Integrated Cost and Environmental Life Cycle Analysis of Biomass Supply Systems for Biofuels and Bioenergy

The production of six regionally important cellulosic biomass feedstocks, including pine, eucalyptus, unmanaged hardwoods, forest residues, switchgrass, and sweet sorghum, was analyzed using consistent life cycle methodologies and system boundaries to identify feedstocks with the lowest cost and environmental impacts. Supply chain analysis was performed for each feedstock, calculating costs and supply requirements for the production of 453,592 dry tonnes of biomass per year. Cradle-to-gate environmental impacts from these modeled supply systems were quantified for nine mid-point indicators using SimaPro 7.2 LCA software. Conversion of grassland to managed forest for bioenergy resulted in large reductions in GHG emissions due to carbon uptake associated with direct land use change. By contrast, converting forests to cropland resulted in large increases in GHG emissions. Production of forest-based feedstocks for biofuels resulted in lower delivered cost, lower greenhouse gas (GHG) emissions, and lower overall environmental impacts than the agricultural feedstocks studied. Forest residues had the lowest environmental impact and delivered cost per dry tonne. Using forest-based biomass feedstocks instead of agricultural feedstocks would result in lower cradle-to-gate environmental impacts and delivered biomass costs for biofuel production in the southern U.S.

The increase in greenhouse gas (GHG) emissions is a global concern due to its impact on climate change. To address this challenge, the development of corporate GHG inventories is crucial, enabling organizations to understand and mitigate their emissions. This study aims to statistically analyze whether there was a significant increase in GHG emissions over a 10-year period by organizations from various sectors of the economy that voluntarily published their inventories in the Brazilian GHG Protocol Program. Data were obtained from the inventories of 66 organizations that published at 2013 and 2022 in the Brazilian GHG Protocol Program. The data was processed and analyzed using Minitab software to determine the significance level of the increase in GHG emissions. A total increase of 159,264,734.26 tCO2e in GHG emissions was observed from 2013 to 2022, with 29 organizations reporting higher emissions and 37 showing reductions. However, statistical analysis demonstrated that there was no significant increase in GHG emissions over the study period. The results highlight the importance of organizations conducting their GHG inventories to enhance transparency and make strategic decisions aimed at mitigating their emissions. Publishing inventories allows for monitoring progress and identifying priority areas for effective interventions. No significant increase in GHG emissions was observed over the 10-year period; therefore, this study reinforces the importance of preparing GHG inventories by organizations. The findings can impact public policies on climate change, supporting the introduction of regulations that mandate the development of inventories and the setting of emission reduction and offsetting targets.

The availability of fossil resources is predicted to decrease in the near future: they are a non-renewable source, they cause environmental concerns, and they are subjected to price instability. Utilization of biomass as raw material in a biorefinery is a promising alternative to fossil resources for production of energy carriers and chemicals, as well as for mitigating climate change and enhancing energy security. This paper focuses on a biorefinery concept which produces bioethanol, bioenergy, and biochemicals from switchgrass, a lignocellulosic crop. Results are compared with a fossil reference system producing the same products/services from fossil sources. The biorefinery system is investigated using a Life Cycle Assessment approach, which takes into account all the input and output flows occurring along the production chain. This paper elaborates on methodological key issues like land use change effects and soil N2O emissions, whose influence on final outcomes is weighted in a sensitivity analysis. Since climate change mitigation and energy security are the two most important driving forces for biorefinery development, the assessment has a focus on greenhouse gas (GHG) emissions and cumulative primary energy demand (distinguished into fossil and renewable), but other environmental impact categories (e.g., abiotic depletion, eutrophication, etc.) are assessed as well. The use of switchgrass in a biorefinery offsets GHG emissions and reduces fossil energy demand: GHG emissions are decreased by 79% and about 80% of non-renewable energy is saved. Soil C sequestration is responsible for a large GHG benefit (65 kt CO2-eq/a, for the first 20 years), while switchgrass production is the most important contributor to total GHG emissions of the system. If compared with the fossil reference system, the biorefinery system releases more N2O emissions, while both CO2 and CH4 emissions are reduced. The investigation of the other impact categories revealed that the biorefinery has higher impacts in two categories: acidification and eutrophication. Results are mainly affected by raw material (i.e., switchgrass) production and land use change effects. Steps which mainly influence the production of switchgrass are soil N2O emissions, manufacture of fertilizers (especially those nitrogen-based), processing (i.e., pelletizing and drying), and transport. Even if the biorefinery chain has higher primary energy demand than the fossil reference system, it is mainly based on renewable energy (i.e., the energy content of the feedstock): the provision of biomass with sustainable practices is then a crucial point to ensure a renewable energy supply to biorefineries. This biorefinery system is an effective option for mitigating climate change, reducing dependence on imported fossil fuels, and enhancing cleaner production chains based on local and renewable resources. However, this assessment evidences that determination of the real GHG and energy balance (and all other environmental impacts in general) is complex, and a certain degree of uncertainty is always present in final results. Ranges in final results can be even more widened by applying different combinations of biomass feedstocks, conversion routes, fuels, end-use applications, and methodological assumptions. This study demonstrated that the perennial grass switchgrass enhances carbon sequestration in soils if established on set-aside land, thus, considerably increasing the GHG savings of the system for the first 20 years after crop establishment. Given constraints in land resources and competition with food, feed, and fiber production, high biomass yields are extremely important in achieving high GHG emission savings, although use of chemical fertilizers to enhance plant growth can reduce the savings. Some strategies, aiming at simultaneously maintaining crop yield and reduce N fertilization application through alternative management, can be adopted. However, even if a reduction in GHG emissions is achieved, it should not be disregarded that additional environmental impacts (like acidification and eutrophication) may be caused. This aspect cannot be ignored by policy makers, even if they have climate change mitigation objectives as main goal.

This paper develops a dynamic micro-economic land use model that maximizes social welfare and internalizes externality from greenhouse gas emissions to obtain the optimal land use allocation for traditional row crops and bioenergy crops (corn stover, miscanthus and switchgrass), the mix of cellulosic feedstocks and fuel and food prices. We use this carbon tax policy as a benchmark to compare the implications of existing biofuel policies on land use, social welfare and the environment for the 2007-2022 period. The model is operationalized using yields of perennial grasses obtained from a biophysical model, county level data on yields of traditional row crops and production costs for row crops and bioenergy crops in Illinois. We show that a carbon tax policy that is directly related to carbon intensity of fuels can generate the highest social welfare among alternative policy scenarios. The existing ethanol tax credits result in substantial deadweight losses and higher GHG emissions as compared to the baseline. Ethanol blending mandates with subsidies lead to further welfare losses and higher GHG emissions. To meet advanced biofuel blending mandates, corn stover and miscanthus are used but the mix of viable cellulosic feedstocks varies spatially and temporally. Corn stover is viable mainly in central and northern Illinois while miscanthus acres are primarily concentrated on southern Illinois. The blending mandates lead to a significant shift in acreage from soybeans and pasture to corn and a change in crop rotation and tillage practices.

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Many agricultural regions in China are likely to become appreciably wetter or drier as the global climate warming increases. However, the impact of these climate change patterns on the intensity of soil greenhouse gas (GHG) emissions (GHGI, GHG emissions per unit of crop yield) has not yet been rigorously assessed. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, we found that climate change is expected to cause a 20.0% crop yield loss, while stimulating soil GHG emissions by 12.2% between 2061 and 2090 in China's agricultural regions. A wetter‐warmer (WW) climate would adversely impact crop yield on an equal basis and lead to a 1.8‐fold‐ increase in GHG emissions relative to those in a drier‐warmer (DW) climate. Without water limitation/excess, extreme heat (an increase of more than 1.5°C in average temperature) during the growing season would amplify 15.7% more yield while simultaneously elevating GHG emissions by 42.5% compared to an increase of below 1.5°C. However, when coupled with extreme drought, it would aggravate crop yield loss by 61.8% without reducing the corresponding GHG emissions. Furthermore, the emission intensity in an extreme WW climate would increase by 22.6% compared to an extreme DW climate. Under this intense WW climate, the use of nitrogen fertilizer would lead to a 37.9% increase in soil GHG emissions without necessarily gaining a corresponding yield advantage compared to a DW climate. These findings suggest that the threat of a wetter‐warmer world to efforts to reduce GHG emissions intensity may be as great as or even greater than that of a drier‐warmer world.

Effects of different agricultural organic wastes on soil GHG emissions: During a 4-year field measurement in the North China Plain

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

Previous studies on the life-cycle environmental impacts of corn ethanol and gasoline focused almost exclusively on energy balance and greenhouse gas (GHG) emissions and largely overlooked the influence of regional differences in agricultural practices. This study compares the environmental impact of gasoline and E85 taking into consideration 12 different environmental impacts and regional differences among 19 corn-growing states. Results show that E85 does not outperform gasoline when a wide spectrum of impacts is considered. If the impacts are aggregated using weights developed by the National Institute of Standards and Technology (NIST), overall, E85 generates approximately 6% to 108% (23% on average) greater impact compared with gasoline, depending on where corn is produced, primarily because corn production induces significant eutrophication impacts and requires intensive irrigation. If GHG emissions from the indirect land use changes are considered, the differences increase to between 16% and 118% (33% on average). Our study indicates that replacing gasoline with corn ethanol may only result in shifting the net environmental impacts primarily toward increased eutrophication and greater water scarcity. These results suggest that the environmental criteria used in the Energy Independence and Security Act (EISA) be re-evaluated to include additional categories of environmental impact beyond GHG emissions.

Quantifying the impact of energy consumption sources on GHG emissions in major economies: A machine learning approach

Organic matter is an indispensable element of soil. Its quantity and quality affect its properties, e.g., structure, buffering, sorption capacity, air–water relations, and thermal properties. The purpose of the research was to assess greenhouse gas (GHG) emissions in soybean cultivation, fertilized with biochar from various crops. Two experimental factors were included: the dose of biochar and the type of biochar used as per raw material used in its production. The adopted functional unit was 1 ton of soybeans. To reach the adopted goal, a strict field experiment was carried out. The total amount of GHG emitted by the cultivation was calculated according to the ISO 14040 and ISO 14044 standards. The system boundaries included: GHG emissions from fertilizers and seeds used, GHG emissions related to biochar production, emissions related to fossil fuel combustion, and emissions related to the decomposition of crop residues and soil organic matter and the decomposition of biochar. The results of the research indicate a significant potential of biochar to reduce GHG emissions in agricultural production. From the environmental and production perspective, the addition of biochar at 60 Mg ha−1 is the most advantageous. A further increase in the addition of biochar was related to a decrease in plant yield and an increase in GHG emissions per functional unit of the product. The use of biochar in soybean cultivation resulted in a 25% reduction in GHG emissions compared to the object without the biochar addition. The amount of GHG emissions for soybeans ranged from 846.9 to 1260.1 kg of CO2/Mg. The use of biochar from forest biomass resulted in a higher yield, 12% on average, compared to sunflower husk biochar. The introduction of biochar to soils can be an effective improvement in the economic and environmental efficiency of plant production, as it increases the use of nutrients by the plant and intensifies carbon sequestration in soils.

In the U.S., bioenergy accounts for about 50% of the total renewable energy that is generated. Every stage in the life cycle of using bioenergy (e.g., growing biomass, harvesting biomass, transporting biomass, and converting to fuels or materials) has consequences in terms of the three dimensions of sustainability: economy, environment, and society. An integrated sustainability model (ISM) using system dynamics is developed for a bioenergy system to understand how changes in a bioenergy system influence environmental measures, economic development, and social impacts.Biomass may be used as a source of energy in a variety of ways. The U.S. corn ethanol system forest residue system for electricity generation, and cellulosic ethanol system have been investigated. Predictions, such as greenhouse gas (GHG) savings, soil carbon sequestration, monetary gain, employment, and social cost of carbon are made for a given temporal scale. For the corn ethanol system, the annual tax revenue created by the ethanol industry can offer a significant benefit to society. For the forest residue system for electricity generation, different policy scenarios varying the bioenergy share of the total electricity generation were identified and examined via the ISM. The results of the scenario analysis indicate that an increase in the bioenergy contribution toward meeting the total electricity demand will stimulate the bioenergy market for electricity generation. For the cellulosic ethanol system, the compliance of cellulosic ethanol can be achieved under the advanced bioconversion technologies and the expansion of energy crops. However, nitrate leaching and biodiversity change should be considered when expanding energy crops on marginal land, pasture, and cropland. Moreover, three bioenergy systems reduce GHG emissions significantly, relative to fossil fuel sources that are displaced, and create economic benefits (e.g., GDP and employment). Additionally, a spatial agent-based modeling is developed to understand farmers’ behaviors of energy crop adoption and the viability of cellulosic biofuel commercialization.

The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production and end use costs, greenhouse gas emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol from various feedstocks (switchgrass, corn stover, forest residue, and farmed trees), biodiesel, and diesels derived from natural gas (gas to liquid, or GTL), coal (coal to liquid, or CTL), and coal with biomass (CBTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion ratio, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the structure and methodology of AltSim, presents results, and provides a detailed sensitivity analysis. The Energy Independence and Security Act (EISA) of 2007 sets a goal for the increased use of biofuels in the U.S., ultimately reaching 36 billion gallons by 2022. AltSim's base case assumes EPA projected feedstock costs in 2022 (EPA, 2009). For the base case assumptions, AltSim estimates per gallon production costs for the five ethanol feedstocks (corn, switchgrass, corn stover, forest residue, and farmed trees) of $1.86, $2.32, $2.45, $1.52, and $1.91, respectively. The projected production cost of biodiesel is $1.81/gallon. The estimates for CTL without biomass range from $1.36 to $2.22. With biomass, the estimated costs increase, ranging from $2.19 per gallon for the CTL option with 8% biomass to $2.79 per gallon for the CTL option with 30% biomass and carbon capture and sequestration. AltSim compares the greenhouse gas emissions (GHG) associated with both the production and consumption of the various fuels. EISA allows fuels emitting 20% less greenhouse gases (GHG) than conventional gasoline and diesels to qualify as renewable fuels. This allows several of the CBTL options to be included under the EISA mandate. The estimated GHG emissions associated with the production of gasoline and diesel are 19.80 and 18.40 kg of CO{sub 2} equivalent per MMBtu (kgCO{sub 2}e/MMBtu), respectively (NETL, 2008). The estimated emissions are significantly higher for several alternatives: ethanol from corn (70.6), GTL (51.9), and CTL without biomass or sequestration (123-161). Projected emissions for several other alternatives are lower; integrating biomass and sequestration in the CTL processes can even result in negative net emissions. For example, CTL with 30% biomass and 91.5% sequestration has estimated production emissions of -38 kgCO{sub 2}e/MMBtu. AltSim also estimates the projected well-to-wheel, or lifecycle, emissions from consuming each of the various fuels. Vehicles fueled with conventional diesel or gasoline and driven 12,500 miles per year emit 5.72-5.93 tons of CO{sub 2} equivalents per year (tCO{sub 2}e/yr). Those emissions are significantly higher for vehicles fueled with 100% ethanol from corn (8.03 tCO{sub 2}e/yr) or diesel from CTL without sequestration (10.86 to 12.85 tCO{sub 2}/yr). Emissions could be significantly lower for vehicles fueled with diesel from CBTL with various shares of biomass. For example, for CTL with 30% biomass and carbon sequestration, emissions would be 2.21 tCO{sub 2}e per year, or just 39% of the emissions for a vehicle fueled with conventional diesel. While the results presented above provide very specific estimates for each option, AltSim's true potential is as a tool for educating policy makers and for exploring 'what if?' type questions. For example, AltSim allows one to consider the affect of various levels of carbon taxes on the production cost estimates, as well as increased costs to the end user on an annual basis. Other sections of AltSim allow the user to understand the implications of various polices in terms of costs to the government or land use requirements. AltSim's structure allows the end user to explore each of these alternatives and understand the sensitivities implications associated with each assumption as well as the implications for bottom line economics, energy use, and greenhouse gas emissions.

Biofuels have been widely promoted as an important part of the global energy mix, due to public interest in alternative energy sourcing and a potential to reduce greenhouse gas emissions. Concurrently, questions have been raised about the social and environmental costs of biofuel production. While previous studies have focused primarily on biofuel production from conventional, starch-based feedstocks, this study provides a preliminary analysis of the production of cellulosic-based ethanol mandated in the U.S. renewable fuel standard. Using a global general equilibrium framework and switchgrass as a model bioenergy crop, results suggests that meeting the mandate will further intensify competition for land both domestically and abroad. Impacts of cellulosic production on global commodity prices, quantities, export, and land use are also documented.

Production of furfural from corn-cobs