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The rise of low-cost sensing for managing air pollution in cities

TLDR
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.

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Citations
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Proceedings ArticleDOI

Laboratory and field evaluation of three low-cost particulate matter sensors

TL;DR: In this article , three different types of low-cost, light-scattering-based widely available particulate matter (PM) sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F and Laser SEN0177) are evaluated, compared, and calibrated with the reference instruments in a controlled environment as well as in a field experiment (surface coal mine).
Dissertation

Reducing the Errors in High Resolution Environmental Modelling

Gabor Makrai
TL;DR: The developed air pollution model presented in this thesis produces more accurate hourly concentration level predictions than the current state-of-the-art method, hence, the approach gives the opportunity for better understanding of the pollution in the urban area.
Posted ContentDOI

Evaluation of high-resolution GRAMM/GRAL NO x simulations over the city of Zurich, Switzerland

TL;DR: In this article, hourly NO x concentrations were simulated for the city of Zurich, Switzerland, at 10m resolution for the years 2013-2014 using the nested mesoscale meteorology and microscale dispersion model system GRAMM/GRAL by applying a catalogue-based approach.
Posted ContentDOI

Long-term behavior and stability of calibration models for NO and NO2 low cost sensors

TL;DR: In this article , the behavior and performance of electrochemical sensors for NO and NO2 were determined over a longer operating period in a real-world deployment, based on co-location with reference instruments at a rural traffic site during six months.
Journal ArticleDOI

RACIMO@Bucaramanga: A Citizen Science Project on Data Science and Climate Awareness

TL;DR: A collaborative experience to empower organized communities to produce, curate and disseminate environmental data with particular emphasis on the description of open hardware & software architecture and the processes of commissioning of the low cost ArduinoRaspberry-Pi weather station.
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