Abstract As the world’s largest consumer of coal, China is now facing serious pollution of atmospheric polycyclic aromatic hydrocarbons (PAHs) produced by coal utilization processes, i.e., coal-related PAHs, which should… Click to show full abstract
Abstract As the world’s largest consumer of coal, China is now facing serious pollution of atmospheric polycyclic aromatic hydrocarbons (PAHs) produced by coal utilization processes, i.e., coal-related PAHs, which should be of concern for relevant policy-makers. Based on the interrelationships among coal-related PAHs emission, coal consumption and socio-economic development, this study applied a coupled method of system dynamics (SD) and geographic information system (GIS) to successfully model the spatiotemporal changing processes of coal-related PAHs emission reduction in China’s 31 provinces. In these models, four different policies including industry structure adjustment, energy consumption structure adjustment, industrial emission control and household emission control were quantitatively designed to evaluate the emission reduction differences from national and provincial perspectives. And then, cluster analysis was used to identify the provinces with similar policy effects. The results indicated that, without any policy stimulation, atmospheric coal-related PAHs emission in China would maintain a gradual growth trend. The implementation of energy consumption structure adjustment had better national emission reduction effect than the other three policies, while not all provinces could succeed in emission reduction when the four policies were implemented, respectively. Besides, the different policy effects among provinces resulted from their development discrepancies in industry structure, energy structure and emission source characteristics. Therefore, to simultaneously realize the maximum national emission reduction effect and the integrated emission reduction for different provinces, all provinces should take energy consumption structure adjustment as the guiding policy and consider their targeted policies as supplementary. In short, the coupled SD-GIS method can be used to comprehensively analyze the spatiotemporal variations of unconventional atmospheric pollutants and the specific impacts of pollution control policies, which will provide a theoretical basis for local governments to reasonably direct the coordinated development of regional economy, energy structure and environmental quality.
               
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