Bioethanol production from sugarcane and emissions of greenhouse gases – known and unknowns

Bioethanol production from sugarcane is discussed as an alternative energy source to reduce dependencies of regional economies on fossil fuels. Even though bioethanol production from sugarcane is considered to be a beneficial and cost‐effective greenhouse gas (GHG) mitigation strategy, it is still a matter of controversy due to insufficient information on the total GHG balance of this system. Aside from the necessity to account for the impact of land use change (LUC), soil N₂O emissions during sugarcane production and emissions of GHG due to preharvest burning may significantly impact the GHG balance. Based on a thorough literature review, we show that direct N₂O emissions from sugarcane fields due to nitrogen (N) fertilization result in an emission factor of 3.87±1.16% which is much higher than suggested by IPCC (1%). N₂O emissions from N fertilization accounted for 40% of the total GHG emissions from ethanol–sugarcane production, with an additional 17% from trash burning. If LUC‐related GHG emissions are considered, the total GHG balance turns negative mainly due to vegetation carbon losses. Our study also shows that major gaps in knowledge still exist about GHG sources related to agricultural management during sugarcane production, e.g. effects of irrigation, vinasse and filter cake application. Therefore, more studies are needed to assess if bioethanol from sugarcane is a viable option to reduce energy‐related GHG emissions.     

Emergy analysis of cassava chips-suitable feedstock for fuel ethanol in China

The theory and indices of Odum's concept of emergy are explained. The environmental and economic inputs and sustainability of cassava chips production system are evaluated by emergy methodology. The emergy indices of cassava chips production system were calculated as follows: Tr (transformity) was 6.85E + 11 sej/kg, EYR (emergy yield ratio) was 1.11, ELR (environmental loading ratio) was 1.75, EIR (emergy investment ratio) was 9.33, and ESI (emergy sustainability indice) was 0.63. The emergy indices of four kinds of feedstock for fuel ethanol—corn, wheat, sugarcane, and cassava chips—were compared. Least solar energy was consumed when taking cassava chips as feedstock for fuel ethanol. According to the emergy indices, using cassava chips as the feedstock of fuel ethanol is helpful for sustainable development in China.     

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.     

Regional variations in life cycle greenhouse gas emissions of canola‐derived jet fuel produced in western Canada

This study investigates the life cycle GHG emissions of jet fuel produced via the hydroprocessed esters and fatty acids (HEFA) pathway from canola grown in western Canada, with a focus on characterizing regional influences on emissions. We examine the effects of geographic variations in soil type, agricultural inputs, farming practices, and direct land use changes on life cycle GHG emissions. We utilize GREET 2016 but replace default feedstock production inputs with geographically representative data for canola production across eight western Canadian regions (representing 99% of Canada's canola production) and replace the default conversion process with data from a novel process model previously developed in ASPEN in our research group wherein oil extraction is integrated with the HEFA‐based fuel production process. Although canola production inputs and yields vary across the regions, resulting life cycle GHG emissions are similar if effects of land use and land management changes (LMC) are not included; 44–48 g CO₂e/MJ for the eight regions (45%–50% reduction compared to petroleum jet fuel). Results are considerably more variable, 16–58 g CO₂e/MJ, when including effects of land use and LMC directly related to conversion of lands from other uses to canola production (34%–82% reduction compared to petroleum jet fuel). We establish the main sources of emissions in the life cycle of canola jet fuel (N‐fertilizer and related emissions, fuel production), identify that substantially higher emissions may occur when using feedstock sourced from regions where conversion of forested land to cropland had occurred, and identify benefits of less intense tillage practices and increased use of summerfallow land. The methods and findings are relevant in jurisdictions internationally that are incorporating GHG emissions reductions from aviation fuels in a low carbon fuel market or legislating carbon intensity reduction requirements.     

Production, transportation and milling costs of sweet sorghum as a feedstock for centralized bioethanol production in the upper Midwest

Sweet sorghum has been identified as a possible ethanol feedstock because of its biomass yield and high concentration of readily fermentable sugars. It has found limited use, however, because of poor post-harvest storage characteristics and short harvest window in cooler climates. Previous research (Bennett, A.S., Anex, R.P., 2008. Farm-gate production costs of sweet sorghum as a bioethanol feedstock. Transactions of the ASABE 51(2), 603-613) indicates that fermentable carbohydrates (FC) can be produced at less expense from sweet sorghum than from corn grain. Previous research, however, did not include costs associated with off-farm transportation, storage, or capital costs associated with milling and energy recovery equipment that are required to provide FC suitable for biological conversion. This study includes these additional costs and reevaluates sweet sorghum as a biocommodity feedstock. A total of eight harvest-transport-processing options are modeled, including 4-row self-propelled and 2-row tractor-pulled forage harvesters, two different modes of in-field transport, fresh processing, on-farm ensilage and at-plant ensilage. Monte Carlo simulation and sensitivity analysis are used to account for system variability and compare scenarios. Transportation costs are found to be significant ranging from $33 to $71 Mg (-1) FC, with highest costs associated with at-plant ensilage scenarios. Economies of scale benefit larger milling equipment and boiler systems reducing FC costs by more than 50% when increasing annual plant capacity from 37.9 to 379 million liters. Ensiled storage of high moisture sweet sorghum in bunkers can lead to significant losses of FC (>20%) and result in systems with net FC costs well above those of corn-derived FC. Despite relatively high transport costs, seasonal, fresh processed sweet sorghum is found to produce FC at costs competitive with corn grain derived FC.     

Sugarcane as a Bioenergy Source: History,Performance, and Perspectives for Second-Generation Bioethanol

For hundreds of years, sugarcane has been a main source of sugar, used as a sweetener, and alcohol, fermented from the plant juice. The high cost of petroleum towards the end of the twentieth century stimulated the development of new fermentation technologies for producing economically viable bioethanol from sugarcane as an alternative to importing petroleum. More recently, awareness of the effects of greenhouse gas emissions due to the global climate changes propelled bioethanol as a viable renewable fuel. Consequently, sugarcane gained importance as a bioenergy feedstock. However, the lack of knowledge about sugarcane physiology, notably on aspects of photosynthesis and source–sink relationship, has slowed the advance of this expanding bioenergy-producing system. Besides the changes in source–sink relationship, another option to increase bioethanol production even more would be to use a greater fraction of the total biomass of plants, i.e., not only the soluble sugars but also the sugars present in the cell wall fractions. Here, we review the history of sugarcane as a bioenergy crop and discuss some of the relevant routes that could be adopted in the near future to make sugarcane an even better feedstock for producing biofuels.     

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.     

Life cycle assessment of energy and GHG emissions during ethanol production from grass straws using various pretreatment processes

Purpose  

The aim of this study was to perform a well-to-pump life cycle assessment (LCA) to investigate the overall net energy balance and environmental impact of bioethanol production using Tall Fescue grass straw as feedstock. The energy requirements and greenhouse gas (GHG) emissions were compared to those of gasoline to explore the potential of bioethanol as sustainable fuel.     

Process design and optimization of bioethanol production from cassava bagasse using statistical design and genetic algorithm

Abstract

Bioethanol production from agro-industrial residues is gaining attention because of the limited production of starch grains and sugarcane, and food–fuel conflict. The aim of the present study is to maximize the bioethanol production using cassava bagasse as a feedstock. Enzymatic liquefaction, by α-amylase, followed by simultaneous saccharification and fermentation (SSF), using glucoamylase and Zymomonas mobilis MTCC 2427, was investigated for bioethanol production from cassava bagasse. The factors influencing ethanol production process were identified and screened for significant factors using Plackett–Burman design. The significant factors (cassava bagasse concentration (10–50?g/L), concentration of α-amylase (5–25% (v/v), and temperature of fermentation (27–37?°C)) were optimized by employing Box–Behnken design and genetic algorithm. The maximum ethanol concentrations of 25.594?g/L and 25.910?g/L were obtained from Box–Behnken design and genetic algorithm, respectively, under optimum conditions. Thus, the study provides valuable insights in utilizing the cost-effective industrial residue, cassava bagasse, for the bioethanol production.     

Straw utilization for biofuel production: A consequential assessment of greenhouse gas emissions from bioethanol and biomethane provision with a focus on the time dependency of emissions

The shift from straw incorporation to biofuel production entails emissions from production, changes in soil organic carbon (SOC) and through the provision of (co‐)products and entailed displacement effects. This paper analyses changes in greenhouse gas (GHG) emissions arising from the shift from straw incorporation to biomethane and bioethanol production. The biomethane concept comprises comminution, anaerobic digestion and amine washing. It additionally provides an organic fertilizer. Bioethanol production comprises energetic use of lignin, steam explosion, enzymatic hydrolysis and co‐fermentation. Additionally, feed is provided. A detailed consequential GHG balance with in‐depth focus on the time dependency of emissions is conducted: (a) the change in the atmospheric load of emissions arising from the change in the temporal occurrence of emissions comparing two steady states (before the shift and once a new steady state has established); and (b) the annual change in overall emissions over time starting from the shift are assessed. The shift from straw incorporation to biomethane production results in net changes in GHG emissions of (a) ?979 (?436 to ?1,654) and (b) ?955 (?220 to ?1,623) kg CO₂‐eq. per t_{dry matter} straw converted to biomethane (minimum and maximum). The shift to bioethanol production results in net changes of (a) ?409 (?107 to ?610) and (b) ?361 (57 to ?603) kg CO₂‐eq. per t_{dry matter} straw converted to bioethanol. If the atmospheric load of emissions arising from different timing of emissions is neglected in case (a), the change in GHG emissions differs by up to 54%. Case (b) reveals carbon payback times of 0 (0–49) and 19 (1–100) years in case of biomethane and bioethanol production, respectively. These results demonstrate that the detailed inclusion of temporal aspects into GHG balances is required to get a comprehensive understanding of changes in GHG emissions induced by the introduction of advanced biofuels from agricultural residues.     

C_4 Plants as Biofuel Feedstocks: Optimising Biomass Production and Feedstock Quality from a Lignocellulosic Perspective

The main feedstocks for bioethanol are sugarcane (Saccharum officinarum) and maize (Zea mays),both of which are C4 grasses,highly efficient at converting solar energy into chemical energy,and both are food crops.As the systems for lignocellulosic bioethanol production become more efficient and cost effective,plant biomass from any source may be used as a feedstock for bioethanol production.Thus,a move away from using food plants to make fuel is possible,and sources of biomass such as wood from forestry and ...     

A Novel Wild-Type Saccharomyces cerevisiae Strain TSH1 in Scaling-Up of Solid-State Fermentation of Ethanol from Sweet Sorghum Stalks

The rising demand for bioethanol, the most common alternative to petroleum-derived fuel used worldwide, has encouraged a feedstock shift to non-food crops to reduce the competition for resources between food and energy production. Sweet sorghum has become one of the most promising non-food energy crops because of its high output and strong adaptive ability. However, the means by which sweet sorghum stalks can be cost-effectively utilized for ethanol fermentation in large-scale industrial production and commercialization remains unclear. In this study, we identified a novel Saccharomyces cerevisiae strain, TSH1, from the soil in which sweet sorghum stalks were stored. This strain exhibited excellent ethanol fermentative capacity and ability to withstand stressful solid-state fermentation conditions. Furthermore, we gradually scaled up from a 500-mL flask to a 127-m³ rotary-drum fermenter and eventually constructed a 550-m³ rotary-drum fermentation system to establish an efficient industrial fermentation platform based on TSH1. The batch fermentations were completed in less than 20 hours, with up to 96 tons of crushed sweet sorghum stalks in the 550-m³ fermenter reaching 88% of relative theoretical ethanol yield (RTEY). These results collectively demonstrate that ethanol solid-state fermentation technology can be a highly efficient and low-cost solution for utilizing sweet sorghum, providing a feasible and economical means of developing non-food bioethanol.     

Contribution of above‐ and belowground bioenergy crop residues to soil carbon

GHG mitigation by bioenergy crops depends on crop type, management practices, and the input of residue carbon (C) to the soil. Perennial grasses may increase soil C compared to annual crops because of more extensive root systems, but it is less clear how much soil C is derived from above‐ vs. belowground inputs. The objective of this study was to synthesize the existing knowledge regarding soil C inputs from above‐ and belowground crop residues in regions cultivated with sugarcane, corn, and miscanthus, and to predict the impact of residue removal and tillage on soil C stocks. The literature review showed that aboveground inputs to soil C (to 1‐m depth) ranged from 70% to 81% for sugarcane and corn vs. 40% for miscanthus. Modeled aboveground C inputs (to 30 cm depth) ranged from 54% to 82% for sugarcane, but were 67% for miscanthus. Because 50% of observed miscanthus belowground biomass is below 30 cm depth, it may be necessary to increase the depth of modeled soil C dynamics to reconcile modeled belowground C inputs with measured. Modeled removal of aboveground corn residue (25–100%) resulted in C stock reduction in areas of corn–corn–soybean rotation under conventional tillage, while no‐till management lessoned this impact. In sugarcane, soil C stocks were reduced when total aboveground residue was removed at one site, while partial removal of sugarcane residue did not reduce soil C stocks in either area. This study suggests that aboveground crop residues were the main C‐residue source to the soil in the current bioethanol sector (corn and sugarcane) and the indiscriminate removal of crop residues to produce cellulosic biofuels can reduce soil C stocks and reduce the environmental benefits of bioenergy. Moreover, a switch to feedstocks such as miscanthus with more allocation to belowground C could increase soil C stocks at a much faster rate.     

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.     

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.     

Reference and functional unit can change bioenergy pathway choices

Purpose

This study aims to compare the life cycle greenhouse gas (GHG) emissions of two cellulosic bioenergy pathways (i.e., bioethanol and bioelectricity) using different references and functional units. It also aims to address uncertainties associated with a comparative life cycle analysis (LCA) for the two bioenergy pathways.

Methods

We develop a stochastic, comparative life cycle GHG analysis model for a switchgrass-based bioenergy system. Life cycle GHG offsets of the biofuel and bioelectricity pathways for cellulosic bioenergy are compared. The reference system for bioethanol is the equivalent amount of gasoline to provide the same transportation utility (e.g., vehicle driving for certain distance) as bioethanol does. We use multiple reference systems for bioelectricity, including the average US grid, regional grid in the USA according to the North American Electric Reliability Corporation (NERC), and average coal-fired power generation, on the basis of providing the same transportation utility. The functional unit is one unit of energy content (MJ). GHG offsets of bioethanol and bioelectricity relative to reference systems are compared in both grams carbon dioxide equivalents per hectare of land per year (g CO₂-eq/ha-yr) and grams carbon dioxide equivalents per vehicle kilometer traveled (g CO₂-eq/km). For the latter, we include vehicle cycle to make the comparison meaningful. To address uncertainty and variability, we derive life cycle GHG emissions based on probability distributions of individual parameters representing various unit processes in the life cycle of bioenergy pathways.

Results and discussion

Our results show the choice of reference system and functional unit significantly changes the competition between switchgrass-based bioethanol and bioelectricity. In particular, our results show that the bioethanol pathway produces more life cycle GHG emissions than the bioelectricity pathway on a per unit energy content or a per unit area of crop land basis. However, the bioethanol pathway can offer more GHG offsets than the bioelectricity pathway on a per vehicle kilometer traveled basis when using bioethanol and bioelectricity for vehicle operation. Given the current energy mix of regional grids, bioethanol can potentially offset more GHG emissions than bioelectricity in all grid regions of the USA.

Conclusions

The reference and functional unit can change bioenergy pathway choices. The comparative LCA of bioenergy systems is most useful for decision support only when it is spatially explicit to address regional specifics and differences. The difference of GHG offsets from bioethanol and bioelectricity will change as the grid evolves. When the grids get cleaner over time, the favorability of bioethanol for GHG offsets increases.     

Ethanol production potential of sweet sorghum assessed using forage fiber analysis procedures

Sweet sorghum (Sorghum bicolor (L.) Moench) is widely recognized as a highly promising biomass energy crop with particular potential to complement sugarcane production in diversified cropping systems. Agronomic assessments have led to identification of four cultivars well suited for such sugarcane‐based production systems in southern Louisiana. Sweet sorghum biofuel production systems are currently being developed, and research producing large sample numbers requiring ethanol yield assessment is anticipated. Fiber analysis approaches developed for forage evaluation appear to be useful for screening such large numbers of samples for relative ethanol yield. Chemical composition, forage fiber characteristics, digestibility, and ethanol production of sweet sorghum bagasse from the four cultivars were assessed. Measures of detergent fiber, lignin, and digestibility were highly correlated with ethanol production (P < 0.01). The best linear regression models accounted for about 80% of the variation among cultivars in ethanol production. Bagasse from the cultivar Dale produced more ethanol per gram of material than any of the other cultivars. This superior ethanol production was apparently associated with less lignin in stems of Dale. Forage evaluation measures including detergent fiber analyses, in vitro digestibility, and an in vitro gas production technique successfully identified the cultivar superior in ethanol yield indicating their usefulness for screening sweet sorghum samples for potential ethanol production in research programs generating large sample numbers from evaluations of germ plasm or agronomic treatments. These screening procedures reduce time and expense of alternatives such as hexose sugar assessment for calculating theoretical ethanol yield.     

An economic analysis of sweet sorghum cultivation for ethanol production in North China

Sweet sorghum [Sorghum bicolor (L.) Moench] is a promising non‐food energy crop. The objective of this study was to determine the economic costs and input sensitivity of sweet sorghum compared to cotton, maize, and sunflower, at two saline‐alkali sites in Shandong (Wudi County) and Inner Mongolia (Wuyuan County) provinces of China. The data were collected quantitatively based on a face‐to‐face interview with 100 and 67 sweet sorghum growers at the two sites, respectively. The sweet sorghum grown at Wudi had lower external input (5469 CNY ha^?1), higher net return (7305 CNY ha^?1) and benefit‐cost ratio (2.36) than its reference crop, cotton (18 454 CNY ha^?1; 3615 CNY ha^?1; 1.24). At Wuyuan, the sweet sorghum showed contrasting economic performance (19 541 CNY ha^?1; ?3438 CNY ha^?1; 0.91), which was largely because of the higher labor costs compared to sunflower (10 896 CNY ha^?1; 15 133 CNY ha^?1; 2.49); and maize (9108 CNY ha^?1; 14 760 CNY ha^?1; 2.76). The productivity of sweet sorghum per unit of external input costs (kg CNY^?1) was 13.12 for Wudi and only 3.26 for Wuyuan. Based on the Cobb‐Douglas production function, the external inputs of diesel and seed had a significantly positive impact on the profitability of sweet sorghum at Wudi but not at Wuyuan. However, the costs of irrigation and film cover were significantly negative. The energy crop, sweet sorghum, showed a better return to scale on investment than cotton and sunflower.     

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.     

GHG emissions and other environmental impacts of indirect land use change mitigation

The implementation of measures to increase productivity and resource efficiency in food and bioenergy chains as well as to more sustainably manage land use can significantly increase the biofuel production potential while limiting the risk of causing indirect land use change (ILUC). However, the application of these measures may influence the greenhouse gas (GHG) balance and other environmental impacts of agricultural and biofuel production. This study applies a novel, integrated approach to assess the environmental impacts of agricultural and biofuel production for three ILUC mitigation scenarios, representing a low, medium and high miscanthus‐based ethanol production potential, and for three agricultural intensification pathways in terms of sustainability in Lublin province in 2020. Generally, the ILUC mitigation scenarios attain lower net annual emissions compared to a baseline scenario that excludes ILUC mitigation and bioethanol production. However, the reduction potential significantly depends on the intensification pathway considered. For example, in the moderate ILUC mitigation scenario, the net annual GHG emissions in the case study are 2.3 MtCO₂‐eq yr^?1 (1.8 tCO₂‐eq ha^?1 yr^?1) for conventional intensification and ?0.8 MtCO₂‐eq yr^?1 (?0.6 tCO₂‐eq ha^?1 yr^?1) for sustainable intensification, compared to 3.0 MtCO₂‐eq yr^?1 (2.3 tCO₂‐eq ha^?1 yr^?1) in the baseline scenario. In addition, the intensification pathway is found to be more influential for the GHG balance than the ILUC mitigation scenario, indicating the importance of how agricultural intensification is implemented in practice. Furthermore, when the net emissions are included in the assessment of GHG emissions from bioenergy, the ILUC mitigation scenarios often abate GHG emissions compared to gasoline. But sustainable intensification is required to attain GHG abatement potentials of 90% or higher. A qualitative assessment of the impacts on biodiversity, water quantity and quality, soil quality and air quality also emphasizes the importance of sustainable intensification.