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An Optimal Planning for the Reuse of Municipal Solid Waste Considering Economic, Environmental and Safety Objectives
Aiche Journal
Abstract
This paper presents a mathematical programming model for the optimal planning of the reuse of municipal solid waste to maximize the economic benefit while simultaneously considering sustainability and safety criteria. The proposed methodology considers several phases of the supply chain including waste separation, distribution to processing facilities, processing to obtain useful products and distribution of products to consumers. Additionally, the safety criteria are based on the potential fatalities associated with waste management. The proposed optimization model is formulated as a multi-objective optimization problem, which considers three different objectives including the maximization of the net annual profit, the maximization of the amount of reused municipal solid waste and the minimization of the social risk associated with the supply chain. The proposed model is applied to a case study in the central-west region of Mexico. The results show the tradeoff between the social risk and the economic and environmental criteria. This article is protected by copyright. All rights reserved.
... It was shown that designing an efficient distribution system to reuse the MSW results in maximizing the net profit of the SC network. Santibañez-Aguilar et al. (2015) extended the model by embedding the safety aspect based on the total societal risk in order to provide sustainable processes. Santibañez-Aguilar et al. (2017) further developed the approach by considering the dynamic behavior of the waste management system and inventory levels in landfills and plants. ...
... Acquiring a better energy efficiency Ng et al., 2014;Pan et al., 2015;Watkins and McKendry, 2015;Marchi and Zanoni, 2017 . Lowering the environmental impacts Arbulú et al., 2013;Santibañez-Aguilar et al., 2015;Asefi and Lim, 2017;Diaz-Barriga-Fernandez et al., 2017 . Improving responsiveness and increasing the service level Andiç et al., 2012;Toso and Alem, 2014;Kadambala et al., 2017 . ...
... Table 2 shows the seasonal production of waste in the five considered cities. It can be observed that cities 1 and 5 produce the highest quantity of MSW during a year mainly due to the higher population density in those cities (the data for the population of each city can be found in Santibañez-Aguilar et al., 2015 ). The proportion of metal waste is 3.5% of the total waste in every city, followed by plastic waste (5.1%) and glass waste (5.8%). ...
Waste management can be considered as a strategic supply chain problem as it involves the waste generation, collection, separation, transportation, treatment, distribution, and disposal. This paper presents a mixed integer linear programming model for the coordination of tactical and operational decisions in waste supply chain networks including the logistics, production, and distribution. The model aims at maximizing the profit of the entire supply chain while satisfying the demand, production, transportation, and inventory constraints imposed by different entities of the network. A case study is selected to test the effectiveness and efficiency of the proposed model. Such an integrated network contributes to the maximum utilization of recyclable waste including paper, plastic, glass, and metal processed by recycling plants, and non-recyclable waste treated in waste to energy plants. Sensitivity analyses are performed to investigate how changing parameters including the time periods and products’ prices affect the supply chain performance.
... Such SC strategy focuses on the integration of internal and external processes of the organization across the chain to better serve the customers while improving the performance of each member of the SC network. 14 Some of the advantages of integrating the SC network into the WM system are the smooth flow of waste among the SC entities, 15 balancing the vehicle loads and minimizing the transportation cost, 16 balancing the inventory levels and reducing the inventory cost, 17 and improving responsiveness and increasing the service level. 18 In addition, it contributes to extracting the maximum value from the generated waste, 19 increasing the use of renewable source of energy, 20 acquiring a better energy efficiency, 21 lowering the environmental impacts, 22 and accelerating the transition toward a circular economy. ...
... However, they concluded that the MSW utilization was not economically profitable mainly due to the high cost of WtE technologies. Santibañez-Aguilar et al. 15 presented a multi-objective model considering several functions of the SC for the optimal planning of the reuse of MSW, maximizing the annual profit, and minimizing the social risk. A case study in the region of Mexico was used to investigate the tradeoff between the social, economic, and environmental criteria. ...
... As the use of fuel gives rise to emissions, emission limits based on the environmental regulations attached to the transport are taken into account. Equation 15 calculates the amount of emission exceeding the emission limit (AE tran st Þ, which incurs a penalty cost paid by the separation center. As it is difficult to predict how much a given load costs in fuel consumed, it is assumed that fuel consumption is only based on the distance traveled and the load does not raise the fuel consumption. ...
The growing waste generation, increasing environmental regulations, and limited land area for waste disposal necessitate an effective and efficient waste supply chain management solution in terms of both socioeconomic perspectives and environmental sustainability. Waste management is connected to supply chain decisions as it involves waste generation, collection, separation, transportation, processing, and disposal. Accordingly, this article develops a mixed integer linear programming model for the optimal planning of a waste management system in a multi‐echelon supply chain network, which aims to find a trade‐off between supply chain costs, depletion of waste, and efficient use of generated waste while considering the environmental impacts. Various recycling and waste‐to‐energy technologies are used to convert plastic and mixed waste into value‐added products including fuel, electricity, and heat. Although recycling is preferable from an environmental point of view, it is shown that the waste‐to‐energy option is more economically efficient. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16464 2019
... [16][17][18][19][20][21][22] Santibañez-Aguilar et al. formulated an MILP approach to designing a municipal waste management system consisting of cities as collection sites, dumps as sorting stages, and landfills and processing facilities as end-of-life disposal processes. 23 By generating different Pareto curves, they were able to observe how the SC configuration changes with trade-offs between economic, societal, and environmental considerations for a case study of the central-west region of Mexico. Saif et al. proposed an MILP model which described a twostep municipal solid waste management SC (collection/separation and end-of-life processing) that considered three objectives: maximization of net present value, minimization of environmental impacts, and maximization of job creation. ...
... It is either assumed that the composition of waste in all collection locations is fixed, 7 that waste is only divided into broader categories (e.g., recyclable, garbage, hazardous), 25,26 or that complete separation of all components is possible in the sorting stage. 23,29 As far as the authors are aware, this article is the first to develop a model to address the specific impact of sorting and composition of MPW on SC design. Tracking MPW composition is a crucial aspect of the MPW management problem, as many emerging technologies in the plastic waste management area can be sensitive to the composition of incoming waste streams. ...
This article introduces three mixed integer programming (MIP) models to address a network design problem for mixed plastic waste (MPW) supply chains. By tracking waste compositions throughout the supply chain, the models optimize the technologies needed to process MPW. The three models adopt different approaches to preserve composition information in the supply chain. We also remark on how to improve solution times with additional constraints, and how the models can be easily modified to handle larger‐scale problems. The proposed models provide an approach for examining emerging MPW recycling technologies that may be more sensitive to input composition, as well as determining the extent to which advanced sorting is useful.
... Municipal solid waste disposal started when cities were created and expanded after industrialization, as large parts of the population migrated from rural to urban areas [2]. The municipal solid waste generation in the world is increasing and reflects consumer habits and lifestyles [3]. The large amount of municipal solid waste being generated exceeds the capacity of the environment to assimilate through natural processes [4]. ...
... Waste generation kept increasing around these villages as a result of population increase with different kinds of lifestyles. The municipal solid waste generation in the world is increasing and reflects consumer habits and lifestyles [3]. ...
Disposal is a critical phase in the management of municipal solid waste, due to unavailability of suitable facilities to treat and dispose of the large amount of municipal solid waste generated daily in metropolitan cities. Improper municipal solid waste disposal locally, cause environmental impacts such as contamination of soil, water pollution, and increase methane emissions. In this study, an attempt has been made to use GIS and remote sensing to identify high potential zones for solid waste disposal in Jos South Local Government Area of Plateau State between 2019 and 2020. Primary data and secondary data were used for this study. The position data of the existing dumpsites in the study area were acquired in-situ with a handheld Global Positioning System (GPS) receiver. The secondary data consists of NigeriaSAT-X, geological, administrative maps, Google map, hydro-geophysical data and Shuttle Radar Topographic Mission (SRTM) images. Thematic layers considered in this study include drainage, road and land use/land cover, lithology and geology. The dumpsite point (X, Y) was imported as shapefile and superimposed on the study area boundary to show the existing location. Digital image segmentation of NigeriaSAT-X and geology dataset was carried out to derive the land use/ land cover and geology classifications of the study area. Lithological analysis was carried out using Kriging Method to interpolate the hydro-geophysical data. The slope, land/use, geology, drainage, road, waterbody, built-up and lithology were reclassified and overlaid using Weighted Sum Overlay Method a Spatial Analyst tool in ArcGIS 10.4 to generate the potential zones for solid waste disposal. The result shows the potential zones for solid waste disposal and characterized into unsuitable, less suitable, moderately suitable, suitable and highly suitable.
... Acquiring a better energy efficiency Ng et al., 2014;Pan et al., 2015;Watkins and McKendry, 2015;Marchi and Zanoni, 2017 . Lowering the environmental impacts Arbulú et al., 2013;Santibañez-Aguilar et al., 2015;Asefi and Lim, 2017;Diaz-Barriga-Fernandez et al., 2017 . Improving responsiveness and increasing the service level Andiç et al., 2012;Toso and Alem, 2014;Kadambala et al., 2017 . ...
... Table 2 shows the seasonal production of waste in the five con- sidered cities. It can be observed that cities 1 and 5 produce the highest quantity of MSW during a year mainly due to the higher population density in those cities (the data for the population of each city can be found in Santibañez-Aguilar et al., 2015 ). The pro- portion of metal waste is 3.5% of the total waste in every city, fol- lowed by plastic waste (5.1%) and glass waste (5.8%). ...
In this paper, a mixed integer linear programming (MILP) model for the optimization of a municipal solid waste (MSW) system in a supply chain (SC) network is presented with the aim of maximizing the total net profit over a specified time horizon. The proposed model covers waste collection at sites, separation at dumps, and processing for waste recycling and waste to energy (WtE) production at plants, as well as selling the end products. A case study is illustrated to demonstrate the feature and validity of the model. MSWs including biomass materials such as paper and food waste, non-biomass combustible materials such as plastic, and non-combustible materials such as glass and metal are managed by a combination of disposal in landfill sites, recycling to produce useful products, and incineration to produce power.
... The compensation factors of risk level in Equations (9) and (10) are introduced in order to formulate the risk of hazardous waste treatment and transportation in a more appropriate fashion, but the quantification of RS x is not an easy task. Even through researches have been extensively carried out for risk assessment and risk mitigation of hazardous material transportation [34][35][36], chemical substance storage and processing [37][38][39][40], incineration [41,42] and landfill [42], it is still difficult to find a general framework for risk assessment of hazardous waste management, which enables the quantification of risk level of all types of treatment and transportation on a common basis. In this regard, a simplified method for generalization and quantification of compensation factors of risk level is formulated in Equations (11)- (13). ...
... The compensation factors of risk level in Equations (9) and (10) are introduced in order to formulate the risk of hazardous waste treatment and transportation in a more appropriate fashion, but the quantification of RS x is not an easy task. Even through researches have been extensively carried out for risk assessment and risk mitigation of hazardous material transportation [34][35][36], chemical substance storage and processing [37][38][39][40], incineration [41,42] and landfill [42], it is still difficult to find a general framework for risk assessment of hazardous waste management, which enables the quantification of risk level of all types of treatment and transportation on a common basis. In this regard, a simplified method for generalization and quantification of compensation factors of risk level is formulated in Equations (11)- (13). ...
Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
... Further, the reuse processes are assumed to generate jobs, which improves quality of life. Later, Santibañez-Aguilar et al. [24] expanded their model to include a safety objective function to capture the exposure of a population to toxicity due to leaching and burning dumps. Olapiriyakul [25] included a social objective function to account for people living within 1 km of disposal and treatment sites. ...
Waste management is a critical sector that needs to co-ordinate its activities with outcomes that impact society. Multi-criteria decision-making methods for waste management have been widely considered using environmental and economic criteria. With the development of new social regulations and concerns, sustainable waste management needs to additionally target socially acceptable practices. Despite the need to aid solid waste management decision-makers in contemplating the three pillars of sustainability, a limited inclusion of social impact has been found in the multi-objective decision-making literature. This study presents a systematic literature review of multi-criteria decision-making methods in solid waste management. The purpose of this study is threefold. (1) Emphasize the application of multi-objective decision-making methods, summarizing the models that have been used and their applications; (2) provide insights into the quantification of social aspects and their inclusion in decision-making methods, providing a list of social indicators collected from the reviewed studies; (3) offer an analysis of stakeholders’ involvement in waste management. From the articles investigated, one can observe the importance of understanding the local context in which the waste management system is located and the necessity of community consultation to recognize the potential challenges and improvements to solid waste management systems. Consequently, the involvement of stakeholders is crucial during the quantification process of social indicators. In alignment with the findings and needs raised by this review, a methodological approach is suggested for integrating optimization, social aspects, and stakeholders under a waste management context.
... Mathematical models used in planning sustainable waste management solutions in a predictable structure have an important function in this development process [29]. In the planning and operation of sustainable integrated waste management processes, optimization modeling [30][31][32][33][34], multiobjective approaches [35][36][37][38], multicriteria decision analysis [39][40][41][42], and artificial neural networks [43][44][45][46] are extensively utilized in a user-friendly format that can assist decisionmakers. Integrated waste management is complex, as it requires many processes starting with the generation of the waste and extending to its collection, transfer, and transportation, the treatment of leachate, the biological and the thermal recovery of waste, and the selection of waste disposal sites. ...
The need to transition from a consumption-based waste hierarchy to a resource-conserving zero-waste management system for sustainable resource management has become unavoidable in today’s world. In this study, five different methods for waste separation at source were analyzed using an analytical hierarchy process based on five commonly used waste disposal methods. As a result of the analytical hierarchy analysis, ratios of 0.347, 0.286, 0.200, 0.101, and 0.066 were obtained for the five separation methods (0.347 for separation with six-parameter separate collection and 0.101 for mixed waste collection). The ratio of 0.286, achieved for the triple-separation method, was chosen to meet the requirements of the zero-waste regulation in Türkiye, and a district in Istanbul was selected as the study area. A model based on the residence density was developed. Within the scope of the model, the neighborhoods in the study area were statistically divided into three classes. By choosing one neighborhood from each class, route optimizations were made for both the existing routes and triple separations. The Network Analyst function in ArcGIS was used to determine the optimal routes based on the traveling distances and operational times of vehicles associated with each route. The results of the route-based analyses show that carbon dioxide emissions will increase by only 1.15% compared to the current situation, but the total amount will decrease in the long term if all waste management processes are carried out within the scope of zero-waste management.
... Santibañez-Aguilar et al. (2013) proposed a multi-objective model to determine the deployment of processing technologies, the location of processing facilities, and the distribution of waste and products with the objectives of maximizing the profit and the amount of recycled waste. Santibañez-Aguilar et al. (2015) later presented a multi-objective optimization model considering social risk for MSW planning. Asefi and Lim (2017) developed a multi-dimensional modelling approach to minimize the fixed and transport costs while maximizing the suitability of the MSW management system. ...
Increasing municipal solid waste (MSW) generation in the city has caused a serious problem to the authority, especially for emerging countries. Improper management of MSW will increase greenhouse gas (GHG) emissions. Apart from landfill, there are other options to convert MSW into valuable products or energy, such as recycling and incineration. This paper presents crisp and fuzzy optimization models for designing optimal supply chain networks for sustainable MSW management, considering economic (cost minimization) and environmental objectives (emissions reduction). The crisp model is based on a superstructure and consists of material balances, capacity limits and planning constraints for MSW transfer stations, disposal sites and treatment technologies. Fuzzy optimization with max-min aggregation is then incorporated to handle conflicting economic and environmental objectives, as well as uncertainties in GHG emission factors and cost coefficients of MSW treatment. A case study for the design of an optimal MSW supply chain network in the city of Qingdao, China is presented to illustrate the proposed approach. The conflicting objectives of minimizing the total net cost and GHG emissions for MSW transport and treatment are analyzed using the crisp model, yielding a set of Pareto optimal solutions. A compromise solution achieving a 21.6% cost reduction and a 28.4% emissions reduction is identified using the fuzzy model. An inferior solution is also found with smaller cost (19.1%) and emissions reductions (25.1%) due to the use of conservative estimates of uncertain cost coefficients and emission factors. These results demonstrate the effectiveness of the proposed models in dealing with the MSW management problem.
... Recently, MSW optimal allocation models have been developed to incorporate multiple disposal technology, especially waste-to-energy (WTE) technology [16,17]. Considering several WTE technologies, Santibañez Aguilar et al. [18] proposed an optimization model to achieve the optimal MSW allocation. Xiong et al. [19] took into account a hybrid WTE system and found that an optimal incorporation of WTE technologies is more economically advantageous. ...
The municipal solid waste (MSW) disposal system is the key for building the smart city. In the MSW disposal system, the MSW is allocated among the disposal plants in the first echelon, and then the derivatives (incineration residues and RDF) are allocated between residues disposal plants and markets in the second echelon. In the two-echelon optimal allocation of MSW disposal system, two objectives, cost and environmental impact, should be considered. Considering the uncertainty in the MSW disposal system, this paper constructs a grey fuzzy multi-objective two-echelon MSW allocation model. The model is divided into two sub models and the expected value sorting method is applied to solve the model. The proposed model successfully was applied to a real case in Huangshi, China. The numerical experiments showed RDF technology has advantages on both cost and environmental impact comparing to other disposal technology on disposing MSW.
... However, the developed optimization framework did not consider the potential of recyclable materials which can be further processed to compensate for any expenses. Santibanez-Aguilar et al. [30] developed a mathematical programming model used to determine the reuse of MSW to maximize the economic objective while considering the environmental and safety aspects simultaneously. Satchatippavarn et al. [24] employed a superstructure optimization approach together with the biorefinery concept for the design of an integrated MSW management system. ...
The main objective of this study is to develop a decision-making tool for the design of the optimal municipal solid waste (MSW) facilities based on superstructure optimization. Currently, the disposal of MSW is a major problem due to the lack of awareness of the negative impacts resulting from dumping MSW into the environment. This poses a challenge for the authorities. MSW valorization such as anaerobic digestion, pyrolysis, and gasification has been increasingly focused on as an approach when handling MSW to enhance both economic and environmental sustainability. However, with an increasing array of processing technologies, the design of MSW facilities involving the integration of these technologies is becoming tedious and unmanageable. To deal with this problem, superstructure optimization is proposed. It is an effective tool for the design of several chemical processes because it is able to consider all potential process alternatives including the optimal solution using mathematical models based on mass and energy balances. Uncertainty is incorporated into the optimization framework to enhance the robustness of the solution. The proposed methodology was applied in the design process of the MSW facility in Ubon Rathathani Province, Thailand, with the objective function of maximizing the profit. The optimization problem was developed as Mixed Integer Linear Programming and it was solved using an optimization platform, General Algebraic Modeling System, with CPLEX as the solver related to obtaining the optimal solution. The results show there to be as positive profit that is economically viable compared to the use of landfill technology.
... Así como, presentando riesgos extremos respecto al tratamiento, exposición, o manejo inadecuado de los subproductos generados en la descomposición de los RSU. Un mal manejo de los subproducto generados de la descomposición de los RSU como el Biogás puede dar lugar a una explosión en los lugares destinados a la disposición de los residuos sólidos (Santibañez-Aguilar et al., 2015). ...
... However, the developed optimization framework did not consider the potential of recyclable materials which can be further processed to compensate for any expenses. Santibanez-Aguilar et al. [30] developed a mathematical programming model used to determine the reuse of MSW to maximize the economic objective while considering the environmental and safety aspects simultaneously. Satchatippavarn et al. [24] employed a superstructure optimization approach together with the biorefinery concept for the design of an integrated MSW management system. ...
The main objective of this study is to develop a decision-making tool for the design of the optimal municipal solid waste (MSW) facilities based on superstructure optimization. Currently, the disposal of MSW is a major problem due to the lack of awareness of the negative impacts resulting from dumping MSW into the environment. This poses a challenge for the authorities. MSW valorization such as anaerobic digestion, pyrolysis, and gasification has been increasingly focused on as an approach when handling MSW to enhance both economic and environmental sustainability. However, with an increasing array of processing technologies, the design of MSW facilities involving the integration of these technologies is becoming tedious and unmanageable. To deal with this problem, superstructure optimization is proposed. It is an effective tool for the design of several chemical processes because it is able to consider all potential process alternatives including the optimal solution using mathematical models based on mass and energy balances. Uncertainty is incorporated into the optimization framework to enhance the robustness of the solution. The proposed methodology was applied in the design process of the MSW facility in Ubon Rathathani Province, Thailand, with the objective function of maximizing the profit. The optimization problem was developed as Mixed Integer Linear Programming and it was solved using an optimization platform, General Algebraic Modeling System, with CPLEX as the solver related to obtaining the optimal solution. The results show there to be as positive profit that is economically viable compared to the use of landfill technology.
... A superstructure-based approach is the design methodology followed in this work to assess different wastewater thermochemical conversion routes, corresponding to the use and/or combination of different technologies. A similar approach has been proposed and used by several authors (Maronese et al., 2015;Santibañez-Aguilar et al., 2015). All process units are represented as black-box models, built by assessing the conversion features, either from extensive literature review or real, operating, units. ...
Wastewater treatment and sludge disposal are responsible for considerable costs and emissions in a global scale. With population and urbanization growing, tackling the rational and efficient use of energy while fulfilling the desired effluent standards are imperative. In this work, a superstructure-based approach is designed to incorporate alternative treatments for wastewater. In particular, technologies like hydrothermal liquefaction and gasification, coupled with technologies for CO2 conversion to value-added products are studied. Multi-objective optimization is applied as a way to generate multiple solutions that correspond to different system configurations. From a reference treatment cost of almost 0.16 $/mWW3, an environmental impact of 0.5kgCO2/mWW3 and an energy efficiency of 5%, different configurations are able to transform a waste water treatment plant to a net profit unit, with a net environmental benefit and energy efficiency close to 65%. The investment in hydrothermal liquefaction producing biocrude coupled with catalytic hydrothermal gasification demonstrated to yield consistently better total costs and environmental impacts. Parametric analysis is performed in the inlet flow of wastewater to account for different sizes of waste water treatment plant, with smaller inlets achieving values closer to those of the state-of-the-art configuration.
... However, the developed optimization framework did not consider the potential of recyclable materials which can be further processed to compensate for any expenses. Santibañez-Aguilar et al. [29] developed a mathematical programming model used to determine the reuse of MSW to maximize the economic objective while considering the environmental and safety aspects simultaneously. Satchatippavarn et al. [24] employed a superstructure optimization approach together with the biorefinery concept for the design of an integrated MSW management system. ...
The main objective of this study is to develop a decision-making tool for the design of the optimal municipal solid waste (MSW) facilities based on superstructure optimization. Currently, the disposal of MSW is a major problem due to the lack of awareness of the negative impacts resulting from dumping MSW into the environment. This poses a challenge for the authorities. MSW valorization such as anaerobic digestion (AD), pyrolysis, gasification etc has been increasingly focused on as an approach when handling MSW to enhance both economic and environmental sustainability. However, with an increasing array of processing technologies, the design of MSW facilities involving the integration of these technologies is becoming tedious and unmanageable. To deal with this problem, superstructure optimization is proposed. It is an effective tool for the design of several chemical processes because it is able to consider all potential process alternatives including the optimal solution using mathematical models based on mass and energy balances. Uncertainty is incorporated into the optimization framework to enhance the robustness of the solution. The proposed methodology was applied in the design process of the MSW facility in Ubon Rathathani province, Thailand, with the objective function of maximizing the profit. The optimization problem was developed as Mixed Integer Linear Programming (MILP) and it was solved using an optimization platform, GAMS, with CPLEX as the solver related to obtaining the optimal solution. The results show there to be as positive profit that is economically viable compared to the use of landfill technology.
... Santibañez-Aguilar y col. presentan un modelo para maximizar el beneficio económico en la planeación del reciclaje de residuos sólidos municipales considerando también de forma simultánea criterios de sustentabilidad y de seguridad [81]. En la misma línea, Azadeh y col. ...
Los productos en aerosol representan un segmento en crecimiento en el mercado de los productos de consumo masivo y con una importante proyección hacia el futuro. Para su correcto desempeño, requieren en su mayoría del uso de gases licuados («propelentes») que están contenidos a presión dentro del recipiente con producto. Entre las propiedades clave que requieren estos propelentes están la alta volatilidad y ser inertes químicamente con el �fin de no interferir con el resto de ingredientes en la formulación; esto hace que el
universo de posibles sustancias a seleccionar sea limitado, y que se conforme de sustancias que son altamente inflamables o que tienen un alto potencial de calentamiento global (o ambos). Desde un punto de vista de seguridad, almacenar sustancias inflamables y bajo presión representa un riesgo elevado de incidentes de incendio y explosión. Por otro lado, el diseño de un producto tipo spray que utiliza gases licuados significa que necesariamente la mezcla propelente será expulsada a la atmósfera junto con el producto, con consecuencias negativas sobre el ambiente en el caso que se trate de sustancias con un potencial de calentamiento global elevado.
Mientras avanza la agenda de investigación y desarrollo de nuevas sustancias propelentes que sean seguras, amigables con el medio ambiente y competitivas en costo, es relevante contar con una metodología que permita optimizar la composición de las mezclas propelentes buscando el mínimo impacto en indicadores económicos, de seguridad y ambientales. En este trabajo se presenta un modelo de optimización multiobjetivo que selecciona entre un conjunto de sustancias propelentes, aquellas que formen la mezcla que además del mínimo costo, logre los menores impactos ambientales y los
menores riesgos de seguridad en su manejo. Para ello, se modela el equilibrio líquido-vapor de la mezcla utilizando la ecuación de estado de Peng-Robinson-Stryjek-Vera con la regla de mezclado clásica de Van der Waals. La función objetivo económica es la suma ponderada del costo de cada componente de la mezcla; la función objetivo de seguridad se formula utilizando el Índice Dow de Incendio y Explosión para la mezcla; la función objetivo ambiental es la suma ponderada de los valores de potencial de calentamiento global de cada compuesto presente.
El modelo de optimización se resolvió en GAMS® siguiendo una secuencia evolutiva: iniciando con un planteamiento NLP con equilibrio líquido-vapor ideal hasta llegar al planteamiento MINLP con equilibrio líquido-vapor riguroso. La composición óptima reportada como solución del problema MINLP riguroso cumple con los objetivos planteados, es económicamente viable y es físicamente factible. El resultado fue verifi�cado satisfactoriamente utilizando un simulador de procesos para comprobar la consistencia termodinámica así como las propiedades de la mezcla en el equilibrio.
... The considered waste is non-reusable, nonrecyclable, and non-biodegradable MSW with a low moisture content that is suitable for combustion. Related data is taken from Santibañez-Aguilar et al. (2015). The waste processing technologies used for electricity generation are incineration with the capacity of processing 1000 tons of MSW per day and energy potential of 600 kWh per ton of waste, gasification having capacity of 900 tons MSW/day and 700 kWh/ton waste, and pyrolysis with 700 tons MSW/day and 650 kWh/ton waste. ...
This paper addresses a mixed integer linear programming model for the optimal utilization of municipal solid waste in a multi-echelon supply chain network. The model focuses on tactical and operational level decisions including the supply, production, and distribution. It aims to maximize the annual net profit by optimizing the choice of waste-to-energy technologies through observing the related capacity and environmental constraints and market demands. The proposed sustainable waste management model not only reduces the burden on the environment, but also optimally distributes the solid waste through the system and converts it into electricity, thus contributing towards energy supply. Sensitivity analyses are conducted to investigate the effects of changes in waste separation rate, energy conversion rate, and energy efficiencies on the system performance and on the environment. The model is solved using GAMS/CPLEX.
... The considered waste is non-reusable, nonrecyclable, and non-biodegradable MSW with a low moisture content that is suitable for combustion. Related data is taken from Santibañez-Aguilar et al. (2015). The waste processing technologies used for electricity generation are incineration with the capacity of processing 1000 tons of MSW per day and energy potential of 600 kWh per ton of waste, gasification having capacity of 900 tons MSW/day and 700 kWh/ton waste, and pyrolysis with 700 tons MSW/day and 650 kWh/ton waste. ...
This paper addresses a mixed integer linear programming model for the optimal utilization of municipal solid waste in a multi-echelon supply chain network. The model focuses on tactical and operational level decisions including the supply, production, and distribution. It aims to maximize the annual net profit by optimizing the choice of waste-to-energy technologies through observing the related capacity and environmental constraints and market demands. The proposed sustainable waste management model not only reduces the burden on the environment, but also optimally distributes the solid waste through the system and converts it into electricity, thus contributing towards energy supply. Sensitivity analyses are conducted to investigate the effects of changes in waste separation rate, energy conversion rate, and energy efficiencies on the system performance and on the environment. The model is solved using GAMS/CPLEX.
... This may imply greater complexity for the optimization model and can drastically increase the computational burden in comparison with singleobjective optimization. This requires a range of assumptions or simplifications to deal with the computational complexity that arises, e.g., by adopting a reference point (Minciardi et al. 2008) or obtaining Pareto fronts through optimization of individual objectives (Santibanez-Aguilar et al. 2015). In this view, the attempt to incorporate LCA, or social oriented criteria, into the optimization model poses additional challenges to it, such as the introduction of a greater complexity into the problem, tractability, and the difficulty of aggregating different objectives into one term. ...
... In addition, the income generated could help finance the investment made in the cogeneration plants, saving money that could benefit public entities. Santibañez-Aguilar et al. (2015) propose a mathematical programming model for the optimal planning of the supply chain associated with the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The results show that it is possible to implement a distributed processing system to reuse MSW while maximizing the net supply chain profit. ...
This article is focused on financial sustainability of waste management activities. It aims to understand if and how choices oriented to environmental protection and contextual factors influence waste management companies’ revenues and costs, which in turn affect their financial sustainability and, thus, companies’ ongoing viability. For this purpose, an empirical analysis on 880 Italian municipalities has been conducted for three years.
The financial sustainability has been evaluated with reference to waste management companies working in those territories; whereas a set of quantitative and qualitative data has been taken into account to investigate possible influencing factors. The results show that separate waste collection may positively influence the companies’ financial performance, while the municipalities’ territorial extension affects the profitability negatively. Lastly, there is no evidence of a relationship between companies’ financial sustainability and the potential presence of disposal waste plants and the geographical area in which they operate. For the analyzed companies, it seems that it would be more convenient expanding their business by boosting the separate waste collection activities, than enlarge the extension of the served territories. These findings are important to support firms’ decisions regarding both environmental and financial issue,
either crucial for their sustainability over time, and for policy makers in order to detect appropriate tools that can support companies in implementing the EU waste management targets.
... Thus, Santibañez-Aguilar et al. (2013) proposed a mathematical programming model for the optimal planning of the supply chain associated to the MSWM system to maximize the economic benefit while accounting for technical and environmental issues. More recently, Santibañez-Aguilar et al. (2014 ) included safety issues in this model. Tan et al. (2014 ) implemented a study for synthetizing a MSW processing network to produce energy and other value-added products. ...
This paper presents a multi-objective optimization approach for the strategic planning of a municipal solid waste (MSW) management system under uncertainty. The formulation considers the involved tasks such as recycle, reuse, transportation, separation and distribution. The proposed approach also accounts for the multiple involved stakeholders with the objective of maximizing the benefit to all the participants. The main variables that are considered under uncertainty were the MSW availability and the prices of the products made from the recovered MSW. A case study for Mexico is analyzed, where a random generation approach based on historical data is used to introduce three different financial risk levels: the optimistic, mean and pessimistic cases. This way, the obtained results provide additional information about the system. Then, the stakeholders will be more certain of making any decision.
... However, capacities of each technology were fixed, and they did not consider treatment of recyclable components. Santibñ aez-Aguilar et al. considered economic, environmental, and safety objectives of a MSW supply chain considering collection, transportation, and treatment, although they modeled the treatment stage with a black box approach [86 ]. Additionally, Harijani et al. considered recyclable streams as well as economic, environmental, and social aspects of waste utilization and discard along the supply chain, applying an MILP framework to a case study in Tehran [87]. ...
Managing food, water, and energy waste streams leads to more sustainable production, consumption, and distribution processes in the food–water–energy nexus (FWEN). Agricultural and organic waste streams within the FWEN can be difficult to manage due to both volume and their potential environmental impacts. However, they are also often characterized by a rich mix of organic compounds, ripe for conversion into energy or value-added products. Process systems engineering (PSE) stands uniquely positioned to understand the interconnections between food, water, and energy of agricultural and food wastes, wastewater, and municipal solid waste (MSW). Targeted advances in systems analysis as well as design and optimization of integrated FWEN waste management technologies and processes are expected to have the greatest impact. When building integrated mathematical models, care must be taken to consider waste treatment not as an independent process unaffected by the FWEN, but as a core component of the FWEN, connected to all nexus resources and systems.
... 11 Santibanẽz-Aguilar et al. considered economic and environmental issues in the design of MSW reuse systems 12 and then included safety objectives. 13 Carvalho et al. presented an approach that takes into account the economies of scale in the MSW management system. 14 Recently, Mirmajlesi and Shafei reported a multi-period, multi-product, and multi-echelon model for designing supply chains. ...
... 4. Overview of the exchanges between a CIWMS and the ecosystems. Santibañez- Aguilar et al., 2013;Santibañez-Aguilar et al., 2015;Srivastava and Nema, 2012;Vadenbo et al., 2014a,b), is possibly the most adequate technique to take into account all the sustainability criteria. Oppositely, other authors (Menikpura et al., 2012;Tulokhonova and Ulanova, 2013) combined LCA with a set of indicators to account for the other sustainability dimensions of an IWMS. ...
The continuous depletion of natural resources related to our lifestyle cannot be sustained indefinitely. Two major lines of action can be taken to overcome this challenge: the application of waste prevention policies and the shift from the classical linear Integrated Waste Management Systems (IWMSs) that focus solely on the treatment of Municipal Solid Waste (MSW) to circular IWMSs (CIWMSs) that combine waste and materials management, incentivizing the circularity of resources. The system analysis tools applied to design and assess the performance of linear IWMSs were reviewed in order to identify the weak spots of these methodologies, the difficulties of applying them to CIWMSs, and the topics that could benefit from further research and standardization. The findings of the literature review provided the basis to develop a methodological framework for the analysis of CIWMSs that relies on the expansion of the typical IWMS boundaries to include the upstream subsystems that reflect the transformation of resources and its interconnections with the waste management subsystems.
... Here, safety was measured through a risk quantification for the stages that are part of a life cycle for the biorefinery. Similar approaches have been used for municipal solid waste management [54], for facility location and the interaction of processing facilities with surround watersheds [55], for safe heat exchanger network allocation [56], optimal placement of gas detectors [57], facility layout problem considering toxic release and mitigations systems [58] and for quantifying stability points in a steady state operation [59]. ...
Several indices have been developed as a measure of safety for different pieces of equipment, use of chemicals and operating conditions in transformation processes. Current efforts are being observed on the application of such types of metrics as part of the design of a process. This application focuses on the synthesis of inherently safer designs. It is then important to recognize proper safety metrics that can be applied from the early design stage of a chemical process. In this paper a review on the development of safety indices, with particular emphasis on their application for process design, is presented. The type of information and the output one obtains from the application of such indices is described. Some examples of recent applications that include safety as part of the design of several chemical processes are given.
... Here, safety was measured through a risk quantification for the stages that are part of a life cycle for the biorefinery. Similar approaches have been used for municipal solid waste management [54], for facility location and the interaction of processing facilities with surround watersheds [55], for safe heat exchanger network allocation [56], optimal placement of gas detectors [57], facility layout problem considering toxic release and mitigations systems [58] and for quantifying stability points in a steady state operation [59]. ...
Several indices have been developed as a measure of safety for different pieces of equipment, use of chemicals and operating conditions in transformation processes. Current efforts are being observed on the application of such types of metrics as part of the design of a process. This application focuses on the synthesis of inherently safer designs. It is then important to recognize proper safety metrics that can be applied from the early design stage of a chemical process. In this paper a review on the development of safety indices, with particular emphasis on their application for process design, is presented. The type of information and the output one obtains from the application of such indices is described. Some examples of recent applications that include safety as part of the design of several chemical processes are given.
This work presents a methodology integrating Non-Linear Programming (NLP) for multi-objective and multi-period optimization, addressing sustainable waste management and energy conversion challenges. It integrates waste-to-energy (WtE) technologies such as Anaerobic Digestion (AD), Incineration (Inc), Gasification (Gsf), and Pyrolysis (Py), and considers thermochemical, technical, economic, and environmental considerations through rigorous non-linear functions. Using Mexico City as a case study, the model develops waste management strategies that balance environmental and economic aims, considering social impacts. A trade-off solution is proposed to address the conflict between objectives. The economical optimal solution generates 1.79M and reduces emissions by 54%, where 40% is due to gasification technology. Moreover, the environmentally optimal solution, with incineration and gasification generates 9500 MWh/day and 5960 MWh/day, respectively, demonstrates the capacity of the model to support sustainable energy strategies. Finally, this work presents an adaptable framework for sustainable waste management decision-making.
The transformation to a resource-circular bio-economy offers a mechanism to mitigate climate change and environmental degradation. As advanced bioeconomy components, biorenewables derived from terrestrial, aquatic biomass and waste resources are expected to play significant roles over the next decades. This study provides an overview of potential biomass resources ranging from higher plant species to phototrophic microbial cluster, and their fundamental photosynthesis processes as well as biogeochemical carbon cycles involved in ecosystems. The review reflects empirical advances in conversion technologies and processes to manufacture value-added biorenewables from biomass and waste resources. The nexus perspective of resource-biorenewable-waste has been analysed to understand their interdependency and wider interaction with environmental resources and ecosystems. We further discussed the systems perspectives of biorenewables to develop fundamental understanding of resource flows and carbon cycles across biorenewable subsystems and highlight their spatial and temporal variability. Our in-depth review suggested the system challenges of biorenewable, which are subject to nonlinearity, variability and complexity. To unlock such system complexity and address the challenges, a whole systems approach is necessary to develop fundamental understanding, design novel biorenewable solutions. Our review reflects recent advances and prospects of computational methods for biorenewable systems modelling. This covers the development and applications of first principle models, process design, quantitative evaluation of sustainability and ecosystem services and mathematical optimisation to improve design, operation and planning of processes and develop emerging biorenewable systems. Coupling these advanced computational methods, a whole systems approach enables a multi-scale modelling framework to inherently link the processes and subsystems involved in biomass ecosystems and biorenewable manufacturing. Reviewing modelling advances, our study provides insights into the emerging opportunities in biorenewable research and highlights the frontier research directions, which have the potential to impact biorenewable sector sustainability.
Over the past few years, supply chains have become globalised and multi-tiered. These factors complicate their structure as the focal company is responsible for the problems experienced at each stage in the multi-tier supply chain. The critical issue for focal companies in managing their multi-tier supply chain is to adopt sustainability standards. One of the study's contributions is the role of weight determination in the tiers and evaluation of alternative suppliers in facilitating the effective management of multi-tier supply chains, especially in complex industries such as the food industry. The other contribution of this study is its proposition for a multi-stage framework based on sustainability concerns. The study identifies 14 criteria for companies in diffusing sustainability standards throughout multi-tier supply chains. The weights of these criteria are determined for each tier of the food supply chain using the Best Worst Method. Results show that the ‘environmental’ criteria are most important for supply chain tiers in the food industry. Supply chain visibility/traceability is the most important criteria for the first tier, followed by environmental responsibilities, for the second and environmental competencies for the third. Finally, for the food company, PROMETHEE is used to evaluate three alternative suppliers for each tier.
The main objective of this study is to develop a decision-making tool for the design of the optimal municipal solid waste (MSW) facilities based on superstructure optimization. Currently, the disposal of MSW is a major problem due to the lack of awareness of the negative impacts resulting from dumping MSW into the environment. This poses a challenge for the authorities. MSW valorization such as anaerobic digestion, pyrolysis, gasification etc has been increasingly focused on as an approach when handling MSW to enhance both economic and environmental sustainability. However, with an increasing array of processing technologies, the design of MSW facilities involving the integration of these technologies is becoming tedious and unmanageable. To deal with this problem, superstructure optimization is proposed. It is an effective tool for the design of several chemical processes because it is able to consider all potential process alternatives including the optimal solution using mathematical models based on mass and energy balances. Uncertainty is incorporated into the optimization framework to enhance the robustness of the solution. The proposed methodology was applied in the design process of the MSW facility in Ubon Rathathani province, Thailand, with the objective function of maximizing the profit. The optimization problem was developed as Mixed Integer Linear Programming and it was solved using an optimization platform, General Algebraic Modeling System, with CPLEX as the solver related to obtaining the optimal solution. The results show there to be as positive profit that is economically viable compared to the use of landfill technology.
La cadena de valor en las operaciones propiciando una mejora de la competitividad en la Industria 4.0 es una obra donde el lector podrá encontrar diferentes temas de investigación básica y aplicada; escritos por expertos en sus áreas y, que a su vez, ayudará tanto a empresarios y académicos en la generación de conocimiento para la toma de decisiones en las organizaciones y que esto detone en lograr una mayor competitividad en las organizaciones.
Los doce capítulos pertenecientes a esta libro fueron elaborados por investigadores de diversas universidades colombianas y mexicanas como son: la Pontificia Universidad Javeriana, Universidad Autónoma de Nuevo León, Universidad de Colima, Universidad de Monterrey, Universidad de la Amazonia, Universidad de Guadalajara, Universidad Iberoamericana, Universidad Autónoma de Aguascalientes, Universidad Michoacana de San Nicolás de Hidalgo y Tecnológico Nacional de México.
Entre los diferentes tópicos se discuten existen tres estudios que se enfocan al sector agrícola en países como México y Colombia, analizando la competitividad de la industria ganadera como de frutos del bosque o bayas (berries) a través de un enfoque sistémico, la cadena de valor y la industria 4.0; bajo este último enfoque se estudian las evidencias de dos investigaciones sobre los clústeres de tecnologías de información en Colima y el de salud en Baja California. Así también se aborda el estudio de la cadena de suministro en México con dos estudios; uno bibliométrico y otro empírico, aplicado en el Estado de Aguascalientes, donde en ambos se analiza como este fenómeno ha afectado los procesos producticos en Pymes manufactureras y por lo tanto su desempeño. Del mismo modo, se estudian temas de cómo resiliencia y la empresa socialmente responsable son elementos importantes para lograr la competitividad. Por ultimo, se tienen tres propuestas donde presentan evidencias empíricas de cómo un sistema de flexibilidad en la producción y su optimización para para lograr la competitividad en diferentes industrias manufactureras.
En este libro se realizó la revisión por pares a doble ciego bajo los estándares del Reglamento para la Actividad Editorial del CUCEA de la Universidad de Guadalajara bajo los siguientes criterios: derivarse de un proyecto de investigación, ser congruentes con el objetivo del libro, así como, mostrar avances significativos en los diferentes ámbitos involucrados, así como tener un comité editorial y la opinión favorable de un dictaminador externo. Además para cuidar que fueran inéditos, los manuscritos fueron analizados con software especializados para garantizar la originalidad de los mismos. Lo anterior, con la idea de garantizar el carácter científico de los trabajos presentados.
The main objective of this study is to develop a decision-making tool for the design of the optimal municipal solid waste (MSW) facilities based on superstructure optimization. Currently, the disposal of MSW is a major problem due to the lack of awareness of the negative impacts resulting from dumping MSW into the environment. This poses a challenge for the authorities. MSW valorization such as anaerobic digestion (AD), pyrolysis, gasification etc has been increasingly focused on as an approach when handling MSW to enhance both economic and environmental sustainability. However, with an increasing array of processing technologies, the design of MSW facilities involving the integration of these technologies is becoming tedious and unmanageable. To deal with this problem, superstructure optimization is proposed. It is an effective tool for the design of several chemical processes because it is able to consider all potential process alternatives including the optimal solution using mathematical models based on mass and energy balances. Uncertainty is incorporated into the optimization framework to enhance the robustness of the solution. The proposed methodology was applied in the design process of the MSW facility in Ubon Rathathani province, Thailand, with the objective function of maximizing the profit. The optimization problem was developed as Mixed Integer Linear Programming (MILP) and it was solved using an optimization platform, GAMS, with CPLEX as the solver related to obtaining the optimal solution. The results show there to be as positive profit that is economically viable compared to the use of landfill technology.
Growing world population along with fast economic growth and increased living standards have increased the municipal waste generation making its management be a foremost global issue. The problem is even more serious in urban areas as its improper management prompts tainting of soil, water, and environment which create public health risks. These problems of waste disposal and management were usually assessed by traditional methods which require loads of data. The recent development in the new software technologies and Internet along with the introduction of gradually more compact and dependable hardware products have presented the ability to accurately deal with these procedures more easily than costly and tedious field experiments. This paper presents an outline of the utilization of different scientific models in solving the environmental problems of municipal waste disposal. The examination of past literature uncovered that usually optimization models were used to find the answer of 'what is the best' under an explicit arrangement of conditions, while, simulation models were usually helpful to get an answer to 'what if? ' due to their predictive capability. An indication of the municipal waste disposal problems and its management alongside the ramifications of the investigation is provided. The rationale and backdrop of the waste disposal issues are described. The applications of optimization modeling, multi-objective approach, multi-criteria decision analysis, and artificial neural networks in waste management are presented and applications of these modeling techniques in diverse case studies
worldwide are described. And finally, the conclusions of the analysis are summarized.
Chemical industries play a significant role in the global debate on reasons behind climate change and adverse social effect. It is necessary to understand as well as find ways to improve the sustainability aspects of the supply chain in the chemical industry. This study presents a systematic review through content analysis using "Five W" namely Why, When, Where, Who, and What; and "Two H" namely How and How much framework, to understand the evolution of sustainable supply chain in the chemical industry over past two decades. Using 145 selected articles, this study attempts to understand the research trend over journal outlets, preferred methodologies, mathematical tools, theoretical perspectives, and issues studied over various stages of growth across various economies. Finally, the SWOT framework has been used to understand the strength-weakness of Sustainable Supply Chain research in the chemical industry and map it to the opportunities-threat across multiple sub-industries. This framework is further used to develop the future scope of research by identifying theories, techniques/tool to overcome challenges across multiple issues in the Chemical industry's achievement of sustainability goal.
Due to problems such as limited land area for waste disposal and waste-borne diseases, waste management organizations have increasingly been offering technologies for recovering energy from waste. These technologies can help governments, local authorities, developers and investors for mitigating climate change and building sustainable societies. The suitable waste-to-energy production technology selection is a complex issue in waste supply chain management that must not only be assessed in terms of both socioeconomic and environmental criteria. With the purpose of balance between energy trilemma issues in the context of waste-to-energy generation and develop sustainable waste management strategies in the waste chain, energy justice criteria must also be taken into consideration. The paper considers the application of an integrated multi-criteria decision-making model consisting of fuzzy decision-making trail and evaluation laboratory method, the analytic network process and the simple additive weighting approaches. The integrated method can be applied to select the suitable technology in a sustainable manner, taking into account energy justice criteria. The applicability of proposed model is demonstrated by a case study of the technology selection in the city of Behbahan, Iran. It includes various technologies for waste-to-energy generation and ranks technologies from the most to least preferred as: Anaerobic digestion, Gasification, Pyrolysis, and Incineration.
Enhancing sustainability in Municipal Solid Waste (MSW) management requires options that alleviate environmental issues and provide economic and social benefits. Though, the social aspect of sustainability has not been thoroughly investigated in the related literature. Therefore, this paper proposes a new multi-objective mathematical programming model considering new employment opportunities as the social side of sustainability. Furthermore, due to ineffective public participation in the waste management processes in the developing countries, incorporating waste separation after collection in the waste management practices is the suggestion of this study to contribute to the social sustainability. Other aspect of the proposed model is uncertainty that is inevitable and should be acknowledged to guarantee reliability in the decision-making process. To handle the uncertain model coefficients and stipulations, we utilize the robust possibilistic programming approach. The application of the proposed model is demonstrated in a real case study associated with the Tehran MSW system. The obtained results indicate that composting is the worst waste final disposal alternative, while anaerobic digestion and incineration have better performance in terms of the sustainability indicators. Moreover, the preliminary findings of a sensitivity analysis show that the waste recovery percentage has a direct influence on rates of waste reuse and recycling.
Storage of municipality solid waste (MSW) in landfills is a traditional practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of MSW by treatment facilities, and markets imposing demand for products. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. An L-shaped decomposition algorithm is shown to be effective in obtaining solutions for the stochastic model. A risk model is adopted to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.
The efficient management of municipal organic waste (OW) will contribute to the transition to a circular economy of nutrients. The goal of this work is to determine the optimal configuration of a waste management system that valorizes the OW generated in Cantabria. The model was developed with the EASETECH and the DNDC softwares, and it assumes that the products generated from the OW (compost, digestate, struvite and ammonium sulphate) are applied to land to grow corn. The closed-loop perspective of the system is given by the application of these products, which results in a reduction in the consumption of the industrial fertilizers required for the production of food, a fraction of which becomes OW in a later life cycle stage. A superstructure comprising technologies to manage OW was developed. A MILP problem was formulated for the multi-objective optimization of the flows of OW that are sent to each technology according to these objective functions to be minimized: the carbon footprint of the system (CF), the landfill area occupied by OW (LFA) and the consumption of non-renewable raw materials (NR-RM). It was found that a combination of different technologies is required to attain a trade-off between the objective functions. The minimization of the CF leads to a system configuration with a high N circularity and the maximal values of LFA and NR-RM, whereas the minimal consumption of NR-RM is achieved at the scenarios with low N recovery rates. This indicates that an enhanced circularity of resources does not necessarily entail that the overall consumption of natural resources and the emission of environmental burdens of the system decrease.
A systematic design of municipal solid waste (MSW) management system can lead to identify a promising and/or sustainable way of handling MSW by processing it into energy and valuable products. In this study, a systematic framework is developed for the superstructure-based optimization of MSW processing routes. The proposed superstructure includes the potential technological alternatives (such as recycling, composting, anaerobic digestion with electricity generation, gasification followed by catalytic transformation, gasification with electricity generation, plasma arc gasification with electricity generation, pyrolysis with electricity generation, incineration with electricity generation, and landfill with electricity generation) for producing valuable products from MSW. Based on the developed superstructure, a mixed integer nonlinear programming (MINLP) model is developed to identify the optimal MSW processing pathways considering two different MSW handling scenarios. For ease of the solution, the MINLP model is linearized to its equivalent MILP form, and solved in GAMS. The solution to the optimization problem provides the optimal/promising route for the synthesis of useful products from MSW under chosen economic objective function. The developed framework is applied on a case study of Abu Dhabi Emirate to find the optimal processing pathway for handling and processing of MSW into energy and value-added products. The optimization results show that an integrated pathway comprising of recycling the recyclable components of MSW along with the production of bioethanol from the rest of the waste via gasification followed by catalytic transformation can provide potential economic benefits. A sensitivity analysis is also executed to investigate the effect of key economic and technical parameters on the optimization results.
Consumption habits and population growth have drastically increased the waste production around the world. However, several developing countries do not have an adequate waste management system. This way, a mathematical model for the optimal planning of a waste management system could be a useful tool to make decisions about the design of a waste processing system to promote sustainable public polices and cooperation among multiple cities. Therefore, this work proposes a mathematical formulation for the optimal planning of a waste management system considering waste from different neighboring cities divided in several sites, as well as the dependence over time for the variables and parameters through a set of differential equations for properly capturing the associated dynamic behavior. Results show that given the data of potential locations for sites, landfills, processing plants and consumers, as well as prices of useful products, availability of waste, upper and lower limits, unitary costs for the different activities carried out in the waste management system and initial values for inventory and order levels, it is possible to obtain the optimal selection and location of the entities of the waste management system as well as the plant capacities and material flows to be transported, processed, stored and sold. The proposed mathematical formulation is general and it can be applied to any waste type, involving different landfills, sites, cities, processing routes and processing plants. Although the CPU time increases for considering the dynamic behavior, it is proved that the associated costs decrease significantly.
Until recently, food production focused mainly on delivering high-quality products at low cost and little attention was paid to environmental impact and depletion of natural resources. As a result of the growing awareness of climate change, shrinking resources, and increasing world population, this trend is changing. A major concern in Food Supply Chains (FSCs) is food waste. To remain competitive, FSCs are challenged to adopt new technologies that reduce or valorize food waste. These technologies can contribute to maintaining or increasing economic output and concurrently reduce the environmental impact of current operations, i.e. achieving what has been defined as eco-efficiency. Designing eco-efficient supply chains requires complex decision support models that can deal with multiple dimensions of sustainability while taking into account the specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM), a research field within Operations Research, is particularly suitable to support decision making when multiple and (mostly) conflicting criteria are involved. In this research, multi-objective optimization was used to quantify trade-offs between conflicting objectives and derive eco-efficient solutions, i.e. solutions in which environmental performance can only be improved at higher cost. The overall objective of this thesis was to support decision making in FSCs by developing dedicated decision support models to optimize and re-design FSCs by balancing the economic and environmental criteria. The emphasis is directed towards valorization of product flows by means of closing loops and waste management at a chain level. In line with this overall objective, four research questions were defined, which are addressed in Chapters 2 to 5.
In Chapter 2, the use of MCDM approaches for designing Green Supply Chains (GSCs) is reviewed; GSCs extend traditional supply chains to include activities that minimize the environmental impact of a product throughout its life cycle. A conceptual framework was developed to find relevant publications and categorize papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that the use of MCDM approaches for designing GSCs is a new but emerging research field. Most publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations. Most papers assume all data to be deterministic. Moreover, little attention has been given to minimization of waste in studies on FSCs, and numerous indicators are used to account for eco-efficiency, indicating the lack of standards. Chapter 2, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with respect to supply chains dealing with food production, and with inclusion of uncertainty in parameters.
Environmental concerns and scarcity of resources encourage decision makers in supply chains to consider alternative production options that include preventing the production of waste streams and simultaneously reusing and recycling waste materials. Until now, quantitative modelling approaches on closing loops in FSCs have been rare in the literature. The aim of Chapter 3 was to develop a mathematical model that can be used for quantitative assessment of alternative production options associated with different ways of dealing with waste in FSCs, i.e. prevention, recycling, and disposal of food waste. A multi-objective mixed integer linear programming model was developed to derive a set of eco-efficient solutions corresponding to production planning decisions. The environmental performance of the chain is expressed by an indicator based on exergy analysis, which has the potential to capture other commonly used indicators, such as energy consumption, fuel consumption, and waste generation, in a single value. This simplifies the calculation of the eco-efficient frontier and enables its intuitive graphical representation, which is much easier to communicate to the decision makers. The applicability of the model is demonstrated on a real-life industrial bread supply chain in the Netherlands. The results confirm the findings from the literature that prevention is the best waste management strategy from an environmental perspective. The advantages of using exergy as an indicator to capture the environmental performance is demonstrated by comparing the outcomes with other commonly used indicators of environmental performance. The potential of studying food production planning decision problems in a multi-objective context is illustrated and the applicability of the model in the assessment of alternative production options is demonstrated.
In contrast to closed-loop studies in industry involving discrete parts, in FSCs the value of the final product usually cannot be regained. However, the components used for production, such as organic matter or a growing medium, can be recycled. The aim of Chapter 4 was to reveal the consequences of closing loops in a mushroom supply chain. A multi-objective mixed integer linear programming model was proposed to quantify trade-offs between economic and environmental indicators and to explore alternative recycling technologies quantitatively. The model was developed to re-design the logistical structure and close loops in the mushroom supply chain. It was found that adopting closing loop technologies in industrial mushroom production has the potential to increase the total profitability of the chain by almost 11% and improve the environmental performance by almost 28%. It is concluded that a comprehensive evaluation of recycling technologies and re-designing logistical structures requires quantitative tools that simultaneously optimize managerial decisions at strategic and tactical levels.
Multi-objective optimization models are often developed under the assumption that all information required for model parameterization is known in advance. In practice, however, not all the required information is available in advance because of various sources of uncertainty in FSCs. In Chapter 5, a multi-objective two-stage stochastic programming model was proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in FSCs. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. It is demonstrated that taking uncertainty into account at the production planning phase in an FSC can bring substantial economic and environmental benefits.
The research presented in this thesis contributes to the scientific literature on eco-efficient FSCs by providing decision support models for use by decision makers to assess alternative logistical structures and quantify the economic and environmental implications of closing loop technologies. This thesis shows that technological innovations, which allow for reuse and recycling of waste streams, have the potential to improve the economic and environmental performance of an FSC substantially. The case studies illustrate that it is worthwhile investing in research on technological innovations (and their development) for closing loops in FSCs. The greatest benefits are brought about by using materials to their full potential by valorizing waste streams as much as possible.
p>Designing Green Supply Chains (GSCs) requires complex decision-support models that can deal with multiple dimensions of sustainability while taking into account specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM) approaches can be used to quantify trade-offs between economic, social, and environmental criteria i.e. to identify green production options. The aim of this paper is to review the use of MCDM approaches for designing efficient and effective GSCs. We develop a conceptual framework to find relevant publications and to categorise papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that (1) the use of MCDM approaches for designing GSCs is a rather new but emerging research field, (2) most of the publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations, (3) the majority of papers assume all data to be deterministic, (4) little attention has been given to minimisation of waste, (5) numerous indicators are used to account for eco-efficiency, indicating the lack of standards. This study, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with inclusion of uncertainty in parameters that are associated with GSCs.</p
Designing Green Supply Chains (GSCs) requires complex decision-support models that can deal with multiple dimensions of sustainability while taking into account specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM) approaches can be used to quantify trade-offs between economic, social, and environmental criteria i.e. to identify green production options. The aim of this paper is to review the use of MCDM approaches for designing efficient and effective GSCs. We develop a conceptual framework to find relevant publications and to categorise papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that (1) the use of MCDM approaches for designing GSCs is a rather new but emerging research field, (2) most of the publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations, (3) the majority of papers assume all data to be deterministic, (4) little attention has been given to minimisation of waste, (5) numerous indicators are used to account for eco-efficiency, indicating the lack of standards. This study, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with inclusion of uncertainty in parameters that are associated with GSCs.
Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.
This work presents a mathematical programing formulation for the optimal management of flowback water in shale gas wells considering economic and safety aspects. The proposed formulation accounts for the time-based generation of the flowback water, as well as the options for treatment, storage, reuse, and disposal. The economic objective function is aimed at determining the minimum cost for the fresh water, treatment, storage, disposals and transportation. The safety objective accounts for the risk associated to a failure in the treatment units and its consequence in human deaths. In this regard, the proposed method is able to consider different treatment units with different operating efficiency factors, costs and risks. To carry out the water integration, a recycle and reuse network is proposed. A given scheduling for the completion phases of the wells is required to implement the proposed method. Finally, an example problem is presented to show the applicability of the proposed method.
This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost-benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.
Solid waste management is a challenge for the cities' authorities in developing countries mainly due to the increasing generation of waste, the burden posed on the municipal budget as a result of the high costs associated to its management, the lack of understanding over a diversity of factors that affect the different stages of waste management and linkages necessary to enable the entire handling system functioning. An analysis of literature on the work done and reported mainly in publications from 2005 to 2011, related to waste management in developing countries, showed that few articles give quantitative information. The analysis was conducted in two of the major scientific journals, Waste Management Journal and Waste Management and Research. The objective of this research was to determine the stakeholders' action/behavior that have a role in the waste management process and to analyze influential factors on the system, in more than thirty urban areas in 22 developing countries in 4 continents. A combination of methods was used in this study in order to assess the stakeholders and the factors influencing the performance of waste management in the cities. Data was collected from scientific literature, existing data bases, observations made during visits to urban areas, structured interviews with relevant professionals, exercises provided to participants in workshops and a questionnaire applied to stakeholders. Descriptive and inferential statistic methods were used to draw conclusions. The outcomes of the research are a comprehensive list of stakeholders that are relevant in the waste management systems and a set of factors that reveal the most important causes for the systems' failure. The information provided is very useful when planning, changing or implementing waste management systems in cities.
The management of residues from thermal waste treatment is an integral part of waste management systems. The primary goal of managing incineration residues is to prevent any impact on our health or environment caused by unacceptable particulate, gaseous and/or solute emissions. This paper provides insight into the most important measures for putting this requirement into practice. It also offers an overview of the factors and processes affecting these mitigating measures as well as the short- and long-term behavior of residues from thermal waste treatment under different scenarios. General conditions affecting the emission rate of salts and metals are shown as well as factors relevant to mitigating measures or sources of gaseous emissions.
Waste to Energy (WTE) carries a trade-off between energy generation and the energy spent on collection, transport and treatment. Major performance indicators are cost, Primary Energy Savings (PES), Carbon Footprint (CFP). This presentation analyses the trade-off introducing a new indicator - the Waste Energy Potential Utilisation (WPU). The results indicate that the impact of logistics and energy distribution can be significant, and distributed WTE architectures may be good candidates for optimal solution, subject to further economical and environmental assessment.
A technical and economic review of emerging waste disposal technologies. Intended for a wide audience ranging from engineers and academics to decision-makers in both the public and private sectors, Municipal Solid Waste to Energy Conversion Processes: Economic, Technical, and Renewable Comparisons reviews the current state of the solid waste disposal industry. It details how the proven plasma gasification technology can be used to manage Municipal Solid Waste (MSW) and to generate energy and revenues for local communities in an environmentally safe manner with essentially no wastes. Beginning with an introduction to pyrolysis/gasification and combustion technologies, the book provides many case studies on various waste-to-energy (WTE) technologies and creates an economic and technical baseline from which all current and emerging WTE technologies could be compared and evaluated. Topics include: Pyrolysis/gasification technology, the most suitable and economically viable approach for the management of wastes. •Combustion technology. •Other renewable energy resources including wind and hydroelectric energy. •Plasma economics. •Cash flows as a revenue source for waste solids-to-energy management. •Plant operations, with an independent case study of Eco-Valley plant in Utashinai, Japan Extensive case studies of garbage to liquid fuels, wastes to electricity, and wastes to power ethanol plants illustrate how currently generated MSW and past wastes in landfills can be processed with proven plasma gasification technology to eliminate air and water pollution from landfills.
Basis Economic Cases Logical Approach for Future Progress References
This work presents a multi-period waste management multi-objective optimization, considering economic and environmental issues. The specific behavior of the considered waste management treatments is included in the optimization problem as black-box models based on practical industrial practice computing utility requirements and emissions. To achieve more realistic solutions, the estimation of waste treatment costs and environmental impacts has been explicitly added to the assessment scheme, as well as the constraints of the operating conditions in the treatment units and the fulfillment of environmental regulations for water and air emissions. This framework is applied to an industrial based case study and used to analyze the waste mixing potential. Two main strategies are proposed to tackle the problem using a rigorous mathematical problem formulation. The performance of both strategies is compared in terms of solution quality and computational complexity with the final aim of finding an efficient methodology for posing the heat and waste management integration problem in a future work.
This paper investigates the production of liquid transportation fuels from municipal solid waste (MSW). A comprehensive process synthesis superstructure is utilized that incorporates a novel mathematical model for MSW gasification. The production of liquid products proceeds through a synthesis gas intermediate that can be converted into Fischer–Tropsch hydrocarbons or methanol. The methanol can be converted into either gasoline or olefins, and the olefins may subsequently be converted into gasoline and distillate. Simultaneous heat, power, and water integration is included within the process synthesis framework to minimize utilities costs. A rigorous deterministic global optimization branch-and-bound strategy is utilized to minimize the overall cost of the waste-to-liquids (WTL) refinery and determine the optimal process topology. Several case studies are presented to illustrate the process synthesis framework and the nonconvex mixed-integer nonlinear optimization model presented in this paper. This is the first study that explores the possibility of liquid fuels production from municipal solid waste utilizing a process synthesis approach within a global optimization framework. The results suggest that the production of liquid fuels from MSW is competitive with petroleum-based processes. The effect that the delivered cost of municipal solid waste has on the overall cost of liquids production is also investigated parametrically.
This article presents a general multi-objective mixed-integer linear programming (MILP) optimization model aimed at providing decision support for waste and resources management in industrial networks. The MILP model combines material flow analysis, process models of waste treatments and other industrial processes, life cycle assessment, and mathematical optimization techniques within a unified framework. The optimization is based on a simplified representation of industrial networks that makes use of linear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heating value or heavy metal contamination, are considered explicitly along with potential technologies or process configurations. The systems perspective, including both provision of waste treatment and industrial production, enables constraints imposed upon the systems, e.g. available treatment capacities, to be explicitly considered in the model. The model output is a set of alternative system configurations in terms of distribution of waste and resources that optimize environmental and economic performance. The MILP also enables quantification of the improvement potential compared to a given reference state. Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficient solutions. This information supports the decision making process by revealing the quantified performance of the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key features of the modeling approach are illustrated in a hypothetical case. The optimization model described in this article is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewage sludge in a region in Switzerland.
Over the last decade, utilization of biomasses is highly encouraged to conserve scarce resources, reduce dependency on energy imports as well as protect the environment. Integrated biorefinery emerged as noteworthy concept to integrate several conversion technologies to have more flexibility in product generation with energy self‐sustained and reduce the overall cost of the process. Integrated biorefinery is a processing facility that converts biomass feedstocks into a wide range of value added products via multiple technologies. In this work, a systematic approach for the synthesis and optimization of a sustainable integrated biorefinery which considers economic, environmental, inherent safety, and inherent occupational health performances is presented. Fuzzy optimization approach is adapted to solve four parameters simultaneously as they are often conflicting in process synthesis and optimization of an integrated biorefinery. An integrated palm oil‐based biorefinery case study is solved to demonstrate the proposed approach. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4212–4227, 2013
Ineffective management of municipal solid waste (MSW) may cause degradation of valuable land resources and create long-term environmental and human health problems. A sustainable and efficient waste management strategy is needed to balance the need for development, the quality of human life and the environment. This study aims to synthesis a MSW processing network to produce energy and value-added products for achieving economic and environmental competitiveness. An optimisation model that integrates four major utilisation technologies was incorporated to facilitate a cost-effective processing network. The model is able to predict the best mix of waste treatment technologies, forecast the production of by-product from waste treatment process, estimate the facility capacity, forecast the greenhouse gas (GHG) emission of the system, and eventually generate an optimal cost-effective solution for municipal solid waste management (MSWM). Four scenarios for MSWM were considered to analyse the economic impact of different waste utilisation alternatives: i) the business as usual (BAU) scenario as a baseline study, ii) the waste-to-energy (WTE) scenario, iii) the waste-to-recycling (WTR) scenario, and iv) the mixed technology (MIXTECH) scenario. The MIXTECH scenario was able to provide the best mix of waste utilisation technologies. The optimal waste allocation in terms of percentage involved landfill gas recovery system (LFGRS) (14%), mass burn incineration (3%), material recycling facilities (MRF) (56%), and composting (27%). The optimal scenario would be able to achieve the renewable energy (RE) target, achieve the recycling target and promote composting as the waste reduction alternative for the region being studied. Sensitivity analyses were conducted for the optimal or MIXTECH scenario to examine the effect of the RE target and GHG emission reduction target with respect to the system cost and waste allocation to each technology. The proposed mixed integer linear programming (MILP) model was applied for Iskandar Malaysia (IM) as a case study.
This paper presents a generic gasifier model towards the production of liquid fuels using Municipal Solid Waste (MSW) as a feedstock. The MSW gasification has been divided into three zones: pyrolysis, oxidation, and reduction. The pyrolysis zone has been mathematically modeled with an optimization based monomer model. Then, the pyrolysis, oxidation, and reduction zones are defined with different chemical reactions and equations in which some extents of these reactions are not known a priori. Using a nonlinear parameter estimation approach, the unknown gasification parameters are obtained to match the experimental gasification results in the best possible way. The results suggest that, a generic MSW mathematical model can be obtained in which the average error is 8.75%. The mathematical model of the MSW gasifier is of major importance since it can be a part of a process superstructure towards the production of liquid transportation fuels.
A new approach for the incorporation of safety criteria into the selection, location, and sizing of a biorefinery is introduced. In addition to the techno-economic factors, risk metrics are used in the decision-making process by considering the cumulative risk associated with key stages of the life cycle of a biorefinery that includes biomass storage and transportation, process conversion into biofuels or bioproducts, and product storage. The fixed cost of the process along with the operating costs for transportation and processing as well as the value of the product are included. An optimization formulation is developed based on a superstructure that embeds potential supply chains of interest. The optimization program establishes the tradeoffs between cost and safety issues in the form of Pareto curves. A case study on bio-hydrogen production is solved to illustrate the merits of the proposed approach. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2427–2434, 2013
Biorefineries appear to be a viable solution to replace traditional fossil fuel refineries, but their implementation requires the exploration of several aspects, including feedstock selection, processing routes, products, harvesting sites, processing and markets, as well as numerous other sustainability criteria. The optimal solution to these problems is not immediately obvious. Therefore, this study presents an optimization model to design and plan sustainable biorefinery supply chains that considers numerous relevant issues. These issues include the multiple available biomass feedstocks at various harvesting sites, the availability and seasonality of biomass resources, different potential geographical locations for processing plants that produce multiple products using diverse production technologies, economies of scale for the production technologies, demands and prices of multiple products in each market, locations of storage facilities and a number of transportation modes between the supply chain components. Sustainability considerations are incorporated into the proposed model by including simultaneous economic, environmental and social performance data in the evaluation of the supply chain designs. The problem was formulated as a multi-objective, multi-period, mixed-integer linear program that seeks to maximize the profit of the supply chain, minimize its environmental impact and maximize the number of jobs generated by its implementation. The environmental impact was measured by the Eco-indicator99 according to the life-cycle assessment technique, and the social objective was quantified by the number of jobs generated. The Pareto-optimal solutions were obtained using the ε-constraint method. To illustrate the capabilities of the proposed multi-site system model, a case study was presented that addresses the optimal design and planning of a biorefinery supply chain to fulfill the expected ethanol and biodiesel demands in Mexico. The results indicate that cost-effective and sustainable solutions can be obtained that satisfy Mexican demand by choosing feedstocks that are available year-round and do not significantly adversely impact the environment. Furthermore, the number of jobs generated by implementing the biorefinery supply chain would have a significant social impact.
Four strategies can be used to achieve safety in chemical processes: inherent, passive, active and procedural. However, the strategy that offers the best results is the inherent safety approach, especially if it is applied during the initial stages of a project. Inherently Safer Design (ISD) permanently eliminates or reduces hazards, and thus avoids or diminishes the consequences of incidents. ISD can be applied using four strategies: substitution, minimization, moderation and simplification. In this paper, we propose a methodology that combines ISD strategies with Quantitative Risk Assessment (QRA) to optimize the design of storage installations. As 17% of major accidents in the chemical industry occur during the storage process and cause significant losses, it is essential to improve safety in such installations. The proposed method applies QRA to estimate the risk associated with a specific design. The design can then be compared to others to determine which is inherently safer. The risk analysis may incorporate complex phenomena such as the domino effect and possible impacts on vulnerable material and human elements. The methodology was applied to the San Juanico tragedy that occurred in Mexico in 1984.
Construction and demolition waste (C&DW) constitutes a priority waste stream due to the large amounts generated and its high potential for reuse and recycling. Specific legislation has been developed for this type of waste at European, national and regional level. In order to fulfill this new legislation, it is necessary to settle down a network of recycling facilities for C&DW (processing plants (PP) and/or transfer stations (TS)). The aim of this paper is to identify the locations and capacity of the transfer stations and processing plants and the corresponding distribution network by means of an optimization model that minimizes: (1) medium transportation distance and (2) total costs (installation, operation and landfill). The model is formulated as Mixed Integer Lineal Programming (MILP) problem where the binary variables represent the presence or not of management facilities at a location. General Algebraic Modeling System (GAMS) is used as a modeling system for the resolution of the mathematical programs. The model has been applied to a real-life case in Cantabria, a northern Spanish region. Two approaches have been considered: (a) the region as a whole area and (b) the region divided in five geographical areas. The results show that when the total costs are minimized, the number of facilities decreases, and when the medium transport distance is minimized, the number of facilities increases. The proposed final network includes location of three PP and two TS, each one of these facilities located in one of the five geographical areas. The optimal results also determine the municipality where each facility must be located, the capacity of them and the distribution network.
A large volume of the waste produced across the world is composed of polymers from plastic wastes such as polyethylene (HDPE or LDPE), polypropylene (PP), and polyethylene terephthalate (PET) amongst others. For years, researchers have been looking for various ways to overcome the problems of such large quantities of waste plastics. On the other hand, carbon nanotubes (CNTs) are materials with extraordinary physical and chemical properties which often have energy- and resource-intensive production processes. In recent years, some researchers have suggested the idea of using plastic polymers as the carbonaceous feed of CNT production. The studies undertaking such a feat are rather scattered. This review paper is the first of its kind reporting, compiling and reviewing these various processes. The production of multi-walled carbon nanotubes (MWCNTs) from plastic polymers is seen to be satisfactorily achievable through a variety of different catalytic and thermal methods in autoclaves, quartz tube reactors, muffle furnaces, fluidized beds, amongst others. Still, much work needs to be done regarding the further investigation of the numerous parameters influencing production yields and qualities. For example, differences in results are seen in varying operating conditions, experimental setups, catalysts, and virgin or waste plastics being used as feeds. The area of producing CNTs from plastic wastes is still very open for further research, and seems as a promising route for both waste reduction, and the synthesis of value-added products such as carbon nanotubes.
The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.
Goal of the work is to present a simplified methodology to optimize an integrated solid waste management system. The methodology performs two optimizations, namely: i) minimization of the total cost of the MSW system and ii) minimization of the equivalent carbon dioxide emissions (CO2e) generated by the whole system. The methodology is modeled via non-linear mathematical equations, uses 32 decision variables and does not require complex LCA databases. The proposed model optimally allocates eight MSW components (paper, cardboard, plastics, metals, glass, food wastes, yard wastes and other wastes) to four MSW management technologies (incineration, composting, anaerobic digestion, and landfilling) after source separation of recyclables has taken place. The Region of East-Macedonia and Thrace in Greece was selected as a case study. Results showed that there is a trade off between cost and CO2e emissions. Incineration and composting were favored as the principal treatment technologies, while landfilling was always the least desirable management technology under both objective functions. The recycling participation rate significantly affected all optimum scenarios.
Products of a hydrocarbon fire accident have both chronic and acute health effects. They cause respiratory issues to lung cancer. While fire is the most frequent phenomenon among the offshore accidents, predicting the contaminants’ concentration and their behaviour are key issues. Safety measures design, such as ventilation and emergency routes based only on predicted contaminants’ concentration seems not to be the best approach. In a combustion process, various harmful substances are produced and their concentration cannot be added. The time duration that any individual spends in different locations of an offshore installation also varies significantly. A risk-based approach considers the duration a person is exposed to contaminants at various locations and also evaluates the hazardous impacts. A risk-based approach has also an additivity characteristic which helps to assess overall risk.
Through the current study, an approach is proposed to be used for risk assessment of combustion products dispersion phenomenon in a confined or semi-confined facility. Considering CO, NO2 and CH4 as the contaminants of concern, the dispersion of the substances over the layout of the facility after a LNG fire is modeled. Considering different exposure times for three major parts of the facility including the processing area, office area and the accommodation module, the risk contours of CO, NO2 and CH4 over the entire facility are developed. The additivity characteristic of the risk-based approach was used to calculate the overall risk. The proposed approach helps to better design safety measures to minimize the impacts and effective emergency evacuation planning.
Introduction:
In this paper, a literature study on risk analysis systems for the transport of hazardous materials was conducted.
Results:
The insights that resulted from this literature review have led to the development of a refined approach to map the risk of hazmat transport in Flanders based on historical accident data. The proposed framework allows setting up an overall risk map for hazmat transport by different transport modes. Additionally, a methodology to calculate a local accident risk, which takes local infrastructure parameters and accident data into account, is being introduced. In the presented framework one of the general principles is that the risk of a catastrophic hazmat incident can be divided into two parts, which can both be validated on the basis of accident data: (a) the calculation of the general probability of the occurrence of an accident based on international accident data of transport of hazardous materials--this is the basis for the global risk map, and (b) the calculation of the local probability of the occurrence of an accident based on accident data and infrastructure parameters of the complete available freight transport in Flanders--this is the basis for the local risk map. The ratio between these two results in a locality parameter, which represents the local specific circumstances that can lead to an accident.
Conclusions:
This evaluation framework makes it possible to estimate the risks of hazmat transport along a specific route for transport by road, rail, inland navigation and even pipelines.
This paper presents a systematic approach for the optimal production planning and facility placement of a biorefinery. A structural representation is first developed to include sources of biomass feedstock, distributed preprocessing hubs, and centralized processing facilities to produce desired products and byproducts. An optimization formulation is developed to determine the optimal supply chain, size, operational strategies, and location of the biorefinery and preprocessing hub facilities. The model considers simultaneously the optimal selection of different configurations considering the specific location configuration (centralized and/or distributed), selection of biomass, and processing facilities to determine the one with the maximum overall net profit. The objective function considers the overall sales and the costs for the feedstocks, transportation costs, capital costs for the facilities, and the operational costs for the facilities. The model also considers nonlinear economy-of-scale behavior of the capital-cost functions that are reformulated using disjunctive models to yield convex relationships to guarantee a global optimal solution. The proposed model was applied to two case studies.
Risk management has become imperative for today's complex supply chains. Most approaches reported in the literature have been ad-hoc and specific to certain risks; a general and comprehensive approach is lacking. To address this, we present a structured methodology for risk identification. Supply chain networks are in many ways similar to chemical plants, therefore well-established methods and concepts from chemical process risk management can be adapted to supply chains. Drawing from this analogy, we propose to represent supply chain structure and operations using flow and work-flow diagrams, equivalent to process flow diagrams (PFDs) and operating procedures. Following the HAZard and OPerability (HAZOP) analysis method common in process safety, risk identification can be performed by systematically generating deviations in different supply chain parameters and identifying their possible causes, consequences, safeguards, and mitigating actions. The application and benefits of the proposed approach are demonstrated using a refinery supply chain case study. © 2009 American Institute of Chemical Engineers AIChE J, 2009
In this work, we present a novel framework that comprises four stages of process modeling and multiobjective decision-makings considering monetary and non-monetary aspects. Four stages in early design phases are considered and characterized by the available information for process modeling and assessment. Appropriate modeling methods, and evaluation indicators for economy, life-cycle environmental impacts, EHS hazard and technical aspects are selected for each defined stage. The framework is demonstrated in the case study of methyl methacylrate (MMA) process design. 17 reaction routes are screened step-by-step up to generating optimal flowsheet of a promising route. As a validation, evaluation profiles of 6 routes are compared over stages to identify key factors that should be well estimated in earlier stages.
This article addresses the optimal design and planning of cellulosic ethanol supply chains under economic, environmental, and social objectives. The economic objective is measured by the total annualized cost, the environmental objective is measured by the life cycle greenhouse gas emissions, and the social objective is measured by the number of accrued local jobs. A multiobjective mixed-integer linear programming (mo-MILP) model is developed that accounts for major characteristics of cellulosic ethanol supply chains, including supply seasonality and geographical diversity, biomass degradation, feedstock density, diverse conversion pathways and byproducts, infrastructure compatibility, demand distribution, regional economy, and government incentives. Aspen Plus models for biorefineries with different feedstocks and conversion pathways are built to provide detailed techno-economic and emission analysis results for the mo-MILP model, which simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The mo-MILP problem is solved with an ε-constraint method; and the resulting Pareto-optimal curves reveal the tradeoff between the economic, environmental, and social dimensions of the sustainable biofuel supply chains. The proposed approach is illustrated through two case studies for the state of Illinois. © 2011 American Institute of Chemical Engineers AIChE J, 2012
A framework for risk assessment due to offsite transportation of hazardous wastes is designed based on the type of event that can be triggered from an accident of a hazardous waste carrier. The objective of this study is to design a framework for computing the risk to population associated with offsite transportation of inflammable and volatile wastes. The framework is based on traditional definition of risk and is designed for conditions where accident databases are not available. The probability based variable in risk assessment framework is substituted by a composite accident index proposed in this study. The framework computes the impacts due to a volatile cloud explosion based on TNO Multi-energy model. The methodology also estimates the vulnerable population in terms of disability adjusted life years (DALY) which takes into consideration the demographic profile of the population and the degree of injury on mortality and morbidity sustained. The methodology is illustrated using a case study of a pharmaceutical industry in the Kolkata metropolitan area.
We report on an actual application of the ELECTRE III decision-aid in the context of choosing a solid waste management system in the Oulu region, Finland, in 1993. The Electre III method proved useful, especially when dealing with environmental problems involving many decision-makers, and in cases where the outcomes of the various alternatives remain to some degree uncertain. One of the main conclusions of our study is that all the proper landfill capacity available in the planning region should be used up. In addition, the energy potential of waste should be utilized within the region. Therefore, the solution recommended for a solid waste management system was intermediate landfilling, composting and RFD-combustion. The decision-makers commented positively on the method used and were satisfied with the options recommended. The scheme will be implemented for use from the beginning of the year 1995.
Despite the relative recent move towards inherent safe materials, the relentless drive of consumerism requires increased quantities of dangerous goods to be manufactured, transported, stored and used year on year. The safety and effectiveness of road transport systems is to be considered a strategic goal in particular in those countries, like Italy, in which 80% of goods are transported by this means. In this paper, we face the risk from dangerous good transport by presenting a site-oriented framework for risk assessment and developing a theoretical approach for emergency planning and optimisation. In the first step, we collected field data on a pilot highway and developed a database useful to allow a realistic evaluation of the accident frequency on a given route, by means of multivariate statistical analysis. To this end, we considered both inherent factors (such as tunnels, bend radii, height gradient, slope etc), meteorological factors, and traffic factors (traffic frequency of tank truck, dangerous good truck etc.) suitable to modify the standard national accident frequency. By applying the results to a pilot area, referring to flammable and explosive scenarios, we performed a risk assessment sensitive to route features and population exposed. The results show that the risk associated to the transport of hazardous materials, in some highway stretches, can be at the boundary of the acceptability level of risk set down by the well known F/N curves established in the Netherlands. On this basis, in the subsequent step, we developed a theoretical approach, based on the graph theory, to plan optimal emergency actions. The effectiveness of an emergency planning can normally be evaluated in term of system quickness and reliability. As a case study, we applied the developed approach to identify optimal consistency and localisation in the pilot area of ‘prompt action vehicles’, properly equipped, quick to move and ready for every eventuality. Applying this method results in an unambiguous and consistent selection criterion that allows reduction of intervention time, in connection with technical and economic optimisation of emergency equipment.
This paper examines the determinants of recycling behaviour among 200 university students from the perspective of the theory of planned behaviour (TPB). Data was analysed using Structural Equation Modelling technique. Findings indicate that environmental awareness was significantly related to attitude towards recycling, whilst attitude and social norms had significant impact on recycling behaviour. However, convenience and cost of recycling were not significant reasons for recycling. The study has enhanced the understanding of the determinants of recycling behaviour and has implications for schools and governmental agencies in educating and encouraging positive recycling behaviour. It also confirms the appropriateness of the TPB in examining studies of this nature. Further suggestions for future research are offered.
The present work deals with the application of biotechnology for the mobilization of metals from different solid wastes: end of life industrial catalysts, heavy metal contaminated marine sediments and fluorescent powders coming from a cathode ray tube glass recycling process. Performed experiments were aimed at assessing the performance of acidophilic chemoautotrophic Fe/S-oxidizing bacteria for such different solid matrices, also focusing on the effect of solid concentration and of different substrata. The achieved results have evidenced that metal solubilization seems to be strongly influenced by the metal speciation and partitioning in the solid matrix. No biological effect was observed for Ni, Zn, As, Cr mobilization from marine sediments (34%, 44%, 15%, 10% yields, respectively) due to metal partitioning. On the other hand, for spent refinery catalysts (Ni, V, Mo extractions of 83%, 90% and 40%, respectively) and fluorescent powders (Zn and Y extraction of 55% and 70%, respectively), the improvement in metal extraction observed in the presence of a microbial activity confirms the key role of Fe/S oxidizing bacteria and ferrous iron. A negative effect of solid concentration was in general observed on bioleaching performances, due to the toxicity of dissolved metals and/or to the solid organic component.
This paper reviews several models developed to support decision making in municipal solid waste management (MSWM). The concepts underlying sustainable MSWM models can be divided into two categories: one incorporates social factors into decision making methods, and the other includes public participation in the decision-making process. The public is only apprised or takes part in discussion, and has little effect on decision making in most research efforts. Few studies have considered public participation in the decision-making process, and the methods have sought to strike a compromise between concerned criteria, not between stakeholders. However, the source of the conflict arises from the stakeholders' complex web of value. Such conflict affects the feasibility of implementing any decision. The purpose of this study is to develop a sustainable decision making model for MSWM to overcome these shortcomings. The proposed model combines multicriteria decision making (MCDM) and a consensus analysis model (CAM). The CAM is built up to aid in decision-making when MCDM methods are utilized and, subsequently, a novel sustainable decision making model for MSWM is developed. The main feature of CAM is the assessment of the degree of consensus between stakeholders for particular alternatives. A case study for food waste management in Taiwan is presented to demonstrate the practicality of this model.
The purpose of this paper is to review the types of models that are currently being used in the area of municipal waste management and to highlight some major shortcomings of these models. Most of the municipal waste models identified in the literature are decision support models and for the purposes of this research, are divided into three categories-those based on cost benefit analysis, those based on life cycle assessment and those based on multicriteria decision making. Shortcomings of current waste management models include that they are concerned with refinements of the evaluation steps (e.g. stage four of AHP or the improvement of weight allocations in ELECTRE) rather than addressing the decision making process itself. In addition, while many models recognise that for a waste management model to be sustainable, it must consider environmental, economic and social aspects, no model examined considered all three aspects together in the application of the model.
Guidelines for Use of Vapor Cloud Dispersion Models
- Aiche Ccps
AICHE/CCPS. Guidelines for Use of Vapor Cloud Dispersion Models. New York: American Institute of Chemical Engineers, 1996.
Mexican Ministry of Transportation and Communications Available at: http://aplicaciones4.sct.gob.mx/sibuac_internet/ ControllerUI?action5cmdEscogeRuta, accessed
- Sct
SCT. Mexican Ministry of Transportation and Communications.
2013. Available at: http://aplicaciones4.sct.gob.mx/sibuac_internet/
ControllerUI?action5cmdEscogeRuta, accessed March 20, 2014.
Chemical Process Safety Fundamentals with Applications
- Da Crowl
- Jf Louvar
Crowl DA, Louvar JF. Chemical Process Safety Fundamentals with
Applications, 3rd ed. Upper Saddle River, New Jersey: Prentice Hall
PTR, 2011.
Waste-to-energy (WTE) network synthesis for municipal solid waste (MSW) Energy Convers Manag
- Wpq Ng
- Hl Lam
- Ps Varbanov
- Jj Klemes
Ng WPQ, Lam HL, Varbanov PS, Klemes JJ. Waste-to-energy
(WTE) network synthesis for municipal solid waste (MSW). Energy
Convers Manag. 2014;85:866–874.
Aluminium recycling in the United States in 2000. US Department of the Interior
- Pa Plunkert
Plunkert PA. Aluminium recycling in the United States in 2000. US
Department of the Interior, US Geological Survey, Washington, D.C.
2006.
Combustion products toxicity risk assessment in an offshore installation. Process Saf Environ Protection
- M Dadashzadeh
- F Khan
- R Abbassi
- K Hawboldt
Dadashzadeh M, Khan F, Abbassi R, Hawboldt K. Combustion products toxicity risk assessment in an offshore installation. Process Saf
Environ Protection. In press. doi:10.1016/j.psep.2013.07.001.
Information for States and Municipalities
- Inegi
- Mexican
INEGI. Mexican Information for States and Municipalities. 2013.
Available at: http://www3.inegi.org.mx/sistemas/mexicocifras/default.
aspx?e516, accessed March 20, 2014.