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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24976

Title: End-user perspective of low-cost sensors for outdoor air pollution monitoring
Authors: Rai, Aakash C.
Kumar, Prashant
Pilla, Francesco
Skouloudis, Andreas N.
Di Sabatino, Silvana
Ratti, Carlo
Yasar, Ansar
Rickerby, David
Issue Date: 2017
Citation: SCIENCE OF THE TOTAL ENVIRONMENT, 607, p. 691-705
Abstract: Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network. (C) 2017 Elsevier B.V. All rights reserved.
Notes: [Rai, Aakash C.; Kumar, Prashant] Univ Surrey, Fac Engn & Phys Sci, Dept Civil & Environm Engn, Global Ctr Clean Air Res GCARE, Guildford GU2 7XH, Surrey, England. [Kumar, Prashant] Univ Surrey, Fac Engn & Phys Sci, Environm Flow EnFlo Res Ctr, Guildford GU2 7XH, Surrey, England. [Pilla, Francesco] Univ Coll Dublin, Dept Planning & Environm Policy, Dublin, Ireland. [Skouloudis, Andreas N.; Rickerby, David] European Commiss, Inst Environm & Sustainabil TP263, JRC, Via E Fermi 2749, I-20127 Ispra, VA, Italy. [Di Sabatino, Silvana] Univ Bologna, Alma Mater Studiorum, Dept Phys & Astron, Viale Berti Pichat 6-2, I-40127 Bologna, Italy. [Ratti, Carlo] MIT, SENSEable City Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA. [Yasar, Ansar] Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspk 5 Bus 6, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/24976
DOI: 10.1016/j.scitotenv.2017.06.266
ISI #: 000408755300069
ISSN: 0048-9697
Category: A1
Type: Journal Contribution
Validation: ecoom, 2018
Appears in Collections: Research publications

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