Abstract. Mobile-platform measurements provide new opportunities
for characterizing spatial variations in air pollution within urban areas,
identifying emission sources, and enhancing knowledge of atmospheric
processes. The Aclima, Inc., mobile measurement and data acquisition platform
was used to equip four Google Street View cars with research-grade
instruments, two of which were available for the duration of this study.
On-road measurements of air quality were made during a series of sampling
campaigns between May 2016 and September 2017 at high (i.e., 1 s)
temporal and spatial resolution at several California locations: Los
Angeles, San Francisco, and the northern San Joaquin Valley (including
nonurban roads and the cities of Tracy, Stockton, Manteca, Merced, Modesto,
and Turlock). The results demonstrate that the approach is effective for
quantifying spatial variations in air pollutant concentrations over
measurement periods as short as 2 weeks. Measurement accuracy and
precision are evaluated using results of weekly performance checks and
periodic audits conducted through the sampler inlets, which show that
research instruments located within stationary vehicles are capable of
reliably measuring nitric oxide (NO), nitrogen dioxide (NO2), ozone
(O3), methane (CH4), black carbon (BC), and particle number (PN)
concentration, with bias and precision ranging from < 10 % for
gases to < 25 % for BC and PN at 1 s time resolution. The quality
of the mobile measurements in the ambient environment is examined by
comparisons with data from an adjacent (< 9 m) stationary regulatory
air quality monitoring site and by paired collocated vehicle comparisons,
both stationary and driving. The mobile measurements indicate that United States Environmental Protection Agency (US EPA)
classifications of two Los Angeles stationary regulatory monitors' scales of
representation are appropriate. Paired time-synchronous mobile measurements
are used to characterize the spatial scales of concentration variations when
vehicles were separated by < 1 to 10 km. A data
analysis approach is developed to characterize spatial variations while
limiting the confounding influence of diurnal variability. The approach is
illustrated using data from San Francisco, revealing 1 km scale differences
in mean NO2 and O3 concentrations up to 117 % and 46 %,
respectively, of mean values during a 2-week sampling period. In San
Francisco and Los Angeles, spatial variations up to factors of 6 to 8 occur
at sampling scales of 100–300 m, corresponding to 1 min averages.
Supplementary material to "Mobile-Platform Measurement of Air Pollutant Concentrations in California: Performance Assessment, Statistical Methods for Evaluating Spatial Variations, and Spatial Representativeness"
