Development of a mobile platform for monitoring gaseous, particulate, and greenhouse gas (GHG) pollutants

The Michigan Pollution Assessment Laboratory (MPAL) is a mobile air quality monitoring platform designed to measure conventional, toxic, and greenhouse gas (GHG) air pollutants. The spatially and temporally resolved data collected can be used for multiple purposes, such as mapping spatial patterns and identifying peaks. The truck-based platform includes instrumentation for 11 gaseous pollutants and for particulate matter (PM), size distribution (7 nm to 20 mu m), PM10, black and brown carbon, and trace metals. MPAL is equipped with meteorological instruments, a high-accuracy GPS, forward and reverse cameras, and a data logging and display system. We selected commercially available instrumentation based on sensitivity, response time, and robustness. The vehicle's power system allows similar to 6.5 h of continuous operation with all instruments operating. This article details the design, construction, and evaluation of MPAL and summarizes data collected in its first year (March 2019 to March 2020) of operation. We completed a series of runs on 84 days in Detroit, Michigan, an area with a diverse set of traffic, industrial, and commercial emission sources, and collected 265,816 1-s observations (excluding collocations, zero checks, and other quality assurance measurements). Using data from these runs as well as special tests, we present results of performance evaluations that examined the response time, PM losses, and wind measurements and compare results to stationary regulatory monitoring data. We highlight key issues and provide practical solutions to help evaluate and resolve these issues and share many lessons learned in developing and using a mobile platform.

Automated summary

The Michigan Pollution Assessment Laboratory (MPAL) is a mobile air quality monitoring platform designed to measure various air pollutants, with data collected and evaluated in Detroit over one year. The study presents performance evaluations of the platform, including response time, PM losses, and wind measurements, comparing results to stationary monitoring data.