Ambient particulate matter (PM) pollution of China has become a global concern and has great impact on air quality and human health. This paper adopts the PM2.5 concentration data obtained from 241 newly located observation points in the Bohai Rim Urban Agglomeration (BRUA), as well as economic, urban and industrial working population data in the study area, revealing the spatio-temporal distribution of PM2.5 and its determinants with the help of a spatial data model. The results indicate that: 1) The BRUA was the core area of PM2.5 pollution in China in 2014, the average PM2.5 concentration of which reached 74 μg/m(3), which is 13 μg/m(3) higher than the country average (61 μg/m(3)); 2) The PM2.5 concentration distribution had a characteristic of high in winter and autumn but low in spring and summer, presenting a U-shaped monthly profile and a U-impulse type daily profile; 3) The urban PM2.5 concentrations showed obvious spatial variation and agglomeration. The highest hot-spot was observed in spring, while the lowest was in summer. High concentration cities were mainly located in southern Hebei and western Shandong, and low concentration cities were in the coastal area around the Bohai Sea and the mountainous areas in northern Hebei. High hot-spot areas demonstrated an M-shaped change, with two cycles of advance and retreat from west to east. 4) The Geographically weighted regression (GWR) model shows that the GDP per capita, urbanization rate and construction of the cities were closely related to PM2.5 concentrations in the BRUA.
Keywords: Bohai Rim Urban Agglomeration (BRUA); Determinants; GWR; Monitoring data; PM(2.5); Spatial-temporal characteristics.
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