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Hofman J, Lazarov B, Stroobants C, Elst E, Smets I, Van Poppel M. Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science. SENSORS (BASEL, SWITZERLAND) 2024; 24:5653. [PMID: 39275564 PMCID: PMC11398000 DOI: 10.3390/s24175653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 08/20/2024] [Accepted: 08/28/2024] [Indexed: 09/16/2024]
Abstract
This study presents a fit-for-purpose lab and field evaluation of commercially available portable sensor systems for PM, NO2, and/or BC. The main aim of the study is to identify portable sensor systems that are capable of reliably quantifying dynamic exposure gradients in urban environments. After an initial literature and market study resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked under laboratory and real-word conditions. We evaluated the comparability to reference analyzers, sensor precision, and sensitivity towards environmental confounders (temperature, humidity, and O3). Moreover, we evaluated if the sensor accuracy can be improved by applying a lab or field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM (R2 = 0.68-0.9, Uexp = 16-66%, BSU = 0.1-0.7 µg/m3) and BC (R2 = 0.82-0.83), but maturity of the tested NO2 sensors is still low (R2 = 0.38-0.55, Uexp = 111-614%) and additional efforts are needed in terms of signal noise and calibration, as proven by the performance after multilinear calibration (R2 = 0.75-0.83, Uexp = 37-44%)). The horizontal accuracy of the built-in GPS was generally good, achieving <10 m accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and the resulting impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.
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Affiliation(s)
- Jelle Hofman
- Environmental Intelligence Unit, Flemish Institute for Technological Research (VITO), Vlasmeer 5, 2400 Mol, Belgium
| | - Borislav Lazarov
- Environmental Intelligence Unit, Flemish Institute for Technological Research (VITO), Vlasmeer 5, 2400 Mol, Belgium
| | | | - Evelyne Elst
- Flanders Environmental Agency (VMM), Kronenburgstraat 45, 2000 Antwerp, Belgium
| | - Inge Smets
- Flanders Environmental Agency (VMM), Kronenburgstraat 45, 2000 Antwerp, Belgium
| | - Martine Van Poppel
- Flanders Environmental Agency (VMM), Kronenburgstraat 45, 2000 Antwerp, Belgium
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Stojanović DB, Kleut D, Davidović M, Živković M, Ramadani U, Jovanović M, Lazović I, Jovašević-Stojanović M. Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia. SENSORS (BASEL, SWITZERLAND) 2024; 24:4052. [PMID: 39000831 PMCID: PMC11244021 DOI: 10.3390/s24134052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 07/16/2024]
Abstract
Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.
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Affiliation(s)
- Danka B. Stojanović
- VIDIS Centre, Vinča Institute of Nuclear Sciences—National Institute of the Republic of Serbia, University of Belgrade, 11000 Belgrade, Serbia; (D.K.); (M.D.); (M.Ž.); (U.R.); (M.J.); (I.L.); (M.J.-S.)
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Porwisiak P, Werner M, Kryza M, ApSimon H, Woodward H, Mehlig D, Gawuc L, Szymankiewicz K, Sawiński T. Application of ADMS-Urban for an area with a high contribution of residential heating emissions - model verification and sensitivity study for PM 2.5. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:168011. [PMID: 37871816 DOI: 10.1016/j.scitotenv.2023.168011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/06/2023] [Accepted: 10/20/2023] [Indexed: 10/25/2023]
Abstract
Air pollution poses a significant risk to both human health and the environment in the contemporary world. Among the various pollutants, particulate matter with a diameter <2.5 μm (PM2.5) is regarded as the most hazardous. It has been implicated in over four million global fatalities in 2019 alone. This research paper divulges the outcomes of modelling the spatial-temporal fluctuations of PM2.5 concentrations within the confines of Wroclaw, a city situated in Poland, Central Europe. The model's output was evaluated through comparison with collected data from two government-operated monitoring stations within the city. For this study, we used the ADMS-Urban model and tested two different sources of background data (low-cost sensors and the EMEP MSC-W atmospheric chemistry transport model). The statistical analysis conducted in the paper indicates that the model reproduces the temporal variability of PM2.5. The conclusions from this research indicate that the average annual PM2.5 concentration within Wroclaw is 13.8 μg/m3, with the concentration peaking in the month of March. The spatial distribution reveals the highest PM2.5 concentrations primarily in the southern and western zones of the city, with additional elevated concentrations observed sporadically throughout the city. The study unveils that 1.3 % of Wroclaw's area experiences PM2.5 concentrations exceeding the EU's annual limit of 20 μg/m3. When considered in relation to the WHO's suggested annual average level of 5 μg/m3, Wroclaw city experiences exceedances throughout. When background concentrations are excluded from the model, the annual average PM2.5 concentration across the city is noted to be reduced by >50 %. A thorough investigation of the city's emission structure, taking into account only emissions from the city without background, indicates that the residential sector contributes about 77.3 % of the total annual average PM2.5 concentration in Wroclaw. The transportation and industrial sectors account for nearly 19.5 % and 3.2 %, respectively.
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Affiliation(s)
- Paweł Porwisiak
- Faculty of Earth Sciences and Environmental Management, University of Wrocław, Kosiby 8, 51-621 Wroclaw, Poland.
| | - Małgorzata Werner
- Faculty of Earth Sciences and Environmental Management, University of Wrocław, Kosiby 8, 51-621 Wroclaw, Poland
| | - Maciej Kryza
- Faculty of Earth Sciences and Environmental Management, University of Wrocław, Kosiby 8, 51-621 Wroclaw, Poland
| | - Helen ApSimon
- Centre for Environmental Policy, Imperial College London, London SW7 1NE, UK
| | - Huw Woodward
- Centre for Environmental Policy, Imperial College London, London SW7 1NE, UK
| | - Daniel Mehlig
- Centre for Environmental Policy, Imperial College London, London SW7 1NE, UK
| | - Lech Gawuc
- Institute of Environmental Protection-National Research Institute, Krucza 5/11D, 00-548 Warsaw, Poland
| | - Karol Szymankiewicz
- Institute of Environmental Protection-National Research Institute, Krucza 5/11D, 00-548 Warsaw, Poland
| | - Tymoteusz Sawiński
- Faculty of Earth Sciences and Environmental Management, University of Wrocław, Kosiby 8, 51-621 Wroclaw, Poland
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Kim SY, Blanco MN, Bi J, Larson TV, Sheppard L. Exposure assessment for air pollution epidemiology: A scoping review of emerging monitoring platforms and designs. ENVIRONMENTAL RESEARCH 2023; 223:115451. [PMID: 36764437 PMCID: PMC9992293 DOI: 10.1016/j.envres.2023.115451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/10/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Both exposure monitoring and exposure prediction have played key roles in assessing individual-level long-term exposure to air pollutants and their associations with human health. While there have been notable advances in exposure prediction methods, improvements in monitoring designs are also necessary, particularly given new monitoring paradigms leveraging low-cost sensors and mobile platforms. OBJECTIVES We aim to provide a conceptual summary of novel monitoring designs for air pollution cohort studies that leverage new paradigms and technologies, to investigate their characteristics in real-world examples, and to offer practical guidance to future studies. METHODS We propose a conceptual summary that focuses on two overarching types of monitoring designs, mobile and non-mobile, as well as their subtypes. We define mobile designs as monitoring from a moving platform, and non-mobile designs as stationary monitoring from permanent or temporary locations. We only consider non-mobile studies with cost-effective sampling devices. Then we discuss similarities and differences across previous studies with respect to spatial and temporal representation, data comparability between design classes, and the data leveraged for model development. Finally, we provide specific suggestions for future monitoring designs. RESULTS Most mobile and non-mobile monitoring studies selected monitoring sites based on land use instead of residential locations, and deployed monitors over limited time periods. Some studies applied multiple design and/or sub-design classes to the same area, time period, or instrumentation, to allow comparison. Even fewer studies leveraged monitoring data from different designs to improve exposure assessment by capitalizing on different strengths. In order to maximize the benefit of new monitoring technologies, future studies should adopt monitoring designs that prioritize residence-based site selection with comprehensive temporal coverage and leverage data from different designs for model development in the presence of good data compatibility. DISCUSSION Our conceptual overview provides practical guidance on novel exposure assessment monitoring for epidemiological applications.
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Affiliation(s)
- Sun-Young Kim
- Department of Cancer AI and Digital Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
| | - Magali N Blanco
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Jianzhao Bi
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Timothy V Larson
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA; Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
| | - Lianne Sheppard
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
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Woutersen A, de Ruiter H, Wesseling J, Hendricx W, Blokhuis C, van Ratingen S, Vegt K, Voogt M. Farmers and Local Residents Collaborate: Application of a Participatory Citizen Science Approach to Characterising Air Quality in a Rural Area in The Netherlands. SENSORS (BASEL, SWITZERLAND) 2022; 22:8053. [PMID: 36298407 PMCID: PMC9610964 DOI: 10.3390/s22208053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/12/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
In rural areas, livestock farming is a source of environmental concern. We describe a citizen science (CS) project in Venray, the Netherlands, where air quality was measured at livestock farms and surrounding residential premises. We used low-cost methods to measure air quality components and facilitated a dialogue between stakeholders about the results and solutions for cleaner air. PM2.5 and PM10 were measured using Nova Fitness SDS011 sensors, nitrogen dioxide (NO2) and ammonia (NH3) using Palmes tubes and odour annoyance was reported. Particulate Matter (PM) concentrations were higher close to layer farms, but elevated concentrations were limited at other farms and residential locations. NO2 concentrations were elevated near busy roads, and higher NH3 values were measured near livestock farms. Reporting of odour annoyance was limited, yet during the dialogue residents indicated that this was their largest concern. While both farmers and residents agreed with the general conclusions, they still preferred opposing measures. We conclude that characterisation of air quality using low-cost methods is possible, but expert guidance is needed. Moreover, education, commitment of participants and involvement of independent parties are crucial to ensuring a productive dialogue between stakeholders. The insights gained by participants and resulting dialogue were the greatest benefits of this CS approach.
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Affiliation(s)
- Amber Woutersen
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Henri de Ruiter
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Joost Wesseling
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Wouter Hendricx
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Christa Blokhuis
- Consumption and Healthy Lifestyles, Department of Social Sciences, Wageningen University & Research, P.O. Box 8130, 6700 EW Wageningen, The Netherlands
| | - Sjoerd van Ratingen
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Kirsten Vegt
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Marita Voogt
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
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Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science. SENSORS 2022; 22:s22072543. [PMID: 35408158 PMCID: PMC9003123 DOI: 10.3390/s22072543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 03/18/2022] [Accepted: 03/23/2022] [Indexed: 01/27/2023]
Abstract
As air quality sensors increasingly become commercially available, a deeper consideration of their usability and usefulness is needed to ensure effective application by the public. Much of the research related to sensors has focused on data quality and potential applications. While this information is important, a greater understanding of users’ experience with sensors would provide complementary information. Under a U.S. EPA-funded Science to Achieve Results grant awarded to the South Coast Air Quality Management District in California, titled “Engage, Educate, and Empower California Communities on the Use and Applications of Low-Cost Air Monitoring Sensors”, approximately 400 air quality sensors were deployed with 14 California communities. These communities received sensors and training, and they participated in workshops. Widely varying levels of sensor installation and engagement were observed across the 14 communities. However, despite differences between communities (in terms of participation, demographics, and socioeconomic factors), many participants offered similar feedback on the barriers to sensor use and strategies leading to successful sensor use. Here, we assess sensor use and participant feedback, as well as discuss the development of an educational toolkit titled “Community in Action: A Comprehensive Toolkit on Air Quality Sensors”. This toolkit can be leveraged by future community and citizen science projects to develop networks designed to collect air quality information that can help reduce exposure to and the emissions of pollutants, leading to improved environmental and public health.
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Gardner-Frolick R, Boyd D, Giang A. Selecting Data Analytic and Modeling Methods to Support Air Pollution and Environmental Justice Investigations: A Critical Review and Guidance Framework. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:2843-2860. [PMID: 35133145 DOI: 10.1021/acs.est.1c01739] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Given the serious adverse health effects associated with many pollutants, and the inequitable distribution of these effects between socioeconomic groups, air pollution is often a focus of environmental justice (EJ) research. However, EJ analyses that aim to illuminate whether and how air pollution hazards are inequitably distributed may present a unique set of requirements for estimating pollutant concentrations compared to other air quality applications. Here, we perform a scoping review of the range of data analytic and modeling methods applied in past studies of air pollution and environmental injustice and develop a guidance framework for selecting between them given the purpose of analysis, users, and resources available. We include proxy, monitor-based, statistical, and process-based methods. Upon critically synthesizing the literature, we identify four main dimensions to inform method selection: accuracy, interpretability, spatiotemporal features of the method, and usability of the method. We illustrate the guidance framework with case studies from the literature. Future research in this area includes an exploration of increasing data availability, advanced statistical methods, and the importance of science-based policy.
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Affiliation(s)
- Rivkah Gardner-Frolick
- Department of Mechanical Engineering, University of British Columbia, Vancouver V6T 1Z4, Canada
| | - David Boyd
- Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver V6T 1Z4, Canada
| | - Amanda Giang
- Department of Mechanical Engineering, University of British Columbia, Vancouver V6T 1Z4, Canada
- Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver V6T 1Z4, Canada
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Monitoring and Analysis of Outdoor Carbon Dioxide Concentration by Autonomous Sensors. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Countless problems have been caused by the excessive emission of polluting gases, such as carbon dioxide (CO2), into the atmosphere. Therefore, more effective monitoring of CO2 is essential, especially in central or industrial regions. Thus, this work shows the development of a platform for monitoring the CO2 concentration, which is composed of autonomous and independent sensors that have their own energy source, storage capacity, and data replication for the central server. To validate the platform, CO2 measurements were taken at three strategic points in an outdoor environment in a Brazilian urban center. This platform proved to be an evolution over another system previously proposed by the group that was based on the use of a wireless network of sensors to monitor CO2. This new project managed to overcome limitations that compromised the efficiency of the first platform, which were mainly related to the interference in the communication signals between the network sensors due to the existence of physical barriers in the monitoring environment. With that, this new platform showed greater security in the maintenance of collected data and allowed for the expansion of the physical complexity of the environments that can be monitored.
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Khreis H, Johnson J, Jack K, Dadashova B, Park ES. Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, Texas. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031647. [PMID: 35162669 PMCID: PMC8835131 DOI: 10.3390/ijerph19031647] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/24/2022] [Accepted: 01/24/2022] [Indexed: 02/01/2023]
Abstract
The emergence of low-cost air quality sensors may improve our ability to capture variations in urban air pollution and provide actionable information for public health. Despite the increasing popularity of low-cost sensors, there remain some gaps in the understanding of their performance under real-world conditions, as well as compared to regulatory monitors with high accuracy, but also high cost and maintenance requirements. In this paper, we report on the performance and the linear calibration of readings from 12 commercial low-cost sensors co-located at a regulatory air quality monitoring site in Dallas, Texas, for 18 continuous measurement months. Commercial AQY1 sensors were used, and their reported readings of O3, NO2, PM2.5, and PM10 were assessed against a regulatory monitor. We assessed how well the raw and calibrated AQY1 readings matched the regulatory monitor and whether meteorology impacted performance. We found that each sensor’s response was different. Overall, the sensors performed best for O3 (R2 = 0.36–0.97) and worst for NO2 (0.00–0.58), showing a potential impact of meteorological factors, with an effect of temperature on O3 and relative humidity on PM. Calibration seemed to improve the accuracy, but not in all cases or for all performance metrics (e.g., precision versus bias), and it was limited to a linear calibration in this study. Our data showed that it is critical for users to regularly calibrate low-cost sensors and monitor data once they are installed, as sensors may not be operating properly, which may result in the loss of large amounts of data. We also recommend that co-location should be as exact as possible, minimizing the distance between sensors and regulatory monitors, and that the sampling orientation is similar. There were important deviations between the AQY1 and regulatory monitors’ readings, which in small part depended on meteorology, hindering the ability of the low-costs sensors to present air quality accurately. However, categorizing air pollution levels, using for example the Air Quality Index framework, rather than reporting absolute readings, may be a more suitable approach. In addition, more sophisticated calibration methods, including accounting for individual sensor performance, may further improve performance. This work adds to the literature by assessing the performance of low-cost sensors over one of the longest durations reported to date.
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Affiliation(s)
- Haneen Khreis
- Texas A&M Transportation Institute (TTI), Texas A&M University System, Bryan, TX 77807, USA; (J.J.); (B.D.); (E.S.P.)
- Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH), Texas A&M University System, Bryan, TX 77807, USA
- Correspondence:
| | - Jeremy Johnson
- Texas A&M Transportation Institute (TTI), Texas A&M University System, Bryan, TX 77807, USA; (J.J.); (B.D.); (E.S.P.)
| | - Katherine Jack
- The Nature Conservancy, Texas Chapter, San Antonio, TX 78215, USA;
| | - Bahar Dadashova
- Texas A&M Transportation Institute (TTI), Texas A&M University System, Bryan, TX 77807, USA; (J.J.); (B.D.); (E.S.P.)
| | - Eun Sug Park
- Texas A&M Transportation Institute (TTI), Texas A&M University System, Bryan, TX 77807, USA; (J.J.); (B.D.); (E.S.P.)
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Ionascu ME, Castell N, Boncalo O, Schneider P, Darie M, Marcu M. Calibration of CO, NO 2, and O 3 Using Airify: A Low-Cost Sensor Cluster for Air Quality Monitoring. SENSORS 2021; 21:s21237977. [PMID: 34883981 PMCID: PMC8659498 DOI: 10.3390/s21237977] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 11/16/2022]
Abstract
During the last decade, extensive research has been carried out on the subject of low-cost sensor platforms for air quality monitoring. A key aspect when deploying such systems is the quality of the measured data. Calibration is especially important to improve the data quality of low-cost air monitoring devices. The measured data quality must comply with regulations issued by national or international authorities in order to be used for regulatory purposes. This work discusses the challenges and methods suitable for calibrating a low-cost sensor platform developed by our group, Airify, that has a unit cost five times less expensive than the state-of-the-art solutions (approximately €1000). The evaluated platform can integrate a wide variety of sensors capable of measuring up to 12 parameters, including the regulatory pollutants defined in the European Directive. In this work, we developed new calibration models (multivariate linear regression and random forest) and evaluated their effectiveness in meeting the data quality objective (DQO) for the following parameters: carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). The experimental results show that the proposed calibration managed an improvement of 12% for the CO and O3 gases and a similar accuracy for the NO2 gas compared to similar state-of-the-art studies. The evaluated parameters had different calibration accuracies due to the non-identical levels of gas concentration at which the sensors were exposed during the model’s training phase. After the calibration algorithms were applied to the evaluated platform, its performance met the DQO criteria despite the overall low price level of the platform.
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Affiliation(s)
- Marian-Emanuel Ionascu
- Faculty of Automatics and Computers, Politehnica University of Timisoara, 300223 Timisoara, Romania; (O.B.); (M.M.)
- Correspondence: ; Tel.: +40-745-532-759
| | - Nuria Castell
- Norwegian Institute for Air Research (NILU), 2007 Kjeller, Norway; (N.C.); (P.S.)
| | - Oana Boncalo
- Faculty of Automatics and Computers, Politehnica University of Timisoara, 300223 Timisoara, Romania; (O.B.); (M.M.)
| | - Philipp Schneider
- Norwegian Institute for Air Research (NILU), 2007 Kjeller, Norway; (N.C.); (P.S.)
| | - Marius Darie
- National Institute for Research and Development in Mine Safety and Protection to Explosion–INSEMEX, 332047 Petrosani, Romania;
| | - Marius Marcu
- Faculty of Automatics and Computers, Politehnica University of Timisoara, 300223 Timisoara, Romania; (O.B.); (M.M.)
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van Ratingen S, Vonk J, Blokhuis C, Wesseling J, Tielemans E, Weijers E. Seasonal Influence on the Performance of Low-Cost NO 2 Sensor Calibrations. SENSORS 2021; 21:s21237919. [PMID: 34883922 PMCID: PMC8659619 DOI: 10.3390/s21237919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/15/2021] [Accepted: 11/18/2021] [Indexed: 11/16/2022]
Abstract
Low-cost sensor technology has been available for several years and has the potential to complement official monitoring networks. The current generation of nitrogen dioxide (NO2) sensors suffers from various technical problems. This study explores the added value of calibration models based on (multiple) linear regression including cross terms on the performance of an electrochemical NO2 sensor, the B43F manufactured by Alphasense. Sensor data were collected in duplicate at four reference sites in the Netherlands over a period of one year. It is shown that a calibration, using O3 and temperature in addition to a reference NO2 measurement, improves the prediction in terms of R2 from less than 0.5 to 0.69–0.84. The uncertainty of the calibrated sensors meets the Data Quality Objective for indicative methods specified by the EU directive in some cases and it was verified that the sensor signal itself remains an important predictor in the multilinear regressions. In practice, these sensors are likely to be calibrated over a period (much) shorter than one year. This study shows the dependence of the quality of the calibrated signal on the choice of these short (monthly) calibration and validation periods. This information will be valuable for determining short-period calibration strategies.
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Affiliation(s)
- Sjoerd van Ratingen
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
- Correspondence: ; Tel.: +31-625763243
| | - Jan Vonk
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
- Wageningen Livestock Research, P.O. Box 338, 6700 AH Wageningen, The Netherlands
| | - Christa Blokhuis
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
- Consumption & Healthy Lifestyles, Wageningen University & Research, P.O. Box 8130, 6700 EW Wageningen, The Netherlands
| | - Joost Wesseling
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
| | - Erik Tielemans
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
| | - Ernie Weijers
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (J.V.); (C.B.); (J.W.); (E.T.); (E.W.)
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12
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Perelló J, Cigarini A, Vicens J, Bonhoure I, Rojas-Rueda D, Nieuwenhuijsen MJ, Cirach M, Daher C, Targa J, Ripoll A. Large-scale citizen science provides high-resolution nitrogen dioxide values and health impact while enhancing community knowledge and collective action. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 789:147750. [PMID: 34082196 DOI: 10.1016/j.scitotenv.2021.147750] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/30/2021] [Accepted: 05/10/2021] [Indexed: 06/12/2023]
Abstract
We present outcomes from a large-scale air quality citizen science campaign (xAire, 725 measurements) to demonstrate its positive contribution in the interplay between advances in exposure assessment and developments in policy or collective action. A broad partnership with 1,650 people from communities around 18 primary schools across Barcelona provided the capacity to obtain unprecedented high-resolution NO2 levels and an updated asthma Health Impact Assessment. It is shown that NO2 levels vary considerably with at some cases very high levels. More than a 1,000 new cases of childhood asthma could be prevented each year by lowering NO2 levels. Representativity of site selection and the minimal number of samplers for land use regression modelling are considered. Enhancement of community knowledge and attitudes towards collective response were observed and identified as key drivers for successful large-scale monitoring campaigns. The results encourage strengthening collaboration with local communities when exploring environmental health issues.
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Affiliation(s)
- Josep Perelló
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès, 1, 08028 Barcelona, Catalonia, Spain; Universitat de Barcelona Institute of Complex Systems, Catalonia, Spain.
| | - Anna Cigarini
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès, 1, 08028 Barcelona, Catalonia, Spain; Universitat de Barcelona Institute of Complex Systems, Catalonia, Spain; Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Rambla del Poblenou, 156, 08018 Barcelona, Catalonia, Spain
| | - Julián Vicens
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès, 1, 08028 Barcelona, Catalonia, Spain; Universitat de Barcelona Institute of Complex Systems, Catalonia, Spain
| | - Isabelle Bonhoure
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès, 1, 08028 Barcelona, Catalonia, Spain; Universitat de Barcelona Institute of Complex Systems, Catalonia, Spain
| | - David Rojas-Rueda
- Environmental and Radiological Health Sciences, Colorado State University, 1601 Campus Delivery, 80523 Fort Collins, USA
| | - Mark J Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGLOBAL), Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Marta Cirach
- Barcelona Institute for Global Health (ISGLOBAL), Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Carolyn Daher
- Barcelona Institute for Global Health (ISGLOBAL), Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Jaume Targa
- 4sfera Innova, 17002 Girona, Catalonia, Spain
| | - Anna Ripoll
- 4sfera Innova, 17002 Girona, Catalonia, Spain
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13
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Using Task Farming to Optimise a Street-Scale Resolution Air Quality Model of the West Midlands (UK). ATMOSPHERE 2021. [DOI: 10.3390/atmos12080983] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
High resolution air quality models combining emissions, chemical processes, dispersion and dynamical treatments are necessary to develop effective policies for clean air in urban environments, but can have high computational demand. We demonstrate the application of task farming to reduce runtime for ADMS-Urban, a quasi-Gaussian plume air dispersion model. The model represents the full range of source types (point, road and grid sources) occurring in an urban area at high resolution. Here, we implement and evaluate the option to automatically split up a large model domain into smaller sub-regions, each of which can then be executed concurrently on multiple cores of a HPC or across a PC network, a technique known as task farming. The approach has been tested for a large model domain covering the West Midlands, UK (902 km2), as part of modelling work in the WM-Air (West Midlands Air Quality Improvement Programme) project. Compared to the measurement data, overall, the model performs well. Air quality maps for annual/subset averages and percentiles are generated. For this air quality modelling application of task farming, the optimisation process has reduced weeks of model execution time to approximately 35 h for a single model configuration of annual calculations.
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14
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Sales-Lérida D, Bello AJ, Sánchez-Alzola A, Martínez-Jiménez PM. An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis. SENSORS 2021; 21:s21144781. [PMID: 34300517 PMCID: PMC8309700 DOI: 10.3390/s21144781] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 07/07/2021] [Accepted: 07/09/2021] [Indexed: 11/24/2022]
Abstract
Good air quality is essential for both human beings and the environment in general. The three most harmful air pollutants are nitrogen dioxide (NO2), ozone (O3) and particulate matter. Due to the high cost of monitoring stations, few examples of this type of infrastructure exist, and the use of low-cost sensors could help in air quality monitoring. The cost of metal-oxide sensors (MOS) is usually below EUR 10 and they maintain small dimensions, but their use in air quality monitoring is only valid through an exhaustive calibration process and subsequent precision analysis. We present an on-field calibration technique, based on the least squares method, to fit regression models for low-cost MOS sensors, one that has two main advantages: it can be easily applied by non-expert operators, and it can be used even with only a small amount of calibration data. In addition, the proposed method is adaptive, and the calibration can be refined as more data becomes available. We apply and evaluate the technique with a real dataset from a particular area in the south of Spain (Granada city). The evaluation results show that, despite the simplicity of the technique and the low quantity of data, the accuracy obtained with the low-cost MOS sensors is high enough to be used for air quality monitoring.
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Affiliation(s)
- Diego Sales-Lérida
- Department of Automation Engineering, Electronics and Computer Architecture and Networks, University of Cádiz, 11519 Cádiz, Spain;
- Correspondence:
| | - Alfonso J. Bello
- Department of Statistic and Operations Research, University of Cádiz, 11510 Cádiz, Spain; (A.J.B.); (A.S.-A.)
| | - Alberto Sánchez-Alzola
- Department of Statistic and Operations Research, University of Cádiz, 11510 Cádiz, Spain; (A.J.B.); (A.S.-A.)
| | - Pedro Manuel Martínez-Jiménez
- Department of Automation Engineering, Electronics and Computer Architecture and Networks, University of Cádiz, 11519 Cádiz, Spain;
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15
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Froeling F, Gignac F, Hoek G, Vermeulen R, Nieuwenhuijsen M, Ficorilli A, De Marchi B, Biggeri A, Kocman D, Robinson JA, Grazuleviciene R, Andrusaityte S, Righi V, Basagaña X. Narrative review of citizen science in environmental epidemiology: Setting the stage for co-created research projects in environmental epidemiology. ENVIRONMENT INTERNATIONAL 2021; 152:106470. [PMID: 33677244 DOI: 10.1016/j.envint.2021.106470] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 02/16/2021] [Indexed: 06/12/2023]
Abstract
Several citizen science (CS) initiatives have been adopted in environmental science to monitor air and noise pollution, and water quality related to civic concerns. Nevertheless, CS projects in environmental epidemiology remain scarce. This is because little attention has been paid to evaluate associations of environmental exposures with health effects directly. This narrative review aims to promote the understanding and application of CS in environmental epidemiology. There are many commonalities between CS and other participatory approaches in environmental epidemiology. Yet, CS can foster the democratization of scientific governance and enhance the sustainability of research projects more effectively than other existing participatory approaches. This is especially the case in projects where citizens are invited to participate, engage and become involved throughout all the phases of a research project (co-created projects). This paper identifies various challenges and opportunities specific to the implementation of co-created CS projects in environmental epidemiology. The development of more locally relevant research designs, using local knowledge, obtaining medical ethical clearance, and co-analysing the association between exposure and health, are examples of opportunities and challenges that require epidemiologists to go beyond the traditional research framework and include more outreach activities. Continued efforts, particularly the sharing of information about projects' collaborative processes, are needed to make CS a more concrete and cohesive approach in environmental epidemiology.
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Affiliation(s)
| | - Florence Gignac
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
| | - Gerard Hoek
- Universiteit Utrecht (UU), Utrecht, the Netherlands
| | - Roel Vermeulen
- Universiteit Utrecht (UU), Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands
| | - Mark Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Antonella Ficorilli
- Epidemiologia e Prevenzione "Giulio A. Maccacaro" Social Enterprise, Milan, Italy
| | - Bruna De Marchi
- Epidemiologia e Prevenzione "Giulio A. Maccacaro" Social Enterprise, Milan, Italy; SVT, University of Bergen, Bergen, Norway
| | - Annibale Biggeri
- Epidemiologia e Prevenzione "Giulio A. Maccacaro" Social Enterprise, Milan, Italy; Department of Statistics, Computer Science, Applications "G. Parenti" University of Florence, Florence, Italy
| | - David Kocman
- Jožef Stefan Institute, Department of Environmental Sciences, Ljubljana, Slovenia
| | - Johanna Amalia Robinson
- Jožef Stefan Institute, Department of Environmental Sciences, Ljubljana, Slovenia; Jožef Stefan International Postgraduate School, Ljubljana, Slovenia
| | | | - Sandra Andrusaityte
- Department of Environmental Science, Vytautas Magnus University, Kaunas, Lithuania
| | | | - Xavier Basagaña
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
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Simo A, Dzitac S, Dzitac I, Frigura-Iliasa M, Frigura-Iliasa FM. Air quality assessment system based on self-driven drone and LoRaWAN network. COMPUTER COMMUNICATIONS 2021; 175:13-24. [DOI: 10.1016/j.comcom.2021.04.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
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17
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Venkatraman Jagatha J, Klausnitzer A, Chacón-Mateos M, Laquai B, Nieuwkoop E, van der Mark P, Vogt U, Schneider C. Calibration Method for Particulate Matter Low-Cost Sensors Used in Ambient Air Quality Monitoring and Research. SENSORS (BASEL, SWITZERLAND) 2021; 21:3960. [PMID: 34201377 PMCID: PMC8228976 DOI: 10.3390/s21123960] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/04/2021] [Accepted: 06/06/2021] [Indexed: 11/24/2022]
Abstract
Over the last decade, manufacturers have come forth with cost-effective sensors for measuring ambient and indoor particulate matter concentration. What these sensors make up for in cost efficiency, they lack in reliability of the measured data due to their sensitivities to temperature and relative humidity. These weaknesses are especially evident when it comes to portable or mobile measurement setups. In recent years many studies have been conducted to assess the possibilities and limitations of these sensors, however mostly restricted to stationary measurements. This study reviews the published literature until 2020 on cost-effective sensors, summarizes the recommendations of experts in the field based on their experiences, and outlines the quantile-mapping methodology to calibrate low-cost sensors in mobile applications. Compared to the commonly used linear regression method, quantile mapping retains the spatial characteristics of the measurements, although a common correction factor cannot be determined. We conclude that quantile mapping can be a useful calibration methodology for mobile measurements given a well-elaborated measurement plan assures providing the necessary data.
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Affiliation(s)
- Janani Venkatraman Jagatha
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, D-10099 Berlin, Germany; (A.K.); (C.S.)
| | - André Klausnitzer
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, D-10099 Berlin, Germany; (A.K.); (C.S.)
| | - Miriam Chacón-Mateos
- Department of Flue Gas Cleaning and Air Quality Control, Institute of Combustion and Power Plant Technology (IFK), University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany; (M.C.-M.); (B.L.); (U.V.)
| | - Bernd Laquai
- Department of Flue Gas Cleaning and Air Quality Control, Institute of Combustion and Power Plant Technology (IFK), University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany; (M.C.-M.); (B.L.); (U.V.)
| | - Evert Nieuwkoop
- Netherlands Organisation for Applied Scientific Research, Anna van Buerenplein 1, 2595 DA The Hague, The Netherlands; (E.N.); (P.v.d.M.)
| | - Peter van der Mark
- Netherlands Organisation for Applied Scientific Research, Anna van Buerenplein 1, 2595 DA The Hague, The Netherlands; (E.N.); (P.v.d.M.)
| | - Ulrich Vogt
- Department of Flue Gas Cleaning and Air Quality Control, Institute of Combustion and Power Plant Technology (IFK), University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany; (M.C.-M.); (B.L.); (U.V.)
| | - Christoph Schneider
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, D-10099 Berlin, Germany; (A.K.); (C.S.)
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Wesseling J, Hendricx W, de Ruiter H, van Ratingen S, Drukker D, Huitema M, Schouwenaar C, Janssen G, van Aken S, Smeenk JW, Hof A, Tielemans E. Assessment of PM 2.5 Exposure during Cycle Trips in The Netherlands Using Low-Cost Sensors. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:6007. [PMID: 34205027 PMCID: PMC8199915 DOI: 10.3390/ijerph18116007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 05/27/2021] [Accepted: 05/29/2021] [Indexed: 12/02/2022]
Abstract
Air pollution, especially fine particulate matter (PM2.5), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM2.5. In this study, we use 500 dust (PM2.5) sensors mounted on bicycles to estimate typical PM2.5 levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM2.5, on top of background concentrations, is approximately 2 μg/m3. Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM2.5 compared to routes with less traffic. The results allow for a detailed spatial representation of PM2.5 concentrations and show that choosing a different cycle route might lead to a lower exposure to PM2.5. Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.
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Affiliation(s)
- Joost Wesseling
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
| | - Wouter Hendricx
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
| | - Henri de Ruiter
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
| | - Sjoerd van Ratingen
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
| | - Derko Drukker
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
| | - Maaike Huitema
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
- Province of Utrecht, P.O. Box 80300, 3508 TH Utrecht, The Netherlands; (C.S.); (G.J.); (S.v.A.)
| | - Claar Schouwenaar
- Province of Utrecht, P.O. Box 80300, 3508 TH Utrecht, The Netherlands; (C.S.); (G.J.); (S.v.A.)
| | - Geert Janssen
- Province of Utrecht, P.O. Box 80300, 3508 TH Utrecht, The Netherlands; (C.S.); (G.J.); (S.v.A.)
| | - Stephen van Aken
- Province of Utrecht, P.O. Box 80300, 3508 TH Utrecht, The Netherlands; (C.S.); (G.J.); (S.v.A.)
| | | | - Arjen Hof
- Civity B.V., Handelsweg 6, 3707 NH Zeist, The Netherlands;
| | - Erik Tielemans
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; (W.H.); (H.d.R.); (S.v.R.); (D.D.); (M.H.); (E.T.)
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Citizen Science for Transformative Air Quality Policy in Germany and Niger. SUSTAINABILITY 2021. [DOI: 10.3390/su13073973] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
How can citizen science projects advance the achievement of transformative air quality-related Sustainable Development Goals (SDGs) in Germany and Niger? We investigate the promise of using citizen-generated data (CGD) as an input for official SDG monitoring and implementation in a multidisciplinary project, based on activities undertaken in Niger and Germany ranging from surveys, action research, policy and legislative analysis and environmental monitoring in Niamey and Leipzig, respectively. We critically describe and evaluate the great potential, but very limited actual use of CGD sources for these global goals in both contexts from technical and policy perspectives. Agenda 2030 provides an opportunity to tackle indoor and outdoor air quality in a more integrated and transformative perspective. However, we find this agenda to be remarkably absent in air quality policy and monitoring plans. Likewise, we find no meaningful links of existing citizen science initiatives to official air quality policy. We propose how SDGs-aligned citizen science initiatives could make major contributions to environmental and health monitoring and public debate, especially in the wake of the COVID-19 pandemic. This however requires researchers to more strategically link these initiatives to policymakers and policy frameworks, such as SDG indicators and the governance structures in which they are embedded.
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METER.AC: Live Open Access Atmospheric Monitoring Data for Bulgaria with High Spatiotemporal Resolution. DATA 2020. [DOI: 10.3390/data5020036] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Detailed atmospheric monitoring data are notoriously difficult to obtain for some geographic regions, while they are of paramount importance in scientific research, forecasting, emergency response, policy making, etc. We describe a continuously updated dataset, METER.AC, consisting of raw measurements of atmospheric pressure, temperature, relative humidity, particulate matter, and background radiation in about 100 locations in Bulgaria, as well as some derived values such as sea-level atmospheric pressure, dew/frost point, and hourly trends. The measurements are performed by low-power maintenance-free nodes with common hardware and software, which are specifically designed and optimized for this purpose. The time resolution of the measurements is 5 min. The short-term aim is to deploy at least one node per 100 km2, while uniformly covering altitudes between 0 and 3000 m asl with a special emphasis on remote mountainous areas. A full history of all raw measurements (non-aggregated in time and space) is publicly available, starting from September 2018. We describe the basic technical characteristics of our in-house developed equipment, data organization, and communication protocols as well as present some use case examples. The METER.AC network relies on the paradigm of the Internet of Things (IoT), by collecting data from various gauges. A guiding principle in this work is the provision of findable, accessible, interoperable, and reusable (FAIR) data. The dataset is in the public domain, and it provides resources and tools enabling citizen science development in the context of sustainable development.
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