Grantee Research Project Results
2020 Progress Report: Engage, Educate, and Empower California Communities on the Use and Applications of Low-cost Air Monitoring Sensors
EPA Grant Number: R836184Title: Engage, Educate, and Empower California Communities on the Use and Applications of Low-cost Air Monitoring Sensors
Investigators: Polidori, Andrea , Zhu, Yifang , Fine, Philip M. , Tisopulos, Laki , Dye, Timothy S
Current Investigators: Polidori, Andrea , Zhu, Yifang , Fine, Philip M. , Tisopulos, Laki , Dye, Timothy S , Hafner, Hilary
Institution: South Coast Air Quality Management District , University of California - Los Angeles , Sonoma Technology, Inc.
EPA Project Officer: Callan, Richard
Project Period: May 1, 2016 through April 30, 2019 (Extended to April 30, 2022)
Project Period Covered by this Report: May 1, 2020 through April 30,2021
Project Amount: $749,820
RFA: Air Pollution Monitoring for Communities (2014) RFA Text | Recipients Lists
Research Category: Environmental Justice , Air Quality and Air Toxics , Air , Particulate Matter
Objective:
The overall objective of the proposed research is to provide California communities with the knowledge necessary to appropriately select, use, and maintain “low-cost” sensors and to correctly interpret sensor data. This will be accomplished by pursuing the following four specific aims: (1) develop new methodologies to educate and engage communities on the use and applications of “low-cost” sensors; (2) conduct testing to characterize the performance of commercially available “low-cost” sensors and to identify candidates for field deployment; (3) deploy the selected sensors in California communities, and interpret the collected data; and (4) communicate the lessons learned to the public through a series of outreach activities.
Progress Summary:
Aim 1. South Coast AQMD worked with STI (co-Principal Investigator) to complete the Educational Toolkit. This Toolkit includes the “Community in Action: A Comprehensive Guidebook on Air Quality Sensors”, three training videos, data analysis and visualization tools, and copies of resources developed for use during the STAR Grant (e.g., surveys, a release of liability form, examples of data analysis provided to communities, examples of reports created by communities, etc.). The Guidebook and resources are intended to support future air quality sensor projects through all phases: from planning a project to collecting and analyzing the data to taking action. Furthermore, the lessons and resources shared in the Toolkit will better enable communities to collect high quality and usable data. During this period, South Coast AQMD extended the original contract with Mazama Science, and the collaborative work has resulted in enhancements to the AirSensor (version 1.0) and DataViewer package (version 1.0.1). The AirSensor is a publicly available, open-source R-package that facilitates easier access to data from the project sensors, functions to process that data, and tools for analysis and visualization. This package has undergone external review and been released through CRAN (the Comprehensive R Archive Network). The DataViewer is a web-based application that leverages the capabilities of the AirSensor to allow project participants to engage with their sensor data in an intuitive way (i.e., this tool is user friendly, and no programming experience is required). South Coast AQMD staff presented the DataViewer to STAR Grant communities during final workshops, and the tool is now available for public use. The final workshops were completed during this period. All participants were invited to keep their sensors, and they now have the benefit of access to the tools and resources developed through this project.
Aim 3. Further analysis of the data from the sensors deployed during the STAR Grant was undertaken in the past reporting period. South Coast AQMD assisted UCLA (co-Principal Investigator) with the preparation of a manuscript sharing an analysis of data from paired indoor and outdoor sensors from a single community. This manuscript has been submitted and is in review. In addition, South Coast AQMD staff leveraged the AirSensor package (version 1.0) to complete an analysis of the performance of all STAR Grant sensors. This analysis covers three years, and data from 257 outdoor sensors are included. In this analysis, SOH metrics and QA/QC algorithms were used to examine sensor performance over time. In addition, one subset of 16 sensors was co-located at an air monitoring station (AMS), and the performance of these sensors was examined with respect to the high-quality reference data from the AMS. This dataset is novel regarding the number of sensors included and the length of the deployment and offered key takeaways in terms of sensor drift, seasonal variability in performance, and the agreement between co-located sensors deployed at different times. This manuscript is currently in preparation.
Aim 4. During this reporting period, final workshops were completed, at which South Coast AQMD staff shared a summary of project results and provided a demonstration of the DataViewer tool. A manuscript providing an overview of and introduction to the AirSensor package (version 0.5) and DataViewer tool (version 0.9.7) was published. Another manuscript was drafted sharing lessons learned, discussing how these lessons informed the development of the Educational Toolkit, and introducing the Guidebook. Two additional manuscripts are in preparation, sharing results from analyses of the sensor data.
Figure 1. Sensors deployed in 14 California communities between October 2017 and April 2020.
Future Activities:
Aim 3. We anticipate the completion of two publications that provide in-depth sensor data analysis during the subsequent reporting period. As described, one publication will focus on air quality sensor data from a single community. In contrast, the second publication provides an overview of the long-term performance of all sensors deployed under the STAR Grant.
Aim 4. Work during the subsequent reporting period will focus primarily on the dissemination of lessons learned and final products. For example, South Coast AQMD staff will present the Educational Toolkit both internally and externally. Internal presentations will increase awareness of these resources among other groups at South Coast AQMD, including groups involved with public engagement and outreach. External presentations or webinars (e.g., at scientific conferences) will increase awareness of these resources among communities and researchers working with low-cost air quality sensors. In addition to presentations, we will explore other methods of dissemination, for example, attending local outreach events or making video tutorials to introduce the AirSensor package. Furthermore, the completion of the three publications in preparation will also support disseminating lessons learned and final products.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 32 publications | 9 publications in selected types | All 9 journal articles |
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Feenstra B, Collier-Oxandale A, Papapostolou V, Cocker D, Polidori A. The AirSensor open-source R-package and DataViewer web application for interpreting community data collected by low-cost sensor networks. Environmental Modelling & Software 2020;134:104832. |
R836184 (2020) |
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Progress 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.
Project Research Results
- Final Report
- 2019 Progress Report
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- Original Abstract
9 journal articles for this project