Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-995-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-995-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Feb 2021
Research article |
| 09 Feb 2021
| 09 Feb 2021
Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration
Colby Buehler
Department of Chemical & Environmental Engineering, Yale
University, School of Engineering and
Applied Science, New Haven, Connecticut 06511, USA
SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale
University, New Haven,
Connecticut 06511, USA
Fulizi Xiong
Department of Chemical & Environmental Engineering, Yale
University, School of Engineering and
Applied Science, New Haven, Connecticut 06511, USA
SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale
University, New Haven,
Connecticut 06511, USA
Misti Levy Zamora
SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale
University, New Haven,
Connecticut 06511, USA
Department of Environmental Health and Engineering, Johns Hopkins
Bloomberg School of Public
Health, Baltimore, Maryland 21205, USA
Kate M. Skog
Department of Chemical & Environmental Engineering, Yale
University, School of Engineering and
Applied Science, New Haven, Connecticut 06511, USA
Joseph Kohrman-Glaser
Department of Mechanical Engineering, Yale University, School of
Engineering and Applied Science,
New Haven, Connecticut 06511, USA
Stefan Colton
Department of Mechanical Engineering, Yale University, School of
Engineering and Applied Science,
New Haven, Connecticut 06511, USA
Michael McNamara
Department of Electrical Engineering, Yale University, School of
Engineering and Applied Science,
New Haven, Connecticut 06511, USA
Kevin Ryan
Department of Electrical Engineering, Yale University, School of
Engineering and Applied Science,
New Haven, Connecticut 06511, USA
Carrie Redlich
Department of Internal Medicine, Yale University, School of Medicine, New Haven, Connecticut 06510, USA
Department of Environmental Health Sciences, Yale University, School of Public Health, New Haven,
Connecticut 06511, USA
Matthew Bartos
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin,
Cockrell School of Engineering, Austin, Texas 78712, USA
Brandon Wong
Civil and Environmental Engineering, University of Michigan, 2350
Hayward St, G.G. Brown Building,
Ann Arbor, Michigan 48109, USA
Branko Kerkez
Civil and Environmental Engineering, University of Michigan, 2350
Hayward St, G.G. Brown Building,
Ann Arbor, Michigan 48109, USA
Kirsten Koehler
SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale
University, New Haven,
Connecticut 06511, USA
Department of Environmental Health and Engineering, Johns Hopkins
Bloomberg School of Public
Health, Baltimore, Maryland 21205, USA
Drew R. Gentner
CORRESPONDING AUTHOR
Department of Chemical & Environmental Engineering, Yale
University, School of Engineering and
Applied Science, New Haven, Connecticut 06511, USA
SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale
University, New Haven,
Connecticut 06511, USA
Multiphase Chemistry, Max Planck Institute for Chemistry, 55128 Mainz, Germany
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Cited
18 citations as recorded by crossref.
- Design and Implementation of an Air Quality Testing System Based on STC12C5A F. Wu et al. 10.46300/9106.2021.15.110
- Laboratory and field evaluation of a low-cost methane sensor and key environmental factors for sensor calibration J. Lin et al. 10.1039/D2EA00100D
- Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network M. Levy Zamora et al. 10.1021/acsestengg.1c00367
- Transformational IoT sensing for air pollution and thermal exposures J. Pantelic et al. 10.3389/fbuil.2022.971523
- Machine Learning for Improving Accuracy and Utility of Low-Cost Environmental Air Pollution Sensor Networks for Probabilistic Spatial Exposure Assessment A. Patton et al. 10.2139/ssrn.4001163
- Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi A. Bittner et al. 10.5194/amt-15-3353-2022
- Research on the construction of portable electrochemical sensors for environmental compounds quality monitoring Q. He et al. 10.1016/j.mtadv.2022.100340
- Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. 10.1016/j.atmosenv.2023.119944
- Design, fabrication, and calibration of the Building EnVironment and Occupancy (BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor H. Fritz et al. 10.1016/j.buildenv.2022.109432
- Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment M. Chen et al. 10.3390/s22072767
- Probabilistic Machine Learning with Low-Cost Sensor Networks for Occupational Exposure Assessment and Industrial Hygiene Decision Making A. Patton et al. 10.1093/annweh/wxab105
- Non-linear probabilistic calibration of low-cost environmental air pollution sensor networks for neighborhood level spatiotemporal exposure assessment A. Patton et al. 10.1038/s41370-022-00493-y
- In Pursuit of Local Solutions for Climate Resilience: Sensing Microspatial Inequities in Heat and Air Pollution within Urban Neighborhoods in Boston, MA D. O’Brien & A. Mueller 10.3390/su15042984
- The Association Between Personal Air Pollution Exposures and Fractional Exhaled Nitric Oxide (FeNO): A Systematic Review A. Anand et al. 10.1007/s40572-024-00430-1
- Hyperlocal Air Pollution in London: Validating Low-Cost Sensors for Mobile Measurements from Vehicles H. Russell et al. 10.1021/acsestair.3c00043
- Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
- Identifying optimal co-location calibration periods for low-cost sensors M. Levy Zamora et al. 10.5194/amt-16-169-2023
- Non-linear probabilistic calibration of low-cost environmental air pollution sensor networks for neighborhood level spatiotemporal exposure assessment A. Patton et al. 10.1038/s41370-022-00493-y
17 citations as recorded by crossref.
- Design and Implementation of an Air Quality Testing System Based on STC12C5A F. Wu et al. 10.46300/9106.2021.15.110
- Laboratory and field evaluation of a low-cost methane sensor and key environmental factors for sensor calibration J. Lin et al. 10.1039/D2EA00100D
- Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network M. Levy Zamora et al. 10.1021/acsestengg.1c00367
- Transformational IoT sensing for air pollution and thermal exposures J. Pantelic et al. 10.3389/fbuil.2022.971523
- Machine Learning for Improving Accuracy and Utility of Low-Cost Environmental Air Pollution Sensor Networks for Probabilistic Spatial Exposure Assessment A. Patton et al. 10.2139/ssrn.4001163
- Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi A. Bittner et al. 10.5194/amt-15-3353-2022
- Research on the construction of portable electrochemical sensors for environmental compounds quality monitoring Q. He et al. 10.1016/j.mtadv.2022.100340
- Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. 10.1016/j.atmosenv.2023.119944
- Design, fabrication, and calibration of the Building EnVironment and Occupancy (BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor H. Fritz et al. 10.1016/j.buildenv.2022.109432
- Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment M. Chen et al. 10.3390/s22072767
- Probabilistic Machine Learning with Low-Cost Sensor Networks for Occupational Exposure Assessment and Industrial Hygiene Decision Making A. Patton et al. 10.1093/annweh/wxab105
- Non-linear probabilistic calibration of low-cost environmental air pollution sensor networks for neighborhood level spatiotemporal exposure assessment A. Patton et al. 10.1038/s41370-022-00493-y
- In Pursuit of Local Solutions for Climate Resilience: Sensing Microspatial Inequities in Heat and Air Pollution within Urban Neighborhoods in Boston, MA D. O’Brien & A. Mueller 10.3390/su15042984
- The Association Between Personal Air Pollution Exposures and Fractional Exhaled Nitric Oxide (FeNO): A Systematic Review A. Anand et al. 10.1007/s40572-024-00430-1
- Hyperlocal Air Pollution in London: Validating Low-Cost Sensors for Mobile Measurements from Vehicles H. Russell et al. 10.1021/acsestair.3c00043
- Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
- Identifying optimal co-location calibration periods for low-cost sensors M. Levy Zamora et al. 10.5194/amt-16-169-2023
Latest update: 29 Jun 2024
Short summary
In this paper we develop a stationary and portable low-cost multipollutant monitor capable of measuring a variety of human-health- and climate-related pollutants. While traditional reference instrumentation is sparsely spaced, these monitors can be deployed as a network to gain insight into the spatial and temporal variability within an urban setting, or in other targeted studies. We also implement an online calibration system to address long-term drift of sensors and adjust calibrations.
In this paper we develop a stationary and portable low-cost multipollutant monitor capable of...
