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首页> 外文期刊>Building and Environment >Effects of neighborhood green space on PM_(2.5) mitigation: Evidence from five megacities in China
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Effects of neighborhood green space on PM_(2.5) mitigation: Evidence from five megacities in China

机译：邻里绿地对PM_（2.5）缓解的影响：来自中国五大兆瓦的证据

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摘要

Airborne particulate matter (PM) has been a major threat to air quality and public health in major cities in China for more than a decade. Green space has been deemed to be effective in mitigating PM pollution; however, few studies have examined its effectiveness at the neighborhood scale. In this study, the authors probe the contributions from different landscape components in the green space (i.e., tree, grass), as well as the spatial scale of planning on fine PM (PM2.5) concentrations in urban neighborhoods. PM2.5 data including 37 samples from five megacities were collected from the National Environmental Monitoring Centre in China. Results showed that, neighborhood green space greatly contributed to the spatial variation in PM2.5. The total green space coverage, tree coverage, and grass coverage were all negatively correlated with PM2.5 concentration (p 0.05). The higher green space coverage the site had, the lower the daily mean, daily minimum, and daily maximum of PM2.5 concentration were there. Tree coverage, in particular, was effective in reducing the PM2.5 concentrations, and, more importantly, its effectiveness was more significant with the higher ambient PM2.5 level. According to the examination on the effect of spatial scale, the capability for a neighborhood green space to attenuate PM2.5 pollution would be vanished when its size smaller than 200 m, and would be maximized when its size within 400-500 m. These results will contribute to the evidence-based design and management of green space to mitigating urban PM pollution.
机译：空气颗粒物质（PM）对中国主要城市的空气质量和公共卫生的主要威胁成为十多年。绿色空间被认为是减轻PM污染的有效性;然而，很少有研究已经检查了邻里规模的有效性。在这项研究中，作者探讨了绿色空间（即树，草）中不同景观成分的贡献，以及城市社区中PM 2（PM2.5）浓度的规划空间规模。 PM2.5包括来自中国国家环境监测中心的37个样本的数据，包括来自中国的国家环境监测中心。结果表明，邻域绿色空间大大促进了PM2.5的空间变化。绿色空间覆盖，树覆盖度和草覆盖率都与PM2.5浓度负相关（P <0.05）。该网站的绿色空间覆盖率较高，每日平均值，每日最低和每日PM2.5浓度的日常最小值均越低。特别是树木覆盖率在减少PM2.5浓度方面有效，更重要的是，其有效性与较高的环境PM2.5水平更为显着。根据空间尺度的影响，当其尺寸小于200米的尺寸时，邻域绿色空间能够衰减PM2.5污染的能力将消失，并且在400-500米范围内的尺寸将最大化。这些结果将有助于循证的设计和管理绿色空间，以减轻城市PM污染。

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  • 来源
    《Building and Environment》 |2019年第6期|33-45|共13页
  • 作者

    Chen Ming; Dai Fei; Yang Bo; Zhu Shengwei;

  • 作者单位

    Huazhong Univ Sci & Technol Sch Architecture & Urban Planning Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci & Technol Sch Architecture & Urban Planning Wuhan 430074 Hubei Peoples R China;

    Univ Arizona Sch Landscape Architecture & Planning Tucson AZ 85719 USA;

    Univ Maryland Dept Mech Engn College Pk MD 20740 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Green space; Fine particulate matter; Neighborhood; Measured data;

    机译：绿色空间;细颗粒物质;邻里;测量数据;

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