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Relationship between Air Pollution and Urban Forms: Evidence from Prefecture-Level Cities of the Yangtze River Basin

机译:空气污染与城市形态的关系:来自长江流域地级市的证据

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摘要

Urban forms, such as size, shape, density, compactness, and fragmentation, are associated with local air pollution concentrations. However, empirical analyses on how urban form improves or degrades urban air quality are still limited and inconclusive, especially for those rapidly expanding cities in developing countries. In this study, by using the improved STIRPAT (stochastic impacts by regression on population, affluence, and technology) model, the quantitative impact of urban form on near-surface PM2.5 and NO2 concentrations was identified in the 10 prefecture-level cities of the Yangtze River Basin (YRB) from 2000 to 2013. Trend analyses showed a significant increasing trend in both PM2.5 (9.69 × 10−4 µg·m−3·year−1) and NO2 (1.73 × 10−4 ppb·year−1) for the whole study period. Notably, a turning point of PM2.5 from increasing to decreasing trends occurred around 2007. In addition, both pollutants showed a spatial agglomeration. The STIRPAT model demonstrated that socioeconomic, transportation and urban form factors played an important role in alleviating the increase of PM2.5 and NO2. In particular, a 1% decrease in urban extent density (UED) significantly increased NO2 by 0.203%, but reduced PM2.5 by 0.033%. The proximity index (PI) measured as a city’s compactness was significantly negatively correlated with PM2.5 and NO2. Conversely, a significant positive relationship of PM2.5 and NO2 concentrations against the openness index (OI) was observed, an important variable for measuring a city’s fragmentation. In addition, the environmental Kuznets curve (EKC) hypothesis between per capita GDP and PM2.5 concentration was confirmed but failed in NO2. Overall, this study encouraged a less fragmented and more compact urban form, which helped alleviate local air pollution concentrations by enhancing urban connectivity, reducing vehicle dependence, and facilitating the use of bicycles and walking.
机译:城市形式,例如大小,形状,密度,紧凑性和碎片化,与当地空气污染浓度有关。但是,关于城市形态如何改善或降低城市空气质量的实证分析仍然是有限的,也没有定论,特别是对于那些发展中国家迅速扩张的城市而言。在这项研究中,通过使用改进的STIRPAT(回归对人口,富裕程度和技术的随机影响)模型,在10个地级市中确定了城市形态对近地表PM2.5和NO2浓度的定量影响。长江流域(YRB)从2000年到2013年。趋势分析显示,PM2.5均显着增加(9.69×10 −4 µg·m −3 ·整个研究期间的年 −1 )和二氧化氮(1.73×10 −4 ppb·year −1 )。值得注意的是,PM2.5从上升趋势到下降趋势的转折点出现在2007年左右。此外,两种污染物都显示出空间聚集现象。 STIRPAT模型表明,社会经济,交通运输和城市形态因素在缓解PM2.5和NO2的增加方面发挥了重要作用。特别是,城市范围密度(UED)降低1%会使二氧化氮增加0.203%,而PM2.5减少0.033%。衡量城市紧凑程度的接近度指数(PI)与PM2.5和NO2呈显着负相关。相反,观察到PM2.5和NO2浓度与开放度指数(OI)之间存在显着的正相关关系,而开放度指数是衡量城市碎片化程度的重要变量。另外,人均GDP与PM2.5浓度之间的环境库兹涅茨曲线(EKC)假设得到了证实,但二氧化氮却失败了。总体而言,这项研究鼓励了分散的,紧凑的城市形式,通过增强城市连通性,减少车辆依赖性以及便利使用自行车和步行来减轻局部空气污染。

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