The rise of low-cost sensing for managing air pollution in cities
01 Feb 2015-
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.
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Queensland University of Technology1, Norwegian Institute for Air Research2, United States Environmental Protection Agency3, University of Surrey4, Hong Kong University of Science and Technology5, Hong Kong Environmental Protection Department6, City University of Hong Kong7, Curtin University8, Southern Cross University9
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
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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Posted Content•
TL;DR: This work presents two fashionable instantiations of Project Calico involving UV irradiation, including EcoHair, which is UV-sensitive hair that intensifies in color saturation depending on the UV intensity, and EcoPatches, which can be worn as temporary tattoos that change their color to reflect cumulative UV exposure over time.
Abstract: Environmental hazards often go unnoticed because they are invisible to the naked eye, posing risks to our health over time Project Calico aims to raise awareness of these risks by augmenting everyday fashion with color-changing chemical sensors that can be observed at a glance or captured by a smartphone camera Project Calico leverages existing cosmetic and fabrication processes to democratize environmental sensing, enabling creators to make their own accessories We present two fashionable instantiations of Project Calico involving UV irradiation EcoHair, created by hair treatment, is UV-sensitive hair that intensifies in color saturation depending on the UV intensity EcoPatches, created by inkjet printing, can be worn as temporary tattoos that change their color to reflect cumulative UV exposure over time We present findings from two focus groups regarding the Project Calico vision and gathered insights from their overall impressions and projected use patterns
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TL;DR: Experimental results show that BoT can be effectively deployed through this algorithmic middleware which can support 'n' no.
Abstract: The paper illustrates a novel concept & implementation technique for "[Bio-Net]-of-Things (BoT)". BoT discloses a method for bringing all the living systems online - so we have humans, IoT devices (inanimate) & bacteria, viruses, plants, crops, etc. all under one bracket of Internet. In this paper we are envisaging symbiotic intelligence for solving the problem of air pollution through BoT. We are facing the pollution menace from vehicles, industries, etc. to a greater extent, especially to the people who are living near roadsides in cities. Carbon monoxide, Nitrogen oxides (NOx), SO2 are the prominent air pollutants found in most cities. Out of these, NOx is one of the major pollutants emitted from vehicles. NOx gases react to form smog and acid rain, as well as being central to the formation of fine particles and ground level ozone, both of which are associated with adverse health effects. The paper demonstrates a setup that utilizes the photo catalytic effect of Titanium dioxide (TiO2) for reducing the effect of air pollution. The pollutants in the air are explicitly identified with the help of on-chip spectrometers and TiO2 is economically sprayed onto those target air pollutants. The cost effective usage of TiO2 is worked out by implementing an 'Unsupervised Particle Swarm Optimization' algorithm. The viability of the proposed IoT platform is confirmed by building a smart test-bed for executing the unsupervised algorithm. Experimental results show that BoT can be effectively deployed through this algorithmic middleware which can support 'n' no. of BoT devices. Thus a pioneering technique is disclosed for tackling the problem of air pollution.
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01 Jul 2019
TL;DR: Low-cost sensor networks could finally deliver effective pro-active management of SCMs, where numerous sensors measure various aspects of SCM state and performance, generating alerts to those involved in their maintenance.
Abstract: Maintenance of stormwater control measures (SCMs) is perhaps the biggest threat to their adoption and performance. Assuring long-term performance which matches the design intent requires suitable monitoring, at the right place and right time, to intervene before malfunctions occur. Doing so has traditionally been very expensive and labour-intensive. The advent of low-cost sensors, however, opens up the potential for entirely new approaches, where numerous sensors measure various aspects of SCM state and performance, generating alerts to those involved in their maintenance. Such sensors could control changes to system configuration to optimise performance relative to (i) operating conditions and (ii) maintenance state of the system. Delivering on this potential will require learning from other related applications of such technology, delivering solutions that match the specifics of stormwater management. Low-cost sensor networks could finally deliver effective pro-active management of SCMs.
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TL;DR: The main contribution of this study is the goal-driven development of an indoor quality apparatus for environmental monitoring data by using smart sensor systems that can help users to monitor and control their environmental factors and provides functionalities for assessing comfortable ranges.
Abstract: The purpose of this study is to implement environmental control systems; information and communication technologies based on user behavior for smart buildings and describe their definitions, technological advances, advantages and modern uses. It also highlights the complexity and difficulty of energy management and comfort via control devices.,This study reviews recent progress in control, information technologies, sensing and optimization in buildings and addresses the automation and environmental control systems of important parameters such as lighting, noise, temperature and humidity. It also explores the technological innovations and methods of management through sensors based on user behavior for the processes of optimization and control.,A proposed prototype has been developed by the combination of user behavior and control systems in buildings, mainly related to thermal comfort and energy use. This study addresses the development of a smart-comfort control system based on users’ behavior.,The main contribution of this study is the goal-driven development of an indoor quality apparatus for environmental monitoring data by using smart sensor systems. It can help users to monitor and control their environmental factors and provides functionalities for assessing comfortable ranges.
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01 Jan 2018
TL;DR: In this article, the authors review contemporary theoretical and practical approaches towards the implementation of environmental issues within the process of urban planning in order to present a framework for local planning policies and assess the possibility of application of design guidelines aimed at achieving environmental objectives in local planning documents.
Abstract: The implementation of environmental issues in planning and designing urban structures is
becoming a novel approach and a common practice consistent with the paradigm of sustainable
development. Maintaining environmental quality in urban areas, managing natural resources and
understanding the complexity of urban systems is becoming increasingly challenging. Therefore, it is
important to develop strategies for the integration of environmental quality research into urban
planning policies and for the development of alternative spatial solutions for the existing urban
structure which are aimed at improving environmental quality in urban areas. The aim of the article is
to review contemporary theoretical and practical approaches towards the implementation of
environmental issues within the process of urban planning in order to present a framework for local
planning policies. Described is the research into spatial and design solutions which can efficiently
reduce noise levels, mitigate atmospheric pollution and odour nuisance or prevent the negative effects
of local microclimate effect. The possibility of application of design guidelines aimed at achieving
environmental objectives in local planning documents is also assessed.
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