Impact of the Digital Economy on PM2.5: Experience from the Middle and Lower Reaches of the Yellow River Basin

Abstract

The development of the digital economy holds great significance for alleviating haze pollution. To estimate the impact of the digital economy on haze pollution, this paper explores the spatiotemporal evolutionary characteristics of the digital economy and PM2.5 concentration in the middle and lower reaches of the Yellow River Basin from 2011 to 2019 and conducts regression analysis by combining a fixed effect (FE) model and the spatial Durbin model (SDM). Moreover, this study divides the mitigation effect of haze pollution into a direct effect and a spatial spillover effect, and it further analyzes the mechanism from the perspectives of technological innovation and the industrial structure. The empirical results show that the development level of the digital economy increases year by year and that the concentration of PM2.5 decreases year by year. The digital economy level and PM2.5 concentration in the downstream region are higher than those in the middle region, and the digital economy is negatively correlated with haze pollution. Similarly, the spatial spillover effect of the digital economy is conducive to curbing haze pollution. The robustness test also supports this conclusion. In addition, there is regional heterogeneity in the impact of the digital economy on haze pollution. The direct effect and spatial spillover effect of the digital economy on haze pollution in the downstream region are greater than those in the middle region. This study suggests that to realize air pollution prevention and control, it is necessary to strengthen the construction of digital infrastructure and create a good digital economy development environment based on local conditions. Encouraging the development of digital technological innovation and promoting industrial digital transformation hold great significance for alleviating haze pollution.

Experimental and Numerical Calculation Study on the Slope Stability of the Yellow River Floodplain from Wantan Town to Liuyuankou

“…The average annual precipitation and temperature are 636 mm and 15 °C, respectively, and this area is rich in biological resources, with nearly 800 and 60 kinds of plants and animals, respectively. The economic development of the region is dominated by traditional industries, such as the chemical and energy industries, and crop cultivation, which have a significant impact on the ecological environment of the lower Yellow River [ 57 ]. Cultivated land is widely distributed in this area, and the soil is mainly loam, clay, and silt.…”

Effects of Big Data on PM2.5: A Study Based on Double Machine Learning

“…These advancements are closely associated with green, low-carbon development, playing a crucial role in pollution mitigation. Numerous studies [30][31][32] have highlighted the digital economy's role in fostering the development of cleaner technologies and greener products. This is facilitated through the promotion of scientific and technological innovations, especially patents in green technology.…”

“…Recent studies have indicated that the development of the digital economy significantly impacts the reduction in PM 2.5 pollution [27]. The influence of the digital economy on PM 2.5 is primarily mediated through key factors, such as urban quality development and land use planning [28][29][30][31][32]. The exact manner in which the digital economy affects PM 2.5 pollution is not yet fully understood, necessitating further research to elucidate its mechanisms comprehensively.…”

Synergistic Evolution of PM2.5 and O3 Concentrations: Evidence from Environmental Kuznets Curve Tests in the Yellow River Basin

“…Studies on their spatiotemporal evolution and correlation are also abundant, covering the scales of nations [29], urban agglomerations [30,31], climate zoning [32], provinces [33], and cities [34]. In terms of factors, the main focus is on natural factors-ranging from precipitation [35], vegetation [36], wind speed [37], and per capita GDP [30] to urbanization [38], digital economy [39,40], and other socio-economic factors-to analyze their effects on air pollutant concentrations. The specific factor research methods include GWR [41], machine learning [23,42], GeoDetector [43], and spatial metrics [44].…”

“…First of all, this large river basin is one of the regions most strongly influenced by the relationship between humans and land. Due to the particularity of its natural environment and geographical location, the ecological environment of the YRB is always facing great threats [40]. Secondly, the YRB is a national strategic implementation region.…”