofitted Dry Mill Corn Ethanol Plant

This study conducts a life cycle assessment of a simulated dry mill corn ethanol facility in California’s Central Valley retrofitted to also produce ethanol from corn stover, a cellulosic feedstock. The assessment examines three facility designs, all producing corn ethanol and wet distiller’s grains and solubles as a co-product: a baseline facility with no cellulosic retrofit, a facility retrofitted with a small capacity for stover feedstock, and a facility retrofitted for a large capacity of stover feedstock. Corn grain is supplied by rail from the Midwest, while stover is sourced from in-state farms and delivered by truck. Two stover feedstock supply scenarios are considered, testing harvest rates at 25 or 40 % of stover mass. Allocation is required to separate impacts attributable to co-products. Additional scenarios are explored to assess the effect of co-product allocation methods on life cycle assessment results for the two fuel products, corn ethanol and stover ethanol. The assessment tracks greenhouse gas (GHG) emissions, energy consumption, criteria air pollutants, and direct water consumption. The GHG intensity of corn ethanol produced from the three facility designs range between 61.3 and 68.9 g CO₂e/MJ, which includes 19.8 g CO₂e/MJ from indirect land use change for Midwestern corn grain. The GHG intensity of cellulosic ethanol varies from 44.1 to 109.2 g CO₂e/MJ, and 14.6 to 32.1 g CO₂e/MJ in the low and high stover capacity cases, respectively. Total energy input ranges between 0.60 and 0.71 MJ/MJ for corn ethanol and 0.13 to 2.29 MJ/MJ for stover ethanol. This variability is the result of the stover supply scenarios (a function of harvest rate) and co-product allocation decisions.     

Biofuel technologies: Lessons learned and pathways to decarbonization

This Opinion highlights several successful cases of biofuel technologies recently described by the IEA Bioenergy Intertask Report on Lessons Learned. The report discussed the potential of biofuels to contribute to a significant market supply, thus replacing fossil fuels and mitigating global warming, and it underscores the challenges in expanding biofuel production and replicating successful models between countries and regions. Based on the lessons learned from conventional, established technologies, the authors analyzed policies, feedstocks, products, technologies, economics, environmental concerns, social aspects, scalability, and ease of implementation and replication in different countries or regions. There are blending mandates in place around the world to foster the use of biofuels. Dependence on the availability and price fluctuations of crop feedstocks may limit biofuel production in certain circumstances. Legal restrictions on using food crops as feedstocks present obstacles to scaling up production. Temporary constraints related to feedstock costs and availability, as evidenced by changes and postponements of biofuel blending mandates in various countries (particularly during the COVID-19 pandemic) also pose challenges. Technological hurdles exist for advanced biofuels that implicate premium pricing. Still, 2G ethanol from sugarcane meets very strict feedstock requirements with a carbon footprint so low that only electric vehicles charged in Norway could have life-cycle GHG emissions at the same level as a 2G ethanol-fueled combustion engine car. The authors evaluate whether and how much electrification could contribute to advance the decarbonization efforts in different countries. Drawing from these observations, the authors express their viewpoints to assist researchers and policymakers in the energy sector in formulating viable approaches to combat the climate crisis.     

Net greenhouse gas fluxes in Brazilian ethanol production systems

Biofuels are both a promising solution to global warming mitigation and a potential contributor to the problem. Several life cycle assessments of bioethanol have been conducted to address these questions. We performed a synthesis of the available data on Brazilian ethanol production focusing on greenhouse gas (GHG) emissions and carbon (C) sinks in the agricultural and industrial phases. Emissions of carbon dioxide (CO₂) from fossil fuels, methane (CH₄) and nitrous oxide (N₂O) from sources commonly included in C footprints, such as fossil fuel usage, biomass burning, nitrogen fertilizer application, liming and litter decomposition were accounted for. In addition, black carbon (BC) emissions from burning biomass and soil C sequestration were included in the balance. Most of the annual emissions per hectare are in the agricultural phase, both in the burned system (2209 out of a total of 2398 kg C_eq), and in the unburned system (559 out of 748 kg C_eq). Although nitrogen fertilizer emissions are large, 111 kg C_eq ha^?1 yr^?1, the largest single source of emissions is biomass burning in the manual harvest system, with a large amount of both GHG (196 kg C_eq ha^?1 yr^?1). and BC (1536 kg C_eq ha^?1 yr^?1). Besides avoiding emissions from biomass burning, harvesting sugarcane mechanically without burning tends to increase soil C stocks, providing a C sink of 1500 kg C ha^?1 yr^?1 in the 30 cm layer. The data show a C output: input ratio of 1.4 for ethanol produced under the conventionally burned and manual harvest compared with 6.5 for the mechanized harvest without burning, signifying the importance of conservation agricultural systems in bioethanol feedstock production.     

Integration in a depot‐based decentralized biorefinery system: Corn stover‐based cellulosic biofuel

The current or “conventional” paradigm for producing process energy in a biorefinery processing cellulosic biomass is on‐site energy recovery through combustion of residual solids and biogas generated by the process. Excess electricity is then exported, resulting in large greenhouse gas (GHG) credits. However, this approach will cause lifecycle GHG emissions of biofuels to increase as more renewable energy sources (wind, solar, etc.) participate in grid‐electricity generation, and the GHG credits from displacing fossil fuel decrease. To overcome this drawback, a decentralized (depot‐based) biorefinery can be integrated with a coal‐fired power plant near a large urban area. In an integrated, decentralized, depot‐based biorefinery (IDB), the residual solids are co‐fired with coal either in the adjacent power plant or in coal‐fired boilers elsewhere to displace coal. An IDB system does not rely on indirect GHG credits through grid‐electricity displacement. In an IDB system, biogas from the wastewater treatment facility is also upgraded to biomethane and used as a transportation biofuel. The GHG savings per unit of cropland in the IDB systems (2.7–2.9 MgCO₂/ha) are 1.5–1.6 fold greater than those in a conventional centralized system (1.7–1.8 MgCO₂/ha). Importantly, the biofuel selling price in the IDBs is lower by 28–30 cents per gasoline‐equivalent liter than in the conventional centralized system. Furthermore, the total capital investment per annual biofuel volume in the IDB is much lower (by ~80%) than that in the conventional centralized system. Therefore, utilization of biomethane and residual solids in the IDB systems leads to much lower biofuel selling prices and significantly greater GHG savings per unit of cropland participating in the biorefinery system compared to the conventional centralized biorefineries.     

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.     

Policy Implications of Allocation Methods in the Life Cycle Analysis of Integrated Corn and Corn Stover Ethanol Production

A biorefinery may produce multiple fuels from more than one feedstock. The ability of these fuels to qualify as one of the four types of biofuels under the US Renewable Fuel Standard and to achieve a low carbon intensity score under California’s Low Carbon Fuel Standard can be strongly influenced by the approach taken to their life cycle analysis (LCA). For example, in facilities that may co-produce corn grain and corn stover ethanol, the ethanol production processes can share the combined heat and power (CHP) that is produced from the lignin and liquid residues from stover ethanol production. We examine different LCA approaches to corn grain and stover ethanol production considering different approaches to CHP treatment. In the baseline scenario, CHP meets the energy demands of stover ethanol production first, with additional heat and electricity generated sent to grain ethanol production. The resulting greenhouse gas (GHG) emissions for grain and stover ethanol are 57 and 25 g-CO₂eq/MJ, respectively, corresponding to a 40 and 74 % reduction compared to the GHG emissions of gasoline. We illustrate that emissions depend on allocation of burdens of CHP production and corn farming, along with the facility capacities. Co-product handling techniques can strongly influence LCA results and should therefore be transparently documented.     

Land management change greatly impacts biofuels’ greenhouse gas emissions

Harvesting corn stover for biofuel production may decrease soil organic carbon (SOC) and increase greenhouse gas (GHG) emissions. Adding additional organic matter into soil or reducing tillage intensity, however, could potentially offset this SOC loss. Here, using SOC and life cycle analysis (LCA) models, we evaluated the impacts of land management change (LMC), that is, stover removal, organic matter addition, and tillage on spatially explicit SOC level and biofuels’ overall life cycle GHG emissions in US corn–soybean production systems. Results indicate that under conventional tillage (CT), 30% stover removal (dry weight) may reduce baseline SOC by 0.04 t C ha^?1 yr^?1 over a 30‐year simulation period. Growing a cover crop during the fallow season or applying manure, on the other hand, could add to SOC and further reduce biofuels’ life cycle GHG emissions. With 30% stover removal in a CT system, cover crop and manure application can increase SOC at the national level by about 0.06 and 0.02 t C ha^?1 yr^?1, respectively, compared to baseline cases without such measures. With contributions from this SOC increase, the life cycle GHG emissions for stover ethanol are more than 80% lower than those of gasoline, exceeding the US Renewable Fuel Standard mandate of 60% emissions reduction in cellulosic biofuels. Reducing tillage intensity while removing stover could also limit SOC loss or lead to SOC gain, which would lower stover ethanol life cycle GHG emissions to near or under the mandated 60% reduction. Without these organic matter inputs or reduced tillage intensity, however, the emissions will not meet this mandate. More efforts are still required to further identify key practical LMCs, improve SOC modeling, and accounting for LMCs in biofuel LCAs that incorporate stover removal.     

Consequential Life Cycle Assessment of Policy Vulnerability to Price Effects

The application of life cycle assessment (LCA) in a policy context highlights the need for a “consequential” LCA (CLCA), which differs from an “attributional” LCA (ALCA). Although CLCA offers some advantages over ALCA, such as a capacity to account for emissions resulting from both substitution and price effects, it entails additional assumptions and cost and may yield estimates that are more uncertain (e.g., estimates of impact of biofuel policies on greenhouse gas [GHG] emissions). We illustrate how a CLCA that relies on simple partial equilibrium models could provide important insights on the direction and magnitude of price effects while limiting the complexity of CLCA. We describe how such a CLCA, when applied early in the policy life cycle, could help identify policy formulations that reduce the magnitude of adverse price effects relative to the beneficial substitution effect on emissions because—as the experience with biofuel regulations indicates—regulating price effects is costly and controversial. We conclude that the salient contribution of CLCA in the policy process might lie in warning policy makers about the vulnerabilities in a policy with regard to environmental impact and to help modify potentially counterproductive formulations rather than in deriving the precise estimates for uncertain variables, such as the life cycle GHG intensity of product or average indirect emissions.     

Aboveground productivity and soil carbon storage of biofuel crops in Ohio

Biofuel crops may help achieve the goals of energy‐efficient renewable ethanol production and greenhouse gas (GHG) mitigation through carbon (C) storage. The objective of this study was to compare the aboveground biomass yields and soil organic C (SOC) stocks under four crops (no‐till corn, switchgrass, indiangrass, and willow) 7 years since establishment at three sites in Ohio to determine if high‐yielding biofuel crops are also capable of high levels of C storage. Corn grain had the highest potential ethanol yields, with an average of more than 4100 L ha^?1, and ethanol yields increased if both corn grain and stover were converted to biofuel, while willow had the lowest yields. The SOC concentration in soils under biofuels was generally unaffected by crop type; at one site, soil in the top 10 cm under willow contained nearly 13 Mg C ha^?1 more SOC (or 29% more) than did soils under switchgrass or corn. Crop type affected SOC content of macroaggregates in the top 10 cm of soil, where macroaggregates in soil under corn had lower C, N and C : N ratios than those under perennial grasses or trees. Overall, the results suggest that no‐till corn is capable of high ethanol yields and equivalent SOC stocks to 40 cm depth. Long‐term monitoring and measurement of SOC stocks at depth are required to determine whether this trend remains. In addition, ecological, energy, and GHG assessments should be made to estimate the C footprint of each feedstock.     

Greenhouse gas emissions and abatement costs of biofuel production in South Africa

Transport accounts for about one quarter of South Africa's final energy consumption. Most of the energy used is based on fossil fuels causing significant environmental burdens. This threat becomes even more dominant as a significant growth in transport demand is forecasted, especially in South Africa's economic hub, Gauteng province. The South African government has realized the potential of biofuel usage for reducing oil import dependency and greenhouse gas (GHG) and has hence developed a National Biofuels Industrial Strategy to enforce their use. However, there is limited experience in the country in commercial biofuel production and some of the proposed crops (i.e. rapeseed and sugar beet) have not been yet cultivated on a larger scale. Furthermore, there is only limited research available, looking at the feasibility of commercial scale biofuel production or abatement costs of GHG emissions. To assess the opportunities of biofuel production in South Africa, the production costs and consumer price levels of the fuels recommended by the national strategy are analysed in this article. Moreover, the lifecycle GHG emissions and mitigation costs are calculated compared to the calculated fossil fuel reference including coal to liquid (CTL) and gas to liquid (GTL) fuels. The results show that the cost for biofuel production in South Africa are currently significantly higher (between 30% and 80%) than for the reference fossil fuels. The lifecycle GHG emissions of biofuels (especially for sugar cane) are considerably lower (up to 45%) than the reference fossil GHG emissions. The resulting GHG abatement costs are between 1000 and 2500 ZAR₂₀₀₇ per saved ton of carbon dioxide equivalent, which is high compared to the current European CO₂ market prices of ca. 143 ZAR₂₀₀₇ t^?1. The analysis has shown that biofuel production and utilization in South Africa offers a significant GHG‐mitigation potential but at relatively high cost.     

Simulating the effects of harvest and biofuel production on the forest system carbon balance of the Midwest,USA

Forests of the Midwestern United States are an important source of fiber for the wood and paper products industries. Scientists, land managers, and policy makers are interested in using woody biomass and/or harvest residue for biofuel feedstocks. However, the effects of increased biomass removal for biofuel production on forest production and forest system carbon balance remain uncertain. We modeled the carbon (C) cycle of the forest system by dividing it into two distinct components: (1) biological (net ecosystem production, net primary production, autotrophic and heterotrophic respiration, vegetation, and soil C content) and (2) industrial (harvest operations and transportation, production, use, and disposal of major wood products including biofuel and associated C emissions). We modeled available woody biomass feedstock and whole‐system carbon balance of 220 000 km² of temperate forests in the Upper Midwest, USA by coupling an ecosystem process model to a collection of greenhouse gas life‐cycle inventory models and simulating seven forest harvest scenarios in the biological ecosystem and three biofuel production scenarios in the industrial system for 50 years. The forest system was a carbon sink (118 g C m^?2 yr^?1) under current management practices and forest product production rates. However, the system became a C source when harvest area was doubled and biofuel production replaced traditional forest products. Total carbon stores in the vegetation and soil increased by 5–10% under low‐intensity management scenarios and current management, but decreased up to 3% under high‐intensity harvest regimes. Increasing harvest residue removal during harvest had more modest effects on forest system C balance and total biomass removal than increasing the rate of clear‐cut harvests or area harvested. Net forest system C balance was significantly, and negatively correlated (R² = 0.67) with biomass harvested, illustrating the trade‐offs between increased C uptake by forests and utilization of woody biomass for biofuel feedstock.     

Global relative species loss due to first‐generation biofuel production for the transport sector

The global demand for biofuels in the transport sector may lead to significant biodiversity impacts via multiple human pressures. Biodiversity assessments of biofuels, however, seldom simultaneously address several impact pathways, which can lead to biased comparisons with fossil fuels. The goal of the present study was to quantify the direct influence of habitat loss, water consumption and greenhouse gas (GHG) emissions on potential global species richness loss due to the current production of first‐generation biodiesel from soybean and rapeseed and bioethanol from sugarcane and corn. We found that the global relative species loss due to biofuel production exceeded that of fossil petrol and diesel production in more than 90% of the locations considered. Habitat loss was the dominating stressor with Chinese corn, Brazilian soybean and Brazilian sugarcane having a particularly large biodiversity impact. Spatial variation within countries was high, with 90th percentiles differing by a factor of 9 to 22 between locations. We conclude that displacing fossil fuels with first‐generation biofuels will likely negatively affect global biodiversity, no matter which feedstock is used or where it is produced. Environmental policy may therefore focus on the introduction of other renewable options in the transport sector.