Environmental implications of the use of agro‐industrial residues for biorefineries: application of a deterministic model for indirect land‐use changes

Biorefining agro‐industrial biomass residues for bioenergy production represents an opportunity for both sustainable energy supply and greenhouse gas (GHG) emissions mitigation. Yet, is bioenergy the most sustainable use for these residues? To assess the importance of the alternative use of these residues, a consequential life cycle assessment (LCA) of 32 energy‐focused biorefinery scenarios was performed based on eight selected agro‐industrial residues and four conversion pathways (two involving bioethanol and two biogas). To specifically address indirect land‐use changes (iLUC) induced by the competing feed/food sector, a deterministic iLUC model, addressing global impacts, was developed. A dedicated biochemical model was developed to establish detailed mass, energy, and substance balances for each biomass conversion pathway, as input to the LCA. The results demonstrated that, even for residual biomass, environmental savings from fossil fuel displacement can be completely outbalanced by iLUC, depending on the feed value of the biomass residue. This was the case of industrial residues (e.g. whey and beet molasses) in most of the scenarios assessed. Overall, the GHGs from iLUC impacts were quantified to 4.1 t CO₂‐eq.ha^?1_demanded yr^?1 corresponding to 1.2–1.4 t CO₂‐eq. t^?1 dry biomass diverted from feed to energy market. Only, bioenergy from straw and wild grass was shown to perform better than the alternative use, as no competition with the feed sector was involved. Biogas for heat and power production was the best performing pathway, in a short‐term context. Focusing on transport fuels, bioethanol was generally preferable to biomethane considering conventional biogas upgrading technologies. Based on the results, agro‐industrial residues cannot be considered burden‐free simply because they are a residual biomass and careful accounting of alternative utilization is a prerequisite to assess the sustainability of a given use. In this endeavor, the iLUC factors and biochemical model proposed herein can be used as templates and directly applied to any bioenergy consequential study involving demand for arable land.     

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.     

Give them credit‐the greenhouse gas performance of regional biogas systems

Anaerobic digestion to produce biogas is an important decentralised renewable energy technology. Production varies extensively between different countries and within countries, as biogas production is heavily dependent on local and regional feedstocks. In Germany, distinct regional differences can be observed. Therefore, understanding the kinds of biogas systems operating within a region is crucial to determine their greenhouse gas (GHG) mitigation potential and carbon neutrality. This is the first study to conduct an integrated life cycle assessment of biogas configurations in the landscape (biogas plants and their biomass catchments) for an entire region. RELCA a ‘REgional Life Cycle inventory Assessment’ approach was used to model the GHG mitigation potential of 425 biogas plants in the region of Central Germany (CG), aggregated to nine biogas clusters, based on feedstock mix (e.g. animal manures and energy crops) and installed capacity. GHG emission profiles were generated to compare and to identify the role of GHG credits and size of installed capacity on the mitigation performance of the regional biogas clusters. We found that smaller scaled slurry dominant clusters had significantly better GHG mitigation performance (?0.1 to ?0.2 kg CO_2eq kWh_el^?1), than larger energy crop dominant (EC_dom) clusters (0.04–0.16 kg CO_2eq kWh_el^?1), due to lower cultivation emissions and larger credits for avoided slurry storage. Thus, for the CG region larger EC_dom clusters should be targeted first, to support GHG mitigation improvements to the overall future electricity supplied by the regional biogas systems. With the addition of GHG credits, the CG region is producing biogas with GHG savings (?0.15 kg CO_2eq kWh_el^?1, interquartile range: 0.095 kg CO_2eq kWh_el^?1). This infers that biogas production, as a waste management strategy for animal manures, could have important ramifications for future policy setting and national inventory accounting.     

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.     

Life Cycle Assessment of End‐of‐Life Management Options for Construction and Demolition Debris

A life cycle assessment (LCA) of various end‐of‐life management options for construction and demolition (C&D) debris was conducted using the U.S. Environmental Protection Agency's Municipal Solid Waste Decision Support Tool. A comparative LCA evaluated seven different management scenarios using the annual production of C&D debris in New Hampshire as the functional unit. Each scenario encompassed C&D debris transport, processing, separation, and recycling, as well as varying end‐of‐life management options for the C&D debris (e.g., combustion to generate electricity versus landfilling for the wood debris stream and recycling versus landfilling for the nonwood debris stream) and different bases for the electricity generation offsets (e.g., the northeastern U.S. power grid versus coal‐fired power generation). A sensitivity analysis was also conducted by varying the energy content of the C&D wood debris and by examining the impact of basing the energy offsets on electricity generated from various fossil fuels. The results include impacts for greenhouse gas (GHG) emissions, criteria air pollutants, ancillary solid waste production, and organic and inorganic constituents in water emissions. Scenarios with nonwood C&D debris recycling coupled with combustion of C&D wood debris to generate electricity had lower impacts than other scenarios. The nonwood C&D debris recycling scenarios where C&D wood debris was landfilled resulted in less overall impact than the scenarios where all C&D debris was landfilled. The lowest impact scenario included nonwood C&D debris recycling with local combustion of the C&D wood debris to generate electricity, providing a net gain in energy production of more than 7 trillion British thermal units (BTU) per year and a 130,000 tons per year reduction in GHG emissions. The sensitivity analysis revealed that for energy consumption, the model is sensitive to the energy content of the C&D wood debris but insensitive to the basis for the energy offset, and the opposite is true for GHG emissions.     

Mass balance and life cycle assessment of biodiesel from microalgae incorporated with nutrient recycling options and technology uncertainties

This article presents mass balances and a detailed life cycle assessment (LCA) for energy and greenhouse gases (GHGs) of a simulated microalgae biodiesel production system. Key parameters of the system include biomass productivity of 16 and 25 g m^?2 day^?1 and lipid content of algae of 40% and 25% for low and normal nitrogen conditions respectively. Based on an oil extraction efficiency from wet biomass of 73.6% and methane yields from anaerobically digested lipid‐extracted biomass of 0.31 to 0.34 l per gram of volatile solids, the mass balance shows that recycling growth media and recovering nutrients from residual biomass through anaerobic digestion can reduce the total demand for nitrogen by 66% and phosphorus by 90%. Freshwater requirements can be reduced by 89% by recirculating growth media, and carbon requirements reduced by 40% by recycling CO₂ from biogas combustion, for normal nitrogen conditions. A variety of technology options for each step of the production process and allocation methods for coproducts used outside the production system are evaluated using LCA. Extensive sensitivity and scenario analysis is also performed to provide better understanding of uncertainty associated with results. The best performing scenario consists of normal nitrogen cultivation conditions, bioflocculation and dissolved air flotation for harvesting, centrifugation for dewatering, wet extraction with hexane, transesterification for biodiesel production, and anaerobic digestion of biomass residual, which generates biogas used in a combined heat and power unit for energy recovery. This combination of technologies and operating conditions results in life cycle energy requirements and GHG emissions of 1.02 MJ and 71 g CO₂‐equivalent per MJ of biodiesel, with cultivation and oil extraction dominating energy use and emissions. Thus, even under optimistic conditions, the near‐term performance of this biofuel pathway does not achieve the significant reductions in life cycle GHG emissions hoped for from second‐generation biofuel feedstocks.     

Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska,USA

Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km² of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km² (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Impact of land‐use change to Jatropha bioenergy plantations on biomass and soil carbon stocks: a field study in Mali

Small‐scale Jatropha cultivation and biodiesel production have the potential of contributing to local development, energy security, and greenhouse gas (GHG) mitigation. In recent years however, the GHG mitigation potential of biofuel crops is heavily disputed due to the occurrence of a carbon debt, caused by CO₂ emissions from biomass and soil after land‐use change (LUC). Most published carbon footprint studies of Jatropha report modeled results based on a very limited database. In particular, little empirical data exist on the effects of Jatropha on biomass and soil C stocks. In this study, we used field data to quantify these C pools in three land uses in Mali, that is, Jatropha plantations, annual cropland, and fallow land, to estimate both the Jatropha C debt and its C sequestration potential. Four‐year‐old Jatropha plantations hold on average 2.3 Mg C ha^?1 in their above‐ and belowground woody biomass, which is considerably lower compared to results from other regions. This can be explained by the adverse growing conditions and poor local management. No significant soil organic carbon (SOC) sequestration could be demonstrated after 4 years of cultivation. While the conversion of cropland to Jatropha does not entail significant C losses, the replacement of fallow land results in an average C debt of 34.7 Mg C ha^?1, mainly caused by biomass removal (73%). Retaining native savannah woodland trees on the field during LUC and improved crop management focusing on SOC conservation can play an important role in reducing Jatropha's C debt. Although planting Jatropha on degraded, carbon‐poor cropland results in a limited C debt, the low biomass production, and seed yield attained on these lands reduce Jatropha's potential to sequester C and replace fossil fuels. Therefore, future research should mainly focus on increasing Jatropha's crop productivity in these degraded lands.     

Could a bioenergy program stimulate electric vehicle market penetration? Potential impacts of biogas to electricity annual rebate program

The biogas‐to‐electricity pathway under the Renewable Fuel Standard (RFS) allows for Renewable Identification Number (RIN) credits to be generated when electricity produced from biogas is used in the transportation sector. Though approved as a general pathway, EPA has proposed multiple credit allocation methods to functionalize this pathway. This study describes and evaluates a potential credit allocation framework where vehicle manufacturers generate electricity RIN (E‐RIN) credits and use these credits to increase the sales of plug‐in electric vehicles (PEVs). Under this framework, manufacturers use part of the credit value to reimburse electricity generators, offsetting potential higher biogas electricity generation cost. The remaining credit value is passed on to consumers as an annual PEV rebate to stimulate PEV sales. An iterative simulation framework is developed to fulfill two tasks: (a) to estimate the annual rebate amounts and their upfront value to consumers based on various factors, such as vehicle mileage, E‐RIN equivalence value, and biogas capacity, and (b) to evaluate potential impacts of the E‐RIN program on electrification of the future light‐duty vehicles (LDVs) and energy use. The annual rebate amount varies by vehicle technology and could be up to $870/year for battery electric vehicles (BEVs) and range between $230 and 825/year for plug‐in hybrid electric vehicles (PHEVs) depending on the electric range. These per vehicle rebates decrease when demand for electricity exceeds biogas electricity availability. The effectiveness of the program as modeled here is subject to different factors, such as the E‐RIN equivalence value, biogas electricity generation cost, biogas electricity generation capacity, and consumers’ valuation of the E‐RIN rebate. Our modeling results indicate that an E‐RIN program has the potential to produce nearly $12 billion in E‐RIN credits annually and to significantly increase PEV annual sales by up to 2.3 million and the PEV population by about 19.7 million in 2030.     

Techno‐economic analysis for incorporating a liquid–liquid extraction system to remove acetic acid into a proposed commercial scale biorefinery

Mitigating the effect of fermentation inhibitors in bioethanol plants can have a great positive impact on the economy of this industry. Liquid–liquid extraction (LLE) using ethyl acetate is able to remove fermentation inhibitors—chiefly, acetic acid—from an aqueous solution used to produce bioethanol. The fermentation broth resulting from LLE has higher performance for ethanol yield and its production rate. Previous techno‐economic analyses focused on second‐generation biofuel production did not address the impact of removing the fermentation inhibitors on the economic performance of the biorefinery. A comprehensive analysis of applying a separation system to mitigate the fermentation inhibition effect and to provide an analysis on the economic impact of removal of acetic acid from corn stover hydrolysate on the overall revenue of the biorefinery is necessary. This study examines the pros and cons associated with implementing LLE column along with the solvent recovery system into a commercial scale bioethanol plant. Using details from the NREL‐developed model of corn stover biorefinery, the capital costs associated with the equipment and the operating cost for the use of solvent were estimated and the results were compared with the profit gain due to higher ethanol production. Results indicate that the additional capital will add 1% to the total capital and manufacturing cost will increase by 5.9%. The benefit arises from the higher ethanol production rate and yield as a consequence of inhibitor extraction and results in a $0.35 per gallon reduction in the minimum ethanol selling price (MESP). © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:971–977, 2016     

Investigating flexible feeding effects on the biogas quality in full‐scale anaerobic digestion by high resolution,photoacoustic‐based NDIR sensing

In future energy systems based on renewable energies, biogas plants can make a significant contribution to stabilizing the electricity grids. However, this requires load‐flexible and demand‐oriented electricity production by means of flexible feed management. However, these flexible feeding strategies using greatly oscillating, temporally varying high mass loads may lead to critical process failures of the anaerobic digestion process. Currently there is no online, high resolution gas quality measurement technique to detect and prevent biological process failures available. In this contribution, we present a miniaturized, low‐cost biogas quality measurement system providing data with high precision and high temporal resolution to overcome this technology gap. To highlight the capabilities of the system we have installed it using a bypass to the main biogas duct after hydrogen sulfide removal at a full‐scale research biogas plant. During a three‐month field trial, the effect of flexible feeding on the biogas quality has been monitored. The results demonstrate long‐term stability of the sensor solution and reveal the effects of changing feeding frequency and composition on gas quantity and quality, which cannot be detected with commercially available state‐of‐the‐art sensing systems.     

Environmental Assessment of Refuse‐Derived Fuel Co‐Combustion in a Coal‐Fired Power Plant

Municipal residual waste (RW) produced in the Venice area undergoes mechanical‐biological treatment (MBT) in the Fusina plant to produce refuse‐derived fuel (RDF) that is then co‐combusted in a nearby coal‐fired power station. Being the first significant project for RDF co‐firing in power plants in Italy, a number of different testing phases were performed starting in 2003, aimed at evaluating differences between so‐called blank operation (i.e., with only coal feeding) and RDF co‐firing at different feeding rates. The analysis of data gathered during the industrial experimentation shows a savings of 0.7 tonnes (t) of coal per each tonne of co‐fired RDF; stack concentrations of some pollutants (hydrochloric acid [HCl], ammonia [NH₃], carbon monoxide [CO], chromium [Cr], and lead [Pb]) appear slightly higher during co‐combustion compared with blank operation, whereas concentrations of dust, sulfur oxides (SOx), and some metals (manganese [Mn], nickel [Ni], vanadium [V]) are lower. To assess the overall environmental performance of this practice, a life cycle assessment (LCA) study was then performed, where different strategies of energy recovery from RW were compared: production of RDF and its co‐combustion in the Fusina power plant, RW combustion without any pretreatment in a mass‐burn waste‐to‐energy (WTE) plant, and production of RDF and its combustion in a dedicated WTE plant. The LCA results show that co‐combustion of RDF performs better than the other strategies for all impact categories evaluated. The only exception is when the WTE plant operates in combined heat and power mode, with very high overall conversion efficiencies.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part I: Analytical Framework and Baseline Results

This first article of a two‐article series describes a framework and life cycle–based model for typical almond orchard production systems for California, where more than 80% of commercial almonds on the world market are produced. The comprehensive, multiyear, life cycle–based model includes orchard establishment and removal; field operations and inputs; emissions from orchard soils; and transport and utilization of co‐products. These processes are analyzed to yield a life cycle inventory of energy use, greenhouse gas (GHG) emissions, criteria air pollutants, and direct water use from field to factory gate. Results show that 1 kilogram (kg) of raw almonds and associated co‐products of hulls, shells, and woody biomass require 35 megajoules (MJ) of energy and result in 1.6 kg carbon dioxide equivalent (CO₂‐eq) of GHG emissions. Nitrogen fertilizer and irrigation water are the dominant causes of both energy use and GHG emissions. Co‐product credits play an important role in estimating the life cycle environmental impacts attributable to almonds alone; using displacement methods results in net energy and emissions of 29 MJ and 0.9 kg CO₂‐eq/kg. The largest sources of credits are from orchard biomass and shells used in electricity generation, which are modeled as displacing average California electricity. Using economic allocation methods produces significantly different results; 1 kg of almonds is responsible for 33 MJ of energy and 1.5 kg CO₂‐eq emissions. Uncertainty analysis of important parameters and assumptions, as well as temporary carbon storage in orchard trees and soils, are explored in the second article of this two‐part article series.     

Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricity produced by individual gas‐ and oil‐fired power plants across the world. The regression model uses power plant characteristics as predictors, including capacity, age, fuel type (fuel oil or natural gas), and technology type (single or combined cycle) of the plant. The predictive power of the model was relatively high (R² = 81% for predictions). Fuel and technology type were identified as the most important predictors. Estimated emission factors ranged from 0.45 to 1.16 kilograms carbon dioxide equivalents per kilowatt‐hour (kg CO₂‐eq/kWh) and were clearly different between natural gas combined cycle (0.45 to 0.57 kg CO₂‐eq/kWh), natural gas single cycle (0.66 to 0.85 kg CO₂‐eq/kWh), oil combined cycle power plants (0.63 to 0.79 kg CO₂‐eq/kWh), and oil single cycle (0.94 to 1.16 kg CO₂‐eq/kWh). Our results thus indicate that emission data averaged by fuel and technology type can be profitably used to estimate the emissions of individual plants.     

Abatement cost of wood‐based energy products at the production level on afforested and reforested lands

We combined economic and life‐cycle analyses in an integrated framework to ascertain greenhouse gas (GHG) intensities, production costs, and abatement costs of GHG emissions for ethanol and electricity derived from three woody feedstocks (logging residues only, pulpwood only, and pulpwood and logging residues combined) across two forest management choices (intensive and nonintensive) and 31 harvest ages (year 10–year 40 in steps of 1 year) on reforested and afforested lands at the production level for slash pine (Pinus elliottii) in the Southern United States. We assumed that wood chips and wood pellets will be used to produce ethanol and generate electricity, respectively. Production costs and GHG intensities of ethanol and electricity were lowest for logging residues at the optimal rotation age for both forest management choices. Opportunity cost related with the change in rotation age was a significant determinant of the variability in the overall production cost. GHG intensity of feedstocks obtained from afforested land was lower than reforested land. Relative savings in GHG emissions were higher for ethanol than electricity. Abatement cost of GHG emissions for ethanol was lower than electricity, especially when feedstocks were obtained from a plantation whose rotation age was close to the optimal rotation age. A carbon tax of at least $25 and $38 Mg^?1 CO₂e will be needed to promote production of ethanol from wood chips and electricity from wood pellets in the US, respectively.     

The potential impact of second‐generation biofuel landscapes on at‐risk species in the US

The recent increase in corn ethanol production has drawn attention to the environmental sustainability of biofuel production. Environmental assessments of second‐generation biofuel crops (SGBC) have focused primarily on greenhouse gas emissions and water quality. However, expanding the production of cellulosic biomass resources, especially those that require dedicated agricultural land, is also likely to have impacts on biodiversity. We developed an optimization framework for projecting the spatial pattern of SGBC expansion in the United States and intersected these predictions with occurrence data for at‐risk species. In particular, we focused on two candidate perennial grass feedstocks, Panicum virgatum (switchgrass), and Miscanthus × giganteus (Miscanthus). Tradeoffs between biodiversity and economic profitability are assessed using county level data sets of SGBC yield, agricultural land availability, land rents, and at‐risk species occurrences. Results show that future SGBC expansion is likely to occur outside of the Corn Belt, where conventional biofuel feedstocks are currently grown. The set of at‐risk species that could potentially be impacted is therefore likely to be different from the at‐risk species prevalent in the agroecological landscapes of the Upper Midwest that are dominated by corn and soy production. The total number and type of potentially impacted taxa is influenced by several factors, including the total demand for cellulosic biomass, the type of agricultural land used for production, and the method for defining at‐risk species. SGBC production is also concentrated in fewer counties when a national species conservation constraint is combined with a biofuel production mandate. This analysis provides a foundation for future research on species conservation in bioenergy production landscapes and highlights the importance of incorporating biodiversity into broader environmental assessments of biofuel sustainability.     

Adapting Stand‐Alone Renewable Energy Technologies for the Circular Economy through Eco‐Design and Recycling

Renewable energy (RE) technologies are looked upon favorably to provide for future energy demands and reduce greenhouse gas (GHG) emissions. However, the installation of these technologies requires large quantities of finite material resources. We apply life cycle assessment to 100 years of electricity generation from three stand‐alone RE technologies—solar photovoltaics, run‐of‐river hydro, and wind—to evaluate environmental burden profiles against baseline electricity generation from fossil fuels. We then devised scenarios to incorporate circular economy (CE) improvements targeting hotspots in systems’ life cycle, specifically (1) improved recycling rates for raw materials and (ii) the application of eco‐design. Hydro presented the lowest environmental burdens per kilowatt‐hour of electricity generation compared with other RE technologies, owing to its higher efficiency and longer life spans for main components. Distinct results were observed in the environmental performance of each system based on the consideration of improved recycling rates and eco‐design. CE measures produced similar modest savings in already low GHG emissions burdens for each technology, while eco‐design specifically had the potential to provide significant savings in abiotic resource depletion. Further research to explore the full potential of CE measures for RE technologies will curtail the resource intensity of RE technologies required to mitigate climate change.     

Implications of emissions timing on the cost‐effectiveness of greenhouse gas mitigation strategies: application to forest bioenergy systems

Conventional cost‐effectiveness calculations ignore the implications of greenhouse gas (GHG) emissions timing and thus may not properly inform decision‐makers in the efficient allocation of resources to mitigate climate change. To begin to address this disconnect with climate change science, we modify the conventional cost‐effectiveness approach to account for emissions timing. GHG emissions flows occurring over time are translated into an ‘Equivalent Present Emission’ based on radiative forcing, enabling a comparison of system costs and emissions on a consistent present time basis. We apply this ‘Present Cost‐Effectiveness’ method to case studies of biomass‐based electricity generation (biomass co‐firing with coal, biomass cogeneration) to evaluate implications of forest carbon trade‐offs on the cost‐effectiveness of emission reductions. Bioenergy production from forest biomass can reduce forest carbon stocks, an immediate emissions source that contributes to atmospheric greenhouse gases. Forest carbon impacts thereby lessen emission reductions in the near‐term relative to the assumption of biomass ‘carbon neutrality’, resulting in higher costs of emission reductions when emissions timing is considered. In contrast, conventional cost‐effectiveness approaches implicitly evaluate strategies over an infinite analytical time horizon, underestimating nearer term emissions reduction costs and failing to identify pathways that can most efficiently contribute to climate change mitigation objectives over shorter time spans (e.g. up to 100 years). While providing only a simple representation of the climate change implications of emissions timing, the Present Cost‐Effectiveness method provides a straightforward approach to assessing the cost‐effectiveness of emission reductions associated with any climate change mitigation strategy where future GHG reductions require significant initial capital investment or increase near‐term emissions. Timing is a critical factor in determining the attractiveness of any investment; accounting for emissions timing can better inform decisions related to the merit of alternative resource uses to meet near‐, mid‐, and long‐term climate change mitigation objectives.