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Correlation between urbanization and environmental pollution is a major focus of study in geography, environmental science, and economics. Particulate matter is the primary pollutant of air pollution and made up of heavy metal, organic carbon and aromatic hydrocarbon and complicated chemicals. PM 2.5 are fine particulate matter with diameters that are less than 2.5 μm. The aim of this study on the relationship between urbanization and PM 2.5 concentration is to achieve a win-win situation of both economic development and environmental protection, which is of great significance to sustainable development in China. This paper uses PM 2.5 remote sensing data and statistical yearbook data from 2000 to 2011 to build four panel data models within the urbanization-PM 2.5 concentration Environmental Kuznets Curve (EKC) framework. The goal is to find out the correlations between PM 2.5 concentration and economic urbanization, population urbanization, and space urbanization. Furthermore, scenario simulations are set to predict when China will reach inflection point and achieve its target concentration. Results show that the relationship between economic urbanization and PM 2.5 concentration is an inverted N-shaped or inverted U-shaped curve. Most cities in East China have reached the second inflection point of inverted-N curve to step into the win-win stage while many cities in Middle China still need 10–15 years to arrive at the inflection point of the inverted-U curve. Therefore, China is under great pressure to prevent PM 2.5 pollution and pursue more targeted PM 2.5 -reduction policies for air quality improvement. [ABSTRACT FROM AUTHOR]

While the concept of remanufacturing is gaining popularity in practice, its effect on environmental protection and energy saving is significant, which has attracted widespread concerns, especially in the automotive components field. Automotive components remanufacturing (ACR), as a prominent part in automotive life-cycle development, can dramatically reduce resources-waste and mitigate energy-crisis, which has become a prominent direction to promote sustainable development of Chinese economy. Thus, influence factors analysis and enterprise operation patterns assessment which primarily contribute to ACR industry development are of paramount importance. This paper elaborates the criteria influencing the ACR industry operation and analyzes the main operation patterns for ACR in China. To overcome the uncertainty of the evaluation process, a new hybrid multi-criterion decision-making (MCDM) model that combines fuzzy AHP (analytical hierarchy process) and fuzzy G-TOPSIS (combining gray relation analysis and technique for order performance by similarity to ideal solution) is proposed to determine weights of influence criteria and evaluate ACR production operation patterns. In addition, sensitivity analysis is applied to monitor the robustness of the method. The study refers to the experience of Chinese end-of-life vehicle (ELV) laws and implementation requirements of extended producer responsibility (EPR). The obtained results provide the new guideline to revise the regulations of Chinese ACR industry. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for Sustainable Development stipulates 17 Sustainable Development Goals (SDGs). The implementation of this agenda will mobilize countries worldwide to incorporate the SDGs into their national development strategies. The agenda does not specify how these goals are interconnected, thus limiting their implementation. In addition, air quality affects human life and plays a vital role in achieving these SDGs. Clarifying the interconnections between SDGs related to air pollution and other SDGs will accelerate the implementation of air protection and SDGs while simultaneously promoting policy coherence. In this paper, we use the latest calculation of the SDGs in China to construct national and provincial panel data to investigate the trade-offs and synergies among Chinese air pollution-related SDGs. The findings are as follows. First, most air pollution-related SDGs have synergetic relationships, except for SDG12, which has a trade-off relationship with other air pollution-related SDGs. Second, the synergies between air pollution-related SDGs and other SDGs far outweigh the trade-offs. Third, rapidly developing areas are more likely to experience a trade-off between economic development and air pollution problems. Fourth, geographic advantages in reducing air pollution, such as being adjacent to the sea, may weaken the synergies among air pollution-related SDGs and their synergies with other SDGs. These findings indicate that most air-pollution-related SDGs and interactions between air-pollution-related SDGs and other SDGs have substantial synergy; that is, measures aimed at one goal are conducive to the advancement of other goals. However, SDG12 reflects a trade-off relationship between economic development, environmental protection, and resource utilization. [ABSTRACT FROM AUTHOR]

Green innovation is the main force to drive China's intensive pollution industries (IPIs) into sustainable development. Improving green innovation efficiency (GIE) is an effective way to reach this goal. The correct approach to measuring IPIs' GIE and its influencing factors is a hot issue. Based on the panel data of China's 21 subdivided industries of IPIs over the period from 2011 to 2015, this paper applies the Super-Slack-Based Measurement (Super-SBM) and Tobit model to analyse IPIs' GIE and its influencing factors, respectively. The results show that IPIs' overall efficiency fluctuates around 0.67 in the first 4 years and increases to 0.776 in 2015, failing to be DEA-efficient; there are obvious gaps in GIE between the 21 industries, and the ferrous metal smelting and calendering industry has the weakest GIE. The regression results show that, government R&D support and environmental regulation have inverted U-shaped and U-shaped relationship with IPIs' GIE, respectively. Foreign market demand and market competition have significant positive and negative impacts on GIE, respectively, but the impact of market openness is not significant. The results suggest that (1) Chinese government should increase R&D support for IPIs, especially for those with low GIE, and strengthen supervision of the use of government R&D funds to avoid the crowding-out effect, (2) strengthen the intensity of environmental supervision and enforcement of environmental regulation policies, (3) improve environmental protection standards and preferential policies for exportation at the same time, (4) promote industrial restructuring and improve the mechanism of resource and benefit sharing to promote the flow of innovative resources and diffusion of innovative achievements. • Supplementing the evaluation indexes of GIE to reflect the requirements of recycling, low-carbon development, cleanness. • The GIE of IPIs has been improved from 0.67 to 0.776 during 2011–2015, but still fail to be DEA-efficient. • GIE of different industries varies greatly, and the ferrous metal smelting and calendaring industry's GIE is the weakest. • Government R&D support and environmental regulation have inverted U–shaped and U-shaped relationship with GIE, respectively. • Foreign market demand and market competition have significant positive and negative impacts on GIE, respectively. [ABSTRACT FROM AUTHOR]