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Abstract

Abstract The fossil fuel consumption is still a global concern that has received great deal of attention from Chemical Engineering and Operation Research fields. In this sense, this paper presents a SCND (Supply Chain Network Design) for second-generation biofuel production. For this aim, we proposed a mathematical model that includes, simultaneously, economic and environmental issues. The model feasibility has been tested in Colombia. In this case study, the bioethanol production from Coffee Cut Stem (Coffee-CS) is examined considering the three main echelons of the supply chain. Experimental results showed that Coffee-CS is a profitable and sustainable feedstock for biofuel production.

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... In a study conducted in Colombia by Triana et al. (2011), they found that only 21% of the farms renew crops each year. In the case of coffee pulp, this residue is generated in small quantities posing logistical challenges in SCND (Duarte et al., 2016). In all cases, the raw material availability is a relevant issue to guarantee the supply chain feasibility. ...
... da Freitas (2016) evaluated the technical and economic feasibility of ethanol production from coffee husk. Other studies based on mucilage (Pérez-Sariñana et al., 2014), pulp (Shenoy et al., 2011;Bonilla-Hermosa, 2014;Gurram et al. (2016) and coffee stems (Triana, et al., 2011;Duarte et al., 2016), were developed from an experimental perspective. However, to the best of our knowledge, the study of Duarte et al. (2016) is the only one addressing the BSCND problem using a single coffee residue (stems). ...
... Other studies based on mucilage (Pérez-Sariñana et al., 2014), pulp (Shenoy et al., 2011;Bonilla-Hermosa, 2014;Gurram et al. (2016) and coffee stems (Triana, et al., 2011;Duarte et al., 2016), were developed from an experimental perspective. However, to the best of our knowledge, the study of Duarte et al. (2016) is the only one addressing the BSCND problem using a single coffee residue (stems). In this study, facility location and material flows as well as their impacts on environment were analyzed; however, other supply chain decisions such as gathering centers location, dynamic capacity strategy and multiple material flows decisions were not included. ...
Article
Biofuel production from agricultural waste has been identified as a promising strategy in the field of renewable energy. This topic involves complex mathematical modeling tasks such as feedstock characteristics, biorefinery location, capacity strategy and material flows. This paper proposes a Multiple Objective Mixed Integer Linear Programming model (MOMILP) for the design of a sustainable supply chain using multiple agricultural residues. The proposed comprehensive model is utilized in a case study in Colombia, using coffee crop residues. Computational results show the model’s robustness as a decision-making tool, which allows the projection of a flexible supply chain structure in the long term.
... A literature review presents that few studies have been researched the elements of an integrated biofuel and petroleum derivative supply chain planning and capacity expansion considering environmental constraints. Duarte et al. (2014) develop a design of a supply chain as a facility location model for biofuel plants in Colombia, which is improved by considering environmental constraints in Duarte et al. (2016) . These studies consider the use of coffee residues for the production of ethanol in which decisions to be made are related to a strategic level where fixed plant capacities are selected. ...
Article
The petroleum infrastructure, hydrocarbon costs, and process and distribution networks influence integrated supply chains of mixed biofuels and petroleum derivatives (gasoline and diesel). Furthermore, the seasonality of biomass feedstock poses more complexities when optimizing such a combined bio-fossil-fuel industry. As such, a multi-period mixed-integer linear programming (MILP) planning model proposal addresses this supply chain mixed fuels, whereby strategic and tactical decisions under environmental constraints account for different process design in response to demand fluctuations along the long-term horizon. This work is applied in the bio-fossil-fuel market in Brazil by considering diverse plant configurations and different feedstock with their seasonality. Results yield an optimal facility location and plant configurations optimizing over time the evolution of installed capacities, capacity utilization, carbon credit and emissions profiles. The study involves ethanol streams to be added in the gasoline mix considering exclusive and flex sugarcane and corn-based processing plants.
... The authors focused on strategic planning of biorefineries assuming a steady flow of petroleum fuel with a strict blend recipe to meet domestic and international biofuel demands. However, this work does not consider the environmental impacts of the supply chain but was further updated to a multiobjective optimization problem in [6] where the facility location problem was carried out under environmental considerations. ...
... The model determines number, capacity, and location of storage yards and bio-refineries as strategic decisions while it shows tactical decisions included the amount of biomass shipped, processed and inventoried during a time period. Duarte et al. (2016) proposed a mathematical model including economic and environmental issues. They considered coffee cut stem for producing bioethanol. ...
Article
Full-text available
Nowadays the use of fossil fuels as a non-renewable energy source has become a major challenge because of the pollution and the environmental impact. Substitution of biomass as an energy source and its supply chain design is the main question. Because of difficulties such as supply chain complexity, uncertainty in variables and selecting the site of bio-refineries many studies have been conducted in this regard. Studies in the field of biomass and biofuel production are described and classified. Also the strategic decisions such as choosing the sites, selecting energy conversation technology, ensuring economic, environmental, technical, and social sustainability and tactical decisions including allocating resources to productive plants, selecting transport modes, and types of warehouses are addressed in the reviewed papers. We have reviewed 140 papers in the interval between 1997 and 2016 and classified them based on the objective functions. The articles are classified based on their being single or multi objectivity, linearity or nonlinearity. Finally, a classification based on the regions in which the studies have been done.
... The environmental dimension is measured through Eco-costs method; also, the social impact is quantified through two indicators: the total number of created local jobs and the competition between energy and food. Duarte et al. (2016) proposed an MILP model for designing the sustainable supply chain of biofuel from coffee cut stem. The goal of their proposed model is maximizing a global objective function in terms of economic benefits and positive environmental balance. ...
Article
This paper proposes a multi-objective robust possibilistic programming model for the design of a sustainable switchgrass-based bioethanol supply chain network under the epistemic uncertainty of input data considering conflicting economic, environmental and social objectives. The newest and most effective environmental and social life cycle assessment-based methods are applied to the proposed model to measure the relevant environmental and social impacts. To deal with uncertain parameters effectively, a novel multi-objective robust possibilistic programming approach is developed which is able to maximize the mean value of supply chain performance and control the optimality as well as feasibility robustness. Computational analysis is also provided by using a real case study in Iran to show the performance and validity of the proposed model. The results show that with an increase of 2.43% in the economic objective function, a desirable level of environmental and social protection is achieved. Additionally, the mean value of supply chain performance will enjoy more desirable values if the influence of optimality robustness and feasibility robustness decreases. The results also demonstrate that the proposed robust model outperforms the deterministic model in terms of the average and standard deviation measures.
... Sarkar (2013) proposed a production-inventory model with probabilistic deterioration in two-echelon supply chain management. The ecological and economic performance of biofuel production from coffee cut stems has been examined using an optimization technique, and the results showed that this is a sustainable source of energy and a profitable business (Duarte et al., 2016). A channel coordination supply chain model between a vendor and a buyer with a single setup multiple delivery policy is proposed to reduce the joint total cost among supply chain players (Sarkar, 2016). ...
Article
Global warming due to excessive use of fossil fuels has driven researchers to focus on sustainable energy sources for the future. For clean production systems, biofuel is expanding the domain of renewable and sustainable energy supplies. An efficient and sustainable supply chain plays a pivotal role in ensuring this supply. In this research, crop residuals in different agricultural zones, transportation for shipment of residual biomass as well as biofuel, multiple biorefineries, and multiple market centers are considered. The expense of the resources, the yield of residual biomass in agricultural zones, and the demand of market centers are represented by fuzzy numbers as they are assumed to be uncertain. The carbon emissions cost at all stages of the supply chain was also incorporated into this model. This objective of this study is to develop a supply chain model that minimizes the total cost of a second generation biofuel supply chain and location-allocation for agricultural zones and biorefineries to meet the uncertain demand for market centers. Two numerical examples are analyzed, and the results proves that the cost of biofuel production in biorefineries contributed 52.16%, which is a major proportion of the total cost. In the entire supply chain, the transportation sector is the foremost source of carbon emissions in an environment with 88.50% of the total carbon emissions. The results confirms that the proposed model is viable for designing second generation biofuel supply chains under uncertainty. Significant managerial insights of this research are also described to better express the efficiency of the model.
... Biodiesel supply chains have been studied and developed by many researchers in different aspects of strategic level including facility location [32][33][34][35], capacity determination [36,37] and technology selection [38,39]. ...
Article
Biodiesel has recently attracted much interest as an appropriate alternative for the fossil diesel which is mostly consumed in the transportation sector. Meanwhile, Jatropha Curcas L. has emerged as one of the most promising biofuel feedstocks due largely to its salient features such as compatibility with arid and semi-arid lands. In this regard, this paper unveils a two-stage stochastic programming model for the design of an integrated green biodiesel supply chain network from Jatropha Curcas feedstocks. The concerned biodiesel supply chain design is an environmentally friendly mixed-integer linear programming, multi-period and multi-product model. Furthermore, a flexible stochastic programming approach is developed and applied to the supply chain network model. This proposed approach is indeed an extension of a two-stage scenario-based stochastic programming approach which incorporates min-max relative regret in a soft worst-case framework. Given the natural variability of long-term decision-making, fuel demand and Jatropha Curcas trees yielding are hemmed in by uncertainty in this model. The performance of the proposed framework and biodiesel supply chain network design is corroborated through ten realizations and a myriad of various analyses in a real case study of Iran. The derived results and their analyses acknowledge the efficiency and applicability of the model.
... From the mathematical perspective, operations research (OR) methods have been widely used in strategic, tactical and operational decisions (Shukla and Jharkharia, 2013). Various OR applications can be found in the design and optimization of agroindustrial operations, such as that of sugarcane (Colin, 2009;Higgins, 2006;Jena and Poggi, 2013;Lopez Milan et al., 2006), fresh fruits and vegetables (Soto-Silva et al. 2017;Zhou et al., 2015), animal feed, fish farming, meat and its derivatives (Basso and Varas, 2017;Verderame et al., 2010;Visagie et al., 2004), and agricultural waste (Duarte et al., 2014(Duarte et al., , 2016Lee and Tongarlak, 2017). Due to the complexity of the ASC, different authors emphasize the importance of operations integration in the supply chain network design and management (Ahumada and Villalobos, 2009;Higgins et al., 2010;Borodin et al., 2016;Soto-Silva et al., 2016). ...
Article
The aim in new agricultural investment projects is to achieve a proper balance between customer value creation and investor economic benefits. Several authors have highlighted the importance of integrating agroindustrial supply chain operations, as a way to improve competitiveness. In the specific case of sugarcane, most research only integrates harvest and transport operations, lacking simultaneous analysis of sowing, growing and harvesting. Also, from the perspective of sugarcane supply chain planning, few contributions undertake tactical and strategic decisions. This paper proposes an optimization model for sugarcane supply chain planning, integrating several agricultural decisions from a strategic-tactical planning perspective. The uncertainty effects generated by weather conditions were also considered. As a main contribution, the model establishes a set of agricultural decisions that maximize cane yield, in order to optimize the Net Present Value (NPV) of expected profits. The proposed model is utilized to evaluate the feasibility of a new biofuel production plant in Colombia. Results allowed for the identification of critical variables to control, in order to reduce investment risk.
... They incorporated this social benefit into a multi-objective MILP model so as to maximize the social benefit, net present value, and greenhouse gas emission potential saving of the supply chain. In order to determine the optimal design of a sustainable biofuel supply chain from coffee cut stem, Duarte et al. (2016) proposed an MILP model in which a global objective function in terms of economic benefits and positive environmental balance is maximized. ...
Article
This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total cost of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran.
... Single objective Deterministic Eco þ Env (Accorsi et al., 2016;Almansoori and Betancourt-Torcat, 2016;Clavijo Buritica and Escobar, 2017;Costa et al., 2018;Duarte et al., 2016;Galvez et al., 2015;Izadikhah and Saen, 2016;Mohd Idris et al., 2018;Zhang et al., 2017;Zhou et al., 2017;Zohal and Soleimani, 2016) Eco þ Soc Babazadeh et al. (2017) Eco þ Env Stochastic (Ahn and Han, 2018;Fahimnia et al., 2018;Ghelichi et al., 2018;Quddus et al., 2017;Rezaee et al., 2017;Saif and Elhedhli, 2016;Xu et al., 2017) Multiple objectives Deterministic Eco þ Env Chen et al., 2017a;Chen et al., 2018a;Chen et al., 2017b;Colicchia et al., 2016;Domínguez-García et al., 2017;Fang et al., 2018;Gao and You, 2015;Govindan et al., 2016a;Kuo et al., 2018;Miranda-Ackerman et al., 2017;Murillo-Alvarado et al., 2015;Nodooshan et al., 2018;Palacio et al., 2015;Tang et al., 2016;Urata et al., 2017) Eco þ Env þ Soc (Aalirezaei and Shokouhyar, 2017;Anvari and Turkay, 2017;Arampantzi and Minis, 2017;Awad-Nunez et al., 2015;Ch avez et al., 2018;Govindan et al., 2016b;Jafari et al., 2017;Jiang et al., 2018;Kesharwani et al., 2018;Miret et al., 2016;Mota et al., 2015a;Rabbani et al., 2018;Roni et al., 2017;Varsei and Polyakovskiy, 2017;Zhu and Hu, 2017) Stochastic Eco þ Env (Asadi et al., 2018;Azadeh et al., 2017;Brandenburg, 2015;Ebrahimi, 2018;Fahimnia and Jabbarzadeh, 2016;Fazli-Khalaf et al., 2017;Gargalo et al., 2017;Govindan et al., 2015;Khorasani and Almasifard, 2018;Rahmani Ahranjani et al., 2017;Rajkumar & Satheesh Kumar, 2015;Tosarkani and Amin, 2018;Yılmaz Balaman et al., 2018;Zeballos et al., 2018) Eco þ Soc types of electronic waste. Studies addressing sustainability in this sector often use a closed loop supply chain approach. ...
Article
Increasing pressure from governments and stakeholders has motivated the study of sustainability assessment in the supply chain context at operational, tactical, and strategic levels. Several papers have been published during the last two decades, and the number is still rising. Although several authors present complex models that include environmental and social assessment, the applicability and usefulness of these works is often limited by lack of data availability and lack of consensus in what is to be measured on implementations of sustainable practices and strategies. This paper presents a systematic literature review of works addressing the supply chain network design (SCND) problem, in which at least two of the three dimensions of sustainability are assessed. This paper aims to identify indicators that are used when sustainability is evaluated in real applied cases. A total of 113 papers from 2015 to 2018 were selected, including documents studying forward, reverse, and closed loop supply chains (CLSC). Indicators in the economic, environmental, and social dimensions were classified according to an existing framework in the sustainable supply chain literature. The review finds a highlighted emphasis on environmental considerations; social criteria are still hardly studied. The study country origin analysis also shows an increasing concern for sustainable practices in developing economies, mainly in Asia. Finally, this paper presents a brief description of the areas where research opportunities exist, including sectors, measures, and methodologies to assess sustainability in the SCND problem.
... Carvajal et al. (2019) proposed a sugarcane SC planning model for Columbia integrating strategic (long) and tactical (mid) decisions to maximize cane yield leading to NPV maximization subject to constraints on sowing, growing and harvesting. SCN planning for bioethanol has been developed by Duarte et al. (2016) for Colombian geography considering 2nd generation biomass feed from coffee cut stem. The MILP model addresses economics (profit) and environmental impact taking care of facility locations, unfulfilled penalty cost, CO 2 price sensitivity in a multi period fashion. ...
Article
To deal with the rising demand of fossil fuels and their associated untoward environmental and economic effects, the feasibility of Indian government's green move towards blending of 20% fuel grade ethanol with gasoline has been studied by performing techno-economic-environmental analysis of second generation lignocellulose biomass as feedstock. An optimized supply chain network (SCN) has been designed with four layers of structure starting from raw material suppliers to the retailers through the layers of the manufacturers and the distributors aiming at the net present value (NPV) maximization. The cost calculation includes operating expenditure (OPEX) and capital expenditure (CAPEX) components involving transport, storage, production and import decisions as linear variables and decisions on connections between two nodes between two consecutive layers as binary variables. The distribution layer of the mixed integer linear programming (MILP model has been uniquely designed for the imported ethanol to serve the twin purposes of meeting the unmet demand as well as enhancing the bio-ethanol product quality in term of research octane number. The revenue generation is calculated not only from selling the final product but also from the carbon credits calculated using greenhouse gas emission (GHGe) during project life cycle assessment. Further, sensitivity analysis has been performed to show the effect of various parameters such as modes of transport, transport distance limitation on feedstock and product, number of zones, international fuel price fluctuations, feedstock availability on NPV. With ∼80% increase in demand over the 9-year planning horizon, a dynamically changing supply chain (SC) structure shows a ∼36% increase in the newly added locations. Feed availability, critical for Indian scenario, to the tune of at least 40% of the capacity is needed to meet the projected demands.
... Norbatan, Sweden, has been the center of a study wherein Leduc et al. [10] have tried to design a model to locate a plant that produces methanol from biomass. In a case study carried out in Colombia, Duarte et al. [11] have proposed a supply chain model that produces biofuel from cut-stems of coffee concluding that these cut-stems are not only nature-friendly but are also economical sources for the purpose. ...
Article
Full-text available
Nowadays, oil price fluctuation, fossil fuel depletion, and the potential environmental impact of these energy resources are highly threatening the global economy. Developing renewable resources, hence, is quite unavoidable. Sugarcane, as a source of renewable energy, can be converted to bioethanol. Therefore, this study has proposed a mixed-integer linear programming to design an international network of the sugarcane-to-biofuel supply chain. To deal with uncertainty, the robust optimization approach is employed in order to maximize the profit earned from the bioethanol sales at the foreign/domestic markets, minimize the environmental impacts caused by these supply chain activities, and maximize this network generated employment. The multi-echelon supply chain model involves different production/storage capacities, bio-refineries technologies, and transportation modes. This supply chain configuration has specified the optimal production capacity/technology, the appropriate transportation mode in each route, and the bio-refineries’ development capacities. The biofuel export price and the domestic/foreign markets’ demands are among the SC uncertain parameters addressed through the robust possibilistic programming. Finally, the tri-objective model has been solved using an approach that considers the decision maker’s preferences; the model performance has been verified by a case study performed in Iran. To verify the robust model’s efficiency, the DLP realization model is also formulated. The structure of global sugarcane-to-biofuel supply chain network.
... Nevertheless, these alternatives are incipient and time is required to observe improvements in the environmental issues of the world. Meanwhile, social consequences of the appropriation of new oil sources, natural resources pollution, and unequal economic system are increasing through the years (Allesina et al., 2017;Duarte et al., 2016;Peshev et al., 2018). ...
... These applications consume only a fraction of the resources available [2]. Another portion is burned in cookstoves, in open fields or disposed on land until decomposition, deriving in health and environmental problems [11], still remaining untapped or inefficiently used [2,8,[10][11][12][13][14][15]. ...
Article
Full-text available
The coffee industry constitutes an important part of the global economy. Developing countries produce over 90% of world coffee production, generating incomes for around 25 million smallholder farmers. The scale of this industry poses a challenge with the generation of residues along with the coffee cultivation and processing chain. Coffee stems, obtained after pruning of coffee trees, are one of those abundant and untapped resources in the coffee supply chain. Their high lignocellulosic content, the low calorific value ranging between 17.5 and 18 MJ kg⁻¹ and the low ash content make them a suitable solid fuel for thermochemical conversion, such as gasification. This research evaluates the feasibility of using these residues in small-scale downdraft gasifiers coupled to internal combustion engines for power and low-grade heat generation, using process modelling and the Colombian coffee sector as a case study. The producer gas properties (5.6 MJ Nm⁻³) and the gasifier’s performance characteristics suggest that this gas could be utilized for power generation. A cogeneration system efficiency of 45.6% could be attainable when the system’s low-grade heat is recovered for external applications, like in the coffee drying stage. An analysis of the energy demand and coffee stems availability within the Colombian coffee sector shows that the biomass production level in medium- to large-scale coffee farms is well matched to their energy demands, offering particularly attractive opportunities to deploy this bioenergy system. This work assesses the feasibility of providing coffee stem–sourced low-carbon energy for global coffee production at relevant operating scales in rural areas.
... Case study USA Xie et al. (2014) x x x x x Case study USA Palak et al. (2014) x x Numerical example - Gong and You (2014) x x Numerical example - Grigoroudis et al. (2014) x x x Numerical example - Marufuzzaman et al. (2014a) x x x x Case study USA Natarajan et al. (2014) x x x Case study Finland Osmani and Zhang (2013) x x x Case study USA Akgul et al. (2014) x x Case study UK Giarola et al. (2014) x x x x Case study France, Germany and Hungary Foo et al. (2013) x x Case study Malaysia Ebadian et al. (2013) x x x Case study Canada McLean and Li (2013) x x x x Case study Central Europe Mansoornejad et al. (2013) x x x Case study Canada Cambero et al. (2015) x x x Case study Canada Bairamzadeh et al. (2015) x x x Case study Iran Babazadeh et al. (2015) x x x x x Case study Iran Bai et al. (2015) x x x Case study USA Ren et al. (2015) x x x Numerical example - Murillo-Alvarado et al. (2015) x x x Case study Mexico Ahn et al. (2015) x x x Case study South Korea Sharifzadeh et al. (2015) x x x Case study UK Paulo et al. (2015) x x x Case study Portugal Gonela et al. (2015b) x x x x Case study USA Gonela et al. (2015a) x x x x Case study USA Babazadeh et al. (2016) x x x x x x Case study Iran Paolucci et al. (2016) x x Case study Italy Roni et al. (2016) x x x x x Case study USA Duarte et al. (2016) x x x Case study Colombia Lim and Lam (2016) x x x Case study Malaysia De Meyer et al. (2016) x x x Case study Belgium Miret et al. (2016) x x x x Case study France Ng and Maravelias (2016) x x x Case study USA Poudel et al. (2016) x x x x Case study USA x x x Case study Canada Bai et al. (2016) x x x Case study USA x x x Case study Canada Yue et al. (2016) x x x Case study UK Zhang et al. (2016) x x x Case study USA Mohseni et al. (2016) x x x Case study Iran Hombach et al. (2016) x x x Case study Germany Woo et al. (2016) x x x x Case study South Korea Santibañez-Aguilar et al. (2016) x x x Case study Mexico d'Amore and Bezzo (2016) x x Case study Italy Balaman and Selim (2016) x x x x Case study Turkey Azadeh and Arani (2016) x ...
Article
Optimal network design is a key factor in the enhancement of the economic, environmental, and social performance and efficiency of the biomass supply chain (BSC), and this is why it has become quite popular with the academia and practitioners. The great number of the related papers published in the scientific journals in recent years is the proof of the claim; therefore, to make a framework of the past works and specify the future directions, a comprehensive review of the state-of-the-art papers deems necessary. The objective of this paper is to review the papers regarding the biomass supply chain network design (BSCND) models published in the scientific journals. A total number of 146 papers, published from Jan. 1997 to Jul. 2016 are reviewed, analyzed and classified based on their modeling approaches, decisions, uncertainties, solution methodologies, sustainability, model features, entities, data, and regions of the case studies. To determine the research opportunities and future directions, the gaps existing in the present literature have been clearly explained as well.
... Till now, several works have been reported in the domain of biofuel supply chain network design considering past, present and future (Koberg, 2018). Duarte et al (2016) developed single product bioethanol supply chain network (SCN) with three layered echelon in multi time period for Colombian terrain from 2nd generation biomass feed from coffee cut stem. Calderón et al. (2017) performed a detailed cost analysis while designing a bio-synthetic natural gas supply chain as an alternative to fossil fuels and power cogeneration in United Kingdom with the aim of maximizing net present value (NPV) after meeting greenhouse gas emission (GHGe) targets. ...
Article
To tackle the increasing demand, adverse environmental and financial impact of fossil fuels on Indian economy, Indian government has taken a green move towards blending of 20% bioethanol into gasoline and 20% biodiesel into diesel. A feasibility analysis of this kind of move has been studied by performing techno-economic-environmental analysis of a four-layered SCN using second generation lignocellulose bio mass as feedstock. Using supply chain flow decisions as continuous variables and the existence and connectivity between the nodes among nodes in several echelons as binary variables, overall net present value of the supply chain network is maximized using transport, storage, production and import as operating expenditure and infrastructure as capital expenditure. The overall objective function also considered the revenue generation from selling the final product and also from the carbon credits via greenhouse gas emission savings throughout the project life cycle assessment. External imports are allowed to meet the unmet demand and maintain the product quality in terms of research octane number. With ~80% increase in demand in bioethanol and ~37% increase in biodiesel over the 9-year planning horizon, a dynamically changing SC structure coming as an outcome of the aforementioned mixed integer linear programming framework shows overall ~88% increase in the newly added locations. Further analysis shows that at least 40% of the feed supply should be provided to meet the all-time demand and keep the project alive.
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The growing global population and its effects on world food security, as well as the urgency for climate change mitigation, are issues that foster technological, social, and political innovations to increase the efficiency of use of natural resources, such as biomass among others. While significant research efforts have been devoted to biomass conversion processes, their associated supply chains and their implication for complete process efficiency have only been studied more recently. However, most of the recent investigations into the design and optimization of biomass supply chains have focused on an economic point of view, sidelining other dimensions of sustainability, which represents a serious drawback for this kind of work. This article surveys the recent research on design and management optimization of biorefinery supply chains from a sustainability perspective. 72 published research articles from 2006 to 2015 have been analyzed to highlight the sustainability dimensions considered, as well as the inclusion of uncertainties. A typology of decision-making at three levels of analysis (strategic, tactical and operational), and the specific set of tools used to model and optimize the biorefinery supply chain have also been studied. The conclusion underlines the contributions and shortcomings of current research and suggests possible future directions.
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Investment in biofuels as sustainable alternatives for fossil fuels has gained momentum over the last decade due to the global environmental and health concerns regarding fossil fuel consumption. Hence, effective management of biofuel supply chain (BSC) components, including biomass feedstock production, biomass logistics, biofuel production in biorefineries, and biofuel distribution to consumers, is crucial in transitioning towards a low-carbon and circular economy (CE). The present study aims to render an inclusive knowledge map of the BSC-related scientific production. In this vein, a systematic review, supported by a keywords co-occurrence analysis and qualitative content analysis, was carried out on a total of 1975 peer-reviewed journal articles in the target literature. The analysis revealed four major research hotspots in the BSC literature, including (1) biomass-to-biofuel supply chain design and planning, (2) environmental impacts of biofuel production, (3) biomass to bioenergy, and (4) techno-economic analysis of biofuel production. Besides, the findings showed that the following subject areas of research in the BSC research community have recently attracted more attention: (i) global warming and climate change mitigation, (ii) development of the third-generation biofuels produced from algal biomass, which has recently gained momentum in the CE debate, and (iii) government incentives, pricing, and subsidizing policies. The provided insights shed light on the understanding of researchers, stakeholders, and policy-makers involved in the sustainable energy sector by outlining the main research backgrounds, developments, and tendencies within the BSC arena. Looking at the provided knowledge map, potential research directions in BSCs towards implementing the CE model, including (i) integrative policy convergence at macro, meso, and micro levels, and (ii) industrializing algae-based biofuel production towards the CE transition, were proposed.
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Increasing energy demand and the rising levels of greenhouse gas emissions have increased the necessity of bioenergy and sustainable energy generation. The sustainable bioenergy supply chain is the key to produce sustainable biofuel. This paper points to render an optimization model for planning a versatile and dependable biomass-to-bioenergy sustainable supply chain network in which crop residuals from several agricultural sectors, multi-transportation disruption modes, multi-biorefineries, multi-biogas plants, and multi-market centers are investigated for two bioenergy sources, namely biofuel and biogas. For this reason, supply chain cost optimization, emissions of feedstock transport, processing, and distributing end biofuel to respective markets are utilized. The multi-setup-multi-delivery (MSMD) concept is incorporated and lead time crashing cost is applied to minimize the lead time in this model. The carbon emission costs at all steps and the variable production rate for the production of bioenergy are included within the model. Finally, one small-scale data and another large-scale data of six agricultural areas, four biorefineries, four biogas plants, and six markets are considered to validate the model's usefulness. The model's goal is to show bioenergy's effect to make a sustainable supply chain of biofuel and biogas. The numerical results reveal that the cost of bioenergy production contributed 54.12%, a major extent of the whole cost in biorefinery and biogas plants. The transportation segment is the preeminent initiator of carbon emissions with 83.33% in the entire carbon emission within the whole supply chain. Although, transportation cost contributed 33.09% of the total cost, the multi setup-delivery-multi-delivery policy minimized the whole supply chain cost. The results provide a systematic guideline for developing a sustainable biofuel supply-chain by minimizing cost, various aspects of transportation logistics, and multi-model alternatives under reduced energy effects.
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Environmental concerns such as water pollution and global warming resulted in considerable attention being paid to sustainable bioenergy. Due to the eco-friendly nature of sustainable bioenergy, we investigated an integrated bioenergy supply chain network design. In the proposed network, different energy crops, Azadirachta indica and Eruca sativa are taken into account, which leads to different sources for bioenergy production. Furthermore, to prevent further environmental pollution, the wastewater produced at biorefinery is used to generate bioelectricity. This paper addresses a sustainable-efficient bioenergy supply chain network design under uncertainty. A multi-period, multi-product mathematical model is proposed to minimize inefficiency, environmental impacts, and supply chain costs. Furthermore, to cope with uncertainty, a mixed robust-possibilistic programming approach is applied to the model. Finally, computational results based on Iran's real-world case demonstrate the improved performance of the designed bioenergy network by considering three measures of cost, efficiency, and environmental impacts.
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The use of agricultural residues for bioethanol production greatly depends on availability of raw materials and the proper design of a flexible multi-feedstock facility. Therefore, this article assesses the economic, environmental, and social feasibility of a bioethanol production plant, using multiple coffee crops residues (stems, pulp, and mucilage). A case study was designed for the Colombian context, considering three scenarios for different capacity plant. Results suggest that the production costs of 0.504, 0.508, and 0.515 $USD/l for large, medium and small capacity, respectively, are comparable to the bioethanol market price and are similar to other studies reported in the literature. The CO2 emissions obtained were 1.296 Kg CO2/l, 1.297 Kg CO2/l and 1.3 Kg CO2/l for the large, medium, and small plants respectively. The large plant requires 1,170 million tons per year of fresh water, and generates a gray water footprint of 119 thousand tons per year. However, without recirculation, 2.87 times more water is required. Favorable results were identified in terms of reduction of collateral environmental effects, as well as positive impacts on social aspects. Finally, a sensitivity analysis shows the impacts of key parameters on economic, social, and environmental merits of producing bioethanol from coffee residues.
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In this paper, we present a taxonomic review of the literature devoted to the use of operations research approaches for the design and operation of biomass feedstock supply chains (BFSCs). A total of 185 publications that have appeared from 1989 to 2017 are classified based on (1) the embedded optimisation subproblems; (2) the modelling methodologies used for their formulations; and (3) the methods employed for their solution. Our objective of using this classification scheme is to highlight the presence of some useful substructures in a BFSC problem that can, then, be exploited in developing its solution procedure. We illustrate this idea on some generic BFSC problems and present a Dantzig–Wolfe decomposition-based methodology for developing customised approaches to effectively tackle these difficult and large-sized BFSC problems. Finally, we suggest several promising future research directions.
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Son yıllarda çevre dostu yenilenebilir enerji kaynaklarına ilgi artmaktadır.Ülkemizde Enerji Piyasası Düzenleme Kurumu (EPDK) tarafından, 2013 yılındanitibaren benzine ve motorine yerli katkı olarak, oranları her yıl arttırılmak üzerebiyodizel ve etanol ilave zorunluluğu getirilmiştir. Bu da yenilenebilir enerjikaynakları için etkin ve optimal yeşil tedarik zinciri ağı tasarımı çalışmalarınınyapılmasını gerekli kılmaktadır. Bu bağlamda karar vericiler, ekonomik gelişmesağlayan, çevre hassasiyeti olan ve sosyal refahı sağlayan sürdürülebilir çözümlerüretmek için biyoenerji, rüzgâr, güneş, dalga, gelgit vs. gibi yenilenebilir enerjilereodaklanmışlardır Bu çalışmada biyoyakıtların tedarik zinciri ağ tasarımları ile ilgiliyapılmış geçmiş çalışmalara yer verilmiş ve çalışmalar; amaçları, karar değişkenleri,kısıtları, kullanılan optimizasyon metodu ve sonuçları açısından analiz edilerekdeğerlendirilmiştir. İncelenen çalışmalar, yapay sinir ağlarının özel bir çeşidi olanöz düzenleyici haritalar (Self Organizing Maps-SOM) yöntemi kullanılarakkümelenmiş ve literatürdeki boşluklar tartışılmıştır. Literatürün incelemesi veçalışmaların kümelenmesini içeren bu makale, biyoyakıt tedarik zinciri ağ tasarımıile ilgili çalışma yapacak araştırmacılar için yol gösterici niteliktedir.
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We review the literature on green supply chain network design between 2010 and mid 2017, focusing primarily on models and methodologies that explicitly include carbon emissions and environmental policies. We find that supply chain network design has mostly incorporated four policies: carbon cap, carbon offset, cap-and-trade and carbon tax. All four policies succeed to achieve substantial emission reductions with a slight increase in total cost; mostly by configuring the supply chain to use lower-emitting resources. We investigate the prevalent sources of emissions within the supply chain. As expected, transportation contributes about one third, followed by power-intensive processes such as manufacturing, storage and warehousing. Other sources are raw material extraction and sourcing, facility construction and operation, and disposal. We observe that there is a lack of models that capture the complex nature of emissions. Nonlinear tax rates, multivariate emission functions and uncertainty are only considered in few papers. But most importantly, we find that the effect of emissions on demand is rarely accounted for.
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The limitations on resources of fossil fuels and their destructive effects on the environment have made renewable energy sources more attractive and between these sources, energy from biomass called bioenergy has a special place due to the wide range of resources and other benefits. The purpose of this research is to provide a bi-objective multi-period linear programming model to design the supply chain of bioenergy from various types of biomasses using anaerobic digestion and transesterification processes. Two types of biomasses considered as feedstock are microalgae and Jatropha. The first objective function maximizes the value of the total benefit and the second objective function minimize the amount of water consumption. Selection of raw material resources, locating the production facilities and raw material warehouses, value of optimal material flows, etc. are some of the decisions made by the model. The performance of the proposed model is evaluated and validated through conducting a real case study in Iran.
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Biomass is a valuable renewable source of energy as an alternative to fossil fuels. The main barriers in biomass and biofuel development are feedstock high cost, lack of reliable supply, and uncertainties. A systematic review of comprehensive solution tools to overcome the biomass supply chain (BSC) planning challenges is critical for both academic research and industry. Therefore, the aim of this study is to conduct a systematic review of BSC modeling and optimization and identify future research directions. We reviewed 300 papers that have been published in the past 40 years on this topic to assess the various models of BSCs, their objective functions, solution approaches, and decision levels employed. Results show that researchers are motivated to use mixed integer programming models for BSC problems because of the complexities of nonlinear models, as well as the simplicity of the linear approaches. There is a lack of multi-objective optimization approaches to address the economic, social, and environmental issues simultaneously in BSC. Although factors such as the political regulation, governmental subsidy, impact of biomass and oil price and cost of raw material are uncertain, most studies formally treat only the supply and demand of biomass as uncertain parameters. It is highly recommended that an integrated and holistic model that consider all facilities in the whole BSC be developed and tested with real data. In addition, incorporating strategic, tactical, and operational decision levels in the model is suggested to address the challenges of incorporating day-to-day inventory control and fleet management issues.
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Recently, finding sustainable solutions to deal with the environmental and social problems emerged from combustion of fossil fuel in the transportation sector has attracted many interests. This paper proposes an integrated, multi-period, mixed-integer non-linear programming model to design a biodiesel supply chain network under uncertainty. To deal with uncertainty of parameters of the proposed model a novel formulation of possibilistic programming model based on possibilistic mean and absolute deviation of fuzzy numbers is proposed. The proposed model called the Possibilistic Mean-Absolute Deviation model utilizes not only the advantages of previous possibilistic programming methods such as handling the uncertainty and flexibility in goals and constraints simultaneously, but also balances between mean and risk values of an objective function including uncertain coefficients according to Decision-Maker's (DM) preferences. A real case study is conducted in Iran to evaluate the performance and efficiency of the proposed model. The proposed approach has better performance than pure possibilistic programming model and its results is justified by the robust possibilitic programming approaches.
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This paper aims to develop a scenario-based optimization framework to deals with several issues related to redesign sustainable reverse supply chain; focused particularly in the epistemic uncertainty of supply and demand input parameters and their relationship with supply chain performance, both important for the redesign problem. The two-step optimization framework starts with a Fuzzy Inference System methodology for scenario generation that faces the lack of information, and the necessity of estimate the expected operation cost and environmental impact. Then we use generated scenarios into the epsilon-constraint method which solves a multi-objective model to obtain a relevant set of solutions. After solving the second optimization model, we propose to analyze the robustness of the achieved redesign solutions considering a customer satisfaction approach. The computational experiments show that our proposed framework supports better the inclusion of scenarios for redesigning the plastic recycling supply chain. Furthermore, we study a real-life plastic recycling problem in Cuba which demonstrates that the framework is able to support the redesign decision making with robust solutions sensitive to the changes of the studied uncertain parameters.
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Nowadays, concerns about fossil fuel depletion, ecological crisis, and energy security lead to renewable energy generation. The present study provides a multi-objective, multi-period, multi-product integrated sustainable-resilient mixed-integer linear programming model for the optimal design of second-generation biofuel supply chain networks under uncertainty. A novel hybrid stochastic fuzzy-robust approach was utilized to tackle the uncertainty of parameters, and the weighted sum method was applied to deal with the multi-objective problem. Several resiliency measures are introduced to enhance the resiliency of the network and resist against any disruption. Furthermore, strategies to fulfill social impacts are proposed to promote sustainable development of the considered network. Then, a real case study is implemented to investigate the validation of the proposed model. The results indicated that simultaneously considering three measures, including resilience, social impacts, and cost and setting a trade-off between them by decision-makers can boost biofuel supply chain network design in an optimal manner.
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One of the most critical issues for any production organization to compete in the current competitive business environment is supply chain network design (SCND). Besides, by increasing greenhouse gas emissions, various organizations have imposed many restrictions to prevent the overproduction of these gases in their production planning. This study develops a mathematical model for the location-allocation-inventory problem based on a real case study to design a three-echelon coffee supply chain network. The primary purpose of the problem is to minimize supply chain costs. Minimizing the CO2 emission was also considered to address the increasing eco-friendly challenges. The problem includes various strategic and tactical decisions, such as the number and capacity of manufacturing centers (MCs) and distribution centers (DCs) to be established, how to allocate factories to distribution centers and DCs to customers, material flow throughout the system, and the number of products stored in warehouses. It should be noted the problem's parameters are considered fuzzy to get closer to reality. Finally, by performing several sensitivity analyses, valuable managerial insights were obtained. Applying the developed model to the case study of a coffee company assisted managers in making optimal strategic decisions to establish new MCs and DCs, and reduce CO2 emissions. © 2022 International Society of Management Science and Engineering Management.
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Nowadays, the fossil fuel price fluctuations are high, their doubtless exhaustion is distressing, air pollution is a severe problem, and these issues seriously threaten the global economy. Bioenergy is a significant alternative source, with positive environmental, social, and economic impacts, that can reduce the world’s heavy dependence on fossil fuels. As a result, the importance of the design, implementation, and management of bioenergy supply chains have increased in recent years. This research, hence, is aimed to develop a bioenergy supply chain network design (BSCND) model to study the hybrid second (i.e., Jatropha; agricultural residues; and livestock manure) and third (i.e., microalgae) generations of biomass. Since water and energy are two momentous sources for sustainable development of societies where the increasing demand has become a worldwide concern, the water-energy nexus concept is another subject discussed in this study. And since sustainability is another issue to be dealt with in modern energy supply chains, a multi-objective sustainable mathematical model is developed in this study to present. A three-echelon sustainable hybrid bioenergy supply chain model has been proposed with four objective functions that minimize the total cost, reduce the environmental impacts, maximize the energy production, and minimize the water consumption to produce bioenergy. The GIS-based model, also, has been used to form a suitability map of Jatropha/microalgae cultivation. Results of a case study conducted to show the model performance using the MINMAX goal programming method. It has revealed that producing energy from microalgae/Jatropha is more viable compared to agricultural residues and livestock manure.
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This work proposes a multi-objective robust possibilistic programming (MORPP) model for the design and planning of a multi-period multi-feedstock lignocellulosic biofuel supply chain (LBSC) network under the epistemic uncertainty of the input data. The objective simultaneously considers economic, environmental, and social aspects. The proposed model determines the optimal location, capacity and conversion technology of biorefineries, appropriate transportation modes, material flow and production planning. In order to deal with the inherent uncertainty of input parameters a hybrid robust possibilistic programming (HRPP) approach is applied. A real case study located in Iran is conducted to demonstrate the performance of the model. Based on the DMs' preferences HRPP-I(c) version of the robust model is recognized as the most suitable one. Also, a number of scenarios are defined and some valuable managerial implications are drawn.
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The expansion of land used for crop production causes variable direct and indirect greenhouse gas emissions, and other economic, social and environmental effects. We analyse the use of life cycle analysis (LCA) for estimating the carbon intensity of biofuel production from indirect land-use change (ILUC). Two approaches are critiqued: direct, attributional life cycle analysis and consequential life cycle analysis (CLCA). A proposed hybrid 'combined model' of the two approaches for ILUC analysis relies on first defining the system boundary of the resulting full LCA. Choices are then made as to the modelling methodology (economic equilibrium or cause-effect), data inputs, land area analysis, carbon stock accounting and uncertainty analysis to be included. We conclude that CLCA is applicable for estimating the historic emissions from ILUC, although improvements to the hybrid approach proposed, coupled with regular updating, are required, and uncertainly values must be adequately represented; however, the scope and the depth of the expansion of the system boundaries required for CLCA remain controversial. In addition, robust prediction, monitoring and accounting frameworks for the dynamic and highly uncertain nature of future crop yields and the effectiveness of policies to reduce deforestation and encourage afforestation remain elusive. Finally, establishing compatible and comparable accounting frameworks for ILUC between the USA, the European Union, South East Asia, Africa, Brazil and other major biofuel trading blocs is urgently needed if substantial distortions between these markets, which would reduce its application in policy outcomes, are to be avoided.
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Bio-ethanol, as a clean and renewable fuel, is gaining increasing attention, mostly through its major environmental benefits. It can be produced from different kinds of renewable feedstock such as e.g. sugar cane, corn, wheat, cassava (first generation), cellulose biomass (second generation) and algal biomass (third generation). The conversion pathways for the production of bio-ethanol from disaccharides, from starches, and from lignocellulosic biomass are examined. The common processing routes are described, with their mass and energy balances, and assessed by comparing field data and simulations. Improvements through 5 possible interventions are discussed, being (i) an integrated energy-pinch of condensers and reboilers in the bio-ethanol distillation train; (ii) the use of Very High Gravity (VHG) fermentation; (iii) the current development of hybrid processes using pervaporation membranes; (iv) the substitution of current ethanol dewatering processes to >99.5 wt% pure ethanol by membrane technology; and (v) additional developments to improve the plant operation such as the use of microfiltration of the fermenter broth to protect heat exchangers and distillation columns against fouling, or novel distillation concepts.
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Biofuels production has been promoted in the attempt to address global warming and oil dependence concerns. However, the environmental impact of biofuels is a very complex issue and cannot be represented by GHG (greenhouse gas) emissions only (carbon footprint). In particular, water consumption (water footprint) has been recognized as a key issue in renewable fuels production. This paper proposes a multiobjective Mixed Integer Linear Programming modeling framework to optimize the environmental (i.e., the carbon and water footprints) and economic performances of bioethanol supply chains. Multiechelon, multiperiod, and spatially explicit features are embedded within the formulation to steer decisions and investments through a global approach. The strategic design and planning of corn- and stover-based bioethanol production networks is taken into account. A case study is presented referring to the emerging Italian ethanol production. Results show the effectiveness of mathematical programming-based tools to provide decision makers with a quantitative analysis assessing the economic and environmental performances of different design configurations.
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To reduce the logistical and operating costs for biofuel plants, it is important to make a strategic decision to select the proper site for a new facility. Due to the facility's complexity, the facility-location problem must consider the supply-chain structure, involving the material flow from suppliers to customers. This paper proposes an optimisation framework that combines the process design and configuration of the supply chain using an MILP (mixed-integer linear programming) formulation. The model was applied to locate a second-generation bioethanol plant in Colombia that uses an agricultural residue known as Coffee-CSs (coffee cut stems). The experimental results indicate that placing a processing plant at Ibagué city results in the best profitability. A post-optimisation analysis indicated that even for a long period, the location decision did not change.
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Vehicular networks have attracted a lot of attention recently. One potential application of vehicular networks is to use video cameras embedded in vehicles to support video surveillance, which we call “surveillance on-the-road”. Traditional surveillance systems only rely on fixed stations on the roads to monitor road conditions. With vehicular cameras, deeper and richer road conditions may be tracked. In this paper, we study the related communication issues to support such “on-the-road” surveillance scenarios. We use monitoring and tracking suspicious vehicles (such as stolen cars) on the road through license plate recognition (LPR) as an example (our results should be applicable to other scenarios as well). We show how vehicles can work cooperatively through vehicle-to-vehicle (V2V) communications to achieve this goal. With a tracking and a reporting modules, our solution does not rely on infrastructure networks. The tracking module allows handoff of a tracking job to neighboring vehicles as necessary and report of suspicious vehicles to nearby police cars. The reporting module can help guide message flows to avoid flooding the network. Simulation results verify the message efficiency of our approach. We also show how our framework can be applied to the developing WAVE/DSRC (Wireless Access in Vehicular Environments/Dedicated Short Range Communications) standards.
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Energy demand is increasing by the years. Population's needs and technological investments bring the new approach about generating energy. It is considered that fossil fuels will not be able to respond to all energy requirements after approximately 150 years. Turkey imports nearly all of its petroleum and so this causes major economic problems. Turkey, as a major cereal producer, has a huge potential to grow energy crops and other cellulosic biomaterials and can obtain plant's residues, which are suitable to produce second generation bioethanol (SGB). With domestic production, bioethanol can reduce the dependence of petroleum for Turkey, and greenhouse gas emissions can be decreased. Taking into account Turkey's situation in fuel–oil consumption, costliness of gasoline and environmentally hazardous specification of fossil fuels, bioethanol gains more importance and increases in value. Especially, SGB production is rising. Foodstuffs are valuable, and producing ethanol from directly those materials can cause a crisis in Turkey because lignocellulosic bioethanol is becoming prominent. In this regard, bioethanol production in Turkey becomes a major alternative to petroleum and may be a key to new and clean energy source.
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Corn stover was used for manufacturing 2nd generation bioethanol following a biorefinery scheme based on fractionation by autohydrolysis and further Simultaneous Saccharification and Fermentation (SSF) of pretreated solids. Autohydrolysis was performed under a wide range of severities to identify conditions leading simultaneously to a liquid phase containing hemicellulosic saccharides (accounting for up to 68% of initial xylan) and to a solid phase with high enzymatic susceptibility. SSF experiments were carried out under a variety of experimental conditions to assess the effects of the major operational variables.The glucan conversion into ethanol reached values up to 86%, with a bioethanol concentration of 37.8 g/L. Fed-batch operation in the SSF stage allowed the utilization of higher solid loadings, allowing an increase in the bioethanol concentration up to 51.6 g/L, or to reduce the amount of enzymes needed for reaching a given conversion.
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This work proposes a spatially explicit mixed integer linear programming modelling framework representing the dynamic evolution of a bioethanol supply chain (SC) under increasing biofuel demand and greenhouse gas (GHG) emission savings over time. Key features of the proposed framework comprise: (i) the incorporation of available set-aside rural surfaces for energy crop cultivation; (ii) the acknowledgement ofan economic value to the overall GHG emissions through the introduction of an Emission Trading System. Multiple technological options are assessed to exploit the co-product Distiller's Dried Grains with Solubles either as animal fodder (standard usage) or as fuel for heat and power generation or as raw material for biogas production (and hence heat and power). Bioethanol production in Northern Italy is chosen as a demonstrative case study.
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Process industry supply chains (SCs) involve challenging and complex problems that have been addressed by the process systems engineering community in recent years. Shah in 2005 (Shah N: Process industry supply chains: advances and challenges. Comput Chem Eng 2005, 29:1225-1235. The paper provides a comprehensive review on the process industry supply chains. Discusses major achievements and explores industrial examples. Challenges are identified where the evidence that supply chains of the future will be quite different from the past is recognized) stated in his review that process industry SCs were still striving to improve efficiency and responsiveness and were facing new challenges that needed further research. Optimization was pointed out as a possible path to follow aiming at building tools that can help the involved decision makers. From that time onwards several works have explored this pathway but there is still space for improvement, especially due to the outer shell of new emerging problems. The present paper provides a brief review of the progress that has been made on process industry SCs focusing in recent years (2008 onwards). Conclusions on the work done are strained, while the tendencies and future challenges in the area are identified.
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The purpose of this paper is to develop a model for designing the most sustainable bioethanol supply chain. Taking into consideration of the possibility of multiple-feedstock, multiple transportation modes, multiple alternative technologies, multiple transport patterns and multiple waste disposal manners in bioethanol systems, this study developed a model for designing the most sustainable bioethanol supply chain by minimizing the total ecological footprint under some prerequisite constraints including satisfying the goal of the stakeholders', the limitation of resources and energy, the capacity of warehouses, the market demand and some technological constraints. And an illustrative case of multiple-feedstock bioethanol system has been studied by the proposed method, and a global best solution by which the total ecological footprint is the minimal has been obtained.
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This paper presents a MCO (multi-criteria optimisation) of regional biomass supply chains for the conversion of biomass to energy through the simultaneous maximisation of economic performance and minimisation of the environmental and social FPs (footprints). The energy supply-chain model contains agricultural, pre-processing, processing, and distribution layers. An integrated model, previously developed by the authors, for regional biomass energy network optimisation is used as a basis, and now extended for simultaneous assessment of the supply-chain performance based on LCA (Life cycle assessment). Several total FPs are introduced for “cradle” to “grave” evaluation, which, besides direct, comprises also indirect effects caused by products’ substitutions. In the MCO approach, the annual profit is maximised against each FP generating different sets of Pareto optimal solutions, one for each FP. With this approach the aggregation of different environmental and/or social pressures is thus avoided. The results indicate that total FPs enable the obtaining of more realistic solutions, than in those cases when only direct FPs are considered. More profitable and less environmentally harmful solutions can be gained with significant reduction in total carbon and total energy FPs.
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The purpose of this paper is to improve our understanding of carbon footprint within the context of automobile supply chain management. The case study approach is employed as a research method. Primary data were collected through site visits and extensive interviews with HMC’s corporate and plant management. First, identification and measurement of direct and indirect carbon footprint is critical for mitigating supply chain risks. Second, setting the system boundary of measurement is another important issue to integrate the issue of carbon footprint into supply chain management. Third, developing a map of product carbon footprint facilitates identification and measurement of carbon emissions across the supply chain. Companies today operate in a carbon-constrained world. In particular, the automobile industry is under pressure to take a close look at its product carbon footprint. Managing the downstream consequences of the use of its products and inputs from upstream suppliers is critical for developing carbon risk-mitigated supply chain management. This paper is of benefit to academics and managers by providing a new way to integrate carbon emissions in supply chain management. Since climate change and carbon footprint present challenges to many industries, increasing our understanding of how to integrate carbon footprint in supply chain management is necessary, but has seen little research in the automobile industry.
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The worldwide economic growth of the last century has given rise to a vast consumption of goodswhile globalization has led to large streams of goods all over the world. The production,transportation, storage and consumption of all these goods, however, have created largeenvironmental problems. Today, global warming, created by large scale emissions of greenhousegasses, is a top environmental concern. Governments, action groups and companies are asking formeasures to counter this threat. Operations research has a long tradition in improving operationsand especially in reducing costs. In this paper, we present a review that highlights the contribution ofoperations research to green logistics, which involves the integration of environmental aspects inlogistics. We give a sketch of the present and possible developments, focussing on design, planningand control in a supply chain for transportation, inventory of products and facility decisions. Whiledoing this, we also indicate several areas where environmental aspects could be included in ORmodels for logistics.
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In developing an optimization framework to assist in the design process of biofuel systems, the economic effectiveness of the supply network should not be adopted as the sole criterion to focus on. In fact, there has recently been growing attention in including environmental concerns at the strategic level of supply chain management. In this part 2, the spatially explicit multi-echelon mixed integer linear program (MILP) modeling framework described in part 1(1) of this work has been extended by including environmental issues along with the traditional economic ones within a more comprehensive multi-objective optimization tool. The economics have been assessed by means of supply chain analysis techniques, focusing on biomass cultivation site locations, ethanol production capacity assignment and facilities location,. as well as transport system optimization. The environmental performance of the system has been evaluated in terms of greenhouse gas (GHG) emissions, by adopting a well-to-tank (WTT) approach to consider the supply network operating impact on global warming over the entire life cycle. The strategic design tool as developed has been applied and solved in assessing the emerging corn-based Italian ethanol system. The resulting outcomes demonstrate the valuable support that the model may provide in formulating a well-advised strategic policy to promote the market penetration as well as to reduce the social and environmental impacts of biomass-based fuels.
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Environmental consciousness has become critical in the design and operation of globally integrated supply chain networks. This research examines the carbon footprint across supply chains and thus contributes to the knowledge and practice of green supply chain management. The analytical model uses the long-range Lagrangian and the Eulerian transport methods. Analytical and finite difference methods are used to approximate the three-dimensional infinite footprint model. A simplified numerical example validates and illustrates the proposed approach. The results show that carbon emissions across stages in a supply chain can constitute a significant threat that warrants careful attention in the design phase of supply chains.
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This paper presents a new method for regional energy targeting and supply chain synthesis. The method is based on a novel approach to the optimisation of renewable energy supply. A new algorithm for revealing energy supply chain clusters is introduced, described and illustrated by a case study. It has been developed on two levels. The first is a top-level supply chain network with lowest Carbon Footprint generated. It consists of a number of zone clusters. The definition of zones is provided; it can be e.g. a village or a town. Each zone is considered as a unit. At the second level is a supply chain synthesis carried out by P-graph based optimisation within each cluster. It provides a more detailed analysis. The use of the P-graph framework as a synthesis toolset provides a strong mathematically proven fundament for handling the complexity of the synthesis problem. It contributes to the optimal network design with a high computational efficiency. This approach contributes to the cleaner generation of energy from biomass, approaching CO2 neutrality as much as possible. It is beneficial for extending the use of biomass as a renewable source of energy.
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Global water stress is expected to increase due to population growth, economic development and climate change. Because of this trend, there is an increased interest in the water intensity of industrial activities conducted via the product supply chain or within specified geographical boundaries or regions, both at the enterprise- or regulatory-level. The total water footprint of economic activities should be evaluated in consideration of local water resource consumption, virtual water trade and resource availability. As individual entities seek to protect their respective interests, the challenge is to optimize inter-regional trade of goods with the consideration of the interests of participants in the network. This work presents a fuzzy input–output model for optimizing supply chains under water footprint constraints. Two case studies, involving tile manufacturing and biofuel production, are considered to demonstrate the use of the model.
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Interest in bioenergy in recent years has been stimulated by both energy security and climate change concerns. Fuels derived from agricultural crops offer the promise of reducing energy dependence for countries that have traditionally been dependent on imported energy. Nevertheless, it is evident that the potential for biomass production is heavily dependent on the availability of land and water resources. Furthermore, capacity expansion through land conversion is now known to incur a significant carbon debt that may offset any benefits in greenhouse gas reductions arising from the biofuel life cycle. Because of such constraints, there is increasing use of non-local biomass through regional trading. The main challenge in the analysis of such arrangements is that individual geographic regions have their own respective goals. This work presents a multi-region, fuzzy input–output optimization model that reflects production and consumption of bioenergy under land, water and carbon footprint constraints. To offset any local production deficits or surpluses, the model allows for trade to occur among different regions within a defined system; furthermore, importation of additional biofuel from external sources is also allowed. Two illustrative case studies are given to demonstrate the key features of the model.
Article
Interest in producing ethanol from biomass in an attempt to make transportation ecologically sustainable continues to grow. In recent years, a large number of assessments have been conducted to assess the environmental merit of biofuels. Two detailed reviews present contrasting results: one is generally unfavourable, whilst the other is more favourable towards fuel bio-ethanol. However, most work that has been done so far, to assess the conversion of specific feedstocks to biofuels, specifically bio-ethanol, has not gone beyond energy and carbon assessments. This study draws on 47 published assessments that compare bio-ethanol systems to conventional fuel on a life cycle basis, or using life cycle assessment (LCA). A majority of these assessments focused on net energy and greenhouse gases, and despite differing assumptions and system boundaries, the following general lessons emerge: (i) make ethanol from sugar crops, in tropical countries, but approach expansion of agricultural land usage with extreme caution; (ii) consider hydrolysing and fermenting lignocellulosic residues to ethanol; and (iii) the LCA results on grasses as feedstock are insufficient to draw conclusions. It appears that technology choices in process residue handling and in fuel combustion are key, whilst site-specific environmental management tools should best handle biodiversity issues. Seven of the reviewed studies evaluated a wider range of environmental impacts, including resource depletion, global warming, ozone depletion, acidification, eutrophication, human and ecological health, smog formation, etc., but came up with divergent conclusions, possibly due to different approaches in scoping. These LCAs typically report that bio-ethanol results in reductions in resource use and global warming; however, impacts on acidification, human toxicity and ecological toxicity, occurring mainly during the growing and processing of biomass, were more often unfavourable than favourable. It is in this area that further work is needed.
Article
Recently, an active debate has emerged around greenhouse gas emissions due to indirect land use change (iLUC) of expanding agricultural areas dedicated to biofuel production. In this paper we provide a detailed analysis of the iLUC effect, and further address the issues of deforestation, irrigation water use, and crop price increases due to expanding biofuel acreage. We use GLOBIOM – an economic partial equilibrium model of the global forest, agriculture, and biomass sectors with a bottom-up representation of agricultural and forestry management practices. The results indicate that second generation biofuel production fed by wood from sustainably managed existing forests would lead to a negative iLUC factor, meaning that overall emissions are 27% lower compared to the “No biofuel” scenario by 2030. The iLUC factor of first generation biofuels global expansion is generally positive, requiring some 25 years to be paid back by the GHG savings from the substitution of biofuels for conventional fuels. Second generation biofuels perform better also with respect to the other investigated criteria; on the condition that they are not sourced from dedicated plantations directly competing for agricultural land. If so, then efficient first generation systems are preferable. Since no clear technology champion for all situations exists, we would recommend targeting policy instruments directly at the positive and negative effects of biofuel production rather than at the production itself.
Article
The optimal design of biofuels production systems is a key component in the analysis of the environmental and economic performance of new sustainable transport systems. In this paper a general mixed integer linear programming modelling framework is developed to assess the design and planning of a multi-period and multi-echelon bioethanol upstream supply chain under market uncertainty. The optimisation design process of biofuels production systems aims at selecting the best biomass and technologies options among several alternatives according to economic and environmental (global warming potential) performance. A key feature in the proposed approach is the acknowledgement of an economic value to the overall GHG emissions, which is implemented through an emissions allowances trading scheme. The future Italian biomass-based ethanol production is adopted as a case study. Results show the effectiveness of the model as a decision making-tool to steer long-term decisions and investments.
Article
Climate change mitigation has become a binding driver in biofuels production. First generation bioethanol, initially indicated as the most competitive option, is now incurring in ever increasing discredits forcing the transition towards more sustainable productions (i.e. second and third generation technologies). This paper addresses the strategic design and planning of corn grain- and stover-based bioethanol supply chains through first and second generation technologies. A Mixed Integer Linear Programming framework is proposed to optimise the environmental and financial performances simultaneously. Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach. A demonstrative case study is proposed involving the future Italian biomass-based ethanol production. Results show the effectiveness of the optimisation tool at providing decision makers with a quantitative analysis assessing the economic and environmental performance of different design configuration and their effect in terms of technologies, plant sizes and location, and raw materials.
Article
A modelling approach for strategic design of ethanol production systems combining lifecycle analysis (LCA) and supply chain optimisation (SCO) can significantly contribute to assess their economic and environmental sustainability and to guide decision makers towards a more conscious implementation of ad hoc farming and processing practices. Most models applications so far have been descriptive in nature; the model proposed in this work is "normative" in that it aims to guide actions towards optimal outcomes (e.g. optimising the nitrogen balance through the whole supply chain). The modelling framework was conceived to steer strategic policies through a geographically specific design process considering economic and environmental criteria. Results shows how a crop management strategy devised from a whole systems perspective can significantly contribute to mitigate global warming even in first generation technologies.
Article
The contribution of biofuels to the saving of greenhouse gas (GHG) emissions has recently been questioned because of emissions resulting from land use change (LUC) for the bioenergy feedstock production. We investigate how an expanding biofuel feedstock production impacts on land use dynamics if LUC is included into the biofuel carbon accounting framework as scheduled by the European Commission. We first illustrate the change in carbon balances of different biofuels, using methodology and data from the IPCC Guidelines for National Greenhouse Gas Inventories. It turns out that the conversion of natural land except for grassy savannahs impedes meeting the EU’s 35% minimum emissions reduction target for biofuels. We show that the current accounting method promotes biofuel feedstock production mainly on former cropland, thus increases the competition between food and fuel production on the currently available cropland area. We further discuss whether it is profitable to use degraded land for commercial bioenergy production as requested by the European Commission to avoid undesirable LUC and conclude that the current regulation sets little incentives to use such land. The exclusive consideration of LUC for bioenergy production minimizes direct LUC at the expense of increasing indirect LUC but a convincing approach to implement indirect LUC into the framework does not exist. To overcome this problem, we propose the inclusion of all agricultural activities into a regulatory framework for carbon accounting, thus eliminating the indirect LUC risk
Wellto-Wheel evaluation for production of ethanol from wheat. A Report by the LowCVP Fuels Working Group
  • G Punter
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Punter G, Rickeard D, Lariv e J-F, Edwards R, Mortimer N, Horne R, et al. Wellto-Wheel evaluation for production of ethanol from wheat. A Report by the LowCVP Fuels Working Group, WTW Sub-Group. London-UK: Low Carbon Vehicule Partnership; 2004.
Carbon factor for wood fuels for the supplier obligation
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  • S Henry
Bates J, Henry S. Carbon factor for wood fuels for the supplier obligation. Oxfordshire, United Kingdom: AEA Group; 2009.