The work we are proposing has the potential to greatly enhance our capability to assess human exposures to harmful air pollutants. We propose to develop and field test a robust cartop air pollution monitoring package for mounting on vehicles of opportunity such as rideshare (e.g., Uber, Lyft) delivery vehicles (e.g., FedEx, UPS, USPS) and public transportation (e.g., buses, trams). Our approach of using relatively inexpensive air pollutant sensors in the monitoring package, combined with drive-by calibrations of these sensors at fixed stations having more sophisticated air monitoring instruments, optimizes the precision and accuracy of the sensor measurements while?very importantly?providing an economical path for eventual widespread use. This approach would enable a new paradigm for air pollution monitoring that produces high-resolution mapping of air pollutants within cities, towns, and rural areas with the spatial and temporal resolution needed for determining actual exposures of individuals to specific air pollutants. This new capability would overcome the limitations of the current air pollution monitoring network, which uses relatively sparse fixed-base measurement stations that are located so as to provide average concentrations that are useful for determining compliance with EPA air quality standards, but cannot provide the detail needed for human exposure assessment. In this work we will develop a compact, easy-to-install enclosure that will mount on the rooftops of vehicles. The enclosure will house the Personal Air Monitor (PAM) we developed in a previous NIH/NIEHS grant. The PAM makes use of low-cost, low-power sensors that we have evaluated as the most robust on the market today for measuring the air pollutants CO, CO2 and particulates (PM1 and PM2.5). We propose new innovations, for which we have recently filed provisional patent applications, for weatherproofing and powering the PAM in the enclosure while causing minimal inconvenience for the vehicle driver. We will collaborate with the Denver City and County Department of Public Health and Environment to field test the use of the air monitoring package on 5 service vehicles over a period of 3 months. Data from the field test will be transmitted via an LTE module for cellular uploading to a public database. We will analyze the results to evaluate: (1) the robustness of the cartop enclosure during routine extended use and in weather events; (2) performance of the sensors; (3) the effectiveness of the drive-by calibration protocol; (4) the quality of the data obtained; and (5) the ability of non- specialists to follow the procedures and use the rooftop air monitoring system effectively. The proposed work addresses health needs of the U.S., where 43% of the population resides in counties that have unhealthy levels of one or more air pollutants; globally, 4.2 million premature deaths per year are linked to ambient air pollution. Continuous monitoring by hundreds of vehicles within a city would allow creation of real-time air pollution maps that would be extremely useful for identifying major sources of air pollutants and for traffic planning to minimize air pollution. This is particularly important from the environmental justice standpoint in that low-income families tend to live near air pollution sources.

Public Health Relevance

Human exposure to air pollutants is poorly known due to the very small number of mandated air monitoring stations within cities and rural areas. In order to better assess the effects of air pollutants on human health, we will develop and evaluate a low-cost air quality monitoring package for use on rideshare and other vehicles such as buses, trams and delivery vehicles to obtain high resolution mapping of air pollutants on a continuous basis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43ES031884-01A1
Application #
10134741
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ravichandran, Lingamanaidu V
Project Start
2021-02-15
Project End
2022-01-31
Budget Start
2021-02-15
Budget End
2022-01-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Ludlum Measurements, Inc.
Department
Type
DUNS #
116768343
City
Boulder
State
CO
Country
United States
Zip Code
80301