Spatial–Temporal Heterogeneous Evolution of Haze Pollution in China as Deduced with the Use of Spatial Econometrics

Abstract

Haze Pollution, consisting essentially of PM2.5 and PM10, has been arousing wide public concern home and abroad. It has become a universal urgency for atmospheric researchers, governments, organizations, institutions, and the general public to conduct corresponding actions. Therefore, this paper aims to explore the institutional distribution and the regional evolution trend of path characteristics of haze pollution in China under the spatial–temporal heterogeneity on the basis of spatial econometrics, by incorporating the spatial element into the framework of the Multiple Influencing Factors mechanism. The results show that it has been abating under the governance year by year, though with a decreasing intensity; the major polluted regions have been moving from the East to the central and western area; there is significant spatial autocorrelation among the highly polluted area, but the effective local regulations of les- polluted regions do not impact the neighboring regions correspondingly; among the impacting factors, industrial structure, energy intensity, and traffic pollution have a significant Positive Impact on haze pollution, and the level of urbanization has a Negative Impact, while economic growth and innovation performance have no significant Positive Impact and are both weak in promotion. This research, theoretically and practically, offers reference for the Chinese government to integrate regional effective systems into multiregional diversified environmental governance, so as to realize its Green Ecology Transformation Development Strategy.

Interaction mechanism and spatial effect of cross‐regional haze pollution based on a multisectoral economy–energy–environment (3E) model and the evidence from China

“…To explore the temporal evolutionary trend and spatial distribution characteristics, the current situation and changes in relevant variables are first analyzed and drawn by ArcGIS, and the statistical value of Moran's I is calculated to examine whether the variables have spatial correlation. This must be verified before conducting spatial econometric regressions (Hou et al, 2019). Moreover, the spatial agglomeration pattern of variables is further identified in combination with Moran scatterplots (Ma & Zhang, 2014).…”

What Are the Key Factors Affecting Air Pollution? Research on Jiangsu, China from the Perspective of Spatial Differentiation

“…Thus, China is in a process where the development mode is transforming by optimizing the economic structure and shifting the growth momentum. There is an urgent need to improve the efficiency of resource and energy utilization, decrease environmental pressure, and improve the air quality [1]. At present, China's energy consumption is effectively controlled.…”