Sensors and systems for air quality assessment monitoring and management: A review

被引:59
|
作者
Singh, Dharmendra [1 ]
Dahiya, Meenakshi [1 ]
Kumar, Rahul [2 ]
Nanda, Chintan [1 ]
机构
[1] CRID, Haryana Space Applicat Ctr, CCS HAU Campus, Hisar, Haryana, India
[2] Larsen & Tourbro Infotech Ltd, Gurugram, Haryana, India
关键词
Air pollution; Air quality management; Air quality sensors; Satellite remote sensing; Geo-enabled systems; ML& IoT; AEROSOL OPTICAL DEPTH; PARTICULATE MATTER; PM2.5; CONCENTRATIONS; AMBIENT AIR; TRENDS; INDIA; ENVIRONMENT; CLIMATE; DISEASE; TROPOMI;
D O I
10.1016/j.jenvman.2021.112510
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Air quality (AQ) is a global concern for human health management. Therefore, air quality monitoring (AQM) and its management is a must-needed activity for the current world environment. A systematic review of various sensors and systems for AQ management may strengthen our understanding of the monitoring and management of AQ. Thus, the current review presents details on sensors/systems available for AQ assessment, monitoring, and management. First, we had gone through the published literature based on special keywords including AQM, Particulate Matter (PM), Carbon Mono-oxide (CO), Sulfur di-Oxide (SO2), and Nitrogen di-Oxide (NO2) among others, and identified the current scenario of research in AQ management. We discussed various sensors/systems available for the AQ management based on self-conceptualised five major categories including, ground-based AQS (wet chemistry) systems, ground-based digital sensors systems, aerial sensors systems, satellite-based sensors systems, and integrated systems. The prospects in the field of AQ assessment and management (AQA&M) were then discussed in detail. We concluded that the AQA&M can be better achieved by coupling new technologies like ground-based smart sensors, satellite remote sensing sensors, Geospatial technologies, and computational technologies like machine learning, Artificial intelligence, and Internet of Things (IoT). The current work may lead to a junction of information for connecting these sensors/systems, which is expected to be beneficial in future AQ research and management.
引用
收藏
页数:18
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