Solving the multifunctionality dilemma in biorefineries with a novel hybrid mass–energy allocation method

Processing biomass into multifunctional products can contribute to food, feed, and energy security while also mitigating climate change. However, biorefinery products nevertheless impact the environment, and this influence needs to be properly assessed to minimize the burden. Life cycle assessment (LCA) is often used to calculate environmental footprints of products, but distributing the burdens among the different biorefinery products is a challenge. A particular complexity arises when the outputs are a combination of energy carrying no mass, and mass carrying no energy, where neither an allocation based on mass nor on energy would be appropriate. A novel hybrid mass–energy (HMEN) allocation scheme for dealing with multifunctionality problems in biorefineries was developed and applied to five biorefinery concepts. The results were compared to results of other allocation methods in LCA. The reductions in energy use and GHG emissions from using the biorefinery's biofuels were also quantified. HMEN fairly distributed impacts among biorefinery products and did not change the order of the products in terms of the level of the pollution caused. The allocation factors for HMEN fell between mass and economic allocation factors and were comparable to energy allocation factors. Where the mass or the energy allocation failed to attribute burdens, HMEN addressed this shortcoming by assigning impacts to nonmass or to nonenergy products. Under the partitioning methods and regardless of the feedstock used, bioethanol reduced GHG by 72–98% relative to gasoline. The GHG savings were 196% under the substitution method, but no GHG savings occurred for sugar beet bioethanol under the surplus method. Bioethanol from cellulosic crops had lower energy use and GHG emissions than from sugar beet, regardless of the allocation method used. HMEN solves multifunctional problems in biorefineries and can be applied to other complex refinery systems. LCA practitioners are encouraged to further test this method in other case studies.     

Comparative life cycle assessment of centralized and distributed biomass processing systems combined with mixed feedstock landscapes

Lignocellulosic biofuels can help fulfill escalating demands for liquid fuels and mitigate the environmental impacts of petroleum‐derived fuels. Two key factors in the successful large‐scale production of lignocellulosic biofuels are pretreatment (in biological conversion processes) and a consistent supply of feedstock. Cellulosic biomass tends to be bulky and difficult to handle, thereby exacerbating feedstock supply challenges. Currently, large biorefineries face many logistical problems because they are fully integrated, centralized facilities in which all units of the conversion process are present in a single location. The drawbacks of fully integrated biorefineries can potentially be dealt by a network of distributed processing facilities called ‘Regional Biomass Processing Depots’ (RBPDs) which procure, preprocess/pretreat, densify and deliver feedstock to the biorefinery and return by‐products such as animal feed to end users. The primary objective of this study is to perform a comparative life cycle assessment (LCA) of distributed and centralized biomass processing systems. Additionally, we assess the effect that apportioning land area to different feedstocks within a landscape has on the energy yields and environmental impacts of the overall systems. To accomplish these objectives, we conducted comparative LCAs of distributed and centralized processing systems combined with farm‐scale landscapes of varying acreages allocated to a ‘corn‐system’ consisting of corn grain, stover and rye (grown as a winter double crop) and two perennial grasses, switchgrass and miscanthus. The distributed processing system yields practically the same total energy and generates 3.7% lower greenhouse gas emissions than the centralized system. Sensitivity analyses identified perennial grass yields, biomass densification and its corresponding energy requirements, transport energy requirements and carbon sequestration credits for conversion from annual to perennial crops as key parameters that significantly affect the overall results.     

Consequential LCA and LCC using linear programming: an illustrative example of biorefineries

Purpose

This paper aims to demonstrate how LCA can be improved by the use of linear programming (LP) (i) to determine the optimal choice between new technologies, (ii) to identify the optimal region for supplying the feedstock, and (iii) to deal with multifunctional processes without specifying a certain main product. Furthermore, the contribution of LP in the context of consequential LCA and LCC is illustrated.

Methods

We create a mixed integer linear program (MILP) for the environmental and economic assessment of new technologies. The model is applied in order to analyze two residual beech wood-based biorefinery concepts in Germany. In terms of the optimal consequences for the system under study, the principle of the program is to find a scaling vector that minimizes the life cycle impact indicator results of the system. We further transform the original linear program to extend the assessment by life cycle costing (LCC). Thereby, two multi-objective programming methods are used, weighted goal programming and epsilon constraint method.

Results and discussion

The consequential case studies demonstrate the possibility to determine optimal locations of newly developed technologies. A high number of potential system modifications can be studied simultaneously without matrix inversion. The criteria for optimal choices are represented by the objective functions and the additional constraints such as the available feedstock in a region. By combining LCA and LCC targets within a multi-objective programming approach, it is possible to address environmental and economic trade-offs in consequential decision-making.

Conclusions

This article shows that linear programming can be used to extend standard LCA in the field of technological choices. Additional consequential research questions can be addressed such as the determination of the optimal number of new production plants and the optimal regions for supplying the resources. The modifications of the program by additional profit requirements (LCC) into a goal program and Pareto optimization problem have been identified as promising steps toward a comprehensive multi-objective LCSA.

     

Financial Risk Assessment and Optimal Planning of Biofuels Supply Chains under Uncertainty

Biofuels provide an attractive alternative for satisfying energy demands in a more sustainable way than fossil fuels. To establish a biorefinery, an optimal plan must be implemented for the entire associated supply chain, covering such aspects as selection of feedstocks, location, and capacity of biorefineries, selection of processing technologies, production amounts and transportation flows. In this context, there are several parameters, including the availability of biomass, product demand, and product prices, which are difficult to predict because they might change drastically over the different seasons of the year as well as across years. To address this challenge, this work presents a mathematical programming model for the optimal planning of a distributed system of biorefineries that considers explicitly the uncertainty associated with the supply chain operation as well as the associated risk. The potential of the proposed approach is demonstrated through its application to the production of biofuels in Mexico, considering multiple raw materials and products.     

Integrated lignocellulosic value chains in a growing bioeconomy: Status quo and perspectives

Lignocellulose is the most abundant biomass on Earth, with an estimated 181.5 billion tonnes produced annually. Of the 8.2 billion tonnes that are currently used, about 7 billion tonnes are produced from dedicated agricultural, grass and forest land and another 1.2 billion tonnes stem from agricultural residues. Economic and environmentally efficient pathways for production and utilization of lignocellulose for chemical products and energy are needed to expand the bioeconomy. This opinion paper arose from the research network “Lignocellulose as new resource platform for novel materials and products” funded by the German federal state of Baden‐Württemberg and summarizes original research presented in this special issue. It first discusses how the supply of lignocellulosic biomass can be organized sustainably and suggests that perennial biomass crops (PBC) are likely to play an important role in future regional biomass supply to European lignocellulosic biorefineries. Dedicated PBC production has the advantage of delivering biomass with reliable quantity and quality. The tailoring of PBC quality through crop breeding and management can support the integration of lignocellulosic value chains. Two biorefinery concepts using lignocellulosic biomass are then compared and discussed: the syngas biorefinery and the lignocellulosic biorefinery. Syngas biorefineries are less sensitive to biomass qualities and are technically relatively advanced, but require high investments and large‐scale facilities to be economically feasible. Lignocellulosic biorefineries require multiple processing steps to separate the recalcitrant lignin from cellulose and hemicellulose and convert the intermediates into valuable products. The refining processes for high‐quality lignin and hemicellulose fractions still need to be further developed. A concept of a modular lignocellulosic biorefinery is presented that could be flexibly adapted for a range of feedstock and products by combining appropriate technologies either at the same location or in a decentralized form.     

Comparative LCA studies of simulated HMF biorefineries from maize and miscanthus as an example of first- and second-generation biomass as a tool for process development

5-Hydroxymethylfurfural (HMF) is a versatile platform chemical for a fossil free, bio-based chemical industry. HMF can be produced by using fructose as a feedstock. Using edible, first-generation biomass to produce chemicals has been questioned in terms of potential competition with food supply. Second-generation biomass like miscanthus could be an alternative. However, there is a lack of information if second-generation lignocellulosic biomass is a more sustainable feedstock to produce HMF. Therefore, a life cycle assessment was performed in this study to determine the environmental impacts of HMF production from miscanthus and to compare it with HMF from high-fructose corn syrup (HFCS). HFCS from either Hungary or Baden-Württemberg (Germany) was considered. Compared to the HFCS biorefineries the miscanthus concept is producing less emissions in all impact categories studied, except land occupation. Overall, the production and usage of second-generation biomass could be especially beneficial in areas where the use of N fertilizers is restricted. Besides, conclusions for the further development of the on-farm biorefinery concept were elaborated. For this purpose, process simulations from a previous study were used. Results of the previous study in terms of TEA and the current LCA study in terms of environmental sustainability indicate that the lignin depolymerization unit in the miscanthus biorefinery has to be improved. The scenario without lignin depolymerization performs better in all impact categories. The authors recommend to not further convert the lignin to products like phenol and other aromatic compounds. The results of the contribution analyses show that the major impact in the HMF production is caused by the auxiliary materials in the separation units and the required heat. Further technical development should focus on efficient heat as well as solvent use and solvent recovery. At this point further optimizations will lead to reduced emissions and costs at the same time.     

Environmental hotspots of lactic acid production systems

Using selected bio‐based feedstocks as alternative to fossil resources for producing biochemicals and derived materials is increasingly considered an important goal of a viable bioeconomy worldwide. However, to ensure that using bio‐based feedstocks is aligned with the global sustainability agenda, impacts along the entire life cycle of biochemical production systems need to be evaluated. This will help to identify those processes and technologies, which should be targeted for optimizing overall environmental sustainability performance. To address this need, we quantify environmental impacts of biochemical production using distinct bio‐based feedstocks, and discuss the potential for reducing impact hotspots via process optimization. Lactic acid (LA) was used as an example biochemical derived from corn, corn stover, and macroalgae (Laminaria sp.) as feedstocks of different technological maturity. We used environmental life cycle assessment (LCA), a standardized methodology, considering the full life cycle of the analyzed biochemical production systems and a broad range of environmental impact indicators. Across production systems, feedstock production and biorefinery processes dominate life cycle impact profiles, with choice in energy mix and biomass processing as main influencing aspects. Results show that uncertainty decreases with increasing technological maturity. When using Laminaria sp. (least mature among selected feedstocks), impacts are mainly driven by energy utilities (up to 86%) due to biomass drying. This suggests to focus on optimizing or avoiding this process for significantly increasing environmental sustainability of Laminaria sp.‐based LA production. Our results demonstrate that applying LCA is useful for identifying environmental impact hotspots at an earlier stage of technological development across biochemical production systems. With that, our approach contributes to improving the environmental sustainability of future biochemical production as part of moving toward a viable bioeconomy worldwide.     

Pretreatments for Enhanced Enzymatic Hydrolysis of Pinewood: a Review

Pinewood is an abundant source of lignocellulosic biomass that has potential to be used as renewable feedstock in biorefineries for conversion into advanced biofuels and other value-added chemicals. However, its structural recalcitrance, due to the compact packing of its major components, viz. cellulose, hemicellulose and lignin, high lignin content, and high cellulose crystallinity, is a major bottleneck in its widespread use as a biorefinery feedstock. Typical chemical, thermal, and biological pretreatment technologies are aimed at removing lignin and hemicellulose fractions for improving enzyme accessibility and digestibility of cellulose. This review highlights common pine pretreatment procedures, associated key parameters and resulting enzymatic hydrolysis yields. The challenges and limitations are also discussed as well as potential strategies to overcome them, providing an essential source of information to realize pine as a compelling biorefinery biomass source.     

Optimizing Biomass Feedstock Blends with Respect to Cost,Supply, and Quality for Catalyzed and Uncatalyzed Fast Pyrolysis Applications

Biomass cost, supply, and quality are critical parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon feedstock type, location, quantities available, logistics costs, and the quality specifications required by the biorefinery. Biomass quality depends upon feedstock type, growth conditions, weather, harvesting methods, storage conditions, and any preprocessing methods used to improve quality. Biomass quantity depends on location as well as growth conditions, weather, harvesting methods, and storage conditions. This study examines the interdependencies of these parameters and how they affect the biomass blends required by biomass depots and/or biorefineries to achieve the lowest cost feedstock with sufficient quality at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina to each produce 200,000 t of feedstock per year. These depots supply a centrally located 800,000 t biorefinery that converts the feedstocks to bio-oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots utilize biomass based upon availability, but the feedstock or feedstock blend still met the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues, and forest residuals. As necessary, preprocessing methods such as air classification and acid leaching were used to upgrade biomass quality. For both uncatalyzed and catalyzed fast pyrolysis, all four depots could produce biomass blends that met quality and quantity specifications at a cost lower than using a single feedstock.     

Time Horizon and Dominance in Dynamic Life Cycle Assessment

Temporal aspects have traditionally not been recognized adequately in life cycle assessment (LCA). The dynamic LCA model recently proposed offers a significant step forward in the dynamic assessment of global warming impacts. The results obtained with dynamic LCA are highly sensitive to the choice of a time horizon. Therefore, decision making between alternative systems can be critical because conclusions are dependent on the specific time horizon. In this article, we develop a decision‐making methodology based on the concept of time dominance. We introduce instantaneous and cumulative time dominance criteria to the dynamic LCA context and argue why the dominance of an alternative should also imply preference. Our approach allows for the rejection of certain alternatives without the determination of a specific time horizon. The number of decision‐relevant alternatives can thereby be reduced and the decision problem facilitated. We demonstrate our methodology by means of a case study of end‐of‐life alternatives for a wooden chair derived from the original authors of dynamic LCA and discuss the implications and limitations of the approach. The methodology based on time dominance criteria is supplementary to the dynamic LCA model, but does not substitute it. The overall value of this article stretches beyond LCA onto more general assessments of global warming, for example, in policy where the choice of a time horizon is equally significant.     

Life cycle assessment of castor-based biorefinery: a well to wheel LCA

Purpose

Diminishing fossil resources and environmental concerns associated with their vast utilization have been in focus by energy policy makers and researchers. Among the different scenarios put forth to commercialize biofuels, various biorefinery concepts have aroused global interests because of their ability in converting biomass into a spectrum of marketable products and bioenergies. This study was aimed at developing different novel castor-based biorefinery scenarios for generating biodiesel and other co-products, i.e., ethanol and biogas. In these scenarios, glycerin, heat, and electricity were also considered as byproducts. Developed scenarios were also compared with a fossil reference system delivering the same amount of energy through the combustion of neat diesel.

Materials and methods

Life cycle assessment (LCA) was used to investigate the environmental consequences of castor biodiesel production and consumption with a biorefinery approach. All the input and output flows from the cultivation stage to the combustion in diesel engines as well as changes in soil organic carbon (SOC) were taken into account. Impact 2002+ method was used to quantify the environmental consequences.

Results and discussion

The LCA results demonstrated that in comparison with the fossil reference system, only one scenario (i.e., Sc-3 with co-production of significant amounts of biodiesel and biomethane) had 16% lower GHG emissions without even considering the improving effect of SOC. Moreover, resource damage category of this scenario was 50% lower than that of neat diesel combustion. The results proved that from a life cycle perspective, energy should be given priority in biorefineries because it is essential for a biorefinery to have a positive energy balance in order to be considered as a sustainable source of energy. Despite a positive effect on energy and GHG balances, these biorefineries had negative environmental impacts on the other damage categories like Human Health and Ecosystem Quality.

Conclusions

Although biorefineries offer unique features as promising solutions for mitigating climate change and reducing dependence on fossil fuels, the selection of biomass processing options and management decisions can affect the final results in terms of environmental evaluations and energy balance. Moreover, if biorefineries are focused on transportation fuel production, a great deal of effort should still be made to have better environmental performance in Human Health and Ecosystem Quality damage categories. This study highly recommends that future studies focus towards biomass processing options and process optimization to guarantee the future of the most sustainable biofuels.

     

Ecosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design

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

Biomass market dynamics supporting the large‐scale deployment of high‐octane fuel production in the United States

US Department of Energy research aimed at co‐optimizing fuels and engine performance identified several bioblendstocks that can improve fuel economy including an aromatic‐rich hydrocarbon derived from woody biomass. This work supports an analysis of its large‐scale deployment implying a production target of approximately 15 billion liters of bioblendstock for the supply of 57 billion liters of high‐octane fuel by 2050. It simulates potential transition pathways to lignocellulosic feedstock market structures capable of supplying a mature biorefining industry at this scale. In the present absence of biorefineries, transitions are modeled via nonbiofuel feedstock markets, so‐called companion markets. The resource distribution across several demand industries is simulated to determine biomass availability and price dynamics over time. Results indicate that the wood supply base is mainly influenced by traditional markets including housing and pulp and paper. The selected companion market of wood pellet combustion for heat and electricity generation is found to positively stimulate biomass mobilization, especially in the initial absence of biorefineries. Eventually, biorefineries are found to be able to out‐compete the companion market. As such, they directly benefit from the processing (i.e., pelleting) capacity established to produce commodity‐type intermediates for the companion market. We conclude that the amount of bioblendstock produced is directly related to the size of the companion market (and its pelleting capacity). An initially larger companion market generates up to 20 million dry tonnes of additional feedstock, equivalent to 27 commercial‐scale biorefineries, or an additional production of 5 billion liters by 2050. Distinguishing between industry‐specific feedstock preferences based on average biomass quality characteristics, this analysis goes beyond past research efforts that assume automatic fungibility across different feedstocks. Improving engine performance is a key driver for the promotion of low‐carbon fuels derived from bioblendstocks. This analysis portrays feedstock market transition pathways for their large‐scale deployment.     

Life‐cycle assessment of local feedstock supply scenarios to compare candidate biomass sources

The use of life cycle assessment (LCA) as a comprehensive tool to assess environmental impacts of bioenergies is recommended. Nevertheless, several methodological points remain under debate, particularly regarding the feedstock production step, which is a key stage of bioenergy chains. The present work focuses on field emissions during feedstock production, improving assessment methods by the use of process‐based models. To do so, a real bioenergy chain, the local feedstock supply for a boiler located in northern France, was studied. The LCA compares flax shives, (the reference) with four other biomass sources: Miscanthus, cereal straw, linseed straw, and triticale as a whole plant. Six feedstock supply scenarios were also compared. The study aimed to test a new LCA methodology for agricultural chains by integrating local characteristics (such as climate, soil, and crop management data) and using models to estimate field dynamics of pesticide emissions and soil organic carbon (SOC). Results showed that flax shives and linseed straw had the lowest impacts, except for global warming: as a consequence, supply scenarios with the largest share of flax shives had the lowest impacts. For all selected impact categories, transportation and fertilization were the main contributors. SOC dynamics led to high C sequestration level (e.g. with Miscanthus) or to high CO ₂ emissions level (e.g. with flax shives), thus significantly influencing the global warming impact. Sensitivity analysis showed a large influence of allocation method (economic or mass‐based). This study demonstrated the relevance of integrating simulation models using local data in agricultural LCAs, especially for dynamics of SOC and pesticide from fields. Moreover, this work brought scientific elements to support the choice of flax shives as the main biomass feedstock, and the ranking of the other sources as alternative biomass supplies for the boiler.     

Triple bottom line study of a lignocellulosic biofuel industry

Growing concerns about energy security and climate change have prompted interest in Australia and worldwide to look for alternatives of fossil fuels. Among the renewable fuel sources, biofuels are one such alternative that have received unprecedented attention in the past decade. Cellulosic biofuels, derived from agricultural and wood biomass, could potentially increase Australia's oil self‐sufficiency. In this study, we carry out a hybrid life‐cycle assessment (LCA) of a future cellulose‐refining industry located in the Green Triangle region of South Australia. We assess both the upstream and downstream refining stages, and consider as well the life‐cycle effects occurring in conventional industries displaced by the proposed biofuel supply chains. We improve on conventional LCA method by utilising multi‐region input–output (IO) analysis that allows a comprehensive appraisal of the industry's supply chains. Using IO‐based hybrid LCA, we evaluate the social, economic and environmental impacts of lignocellulosic biofuel production. In particular, we evaluate the employment, economic stimulus, energy consumption and greenhouse gas impacts of the biofuel supply chain and also quantify the loss in economic activity and employment in the paper, pulp and paperboard industry resulting from the diversion of forestry biomass to biofuel production. Our results reveal that the loss in economic activity and employment will only account for 10% of the new jobs and additional stimulus generated in the economy. Lignocellulosic biofuel production will create significant new jobs and enhance productivity and economic growth by initiating the growth of new industries in the economy. The energy return on investment for cellulosic biofuel production lies between 2.7 and 5.2, depending on the type of forestry feedstock and the travel distance between the feedstock industry and the cellulose refinery. Furthermore, the biofuel industry will be a net carbon sequester.     

Macroalgae Biorefinery from <Emphasis Type="Italic">Kappaphycus alvarezii:</Emphasis> Conversion Modeling and Performance Prediction for India and Philippines as Examples

Marine macroalgae are potential sustainable feedstock for biorefinery. However, this use of macroalgae is limited today mostly because macroalgae farming takes place in rural areas in medium- and low-income countries, where technologies to convert this biomass to chemicals and biofuels are not available. The goal of this work is to develop models to enable optimization of material and exergy flows in macroalgal biorefineries. We developed models for the currently widely cultivated red macroalgae Kappaphycus alvarezii being biorefined for the production of bioethanol, carrageenan, fertilizer, and biogas. Using flux balance analysis, we developed a computational model that allows the prediction of various fermentation scenarios and the identification of the most efficient conversion of K. alvarezii to bioethanol. Furthermore, we propose the potential implementation of these models in rural farms that currently cultivate Kappaphycus in Philippines and in India.     

Linking a farm model and a location optimization model for evaluating energetic and material straw valorization pathways—A case study in Baden‐Wuerttemberg

Diminishing fossil carbon resources, global warming, and increasing material and energy needs urge for the rapid development of a bioeconomy. Biomass feedstock from agro‐industrial value chains provides opportunities for energy and material production, potentially leading to competition with traditional food and feed production. Simulation and optimization models can support the evaluation of biomass value chains and identify bioeconomy development paths, potentials, opportunities, and risks. This study presents the linkage of a farm model (EFEM) and a techno‐economic location optimization model (BIOLOCATE) for evaluating the straw‐to‐energy and the innovative straw‐to‐chemical value chains in the German federal state of Baden‐Wuerttemberg taking into account the spatially distributed and price‐sensitive nature of straw supply. The general results reveal the basic trade‐off between economies of scale of the energy production plants and the biorefineries on the one hand and the feedstock supply costs on the other hand. The results of the farm model highlight the competition for land between traditional agricultural biomass utilization such as food and feed and innovative biomass‐to‐energy and biomass‐to‐chemical value chains. Additionally, farm‐modeling scenarios illustrate the effect of farm specialization and regional differences on straw supply for biomass value chains as well as the effect of high straw prices on crop choices. The technological modeling results show that straw combustion could cover approximately 2% of Baden‐Wuerttemberg's gross electricity consumption and approximately 35% of the district heating consumption. The lignocellulose biorefinery location and size are affected by the price sensitivity of the straw supply and are only profitable for high output prices of organosolv lignin. The location optimization results illustrate that economic and political framework conditions affect the regional distribution of biomass straw conversion plants, thus favoring decentralized value chain structures in contrast to technological economies of scale.     

Life cycle assessment of forest biomass energy feedstock in the Northeast United States

Life cycle assessment (LCA) was combined with primary data from nine forest harvesting operations in New York, Maine, Massachusetts, and Vermont, from 2013 to 2019 where forest biomass (FB) for bioenergy was one of several products. The objective was to conduct a data‐driven study of greenhouse gas emissions associated with FB feedstock harvesting operations in the Northeast United States. Deterministic and stochastic LCA models were built to simulate the current FB bioenergy feedstock supply chain in the Northeast US with a cradle‐to‐gate scope (forest harvest through roadside loading) and a functional unit of 1.0 Mg of green FB feedstock at a 50% moisture content. Baseline LCA, sensitivity analysis, and uncertainty analyses were conducted for three different FB feedstock types—dirty chips, clean chips, and grindings—enabling an empirically driven investigation of differences between feedstock types, individual harvesting process contributions, and literature comparisons. The baseline LCA average impacts were lower for grindings (4.57 kg CO_2eq/Mg) and dirty chips (7.16 kg CO_2eq/Mg) than for clean chips (23.99 kg CO_2eq/Mg) under economic allocation, but impacts were of similar magnitude under mass allocation, ranging from 24.42 to 27.89 kg CO_2eq/Mg. Uncertainty analysis showed a wider range of probable results under mass allocation compared to economic allocation. Sensitivity analysis revealed the impact of variations in the production masses and total economic values of primary products of forest harvests on the LCA results due to allocation of supply chain emissions. The high variability in fuel use between logging contractors also had a distinct influence on LCA results. The results of this study can aid decision‐makers in energy policy and guide emissions reductions efforts while informing future LCAs that expand the system boundary to regional FB energy pathways, including electricity generation, transportation fuels, pellets for heat, and combined heat and power.     

The environmental consequences of a change in Australian cotton lint production

Purpose

Changes in the production of Australian cotton lint are expected to have a direct environmental impact, as well as indirect impacts related to co-product substitution and induced changes in crop production. The environmental consequences of a 50% expansion or contraction in production were compared to Australian cotton production’s current environmental footprint. Both were then assessed to investigate whether current impacts are suitable for predicting the environmental impact of a change in demand for cotton lint.

Methods

A consequential life cycle assessment (LCA) model of Australian cotton lint production (cradle-to-gin gate) was developed using plausible scenarios regarding domestic regions and technologies affected by changes in supply, with both expansion (additional cotton) and contraction (less cotton) being modelled. Modelling accounted for direct impacts from cotton production and indirect impacts associated with changes to cotton production, including co-product substitution and changes to related crops at regional and global scales. Impact categories assessed included climate change, fossil energy demand, freshwater consumption, water stress, marine and freshwater eutrophication, land occupation and land-use change.

Results and discussion

For both the expansion and contraction scenarios, the changes to climate change impacts (including iLUC) and water impacts were less than would be assumed from current production as determined using attributional LCA. However, the opposite was true for all other impact categories, indicating trade-offs across the impact categories. Climate change impacts under both scenarios were relatively minor because these were largely offset by iLUC. Similarly, under the contraction scenario, water impacts were dominated by indirect impacts associated with regional crops. A sensitivity analysis showed that the results were sufficiently robust to indicate the quantum of changes that could be expected.

Conclusions

A complex array of changes in technologies, production regions and related crops were required to model the environmental impacts of a gross change in cotton production. Australian cotton lint production provides an example of legislation constraining the direct water impacts of production, leading to a contrast between impacts estimated by attributional and consequential LCA. This model demonstrated that indirect products and processes are important contributors to the environmental impacts of Australian cotton lint.

     

Using Attributional Life Cycle Assessment to Estimate Climate‐Change Mitigation Benefits Misleads Policy Makers

Life cycle assessment (LCA) is generally described as a tool for environmental decision making. Results from attributional LCA (ALCA), the most commonly used LCA method, often are presented in a way that suggests that policy decisions based on these results will yield the quantitative benefits estimated by ALCA. For example, ALCAs of biofuels are routinely used to suggest that the implementation of one alternative (say, a biofuel) will cause an X% change in greenhouse gas emissions, compared with a baseline (typically gasoline). However, because of several simplifications inherent in ALCA, the method, in fact, is not predictive of real‐world impacts on climate change, and hence the usual quantitative interpretation of ALCA results is not valid. A conceptually superior approach, consequential LCA (CLCA), avoids many of the limitations of ALCA, but because it is meant to model actual changes in the real world, CLCA results are scenario dependent and uncertain. These limitations mean that even the best practical CLCAs cannot produce definitive quantitative estimates of actual environmental outcomes. Both forms of LCA, however, can yield valuable insights about potential environmental effects, and CLCA can support robust decision making. By openly recognizing the limitations and understanding the appropriate uses of LCA as discussed here, practitioners and researchers can help policy makers implement policies that are less likely to have perverse effects and more likely to lead to effective environmental policies, including climate mitigation strategies.