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RESEARCH ON TEMPORAL AND SPATIAL VARIATIONS OF ATMOSPHERIC PM2.5 AND PM10 AND THE INFLUENCING FACTORS IN SHANDONG, CHINA DURING 2013—2018
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摘要: PM2.5和PM10污染已成为全球关注的重要环境问题，监测其污染状况对人类健康、动植物生长、大气环境评价等具有重要意义。基于2013—2018年山东省17个城市大气PM2.5和PM10监测数据，利用时空分析方法和Spearman相关分析方法，研究其污染时空变化特征，并分析气象、人为及政策因素对二者的影响。结果表明：与2013年相比，2018年山东省大气PM2.5和PM10污染程度明显减轻，年均浓度降幅分别为48.72%、37.72%；6年整体月均PM2.5浓度呈近似"U "形变化规律，月均PM10浓度呈近似" V"形变化规律；PM2.5和PM10污染整体呈由西北内陆向东部沿海地区逐渐减轻的空间趋势；PM2.5和PM10浓度受气温和降水量2个气象因素影响较显著，受道路密度、城市绿化覆盖面积、SO2和NOx排放量等人为因素影响较显著，且气象因素和人为因素对PM2.5浓度的影响较PM10更大。Abstract: PM2.5 and PM10 pollutions have become important environmental problems which have attracted great attention in the world. Monitoring PM2.5 and PM10 pollutions is of great significance to human health, animal and plant growth, atmospheric environment assessment, etc. Based on the atmospheric PM2.5 and PM10 monitoring data of 17 cities in Shandong during 2013—2018, the paper studied spatial and temporal variation characteristics of PM2.5 and PM10 pollution in Shandong and analyzed the influence of meteorological factors, human factors and policy factors on them, using the temporal-spatial analysis method and the Spearman correlation analysis method. The results showed that: compared with 2013, the pollution extent of PM2.5 and PM10 in Shandong was significantly reduced in 2018, with an annual mean concentration dropped of 48.72% and 37.72% respectively; the presentation of the monthly PM2.5 mean concentration variation in the studied six years was similar to the "U" shape change rule, and the monthly PM10 mean concentration was similar to the "V" shape change rule; the overall pollution conditions of PM2.5 and PM10 showed a spatial trend of gradual reduction from the northwest inland to the eastern coastal area; the concentrations of PM2.5 and PM10 were significantly affected by the meteorological factors of temperature and precipitation, as well as the human factors of road density, urban green coverage, SO2 and NOx emissions, etc. Besides, meteorological and human factors had a greater impact on PM2.5 concentration than PM10 concentration.
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Key words:
- PM2.5 /
- PM10 /
- spatial-temporal feature /
- meteorological factor /
- human factor /
- Shandong
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