Abstract

Haze pollution, a serious livelihood and environmental issue, has hindered China’s economic development. This paper, based on the improved output density model, empirically analyzes spatial patterns and impact factors of haze pollution within the Yangtze River Delta from 2015 to 2017 by statistical and spatial econometric models. The study shows that: (1) The characteristics of haze pollution due to seasonal changes are obvious in the Yangtze River Delta region, and the situation has gradually improved. (2) The haze pollution has significant local agglomeration characteristics and spatial heterogeneity, demonstrated as significant low-level agglomerations in Hangzhou, Ningbo, and Taizhou, and high agglomerations in Chuzhou, Yangzhou, Zhenjiang, and Taizhou. The polluted area clusters around the provincial boundary, and its level gradually decreases from northwest to southeast. There is a significant spatial positive correlation and spatial spillover effect of intercity haze pollution, which will have a negative impact on the region and surrounding areas. (3) The population growth, research and development (R&D) investment, industrial structure, industrial smoke and dust emissions, and urban construction in the Yangtze River Delta have positive impacts on haze pollution, while factors, such as investment intensity of foreign direct investment (FDI), energy consumption and precipitation, have a negative impact on smog pollution. However, there is no Kuznets curve relationship between smog pollution and economic growth. By optimizing spatial distribution, incorporating production factors, and sharing pollution control infrastructure, this paper shows that economic agglomeration has an inhibitory effect on haze pollution.

Highlights

  • With dramatic urbanization and industrialization over the past four decades, haze pollution has increased in China

  • Ciccone considered that the externality of economic agglomeration originates from the density of economic activities, and, the basic model is as follows: qi = θi[(ni Hi)βki1−β]α(Qi/Ai)(λ−1)/λ where qi refers to the output per unit area of city I; θi refers to the total factor productivity of city; ni refers to the number of urban employees per unit area; Hi refers to the average human capital level, and ki refers to the material capital input per unit area. α refers to the scale return of unit area capital and labor, and when 0 < α ≤ 1, it indicates a diminishing marginal productivity. β refers to the rate of factor contribution, 0 < β ≤ 1

  • To avoid multi-collinearity influence, SPSS Statistics 20.0 (IBM, Beijing, China) is used to analyze the correlation among each explanatory variable, and the results show that the variance expansion factor (VIF) is all within 10, suggesting that there is no obvious multi-collinearity problem

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Summary

Introduction

With dramatic urbanization and industrialization over the past four decades, haze pollution has increased in China. According to the 2017 meteorological bulletin of the atmospheric environment issued by the China Meteorological Administration, the average concentration of the fine particulate matter (PM2.5) and inhalable particulate matter (PM10) in the whole year is 43 and 75 displacement ug/m3, respectively, and the average number of haze days is 27.5 days per year, which is far from the qualified standard. The increase of haze concentration has adverse effects on human health [7]. As the most developed economic and social regions of China, it is imperative to the prevention and control of haze pollution, and to the promotion and coordinated development of the economy and environment in the Yangtze River Delta (YRD) to study the spatial and temporal distribution characteristics and influencing factors of haze pollution

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