Science Inventory

Mobile air quality monitoring and comparison to fixed monitoring sites for instrument performance assessment

Citation:

Whitehill, A., M. Lunden, B. LaFranchi, S. Kaushik, AND P. Solomon. Mobile air quality monitoring and comparison to fixed monitoring sites for instrument performance assessment. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, Germany, 17(9):2991-3009, (2024). https://doi.org/10.5194/amt-17-2991-2024

Impact/Purpose:

Mobile air pollution monitoring using ground-based measurement platforms can provide high quality spatiotemporal air pollution data. As mobile air quality monitoring campaigns extend to fleet-based platforms and embrace lower cost air quality sensors, it is important to address the quality assurance needs for validating these measurements. We explore collocation-based evaluation of mobile air quality instruments against fixed regulatory sites, both when the mobile platform is parked at the fixed regulatory site and when moving at distances of meters to kilometers from the site. We demonstrate strong agreement between reference monitors in a moving platform and fixed reference sites out to distances of kilometers when using a running mean over many (~40) hourly differences between mobile and stationary site measurements. The comparability is particularly strong when only measurements from residential roads are used, and more generally when highways are excluded from the analysis. We discuss methods for assessing mobile measurements of ozone (O3), nitrogen dioxide (NO2), and odd oxygen (OX = O­3 + NO2) on an ongoing basis through comparisons with fixed regulatory sites, as well as discussing relationships between mobile and fixed reference site nitric oxide (NO) measurements.

Description:

Air pollution monitoring using mobile ground-based measurement platforms can provide high-quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller-scale air quality sensors, it is important to address the need to assess these measurements in a scalable manner. We explore the collocation-based evaluation of air quality measurements in a mobile platform using fixed regulatory sites as a reference. We compare two approaches: a standard collocation assessment technique, in which the mobile platform is parked near the fixed regulatory site for a period of time, and an expanded approach, which uses measurements while the mobile platform is in motion in the general vicinity of the fixed regulatory site. Based on the availability of fixed-reference-site data, we focus on three pollutants (ozone, nitrogen dioxide, and nitric oxide) with distinct atmospheric lifetimes and behaviors. We compare measurements from a mobile laboratory with regulatory site measurements in Denver, CO, USA, and in the San Francisco Bay Area, CA, USA. Our 1-month Denver dataset includes both parked collocation periods near the fixed regulatory sites and general driving patterns around the sites, allowing a direct comparison of the parked and mobile collocation techniques on the same dataset. We show that the mobile collocation approach produces similar performance statistics, including coefficients of determination and mean bias errors, to the standard parked collocation technique. This is particularly true when the comparisons are restricted to specific road types, with residential streets showing the closest agreement and highways showing the largest differences. We extend our analysis to a larger (yearlong) dataset in California, where we explore the relationships between the mobile measurements and the fixed reference sites on a larger scale. We show that using a 40 h running median converges to within ±4 ppbv of the fixed reference site for nitrogen dioxide and ozone and up to about 8 ppbv for nitric oxide. We propose that this agreement can be leveraged to assess instrument performance over time during large-scale mobile monitoring campaigns. We demonstrate an example of how such relationships can be employed during large-scale monitoring campaigns using small sensors to identify potential measurement biases.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:05/17/2024
Record Last Revised:06/27/2024
OMB Category:Other
Record ID: 361935