Understanding the characteristics of the microenvironments in urban street canyons through analysis of pollution measured using a novel pervasive sensor array.
Understanding the characteristics of the microenvironments in urban street canyons through analysis of pollution measured using a novel pervasive sensor array.
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DOI：
10.1007/s10661-014-3939-7
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发表时间：
2014-11
影响因子：
3
通讯作者：
Hill, Graeme
中科院分区：
文献类型：
--
作者：
Galatioto, Fabio;Bell, Margaret Carol;Hill, Graeme
关键词：
本文介绍了对首批122个商用无线环境无处不在传感器（mote）数据的综合分析结果，这些传感器由纽卡斯尔大学开发并部署在英国。污染、气象和交通的测量被用来调查控制城市地区交通污染水平的物理和化学过程的复杂性。在简要介绍了与空气质量有关的健康影响之后，对远程技术进行了说明。聚类分析统计研究了不同污染物类型与交通数据之间的关系，结果表明，仅使用交通流状态不能估计路边污染物的日浓度。此外，绝对水平虽然依赖于气象条件和静态参数，但仅部分受污染物扩散的控制。该研究清楚地说明了城市微环境中普遍浓度测量的好处和附加价值，有可能有效评估人类对交通相关排放的暴露。
This paper presents results of comprehensive analyses of data from the first 122 commercially available wireless environmental pervasive sensors (motes), developed by Newcastle University and deployed in England. Measurements of pollution, meteorology and traffic are used to investigate the complexity of the physical and chemical processes governing the levels of traffic-related pollution in urban areas. Following a brief introduction on health impacts associated with air quality, description of the mote technology is given. Cluster analysis statistics to investigate the relationship between different pollutant types and traffic data demonstrated that traffic flow regimes alone cannot be used to estimate diurnal kerbside pollutant concentrations. Also, the absolute levels, whilst dependent on meteorological conditions and static parameters are only partially governed by the pollutant dispersion. The research clearly illustrates the benefits and added value of pervasive concentration measurement in urban micro environments with potential to effectively evaluate human exposure to transport-related emissions.
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影响因子：
3.4
作者：
Bell, Margaret Carol;Galatioto, Fabio
通讯作者：
Galatioto, Fabio
影响因子：
7.7
作者：
Gotschi, Thomas;Sunyer, Jordi;Kuenzli, Nino
通讯作者：
Kuenzli, Nino
影响因子：
3.7
作者：
RAND, WM
通讯作者：
RAND, WM
影响因子：
9.8
作者：
Brown, Kathleen Ward;Sarnat, Jeremy A.;Koutrakis, Petros
通讯作者：
Koutrakis, Petros
影响因子：
8
作者：
Liao, TW
通讯作者：
Liao, TW