重庆市大气颗粒物时空变化及植物滞尘能力研究

发布时间：2017-12-27 18:11

本文关键词：重庆市大气颗粒物时空变化及植物滞尘能力研究　出处：《北京林业大学》2015年硕士论文　论文类型：学位论文

【摘要】：大气颗粒物污染在中国已成为重要的问题,大气颗粒物对人体健康、环境污染和能见度等都有影响。目前有关大气颗粒物的研究主要集中于来源分析、成分解析、危害评价和动态变化特征。本研究基于重庆市和缙云山森林大气颗粒物的监测数据,运用ArcGIS等分析了大气颗粒物的时空分布规律及气象因子对大气颗粒物浓度的影响；研究了缙云山典型林地大气颗粒物浓度分布特征及其影响因素。选取重庆市典型树种,通过野外实测叶片滞留颗粒物以及利用自制气室实验模拟两种方法,量化评价典型树种阻滞吸附PM2.5的能力,并结合植物生理分析差异原因。主要研究结果如下：(1)重庆市主城区PM2.5和PM10浓度日变化呈现明显的双峰双谷曲线变化。基于ArcGIS研究PM2.5的季节和空间分布。结果表明：季节上,冬季PM2.5浓度最高,气象状况和植被生理活性减弱是影响冬季PM2.5污染降低的主要原因。空间上,PM2.5浓度从市中心到周围区域逐渐降低。研究表明：人类活动频繁、建筑物密度大、交通发达繁忙的区域PM2.5污染较严重；远离城区、绿化和植被覆盖好,人均公用绿地面积大以及邻近水域的地区PM2.5浓度较低。(2)PM2.5为重庆市主城区首要颗粒物污染,商业区污染最为严重,绿地和清洁对照点污染较轻。结合PM2.5空间分布特征和不同土地利用类型分布特征,能够发现植被和水域有助于降低PM2.5污染。(3)大气颗粒物浓度季节变化特征为：冬季春季秋季夏季。四种典型林地中针叶林对PM2.5的阻滞和消减能力较强。降雨对林地内大气颗粒物有明显的降低作用,雨后阴天颗粒物浓度回升较快。(4)野外实测叶片滞留颗粒物的实验结果得到：叶表面滞留的PM2.5颗粒物数量较多；滞留的PM10颗粒物体积占比较多。自制气室模拟试验结果得到：针叶树种滞尘能力远远高于阔叶树种。阔叶树种滞尘能力也有很大差异。(5)植物叶片能有效的滞留颗粒物,叶表面生理结构和粗糙度是影响叶片滞尘能力的两大因素。植物叶片对不同粒径颗粒物的滞留能力差异与叶表面结构有关。
[Abstract]:Particulate matter pollution in the atmosphere has become an important problem in China, and atmospheric particulate matter has an impact on human health, environmental pollution and visibility. At present, the research on atmospheric particulates mainly focuses on the characteristics of source analysis, component analysis, hazard assessment and dynamic change. This study is based on the monitoring data of Chongqing city and the Jinyun Mountain forest of atmospheric particles, using ArcGIS to analyze the influence of temporal and spatial distribution of meteorological factors of atmospheric particulates on the concentration of atmospheric particulate matter; factors of Jinyun Mountain of typical forest atmosphere particle concentration distribution and its influence. Two typical tree species in Chongqing were selected, and the ability of blocking the adsorption of PM2.5 by typical tree species was quantitatively evaluated by field measurement of leaf retained particulate matter and experimental simulation of self-made air chamber. The main results are as follows: (1) the diurnal variation of PM2.5 and PM10 concentration in the main city of Chongqing city shows a obvious change in the double Valley curve of Shuangfeng. Study on the seasonal and spatial distribution of PM2.5 based on ArcGIS. The results showed that in the season, the concentration of PM2.5 in winter was the highest, and the weakening of the meteorological conditions and the physiological activity of vegetation was the main reason for the decrease of the PM2.5 pollution in winter. In space, the concentration of PM2.5 gradually decreases from the center of the city to the surrounding area. The research shows that PM2.5 pollution is more serious in areas where human activities are frequent, buildings are dense and traffic is busy and busy. Far away from urban area, greening and vegetation coverage, the area of public green area per capita is large and the concentration of PM2.5 is relatively low in adjacent waters. (2) PM2.5 is the main particle pollution in the main city of Chongqing, the most serious pollution in the commercial area, and the light pollution of green space and clean control point. Combining the spatial distribution characteristics of PM2.5 and the distribution characteristics of different land use types, it can be found that vegetation and water can help to reduce PM2.5 pollution. (3) the seasonal variation of atmospheric particulates concentration is: winter spring and autumn summer. The Four Typical Forestland coniferous forests have strong ability to block and reduce PM2.5. The rainfall has a significant reduction in the atmospheric particulates in the woodland, and the concentration of particles in the cloudy day after rain increases rapidly. (4) field experiment results showed that the number of PM2.5 particulates retained on the leaf surface was larger than that of the remaining particles, and the retained PM10 particles occupied much more. Homemade chamber simulated test results: dust removal capacity is much higher than that of conifer broadleaf tree species. The dust retention ability of broadleaf species also have very big difference. (5) leaf particles effectively, leaf surface physical structure and roughness are two major factors affecting the blade dust retention ability. The difference of the retention capacity of plant leaves to different particle size particles is related to the structure of the leaf surface.
【学位授予单位】：北京林业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X513;X173

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