Using highly time resolved fine particulate compositions to find particle sources in St. Louis, MO

Abstract

High time resolution measurements of fine particulate matter composition were a component of the St. Louis – Midwest Supersite in East St. Louis, IL. Measurements of fifteen particulate matter species (Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se, Zn, OC, EC, SO4=, and NO3–) were made using semi–continuous sampling and monitoring techniques. In this study, three weeks of the hourly species data have been combined with on–site surface winds data using conditional probability function (CPF) analysis and 1–D non–parametric regression (NPR) to identify the bearing of putative local emission sources. Typically there was good agreement between the CPF and NPR results and most (but not all) of the identified emission source bearings were consistent with the location of known emission sources. Differences between the CPF and NPR methods occurred when there were infrequent high concentration events, typically a single hour, which yielded a high expected concentration with NPR but a low conditional probability with CPF. Challenges to fully identifying the suite of local point sources impacting the monitoring site include the relatively poor representation of some wind directions in such a small data set, confounding by multiple emission sources at similar bearings, and for some elements high impacts from regional scale contributions.