https://scholars.lib.ntu.edu.tw/handle/123456789/380096
標題: | Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework | 作者: | TZAI-HUNG WEN JOE-AIR JIANG Chih-Hong Sun JEHN-YIH JUANG Tzu-Shiang Lin |
關鍵字: | Geographic information system (GIS); Real-time monitoring; Street-level air quality; Wireless sensor network (WSN) | 公開日期: | 十一月-2013 | 卷: | 10 | 期: | 12 | 起(迄)頁: | 6380--6396 | 來源出版物: | IJERPH | 摘要: | Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. © 2013 by the authors; licensee MDPI, Basel, Switzerland. |
URI: | http://scholars.lib.ntu.edu.tw/handle/123456789/380096 | DOI: | 10.3390/ijerph10126380 | SDG/關鍵字: | carbon monoxide; air quality; atmospheric pollution; carbon monoxide; environmental monitoring; GIS; monitoring system; pollution exposure; sensor; spatial resolution; spatiotemporal analysis; traffic emission; urban pollution; visualization; air pollution; air quality; article; car; controlled study; environmental monitoring; geographic information system; pollutant; semiconductor; sensor; signal processing; Taiwan; urban area; wireless communication; wireless sensor network; Taipei; Taiwan; Air Pollutants; Carbon Monoxide; Cities; Environmental Exposure; Environmental Monitoring; Humans; Pilot Projects; Risk Assessment; Taiwan; Wireless Technology |
顯示於: | 地理環境資源學系 |
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