Sensor-based Wireless Air Quality Monitoring Network (SWAQMN) - A smart tool for urban air quality management

被引:26
|
作者
Gulia, Sunil [1 ]
Prasad, Poonam [2 ]
Goyal, S. K. [1 ]
Kumar, Rakesh [2 ]
机构
[1] Natl Environm Engn Res Inst, Delhi Zonal Ctr, CSIR, New Delhi, India
[2] Natl Environm Engn Res Inst, CSIR, Nagpur, Maharashtra, India
关键词
Optical sensors; Sensor-based wireless air quality monitoring network; Low-cost; Polludrone; Urban air quality management; LOW-COST; EXPOSURE ASSESSMENT; POLLUTION; PM2.5; FINE;
D O I
10.1016/j.apr.2020.06.016
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An air quality monitoring network (AQMN) having the ability to provide high spatial resolution real-time information is one of the key tools for developing management strategies for air quality improvement. National Environmental Engineering Research Institute (CSIR-NEERI) has deployed a Sensor-based Wireless Air Quality Monitoring Network (SWAQMN) to monitor real-time particulate matter (PM10 and PM2.5) concentrations in a highly urbanized megacity, Delhi, the capital of India. The sensors are equipped in a device, called Polludrone and located at ten locations covering different land use and source activities in the city. The Polludrone monitored data was compared with another calibrated PM monitor (GRIMM) for PM10. and PM2.5 concentrations and found a similar trend with correlation coefficient (r(2)) values of 0.73 and 0.85, respectively. The hourly average concentrations of PM10. and PM2.5 were found to be 446 and 242 mu g/m(3) by PM monitor, whereas the Polludrone recorded corresponding values as 314 mu g/m 3 and 176 mu g/m(3), respectively. Daily, diurnal and seasonal variability in PM a . and PM2.5 levels are analyzed at 09 locations in Delhi city using SWAQMN. Further, sensor's monitored data were compared with nearest located Continuous Ambient Air Quality Monitoring Stations (CAAQMS) in the form of Air Quality Index (AQI) and found the AQI values are comparable in all the four seasons. The sensor monitored low AQI values as compared to CAAQMS during monsoon and summer seasons. The present analysis suggests that the sensor-based network (low/affordable cost) can be successfully operated to get the real time air quality levels in an urban area.
引用
收藏
页码:1588 / 1597
页数:10
相关论文
共 50 条
  • [21] An Improved Air Quality Monitoring System Based On Wireless Sensor Networks
    Sun, Jian
    Zhang, Zailong
    Shen, Shu
    Zou, Zhiqiang
    PROCEEDINGS OF 2017 2ND INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION SYSTEMS (ICCIS 2017), 2015, : 31 - 36
  • [22] Deployment of Wireless Sensor Networks for Air Quality Monitoring
    Wang, Mingwei
    Wang, Yue
    Li, Qianghua
    ADVANCES IN MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-4, 2013, 712-715 : 1851 - +
  • [23] Wireless sensor networks for indoor air quality monitoring
    Yu, Tsang-Chu
    Lin, Chung-Chih
    Chen, Chun-Chang
    Lee, Wei-Lun
    Lee, Ren-Guey
    Tseng, Chao-Heng
    Liu, Shi-Ping
    MEDICAL ENGINEERING & PHYSICS, 2013, 35 (02) : 231 - 235
  • [24] Real Time Wireless Sensor Network (WSN) based Indoor Air Quality Monitoring System
    Salman, N.
    Kemp, Andrew H.
    Khan, A.
    Noakes, C. J.
    IFAC PAPERSONLINE, 2019, 52 (24): : 324 - 327
  • [25] Air Quality Monitoring and Analysis in Qatar using a Wireless Sensor Network Deployment
    Yaacoub, Elias
    Kadri, Abdullah
    Mushtaha, Mohammed
    Abu-Dayya, Adnan
    2013 9TH INTERNATIONAL WIRELESS COMMUNICATIONS AND MOBILE COMPUTING CONFERENCE (IWCMC), 2013, : 596 - 601
  • [26] Evolution of Wireless Sensor Network for Air Quality Measurements
    Arroyo, Patricia
    Lozano, Jesus
    Ignacio Suarez, Jose
    ELECTRONICS, 2018, 7 (12):
  • [27] Poster: A Bicycle-borne Sensor Network for Monitoring Urban Air Quality
    Xiang, Chaosheng
    Liu, Xiaofeng
    Jiang, Aimin
    Yan, Bin
    Xia, Jing
    MOBISYS'16: COMPANION COMPANION PUBLICATION OF THE 14TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS, AND SERVICES, 2016, : 88 - 88
  • [28] Smart Sensors Network for Air Quality Monitoring Applications
    Postolache, Octavian A.
    Dias Pereira, J. M.
    Silva Girao, P. M. B.
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2009, 58 (09) : 3253 - 3262
  • [29] Embedding IEEE 1451.4 smart sensing nodes in a wireless air quality monitoring network
    Ramos, Helena Geirinhas
    Postolache, Octavian
    Pereira, Miguel
    Girao, Pedro Silva
    IEEE MWSCAS'06: PROCEEDINGS OF THE 2006 49TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS,, 2006, : 177 - +
  • [30] Sensor-Based Machine Learning Approach for Indoor Air Quality Monitoring in an Automobile Manufacturing
    Wandy, Yose
    Vogt, Marcus
    Kansara, Rushit
    Felsmann, Clemens
    Herrmann, Christoph
    ENERGIES, 2021, 14 (21)