云南省8个主要城市PM2.5时空变化特征研究

M. Teng, Kun Yang, Yan Shi, Yi Luo
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引用次数: 2

摘要

空气雾霾污染严重影响人类健康、生态环境和气候变化。近年来,随着国家新政策的出台和人们环保意识的增强,雾霾受到了社会的广泛关注。雾霾污染在中国一直是一个突出的环境问题。雾霾污染频繁发生的主要原因是PM2.5,它不仅发生在工业化或城市化程度高的城市,也经常出现在空气质量较好的地区。本文选取云南省8个主要城市作为研究区域,以云南省2015年1月至2018年2月8个主要城市的PM2.5实测数据为基础数据,以8个城市气象数据为基础数据,采用MK趋势检验和相关系数法对云南省近3年PM2.5的时空变化及相关性进行研究。时空分析表明,丽江市PM2.5年平均浓度最低,宝山市月平均浓度最高,普洱市日平均浓度呈平缓趋势;2015年3月17日至26日,除丽江外,其他7个城市均出现了不同程度的污染;各城市PM2.5浓度在冬春、夏秋两季均呈“U”型季节性和脉冲型日变化规律;全省年平均浓度较高的城市主要集中在东北部和西南部。相关分析表明,PM2.5浓度与降水量、风速呈显著负相关,与日平均湿度、气温呈显著负相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the Temporal and Spatial Variation of PM2.5 in Eight Main Cities of Yunnan Province
Air haze pollution has a serious impact on human health, ecological environment and climate change. In recent years, with the introduction of new national policies and people's increasing awareness of environmental protection, haze has received widespread social attention. Haze pollution in China has always been a prominent environmental problem. The main reason for the frequent occurrence of haze pollution is PM2.5, which not only occurs in cities with high degree of industrialization or urbanization, but also often appear in regions with good air quality. This paper selects eight main cities in Yunnan Province as the research area, and uses the measured PM2.5 data from eight main cities in January 2015 to February 2018 in Yunnan Province as the basic data, using the eight urban meteorological data as the basic data, using the MK trend test and Correlation coefficient method to carry out research on the spatial-temporal variation and correlation of PM2.5 in the last three years in Yunnan Province. The space-time analysis shows that the average annual PM2.5 concentration in Lijiang City is the lowest, the monthly average concentration in Baoshan City is the highest, and the daily average concentration in Puer City is in a gentle trend; Except for Lijiang, the other seven cities all experienced different levels of pollution from March 17 to March 26, 2015; The concentration of PM2.5 in each city showed a seasonal pattern of “U” and a pulse-like diurnal variation pattern in winter and spring, summer and autumn; cities with higher annual average concentrations in the province are concentrated in the northeast and southwest. Correlation analysis showed that PM2.5 concentration was significantly negatively correlated with precipitation and wind speed, and negatively correlated with daily average humidity and temperature.
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