[Spatial-temporal Variation and Spatial Differentiation Geographic Detection of PM_2.5 Concentration in the Shandong...

PM_2.5 remote sensing data was applied in this study, and Theil-Sen Median trend analysis and the Mann-Kendall significance test were utilized to analyze the temporal and spatial variation in PM_2.5 in the Shandong Province from 2000 to 2021. The influencing power of the influencing factors on the spatial differentiation of PM_2.5 concentration in the Shandong Province was detected at the provincial-city-county levels based on Geo-detector data. The results showed that:① on the temporal scale, the mean ρ(PM_2.5)in the Shandong Province ranged from 38.15 to 88.63 μg·m^-3 from 2000 to 2021, which was slightly higher than the secondary limit of inhalable particulate matter (35 μg·m^-3) in the Ambient Air Quality Standards. On the interannual scale, 2013 was the peak year for the variation in ρ(PM_2.5) with a value of 83.36 μg·m^-3, according to which the trend of PM_2.5 concentrations in the Shandong Province was divided into two phases:a continuous increase and a rapid decrease. On the seasonal scale, PM_2.5 concentration presented the distribution characteristics of "low in summer and high in winter and moderate in spring and autumn" and the U-shaped change rule of first decreasing and then increasing. ② On the spatial scale, the PM_2.5 concentration in the Shandong Province presented a spatial distribution pattern of "high in the west and low in the east." The areas with high PM_2.5 concentration were distributed in the western area of the Shandong Province, whereas the areas with low PM_2.5 concentration were distributed in the eastern peninsula region. The spatial variation in the changing trend of PM_2.5 concentration showed significant spatial heterogeneity, and the extremely significant decrease was mainly distributed in the eastern peninsula region. ③ The results of factor detection showed that climate factor was an important factor affecting the spatial differentiation of PM_2.5 concentration in the Shandong Province. Mean temperature had the highest influence on the spatial differentiation of PM_2.5 concentration in the Shandong Province, with a q value of 0.512. Provincial-city-county multi-scale detection results showed that the influencing factors affecting the spatial differentiation of PM_2.5 concentration and their influencing power differed at different spatial scales. At the provincial scale, mean temperature, sunshine duration, and slope were the main factors affecting the spatial differentiation of PM_2.5 concentration. At the city level, precipitation, elevation, and relative humidity were the main factors affecting the spatial differentiation of PM_2.5. At the county level, precipitation, mean temperature, and sunshine duration were the main factors affecting the spatial variation in PM_2.5 concentration.