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Uncertainty in collocated mobile measurements of air quality
Citation:
Whitehill, A., M. Lunden, S. Kaushik, AND P. Solomon. Uncertainty in collocated mobile measurements of air quality. Atmospheric Environment: X. Elsevier B.V., Amsterdam, Netherlands, 7:na, (2020). https://doi.org/10.1016/j.aeaoa.2020.100080
Impact/Purpose:
This study addresses methods for analyzing mobile air pollution monitoring data. Mobile monitoring of air pollution has the potential to revolutionize our understanding of air pollution exposure on ultra-fine spatial scales, especially in environmental justice neighborhoods. However, the multi-dimensional spatiotemporal data acquired by mobile air pollution monitoring platforms in complex and challenging to analyze. In this paper, we address challenges with assessing quality assurance and method performance evaluations in a mobile monitoring environment. We utilize robust statistical metrics based on the median to assess potential sources of uncertainty in mobile measurements of air pollution in both stationary and mobile environments. We use a dataset from Denver, CO in 2014, in which3 identical mobile platforms drove in coordinated driving patterns. This unique dataset allowed us to directly compare collocated platforms while parked and while driving. This work will form the basis for developing statistical measures of quality assurance and data validation for future mobile monitoring campaigns.
Description:
Mobile mapping of air pollution has the potential to provide pollutant concentration data at unprecedented spatial scales. Characterizing instrument performance in the mobile context is challenging, but necessary to analyze and interpret the resulting data. We used robust statistical methods to assess mobile platform performance using data collected with the Aclima Inc. mobile air pollution measurement and data acquisition platform installed on three Google Street View cars. They were driven throughout the greater Denver metropolitan area between July 25, 2014 and August 14, 2014, measuring ozone (O3), nitrogen dioxide (NO2), nitric oxide (NO), black carbon (BC), and size-resolve particle number counts (PN) betw¬een 0.3 μm and 5.0 μm diameter. August 6, 2014 was dedicated to parked and moving collocations among the three cars, allowing an assessment of measurement precision and bias. We used the median absolute deviation (MAD) to estimate instrument precision from outdoor, parked collocations. Bias was assessed by measurements obtained from parked cars using the standard deviation of median values over a collocated measurement period, as well as by Passing-Bablok regression statistics while the cars were moving and collocated. For the moving collocation periods, we compared the distribution of 1-σ standard deviations among the 3 cars to the estimated distribution assuming only measurement uncertainty (precision and bias). The distribution of mobile measurements agreed well with the theoretical uncertainty distribution at the lower end of the distribution for O3, NO2, and PN. We assert that the difference between the actual and theoretical distributions is due to real spatial variability between pollutants. The agreement between the parked car estimates of uncertainty and that measured during the mobile collocations (at the lower quantiles) provides evidence that on-road collocation while parked could be sufficient for estimating measurement uncertainties of a mobile platform, even when extended to the moving environment.
