森林植被对信阳市城郊PM2.5等颗粒物污染的影响

doi:10.14088/j.cnki.issn0439-8114.2019.16.011

湖北农业科学 ›› 2019, Vol. 58 ›› Issue (16): 49-53.doi: 10.14088/j.cnki.issn0439-8114.2019.16.011

森林植被对信阳市城郊PM2.5等颗粒物污染的影响

冯万富^1,2, 邱林¹, 单燕祥^1,2, 张建设^1,2, 李月凤^1,2, 周继良³, 柳勇^1,2

1.信阳市林业科学研究所,河南信阳 464031;
2.河南鸡公山森林生态系统国家定位观测研究站,河南信阳 464031;
3.信阳市环境监测站,河南信阳 464000

收稿日期:2019-02-11 出版日期:2019-08-25 发布日期:2019-11-12
作者简介:冯万富（1974-）,男,河南信阳人,高级工程师,主要从事森林生态系统关键过程观测与模拟以及城市森林净化环境空气功能研究,（电话）13937646790（电子信箱）lksfwf@163.com。
基金资助:
国家林业公益性行业科研专项（201304301）; 河南省省级科技计划项目（172102310561）; 信阳市科技计划项目（150088）

The influence of forest vegetation on PM2.5 and other particulate matter pollution in suburb of Xinyang city

FENG Wan-fu^1,2, QIU Lin¹, SHAN Yan-xiang^1,2, ZHANG Jian-she^1,2, LI Yue-feng^1,2, ZHOU Ji-liang³, LIU Yong^1,2

1.Xinyang Forest Science Research Institute,Xinyang 464031,Henan,China;
2.Henan Jigongshan Forest Ecosystem Research Station,Xinyang 464031,Henan,China;
3.Xinyang Environmental Monitoring Station,Xinyang 464000,Henan,China

Received:2019-02-11 Online:2019-08-25 Published:2019-11-12

摘要/Abstract

摘要： 选择森林植被盖度存在明显差异的信阳市中心城区-近郊区-远郊区分别设立监测点开展大气颗粒物污染同步定位观测,比较分析了3个监测点TSP、PM10、PM2.5和PM1等4种粒径颗粒物质量浓度日变化和季节变化特征及其影响因素。结果表明,3个监测点4种颗粒物质量浓度日变化特征基本一致,峰值和最低值出现的时间基本同步。上午颗粒物污染比下午严重。3个监测点的颗粒物污染均表现为夏季最轻,秋季次之,冬季污染最严重。森林植被具有强大的削减PM2.5等颗粒物污染的功能,监测点颗粒物质量浓度与森林植被盖度呈负相关。在日变化和季节变化中,森林植被盖度最高的生态站监测点4种颗粒物质量浓度均明显低于其他2个监测点;同样,森林植被盖度较高的浉河景观带监测点4种颗粒物质量浓度均明显低于缺林少绿的体彩广场监测点。影响颗粒物污染的主要气象因子是气温和气压。PM2.5等4种颗粒物质量浓度与日均气温均呈极显著负相关,与日均气压均呈极显著正相关。

关键词: 森林植被, PM2.5, 大气颗粒物, 气象因子, 信阳市

Abstract: The Xinyang central city-near suburb-far suburbs, where there were obvious differences in forest vegetation coverage were chosen to set up monitoring points to carry out simultaneous location observation of atmospheric particulate matter pollution, and the diurnal and seasonal variation characteristics and influencing factors of mass concentration of four kinds of particulate matter, such as TSP, PM10, PM2.5 and PM1, were compared and analyzed in three monitoring sites. The results showed that the daily variation characteristics of the mass concentration of 4 particles in 3 monitoring points were basically consistent, and the time of peak and lowest value was basically synchronized. Particulate pollution in the morning was more serious than in the afternoon. The pollution of particulate matter in 3 monitoring points was the lightest in summer, the second in autumn and the worst in winter. Forest vegetation had a strong function of reducing particulate matter pollution such as PM2.5, and the concentration of particulate matter in the monitoring point was negatively correlated with the canopy of forest vegetation. In the diurnal and seasonal variations, the concentration of 4 kinds of particulate matter in the Ecological station monitoring site with the highest forest cover was significantly lower than that of other 2 monitoring points; In the same way, the mass concentrations of four kinds of particulate matter in the monitoring sites of Shihe River landscape zone with higher forest vegetation coverage were significantly lower than those in the Ticai square, where there was a lack of greening. The main meteorological factors affecting particulate matter are temperature and air pressure. The mass concentrations of 4 kinds of particulate matter were significantly negatively correlated with daily average temperature, and were significantly positively correlated with daily air pressure PM2.5.

Key words: forest vegetation, PM2.5, atmospheric particulate matter, meteorological factors, Xinyang ci

中图分类号:

S731.2

冯万富, 邱林, 单燕祥, 张建设, 李月凤, 周继良, 柳勇. 森林植被对信阳市城郊PM2.5等颗粒物污染的影响[J]. 湖北农业科学, 2019, 58(16): 49-53.

FENG Wan-fu, QIU Lin, SHAN Yan-xiang, ZHANG Jian-she, LI Yue-feng, ZHOU Ji-liang, LIU Yong. The influence of forest vegetation on PM2.5 and other particulate matter pollution in suburb of Xinyang city[J]. HUBEI AGRICULTURAL SCIENCES, 2019, 58(16): 49-53.

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森林植被对信阳市城郊PM2.5等颗粒物污染的影响

The influence of forest vegetation on PM2.5 and other particulate matter pollution in suburb of Xinyang city

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