Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.
Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.
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DOI：
10.3390/s17102263
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发表时间：
2017-10-02
期刊：
影响因子：
--
通讯作者：
Citi-Sense Project Collaborators
中科院分区：
文献类型：
--
作者：
Broday DM;Citi-Sense Project Collaborators
评估空气污染对公众健康和人类福祉的影响需要可靠的数据。标准的空气质量监测站提供了对空气污染物水平的精确测量，但是，由于它们的稀疏分布，它们不能准确地捕捉城市内空气污染物浓度的空间变化。专门的深入实地活动具有密集的测量空间覆盖范围，但持续时间相对较短。因此，他们的代表性是有限的。此外，通常积分的测量值代表时间平均记录。通信和传感器技术的最新进展，使密集的网格部署的无线分布式环境传感器网络的空气质量监测，但他们的能力，以捕捉城市规模的时空污染物模式尚未得到彻底检查。在这里，我们总结了我们的研究使用传感器节点的数据流的空气质量测量和所需的方法来调整结果，以不同的利益相关者和应用程序的实用性。我们总结了来自欧洲八个城市的结果，五种传感器技术-三种固定的（其中一种在移动时也进行了测试）和两种个人传感器平台，以及八种环境污染物。总体而言，很少有传感器表现出特殊的和一致的性能，这可以揭示精细的时空城市污染物浓度的变化。固定的传感器节点比个人节点更可靠。一般来说，传感器测量往往受到各种环境因素的干扰，需要频繁校准。这就要求开发合适的现场校准程序，并提出了几个这样的现场校准。
The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.
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影响因子：
4.3
作者：
Hasenfratz, David;Saukh, Olga;Thiele, Lothar
通讯作者：
Thiele, Lothar
影响因子：
5
作者：
Mead, M. I.;Popoola, O. A. M.;Jones, R. L.
通讯作者：
Jones, R. L.
DOI：
10.3390/s130607079
发表时间：
2013-05-29
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Gibson D;MacGregor C
通讯作者：
MacGregor C
影响因子：
4.5
作者：
Manikonda, Abhisek;Zikova, Nadezda;Ferro, Andrea R.
通讯作者：
Ferro, Andrea R.
影响因子：
5
作者：
Kanaroglou, PS;Jerrett, M;Brook, JR
通讯作者：
Brook, JR