Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China
Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China
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中国广州城市居民住宅绿化、空气污染与心理健康
DOI：
10.1016/j.scitotenv.2019.134843
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发表时间：
2019
影响因子：
9.8
通讯作者：
Guanghui Dong
中科院分区：
文献类型：
--
作者：
Ruoyu Wang;Boyi Yang;Yao Yao;Michael S. Bloom;Zhiqiang Feng;Yuan Yuan;Jinbao Zhang;Penghua Liu;Wenjie Wu;Yi Lu;Gergo Baranyi;Rong Wu;Ye Liu;Guanghui Dong
中国的快速城市化导致城市人口暴露于空气污染水平的增加和植被暴露水平的下降。这两种趋势都可能对心理健康构成威胁。以往关于绿化、空气污染和心理健康之间相互关系的研究依赖于来自遥感数据的暴露测量，这可能无法准确捕捉到人们如何感知地面上的植被。为了解决这一研究空白，本研究旨在探讨社区绿化、空气污染暴露和心理健康之间的关系，利用居住在中国广州35个社区的1029名成年人的调查数据。我们使用归一化植被指数（NDVI）和街景绿化（SVG）来评估邻里水平的绿化暴露，并在生成街景绿化暴露指标时区分树木（SVG-tree）和草（SVG-grass）。我们使用两种客观测量（pm2.5和no2浓度）和一种主观测量（感知空气污染）来量化空气污染暴露。我们使用世界卫生组织幸福指数（WHO-5）对心理健康进行量化。多层结构方程模型（SEM）结果表明，在平行中介模型中，SVG-grass与心理健康的关系完全由感知空气污染和NO2介导，而SVG-tree与心理健康的关系完全由环境PM2.5、NO2和感知空气污染介导。三种空气污染指标均未介导心理健康与NDVI之间的关联。在序列中介模型中，空气污染措施没有中介NDVI与心理健康之间的关系。虽然SVG-grass与心理健康评分之间的联系部分由no2感知空气污染介导，但SVG-tree与环境pm2.5感知空气污染和no2感知空气污染同时介导。我们的研究结果表明，与草相比，行道树可能与较低的空气污染水平和更好的心理健康更相关。
China’s rapid urbanization has led to an increasing level of exposure to air pollution and a decreasing level of exposure to vegetation among urban populations. Both trends may pose threats to psychological well-being. Previous studies on the interrelationships among greenness, air pollution and psychological well-being rely on exposure measures from remote sensing data, which may fail to accurately capture how people perceive vegetation on the ground. To address this research gap, this study aimed to explore relationships among neighbourhood greenness, air pollution exposure and psychological well-being, using survey data on 1029 adults residing in 35 neighbourhoods in Guangzhou, China. We used the Normalized Difference Vegetation Index (NDVI) and streetscape greenery (SVG) to assess greenery exposure at the neighbourhood level, and we distinguished between trees (SVG-tree) and grasses (SVG-grass) when generating streetscape greenery exposure metrics. We used two objective (PM2.5and NO2concentrations) measures and one subjective (perceived air pollution) measure to quantify air pollution exposure. We quantified psychological well-being using the World Health Organization Well-Being Index (WHO-5). Results from multilevel structural equation models (SEM) showed that, for parallel mediation models, while the association between SVG-grass and psychological well-being was completely mediated by perceived air pollution and NO2, the relationship between SVG-tree and psychological well-being was completely mediated by ambient PM2.5, NO2and perceived air pollution. None of three air pollution indicators mediated the association between psychological well-being and NDVI. For serial mediation models, measures of air pollution did not mediate the relationship between NDVI and psychological well-being. While the linkage between SVG-grass and psychological well-being scores was partially mediated by NO2-perceived air pollution, SVG-tree was partially mediated by both ambient PM2.5-perceived air pollution and NO2-perceived air pollution. Our results suggest that street trees may be more related to lower air pollution levels and better mental health than grasses are.