Sequencing diurnal air flow patterns for ozone exposure assessment around Houston, Texas

Abstract Understanding the human health impacts of ground level ozone requires detailed knowledge of its spatial–temporal distribution beyond that provided by surface monitoring networks. Here, a novel methodology based on unsupervised multivariate statistical techniques has been developed and used to identify the transport and dispersion patterns of tropospheric ozone. The hierarchical clustering method is used to visualize air flow patterns at two time scales relevant for ozone buildup. Sequentially executed statistical methods consider hourly 1-h surface wind field measurements. First, clustering is performed at the hourly time scale to identify 1-h surface flow patterns. Then, sequencing is performed at the daily time scale to identify groups of days sharing similar diurnal cycles for the surface flow. Selection of appropriate numbers of air flow patterns allows inference of regional transport and dispersion patterns for understanding population exposure to ozone. The methods are applied to the Houston, Galveston, and Beaumont-Port Arthur, TX study domain. Representative hourly wind field patterns are determined for the entire 2004 ozone season. Then, sequencing is performed for the 32 days in exceedance of the NAAQS for 8-h ozone. Four diurnal flow patterns capturing different ozone exceedance scenarios are isolated; each scenario is associated with a distinct spatial distribution for atmospheric pollutants.