Citation:

Mathur, R., C. Hogrefe, A. Hakami, S. Zhao, Jim Szykman, AND G. Hagler. A Call for an Aloft Air Quality Monitoring Network: Need, Feasibility, and Potential Value. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 52(19):10903–10908, (2018). https://doi.org/10.1021/acs.est.8b02496

Impact/Purpose:

Ground-based air quality measurement networks have played a key role in characterizing human and ecological exposure to ozone air pollution and in monitoring compliance with existing air quality standards. Declining local precursor emissions due to mitigation actions, changing source composition, and technological advancements, in conjunction with health protective lower threshold air quality standards, necessitate the need to accurately quantify at a location the non-local contributions to air pollution due to atmospheric transport that by nature predominantly occurs aloft nocturnally. Yet a concerted effort to characterize ozone aloft on a continuous basis to quantify its contribution to ground-level concentrations has been lacking. Applying our classical understanding of air pollution dynamics to analyze variations in widespread surface-level ozone measurements, in conjunction with process-based interpretation from a comprehensive air pollution modeling system and detailed backward-sensitivity calculations that quantitatively link surface-level and aloft pollution, we show that accurate quantification of the amount of ozone in the air entrained from aloft every morning as the atmospheric boundary layer grows in response to surface heating is a key component for characterizing background or the non-local contribution of ozone pollution at a location. We demonstrate the need for measuring this key quantity to overcome existing limitations in attributing local versus non-local contributions. Leveraging new technology developments, we propose a cost-effective continuous aloft ozone measurement strategy that can be deployed immediately to address this critical data gap in observations and modeling capabilities supporting air quality management.

Description:

Changing precursor emission patterns in conjunction with stringent health protective air quality standards, necessitate accurate quantification of non-local contributions to ozone pollution at a location due to atmospheric transport, that by nature predominantly occurs aloft nocturnally. Concerted efforts to characterize ozone aloft on a continuous basis to quantify its contribution to ground-level concentrations however are lacking. Applying our classical understanding of air pollution dynamics to analyze variations in widespread surface-level ozone measurements, in conjunction with process-based interpretation from a comprehensive air pollution modeling system and detailed backward-sensitivity calculations that quantitatively link surface-level and aloft pollution, we show that accurate quantification of the amount of ozone in the air entrained from aloft every morning as the atmospheric boundary layer grows is the key missing component for characterizing background pollution at a location, and propose a cost-effective continuous aloft ozone measurement strategy to address critical scientific gaps in current air quality management. Continuous aloft air pollution measurements can cost-effectively be achieved through leveraging advances in sensor technology and proliferation of tall telecommunications masts. Resultant improvements in ozone distribution characterization at 400-500m altitude are estimated to be 3-4 times more effective in characterizing the surface-level daily maximum 8-hour average ozone (DM8O3) than improvements from surface measurements since they directly quantify the amount of pollution imported to a location, and furnish key-missing information on processes and sources regulating background ozone and its modulation of ground-level concentrations. Since >80% of the DM8O3 sensitivity to tropospheric ozone is potentially captured through measurements between 200-1200m altitude (a possible design goal for future remote sensing instrumentation), their assimilation will dramatically improve air quality forecast and health advisories.

URLs/Downloads:

Record Details: