ABSTRACTIn recent years, high-polluting industries have been gradually shifted from the eastern developed regions to the central and western underdeveloped regions in China. Certain environmental regulations have been in place accordingly in various regions, but the pollution in the central and western regions has risen sharply. Based on the data of interprovincial panel in China from 2006 to 2015, this paper calculates high-pollution industry dynamic agglomeration index, environmental pollution agglomeration index and relative environmental regulation intensity index, and uses Generalized Method of Moments to carry out the regression analyses of the whole samples, regional heterogeneity and temporal heterogeneity. The results show that there is an inverted U-shaped relationship between relative environmental regulation and environmental pollution concentration in China. The concentration degrees of industrial wastewater pollution and industrial waste gas pollution are deepened, which are mainly caused by the transfer of highly polluting industries. However, the concentration of industrial solid waste pollution caused by the transfer is not obvious. Furthermore, the deepening of industrialization intensifies the concentration of regional environmental pollution. Environmental Kuznets Curve does exist in China, but it is not significant. The increase of labor cost and quality will reduce the concentration of environmental pollution. 相似文献
The continuous increase in waste generation warrants global management of waste to reduce the adverse economic, social, and environmental impact of waste while achieving goals for sustainability. The complexity of waste management systems due to different waste management practices renders such systems difficult to analyze. System dynamics (SD) approach aids in conceptualizing and analyzing the structure, interactions, and mode of behavior of the complex systems. The impact of the underlying components can therefore be assessed in an integrated way while the impact of possible policies on the system can be studied to implement appropriate decisions. This review summarizes various applications of SD pertinent to the waste management practices in different countries. Practices may include waste generation, reduction, reuse/recovery, recycling, and disposal. Each study supports regional-demanding targets in environmental, social, and economic scopes such as expanding landfill life span, implementing proper disposal fee, global warming mitigation, energy generation/saving, etc. The interacting variables in the WMS are specifically determined based on the defined problem, ultimate goal, and the type of waste. Generally, population and gross domestic product can increase the waste generation. An increase in waste reduction, source separation, and recycling rate could decrease the environmental impact, but it is not necessarily profitable from an economic perspective. Incentives to separate waste and knowledge about waste management are variables that always have a positive impact on the entire system.