DocumentCode
1763459
Title
High-Resolution Monitoring of Atmospheric Pollutants Using a System of Low-Cost Sensors
Author
Rajasegarar, Sutharshan ; Havens, Timothy C. ; Karunasekera, Shanika ; Leckie, Christopher ; Bezdek, James C. ; Jamriska, Milan ; Gunatilaka, Ajith ; Skvortsov, Alex ; Palaniswami, Marimuthu
Author_Institution
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Parkville, VIC, Australia
Volume
52
Issue
7
fYear
2014
fDate
41821
Firstpage
3823
Lastpage
3832
Abstract
Increased levels of particulate matter (PM) in the atmosphere have contributed to an increase in mortality and morbidity in communities and are the main contributing factor for respiratory health problems in the population. Currently, PM concentrations are sparsely monitored; for instance, a region of over 2200 square kilometers surrounding Melbourne in Victoria, Australia, is monitored using ten sensor stations. This paper proposes to improve the estimation of PM concentration by complementing the existing high-precision but expensive PM devices with low-cost lower precision PM sensor nodes. Our evaluation reveals that local PM estimation accuracies improve with higher densities of low-precision sensor nodes. Our analysis examines the impact of the precision of the lost-cost sensors on the overall estimation accuracy.
Keywords
air pollution; atmospheric measuring apparatus; health hazards; sensors; Australia; Melbourne; Victoria; high-precision expensive particulate matter devices; high-resolution atmospheric pollutant monitoring; local particulate matter estimation accuracies; lost-cost sensors; low-cost lower precision particulate matter sensor nodes; low-precision sensor nodes; morbidity; mortality; overall estimation accuracy; particulate matter concentrations; respiratory health problems; sensor stations; Atmospheric modeling; Computational modeling; Data models; Monitoring; Pollution measurement; Sensor phenomena and characterization; Air pollution; Bayesian maximum entropy; geospatial analysis; kriging; particulate matter; spatiotemporal estimation; wireless sensor networks;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2013.2276431
Filename
6587138
Link To Document