Equilibrium Strategy Based Recycling Facility Site Selection towards Mitigating Coal Gangue Contamination

Jiuping Xu, Lurong Fan, Chengwei Lv
2017 Sustainability  
Environmental pollution caused by coal gangue has been a significant challenge for sustainable development; thus, many coal gangue reduction approaches have been proposed in recent years. In particular, coal gangue facility (CGF) construction has been considered as an efficient method for the control and recycling of coal gangue. Meanwhile, the identification and selection of suitable CGF sites is a fundamental task for the government. Therefore, based on the equilibrium strategy, a site
more » ... tegy, a site selection approach under a fuzzy environment is developed to mitigate coal gangue contamination, which integrates a geographical information system (GIS) technique and a bi-level model to identify candidate CGF sites and to select the most suitable one. In this situation, the GIS technique used to identify potential feasible sites is able to integrate a great deal of geographical data to fit with practical circumstances; the bi-level model used to screen the appropriate site can reasonably deal with the conflicts between the local authority and the colliery. Moreover, a Karush-Kuhn-Tucker (KKT) condition-based approach is used to find an optimal solution, and a case study is given to demonstrate the effectiveness of the proposed method. The results across different scenarios show that appropriate site selection can achieve coal gangue reduction targets and that a suitable excess stack level can realize an environmental-economic equilibrium. Finally, some propositions and management recommendations are given. be used to produce glass ceramics with coal gangue accounting for 70% of the starting material [17] . Wang et al. [18] proposed a new type of autoclaved aerated concrete using coal gangue. In addition, coal gangue can also be used in the cement industry to replace clay as a raw material [19] . Further, governments and agencies around the world have developed policies and laws to mitigate the harmful influence of gangue piles, such as the Chinese Management Measures for the Comprehensive Utilization of Coal Gangue, the German's Dual Recovery System (DSD) Mode and the Pollution Prevention Law of the United States. Though the undesirable impacts of gangue piles has been alleviated somewhat through the use of recycling technologies and government policies, the coal gangue utilization rate is still less than 15% in China [20] . In addition, regardless of these policies, the environmental problems caused by coal gangue are still serious [21] [22] [23] . Therefore, it is necessary to determine other feasible methods for dealing with coal gangue. Constructing a coal gangue facility (CGF) in coal fields based on gangue-by-gangue characteristics has been proposed as a reasonable method to improve coal gangue utilization efficiency and to realize stack reduction targets [24] [25] [26] , but few studies have considered the coal gangue pollution problem from a managerial point of view. To ensure a more effective CGF, the identification and selection of suitable sites is fundamental, which affects both the environment and the recycling efficiency of coal gangue. Appropriate CGF site identification and selection require the consideration of many factors, such as transportation conditions, costs, local geographical characteristics, development planning and environmental pollution. As a result of this complex, but important decision process, there has been increased research on site selection in recent years. Avittathur et al. [27] developed non-linear mixed integer programming to select the optimal location for a distribution center with different sales tax structures. A mean-shift algorithm was proposed by He et al. [28] to solve large-scale planar maximal covering location problems. Gołȩbiewski et al. [29] established a non-linear modeling to determine vehicle recycling facility site selection by defining the most suitable dismantling facilities sites. To reduce the effects of unexpected disasters, a stochastic modeling framework was proposed to decide the location and capacities of distribution centers for emergency stockpiles [30] . Meanwhile, some scholars attempted to solve the site selection problem by GIS. Aydin et al. [31] developed a decision tool using GIS for the hybrid wind solar-PV renewable energy systems location problem. Taking landslide exposure into consideration, Mahnaz et al. [32] proposed to mask unsuitable areas using GIS for selecting waste disposal sites. Latinopoulos et al. [33] integrated a methodology by combining the spatial multi-criteria decision analysis and GIS for wind-farm planning at the regional level. This application of GIS in the location problem has received considerable attention, which ignored the inherent relationship among multi-decision makers. In addition to these approaches, other methods, such as bi-level programming, have been applied to the site selection problem. Supalin et al. [34] selected the optimal site for production distributions and distribution centers via a bi-level programming model. Considering benefits for customers and logistics planning departments, Sun et al. [35] formulated a bi-level programming model to select the appropriate site for logistics distribution centers. With a hierarchical structure composed of a local authority and several stone enterprises, Gang et al. [36] solved a stone industrial park location problem by establishing a bi-level programming model. These studies had important impacts on optimal site selection for predetermined construction projects, which ignored the influence from geospatial data. When considering CGF site selection approaches, many of these existing methods are not suitable for the following reasons. First, many studies have tended to identify candidate sites using only historical experience and have ignored the significant effects of geospatial data on site identification. Second, traditional site selection research has mostly included only a single decision maker; however, for CGF site selection, such an approach that only takes into account the local authority's perspectives is impractical, as the colliery decisions also influence site selection by determining optimum production and recycling quantity. Therefore, the complex interactive relationships between the local authority and the colliery need to be taken into account for CGF site selection. Third, site selection needs to include a consideration of the uncertain environment, as there are many uncertainties in large
doi:10.3390/su9020251 fatcat:24ca65bak5g6tczshkjtenr544