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

TL;DR: 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.
Citations
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01 Jul 2018
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.
Abstract: Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we 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. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve.

138 citations

Journal Article
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.
Abstract: Household air pollution is ranked the 9th largest Global Burden of Disease risk (Forouzanfar et al., The Lancet 2015). People, particularly urban dwellers, typically spend over 90% of their daily time indoors, where levels of air pollution often surpass those of outdoor environments. Indoor air quality (IAQ) standards and approaches for assessment and control of indoor air require measurements of pollutant concentrations and thermal comfort using conventional instruments. However, the outcomes of such measurements are usually averages over long integrated time periods, which become available after the exposure has already occurred. Moreover, conventional monitoring is generally incapable of addressing temporal and spatial heterogeneity of indoor air pollution, or providing information on peak exposures that occur when specific indoor sources are in operation. This article provides a review of the new air pollution sensing methods to determine IAQ and discusses how real-time sensing could bring a paradigm shift in controlling the concentration of key air pollutants in billions of urban houses worldwide. However, we also show that besides the opportunities, challenges still remain in terms of maturing technologies, or data mining and their interpretation. Moreover, we discuss further research and essential development needed to close gaps between what is available today and needed tomorrow. In particular, we demonstrate that awareness of IAQ risks and availability of appropriate regulation are lagging behind the technologies.

68 citations

Journal ArticleDOI
01 Jan 2022-Sensors
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.
Abstract: Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

33 citations

01 Jan 2014
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.
Abstract: Ultrafine particles (UFP; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggest that average exposure to outdoor UFPs in Asian cities is about four-times larger than those in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.

32 citations

01 Jun 2016
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.
Abstract: Air pollution related to traffic emissions pose an especially significant problem in cities; this is due to its adverse impact on human health and well-being. Previous studies which have aimed to quantify emissions from the transportation sector have been limited by either simulated or coarsely resolved traffic volume data. Emissions inventories form the basis of urban pollution models, therefore in this study, Global Positioning System (GPS) trajectory data from a taxi fleet of over 15,000 vehicles were analyzed with the aim of predicting air pollution emissions for Singapore. This novel approach enabled the quantification of instantaneous drive cycle parameters in high spatio-temporal resolution, which provided the basis for a microscopic emissions model. Carbon dioxide (CO2), nitrogen oxides (NOx), volatile organic compounds (VOCs) and particulate matter (PM) emissions were thus estimated. Highly localized areas of elevated emissions levels were identified, with a spatio-temporal precision not possible with previously used methods for estimating emissions. Relatively higher emissions areas were mainly concentrated in a few districts that were the Singapore Downtown Core area, to the north of the central urban region and to the east of it. Daily emissions quantified for the total motor vehicle population of Singapore were found to be comparable to another emissions dataset. Results demonstrated that high-resolution spatio-temporal vehicle traces detected using GPS in large taxi fleets could be used to infer highly localized areas of elevated acceleration and air pollution emissions in cities, and may become a complement to traditional emission estimates, especially in emerging cities and countries where reliable fine-grained urban air quality data is not easily available. This is the first study of its kind to investigate measured microscopic vehicle movement in tandem with microscopic emissions modeling for a substantial study domain.

21 citations

References
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Journal ArticleDOI
TL;DR: In this article, the authors identify current knowledge gaps in fate, exposure, and toxicity of engineered nanomaterials (ENMs), highlight research gaps, and suggest future research directions.
Abstract: The aim of this study is to identify current knowledge gaps in fate, exposure, and toxicity of engineered nanomaterials (ENMs), highlight research gaps, and suggest future research directions. Humans and other living organisms are exposed to ENMs during production or use of products containing them. To assess the hazards of ENMs, it is important to assess their physiochemical properties and try to relate them to any observed hazard. However, the full determination of these relationships is currently limited by the lack of empirical data. Moreover, most toxicity studies do not use realistic environmental exposure conditions for determining dose-response parameters, affecting the accurate estimation of health risks associated with the exposure to ENMs. Regulatory aspects of nanotechnology are still developing and are currently the subject of much debate. Synthesis of available studies suggests a number of open questions. These include (i) developing a combination of different analytical methods for determining ENM concentration, size, shape, surface properties, and morphology in different environmental media, (ii) conducting toxicity studies using environmentally relevant exposure conditions and obtaining data relevant to developing quantitative nanostructure-toxicity relationships (QNTR), and (iii) developing guidelines for regulating exposure of ENMs in the environment.

56 citations

Journal ArticleDOI
TL;DR: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area and calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM2.5 and coarse PM.
Abstract: Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM2.5 concentration (13.2 ± 13.7 µg/m3) was si...

55 citations

Journal ArticleDOI
TL;DR: Special protection measures during conveyance of in-pram babies, especially at pollution hotspots such as traffic intersections and bus stands, could help to limit their exposure.

54 citations

Journal ArticleDOI
TL;DR: In this paper, a field evaluation of Purple Air PA-II devices (low-cost, compact, particulate matter (PM) sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments.
Abstract: Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.

54 citations

Journal ArticleDOI
TL;DR: This study showed different results for sensor performance than previous studies performed by the U.S. EPA and others, which could be due to different geographic location, meteorology, and aerosol properties, which imply that continued field testing is necessary to understand emerging air sensing technology.
Abstract: Air pollution sensors are quickly proliferating for use in a wide variety of applications, with a low price point that supports use in high-density networks, citizen science, and individual consumer use This emerging technology motivates the assessment under real-world conditions, including varying pollution levels and environmental conditions A seven-month, systematic field evaluation of low-cost air pollution sensors was performed in Denver, Colorado, over 2015–2016; the location was chosen to evaluate the sensors in a high-altitude, cool, and dry climate A suite of particulate matter (PM), ozone ( O3 ), and nitrogen dioxide ( NO2 ) sensors were deployed in triplicate and were collocated with federal equivalent method (FEM) monitors at an urban regulatory site Sensors were evaluated for their data completeness, correlation with reference monitors, and ability to reproduce trends in pollution data, such as daily concentration values and wind-direction patterns Most sensors showed high data completeness when data loggers were functioning properly The sensors displayed a range of correlations with reference instruments, from poor to very high (eg, hourly-average PM Pearson correlations with reference measurements varied from 001 to 086) Some sensors showed a change in response to laboratory audits/testing from before the sampling campaign to afterwards, such as Aeroqual, where the O3 response slope changed from about 12 to 06 Some PM sensors measured wind-direction and time-of-day trends similar to those measured by reference monitors, while others did not This study showed different results for sensor performance than previous studies performed by the US EPA and others, which could be due to different geographic location, meteorology, and aerosol properties These results imply that continued field testing is necessary to understand emerging air sensing technology

53 citations