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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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Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

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

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Journal ArticleDOI

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References
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Journal ArticleDOI

Gas Sensor for Volatile Organic Compounds Detection Using Silicon Photonic Ring Resonator

TL;DR: In this paper, a VOC sensor built on a SOI-based photonic platform is presented, which consists of a high-Q factor ring-resonator, achieving a detection limit of 200 ppm.
Proceedings ArticleDOI

Low cost sensor implementation and evaluation for measuring NO2 and O3 pollutants

TL;DR: This work presents a low cost, low energy consumption and high processing power monitoring station that incorporates Alphasense electrochemical sensors of measuring NO2 and O3 as well as NO2-B43F and OX-B431 in order to design proper calibration and correction formulas.
Proceedings ArticleDOI

Mapping Air Quality in IoT Cities: Cloud Calibration and Air Quality Inference of Sensor Data

TL;DR: An innovative IoT approach for highly granular air quality mapping in cities relying on a combination of cloud-calibrated fixed and mobile air quality sensors and machine learning approaches to infer the collected spatiotemporal point measurements in both space and time is presented.
Journal ArticleDOI

AirNet: A Calibration Model for Low-Cost Air Monitoring Sensors Using Dual Sequence Encoder Networks

TL;DR: This work proposes a data-driven model based on deep neural networks, referred to as AirNet, for calibrating low-cost air monitoring sensors, and evaluates the proposed method on two real-world datasets and compares it with six baselines.
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