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Tang M, Shen Y, Ge Y, Gao J, Wang C, Wu L, Si S. Laboratory and field evaluation of a low-cost optical particle sizer. J Environ Sci (China) 2024; 142:215-225. [PMID: 38527887 DOI: 10.1016/j.jes.2023.06.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 06/20/2023] [Accepted: 06/21/2023] [Indexed: 03/27/2024]
Abstract
Low-cost sensors are widely used to collect high-spatial-resolution particulate matter data that traditional reference monitoring devices cannot. In addition to the mass concentration, the number concentration and size distribution are also fundamental in determining the origin and hazard level of particulate pollution. Therefore, low-cost optical sensors have been improved to establish optical particle sizers (OPSs). In this study, a low-cost OPS, the Nova SDS029, is introduced, and it is evaluated in comparison to two reference instruments-the GRIMM 11-D and the TSI 3330. We first tested the sizing accuracy using polystyrene latex spheres. Then, we assessed the mass and number size distribution accuracy in three application scenarios: indoor smoking, ambient air quality, and mobile monitoring. The evaluations suggest that the low-cost SDS029 rivals research-grade optical sizers in many aspects. For example, (1) the particle diameters obtained with the SDS029 are close to the reference instruments (usually < 10%) in the 0.3-5 µm range; (2) the number of particles and mass concentration are highly correlated (r ≥ 0.99) with the values obtained with the reference instruments; and (3) the SDS029 slightly underestimates the number concentration, but the derived PM2.5 values are closer to monitoring station than the reference instruments. The successful application of the SDS029 in multiple scenarios suggests that a plausible particle size distribution can be obtained in an easy and cost-efficient way. We believe that low-cost OPSs will increasingly be used to map the sources and risk levels of particles at the city scale.
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Affiliation(s)
- Mingzhen Tang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yicheng Shen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yanzhen Ge
- Tai'an Ecological Environment Protection Control Center, Tai'an 271000, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Chong Wang
- Jinan Grid-Based Supervision Center of Ecological and Environmental Protection, Jinan 250100, China.
| | - Liqing Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Shuchun Si
- School of Physics, Shandong University, Jinan 250013, China
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Huda RK, Kumar P, Gupta R, Sharma AK, Toteja GS, Babu BV. Air Quality Monitoring Using Low-Cost Sensors in Urban Areas of Jodhpur, Rajasthan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:623. [PMID: 38791837 PMCID: PMC11120845 DOI: 10.3390/ijerph21050623] [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: 03/24/2024] [Revised: 05/08/2024] [Accepted: 05/09/2024] [Indexed: 05/26/2024]
Abstract
Air pollution poses a significant health hazard in urban areas across the globe, with India being one of the most affected countries. This paper presents environmental monitoring study conducted in Jodhpur, Rajasthan, India, to assess air quality in diverse urban environments. The study involved continuous indoor and outdoor air quality monitoring, focusing on particulate matter (PM2.5) levels, bioaerosols, and associated meteorological parameters. Laser sensor-based low-cost air quality monitors were utilized to monitor air quality and Anderson 6-stage Cascade Impactor & Petri Dish methods for bioaerosol monitoring. The study revealed that PM2.5 levels were consistently high throughout the year, highlighting the severity of air pollution in the region. Notably, indoor PM2.5 levels were often higher than outdoor levels, challenging the common notion of staying indoors during peak pollution. The study explored the spatial and temporal diversity of air pollution across various land-use patterns within the city, emphasizing the need for tailored interventions in different urban areas. Additionally, bioaerosol assessments unveiled the presence of pathogenic organisms in indoor and outdoor environments, posing health risks to residents. These findings underscore the importance of addressing particulate matter and bioaerosols in air quality management strategies. Despite the study's valuable insights, limitations, such as using low-cost air quality sensors and the need for long-term data collection, are acknowledged. Nevertheless, this research contributes to a better understanding of urban air quality dynamics and the importance of public awareness in mitigating the adverse effects of air pollution. In conclusion, this study underscores the urgent need for effective air quality management strategies in urban areas. The findings provide valuable insights for policymakers and researchers striving to address air pollution in rapidly urbanizing regions.
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Affiliation(s)
- Ramesh Kumar Huda
- Indian Council of Medical Research, National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur 342005, India; (P.K.); (B.V.B.)
| | - Pankaj Kumar
- Indian Council of Medical Research, National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur 342005, India; (P.K.); (B.V.B.)
| | - Rajnish Gupta
- Indian Council of Medical Research, National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur 342005, India; (P.K.); (B.V.B.)
| | - Arun Kumar Sharma
- Department of Community Medicine, University College of Medical Sciences, Delhi 110095, India;
| | - G. S. Toteja
- Indian Institute of Technology, Jodhpur 342030, India;
| | - Bontha V. Babu
- Indian Council of Medical Research, National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur 342005, India; (P.K.); (B.V.B.)
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3
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Zafra-Pérez A, Boente C, García-Díaz M, Gómez-Galán JA, de la Campa AS, de la Rosa JD. Aerial monitoring of atmospheric particulate matter produced by open-pit mining using low-cost airborne sensors. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166743. [PMID: 37659558 DOI: 10.1016/j.scitotenv.2023.166743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/09/2023] [Accepted: 08/30/2023] [Indexed: 09/04/2023]
Abstract
Mining is an economic activity that entails the production and displacement of significant amounts of atmospheric particulate matter (PM) during operations involving intense earthcrushing or earthmoving. As high concentrations of PM may have adverse effects on human health, it is necessary to monitor and control the fugitive emissions of this pollutant. This paper presents an innovative methodology for the online monitoring of PM10 concentrations in air using a low-cost sensor (LCS, <300 USD) onboard an unmanned aerial vehicle. After comprehensive calibration, the LCS was horizontally flown over seven different areas of the large Riotinto copper mine (Huelva, Spain) at different heights to study the PM10 distribution at different longitudes and altitudes. The flights covered areas of zero activity, intense mining, drilling, ore loading, waste discharge, open stockpiling, and mineral processing. In the zero-activity area, the resuspension of PM10 was very low, with a weak wind speed (3.6 m/s). In the intense-mining area, unhealthy concentrations of PM10 (>51 μgPM10/m3) could be released, and the PM10 can reach surrounding populations through long-distance transport driven by several processes being performed simultaneously. Strong dilution was also observed at high altitudes (> 50 m). Mean concentrations were found to be 22-89 μgPM10/m3, with peaks ranging from 86 to 284 μgPM10/m3. This study demonstrates the potential applicability of airborne LCSs in the high-resolution online monitoring of PM in mining, thus supporting environmental managers during decision-making against fugitive emissions in a cost-effective manner.
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Affiliation(s)
- Adrián Zafra-Pérez
- CIQSO-Center for Research in Sustainable Chemistry, Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Campus El Carmen s/n, 21007 Huelva, Spain
| | - Carlos Boente
- Departamento de Ingeniería Geológica y Minera, E.T.S.I. Minas y Energía de Madrid, Universidad Politécnica de Madrid, C/ Ríos Rosas 21, Madrid, 28003, Spain.
| | - Manuel García-Díaz
- Department of Fluid Mechanics, University of Oviedo, C/Wifredo Ricart, Gijón 33204, Spain
| | - Juan Antonio Gómez-Galán
- Department of Electronic Engineering, Computers and Automation, University of Huelva, Huelva 21007, Spain
| | - Ana Sánchez de la Campa
- CIQSO-Center for Research in Sustainable Chemistry, Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Campus El Carmen s/n, 21007 Huelva, Spain; Department of Earth Sciences, Faculty of Experimental Sciences, University of Huelva, Huelva 21007, Spain
| | - Jesús D de la Rosa
- CIQSO-Center for Research in Sustainable Chemistry, Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Campus El Carmen s/n, 21007 Huelva, Spain; Department of Earth Sciences, Faculty of Experimental Sciences, University of Huelva, Huelva 21007, Spain
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Won WS, Noh J, Oh R, Lee W, Lee JW, Su PC, Yoon YJ. Enhancing the reliability of particulate matter sensing by multivariate Tobit model using weather and air quality data. Sci Rep 2023; 13:13150. [PMID: 37573439 PMCID: PMC10423292 DOI: 10.1038/s41598-023-40468-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/10/2023] [Indexed: 08/14/2023] Open
Abstract
Low-cost particulate matter (PM) sensors have been widely used following recent sensor-technology advancements; however, inherent limitations of low-cost monitors (LCMs), which operate based on light scattering without an air-conditioning function, still restrict their applicability. We propose a regional calibration of LCMs using a multivariate Tobit model with historical weather and air quality data to improve the accuracy of ambient air monitoring, which is highly dependent on meteorological conditions, local climate, and regional PM properties. Weather observations and PM2.5 (fine inhalable particles with diameters ≤ 2.5 μm) concentrations from two regions in Korea, Incheon and Jeju, and one in Singapore were used as training data to build a visibility-based calibration model. To validate the model, field measurements were conducted by an LCM in Jeju and Singapore, where R2 and the error after applying the model in Jeju improved (from 0.85 to 0.88) and reduced by 44% (from 8.4 to 4.7 μg m-3), respectively. The results demonstrated that regional calibration involving air temperature, relative humidity, and other local climate parameters can efficiently correct the bias of the sensor. Our findings suggest that the proposed post-processing using the Tobit model with regional weather and air quality data enhances the applicability of LCMs.
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Affiliation(s)
- Wan-Sik Won
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
- Department of Aerospace Industrial and Systems Engineering, Hanseo University, Taean, Chungcheongnam-do, 32158, Republic of Korea
| | - Jinhong Noh
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Rosy Oh
- Department of Mathematics, Korea Military Academy, Seoul, 01805, Republic of Korea
| | - Woojoo Lee
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jong-Won Lee
- Observer Foundation, Seoul, 04050, Republic of Korea
| | - Pei-Chen Su
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
| | - Yong-Jin Yoon
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
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5
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Shukla N, Gulia S, Goyal P, Dey S, Bosu P, Goyal SK. Performance-based protocol for selection of economical portable sensor for air quality measurement. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:845. [PMID: 37318651 DOI: 10.1007/s10661-023-11438-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 06/01/2023] [Indexed: 06/16/2023]
Abstract
An effective micro-level air quality management plan requires high-resolution monitoring of pollutants. India has already developed a vast network of air quality monitoring stations, both manual and real time, located primarily in urban areas, including megacities. The air quality monitoring network consists of conventional manual stations and real time Continuous Ambient Air Quality Monitoring Stations (CAAQMS) which comprise state-of-the-art analysers and instruments. India is currently in the early stages of developing and adopting economical portable sensor (EPS) in air quality monitoring systems. Protocols need to be established for field calibration and testing. The present research work is an attempt to develop a performance-based assessment framework for the selection of EPS for air quality monitoring. The two-stage selection protocol includes a review of the factory calibration data and a comparison of EPS data with a reference monitor, i.e. a portable calibrated monitor and a CAAQMS. Methods deployed include calculation of central tendency, dispersion around a central value, calculation of statistical parameters for data comparison, and plotting pollution rose and diurnal profile (peak and non-peak pollution measurement). Four commercially available EPS were tested blind, out of which, data from EPS 2 (S2) and EPS 3 (S3) were closer to reference stations at both locations. The selection was made by evaluating monitoring results, physical features, measurement range, and frequency along with examining capital cost. This proposed approach can be used to increase the usability of EPS in the development of micro-level air quality management strategies, other than regulatory compliance. For regulatory compliance, additional research is needed, including field calibration and evaluating EPS performance through additional variables. This proposed framework may be used as starting point, for such experiments, in order to develop confidence in the use of EPS.
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Affiliation(s)
- Nidhi Shukla
- Delhi Zonal Centre, CSIR-National Environmental Engineering Research Institute, Naraina, New Delhi, 110028, India
| | - Sunil Gulia
- Delhi Zonal Centre, CSIR-National Environmental Engineering Research Institute, Naraina, New Delhi, 110028, India.
| | - Prachi Goyal
- Delhi Zonal Centre, CSIR-National Environmental Engineering Research Institute, Naraina, New Delhi, 110028, India
| | - Swagata Dey
- Environmental Defense Fund, New Delhi, India
| | | | - S K Goyal
- Delhi Zonal Centre, CSIR-National Environmental Engineering Research Institute, Naraina, New Delhi, 110028, India
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Peck A, Handy RG, Sleeth DK, Schaefer C, Zhang Y, Pahler LF, Ramsay J, Collingwood SC. Aerosol Measurement Degradation in Low-Cost Particle Sensors Using Laboratory Calibration and Field Validation. TOXICS 2023; 11:56. [PMID: 36668782 PMCID: PMC9862639 DOI: 10.3390/toxics11010056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/22/2022] [Accepted: 12/25/2022] [Indexed: 06/17/2023]
Abstract
Increasing concern over air pollution has led to the development of low-cost sensors suitable for wide-scale deployment and use by citizen scientists. This project investigated the AirU low-cost particle sensor using two methods: (1) a comparison of pre- and post-deployment calibration equations for 24 devices following use in a field study, and (2) an in-home comparison between 3 AirUs and a reference instrument, the GRIMM 1.109. While differences (and therefore some sensor degradation) were found in the pre- and post-calibration equation comparison, absolute value changes were small and unlikely to affect the quality of results. Comparison tests found that while the AirU did tend to underestimate minimum and overestimate maximum concentrations of particulate matter, ~88% of results fell within ±1 μg/m3 of the GRIMM. While these tests confirm that low-cost sensors such as the AirU do experience some sensor degradation over multiple months of use, they remain a valuable tool for exposure assessment studies. Further work is needed to examine AirU performance in different environments for a comprehensive survey of capability, as well as to determine the source of sensor degradation.
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Affiliation(s)
- Angela Peck
- Occupational and Environmental Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Rodney G. Handy
- Occupational and Environmental Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Darrah K. Sleeth
- Occupational and Environmental Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Camie Schaefer
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Yue Zhang
- Department of Internal Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Leon F. Pahler
- Occupational and Environmental Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
| | - Joemy Ramsay
- Occupational and Environmental Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA
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7
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Ryan I, Deng X, Thurston G, Khwaja H, Romeiko X, Zhang W, Marks T, Ye B, Lin S. Measuring students' exposure to particulate matter (PM) pollution across microenvironments and seasons using personal air monitors. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 195:103. [PMID: 36374344 DOI: 10.1007/s10661-022-10624-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Particulate matter (PM) pollution is a significant concern in public health, yet children's exposure is not adequately characterized. This study evaluated PM exposures among primary school-aged children in NYS across different microenvironments. This study helps fill existing knowledge gaps by characterizing PM exposure among this population across seasons and microenvironments. Sixty students were recruited from randomly selected public primary schools representing various socioeconomic statuses. Individual real-time exposure to PM2.5 was measured continuously using AirBeam personal monitors for 48 h. Children were consistently exposed to higher PM2.5 concentrations in the fall (median: fall = 2.84, spring = 2.31, winter = 0.90 µg/m3). At school, 2.19% of PM2.5 measurements exceeded the EPA annual fine particle standard, 12 µg/m3 (winter = 7.38%, fall = 2.39%, spring = 1.38%). In classrooms, PM1-4 concentrations were higher in spring and overnight, while PM7-10 concentrations were higher in fall and school hours. At home, 37.2% of fall measurements exceeded EPA standards (spring = 10.39%, winter = 4.37%). Overall, PM2.5 levels in classrooms and during transportation never rose above the EPA standard for any significant length of time. However, PM2.5 levels routinely exceeded these standards at home, in the fall, and the evening. More extensive studies are needed to confirm these results.
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Affiliation(s)
- Ian Ryan
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Xinlei Deng
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - George Thurston
- Department of Environmental Medicine, School of Medicine, New York University, New York, NY, USA
| | - Haider Khwaja
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Xiaobo Romeiko
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Wangjian Zhang
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Tia Marks
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Bo Ye
- Department of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Shao Lin
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
- Department of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY, USA.
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Roberts FA, Van Valkinburgh K, Green A, Post CJ, Mikhailova EA, Commodore S, Pearce JL, Metcalf AR. Evaluation of a new low-cost particle sensor as an internet-of-things device for outdoor air quality monitoring. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2022; 72:1219-1230. [PMID: 35759771 DOI: 10.1080/10962247.2022.2093293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 06/13/2022] [Accepted: 06/15/2022] [Indexed: 06/15/2023]
Abstract
Many low-cost particle sensors are available for routine air quality monitoring of PM2.5, but there are concerns about the accuracy and precision of the reported data, particularly in humid conditions. The objectives of this study are to evaluate the Sensirion SPS30 particulate matter (PM) sensor against regulatory methods for measurement of real-time particulate matter concentrations and to evaluate the effectiveness of the Intelligent AirTM sensor pack for remote deployment and monitoring. To achieve this, we co-located the Intelligent AirTM sensor pack, developed at Clemson University and built around the Sensirion SPS30, to collect data from July 29, 2019, to December 12, 2019, at a regulatory site in Columbia, South Carolina. When compared to the Federal Equivalent Methods, the SPS30 showed an average bias adjusted R2 = 0.75, mean bias error of -1.59, and a root mean square error of 2.10 for 24-hour average trimmed measurements over 93 days, and R2 = 0.57, mean bias error of -1.61, and a root mean square error of 3.029, for 1-hr average trimmed measurements over 2300 hours when the central 99% of data was retained with a data completeness of 75% or greater. The Intelligent AirTM sensor pack is designed to promote long-term deployment and includes a solar panel and battery backup, protection from the elements, and the ability to upload data via a cellular network. Overall, we conclude that the SPS30 PM sensor and the Intelligent AirTM sensor pack have the potential for greatly increasing the spatial density of particulate matter measurements, but more work is needed to understand and calibrate sensor measurements.Implications: This work adds to the growing body of research that indicates that low-cost sensors of particulate matter (PM) for air quality monitoring has a promising future, and yet much work is left to be done. This work shows that the level of data processing and filtering effects how the low-cost sensors compare to existing federal reference and equivalence methods: more data filtering at low PM levels worsens the data comparison, while longer time averaging improves the measurement comparisons. Improvements must be made to how we handle, calibrate, and correct PM data from low-cost sensors before the data can be reliably used for air quality monitoring and attainment.
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Affiliation(s)
- F A Roberts
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, USA
| | - Kathryn Van Valkinburgh
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, USA
| | - Austin Green
- Department of Forestry and Environmental Conservation, Clemson University, Clemson, South Carolina, USA
| | - Christopher J Post
- Department of Forestry and Environmental Conservation, Clemson University, Clemson, South Carolina, USA
| | - Elena A Mikhailova
- Department of Forestry and Environmental Conservation, Clemson University, Clemson, South Carolina, USA
| | - Sarah Commodore
- Department of Environmental and Occupational Health, Indiana University, Bloomington, Indiana, USA
| | - John L Pearce
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Andrew R Metcalf
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, USA
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Dubey R, Patra AK, Joshi J, Blankenberg D. Evaluation of vertical and horizontal distribution of particulate matter near an urban roadway using an unmanned aerial vehicle. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155600. [PMID: 35504396 DOI: 10.1016/j.scitotenv.2022.155600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 04/19/2022] [Accepted: 04/26/2022] [Indexed: 06/14/2023]
Abstract
Measurement of traffic emissions has gained a lot of interest in recent times due to its contribution to urban pollution. This paper reports the outcome from an unmanned aerial vehicle (UAV) based measurement of PM concentration near an urban roadway at Kolkata, India. A total of 54 flights were carried out for simultaneous measurements of PM1, PM2.5 and PM10 mass concentration and meteorological parameters in vertical as well as in horizontal direction. Results for the vertical flight up to 100 m showed that the PM1, PM2.5 and PM10 concentrations at higher altitudes are less (mean; 24.6, 39.9 and 103.8 μg m-3) compared to the respective ground level concentrations (mean; 26.3, 50.4 and 201.9 μg m-3). For all the three particle sizes, the majority of the cases of higher PM concentration at higher altitudes happened during the evening flight. Low mixing height and low wind speed are suggested to be the reasons for the poor dispersion of pollutants in the evening. While there was a 7-10% fall of fine particles (PM1 and PM2.5) mass concentrations up to 90 m away from the road, no trend could be seen for PM10. The random forest model to predict the UAV/Ground concentration ratio showed high accuracy (R2 = 0.82-0.95) for all three particle sizes. This is an important finding from this study, which shows how UAV measurement data can be used to generate models that can predict the higher altitude concentrations from the ground based measurements.
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Affiliation(s)
- Ravish Dubey
- School of Environmental Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Aditya Kumar Patra
- School of Environmental Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India; Department of Mining Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India.
| | - Jayadev Joshi
- Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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Xiong J, Li J, Wu X, Wolfson JM, Lawrence J, Stern RA, Koutrakis P, Wei J, Huang S. The association between daily-diagnosed COVID-19 morbidity and short-term exposure to PM 1 is larger than associations with PM 2.5 and PM 10. ENVIRONMENTAL RESEARCH 2022; 210:113016. [PMID: 35218713 PMCID: PMC8865934 DOI: 10.1016/j.envres.2022.113016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 06/11/2023]
Abstract
Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (-1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.
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Affiliation(s)
- Jianyin Xiong
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
| | - Jing Li
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Xiao Wu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Jack M Wolfson
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joy Lawrence
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rebecca A Stern
- Harvard John A. Paulson School of Engineering & Applied Sciences, Cambridge, MA, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Shaodan Huang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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11
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Kang Y, Aye L, Ngo TD, Zhou J. Performance evaluation of low-cost air quality sensors: A review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151769. [PMID: 34801495 DOI: 10.1016/j.scitotenv.2021.151769] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/27/2021] [Accepted: 11/14/2021] [Indexed: 06/13/2023]
Abstract
The monitoring of air quality compliance requires the use of Federal Reference Methods (FRM)/Federal Equivalent Methods (FEM); nevertheless, the validity and reliability of low-cost sensors deserve attention due to their affordability and accessibility. This review examines the methodologies of previous studies to characterise the performance of low-cost air quality sensors and to identify the influential factors in sensor evaluation experiments. The data on four statistical measures (Correlation of Determination, r2; Root Mean Square Error, RMSE; Mean Normalised Bias, MNB; and Coefficient of Variation, CV) and details about five methodological factors in experimental design (environmental setting, reference instrument, regression model, pollutant attribute, and sensor original equipment manufacturer (OEM) specification) were extracted from a total of 112 primary articles for a detailed analysis. The results of the analysis suggested that low-cost air quality sensors exhibited improved r2 and RMSE in the experiments with stable environmental settings, in the comparison against non-designated reference instruments, or in the analysis where advanced regression models were used to adjust the sensor readings. However, the pollutant attribute and sensor OEM specification had inconclusive effects on r2 and RMSE due to contradictory results and lack of sufficient data. MNB and CV, two measures that US EPA recommends to determine the suitable application tier of air quality sensors, varied significantly among published experiments due to the discrepancy in experimental design. The outcomes of this work could provide direction to researchers regarding sensor evaluation experiments and guide practitioners to effectively select and deploy low-cost sensors for air quality monitoring.
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Affiliation(s)
- Ye Kang
- Department of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Lu Aye
- Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Tuan Duc Ngo
- Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Jin Zhou
- Department of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia.
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12
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Huang J, Kwan MP, Cai J, Song W, Yu C, Kan Z, Yim SHL. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research. SENSORS 2022; 22:s22062381. [PMID: 35336552 PMCID: PMC8948698 DOI: 10.3390/s22062381] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 02/04/2023]
Abstract
This paper seeks to evaluate and calibrate data collected by low-cost particulate matter (PM) sensors in different environments and using different aggregated temporal units (i.e., 5-s, 1-min, 10-min, 30 min intervals). We first collected PM concentrations (i.e., PM1, PM2.5, and PM10) data in five different environments (i.e., indoor and outdoor of an office building, a train platform and lobby of a subway station, and a seaside location) in Hong Kong, using five AirBeam2 sensors as the low-cost sensors and a TSI DustTrak DRX Aerosol Monitor 8533 as the reference sensor. By comparing the collected PM concentrations, we found high linearity and correlation between the data reported by the AirBeam2 sensors in different environments. Furthermore, the results suggest that the accuracy and bias of the PM data reported by the AirBeam2 sensors are affected by rainy weather and environments with high humidity and a high level of hygroscopic salts (i.e., a seaside location). In addition, increasing the aggregation level of the temporal units (i.e., from 5-s to 30 min intervals) increases the correlation between the PM concentrations obtained by the AirBeam2 sensors, while it does not significantly improve the accuracy and bias of the data. Lastly, our results indicate that using a machine learning model (i.e., random forest) for the calibration of PM concentrations collected on sunny days generates better results than those obtained with multiple linear models. These findings have important implications for researchers when designing environmental exposure studies based on low-cost PM sensors.
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Affiliation(s)
- Jianwei Huang
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Mei-Po Kwan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China
- Correspondence:
| | - Jiannan Cai
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Wanying Song
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Changda Yu
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Zihan Kan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Steve Hung-Lam Yim
- Asian School of the Environment, Nanyang Technological University, Singapore 639798, Singapore;
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798, Singapore
- Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798, Singapore
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13
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Visualization of Dust Generation in Outdoor Workplaces Using A Wearable Particle Monitor and Global Navigation Satellite System. J UOEH 2022; 44:1-13. [PMID: 35249934 DOI: 10.7888/juoeh.44.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We manufactured a wearable particle monitor (WPM), which is a simple and low-cost dust monitor. We aimed to evaluate the usefulness of the device by using it and location information of a Global Navigation Satellite System (GNSS) to measure dust generation in outdoor workplaces. We used nine WPMs and a particle counter KC-52 to measure in parallel the dust concentration diffusing standard particles in a dust exposure apparatus to evaluate the measurability of the WPM, and visualized dust generation in outdoor workplaces to evaluate its usability. We obtained location information using a GNSS in parallel with measuring with the WPM. The measured values of the WPM followed the measured values of the KC-52, with a strong correlation of the values between the KC-52 and each WPM. The discrepancy among devices tended to increase, however, because the measured values of the WPMs increased. For outdoor measurements, we could create a heat map of the relative values of dust generation by combining two data of the WPM and the GNSS. The methods of using the WPM could overview the conditions needed to produce dust emissions in dust-generating workplaces.
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14
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Báthory C, Dobó Z, Garami A, Palotás Á, Tóth P. Low-cost monitoring of atmospheric PM-development and testing. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 304:114158. [PMID: 34922187 DOI: 10.1016/j.jenvman.2021.114158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/01/2021] [Accepted: 11/23/2021] [Indexed: 06/14/2023]
Abstract
Ambient particulate matter (PM) pollution is a significant problem in many urban and rural regions and has severe human health implications. Real-time, spatially dense monitoring using a network of low-cost sensors (LCS) was previously proposed as a way to alleviate the problem of PM. In this study, the performance of an LCS (Plantower PMS7003), a candidate for use in such a network, was investigated. The sensor was calibrated in a controlled climate chamber against a standard reference aerosol monitor. Reproducibility and calibration were evaluated in laboratory tests. Long-term, in-field performance was studied via deploying an LCS assembly at an environmental monitoring station. Results indicated excellent unit-to-unit consistency; however, each sensor needed to be calibrated individually as their characteristics varied slightly. Based on the results of a 15-month field test, quantitative and indicative LCS performance appeared promising: overall indicative accuracy was approximately 73-75% with comparable precision and recall. It is advised that the LCS are cleaned after 6-8 months of operation. Overall, the LCS appeared suitable for low-cost monitoring.
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Affiliation(s)
- Csongor Báthory
- University of Miskolc, Department of Combustion Technology and Thermal Energy, Miskolc-Egyetemvaros, H-3515, Hungary
| | - Zsolt Dobó
- University of Miskolc, Department of Combustion Technology and Thermal Energy, Miskolc-Egyetemvaros, H-3515, Hungary
| | - Attila Garami
- University of Miskolc, Department of Combustion Technology and Thermal Energy, Miskolc-Egyetemvaros, H-3515, Hungary
| | - Árpád Palotás
- University of Miskolc, Department of Combustion Technology and Thermal Energy, Miskolc-Egyetemvaros, H-3515, Hungary
| | - Pál Tóth
- University of Miskolc, Department of Combustion Technology and Thermal Energy, Miskolc-Egyetemvaros, H-3515, Hungary.
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15
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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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16
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Real-Time Low-Cost Personal Monitoring for Exposure to PM2.5 among Asthmatic Children: Opportunities and Challenges. ATMOSPHERE 2021. [DOI: 10.3390/atmos12091192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
This study aims to evaluate the accuracy and effectiveness of real-time personal monitoring of exposure to PM concentrations using low-cost sensors, in comparison to conventional data collection method based on fixed stations. PM2.5 data were measured every 5 min using a low-cost sensor attached to a bag carried by 47 asthmatic children living in the Seoul Metropolitan area between November 2019 and March 2020, along with the real-time GPS location, temperature, and humidity. The mobile sensor data were then matched with station-based hourly PM2.5 data using the time and location. Despite some uncertainty and inaccuracy of the sensor data, similar temporal patterns were found between the two sources of PM2.5 data on an aggregate level. However, average PM2.5 concentrations via personal monitoring tended to be lower than those from the fixed stations, particularly when the subjects were indoors, during nighttime, and located farther from the fixed station. On an individual level, a substantial discrepancy is observed between the two PM2.5 data sources while staying indoors. This study provides guidance to policymakers and researchers on improving the feasibility of personal monitoring via low-cost mobile sensors as an alternative or supplement to the conventional station-based monitoring.
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17
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Feasibility and acceptability of monitoring personal air pollution exposure with sensors for asthma self-management. Asthma Res Pract 2021; 7:13. [PMID: 34482835 PMCID: PMC8420032 DOI: 10.1186/s40733-021-00079-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Accepted: 08/08/2021] [Indexed: 11/18/2022] Open
Abstract
Background Exposure to fine particulate matter (PM2.5) increases the risk of asthma exacerbations, and thus, monitoring personal exposure to PM2.5 may aid in disease self-management. Low-cost, portable air pollution sensors offer a convenient way to measure personal pollution exposure directly and may improve personalized monitoring compared with traditional methods that rely on stationary monitoring stations. We aimed to understand whether adults with asthma would be willing to use personal sensors to monitor their exposure to air pollution and to assess the feasibility of using sensors to measure real-time PM2.5 exposure. Methods We conducted semi-structured interviews with 15 adults with asthma to understand their willingness to use a personal pollution sensor and their privacy preferences with regard to sensor data. Student research assistants used HabitatMap AirBeam devices to take PM2.5 measurements at 1-s intervals while walking in Philadelphia neighborhoods in May–August 2018. AirBeam PM2.5 measurements were compared to concurrent measurements taken by three nearby regulatory monitors. Results All interview participants stated that they would use a personal air pollution sensor, though the consensus was that devices should be small (watch- or palm-sized) and light. Patients were generally unconcerned about privacy or sharing their GPS location, with only two stating they would not share their GPS location under any circumstances. PM2.5 measurements were taken using AirBeam sensors on 34 walks that extended through five Philadelphia neighborhoods. The range of sensor PM2.5 measurements was 0.6–97.6 μg/mL (mean 6.8 μg/mL), compared to 0–22.6 μg/mL (mean 9.0 μg/mL) measured by nearby regulatory monitors. Compared to stationary measurements, which were only available as 1-h integrated averages at discrete monitoring sites, sensor measurements permitted characterization of fine-scale fluctuations in PM2.5 levels over time and space. Conclusions Patients were generally interested in using sensors to monitor their personal exposure to PM2.5 and willing to share personal sensor data with health care providers and researchers. Compared to traditional methods of personal exposure assessment, sensors captured personalized air quality information at higher spatiotemporal resolution. Improvements to currently available sensors, including more reliable Bluetooth connectivity, increased portability, and longer battery life would facilitate their use in a general patient population. Supplementary Information The online version contains supplementary material available at 10.1186/s40733-021-00079-9.
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18
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Jones ER, Laurent JGC, Young AS, MacNaughton P, Coull BA, Spengler JD, Allen JG. The Effects of Ventilation and Filtration on Indoor PM 2.5 in Office Buildings in Four Countries. BUILDING AND ENVIRONMENT 2021; 200:107975. [PMID: 34366550 PMCID: PMC8336933 DOI: 10.1016/j.buildenv.2021.107975] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Fine particulate matter (PM2.5) is an airborne pollutant associated with negative acute and chronic human health outcomes. Although the majority of PM2.5 research has focused on outdoor exposures, people spend the majority of their time indoors, where PM2.5 of outdoor origin can penetrate. In this work, we measured indoor PM2.5 continuously for one year in 37 urban commercial offices with mechanical or mixed-mode ventilation in China, India, the United Kingdom, and the United States. We found that indoor PM2.5 concentrations were generally higher when and where outdoor PM2.5 was elevated. In India and China, mean workday indoor PM2.5 levels exceeded the World Health Organization's 24-hour exposure guideline of 25 µg/m3 about 17% and 27% of the time, respectively. Our statistical models found evidence that the operation of mechanical ventilation systems could mitigate the intrusion of outdoor PM2.5: during standard work hours, a 10 µg/m3 increase in outdoor PM2.5 was associated with 19.9% increase in the expected concentration of indoor PM2.5 (p<0.0001), compared to a larger 23.4% increase during non-work hours (p<0.0001). Finally, our models found that using filters with ratings of MERV 13-14 or MERV 15+ was associated with a 30.9% (95% CI: -55.0%, +6.2%) or 39.4% (95% CI: -62.0%, -3.4%) reduction of indoor PM2.5, respectively, compared to filters with lower MERV 7-12 ratings. Our results demonstrate the potential efficacy of mechanical ventilation with efficient filtration as a public health strategy to protect workers from PM2.5 exposure, particularly where outdoor levels of PM2.5 are elevated.
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Affiliation(s)
- Emily R. Jones
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
- Harvard Graduate School of Arts and Sciences, 1350 Massachusetts Avenue, Cambridge, MA, 02138, USA
- Corresponding author: ; 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
| | | | - Anna S. Young
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
| | - Piers MacNaughton
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
| | - Brent A. Coull
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
| | - John D. Spengler
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
| | - Joseph G. Allen
- Harvard T.H. Chan School of Public Health, 401 Park Drive, 4 Floor West, Boston, MA, 02215, USA
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19
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Assessment of Low-Cost Particulate Matter Sensor Systems against Optical and Gravimetric Methods in a Field Co-Location in Norway. ATMOSPHERE 2021. [DOI: 10.3390/atmos12080961] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.
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20
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An Integrated Individual Environmental Exposure Assessment System for Real-Time Mobile Sensing in Environmental Health Studies. SENSORS 2021; 21:s21124039. [PMID: 34208244 PMCID: PMC8230798 DOI: 10.3390/s21124039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 06/01/2021] [Accepted: 06/06/2021] [Indexed: 11/30/2022]
Abstract
The effects of environmental exposure on human health have been widely explored by scholars in health geography for decades. However, recent advances in geospatial technologies, especially the development of mobile approaches to collecting real-time and high-resolution individual data, have enabled sophisticated methods for assessing people’s environmental exposure. This study proposes an individual environmental exposure assessment system (IEEAS) that integrates objective real-time monitoring devices and subjective sensing tools to provide a composite way for individual-based environmental exposure data collection. With field test data collected in Chicago and Beijing, we illustrate and discuss the advantages of the proposed IEEAS and the composite analysis that could be applied. Data collected with the proposed IEEAS yield relatively accurate measurements of individual exposure in a composite way, and offer new opportunities for developing more sophisticated ways to measure individual environmental exposure. With the capability to consider both the variations in environmental risks and human mobility in high spatial and temporal resolutions, the IEEAS also helps mitigate some uncertainties in environmental exposure assessment and thus enables a better understanding of the relationship between individual environmental exposure and health outcomes.
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21
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Sekula P, Zimnoch M, Bartyzel J, Bokwa A, Kud M, Necki J. Ultra-Light Airborne Measurement System for Investigation of Urban Boundary Layer Dynamics. SENSORS 2021; 21:s21092920. [PMID: 33919343 PMCID: PMC8122531 DOI: 10.3390/s21092920] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 03/29/2021] [Accepted: 04/15/2021] [Indexed: 11/16/2022]
Abstract
Winter smog episodes are a severe problem in many cities around the world. The following two mechanisms are responsible for influencing the level of pollutant concentrations: emission of pollutants from different sources and associated processes leading to formation of secondary aerosols in the atmosphere and meteorology, including advection, which is stimulated by horizontal wind, and convection, which depends on vertical air mass movements associated with boundary layer stability that are determined by vertical temperature and humidity gradients. The aim of the present study was to evaluate the performance of an unmanned aerial vehicle (UAV)-based measurement system developed for investigation of urban boundary layer dynamics. The evaluation was done by comparing the results of temperature, relative humidity, wind speed and particulate matter fraction with aerodynamic diameter below 10 μm (PM10) concentration vertical profiles obtained using this system with two reference meteorological stations: Jagiellonian University Campus (JUC) and radio transmission tower (RTCN), located in the urban area of Krakow city, Southern Poland. The secondary aim of the study was to optimize data processing algorithms improving the response time of UAV sensor measurements during the ascent and descent parts of the flight mission.
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Affiliation(s)
- Piotr Sekula
- Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Krakow, Poland; (M.Z.); (J.B.); (M.K.); (J.N.)
- Institute of Meteorology and Water Management, National Research Institute, IMGW-PIB Branch of Krakow, 30-215 Krakow, Poland
- Correspondence: ; Tel.: +48-516-467-918
| | - Miroslaw Zimnoch
- Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Krakow, Poland; (M.Z.); (J.B.); (M.K.); (J.N.)
| | - Jakub Bartyzel
- Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Krakow, Poland; (M.Z.); (J.B.); (M.K.); (J.N.)
| | - Anita Bokwa
- Institute of Geography and Spatial Management, Jagiellonian University, 30-387 Krakow, Poland;
| | - Michal Kud
- Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Krakow, Poland; (M.Z.); (J.B.); (M.K.); (J.N.)
| | - Jaroslaw Necki
- Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Krakow, Poland; (M.Z.); (J.B.); (M.K.); (J.N.)
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22
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Duvall R, Hagler G, Clements A, Benedict K, Barkjohn K, Kilaru V, Hanley T, Watkins N, Kaufman A, Kamal A, Reece S, Fransioli P, Gerboles M, Gillerman G, Habre R, Hannigan M, Ning Z, Papapostolou V, Pope R, Quintana P, Snyder JL. Deliberating Performance Targets: Follow-on workshop discussing PM 10, NO 2, CO, and SO 2 air sensor targets. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2021; 246:10.1016/j.atmosenv.2020.118099. [PMID: 33746555 PMCID: PMC7970457 DOI: 10.1016/j.atmosenv.2020.118099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The use of air sensor technology is increasing worldwide for a variety of applications, however, with significant variability in data quality. The United States Environmental Protection Agency held a workshop in July 2019 to deliberate possible performance targets for air sensors measuring particles with aerodynamic diameters of 10 μm or less (PM10), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). These performance targets were discussed from the perspective of non-regulatory applications and with the sensors operating primarily in a stationary mode in outdoor environments. Attendees included representatives from multiple levels of government organizations, sensor developers, environmental nonprofits, international organizations, and academia. The workshop addressed the current lack of sensor technology requirements, discussed fit-for-purpose data quality needs, and debated transparency issues. This paper highlights the purpose and key outcomes of the workshop. While more information on performance and applications of sensors is available than in past years, the performance metrics, or parameters used to describe data quality, vary among the studies reports and there is a need for more clear and consistent approaches for evaluating sensor performance. Organizations worldwide are increasingly considering, or are in the process of developing, sensor performance targets and testing protocols. Workshop participants suggested that these new guidelines are highly desirable, would help improve data quality, and would give users more confidence in their data. Given the wide variety of uses for sensors and user backgrounds, as well as varied sensor design features (e.g., communication approaches, data tools, processing/adjustment algorithms and calibration procedures), the need for transparency was a key workshop theme. Suggestions for increasing transparency included documenting and sharing testing and performance data, detailing best practices, and sharing data processing and correction approaches.
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Affiliation(s)
- R.M. Duvall
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - G.S.W. Hagler
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - A.L. Clements
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - K. Benedict
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
| | - K. Barkjohn
- Oak Ridge Institute for Science and Education Fellow, U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - V. Kilaru
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - T. Hanley
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
| | - N. Watkins
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
| | - A. Kaufman
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
| | - A. Kamal
- U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Ann Arbor, MI, USA
| | - S. Reece
- Former Oak Ridge Institute for Science and Education Fellow, U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
| | - P. Fransioli
- Clark County Department of Air Quality, Las Vegas, NV, USA
| | - M. Gerboles
- European Commission, Joint Research Centre, Ispra, Italy
| | - G. Gillerman
- National Institute of Standards and Technology, Standards Coordination Office, Gaithersburg, MD, USA
| | - R. Habre
- University of Southern California, Keck School of Medicine, Los Angeles, CA, USA
| | - M. Hannigan
- University of Colorado-Boulder, Mechanical Engineering Department, Boulder, CO, USA
| | - Z. Ning
- Hong Kong University of Science and Technology, Hong Kong, China
| | - V. Papapostolou
- South Coast Air Quality Management District, Diamond Bar, CA, USA
| | - R. Pope
- Maricopa County Air Quality Department, Phoenix, AZ, USA
| | - P.J.E. Quintana
- San Diego State University, School of Public Health, San Diego, CA, USA
| | - J. Lam Snyder
- Sacramento Metropolitan Air Quality Management District, Sacramento, CA, USA
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23
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Kosmopoulos G, Salamalikis V, Pandis SN, Yannopoulos P, Bloutsos AA, Kazantzidis A. Low-cost sensors for measuring airborne particulate matter: Field evaluation and calibration at a South-Eastern European site. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 748:141396. [PMID: 32798875 DOI: 10.1016/j.scitotenv.2020.141396] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/27/2020] [Accepted: 07/29/2020] [Indexed: 06/11/2023]
Abstract
Low-cost sensors are useful tools for the collection of air quality data, augmenting the existing regulatory monitoring networks and providing an unprecedented opportunity to increase their spatial coverage. This study presents a calibration process of a low-cost PM sensor (PurpleAir PA-II, PAir) in ambient conditions in the city of Patras, Greece, during 18 months of 2017-2018. The hourly PM1 and PM2.5 measurements using the original sensor values were reasonably well correlated (R2 = 0.82 for PM1 and R2 = 0.56 for PM2.5) with the reference instrument, but with a high mean bias and root mean square error. There was a small improvement of around 10% for the daily averages. For PM1-2.5 (particles with diameters between 1 and 2.5 μm), PM2.5-10 (diameters between 2.5 and 10 μm) and PM10, the performance of the low-cost sensors was poor in this area with R2 < 0.37 in all cases. The response of the PAir sensor for PM1 and PM2.5 changed significantly compared to the reference instrument during periods with high dust (or other coarse particle) concentrations. These periods were excluded and a simple linear calibration was then developed for the rest of the fine PM measurements. A method for the identification of these high dust periods based on regional model predictions is proposed. This calibration reduces the relative mean error for hourly PM1 to 19% (1.1 μg m-3) and for PM2.5 to 18% (1.1 μg m-3). The corresponding root mean square errors are 25% (1.4 μg m-3) for hourly PM1 and 25% (1.6 μg m-3) for PM2.5. The biases of the corrected values are, as expected, practically zero. Surprisingly, the relative humidity had a negligible effect on fine PM measurements of the PAir in this location and for the conditions of the study.
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Affiliation(s)
- G Kosmopoulos
- Laboratory of Atmospheric Physics, Department of Physics, University of Patras, Patras GR 26500, Greece
| | - V Salamalikis
- Laboratory of Atmospheric Physics, Department of Physics, University of Patras, Patras GR 26500, Greece
| | - S N Pandis
- Department of Chemical Engineering, University of Patras, Patras GR 26500, Greece; Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas (FORTH/ICE-HT), Patras, Greece; Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - P Yannopoulos
- Department of Civil Engineering, University of Patras, Patras GR 26500, Greece
| | - A A Bloutsos
- Department of Civil Engineering, University of Patras, Patras GR 26500, Greece
| | - A Kazantzidis
- Laboratory of Atmospheric Physics, Department of Physics, University of Patras, Patras GR 26500, Greece.
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24
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Alfano B, Barretta L, Del Giudice A, De Vito S, Di Francia G, Esposito E, Formisano F, Massera E, Miglietta ML, Polichetti T. A Review of Low-Cost Particulate Matter Sensors from the Developers' Perspectives. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6819. [PMID: 33260320 PMCID: PMC7730878 DOI: 10.3390/s20236819] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 11/25/2022]
Abstract
The concerns related to particulate matter's health effects alongside the increasing demands from citizens for more participatory, timely, and diffused air quality monitoring actions have resulted in increasing scientific and industrial interest in low-cost particulate matter sensors (LCPMS). In the present paper, we discuss 50 LCPMS models, a number that is particularly meaningful when compared to the much smaller number of models described in other recent reviews on the same topic. After illustrating the basic definitions related to particulate matter (PM) and its measurements according to international regulations, the device's operating principle is presented, focusing on a discussion of the several characterization methodologies proposed by various research groups, both in the lab and in the field, along with their possible limitations. We present an extensive review of the LCPMS currently available on the market, their electronic characteristics, and their applications in published literature and from specific tests. Most of the reviewed LCPMS can accurately monitor PM changes in the environment and exhibit good performances with accuracy that, in some conditions, can reach R2 values up to 0.99. However, such results strongly depend on whether the device is calibrated or not (using a reference method) in the operative environment; if not, R2 values lower than 0.5 are observed.
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Affiliation(s)
- Brigida Alfano
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Luigi Barretta
- Department of Physics, University of Naples Federico II, via Cinthia, 80100 Napoli, Italy;
- STmicroelectronics, via R. De Feo, Arzano, 80022 Napoli, Italy
| | - Antonio Del Giudice
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Saverio De Vito
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Girolamo Di Francia
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Elena Esposito
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Fabrizio Formisano
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Ettore Massera
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Maria Lucia Miglietta
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
| | - Tiziana Polichetti
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (B.A.); (A.D.G.); (G.D.F.); (E.E.); (F.F.); (E.M.); (M.L.M.); (T.P.)
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25
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A Systematic Review of Air Quality Sensors, Guidelines, and Measurement Studies for Indoor Air Quality Management. SUSTAINABILITY 2020. [DOI: 10.3390/su12219045] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The existence of indoor air pollutants—such as ozone, carbon monoxide, carbon dioxide, sulfur dioxide, nitrogen dioxide, particulate matter, and total volatile organic compounds—is evidently a critical issue for human health. Over the past decade, various international agencies have continually refined and updated the quantitative air quality guidelines and standards in order to meet the requirements for indoor air quality management. This paper first provides a systematic review of the existing air quality guidelines and standards implemented by different agencies, which include the Ambient Air Quality Standards (NAAQS); the World Health Organization (WHO); the Occupational Safety and Health Administration (OSHA); the American Conference of Governmental Industrial Hygienists (ACGIH); the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE); the National Institute for Occupational Safety and Health (NIOSH); and the California ambient air quality standards (CAAQS). It then adds to this by providing a state-of-art review of the existing low-cost air quality sensor (LCAQS) technologies, and analyzes the corresponding specifications, such as the typical detection range, measurement tolerance or repeatability, data resolution, response time, supply current, and market price. Finally, it briefly reviews a sequence (array) of field measurement studies, which focuses on the technical measurement characteristics and their data analysis approaches.
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26
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Awokola BI, Okello G, Mortimer KJ, Jewell CP, Erhart A, Semple S. Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM 2.5 Measurement Using Low-Cost Sensors. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E7243. [PMID: 33023037 PMCID: PMC7579047 DOI: 10.3390/ijerph17197243] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 09/24/2020] [Accepted: 09/25/2020] [Indexed: 11/16/2022]
Abstract
Ambient air pollution in urban cities in sub-Saharan Africa (SSA) is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM2.5). On most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24 h concentration measured across all sites was 38 µg/m3 with the highest PM2.5 period average concentration of 91 µg/m3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m3 measured in Faraja, The Gambia. Kampala in Uganda and Nnewi in Nigeria recorded the longest periods with concentrations >250µg/m3. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM2.5 concentrations in SSA countries. Such data are crucially needed to raise public, societal and policymaker awareness about air pollution across SSA.
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Affiliation(s)
- Babatunde I. Awokola
- Centre for Health Informatics, Computing & Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster LA1 4YW, UK;
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK;
- Department of Clinical Services, Medical Research Council Gambia at London School of Hygiene & Tropical Medicine, P.O. Box 273 Banjul, Gambia
| | - Gabriel Okello
- Institute for Sustainability Leadership, University of Cambridge, 2 Trumpington Street, Cambridge CB2 1QA, UK;
- African Centre for Clean Air, P.O. Box 4357 Kampala, Uganda
| | - Kevin J. Mortimer
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK;
- Respiratory Medicine Department, Aintree University Hospital NHS Foundation Trust, Liverpool L9 7AL, UK
| | - Christopher P. Jewell
- Centre for Health Informatics, Computing & Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster LA1 4YW, UK;
| | - Annette Erhart
- Disease Control & Elimination Theme, Medical Research Council Gambia at London School of Hygiene & Tropical Medicine, P.O. Box 273 Banjul, Gambia;
| | - Sean Semple
- Institute for Social Marketing and Health, University of Stirling, Stirling FK9 4LA, UK;
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27
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Wang WCV, Lung SCC, Liu CH. Application of Machine Learning for the in-Field Correction of a PM 2.5 Low-Cost Sensor Network. SENSORS 2020; 20:s20175002. [PMID: 32899301 PMCID: PMC7506620 DOI: 10.3390/s20175002] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 08/27/2020] [Accepted: 08/31/2020] [Indexed: 01/12/2023]
Abstract
Many low-cost sensors (LCSs) are distributed for air monitoring without any rigorous calibrations. This work applies machine learning with PM2.5 from Taiwan monitoring stations to conduct in-field corrections on a network of 39 PM2.5 LCSs from July 2017 to December 2018. Three candidate models were evaluated: Multiple linear regression (MLR), support vector regression (SVR), and random forest regression (RFR). The model-corrected PM2.5 levels were compared with those of GRIMM-calibrated PM2.5. RFR was superior to MLR and SVR in its correction accuracy and computing efficiency. Compared to SVR, the root mean square errors (RMSEs) of RFR were 35% and 85% lower for the training and validation sets, respectively, and the computational speed was 35 times faster. An RFR with 300 decision trees was chosen as the optimal setting considering both the correction performance and the modeling time. An RFR with a nighttime pattern was established as the optimal correction model, and the RMSEs were 5.9 ± 2.0 μg/m3, reduced from 18.4 ± 6.5 μg/m3 before correction. This is the first work to correct LCSs at locations without monitoring stations, validated using laboratory-calibrated data. Similar models could be established in other countries to greatly enhance the usefulness of their PM2.5 sensor networks.
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Affiliation(s)
- Wen-Cheng Vincent Wang
- Research Center for Environmental Changes, Academia Sinica, Nangang, Taipei 115, Taiwan; (W.-C.V.W.); (C.-H.L.)
| | - Shih-Chun Candice Lung
- Research Center for Environmental Changes, Academia Sinica, Nangang, Taipei 115, Taiwan; (W.-C.V.W.); (C.-H.L.)
- Department of Atmospheric Sciences, National Taiwan University, Taipei 106, Taiwan
- Institute of Environmental Health, National Taiwan University, Taipei 106, Taiwan
- Correspondence:
| | - Chun-Hu Liu
- Research Center for Environmental Changes, Academia Sinica, Nangang, Taipei 115, Taiwan; (W.-C.V.W.); (C.-H.L.)
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28
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Kwarteng L, Baiden EA, Fobil J, Arko‐Mensah J, Robins T, Batterman S. Air Quality Impacts at an E-Waste Site in Ghana Using Flexible, Moderate-Cost and Quality-Assured Measurements. GEOHEALTH 2020; 4:e2020GH000247. [PMID: 32832821 PMCID: PMC7431652 DOI: 10.1029/2020gh000247] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 06/19/2020] [Accepted: 06/23/2020] [Indexed: 05/08/2023]
Abstract
Air quality information is scarce in low- and middle-income countries. This study describes the application of moderate cost approaches that can provide spatial and temporal information on concentrations of particulate matter (PM) needed to assess community and occupational exposures. We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations, obtaining both optical and gravimetric measurements, local meteorological data and satellite aerosol optical depth. Due to overload issues, the gravimetric 24-hr samplers were modified for periodic sampling and some optical data were screened for quality assurance. Exceptionally high concentrations (e.g., 1-hr average PM10 exceeding 2000 μg/m3) were sometimes encountered near combustion sources, including open fires at the e-waste site and spoil piles. 24-hr PM2.5 levels averaged 31, 88 and 57 μg/m3 at upwind, e-waste and downwind sites, respectively, and PM10 averaged 145, 214 and 190 μg/m3, considerably exceeding air quality standards. Upwind levels likely reflected biomass burning that is prevalent in the surrounding informal settlements; levels at the e-waste and downwind sites also reflected contributions from biomass combustion and traffic. The highest PM levels occurred in evenings, influenced by diurnal changes in emission rates, atmospheric dispersion and wind direction shifts. We demonstrate that moderate cost instrumentation, with some modifications, appropriate data cleaning protocols, and attention to understanding local sources and background levels, can be used to characterize spatial and temporal variation in PM levels in urban and industrial areas.
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Affiliation(s)
- Lawrencia Kwarteng
- Department of Biological, Environmental and Occupational Health SciencesUniversity of GhanaAccraGhana
| | - Emmanuel Acquah Baiden
- Department of Biological, Environmental and Occupational Health SciencesUniversity of GhanaAccraGhana
| | - Julius Fobil
- Department of Biological, Environmental and Occupational Health SciencesUniversity of GhanaAccraGhana
| | - John Arko‐Mensah
- Department of Biological, Environmental and Occupational Health SciencesUniversity of GhanaAccraGhana
| | - Thomas Robins
- Environmental Health SciencesUniversity of MichiganAnn ArborMichiganUSA
| | - Stuart Batterman
- Environmental Health SciencesUniversity of MichiganAnn ArborMichiganUSA
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29
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Monitoring Excess Exposure to Air Pollution for Professional Drivers in London Using Low-Cost Sensors. ATMOSPHERE 2020. [DOI: 10.3390/atmos11070749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
In this pilot study, low-cost air pollution sensor nodes were fitted in waste removal trucks, hospital vans and taxis to record drivers’ exposure to air pollution in Central London. Particulate matter (PM 2.5 and PM 10 ), CO 2 , NO 2 , temperature and humidity were recorded in real-time with nodes containing low-cost sensors, an electrochemical gas sensor for NO 2 , an optical particle counter for PM 2.5 and PM 10 and a non-dispersive infrared (NDIR) sensor for CO 2 , temperature and relative humidity. An intervention using a pollution filter to trap PM and NO 2 was also evaluated. The measurements were compared with urban background and roadside monitoring stations at Honor Oak Park and Marylebone Road, respectively. The vehicle records show PM and NO 2 concentrations similar to Marylebone Road and a higher NO 2 -to-PM ratio than at Honor Oak Park. Drivers are exposed to elevated pollution levels relative to Honor Oak Park: 1.72 μ g m − 3 , 1.92 μ g m − 3 and 58.38 ppb for PM 2.5 , PM 10 , and NO 2 , respectively. The CO 2 levels ranged from 410 to over 4000 ppm. There is a significant difference in average concentrations of PM 2.5 and PM 10 between the vehicle types and a non-significant difference in the average concentrations measured with and without the pollution filter within the sectors. In conclusion, drivers face elevated air pollution exposure as part of their jobs.
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30
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Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor. SENSORS 2020; 20:s20133617. [PMID: 32605048 PMCID: PMC7374294 DOI: 10.3390/s20133617] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 06/15/2020] [Accepted: 06/24/2020] [Indexed: 01/08/2023]
Abstract
Low-cost light scattering particulate matter (PM) sensors have been widely researched and deployed in order to overcome the limitations of low spatio-temporal resolution of government-operated beta attenuation monitor (BAM). However, the accuracy of low-cost sensors has been questioned, thus impeding their wide adoption in practice. To evaluate the accuracy of low-cost PM sensors in the field, a multi-sensor platform has been developed and co-located with BAM in Dongjak-gu, Seoul, Korea from 15 January 2019 to 4 September 2019. In this paper, a sample variation of low-cost sensors has been analyzed while using three commercial low-cost PM sensors. Influences on PM sensor by environmental conditions, such as humidity, temperature, and ambient light, have also been described. Based on this information, we developed a novel combined calibration algorithm, which selectively applies multiple calibration models and statistically reduces residuals, while using a prebuilt parameter lookup table where each cell records statistical parameters of each calibration model at current input parameters. As our proposed framework significantly improves the accuracy of the low-cost PM sensors (e.g., RMSE: 23.94 → 4.70 μg/m3) and increases the correlation (e.g., R2: 0.41 → 0.89), this calibration model can be transferred to all sensor nodes through the sensor network.
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31
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Liu X, Jayaratne R, Thai P, Kuhn T, Zing I, Christensen B, Lamont R, Dunbabin M, Zhu S, Gao J, Wainwright D, Neale D, Kan R, Kirkwood J, Morawska L. Low-cost sensors as an alternative for long-term air quality monitoring. ENVIRONMENTAL RESEARCH 2020; 185:109438. [PMID: 32276167 DOI: 10.1016/j.envres.2020.109438] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 03/02/2020] [Accepted: 03/24/2020] [Indexed: 06/11/2023]
Abstract
Low-cost air quality sensors are increasingly being used in many applications; however, many of their performance characteristics have not been adequately investigated. This study was conducted over a period of 13 months using low-cost air quality monitors, each comprising two low-cost sensors, which were subjected to a wide range of pollution sources and concentrations, relative humidity and temperature at four locations in Australia and China. The aim of the study was to establish the performance characteristics of the two low-cost sensors (a Plantower PMS1003 for PM2.5 and an Alphasense CO-B4 for carbon monoxide, CO) and the KOALA monitor as a whole under various conditions. Parameters evaluated included the inter-variability between individual monitors, the accuracy of monitors in comparison with the reference instruments, the effect of temperature and RH on the performance of the monitors, the responses of the PM2.5 sensors to different types of aerosols, and the long-term stability of the PM2.5 and CO sensors. The monitors showed high inter-correlations (r > 0.91) for both PM2.5 and CO measurements. The monitor performance varied with location, with moderate to good correlations with reference instruments for PM2.5 (0.44< R2 < 0.91) and CO (0.37< R2 < 0.90). The monitors performed well at relative humidity < 75% and high temperature conditions; however, two monitors in Beijing failed at low temperatures, probably due to electronic board failure. The PM2.5 sensor was less sensitive to marine aerosols and fresh vehicle emissions than to mixed urban background emissions, aged traffic emissions and industrial emissions. The long-term stability of the PM2.5 and CO sensors was good, while CO relative errors were affected by both high and low temperatures. Overall, the KOALA monitors performed well in the environments in which they were operated and provided a valuable contribution to long-term air quality monitoring within the elucidated limitations.
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Affiliation(s)
- Xiaoting Liu
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Rohan Jayaratne
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Phong Thai
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Tara Kuhn
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Isak Zing
- Institute for Future Environments, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Bryce Christensen
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Riki Lamont
- Institute for Future Environments, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Matthew Dunbabin
- Institute for Future Environments, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Sicong Zhu
- MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China
| | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - David Wainwright
- Queensland Department of Environment and Science, GPO Box 2454, Brisbane, QLD, 4001, Australia
| | - Donald Neale
- Queensland Department of Environment and Science, GPO Box 2454, Brisbane, QLD, 4001, Australia
| | - Ruby Kan
- Office of Environment and Heritage, PO Box 29, Lidcombe, NSW, 1825, Australia
| | - John Kirkwood
- Office of Environment and Heritage, PO Box 29, Lidcombe, NSW, 1825, Australia
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, 4001, Australia.
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32
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Brattich E, Bracci A, Zappi A, Morozzi P, Di Sabatino S, Porcù F, Di Nicola F, Tositti L. How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations. SENSORS (BASEL, SWITZERLAND) 2020; 20:E3073. [PMID: 32485914 PMCID: PMC7309006 DOI: 10.3390/s20113073] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 05/20/2020] [Accepted: 05/26/2020] [Indexed: 12/28/2022]
Abstract
Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30' N, 11°21' E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.
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Affiliation(s)
- Erika Brattich
- Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.B.); (S.D.S.); (F.P.); (F.D.N.)
| | - Alessandro Bracci
- Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.B.); (S.D.S.); (F.P.); (F.D.N.)
| | - Alessandro Zappi
- Department of Chemistry “G. Ciamician”, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.Z.); (P.M.); (L.T.)
| | - Pietro Morozzi
- Department of Chemistry “G. Ciamician”, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.Z.); (P.M.); (L.T.)
| | - Silvana Di Sabatino
- Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.B.); (S.D.S.); (F.P.); (F.D.N.)
| | - Federico Porcù
- Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.B.); (S.D.S.); (F.P.); (F.D.N.)
| | - Francesca Di Nicola
- Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.B.); (S.D.S.); (F.P.); (F.D.N.)
| | - Laura Tositti
- Department of Chemistry “G. Ciamician”, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (A.Z.); (P.M.); (L.T.)
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Qin X, Hou L, Gao J, Si S. The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methods. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 715:136791. [PMID: 32014763 DOI: 10.1016/j.scitotenv.2020.136791] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 01/14/2020] [Accepted: 01/17/2020] [Indexed: 06/10/2023]
Abstract
With the development of the air pollution control, the low-cost sensors are widely used in air quality monitoring, while the data quality of these sensors is always the most concern for users. In this study, data from nine air monitoring stations with standard PM instruments were used as reference and compared with the data of mobile and fixed PM sensors in Jinan, the capital city of Shandong Province, China. Data quality of PM sensors was checked by the cross-comparison among standard method, fixed and mobile sensors. And the impacts of relative humidity and size distribution (PM2.5/PM10) on the performance of PM sensors were evaluated as well. To optimize the calibration method for both fixed and mobile PM sensors, a two-step model was designed, in which the RH and PM2.5/PM10 ratio were both used as input parameters. We firstly calibrated the sensors with five independent models, and then all the calibrated data were linearly fitted by the LR-final model. In comparison with standard instruments, the LR-final model increased the R2 values of the PM2.5 and PM10 measured by fixed sensors from 0.89 and 0.79 to 0.98 and 0.97, respectively. The R2 values of PM2.5 and PM10 measured by the mobile sensors both increased to 0.99 from 0.79 and 0.62. Overall, the two-step calibration model appeared to be a promising approach to solve the poor performance of low-cost sensors.
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Affiliation(s)
- Xiaoliang Qin
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Lujian Hou
- Jinan Ecological Environment Monitoring Center, Shandong Province, Jinan 250013, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Shuchun Si
- School of Physics, Shandong University, Jinan 250013, China
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Bulot FMJ, Russell HS, Rezaei M, Johnson MS, Ossont SJJ, Morris AKR, Basford PJ, Easton NHC, Foster GL, Loxham M, Cox SJ. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution. SENSORS (BASEL, SWITZERLAND) 2020; 20:E2219. [PMID: 32326452 PMCID: PMC7218914 DOI: 10.3390/s20082219] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 03/27/2020] [Accepted: 04/01/2020] [Indexed: 12/21/2022]
Abstract
Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.
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Affiliation(s)
- Florentin Michel Jacques Bulot
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK; (S.J.J.O.); (P.J.B.); (S.J.C.)
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
| | - Hugo Savill Russell
- Danish Big Data Centre for Environment and Health (BERTHA), Aarhus University, DK-4000 Roskilde, Denmark;
- Airlabs Denmark, Lersø Park Allé 107, DK-2100 Copenhagen Ø, Denmark;
- Department of Environmental Science, Atmospheric Measurement, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark
| | - Mohsen Rezaei
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen Ø, Denmark;
| | - Matthew Stanley Johnson
- Airlabs Denmark, Lersø Park Allé 107, DK-2100 Copenhagen Ø, Denmark;
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen Ø, Denmark;
| | - Steven James Johnston Ossont
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK; (S.J.J.O.); (P.J.B.); (S.J.C.)
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
| | | | - Philip James Basford
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK; (S.J.J.O.); (P.J.B.); (S.J.C.)
| | - Natasha Hazel Celeste Easton
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
- School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton SO14 3ZH, UK
| | - Gavin Lee Foster
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
- School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton SO14 3ZH, UK
| | - Matthew Loxham
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
- Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK
- National Institute for Health Research, Southampton Biomedical Research Centre, Southampton SO16 6YD, UK
- Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, UK
| | - Simon James Cox
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK; (S.J.J.O.); (P.J.B.); (S.J.C.)
- Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK; (N.H.C.E.); (G.L.F.); (M.L.)
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DeWitt HL, Crow WL, Flowers B. Performance evaluation of ozone and particulate matter sensors. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2020; 70:292-306. [PMID: 31961265 DOI: 10.1080/10962247.2020.1713921] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 11/27/2019] [Accepted: 12/02/2019] [Indexed: 06/10/2023]
Abstract
As public awareness and concern about air quality grows, companies and researchers have begun to develop small, low-cost sensors to measure local air quality. These sensors have been used in citizen science projects, in distributed networks within cities, and in combination with public health studies on asthma and other air-quality-associated diseases. However, sensor long-term performance under different environmental conditions and pollutant levels is not fully understood. In addition, further evaluation is needed for other long-term performance trends such as performance among sensors of the same model, comparison between sensors from different companies and comparison of sensor data to federal equivalence or reference method (FEM/FRM) measurements. A 10-month evaluation of two popular particulate matter (PM) sensors, Dylos DC1100 and AirBeam, and a popular ozone (O3) sensor, Aeroqual 500, was performed as part of this study. Data from these sensors were compared to each other and to FEM/FRM data and local meteorology. The study took place at the Houston Regional Monitoring (HRM) site 3, located between the Houston Ship Channel and Houston's urban center. PM sensor performance was found to vary in time, with multivariate analysis, binning of data by meteorological parameter, and machine learning techniques able to account for some but not all performance variations. PM type (i.e., size distribution, fiber-flake-spheroid shape and black-brown-white color) likely played a role in the changing sensor performance. Triplicate individual Aeroqual O3 sensors tracked reasonably well with the FEM data for most of the measurement period but had irregular periods of O3 measurement offset. While the FEM data indicated 4 days where ozone levels were above the NAAQS, the Aeroqual ozone sensors indicated a substantially higher number of days, ranging from 9 to 16 for the three sensors.Implications: This paper evaluated the long-term performance of several commercial low-cost sensors (PM2.5 and ozone) as compared to federal equivalence method (FEM) monitors under a range of meteorological and air quality conditions. PM2.5 sensors performed well on low humidity days with winds indicative of sea salt or dust PM sources but had poor correlation with FEM data under other conditions. Two types of PM sensors were studied (Dylos 1100 and AirBeam) and data only correlated well between sensors of the same type. Sensor networks with multiple PM sensor types would not be as useful for comparative purposes as sensor networks of the same type. Relative humidity corrections alone did not increase sensor agreement with FEM to acceptable levels, specific information about PM sources and sensor response in the area measured is needed. Low-cost ozone sensors tested (Aeroqual) performed well but were biased high and overestimated days above ozone NAAQS.
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Sahu R, Dixit KK, Mishra S, Kumar P, Shukla AK, Sutaria R, Tiwari S, Tripathi SN. Validation of Low-Cost Sensors in Measuring Real-Time PM 10 Concentrations at Two Sites in Delhi National Capital Region. SENSORS (BASEL, SWITZERLAND) 2020; 20:E1347. [PMID: 32121462 PMCID: PMC7085545 DOI: 10.3390/s20051347] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 02/17/2020] [Accepted: 02/19/2020] [Indexed: 12/30/2022]
Abstract
In the present study, we assessed for the first time the performance of our custom-designed low-cost Particulate Matter (PM) monitoring devices (Atmos) in measuring PM10 concentrations. We examined the ambient PM10 levels during an intense measurement campaign at two sites in the Delhi National Capital Region (NCR), India. In this study, we validated the un-calibrated Atmos for measuring ambient PM10 concentrations at highly polluted monitoring sites. PM10 concentration from Atmos, containing laser scattering-based Plantower PM sensor, was comparable with that measured from research-grade scanning mobility particle sizers (SMPS) in combination with optical particle sizers (OPS) and aerodynamic particle sizers (APS). The un-calibrated sensors often provided accurate PM10 measurements, particularly in capturing real-time hourly concentrations variations. Quantile-Quantile plots (QQ-plots) for data collected during the selected deployment period showed positively skewed PM10 datasets. Strong Spearman's rank-order correlations (rs = 0.64-0.83) between the studied instruments indicated the utility of low-cost Plantower PM sensors in measuring PM10 in the real-world context. Additionally, the heat map for weekly datasets demonstrated high R2 values, establishing the efficacy of PM sensor in PM10 measurement in highly polluted environmental conditions.
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Affiliation(s)
- Ravi Sahu
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
| | - Kuldeep Kumar Dixit
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
| | - Suneeti Mishra
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
| | - Purushottam Kumar
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
| | - Ashutosh Kumar Shukla
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
| | - Ronak Sutaria
- Centre for Urban Science and Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra 400076, India;
| | - Shashi Tiwari
- Department of Civil Engineering, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana 121004, India;
| | - Sachchida Nand Tripathi
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India; (R.S.); (K.K.D.); (S.M.); (P.K.); (A.K.S.)
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Exercise in Thermal Inversions: PM 2.5 Air Pollution Effects on Pulmonary Function and Aerobic Performance. Wilderness Environ Med 2020; 31:16-22. [PMID: 32033838 DOI: 10.1016/j.wem.2019.10.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 10/03/2019] [Accepted: 10/09/2019] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Wintertime thermal inversions can lead to the accumulation of small particulate matter (PM2.5). Despite an association between respiratory hospital admissions and elevated PM2.5 levels, many people continue to exercise outdoors during inversions. This study compared pulmonary function and exercise performance during periods of low and high ambient PM2.5 concentrations. METHODS Forced vital capacity and forced expiratory volume in 1 s were measured outdoors before and after two 3200 m running time trials: one with low ambient PM2.5 (0.6-14.7 microgram·m-3), and the other during high PM2.5 (19.1-42.5 micrograms·m-3). A 10 cm visual analog scale (VAS) administered postexercise quantified subjective ratings of respiratory discomfort. RESULTS The PM2.5 differential between trials was ≥18 micrograms·m-3 for 10 healthy runners. Despite feeling more respiratory discomfort (P=0.044) during the bad air trial (VAS: 4.6±1.8 cm) compared with the good air trial (VAS: 2.9±1.8 cm), the 3200 m run time (low PM2.5: 13:54±1:34 min:s; high PM2.5: 14:07±1:44 min:s) was not different (P=0.261) between trials. Postexercise forced vital capacity was not significantly different (P=0.846) between the low (4.86±1.00 L) and high (4.84±0.95 L) PM2.5 conditions. Similarly, the difference in postexercise forced expiratory volume in 1 s was not significant (P=0.750) between trials (4.22±0.89 L vs 4.23±0.85 L). CONCLUSIONS Neither run time nor pulmonary function of healthy adults were adversely affected by an acute bout of exercise in elevated ambient PM2.5, equivalent to yellow or orange on the air quality index.
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Zusman M, Schumacher CS, Gassett AJ, Spalt EW, Austin E, Larson TV, Carvlin G, Seto E, Kaufman JD, Sheppard L. Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study. ENVIRONMENT INTERNATIONAL 2020; 134:105329. [PMID: 31783241 PMCID: PMC7363217 DOI: 10.1016/j.envint.2019.105329] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 11/01/2019] [Accepted: 11/12/2019] [Indexed: 05/21/2023]
Abstract
Low-cost air monitoring sensors are an appealing tool for assessing pollutants in environmental studies. Portable low-cost sensors hold promise to expand temporal and spatial coverage of air quality information. However, researchers have reported challenges in these sensors' operational quality. We evaluated the performance characteristics of two widely used sensors, the Plantower PMS A003 and Shinyei PPD42NS, for measuring fine particulate matter compared to reference methods, and developed regional calibration models for the Los Angeles, Chicago, New York, Baltimore, Minneapolis-St. Paul, Winston-Salem and Seattle metropolitan areas. Duplicate Plantower PMS A003 sensors demonstrated a high level of precision (averaged Pearson's r = 0.99), and compared with regulatory instruments, showed good accuracy (cross-validated R2 = 0.96, RMSE = 1.15 µg/m3 for daily averaged PM2.5 estimates in the Seattle region). Shinyei PPD42NS sensor results had lower precision (Pearson's r = 0.84) and accuracy (cross-validated R2 = 0.40, RMSE = 4.49 µg/m3). Region-specific Plantower PMS A003 models, calibrated with regulatory instruments and adjusted for temperature and relative humidity, demonstrated acceptable performance metrics for daily average measurements in the other six regions (R2 = 0.74-0.95, RMSE = 2.46-0.84 µg/m3). Applying the Seattle model to the other regions resulted in decreased performance (R2 = 0.67-0.84, RMSE = 3.41-1.67 µg/m3), likely due to differences in meteorological conditions and particle sources. We describean approach to metropolitan region-specific calibration models for low-cost sensors that can be used with cautionfor exposure measurement in epidemiological studies.
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Affiliation(s)
- Marina Zusman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Cooper S Schumacher
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Amanda J Gassett
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Elizabeth W Spalt
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Elena Austin
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Timothy V Larson
- Department of Civil & Environmental Engineering, University of Washington, Seattle, WA, USA
| | - Graeme Carvlin
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Edmund Seto
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Joel D Kaufman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA; Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, 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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Johnston JE, Juarez Z, Navarro S, Hernandez A, Gutschow W. Youth Engaged Participatory Air Monitoring: A 'Day in the Life' in Urban Environmental Justice Communities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 17:E93. [PMID: 31877745 PMCID: PMC6981490 DOI: 10.3390/ijerph17010093] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 12/12/2019] [Accepted: 12/18/2019] [Indexed: 11/17/2022]
Abstract
Air pollution in Southern California does not impact all communities equally; communities of color are disproportionately burdened by poor air quality and more likely to live near industrial facilities and freeways. Government regulatory monitors do not have the spatial resolution to provide air quality information at the neighborhood or personal scale. We describe the A Day in the Life program, an approach to participatory air monitoring that engages youth in collecting data that they can then analyze and use to take action. Academics partnered with Los Angeles-based youth environmental justice organizations to combine personal air monitoring, participatory science, and digital storytelling to build capacity to address local air quality issues. Eighteen youth participants from four different neighborhoods wore portable personal PM2.5 (fine particles <2.5 µm in diameter) monitors for a day in each of their respective communities, documenting and mapping their exposure to PM2.5 during their daily routine. Air monitoring was coupled with photography and videos to document what they experienced over the course of their day. The PM2.5 exposure during the day for participants averaged 10.7 µg/m3, although the range stretched from <1 to 180 µg/m3. One-third of all measurements were taken <300 m from a freeway. Overall, we demonstrate a method to increase local youth-centered understanding of personal exposures, pollution sources, and vulnerability to air quality.
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Affiliation(s)
- Jill E. Johnston
- Division of Environmental Health, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; (Z.J.); (W.G.)
| | - Zully Juarez
- Division of Environmental Health, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; (Z.J.); (W.G.)
| | | | - Ashley Hernandez
- Communities for a Better Environment, Los Angeles, CA 90089, USA;
| | - Wendy Gutschow
- Division of Environmental Health, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; (Z.J.); (W.G.)
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Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler. SUSTAINABILITY 2019. [DOI: 10.3390/su11247220] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
A suitable and quick determination of air quality allows the population to be alerted with respect to high concentrations of pollutants. Recent advances in computer science have led to the development of a high number of low-cost sensors, improving the spatial and temporal resolution of air quality data while increasing the effectiveness of risk assessment. The main objective of this work is to perform a validation of a particulate matter (PM) sensor (HM-3301) in indoor and outdoor environments to study PM2.5 and PM10 concentrations. To date, this sensor has not been evaluated in real-world situations, and its data quality has not been documented. Here, the HM-3301 sensor is integrated into an Internet of things (IoT) platform to establish a permanent Internet connection. The validation is carried out using a reference sampler (LVS3 of Derenda) according to EN12341:2014. It is focused on statistical insight, and environmental conditions are not considered in this study. The ordinary Linear Model, the Generalized Linear Model, Locally Estimated Scatterplot Smoothing, and the Generalized Additive Model have been proposed to compare and contrast the outcomes. The low-cost sensor is highly correlated with the reference measure ( R 2 greater than 0.70), especially for PM2.5, with a very high accuracy value. In addition, there is a positive relationship between the two measurements, which can be appropriately fitted through the Locally Estimated Scatterplot Smoothing model.
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Giechaskiel B, Mamakos A, Woodburn J, Szczotka A, Bielaczyc P. Evaluation of a 10 nm Particle Number Portable Emissions Measurement System (PEMS). SENSORS 2019; 19:s19245531. [PMID: 31847386 PMCID: PMC6960637 DOI: 10.3390/s19245531] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 12/03/2019] [Accepted: 12/12/2019] [Indexed: 01/12/2023]
Abstract
On-board portable emissions measurement systems (PEMS) are part of the type approval, in-service conformity, and market surveillance aspects of the European exhaust emissions regulation. Currently, only solid particles >23 nm are counted, but Europe will introduce a lower limit of 10 nm. In this study, we evaluated a 10-nm prototype portable system comparing it with laboratory systems measuring diesel, gasoline, and CNG (compressed natural gas) vehicles with emission levels ranging from approximately 2 × 1010 to 2 × 1012 #/km. The results showed that the on-board system differed from the laboratory 10-nm system on average for the tested driving cycles by less than approximately 10% at levels below 6 × 1011 #/km and by approximately 20% for high-emitting vehicles. The observed differences were similar to those observed in the evaluation of portable >23 nm particle counting systems, despite the relatively small size of the emitted particles (with geometric mean diameters <42 nm) and the additional challenges associated with sub-23 nm measurements. The latter included the presence of semivolatile sub-23 nm particles, the elevated concentration levels during cold start, and also the formation of sub-23 nm artefacts from the elastomers that are used to connect the tailpipe to the measurement devices. The main conclusion of the study is that >10 nm on-board systems can be ready for introduction in future regulations.
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Affiliation(s)
- Barouch Giechaskiel
- European Commission, Joint Research Centre, 21027 Ispra, Italy
- Correspondence: ; Tel.: +39-0332-78-5312
| | | | - Joseph Woodburn
- BOSMAL Automotive R&D Institute Ltd., 43300 Bielsko-Biala, Poland; (J.W.); (A.S.); (P.B.)
| | - Andrzej Szczotka
- BOSMAL Automotive R&D Institute Ltd., 43300 Bielsko-Biala, Poland; (J.W.); (A.S.); (P.B.)
| | - Piotr Bielaczyc
- BOSMAL Automotive R&D Institute Ltd., 43300 Bielsko-Biala, Poland; (J.W.); (A.S.); (P.B.)
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Mukherjee A, Brown SG, McCarthy MC, Pavlovic NR, Stanton LG, Snyder JL, D'Andrea S, Hafner HR. Measuring Spatial and Temporal PM 2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors. SENSORS (BASEL, SWITZERLAND) 2019; 19:E4701. [PMID: 31671841 PMCID: PMC6864658 DOI: 10.3390/s19214701] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 10/24/2019] [Accepted: 10/24/2019] [Indexed: 11/16/2022]
Abstract
Low-cost sensors can provide insight on the spatio-temporal variability of air pollution, provided that sufficient efforts are made to ensure data quality. Here, 19 AirBeam particulate matter (PM) sensors were deployed from December 2016 to January 2017 to determine the spatial variability of PM2.5 in Sacramento, California. Prior to, and after, the study, the 19 sensors were deployed and collocated at a regulatory air monitoring site. The sensors demonstrated a high degree of precision during all collocated measurement periods (Pearson R2 = 0.98 - 0.99 across all sensors), with little drift. A sensor-specific correction factor was developed such that each sensor reported a comparable value. Sensors had a moderate degree of correlation with regulatory monitors during the study (R2 = 0.60 - 0.68 at two sites). In a multi-linear regression model, the deviation between sensor and reference measurements of PM2.5 had the highest correlation with dew point and relative humidity. Sensor measurements were used to estimate the PM2.5 spatial variability, finding an average pairwise coefficient of divergence of 0.22 and a range of 0.14 to 0.33, indicating mostly homogeneous distributions. No significant difference in the average sensor PM concentrations between environmental justice (EJ) and non-EJ communities (p value = 0.24) was observed.
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Affiliation(s)
- Anondo Mukherjee
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
- Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80309, USA.
| | - Steven G Brown
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
| | - Michael C McCarthy
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
| | - Nathan R Pavlovic
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
| | - Levi G Stanton
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
| | - Janice Lam Snyder
- Sacramento Metropolitan Air Quality Management District (SMAQMD), Sacramento, CA 95814, USA.
| | - Stephen D'Andrea
- Sacramento Metropolitan Air Quality Management District (SMAQMD), Sacramento, CA 95814, USA.
| | - Hilary R Hafner
- Sonoma Technology, 1450 N. McDowell Blvd., Suite 200, Petaluma, CA 94954, USA.
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Caquilpán P V, Aros G G, Elgueta A S, Díaz S R, Sepúlveda K G, Sierralta J C. Advantages and challenges of the implementation of a low-cost particulate matter monitoring system as a decision-making tool. ENVIRONMENTAL MONITORING AND ASSESSMENT 2019; 191:667. [PMID: 31650385 DOI: 10.1007/s10661-019-7875-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 10/10/2019] [Indexed: 06/10/2023]
Abstract
The integration of monitoring technologies in the last decades has been a key factor in the development of new ways to track air pollutants and supplementing the network of traditional monitoring systems. In this regard, the appearance of affordable and accurate sensor devices to monitor air quality has made possible to obtain relevant data about the state of the air, and moreover, eminent institutions are interested in promoting the use of novel and more affordable tools for air pollution, such as the United States Environmental Protection Agency and European institutions, within a new approach to environmental surveillance, known as Next Generation Compliance and Enforcement technologies. On other hand, in order to get more reliable measurements, the use of machine learning to support adjustment or calibration process has been used in some studies to improve the performance of monitoring devices. On this paper, led by a group of specialists of the Chilean Superintendence of Environment (henceforth, SMA from its Spanish initials), a first approach case study related to the convenience of the usage of low-cost devices in environmental enforcement will be presented. The study was made in the Metropolitan Region of Santiago and considers the spatial distribution of different particulate matter sensors in the region. Some aspects regarding communication and technical issues are presented as well as the main findings about their performance. Results illustrate that low-cost sensors, aided by machine learning algorithms, could provide a reliable enough general screening of particulate matter within a large city, constituting a valuable decision-making tool for environmental oversight, as well as a powerful preventive and deterrent approach for compliance.
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Affiliation(s)
- Víctor Caquilpán P
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile
| | - Gabriel Aros G
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile
| | - Sebastián Elgueta A
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile
| | - Rodrigo Díaz S
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile
| | - Gonzalo Sepúlveda K
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile
| | - Carlos Sierralta J
- Information Management Department, Superintendence of Environment, Santiago de Chile, Teatinos 280, piso 8, Santiago, Chile.
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Mutual Information Input Selector and Probabilistic Machine Learning Utilisation for Air Pollution Proxies. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9204475] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
An air pollutant proxy is a mathematical model that estimates an unobserved air pollutant using other measured variables. The proxy is advantageous to fill missing data in a research campaign or to substitute a real measurement for minimising the cost as well as the operators involved (i.e., virtual sensor). In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach. We propose a mutual information concept to determine the interdependence of different variables and thus select the most correlated inputs. The most relevant variables are selected to be the best proxy inputs, where several metrics and data loss are also involved for guidance. The input selection method determines the used data for training pollutant proxies based on a probabilistic machine learning method. In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction. In this way, the prediction uncertainty could be assessed and evaluated. In order to demonstrate the effectiveness of our approach, we test it on an extensive air pollution database to estimate ozone concentration.
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Lim CC, Kim H, Vilcassim MJR, Thurston GD, Gordon T, Chen LC, Lee K, Heimbinder M, Kim SY. Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea. ENVIRONMENT INTERNATIONAL 2019; 131:105022. [PMID: 31362154 PMCID: PMC6728172 DOI: 10.1016/j.envint.2019.105022] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 06/26/2019] [Accepted: 07/15/2019] [Indexed: 05/04/2023]
Abstract
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practical approach to measure and model air pollution concentration levels. In this study, we developed LUR models for street-level fine particulate matter (PM2.5) concentration levels in Seoul, South Korea. 169 h of data were collected from an approximately three week long campaign across five routes by ten volunteers sharing seven AirBeams, a low-cost ($250 per unit), smartphone-based particle counter, while geospatial data were extracted from OpenStreetMap, an open-source and crowd-generated geographical dataset. We applied and compared three statistical approaches in constructing the LUR models - linear regression (LR), random forest (RF), and stacked ensemble (SE) combining multiple machine learning algorithms - which resulted in cross-validation R2 values of 0.63, 0.73, and 0.80, respectively, and identification of several pollution 'hotspots.' The high R2 values suggest that study designs employing mobile sampling in conjunction with multiple low-cost air quality monitors could be applied to characterize urban street-level air quality with high spatial resolution, and that machine learning models could further improve model performance. Given this study design's cost-effectiveness and ease of implementation, similar approaches may be especially suitable for citizen science and community-based endeavors, or in regions bereft of air quality data and preexisting air monitoring networks, such as developing countries.
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Affiliation(s)
- Chris C Lim
- Department of Environmental Medicine, New York School of Medicine, New York, NY, United States of America.
| | - Ho Kim
- Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | - M J Ruzmyn Vilcassim
- Department of Environmental Medicine, New York School of Medicine, New York, NY, United States of America
| | - George D Thurston
- Department of Environmental Medicine, New York School of Medicine, New York, NY, United States of America
| | - Terry Gordon
- Department of Environmental Medicine, New York School of Medicine, New York, NY, United States of America
| | - Lung-Chi Chen
- Department of Environmental Medicine, New York School of Medicine, New York, NY, United States of America
| | - Kiyoung Lee
- Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | | | - Sun-Young Kim
- Graduate School of Cancer Science and Policy, National Cancer Center, Gyeonggi, South Korea
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Feinberg SN, Williams R, Hagler G, Low J, Smith L, Brown R, Garver D, Davis M, Morton M, Schaefer J, Campbell J. Examining spatiotemporal variability of urban particulate matter and application of high-time resolution data from a network of low-cost air pollution sensors. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2019; 213:579-584. [PMID: 34121907 PMCID: PMC8193829 DOI: 10.1016/j.atmosenv.2019.06.026] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Traditional air monitoring approaches using regulatory monitors have historically been used to assess regional-scale trends in air pollutants across large geographical areas. Recent advances in air pollution sensor technologies could provide additional information about nearby sources, support the siting of regulatory monitoring stations, and improve our knowledge of finer-scale spatiotemporal variation of ambient air pollutants and their associated health effects. Sensors are now being developed that are much smaller and lower cost than traditional ambient air monitoring systems and are capable of being deployed as a network to provide greater coverage of a given area. The CitySpace project conducted by the US EPA and the Shelby County Health Department included the deployment of a network of 17 sensor pods using Alphasense OPC-N2 particulate matter (PM) sensors integrated with meteorological sensors in Memphis, TN for six months. Sensor pods were collocated with a federal equivalent method (FEM) tapered element oscillating microbalance (TEOM) monitor both before and after the primary study period. Six of the sensor pods were found to meet the data quality objective (DQO) of coefficient of determination (R2) greater than 0.5 when collocated with the TEOM. Seven pods were decommissioned before the end of the study due to mechanical failure. The six pods meeting the DQO were used to examine the spatiotemporal variability of fine PM (PM2.5) across the Memphis area. One site was found to have higher relative PM2.5 concentrations when compared to the other sites in the network. The 1-min data from this sensor pod were evaluated to quantify the regional urban background and local-scale contributions to PM2.5 at that monitoring location. This method found that approximately 20% of the PM2.5 was attributed to local sources at this location, compared to 9% at a local regulatory monitoring site. Additionally, the 1-min data were combined with 1-min wind speed and wind direction data to examine potential sources in the area using the nonparametric trajectory analysis (NTA) technique. This method geographically identified local source areas that contributed to the measured concentrations at the high reading sensor location throughout the course of the study.
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Affiliation(s)
- Stephen Neil Feinberg
- Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830
- U.S Environmental Protection Agency (EPA), Office of Research and Development, Research Triangle Park, NC 27711
| | - Ron Williams
- U.S Environmental Protection Agency (EPA), Office of Research and Development, Research Triangle Park, NC 27711
| | - Gayle Hagler
- U.S Environmental Protection Agency (EPA), Office of Research and Development, Research Triangle Park, NC 27711
| | - Judy Low
- Shelby County Health Department, Memphis, TN 38105
| | - Larry Smith
- Shelby County Health Department, Memphis, TN 38105
| | | | | | | | | | | | - John Campbell
- General Dynamics Information Technology; Edison, NJ 08837
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47
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Lee CH, Wang YB, Yu HL. An efficient spatiotemporal data calibration approach for the low-cost PM 2.5 sensing network: A case study in Taiwan. ENVIRONMENT INTERNATIONAL 2019; 130:104838. [PMID: 31203027 DOI: 10.1016/j.envint.2019.05.032] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Revised: 04/22/2019] [Accepted: 05/13/2019] [Indexed: 06/09/2023]
Abstract
The rapid growth of Internet of Things has provided a new aspect to air quality monitoring system. In Taiwan, over 5000 PM2.5 sensors have been installed in the last two years. The greatest asset of low-cost sensors is possibly mapping spatiotemporal air pollution with finer resolution. But the data quality of low-cost sensors is the most common question that how to take proper interpretation of the measurements. This study proposes an efficient calibration approach based on generalized additive model which is further applied to a particular low-cost PM2.5 sensor in Taiwan. The study carried out a field calibration that collecting both measurements of low-cost sensors and the regulatory stations, and investigated the space/time bias between the low-cost sensors and regulatory stations. Results show that the proposed approach can explain the variability of the biases from the low-cost sensors with R-square of 0.76. In addition, the present calibration model can quantify the uncertainty of the low-cost sensors observations and the average standard deviation is about 13.85% with respect to its adjusted levels. This operational spatiotemporal data calibration approach provides an useful information for local communities and governmental agency to face the new era of IoT sensor for air quality monitoring.
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Affiliation(s)
- Chieh-Han Lee
- Dept. of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
| | - Yeuh-Bin Wang
- Dept. of Environmental Monitoring and Information Management, Taiwan Environmental Protection Administration, Taipei 10042, Taiwan
| | - Hwa-Lung Yu
- Dept. of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan.
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Abstract
A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.
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49
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Caubel JJ, Cados TE, Preble CV, Kirchstetter TW. A Distributed Network of 100 Black Carbon Sensors for 100 Days of Air Quality Monitoring in West Oakland, California. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:7564-7573. [PMID: 31244080 DOI: 10.1021/acs.est.9b00282] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Ambient particulate matter (PM) pollution is a major environmental health risk in urban areas. Dense networks of low-cost air quality sensors are emerging to characterize the spatially heterogeneous concentrations that are typical of urban settings, but are not adequately captured using traditional regulatory monitors at central sites. In this study, we present the 100×100 BC Network, a 100-day deployment of low-cost black carbon (BC) sensors across 100 locations in West Oakland, California. This 15 km2 community is surrounded by freeways and affected by emissions associated with local port and industrial activities. We assess the reliability of the sensor hardware and data collection systems, and identify modes of failure to both quantify and qualify network performance. We illustrate how dynamic, local emission sources build upon background BC concentrations. BC concentrations varied sharply over short distances (∼100 m) and timespans (∼1 hour), depending on surrounding land use, traffic patterns, and downwind distance from pollution sources. Strong BC concentration fluctuations were periodically observed over the diurnal and weekly cycles, reflecting the impact of localized traffic emissions and industrial facilities in the neighborhood. Overall, the results demonstrate how distributed sensor networks can reveal the complex spatiotemporal dynamics of combustion-related air pollution within urban neighborhoods.
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Affiliation(s)
- Julien J Caubel
- Department of Mechanical Engineering , University of California, Berkeley , Berkeley , California 94720 , United States
- Energy Technologies Area , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - Troy E Cados
- Energy Technologies Area , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - Chelsea V Preble
- Energy Technologies Area , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
- Department of Civil and Environmental Engineering , University of California, Berkeley , Berkeley , California 94720 , United States
| | - Thomas W Kirchstetter
- Energy Technologies Area , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
- Department of Civil and Environmental Engineering , University of California, Berkeley , Berkeley , California 94720 , United States
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50
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Kimbrough S, Krabbe S, Baldauf R, Barzyk T, Brown M, Brown S, Croghan C, Davis M, Deshmukh P, Duvall R, Feinberg S, Isakov V, Logan R, McArthur T, Shields A. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS): Integration of Low-Cost Sensors and Reference Grade Monitoring in a Complex Metropolitan Area. Part 1: Overview of the Project. CHEMOSENSORS (BASEL, SWITZERLAND) 2019; 7:26. [PMID: 32704490 PMCID: PMC7377253 DOI: 10.3390/chemosensors7020026] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Emissions from transportation sources can impact local air quality and contribute to adverse health effects. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS), conducted over a 1-year period, researched emissions source characterization in the Argentine, Turner, and Armourdale, Kansas (KS) neighborhoods and the broader southeast Kansas City, KS area. This area is characterized as a near-source environment with impacts from large railyard operations, major roadways, and commercial and industrial facilities. The spatial and meteorological effects of particulate matter less than 2.5 μm (PM2.5), and black carbon (BC) pollutants on potential population exposures were evaluated at multiple sites using a combination of regulatory grade methods and instrumentation, low-cost sensors, citizen science, and mobile monitoring. The initial analysis of a subset of these data showed that mean reference grade PM2.5 concentrations (gravimetric) across all sites ranged from 7.92 to 9.34 μg/m3. Mean PM2.5 concentrations from low-cost sensors ranged from 3.30 to 5.94 μg/m3 (raw, uncorrected data). Pollution wind rose plots suggest that the sites are impacted by higher PM2.5 and BC concentrations when the winds originate near known source locations. Initial data analysis indicated that the observed PM2.5 and BC concentrations are driven by multiple air pollutant sources and meteorological effects. The KC-TRAQS overview and preliminary data analysis presented will provide a framework for forthcoming papers that will further characterize emission source attributions and estimate near-source exposures. This information will ultimately inform and clarify the extent and impact of air pollutants in the Kansas City area.
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Affiliation(s)
- Sue Kimbrough
- U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Stephen Krabbe
- U.S. Environmental Protection Agency, Region 7, 300 Minnesota Ave., Kansas City, KS 66101, USA
| | - Richard Baldauf
- U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Timothy Barzyk
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Matthew Brown
- U.S. Environmental Protection Agency, Region 7, 300 Minnesota Ave., Kansas City, KS 66101, USA
| | - Steven Brown
- U.S. Environmental Protection Agency, Region 7, 11201 Renner Blvd., Lenexa, KS 66219, USA
| | - Carry Croghan
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Michael Davis
- U.S. Environmental Protection Agency, Region 7, 300 Minnesota Ave., Kansas City, KS 66101, USA
| | - Parikshit Deshmukh
- Jacobs Technology Inc., 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Rachelle Duvall
- U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Stephen Feinberg
- ORISE Participant, U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Vlad Isakov
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Russell Logan
- Jacobs Technology Inc., 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Tim McArthur
- Science Systems and Applications, Inc., 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA
| | - Amy Shields
- U.S. Environmental Protection Agency, Region 7, 11201 Renner Blvd., Lenexa, KS 66219, USA
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