不同绿地结构消减大气颗粒物的能力

孙晓丹, 李海梅, 刘霞, 徐萌. 不同绿地结构消减大气颗粒物的能力[J]. 环境化学, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
引用本文: 孙晓丹, 李海梅, 刘霞, 徐萌. 不同绿地结构消减大气颗粒物的能力[J]. 环境化学, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
SUN Xiaodan, LI Haimei, LIU Xia, XU Meng. Subduction ability of different green space structure on atmospheric particulate matter[J]. Environmental Chemistry, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
Citation: SUN Xiaodan, LI Haimei, LIU Xia, XU Meng. Subduction ability of different green space structure on atmospheric particulate matter[J]. Environmental Chemistry, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602

不同绿地结构消减大气颗粒物的能力

  • 基金项目:

    山东省青年基金(BS2012NY005),研究生创新立项(760-1215024)和青岛市科技局项目(13-1-4-165-jch)资助.

Subduction ability of different green space structure on atmospheric particulate matter

  • Fund Project: Supported by Youth Fund of Shandong Province(BS2012NY005),Postgraduate technology innovation project(760-1215024) and Qingdao Technology Bureau Project(13-1-4-165-jch).
  • 摘要: 随着城市化和工业化的发展,空气环境问题日益突出,大气颗粒物污染受到人们越来越多的关注.为了研究城市道路中不同绿地结构对大气不同粒径颗粒物的消减作用,本文选择青岛市城阳区主干道——长城路的4种不同绿地结构(“乔-灌-草”、“乔-草”、“乔-灌”、“灌-草”),测定其对不同粒径颗粒物(PM10、PM2.5、PM1)的消减率.结果表明:(1)不同粒径颗粒物的浓度日变化曲线呈现出“早晚高,中午低”的变化趋势,其中8:00-10:00的颗粒物浓度最高;颗粒物浓度日变化与空气湿度变化相一致,与温度变化相反;(2)4种绿地结构对PM10的消减率表现为“乔-灌-草” > “乔-灌” > “灌-草” > “乔-草”,对PM2.5和PM1的消减率表现为“乔-灌-草” > “乔-灌” > “乔-草” > “灌-草”;且各绿地结构对PM2.5的消减能力最强,其次为PM1和PM10;(3)同一种绿地结构,植物种类越丰富,其消减大气颗粒物的能力越强.
  • 加载中
  • [1] 李新宇,赵松婷,李延明,等. 北京市不同主干道绿地群落对大气PM2.5浓度消减作用的影响[J]. 生态环境学报, 2014,23(4):615-621.

    LI X Y, ZHAO S T, LI Y M, et al. Subduction effect of urban arteries green space on atmospheric concentration of PM2.5 in Beijing[J]. Ecology and Environmental Sciences,2014,23(4):615-621(in Chinese).

    [2] 傅伟聪,董嘉莹,王茜,等. 福州市冬季若干典型游憩地大气颗粒物浓度日变化规律研究[J]. 热带作物学报,2014,35(2):348-354.

    FU W C, DONG J Y, WANG Q, et al. Daily changes of atmospheric particulates in several typical recreation sites in Fuzhou City[J]. Chinese Journal of Tropical Crops,2014,35(2):348-354(in Chinese).

    [3] 郭二果,王成,郄光发,等. 北京西山典型游憩林空气颗粒物不同季节的日变化[J]. 生态学报,2009,29(6):3253-3263.

    GUO E G, WANG CH, QIE G F, et al. Diurnal variations of airborne particulate matters in different seasons in typical recreation forests in West Mountain of Beijing[J]. Acta Ecologica Sinaca,2009,29(6):3253-3263(in Chinese).

    [4] CHEN B, LU S W, LI S N, et al. Impact of fine particulate fluctuation and other variables on Beijing's air quality index[J]. Environ Sci Pollut Res,2015,22(7):5139-5152.
    [5] 刘萌萌. 林带对阻滞吸附PM2.5等颗粒物的影响研究[D]. 北京:北京林业大学,2014. LIU M M. Studies on influence of the forest belt to intercept and adsorb particulate matter[D]. Beijing:Beijing Forestry University,2014(in Chinese).
    [6] 陈上杰,牛健植,韩旖旎,等. 道路绿化带内大气PM2.5质量浓度变化特征[J]. 水土保持学报,2015,29(2):100-105.

    CHEN S J, NIU J Z, HAN Y N, et al. Characteristics of mass concentration variations of PM2.5 in the road greenbelts[J]. Journal of Soil and Water Conservation,2015,29(2):100-105(in Chinese).

    [7] 李素莉,杨军,马履一,等. 北京市交通干道防护林带内PM2.5浓度变化特征[J]. 西北林学院学报,2015,30(3):245-252.

    LI S L, YANG J, MA L Y, et al. Variations of PM2.5 concentrations inside the greenbelts along two urban traffic arteries in Beijing[J]. Journal of Northwest Forestry University,2015,30(3):245-252(in Chinese).

    [8] 刘宇,黄旭,偶春,等. 夏季不同结构绿地空气PM2.5浓度与气候因子关系[J]. 西北林学院学报,2015,30(5):241-245.

    LI Y, HUANG X, OU C, et al. Relationships between PM2.5 concentrations in different greenbelts and climate factors in summer[J]. Journal of Northwest Forestry University,2015,30(5):241-245(in Chinese).

    [9] 郑少文,邢国明,李军,等. 不同绿地类型的滞尘效应比较[J]. 山西农业科学,2008,36(5):70-72.

    ZHENG S W, XING G M, LI J, et al. Comparison of dust catching capacity of different greenbelt types[J]. Journal of Shanxi Agricultural Sciences,2008,36(5):70-72(in Chinese).

    [10] 童明坤,王吉喜,田美荣,等. 北京市道路绿地消减PM2.5总量及其健康效益评估[J]. 中国环境科学,2015,35(9):2861-2867.

    TONG M K, WANG J X, TIAN M R, et al. Subduction of PM2.5 by road green space in Beijing and its health benefit evaluation[J]. China Environmental Science,2015,35(9):2861-2867(in Chinese).

    [11] 王国玉,白伟岚,李新宇,等. 北京地区消减PM2.5等颗粒物污染的绿地设计技术探析[J]. 中国园林,2014,30(7):70-76.

    WANG G Y, BAI W L, LI X Y, et al. Research of greenbelt design technology on PM2.5 pollution reduction in Beijing[J]. Chinese Garden,2014,30(7):70-76(in Chinese).

    [12] 陈博,王小平,刘晶岚,等. 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[J]. 生态环境学报,2015,24(7):1171-1181.

    CHEN B, WANG X P, LIU J L, et al. Mass concentration variations of airborne particulate matters inside and outside of a landscape ecological forest under different weather conditions[J]. Ecology and Environmental Sciences, 2015,24(7):1171-1181(in Chinese).

    [13] 陈波,鲁绍伟,李少宁. 北京城市森林不同天气状况下PM2.5浓度变化[J]. 生态学报,2016,36(5):1391-1399.

    CHEN B, LU SH W, LI S N. Dynamic analysis of PM2.5 concentrations in urban forests in beijing for various weather conditions[J]. Acta Ecologica Sinaca,2016,36(5):1391-1399(in Chinese).

    [14] 罗娜娜,赵文吉,晏星,等. 交通与气象因子对不同粒径大气颗粒物的影响机制研究[J]. 环境科学,2013,34(10):3741-3748.

    LUO N N, ZHAO W J, YAN X, et al. Study on influence of traffic and meteorological factors on inhalable particle matters of different size[J]. Environmental Science,2013,34(10):3741-3748(in Chinese).

    [15] 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.

    WANG X L, WANG C, GU L, et al. Concentration variations of atmospheric particulate matters in street greenbelts under typical weather conditions in spring[J]. Chinese Journal of Ecology,2014,33(11):2889-2896(in Chinese).

    [16] 廖莉团,苏欣,李小龙,等. 城市绿化植物滞尘效益及滞尘影响因素研究概述[J]. 森林工程,2014,30(2):21-24.

    LIAO L T, SU X, LI X L, et al. Review on the purification effects of urban landscape plants and factors affecting detaining dust[J]. Forest Engineering,2014,30(2):21-24(in Chinese).

  • 加载中
计量
  • 文章访问数:  1382
  • HTML全文浏览数:  1340
  • PDF下载数:  436
  • 施引文献:  0
出版历程
  • 收稿日期:  2016-09-26
  • 刊出日期:  2017-02-15
孙晓丹, 李海梅, 刘霞, 徐萌. 不同绿地结构消减大气颗粒物的能力[J]. 环境化学, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
引用本文: 孙晓丹, 李海梅, 刘霞, 徐萌. 不同绿地结构消减大气颗粒物的能力[J]. 环境化学, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
SUN Xiaodan, LI Haimei, LIU Xia, XU Meng. Subduction ability of different green space structure on atmospheric particulate matter[J]. Environmental Chemistry, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602
Citation: SUN Xiaodan, LI Haimei, LIU Xia, XU Meng. Subduction ability of different green space structure on atmospheric particulate matter[J]. Environmental Chemistry, 2017, 36(2): 289-295. doi: 10.7524/j.issn.0254-6108.2017.02.2016092602

不同绿地结构消减大气颗粒物的能力

  • 1.  青岛农业大学园林与林学院, 青岛, 266109;
  • 2.  山东绿城市政园林工程有限公司, 聊城, 252000
基金项目:

山东省青年基金(BS2012NY005),研究生创新立项(760-1215024)和青岛市科技局项目(13-1-4-165-jch)资助.

摘要: 随着城市化和工业化的发展,空气环境问题日益突出,大气颗粒物污染受到人们越来越多的关注.为了研究城市道路中不同绿地结构对大气不同粒径颗粒物的消减作用,本文选择青岛市城阳区主干道——长城路的4种不同绿地结构(“乔-灌-草”、“乔-草”、“乔-灌”、“灌-草”),测定其对不同粒径颗粒物(PM10、PM2.5、PM1)的消减率.结果表明:(1)不同粒径颗粒物的浓度日变化曲线呈现出“早晚高,中午低”的变化趋势,其中8:00-10:00的颗粒物浓度最高;颗粒物浓度日变化与空气湿度变化相一致,与温度变化相反;(2)4种绿地结构对PM10的消减率表现为“乔-灌-草” > “乔-灌” > “灌-草” > “乔-草”,对PM2.5和PM1的消减率表现为“乔-灌-草” > “乔-灌” > “乔-草” > “灌-草”;且各绿地结构对PM2.5的消减能力最强,其次为PM1和PM10;(3)同一种绿地结构,植物种类越丰富,其消减大气颗粒物的能力越强.

English Abstract

参考文献 (16)

返回顶部

目录

/

返回文章
返回