The use of conditional probability functions and potential source contribution functions to identify source regions and advection pathways of hydrocarbon emissions in Houston, Texas

Abstract

In this study, we demonstrate the utility of conditional probability functions (CPFs), potential source contribution functions (PSCFs), and hierarchical clustering analysis (HAC) to identify the source region and transport pathways of hydrocarbons measured at five photochemical assessment monitoring stations (PAMS) near the Houston Ship Channel from June to October 2003. In contrast to scatter plots, which only show the pair-wise correlation of species, commonality in CPF figures shows both correlation and information on the source region of the species in question. In this study, we use over 50 hourly volatile organic compound (VOC) concentrations and surface wind observations to show that VOCs with similar CPF patterns likely have common transport pathways. This was established with the multivariate technique, which uses the hierarchical clustering analysis to define clusters of VOCs having similar CPF patterns. This method revealed that alkenes, and in particular those with geometric isomers such as cis-/ trans-2-butene and cis-/ trans-2-pentene, have similar CPF patterns and hence, a common area of origin. The alkane isomers often show CPF patterns among themselves, and similarly, aromatic compounds often show similar patterns. We also show how calculated trajectory information can be used in the PSCF analysis to produce a graphic picture that identifies specific geographic areas associated with a given VOC (or other pollutant). The use of these techniques in the chemically and meteorologically complex environment of Houston, Texas, suggests its further utility in other areas with relatively simpler conditions.