Open Access
The rise of low-cost sensing for managing air pollution in cities
Prashant Kumar,Lidia Morawska,Claudio Martani,George Biskos,George Biskos,George Biskos,Marina Neophytou,Silvana Di Sabatino,Margaret Bell,Leslie Norford,Rex Britter +10 more
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In this article, the authors illustrate the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.Abstract:
Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.read more
Citations
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Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?
Lidia Morawska,Phong K. Thai,Xiaoting Liu,Akwasi Bonsu Asumadu-Sakyi,Godwin A. Ayoko,Alena Bartonova,Andrea Bedini,Fahe Chai,Bryce Christensen,Matthew Dunbabin,Jian Gao,Gayle S.W. Hagler,Rohan Jayaratne,Prashant Kumar,Alexis K.H. Lau,Peter K.K. Louie,Mandana Mazaheri,Zhi Ning,Nunzio Motta,Ben Mullins,Mahmudur Rahman,Zoran Ristovski,Mahnaz Shafiei,Dian Tjondronegoro,Dane Westerdahl,Ronald Williams +25 more
TL;DR: In this article, the authors conducted a comprehensive literature search including both the scientific and grey literature, and concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use.
Journal Article
Real-time sensors for indoor air monitoring and challenges ahead in deploying them to urban buildings
Prashant Kumar,Andreas N. Skouloudis,Margaret Bell,Mar Viana,Maria-Cristina Carotta,George Biskos,Lidia Morawska +6 more
TL;DR: Forouzanfar et al. as discussed by the authors provide a review of the new air pollution sensing methods to determine indoor air quality and discuss how real-time sensing could bring a paradigm shift in controlling the concentration of key air pollutants in billions of urban houses worldwide.
Journal ArticleDOI
Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art
TL;DR: This article summarizes the existing studies on the state-of-the-art of LCS for AQM, and conceptualizes a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data.
Ultrafine particles in cities
Prashant Kumar,Lidia Morawska,Wolfram Birmili,Pauli Paasonen,Min Hu,Markku Kulmala,Roy M. Harrison,Leslie Norford,Rex Britter +8 more
TL;DR: In this paper, the authors reviewed some fundamental drivers of UFP emissions and dispersion, and highlighted unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.
Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model
Marguerite Nyhan,Stanislav Sobolevsky,Chaogui Kang,Prudence Robinson,Andrea Corti,Michael Szell,David G. Streets,Zifeng Lu,Rex Britter,Steven R. H. Barrett,Carlo Ratti +10 more
TL;DR: In this paper, a taxi fleet of over 15,000 vehicles was analyzed with the aim of predicting air pollution emissions for Singapore, and the results showed that highly localized areas of elevated emissions levels were identified, with a spatio-temporal precision not possible with previously used methods for estimating emissions.
References
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Practical Field Calibration of Portable Monitors for Mobile Measurements of Multiple Air Pollutants
Chun Lin,Nicola Masey,Hao Wu,Mark Jackson,David Carruthers,Stefan Reis,Ruth M. Doherty,Iain J. Beverland,Mathew R. Heal +8 more
TL;DR: In this article, the authors investigated ways of establishing and evaluating portable monitor calibration relationships from repeated intermittent deployment cycles over an extended period involving stationary deployment at a reference site, mobile monitoring, and completely switched off.
A Measurement-Driven Approach to Understand Urban Greenhouse Gas Emissions in Nordic Cities
Dirk Ahlers,Patric Arthur Driscoll,Frank Alexander Kraemer,Fredrik Valde Anthonisen,John Krogstie +4 more
TL;DR: The rationale and the design of the Carbon Track and Trace project (CTT) is described that aims to develop an automated system for greenhouse gas emissions monitoring through a low-cost city-level sensor network.
Journal ArticleDOI
The role of materials selection in the urban heat island effect in dry mid-latitude climates
Androula Kakoniti,G Georgiou,Konstantinos Marakkos,Konstantinos Marakkos,Prashant Kumar,Marina Neophytou +5 more
TL;DR: In this article, the role of materials selected for different urban surfaces (e.g. on building walls, roofs and pavements) in the intensity of the urban heat island (UHI) phenomenon was investigated.
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A Traffic-Based Method to Predict and Map Urban Air Quality
TL;DR: In this paper, a decision tree algorithm (C4.8) was used to predict the concentration of PM2.5 during the morning pollution peak from web-based applications (Google Traffic).
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