Development of a mobile platform for monitoring gaseous, particulate, and greenhouse gas (GHG) pollutants
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Development of a mobile platform for monitoring gaseous, particulate, and greenhouse gas (GHG) pollutants Tian Xia & James Catalan & Chris Hu & Stuart Batterman
Received: 12 October 2020 / Accepted: 18 November 2020 # Springer Nature Switzerland AG 2020
Abstract 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 μm), 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 ~ 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 T. Xia (*) : J. Catalan : S. Batterman Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA e-mail: [email protected] C. Hu Department of Electrical Engineering and Computer Science, College of Engineering, University of Michigan, Ann Arbor, MI, USA
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. Keywords Air quality monitoring . Mobile . Pollutant mapping . Gas pollutants . Particulate matter (PM) . Greenhouse gas (GHG)
Introduction Spatially and temporally resolved information on ambient air quality can reduce exposure measurement error in health studies, improve risk and disease burden projections in health impact and accountability studies, and better identify culpable sources in apportionment studies. In urban and industrial areas, air quality can exhibit considerable spatial and temporal variation, a result of different and highly variable emission sources and changing meteorology conditions. Considering PM2.5, for example, local emission sources include thermal power plants and other industry, vehicle exhaust, tire and brake wear, biomass fires, and entrained dust, among others, while re
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