Spatial Patterns, Drivers and Heterogeneous Effects of PM2.5: Experience from China

Abstract

PM2.5 not only affects air visibility, but also can enter the lungs and blood through the respiratory tract, causing important damage to the human respiratory system, cardiovascular and cerebrovascular system. Infants, children, the elderly, patients with cardiovascular disease and chronic lung disease have become more sensitive to it, and has become an important factor endangering public health. Identifying PM2.5 spatial and temporal characteristics and influencing factors can provide key information for urban atmospheric environmental governance and public health improvement. Previous studies have only explored the influencing factors of PM2.5, while ignoring which is the more important factors. Firstly, this study explores the spatial-temporal evolution characteristics and spatial correlation characteristics of PM2.5 distribution in 285 cities in China. Then, a selection model---Bayesian model average method is applied to identify which variables are more likely to affect PM2.5 in China. We find that (1) From 2000 to 2018, the high-value concentration areas of PM2.5 distribution in China were mainly distributed in the central and eastern regions, and showed the trend of "moving eastward". (2) Among all variables in this study, population density, utilization rate of common industrial solid wastes, per capita Gross Domestic Product (GDP), proportion of secondary industry to GDP, centralized treatment rate of sewage treatment plant and industrial emission of sulfur dioxide are the most important drivers to predict PM2.5 in China. In addition, we found that the relationship between the selected variables and PM2.5 tends to change over time. In addition, we also show that the influence of selected variables on PM2.5 depends on the distribution of PM2.5, that is, there is a heterogeneous effect.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity—evidence from the Yangtze River Delta Region of China

“…Ecological priority and green development are vital goals of China's high-quality development [1][2][3][4], and agricultural green development is one of its crucial components [5][6][7]. However, in the past, to maximize agricultural output, China put vast pesticides and chemical fertilizers into agricultural production, which not only caused serious pollution of land, water bodies, and agricultural products [8][9][10], but also increased greenhouse gas emissions [11], leading to climate change and the destruction of ecosystems and posing a serious threat to human survival [12][13][14]. Agriculture, as an essential source of greenhouse gases, has attracted widespread social concern [15].…”

Is There a Relationship between Increased Land-Use Intensity and the Rise in PM2.5 Pollution Levels in the Yangtze River Economic Belt, China (2000–2021)?

“…The YREB is one of the regions with the most rapid economic growth and is very crucial to China's modernization process from a strategic standpoint. The rapid economic growth of the region is accompanied by increases in environmental pollution, land-use imbalances, and other problems, especially in urban agglomerations [12][13][14][15]. Therefore, the YREB, a major national strategic development area, is used as the study area, and the study of the response of PM 2.5 pollution to land-use change is beneficial to promoting regional sustainable development.…”

The Heterogeneous Effects of Urban Form on CO2 Emissions: An Empirical Analysis of 255 Cities in China

“…The authors show that the urban form plays an important role in mitigating CO 2 emissions. Urban form, which involves spatial patterns and organization of urban landscape elements, reflects the temporal and spatial interaction between human socioeconomic activities and natural environment in urban areas [6][7][8]. It can influence CO 2 emission and its efficiency, directly or indirectly, through impacting the structure of land use, urban infrastructure, urban transportation, urban heat island effects, household energy demand and efficiency, and carbon sinks [9][10][11][12][13].…”