| Autor: |
Xu Y; School of Geosciences and Info-physic, Central South University, Changsha 410083, China.; College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China., Wei MX; College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China., Zou B; School of Geosciences and Info-physic, Central South University, Changsha 410083, China., Guo ZD; College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China., Li SX; School of Geosciences and Info-physic, Central South University, Changsha 410083, China. |
| Jazyk: |
čínština |
| Zdroj: |
Huan jing ke xue= Huanjing kexue [Huan Jing Ke Xue] 2024 May 08; Vol. 45 (5), pp. 2596-2612. |
| DOI: |
10.13227/j.hjkx.202306066 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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