Grantee Research Project Results
2024 Progress Report: Using stationary and mobile low-cost sensors to assess air quality
EPA Grant Number: SU840407Title: Using stationary and mobile low-cost sensors to assess air quality
Investigators: El-Sayed, Marwa , Compere, Marc , Adkins, Kevin
Institution: Embry - Riddle Aeronautical University
EPA Project Officer: Harper, Jacquelyn
Phase: I
Project Period: July 1, 2022 through May 9, 2025
Project Period Covered by this Report: July 1, 2023 through June 30,2024
Project Amount: $25,000
RFA: 18th Annual P3 Awards: A National Student Design Competition Focusing on People, Prosperity and the Planet (2021) RFA Text | Recipients Lists
Research Category: Urban Air Toxics , Heavy Metal Contamination of Soil/Water , P3 Awards , P3 Challenge Area - Air Quality
Objective:
Particulate matter (PM) is a well-known atmospheric pollutant that poses significant risks to both human health and the environment. In the United States, PM concentrations are regulated under the National Ambient Air Quality Standards (NAAQS). While current infrastructure is designed to monitor PM pollution at urban and regional scales, traditional monitoring methods face limitations in capturing fine-scale spatial and temporal variations. Additionally, the high cost and size of conventional monitoring equipment restrict widespread deployment, creating gaps in coverage, particularly in densely populated urban areas where air pollution is most concentrated. This project addresses the need for more sustainable and accessible air pollution monitoring methods to enhance environmental protection in these high-risk areas. Our goal is to increase the availability of air quality sensors, expand the number of air quality observations, and improve the spatial resolution of these measurements by using low-cost particulate matter sensors (LCPMS). We aim to characterize and compare the performance of three different commercially available LCPMS, implemented in both stationary and mobile modes of operation, enabling the collection of horizontal and vertical profiles of pollutants. The innovation in this project lies in our ability to measure PM concentrations across three distinct operational dimensions: (1) stationary (1D), (2) mobile on manned vehicles (2D), and (3) mobile on unmanned aerial vehicles (UAVs) (3D). This experimental approach will serve as proof of concept for developing cost-effective monitoring systems that can be used by the public and deployed on both manned and unmanned vehicles. Our findings have the potential to significantly improve atmospheric PM models, enhancing the accuracy of general ambient conditions, point-source pollution, and plume dispersion models. The use of UAVs is particularly critical for capturing vertical profiles, which are essential for advancing PM modeling and, ultimately, improving public health outcomes.
Progress Summary:
The following is a detailed summary of the key milestones and project tasks completed since its initiation in July 2023. This project has generated both technical advancements and educational benefits.
Technical Progress: The 1D stationary testing was successfully conducted at two primary locations: indoors in a laboratory and outdoors in a shed, allowing for data comparisons between the two settings. For the 2D ground-based mobile testing, the stationary configuration was mounted onto a vehicle borrowed from the University of Central Florida. Two types of vehicles were used during the experiments. First, a Ford F-250 truck towed the 1D sensor configuration and DustTrak around Central Florida to collect data. Second, an all-terrain John Deere Gator vehicle, designed for mobile research, was utilized for data collection around the ERAU campus. Sensors were securely mounted using zip ties, and driving tests lasted 60-90 minutes, involving loops around the campus. The 1D stationary and 2D mobile data were then integrated with 3D aerial data sets. A 3D sensor model was designed to fit the constraints of a UAV and 3D-printed using a filament printer. The airborne testing was conducted over the campus athletic field, with particulate matter (PM) readings collected at various elevations during ascents and descents up to 200 feet. Comprehensive analyses and inter- comparison of the sensor data allowed for the development of distinct sensor profiles. These profiles were used to calibrate and adjust sensor readings, ensuring data accuracy. Preliminary results have demonstrated the effectiveness of UAV-based PM sensor payloads across different operating modes. The technical deliverable of the project was a LCPMS setup, capable of monitoring atmospheric particle pollutants in three distinct modes of operation.
Educational Impact: This project also led to the formation of a student club, MOVE UAS, which engages students from diverse disciplines, including Civil, Mechanical, and Aerospace Engineering, as well as Aeronautical Science pilots. The project was incorporated into several courses taught by the PIs at ERAU, with students participating in operational planning, development of best practices and standard operating procedures for flight activities, aircraft development and testing, data collection, and post-processing. Additionally, the project raised awareness among new researchers and students about the Clean Air Act (CAA), the National Ambient Air Quality Standards (NAAQS), and the impact of air pollution on human health and climate change.
Future Activities:
We are continuing our data analysis to compare the performance of the LCPMS across the three modes of operation. Our next step is to conduct a continuous 10-day lab test of the full sensor setup, followed by testing it against reference monitors at the EPA monitoring site in Orange County, Orlando, Florida. Once these phases are completed, our goal is to collect data using all three modes of operation at an emission source, ideally a landfill or industrial facility, to provide recommendations on which sensor performs best in each mode of operation.
Journal Articles:
No journal articles submitted with this report: View all 3 publications for this projectSupplemental Keywords:
air pollution measurement methods, engineering, particulates, ambient air, (atmosphere), environmental justice, low-cost sensors, particulate matterRelevant Websites:
El-Sayed Research Group Exit , Unvail Lab Exit
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.