Atmospheric pollutants have become a serious concern to the Chinese public in recent years due to the reduction of visibility and severe health risks associated with them. In this study, PM2.5, PM10, NO2, and SO2 were measured at a time resolution of 1-hour over the course of a year from January to December 2015 in the urban environment of Qingdao based on the temporal and spatial variations in the concentrations of four air pollutants. We found that (1) seasonal variation exists consistently for all pollutants, with the highest concentration in winter and the lowest in summer. (2) The monthly average of the concentrations of the four air pollutants exhibited U-shaped pattern of "high in autumn and winter but low in spring and summer", and the double-peak or single-peak impulse-shaped daily variation. PM2.5 and PK10 concentrations were lower on weekdays than on weekends while SO2 concentrations were higher on weekdays than on weekends, indicating a "weekend effect". (3) PM2.5, PM10, NO2, and SO2 factors showed strong correlation and low coefficient of divergence (CD) values at nine sites throughout the year, indicating an even distribution across the urban area. (4) Spatial autocorrelation analysis was used to characterize spatial variability showing that air pollutants in urban areas are not produced in the specific local site. The spatial distribution of annual and seasonal air pollution concentrations simulated by ordinary kriging showed that most parts of urban Qingdao suffer from severe air pollution in winter and pollutant concentrations are higher inland than at coastal sites.
FörderungenBeijing Key Laboratory of Big Data Technology for Food Safety High-level Teachers in Beijing Municipal Universities in the Period of 13th Five -year Plan Germany Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of SmartAQnet Research Project of the Ministry of Science and Technology of China National Natural Science Foundation of China