Search

This paper examines CO 2 response to business cycles of six large CO 2 - emitting countries in Asia and the Middle East, namely China, India, Japan, Iran, Saudi Arabia, and South Korea by using a Markov-switching autoregressive models. Emissions are cyclically more volatile than GDP in a typical country, except for Iran. It is observed that emissions are procyclical in all studied countries except for India, but the elasticity of the emission with respect to GDP significantly depends on regimes. In Japan and South Korea, elasticity of CO 2 emissions with respect to GDP during expansions is significantly larger than during recessions. In Iran and Saudi Arabia, elasticity of CO 2 emissions with respect to GDP is significantly smaller than 1, but the CO 2 emissions response to GDP during recessions is significantly larger than during expansions. In China, elasticity of CO 2 emissions to GDP is significantly larger than 1 during recessions and normal and CO 2 emissions response to GDP during recessions is significantly larger than during expansions. These results have implications for environmental policy makers; the optimal response of pollution-abatement costs in Japan and South Korea should be high (low) during expansions (recessions) and in China, Iran and Saudi Arabia should be low (high) during expansions (recessions) after releasing a positive productivity shock. [ABSTRACT FROM AUTHOR]

In reverse supply chains, acquisition price strategy provided by manufacturers plays an essential role in collecting used products. On the other hand, owing to the fact that the acquisition price contributes to the improvement of the environmental sustainability, it can influence the purchasing behaviors of eco-friendly customers. Thus, acquisition price strategy not only can positively affect the amount of returned products but also can positively affect the market demand. This study integrates bilateral effects of the acquisition price to analyze the performance of a sustainable closed-loop supply chain (CLSC) by introducing a dual-function acquisition price. This paper also contributes to the sustainable CLSC literature by proposing an analytical coordination mechanism to coordinate the dual-function acquisition price as an environmental sustainability and corporate social responsibility (CSR) as a social sustainability. Motivated by a real case of dairy industry, the bilateral effects of the acquisition price on both reverse and forward channels are considered through its dual functionality. In the sustainable CLSC consisting of two competitive manufacturers and one retailer, the manufacturers compete with each other on the dual-function acquisition price offered to the customers. Moreover, to facilitate the collection process, the manufacturers encourage the retailer to do the collection process by offering him a credit time scheme. Besides the collection process, the retailer invests in the CSR as social sustainability to boost the market share. At first, we use a manufacturer-Stackelberg game to model the problem under decentralized structure where each member individually optimizes its own profitability. Afterward, the problem is formulated under centralized structure where the decision variables are determined from CLSC viewpoint. Then, a compensation-based wholesale price contract is developed to coordinate the competitive CLSC under coordinated model. Using the data of the case study, the results demonstrate that the proposed contract enhances the whole CLSC and all members' profitability, the manufacturers' dual-function acquisition price, and the retailer's CSR investment. Therefore, the developed contract can improve the performance of the competitive CLSC from environmental, social, and economic viewpoints. • This study is motivated by a real case study of milk industry in Iran. • A dual-function acquisition price is developed in a closed-loop supply chain. • A competitive sustainable closed-loop supply chain is investigated. • Coordination of acquisition price and corporate social responsibility is proposed. • Compensation-based wholesale price contract is efficient from sustainability view. [ABSTRACT FROM AUTHOR]

The general policy of the European Union in reducing greenhouse gas emissions is such that the increased average global temperature is kept below 2 °C. Many countries are looking for more effective solutions and methods to reduce carbon emissions. There are effective factors in the scheduling passenger and freight trains in the inter-city rail transport industry such as number of trains requested at the station, the number of stops, delays and waiting times for trains at the station which lead to increased fossil fuel consumption and carbon emission. In this paper, we want to present a new mixed integer non-linear model that can choose the best schedule for movement of passenger and freight shuttle trains on a single-line route of the railway network with the least environmental pollution. In this model, the carbon emission factor is based on the weight and prioritization of passenger and freight trains. Also, the average number of demands for using trains at a station and the number of planned or non-planned stops and delays at the middle stations are considered. Also, the proposed model selects the best plan for moving trains with the lowest carbon emissions caused by fuel consumption. To validate the proposed model, a case study of a crowded passenger and freight route of an inter-city railway network in Iran will be solved. We solve the real studied problem using the GAMS v24.9.1 optimization software with BARON solver. Finally, after sensitivity analysis of the results, we demonstrate the convenient and efficient performance of the same model in solving the raised problems in an applied manner. Image 10162 • A new model for reducing Carbon emissions through optimal scheduling of trains is developed. • We apply the carbon emission factor based on the weight and prioritization of passenger and freight trains. • We consider the number of planned and non-planned stops, delays, and waiting times of trains. • A real case study is applied for validating the proposed model. [ABSTRACT FROM AUTHOR]

This paper introduces a framework comprising Geographic Information System (GIS) techniques and fuzzy Multi-Criteria Decision-Making (MCDM) methods for application in landfill site selection problem. The developed methodology is utilized in an environmentally critical area related to Mahallat city located in the northwest of Iran. In this process, fourteen effective parameters related to sustainability of the location of landfills are identified and categorized into three groups including environmental, economic, and social criteria. First, criteria weights are obtained by applying the group fuzzy Best-Worst Method (BWM) and then suitability maps are generated based on GIS analysis. From the spatial analysis, eleven potential sites are identified as the most suitable alternatives. These sites are then analyzed and ranked using group fuzzy MULTIMOORA method. This study is different from the previous researches applied the GIS-MCDM approach, in that group fuzzy BWM for weighting criteria is more reliable compared to the other common methods. The group fuzzy MULTIMOORA method, and its three subordinate approaches, select a same candidate, "Site A8" a region near urban area of Mahallat, as the most suitable location for disposing municipal solid waste. Image 1 • A hybrid approach to tackle a sustainable landfill site selection problem is suggested. • The fuzzy group BWM-MULTIMOORA for criteria weighting and alternatives ranking is used. • A GIS tool, i.e., ARCGIS10.5 software, to obtain suitability maps for landfill sites is employed. • The candidate locations for eco-friendly landfilling in Mahallat, Iran are evaluated. • The criteria of the problem are classified as environmental, economic, and social groups. [ABSTRACT FROM AUTHOR]

The demand for bioethanol has increased owing to the growing environmental and social concerns. Designing an efficient Bioethanol Supply Chain (BSC) is a precondition for commercializing the bioethanol production. In this regard, this paper proposes a comprehensive Decision Support Tool (DST) integrating Artificial Neural Network (ANN), mathematical modeling, and solution approach to carefully design and optimize a sustainable second-generation BSC while considering economic, environmental, and social aspects. A multi-objective mixed-integer linear programming model is developed for the strategic and tactical design of BSC in which the bioethanol demand is predicted using an ANN model. To solve the proposed multi-objective model, a hybrid approach based on Best-Worst Method (BWM) and Torabi-Hassini (TH) approach is proposed to find the most preferred solution regarding the decision maker's preference towards the objective functions. The applicability of the proposed DST is demonstrated through assessing the impact of two alternative BSC expansion policies on a real case study in Iran. The results demonstrate that adapting an appropriate ethanol distribution policy over a planning horizon could result in a 33% reduction in total costs. Moreover, it is suggested that a 10% increase in the total costs can be beneficial from environmental and social perspectives. • Developed a comprehensive Decision Support Tool (DST) for the design of sustainable Bioethanol Supply Chain (BSC). • Integrated BWM and TH methods for optimizing the BSC considering the decision maker's preference and priorities. • Used the proposed DST to two alternative policies for the establishment of BSC in a national scale. • Provided managerial insights and discussed policy implications. [ABSTRACT FROM AUTHOR]

With increasing population, urbanization and economic development, especially in developing countries, waste generation is increasing sharply. Traditional waste disposal methods bring many problems, such as air pollution, groundwater contamination, soil contamination and greenhouse gas emissions, and endanger the infrastructure of communities. The optimal waste management reduces waste production, social and environmental problems associated with waste and increases energy production and useful materials. In this paper, a multi-objective mixed integer linear programming (MILP) model with the aim of optimizing total costs and risk objectives is developed for designing a municipal solid waste management (MSWM) network. The economic and environmental aspects are considered in the proposed model. To verify and validate the proposed model, a real case study in Qazvin province of Iran is conducted. To solve the multi-objective model, the ε-constraint method is utilized. The obtained results illustrate that the proposed model is able to design the integrated MSWM network trading off between total costs and risk attitude according to decision maker preferences. • Traditional waste disposal methods bring many environmental and social problems. • Developing a multi-objective MILP model for designing a municipal solid waste management (MSWM) network. • Considering the economic and environmental aspects in the proposed model. • Verification and validation of the proposed model through applying it in a real case study in Qazvin province of Iran. • Utilizing the ε-constraint method to solve the proposed multi-objective model. [ABSTRACT FROM AUTHOR]

The absence or lack of effective stakeholder engagement during project life cycle, especially at the earlier stages of planning and implementation often negatively impacts the expected performance of projects. These coupled consequences of the lack of contextual knowledge from the stakeholders as well as lack of their support in the field necessitates effective stakeholder engagement. However, this integration faces challenges such as limitations of project resources and conflicting interests of the stakeholders. In this sense, project resources can be allocated based on the priorities of the fields of conflicts to facilitate stakeholder engagement of the projects. The goal of this paper is to provide a framework to enhance effectiveness of the stakeholder engagement in projects by systematically ranking the potential conflicts while combining the viewpoints of stakeholders and project management team. For this purpose, we draw on stakeholder theory, value-based management, matrix-based dependency modeling, and Total Quality Management to develop a stakeholder engagement framework while considering fuzzy inputs for reflecting the ambiguities at the project life cycle. The proposed approach is then applied to plan stakeholder engagement in case of a green building project in Iran. Practically, application of the proposed framework facilitates stakeholder engagement for project managers in line with sustainable goals through early assessment of the fields of potential conflicts of interests. • Developing the sustainability paradigm by integrating various theories and concepts. • Extending the literature of stakeholder engagement in projects. • Integrating stakeholders' and project decision-makers' viewpoints into decisions. • Prioritizing stakeholder engagement actions by assessing their conflicting interests. • Proposing and implementing a quantitative approach to organize steering committees in projects. [ABSTRACT FROM AUTHOR]

In recent years, reverse logistics have attracted many attentions due to many reasons, such as extension of new environmental laws, development of social responsibility, and economic interests. Reduction in natural resources and raw material reserves, increasing production costs, and the problems caused by an industrial waste landfill and consumer goods have also increased the focus on reverse logistics over the past decade. This paper proposes a municipal solid waste management network in order to minimize different costs. We develop a bi-level mixed integer linear programming model. The lower-level involves location and establishment costs of solid waste collection stations, and the upper-level includes the allocation of waste to the various centers. In order to deal with uncertainty in the amount of collected solid waste, we need to take a scenario-based robust optimization approach into account. The proposed model is evaluated using a case study in Babol, Mazandaran province, Iran. The results indicate that the collection stations are selected in regions that have less distance from their covered regions which leads to the optimal flow of the wastes/products. The proposed robust optimization approach ensures less sensitivity to model solutions for the provided scenarios. In addition, considering hierarchy in this model leads to a more appropriate analysis compared to when a multi-objective model is used. [ABSTRACT FROM AUTHOR]

Particleboard is one of the non-structural wood-based composites developed in the late 1950s in Iran to utilize agricultural and industrial wood residues. Since there was no published document about its Life Cycle Inventory in Iran, the aim of this study was to document the life cycle inventory data from the particleboard manufacturing in the second hand lines in Iran. The study covers the energy consumption and environmental impacts of raw materials and processes during particleboard production. In order to identify the main hotspots and characterize the production process, impact categories were considered using CML methodology and cumulative exergy demand (CExD) indicator. The results revealed that the board shaping subsystem was the main contributor to the most of impact categories. The main hotspot for resin production was known as Urea-formaldehyde (UF). Electricity was the main hotspot in acidification (AC) and ozone layer depletion (OLD) impact categories, while transportation and production process were the main hotspots in marine aquatic ecotoxicity (ME) and photochemical oxidation (PO) impact categories, respectively. Moreover, rotary dryer, hot press, flaker and hammer mill, vacuum pump and diesel fuel were the most effective sectors in the emissions of the production process. Results for substitution of natural gas showed that, except some impact categories, the use of alternative source of thermal energy such as wood residues could improve emissions from the manufacturing process. [ABSTRACT FROM AUTHOR]

This study deals with the interface between energy consumption and its related emissions in the manufacturing of one cubic meter medium density fiberboard (MDF) in Iran and provides a comprehensive life cycle inventory (LCI) data for production process. The study was developed following the methodological guidelines of ISO 14040. Inventories data for a gate-to-gate assessment of MDF manufacturing were collected by on-site surveys. Ten impact categories including of: Abiotic depletion (AD), Acidification (AC), Eutrophication (EP), Global warming (GW), Ozone layer depletion (OLD), Fresh water aquatic ecotoxicity (FE), Marine aquatic ecotoxicity (ME), Human toxicity (HT), Terrestrial ecotoxicity (TE) and Photochemical oxidation (PO) in three subsystem of manufacturing process were assessed. The subsystem of fiber preparation was the major contributor to the environmental impacts. Urea-formaldehyde (UF) resin production was identified as the main hotspot, except in AD, AC, OLD and PO impacts that natural gas, electricity, transport and production process were the main hotspots, respectively. Moreover, Tube dryer, MDF saw and hogger were the most effective sectors in the emissions of production process. Results for substitution of natural gas showed that except in some impacts categories, use of alternative source of thermal energy such as wood residue could improve emissions from manufacturing. [ABSTRACT FROM AUTHOR]