Spatio-temporal heterogeneity of air pollution and its key influencing factors in the Yellow River Economic Belt of China from 2014 to 2019.

The Yellow River Economic Belt (YREB) plays an important role in China's socio-economic development and ecological security. However, this region has suffered from serious atmospheric pollution in recent years due to intense human activity. Identifying and qualifying the spatio-temporal characteristics of the region's air pollution and its driving forces would help in the formulation of effective mitigation policies. Here, the YREB's spatio-temporal characteristics of air quality were meticulously investigated using air pollution observation, synchronous meteorological, and socio-economic data from 103 cities, for the period of 2014-2019. Furthermore, the factors influencing air pollution were analyzed and qualified. Although air quality improved in the cities of the YREB following the implementation of the Air Pollution Action Plan, the region's quality index (AQI) remained higher than the national average. Annual variations of AQI in the YREB followed a U-shaped pattern, being high in autumn and winter and low in spring and summer; this U shape became shallower following improvements in air quality during autumn and winter. From 2014 to 2019, the annual average AQI values of cities in the eastern, middle, and western YREB dropped from 109.66, 111.70, and 94.65 to 92.00, 103.85, and 73.95, respectively. The air pollution trends of cities revealed obvious spatial agglomeration, and those cities with poor air quality were primarily the western cities of Shandong province, most cities in Henan province, and the eastern cities of Shanxi province. Due to the improvement of air quality in eastern cities, the pollution center of gravity moved gradually from Changzhi (113°3411"E, 36°040"N) to Linfen (110°5222″E, 36°2344″N). The results of the spatial Durbin model (SDM) indicated that air pollution had an apparent spillover effect in the YREB at the watershed scale, and that government technical expenditure, gross domestic product (GDP) per capita, population density, annual wind speed, and relative humidity all had significant negative overall effects on the AQI values of cities. The green cover rate, ratio of secondary industry, and temperature, meanwhile, all had significant positive total effects. Due to differences the natural conditions and stages of socio-economic development between the eastern, middle, and western cities of the YREB, the impact directions and functional strengths of their key factors differed greatly.