Grantee Research Project Results
2018 Progress Report: Democratization of Measurement and Modeling Tools for Community Actionon Air Quality, and Improved Spatial Resolution of Air Pollutant Concentrations
EPA Grant Number: R836286Title: Democratization of Measurement and Modeling Tools for Community Actionon Air Quality, and Improved Spatial Resolution of Air Pollutant Concentrations
Investigators: Presto, Albert , Pandis, Spyros N. , Downs, Julie , Ramachandran, Subramanian
Current Investigators: Presto, Albert , Pandis, Spyros N. , Ramachandran, Subramanian
Institution: Carnegie Mellon University
EPA Project Officer: Callan, Richard
Project Period: May 1, 2016 through April 30, 2019 (Extended to April 30, 2021)
Project Period Covered by this Report: May 1, 2018 through April 30,2019
Project Amount: $749,945
RFA: Air Pollution Monitoring for Communities (2014) RFA Text | Recipients Lists
Research Category: Environmental Justice , Air Quality and Air Toxics , Air , Particulate Matter
Objective:
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Develop portable bipollutant PM2.5/gas monitors and stationary multipollutant (PM + 4 criteria gases + VOCs) monitors; characterize their response to different primary and secondary pollutant mixtures; and test the reliability of these monitors under a variety of environmental conditions.
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Enable environmental justice and biking communities to monitor their pollutant exposure using portable monitors and a new Pittsburgh Air Quality Map (PAQmap), the interfaces of which will be designed with input from a Community Advisory Board.
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Study the interactions between community members and risk information in the form of personal monitoring and interaction with a pollution map.
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Examine the spatial representativeness of the existing air pollution monitoring network in Allegheny County using distributed monitoring and both statistical and chemical transport (PMCAMx) modeling.
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Examine the effect of community-inspired solutions to reduce air pollution exposure. The Community Advisory Board can suggest “what-if” scenarios for PMCAMx runs such as widespread retrofits of public transport buses with diesel particulate filters and emissions reductions at large industrial sources in Allegheny County.
Progress Summary:
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Developed and published new generalized calibration algorithms to convert electrochemical sensor responses from the “Real-time Affordable Multi-Pollutant” (RAMP) monitors to ambient gas concentrations and tested their long-term performance.
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Two types of low-cost PM sensors (Met-One neighborhood PM and PurpleAir monitors) were extensively evaluated by collocation with regulatory BAMs and correction factors were developed for these sensors. The accuracy of the data from these sensors was also evaluated for both short-term (1-hour) and long-term (1 year) averages. The resulting correction algorithms were published.
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About 50 RAMPs were deployed across the Pittsburgh area, including target environmental justice communities (Clairton, Braddock, Millvale), coupled with other grants. After about a year of data collection, several RAMPs were dismantled; about 25 RAMPs are operational. Analysis of pollutant spatial variations and exposure disparities were recently published.
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RAMPs were also deployed in Puerto Rico and Connecticut.
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Online (Amazon mTurk) and in-person (either one-on-one or at Open Streets events) surveys were conducted to better understand community and individual perceptions about air quality and get input on data visualization and risk communication.
- Commuter choice was evaluated through mTurk surveys to quantify whether people include pollutant data in their commute options when pollutant data are made available.
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Community partners Group Against Smog and Pollution (GASP) and Clean Water Fund (CWF) conducted extensive outreach efforts and also participated in RAMP maintenance.
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Results were presented at different workshops and conferences.
Future Activities:
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We will continue our surveys of commuter choice. Specifically, we will
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Perform surveys to determine how visitors adapt their route preferences by their method of transport (e.g., biking versus driving).
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Examine the impact of map color overlay on commuter choice.
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Several presentations will be given at the 2019 AAAR Conference, 2019 AGU Conference and 2020 Air Sensors International Conference. Several publications are in preparation or are planned.
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Several articles will be submitted for publication, including the spatial modeling results and the commuter choice results.
Journal Articles on this Report : 7 Displayed | Download in RIS Format
| Other project views: | All 23 publications | 14 publications in selected types | All 14 journal articles |
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Li HZ, Gu P, Ye Q, Zimmerman N, Robinson ES, Subramanian R, Apte JS, Robinson AL, Presto AA. Spatially dense air pollutant sampling:Implications of spatial variability on the representativeness of stationary air pollutant monitors. Atmospheric Environment:X. 2019 Apr 1;2:100012. |
R836286 (2018) R836286 (2019) R835873 (2018) R835873 (Final) |
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Malings C, Tanzer R, Hauryliuk A, Kumar SP, Zimmerman N, Kara LB, Presto AA, Subramanian R. Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring. Atmospheric Measurement Techniques. 2019 Feb 11;12(2):903-20. |
R836286 (2018) R836286 (2019) |
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Saha PK, Zimmerman N, Malings C, Hauryliuk A, Li Z, Snell L, Subramanian R, Lipsky E, Apte JS, Robinson AL, Presto AA. Quantifying high-resolution spatial variations and local source impacts of urban ultrafine particle concentrations. Science of the Total Environment. 2019; 655:473-81 |
R836286 (2018) R836286 (2019) R835873 (2018) R835873 (Final) |
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Subramanian R, Ellis A, Torres-Delgado E, Tanzer R, Malings C, Rivera F, Morales M, Baumgardner D, Presto A, Mayol-Bracero OL. Air quality in Puerto Rico in the aftermath of Hurricane Maria:a case study on the use of lower cost air quality monitors.ACS Earth and Space Chemistry. 2018 Oct 4;2(11):1179-86. DOI:10.1021/acsearthspacechem.8b00079. |
R836286 (2018) R836286 (2019) |
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Zimmerman N, Presto AA, Kumar SPN, Gu J, Hauryliuk A, Robinson ES, Robinson AL, Subramanian R. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring. Atmospheric Measurement Techniques 2018;11(1):291-313. |
R836286 (2017) R836286 (2018) R836286 (2019) R835873 (2017) R835873 (2018) R835873 (Final) |
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Tanzer R, Malings C, Hauryliuk A, Subramanian R, Presto AA. Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice. International Journal of Environmental Research and Public Health. 2019 Jan;16(14):2523. |
R836286 (2018) R835873 (Final) |
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Malings C, Tanzer R, Hauryliuk A, Saha PK, Robinson AL, Presto AA, Subramanian R. Fine particle mass monitoring with low-cost sensors:Corrections and long-term performance evaluation. Aerosol Science and Technology 2020;54:160–74. doi:10.1080/02786826.2019.1623863. |
R836286 (2018) R836286 (2019) R835873 (2019) R835873 (Final) |
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Supplemental Keywords:
vehicular exhaust, coke ovens, personal exposure, urban pollutionProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.