雁荡山杉木林夏季空气颗粒物的垂直空间变化特征
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摘要
[目的]研究森林空气颗粒物的不同高度垂直空间变化特征,为森林康养环境利用提供理论依据。[方法]于2017年5月对温州雁荡山杉木林林下(人体高度1.5 m)、林冠中部(6 m)及林冠顶部(12 m)3个高度的空气颗粒物质量浓度(TSP、PM_(10)、PM_(2.5)、PM_(1.0))进行同步昼夜24 h监测,分析空气颗粒物质量浓度的空间变化规律。[结果]表明:(1)杉木林垂直空间不同粒径颗粒物的质量浓度存在差异,总颗粒物质量浓度与细颗粒物(<2.5μm)质量浓度在3种高度差异显著,均为林冠层最低;(2)3种不同高度的TSP、PM_(10)质量浓度日均值均达到二类环境功能区质量要求(300、150μg·m~(-3)),其中,林冠层的TSP日均值达到一类环境功能区质量要求(120μg·m~(-3));(3)不同高度各粒径空气颗粒物日变化规律大体一致,均表现为白天低,夜间高;(4)不同垂直高度空气颗粒物质量浓度,白天为林冠层最低;夜间为TSP质量浓度各垂直高度差别不大,PM_(10)、PM_(2.5)与PM_1质量浓度总体为在人体高度较低;(5)各粒径空气颗粒物与露点温度极显著正相关,与气压极显著负相关,其中,PM_(2.5)质量浓度与2项环境因子相关系数最大;除TSP外,其余颗粒物质量浓度与温度、最大风速极显著正相关,与相对湿度极显著负相关,各气象因子共同影响空气颗粒物质量浓度。[结论]通过对结果的综合分析,温州雁荡山杉木林环境林冠层为康养游憩最佳高度,最适宜白天出行。
[Objective] To study the variation of air particles with different vertical heights and provide theoretical basis for the construction and utilization of forest therapy. [Method] In this paper, the mass concentrations of TSP, PM_(10), PM_(2.5), and PM_1 at the height of human body(1.5 m), the middle of forest canopy(6 m), the canopy upper layer(12 m) of Cunninghamia lanceolata forest were observed for 24 hours in summer of 2017 with a cloudy weather in the Yandangshan of Wenzhou. [Result] 1.The mass concentrations of different-sized particle matters varied in different heights. There was a significant difference between the TSP and PM_(2.5), that of the middle of forest canopy were all the lowest in three heights. 2.The daily mean mass concentrations of TSP and PM_(10 )in the three heights were all reached the grad-Ⅱof national standard for urbanized area ambient air quality, and the concentrations of TSP in forest canopy reached the standard grade-Ⅰ. 3.During the observation period, the concentrations of particle matter in different heights were higher at night, and lower in the daytime. 4.The middle of canopy(H2) of air particulate matter in different vertical height was the lowest in the day time; there was no significant difference in TSP mass concentration in three heights, the mass concentrations of PM_(10), PM_(2.5) and PM_1 were generally low in human height at night. 5. The concentrations of four kinds of particles were significantly positively correlated with dew temperature and negatively correlated with air pressure. The correlation coefficient between PM_(2.5 )and both factors was the largest. The concentrations of PM_(10), PM_(2.5), and PM_(1 )were significantly positively correlated with temperature as well as maximum wind velocity, and negatively correlated with relative humidity. Every meteorological factor affected the mass concentration of air particles. [Conclusion] The middle of canopy is the best height for recreation in C. lanceolata forest in the Yandangshan of Wenzhou. It is most suitable for daytime travel.
[Objective] To study the variation of air particles with different vertical heights and provide theoretical basis for the construction and utilization of forest therapy. [Method] In this paper, the mass concentrations of TSP, PM_(10), PM_(2.5), and PM_1 at the height of human body(1.5 m), the middle of forest canopy(6 m), the canopy upper layer(12 m) of Cunninghamia lanceolata forest were observed for 24 hours in summer of 2017 with a cloudy weather in the Yandangshan of Wenzhou. [Result] 1.The mass concentrations of different-sized particle matters varied in different heights. There was a significant difference between the TSP and PM_(2.5), that of the middle of forest canopy were all the lowest in three heights. 2.The daily mean mass concentrations of TSP and PM_(10 )in the three heights were all reached the grad-Ⅱof national standard for urbanized area ambient air quality, and the concentrations of TSP in forest canopy reached the standard grade-Ⅰ. 3.During the observation period, the concentrations of particle matter in different heights were higher at night, and lower in the daytime. 4.The middle of canopy(H2) of air particulate matter in different vertical height was the lowest in the day time; there was no significant difference in TSP mass concentration in three heights, the mass concentrations of PM_(10), PM_(2.5) and PM_1 were generally low in human height at night. 5. The concentrations of four kinds of particles were significantly positively correlated with dew temperature and negatively correlated with air pressure. The correlation coefficient between PM_(2.5 )and both factors was the largest. The concentrations of PM_(10), PM_(2.5), and PM_(1 )were significantly positively correlated with temperature as well as maximum wind velocity, and negatively correlated with relative humidity. Every meteorological factor affected the mass concentration of air particles. [Conclusion] The middle of canopy is the best height for recreation in C. lanceolata forest in the Yandangshan of Wenzhou. It is most suitable for daytime travel.
引文
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[26] 马远,贾雨龙,王成,等.北京市典型道路防护林滞尘时空分布及其影响因子分析[J].林业科学研究,2018,31(5):110-117.
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[30] 陶燕,刘亚梦,米生权,等.大气细颗粒物的污染特征及对人体健康的影响[J].环境科学学报,2014,34(3):592-597.
[2] Yang Gao,Xinyue Guo,Cai Li,et al.Characteristics of PM2.5 in Miyun,the northeastern suburb of Beijing:chemical composition and evaluation of health risk[J].Environmental Science and Pollution Research,2015,22 (21):16688-16699.
[3] Strand Matthew,Hopke Philip K,Zhao Weixiang,et al.A study of health effect estimates using competing methods to model personal exposures to ambient PM2.5[J].Journal of Exposure Science and Environmental Epidemiology,2007,17 (6):549-558.
[4] 杜万光,王成,王茜,等.春季旗山福建柏林内外空气颗粒物变化特征[J].环境科学与技术,2017,40(10):176-184.
[5] 侯贻菊,丁访军,刘延惠,等.贵阳东郊针阔混交林内外空气颗粒物不同季节的日变化[J].江苏农业科学,2017,45(19):280-285.
[6] 古琳,王成,王艳英,等.夏季持续高温天气下无锡惠山游憩林内空气颗粒物变化特征[J].林业科学,2013,49(10):66-73.
[7] 段文军,王成,张昶,等.夏季3种生境森林内空气颗粒物变化特征[J].北京林业大学学报,2017,39(5):73-81.
[8] 王晓磊,王成,古琳,等.春季典型天气下城市街头绿地内大气颗粒物浓度变化特征[J].生态学杂志,2014,33(11):2889-2896.
[9] 高敏,仇天雷,贾瑞志,等.北京雾霾天气生物气溶胶浓度和粒径特征[J].环境科学,2014,35(12):4415-4421.
[10] 欧阳勋志,廖为明,彭世揆.天然阔叶林景观质量评价及其垂直结构优化技术[J].应用生态学报,2007,18(6):1388-1392.
[11] 刘奇,孙楠.修枝强度对硬阔叶混交林主要树种生长的影响[J].黑龙江生态工程职业学院学报,2015,28(3):11-13.
[12] 郑景明,张春雨,周金星,等.云蒙山典型森林群落垂直结构研究[J].林业科学研究,2007,20(6):768-774.
[13] 曹玉昆,雷礼纲,张瑾瑾.我国林下经济集约经营现状及建议[J].世界林业研究,2014,27(6):60-64.
[14] Cox Louis A,Popken Douglas A,Ricci Paolo F.Warmer is healthier:Effects on mortality rates of changes in average fine particulate matter (PM2.5) concentrations and temperatures in 100 U.S.cities[J].Regulatory Toxicology and Pharmacology,2013,66 (3):336-346.
[15] 赵晨曦,王云琦,王玉杰,等.北京地区冬春 PM2.5和 PM10污染水平时空分布及其与气象条件的关系[J].环境科学,2014,35(2):418-427.
[16] 邓利群,钱骏,廖瑞雪,等.2009年8-9 月成都市颗粒物污染及其与气象条件的关系[J].中国环境科学,2012,32(8):1433-1438.
[17] Henian Zhang,Yuhang Wang,et al.Quantifying the relationship between extreme air pollution events and extreme weather events[J].Atmospheric Research,2016,188:64-79
[18] 杨叶.矿业城市大气颗粒物粒径及水溶性离子分布特征[D].安徽:安徽大学,2016.
[19] 林俊,刘卫,李燕,等.大气气溶胶粒径分布特征与气象条件相关性分析[J].气象与环境学报,2013,25(1):1-5.
[20] 孙启祥,彭镇华,张齐生.自然状态下杉木木材挥发物成分及其对人体身心健康的影响[J].安徽农业大学学报,2004,31(2):158-163.
[21] Powe N A,Willis K G.Mortality and morbidity benefits of air pollution (SO2,PM10) absorption attributable to woodland in Britain[J].Journal of Environmental Management,2004,70(2):119-128.
[22] Latha Madhavi K,Badarinath KVS.Seasonal variations of PM10 and PM2.5 particles loading over tropical urban environment[J].International Journal of Environmental Health Research,2005,15 (1):63-68.
[23] 邵龙义,时宗波.都市大气环境中可吸入颗粒物的研究[J].环境保护,2000(1):24-26.
[24] Glavas S D,Nikolakis P,Ambatzoglou D,et al.Factors affecting the seasonal variation of mass and ionic composition of PM2.5 at a central Mediterranean coastal site[J].Atmospheric Environment,2008,42 (21):5365-5373.
[25] 王萌,刘一超,梁琼,等.北京城市森林公园不同树种吸附大气颗粒物能力[J].北京农学院学报,2018,33(1):79-83.
[26] 马远,贾雨龙,王成,等.北京市典型道路防护林滞尘时空分布及其影响因子分析[J].林业科学研究,2018,31(5):110-117.
[27] 马远,贾雨龙,王成,等.北京市3种道路防护林春季滞尘规律研究[J].林业科学研究,2018,31(2):147-155.
[28] Zhang Hua,Li Fengrui,Zhang Tonghui,et al.Yasuhito Shirato.Evaluation of ecological services of Populus simonii forest on Heerqin sandy land[J].Yingyong Shengtai Xuebao,2004,14(10):1591-1596.
[29] Vecchi R,Marcazzan G,Valli M,et al.The role of atmospheric dispersion in the seasonal variation of PM1 and PM2.5 concentration and composition in the urban area of Milan (Italy)[J].Atmospheric Environment.2004,38 (27):4437-4446.
[30] 陶燕,刘亚梦,米生权,等.大气细颗粒物的污染特征及对人体健康的影响[J].环境科学学报,2014,34(3):592-597.
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