Biomass Supply Chain Research Articles

Biomass supply chain resilience: integrating demand and availability predictions into routing decisions using machine learning

ABSTRACT Biomass sources have the potential to mitigate carbon emissions as a renewable source while reducing waste and residues. Seasonality and disruption risks are some of the disadvantages of biomass resources requiring that biomass supply chains be managed such that to withstand disruptions. There has been very limited research on integrating predictions for smart management on supply or demand sides of biomass supply chains. In this study, a number of predictive models are investigated for building energy demand and biomass stock availability subject to forecasts of weather conditions. On that basis, an allocation algorithm is proposed for optimal collection and logistics of biomass from land to depots. Accordingly, Google Maps API will be used to identify the best distribution routes for delivering biomass from depots to end-users. A case study with real (supply and demand) data is considered. The proposed integrated data-driven approach aims at improving the accuracy of biomass supply and demand predictions and coordinating these predictions to enhance the resiliency of bioenergy supply chain routing decisions.

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain.

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

Transgenic ZmMYB167 Miscanthus sinensis with increased lignin to boost bioenergy generation for the bioeconomy

BackgroundPerennial C4 grasses from the genus Miscanthus are widely regarded as leading and promising dedicated bioenergy crops due to their high biomass accumulation on marginal land with low environmental impacts and maintenance requirements over its productive life. There is an urgent socio-political and environmental need to ramp up the production of alternative, affordable and green bioenergy sources and to re-direct the net zero carbon emissions trajectory. Hence, up-scaling of Miscanthus cultivation as a source of biomass for renewable energy could play an important role to strategically address sustainable development goals for a growing bio-based economy. Certain Miscanthus sinensis genotypes are particularly interesting for their biomass productivity across a wide range of locations. As the aromatic biomass component lignin exhibits a higher energy density than cell wall polysaccharides and is generally used as an indicator for heating or calorific value, genetic engineering could be a feasible strategy to develop M. sinensis biomass with increased lignin content and thus improving the energetic value of the biomass.ResultsFor this purpose, transgenic M. sinensis were generated by Agrobacterium-mediated transformation for expression of ZmMYB167, a MYB transcription factor known for regulating lignin biosynthesis in C3 and C4 grasses. Four independent transgenic ZmMYB167 Miscanthus lines were obtained. Agronomic traits such as plant height, tillering and above-ground dry weight biomass of the transgenic plants were not different to that of wild-type control plants. Total lignin content of the transgenic plants was ~ 15–24% higher compared with control plants. However, the structural carbohydrates, glucan and xylan, were decreased by ~ 2–7% and ~ 8–10%, respectively, in the transgenic plants. Moreover, expression of ZmMYB167 in transgenic plants did not alter lignin composition, phenolic compounds or enzymatic saccharification efficiency yields but importantly improved total energy levels in Miscanthus biomass, equivalent to 10% higher energy yield per hectare.ConclusionsThis study highlights ZmMYB167 as a suitable target for genetic lignin bioengineering interventions aimed at advancing and developing lignocellulosic biomass supply chains for sustainable production of renewable bioenergy.

Can Forest Management Practices Counteract Species Loss Arising from Increasing European Demand for Forest Biomass under Climate Mitigation Scenarios?

Forests are home to many species and provide biomass for material and energy. Here, we modeled the potential global species extinction risk from future scenarios of climate mitigation and EU28 forest management. We considered the continuation of current practices, the adoption of closer-to-nature management (low-intensity practices), and set-asides (conversion to unharvested forestland) on portions of EU28 forestland under two climate mitigation pathways as well as the consequences for the wood trade. Expanding set-aside to more than 25% of EU28 currently managed forestland by 2100 increased the global extinction risk compared to the continuation of current practices. This outcome stems from a projected increase in EU forest biomass imports, partially from biodiversity-vulnerable regions to compensate for a decrease in domestic harvest. Conversely, closer-to-nature management on up to 37.5% of EU28 forestland lowered extinction risks. Increasing the internal production and partially sourcing imported biomass from low-intensity managed areas lowered the species extinction footprint even further. However, low-intensity practices could not entirely compensate for the increased extinction risk under a high climate mitigation scenario with greater demand for lignocellulosic crops and energywood. When developing climate mitigation strategies, it is crucial to assess forest biomass supply chains for the early detection of extinction risks in non-EU regions and for developing strategies to prevent increase of global impacts.

A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization

Based on current trends and policies aimed at decarbonizing energy systems, the conversion of biomass to bioenergy has the potential to grow rapidly, but such growth depends on the development of efficient, sustainable, and competitive biomass supply chains. As a result, the biomass supply chain has stimulated the interest of a diverse group of researchers across academia, government, and industry, and there is a need to synthesize and categorize the rapidly expanding literature in this field. We conducted a literature review using advanced bibliometric analysis and visualization of 1711 peer-reviewed articles published from January 1992 to August 2022 with the aim of promoting impactful research in both growing and neglected areas of investigation. The results show that there are potential research gaps and opportunities in six critical areas: globalization of supply chain research; incorporation of uncertainty, stochasticity, and risk into supply chain models; investigation of multi-feedstock supply systems; strengthening supply chain resilience; application of inventory control methods; and broader use of machine learning and artificial intelligence in this field. By providing a holistic examination of how biomass-to-bioenergy supply chain research has grown and evolved over this period, our results and subsequent framework and recommendations can aid researchers in developing future studies and can guide stakeholder strategies to identify, diagnose, and address modern challenges that face the bioenergy industry.

SUPPLY CHAINS FOR VALORIZATION OF OLIVE GROVE RESIDUES AND OLIVE OIL INDUSTRY BY-PRODUCTS: A REVIEW ON RESEARCH AND LITERATURE ON OLIVE BASED BIOECONOMY

The residual biomass produced in the olive sector is the result of the large quantity of olive groves and olive oil manufacturers that generate byproducts with a potentially high energy content. Until now, the disposal and management of pruning residues and olive oil by-products has generally represented disposal problems which lead to environmental problems rather than opportunities for additional revenue. In this context, this study aimed to define a roadmap for studies in Turkey to untap the potential of olive grove residues and olive oil industry by-products and residues, (i.e., olive tree prunings, olive leaves, olive pomace) that could be used to produce high-added value products in an integrated biorefinery or in a bioenergy power plant. This paper presents a review on recent research on the valorization of olive by-products in line with the circular economy principles and the bioeconomy strategy and presents the literature which applies to design and management of olive biomass supply chains. Main objective is to provide a conceptual framework for developing and deploying an effective bioeconomy utilizing olive prunings and olive oil industry byproducts conducting a preliminary review of the olive oil chain residues in Europe and Turkey comparatively, assessment of technical potentials, biomass supply costs and allocation of biomass collection sites and energy production facilities with different supply chain scenarios. Biomass resource assessment, biomass feedstock supply chain design and management, and logistics optimization require multidisciplinary and interdisciplinary approaches. They need to be carried out properly in order to execute efficient projects in energy generation from biomass and/or extracting bio-commodities in biorefineries. Turkish researchers have adequate research on valorization methods for olive based biomass resources, but their studies are limited on general biomass supply chain design and particularly no research has been conducted for olive biomass resources. Taking all the aforementioned into account, the author proposes to conduct further studies on a biomass energy project including design of a supply chain network for energy valorization of olive grove residues and olive oil industry by-products in line with the common practice and being inspired by the leading countries like Spain and Italy, which will both contribute to circular business concept development and renewable energy capacity increase.

Utilisation of Spatial Data in Energy Biomass Supply Chain Research—A Review

The supply logistics of energy biomasses generally involves a complex system of supply chains, which aim to achieve timely and cost-efficient feedstock deliveries to biomass demand points. The performance of supply chains is often examined in case studies where spatial data about biomass sources and transportation networks are deployed in varying resolutions and to different geographical extents. In this paper, we have reviewed 94 publications, in which spatial data were used in case studies that focused on analysing and optimising energy biomass supply chains. The reviewed publications were classified into 16 categories, according to the publication year, study methods and objectives, biomass types, supply system complexity and the spatial features of each study area. This review found that the use of geographical information systems in this context has increased in popularity in recent years, and that and the multiformity of the applied methods, study objectives and data sources have increased simultaneously. Another finding was that most of the studies that we reviewed focused on countries in which spatial biomass and transport network data of high quality were unrestrictedly available. Nevertheless, case studies, including spatial data from multiple countries, were represented marginally in the papers that we reviewed. In this paper we also argue that a standard way of reporting geographical contents in biomass case studies should be developed to improve the comprehension and reproducibility of the publications in this field of research.

An integrated methodology based on machine-learning algorithms for biomass supply chain optimisation

An integrated methodology based on machine-learning algorithms for biomass supply chain optimisation

Optimizing transportation cost for biomass supply chain

Biomass conversion is largely impacted by the cost of transporting biomass materials. As a result, businesses need optimization solutions to optimize their transport operations, allocate resources effectively, and reduce their environmental impact. As part of the process of biomass conversion, this paper discusses the transport and biomass optimization problem in detail. The paper presents optimization of transportation cost of two biomass products, natural gas, and bio fuel during the process of biomass conversion final products depending on the transport routes and other factors.

A sustainable network design of a hybrid biomass supply chain by considering the water–energy–carbon nexus

AbstractNowadays, with population growth, rising global energy demand, increasing water consumption, carbon emissions, and excessive use of fossil fuels, the world faces a major challenge. Biomass is one of the most attractive sources of energy production, with positive effects on the economy, environment, and society, which can decrease the world's reliance on fossil fuels and deal with this universal challenge. Consequently, the biomass supply chain network design has received more attention in recent decades. Since energy and water are two significant sources for society's sustainable development and carbon emissions are essential for environmental health, the study of the water–energy–carbon (WEC) nexus is essential. In this study, a multiobjective multiperiod model for designing a sustainable supply chain network based on hybrid second‐generation (i.e., Jatropha, agricultural waste, and animal waste) and third‐generation (i.e., microalgae) biomasses is presented. The proposed multiobjective model consists of five objective functions that maximize the total energy produced and the number of jobs created and minimize the total water consumed, carbon emitted, and total costs. Case study results demonstrate the performance of the model utilizing the MINMAX goal programming approach. Based on the results, energy production from Jatropha is more appropriate in comparison with energy production from microalgae, agriculture waste, and animal waste. The findings also show that the proposed model in this research considering the WEC nexus performs significantly better than the classical model without considering the WEC nexus.

Financial Model of Levelized Cost of Electricity (LCOE) for Bioenergy Resources in Pakistan

For agriculture-based economies, energy generation through biomass is currently among the few practical means for overcoming energy and environmental crisis. However, economic assessment for bioenergy poses significant challenges to the developing nations due to limited availability of data and existing financial models. This study therefore conducts an economic assessment for Pakistan based on Levelized Cost of Electricity (LCOE) for those bioenergy technologies which are commercially available in developing countries. These technologies vary from thermal processes such as biomass gasification or incineration in turbines to bio-chemical processes such as anaerobic digestion. LCOE modeling was performed through a mathematical set of equations driven by input parameters i.e., Feedstock price, total capital cost, auxiliary cost, operation and maintenance cost, capacity factor, and plant lifecycle. The results obtained from the modeling depicted that LCOE for bioenergy in Pakistan may vary from as low as $0.06/kWh to as high as $0.315/kWh. Combustion techniques like stoker boiler and Circulating Fluidized Bed (CFB) have lower cost and yield better economic value with LCOE ranging from $0.06-0.22/kWh. Further, feedstock cost is the most dominant factor that contributes to approximately 60% of the total LCOE. Hence, to make bioenergy economically viable, a sustainable biomass supply chain is essential. This will not only provide a sound energy alternative for developing countries, but it will also contribute towards social and environmental sustainability.

Can we improve the environmental benefits of biobased PET production through local biomass value chains? – A life cycle assessment perspective

The transition to a bioeconomy is one of the ambitions of the European Union for 2030. Biobased industries play an essential role in this transition. However, there has been an on-going discussion about the actual benefit of using biomass to produce biobased products, specifically the use of agricultural materials (e.g., corn and sugarcane). This paper presents the environmental impact assessment of 30% and 100% biobased polyethylene terephthalate production using European biomass supply chains (e.g., sugar beet, wheat, and miscanthus). An integral assessment between the life cycle assessment methodology and the global sensitivity assessment is presented as an early-stage support tool to propose and select supply chains that improve the environmental performance of biobased polyethylene terephthalate production. From the results, miscanthus is the best option for the production of biobased polyethylene terephthalate: promoting European local supply chains, reducing greenhouse gas emissions (process and land-use change), and generating lower impacts in midpoint categories related to resource depletion, ecosystem quality, and human health. This tool can help improving the environmental performance of processes that could boost the shift to a bioeconomy.

Instant catapult steam explosion: An efficient preprocessing step for the robust and cost-effective chemical pretreatment of lignocellulosic biomass

The biorefinery based on lignocellulosic biomass requires an efficient preprocessing step to address problems regarding with the high cost of biomass transportation and the low cost-effectiveness of subsequent chemical pretreatment . In this study, the instant catapult steam explosion (ICSE) was investigated as an alternative preprocessing method to treat corn stalk feedstocks , and compared with conventional milling preprocessing. Besides reducing the particle size, ICSE can modify the microstructure and improve enzymatic degradability of the corn stalks as well. These preprocessed feedstocks were further pretreated by moderate chemical pretreatment methods, including dilute acid, dilute alkali, acid and alkali, organosolv, and ionic liquid. The ICSE-treated feedstocks showed 3-fold to 7-fold increase in enzymatic saccharification when compared with milled and untreated feedstocks. Meanwhile, its energy consumption only accounted for 5%–20% of the milling process, thereby resulting in an 80%–85% of energy savings. Therefore, the ICSE-based preprocessing can potentially be integrated with the supply chain of lignocellulosic biomass and enhance the economic efficiency of biorefinery. • Instant catapult steam explosion (ICSE) as a preprocess is superior to milling for the downward chemical pretreatment. • ICSE, modifying lignocellulose's structure and composition, prompts the chemical pretreatment and subsequent enzymatic hydrolysis. • The energy consumption of ICSE is significantly lower than the traditional milling process. • ICSE facility can be adopted by the regional biomass preprocessing center to improve the cost-effectiveness of biorefinery.

Analysing the impact of stakeholder relationships in the optimisation of biomass supply chains

Many policies have been rolled out to help biomass supply chains reach their greatest contribution to combat climate issues. However, policies are often undermined by the failure to capture the impact of policy on interactions among players in the supply chain. When players in the supply chain have different perspectives toward a given policy, it impacts the way they interact with one another. This was not considered in the existing literature. A conflict analysis approach is applied to evaluate the impact of the supply chain player's relationship on supply chain decisions. Conflict analysis can be incorporated to mathematically model the behaviours of each supply chain player towards specific proposals or policies. To illustrate the effectiveness of the proposed conflict analysis-embedded model, a case study on a biofuel supply chain based in Malaysia is analysed. In this study, players' reactions in the supply chain toward the three proposed government policies (transport subsidy, workforce reduction and production variation) are systematically modelled and used as an input for the supply chain optimisation. A comparison study is shown to benchmark the results obtained with and without conflict analysis. Based on the optimised results, the conflict analysis model called for a higher amount of empty fruit bunch (i.e., 2.7 times higher between empty fruit brunch sources and first layer storage) than the model without conflict analysis. The total cost associated with the supply chain also increased by 77% after relationships among players were considered (USD 4.5 million to USD 8.0 million). The higher cost and material from the model suggested that conflict reduces the effectiveness of material transfer by reducing the chances of successful trade within the supply chain. By foreseeing and considering the inefficiency of a supply chain in a model, policymakers can, therefore, possible to make more sound decisions. The proposed approach with these findings is crucial in notifying the policymakers of the true potential of their policy toward the supply chain.

Addressing supply uncertainties using multi-period stochastic economic evaluation: A graph-theoretic aided element targeting approach

The challenges to commercialize biomass industry includes biomass supply shortage which is dependent on geographical location and seasonality. Most of the present biomass supply chain studies had not considered incorporation of supply chain uncertainties that may lead to overestimation of financial performance. Therefore, a hybrid framework was proposed via integration of stochastic Monte Carlo Simulation model with element targeting approach (Biomass Element Life Cycle Analysis, BELCA-P-graph model) to perform scheduling and economic analysis for the biomass supply chain. The BELCA-P-graph model aimed to generate a baseline for the feedstock ratio of each input biomass. This was then input into the stochastic model, capable of estimating the financial probability of the supply chain while incorporating supply chain uncertainties (i.e., biomass element characteristics, transportation-related parameters, raw material pricing, biomass availability, market demand, and selling price of final product). Results showed that biomass shortage had decreased the mean Net Present Value (NPV) of the base case scenario (without consideration biomass supply shortage) by 1.39%–12.21%. Storage capacity consideration had decreased the mean NPV by 11.59%–12.21%. The sensitivity analysis found that syngas demand and syngas selling price uncertainty offered significant impact on the mean NPV outcome. • Integrated Monte Carlo model with BELCA-P-graph model was presented. • Six supply chain uncertainties are modelled using Monte Carlo simulation. • Biomass shortage reduced mean NPV of base case up to 12.21%. • Implementation of storage resulted in a further reduction in mean NPV.

Novel Methodology to Assess Advanced Biofuel Production at Regional Level: Case Study for Cereal Straw Supply Chains

Nowadays, there is an urgent necessity for breakthrough technologies able to reduce process complexity and to lower costs to make the biomass-based biodiesel supply chain competitive. This paper presents an innovative methodology for the identification of secondary biomass potentials for biofuel production. The methodology, divided into four steps, defines the criteria that allow identification of promising scenarios of biomass supply chains for commercial application of innovative technologies. The model set up a scoring procedure based on carbon emission avoidance, efficient resource exploitation and sustainability indexes. Applying the four levels of analysis (biomass availability, suitability analysis, regionalization and multi-criteria analysis), the cereal straw supply chains in four European districts (Scandinavian, Hanseatic, Central European and Mediterranean) have been identified and grouped in 18 biomass supply regional clusters (BSRCs). The clusters represent the most promising hotspots where biomass availability, logistics and feedstock requirements for a novel conversion technology meet. Central European and Mediterranean districts are those with the highest cereal straw bioeconomic potentials which allow mono-feedstock supply chains and relatively high capacity of a conversion technology at 200 MWth and beyond. Central Europe has an overall bioeconomic potential of 16.249 kt (232.359 TJ) distributed over 36 regions and organized in 12 BSRCs. The Mediterranean district has an overall bioeconomic potential of 3541 kt (50.630 TJ) distributed over nine regions and organized in four BSRCs.

Sustainability Impact Assessment of Forest Bioenergy Value Chains in Quebec (Canada)—A ToSIA Approach

Forest bioenergy value chains can offer attractive opportunities to promote economic development and mitigate climate change. However, implementing profitable and efficient forest biomass value chains requires overcoming barriers that continue to hinder the development of bioenergy systems in several jurisdictions. The objective of this study was to compare the economic, social, and environmental sustainability of various potential configurations of forest bioenergy value chains, including forest biomass supply and bioenergy production chains, in the Capitale-Nationale region of Quebec (Canada), which is a jurisdiction that has considerable forest resources but makes little use of bioenergy. We based our study on the ToSIA model parameterization and compared various policy measures, biomass supply, and logistics scenarios for 2008 and 2030. Our results showed that wood chip and pellet value chains in the Capitale-Nationale region would positively contribute to the regional economy in 2030, even in the absence of subsidies. Moreover, actions to increase biomass feedstock mobilization in 2030 would lead to an increase in gross value added, employment, and energy production in the region compared with 2008 and a greater increase than other considered policy or logistical measures. However, increased biomass feedstock mobilization would also mean higher relative GHG emissions and more fossil fuel energy input per unit of bioenergy than in the other scenarios. Conversely, optimizing biomass feedstock and combustion technologies could help minimize the fossil fuel energy input needed and GHG and some non-GHG pollutant emissions. Overall, our study suggested that implementing policy and logistical measures for forest biomass value chains could make the significant mobilization of forest bioenergy attainable and, in turn, Quebec’s 2030 bioenergy target of 17 petajoules realistic.

Sustainable operations, managerial decisions, and quantitative analytics of biomass supply chains: A systematic literature review

The global sustainability development mission of achieving carbon neutrality by 2050 is easy to suggest, but incredibly difficult to put into action. Fortunately, continuing reliance on green conversion technologies could effectively address business concerns of energy expenditures, ecological pollution, and fossil fuel depletion. To promote sustainable practices, many researchers and practitioners have put their hopes in the environment-friendly use of biomass. Biomass supply chain management, which contributes to saving the planet, societies, and costs, has a high potential for sustainable development. Besides, successful implementation of regulatory policies that incorporate tax and incentive strategies into decision-making processes has shifted biomass businesses toward greener practices. To this end, quantitative analytics propose primary tools in developing sustainability-driven decisions for biomass supply chains. However, the literature lacks a comprehensive classification of methodologies applied in this field which incorporate the role of policy mechanisms into managerial decisions. The current study conducts a systematic review of 450 peer-reviewed papers, where we apply a rule-governed content analysis approach that includes collecting, filtering, and categorizing the prior research in a reproducible manner. We also classify the collected materials using deductive and inductive approaches to determine various structural dimensions and associated analytic categories. In the context of biomass supply chain management, we provide evidence that energy crops and forest-based biomass are the most addressed biomass feedstock types in the existing literature, while municipal solid waste sources could be explored further in future research. Additionally, from a sustainability development perspective we show that the environmental pillar has attracted much more attention than the social aspect that accounts for job creation, safe workplace, food security, and consumer surplus.

Sustainability assessment of the whole biomass-to-energy chain of a combined heat and power plant based on biomass gasification: biomass supply chain management and life cycle assessment.

Energy generation from waste renewable sources represent an efficient way to provide green power with the highest environmental benefits, tackling problems related to the high costs for their disposal through the conversion of these wastes in biofuels. However, several challenges hinder their intensified use, as the huge variability in the amount and composition of these sources forces authors to enlarge their studies on the entire biomass-to-energy chain sustainability where the power technology can be installed with the highest profits. In present work, the technical, environmental and economic impact of the entire biomass-to-energy supply chain is assessed with reference to a real commercially available Combined Heat and Power (CHP) system, the CMD ECO20X based on biomass gasification, installed as operational demonstration in the Municipality of Laurino in the National Park of Cilento, Vallo di Diano, and Alburni (PNCVD) in Southern part of Italy. Several calculation tools previously developed by authors for the analysis of the performance of the various components of the ECO20X system are here employed to define the mass and energy fluxes that characterize its operations in a local supply chain where forest management residues (oak and beech trees) and olive pomace from oil mills in the area are exploited. The analysis aims to quantify the energy absorption necessary for the pretreatment operations of the organic residue (shredding, briquetting, drying) which are essential for gasification, and how much they affect the production deriving from the biomass cogeneration process itself. Then, measurements in terms of pollutants related to the energy production at the municipality and of the air quality in the area, help in the evaluation of the plant environmental impact from a global perspective, by virtue of data obtained from an LCA analysis conducted considering one year functioning of the CHP plant.

China’s coal power decarbonization via [formula omitted] capture and storage and biomass co-firing: A LCA case study in Inner Mongolia

In this study, a membrane-based CO2 capture and storage (CCS) chain and a co-firing system of coal and biomass were virtually implemented in an existing coal power plant in Inner Mongolia. Three life cycle assessment (LCA) models were developed to evaluate the environmental performance of the power generation system under business-as-usual (BAU) conditions and with the implementation of the selected technologies. The CCS system reduced CO2 emissions from the power plant by about 90%, but significantly increased upstream emissions, limiting the LCA mitigation potential to 37%–48% of the 1.14 kg CO2/kWh estimated for the BAU scenario. Combining biomass co-firing with CCS achieved negative emissions from the power generation stage and reduced the total CO2 emitted under the LCA scope by 57%–67%. However, both technologies had negative impacts on the local environment, which were quantified by a range of indicators such as eutrophication potential (+13%–37%), toxicity for both aquatic (+12%–33%) and terrestrial (+35%–68%) ecosystems, and consumption of freshwater (+46%–61%). The major factors preventing a more significant mitigation of CO2 emissions and shifting the environmental burden to local ecosystems were the increased electricity and coal consumption for implementing CCS and the reliance on diesel and artificial fertilizers in the biomass supply chain.