文献类型：期刊文献

中文题名：不同天气下景观生态林内外大气颗粒物质量浓度变化特征

英文题名：Mass Concentration Variations of Airborne Particulate Matters Inside and Outside of A Landscape Ecological Forest under Different Weather Conditions

作者：陈博[1] 王小平[1] 刘晶岚[2] 陈峻崎[3] 朱建刚[3] 李春义[4]

第一作者：陈博

机构：[1]北京林业大学林学学院;[2]北京林业大学保护区学院;[3]北京市林业碳汇工作办公室;[4]中国林业科学研究院湿地研究所

年份：2015

卷号：24

期号：7

起止页码：1171-1181

中文期刊名：生态环境学报

外文期刊名：Ecology and Environmental Sciences

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：国家林业公益性行业科研项目(201304301);中央级公益性科研院所基本科研业务费专项资金(CAFINT2015C12)

语种：中文

中文关键词：不同天气条件;景观生态林;大气颗粒物;质量浓度

外文关键词：different weather condition;landscape ecological forest;airborne particulate matter;mass concentration

分类号：X16

摘要：为了探讨景观生态林对大气颗粒物的调控作用,以北京大兴区景观生态林为例(主要树种为旱柳Salix matsudana),研究不同季节、不同天气条件下景观生态林内大气颗粒物质量浓度差异以及林内和林外质量浓度对比。于2013年7月至2014年5月,分四季选择不同天气类型,采用水平同步监测法对林内和林外两个监测点3种粒径大气颗粒物(TSP、PM10和PM2.5)质量浓度和气象因子进行每日10 h的连续监测(8:00─18:00)。结果表明,(1)晴朗天气景观生态林内ρ(TSP)、ρ(PM10)和ρ(PM2.5)均处于较低水平,分别为(61.53±21.73)^(174.32±36.01)μg·m-3、(28.91±10.34)^(94.87±20.45)μg·m-3和(6.29±3.86)^(23.91±12.29)μg·m-3;多云、扬尘、雾霾和雾霭天气颗粒物质量浓度较高,污染明显加重,雾霾天气下ρ(PM2.5)的增加效果更为明显,而扬尘天气下ρ(TSP)显著增加。(2)雾滴对于PM2.5与PM10具有一定的湿清除作用,也可以与霾粒子共同作用形成相对稳定的雾霭天气,其颗粒物污染程度高于其他天气状况,此时以粒径为2.5~10μm的颗粒物污染为主。(3)夏、秋和春季晴朗微风天气(风速≤3 m·s-1)和扬尘天气林内ρ(TSP)和ρ(PM10)显著低于林外,多云、轻微至轻度雾霾天气,林内ρ(TSP)、ρ(PM10)和ρ(PM2.5)均显著低于林外,晴朗大风(风速>5 m·s-1)和雾霭天气林内ρ(TSP)和ρ(PM10)不显著高于林外,雾霭天气林内ρ(PM2.5)显著高于林外;冬季不同天气下ρ(TSP)、ρ(PM10)和ρ(PM2.5)林内和林外对比没有明显规律。(4)空气相对湿度、风速和风向是观测时段内影响颗粒物质量浓度的主要因子。ρ(PM2.5)与相对湿度呈线性正相关,而与风速呈非线性负相关,偏南风对颗粒物主要起输送和积累作用,偏北风对颗粒物起到稀释和扩散作用。相对于TSP和PM10,PM2.5更易受近地面气象条件的影响而堆积或扩散。
To investigate the role of landscape ecological forests in controlling airborne particulate matters, this paper took a landscape ecological forest with dominating tree species ofSalix matsudanin Daxing District of Beijing as an example to research the mass concentration variations of airborne particulate matters inside the landscape ecological forest and the mass concentration comparisons inside and outside the forest in different seasons and different weather conditions. The daily mass concentrations of TSP, PM10 and PM2.5 as well as meteorological factors （8：00─18：00） were measured using horizontal synchronous monitoring method inside and outside the forest during one year period （July, 2013 to May, 2014）. The results indicated that： （1） Daily meanρ（TSP）,ρ（PM10） andρ（PM2.5） inside the forest were lower in sunny days than those under other weather conditions. These concentrations were （61.53±21.73）-（174.32±36.01）μg·m-3, （28.91±0.34）-（94.87±20.45）μg·m-3and （6.29±3.86）-（23.91±12.29）μg·m-3, respectively; cloud, dust, haze and fog aggravated the pollution of particulate matters; increased amplitudes of finer particulate matters were larger in hazy days, while those of coarser particulate matters were larger in dry windy days. （2） Fog droplets could reduceρ（PM10） andρ（PM2.5）, but these droplets with haze nuclei could also cause serious air pollution, when 2.5-10μm particles were the main pollutant of airborne particulate matters. （3） During summer, autumn and spring,ρ（TSP） andρ（PM10） were significantly lower inside the forest than those outside the forest in sunny days （wind speed≤ 3 m·s-1） or dusty days,ρ（TSP）,ρ（PM10） andρ（PM2.5） were all significantly lower inside the forest in cloudy and slight hazy days, while the comparison results in sunny days （wind speed 〉 5 m·s-1） and foggy days were contrary. During winter,ρ（TSP）,ρ（PM10） andρ（PM2.5） inside the forest had no significant difference with those outside the forest. And （4） air relative humidity, wind speed and wind direction were the main meteorological factors affecting particles concentrations in this study. The daily averageρ（PM2.5） had significant linear positive correlation with relative humidity and nonlinear negative correlation with wind speed; southerly wind had a major role in exacerbating the air pollution of particulate matters, while northerly flow played important role of effective dilution and diffusion of these matters in monitoring sites.ρ（PM2.5）was more likely to be affected by meteorological factorsthanρ（TSP） andρ（PM10）.