Field study and source attribution for PM_2.5 and PM₁₀ with resulting reduction in concentrations in the neighborhood north of the Houston Ship Channel based on voluntary efforts

Abstract

When annual average PM_2.5 (fine particulate matter sized 2.5 microns and less) data for 2005 became available in April 2006 and the 3-yr average PM_2.5 concentration in an area just north of the Houston Ship Channel reached 15.0 µg/m³, the Texas Commission on Environmental Quality (TCEQ) initiated daily collection of quartz fiber as well as Teflon PM_2.5 filter samples for chemical speciation analysis. The purpose of the chemical speciation analysis was to use the speciation data, together with meteorological data and hourly TEOM (tapered element oscillating microbalance) PM_2.5 mass data, to identify the causes of the high PM_2.5 concentrations affecting the monitoring site and the neighborhood. The ultimate purpose was to target emission reduction efforts to sources contributing to the high measured PM_2.5 concentrations. After a year of data collection, it was recognized that a specific source, unpaved driveways and loading areas along the Ship Channel and dirt tracked onto Clinton Drive, the main artery running east-west north of the Ship Channel, were the primary cause for the Clinton Drive site's measuring PM_2.5 concentrations significantly higher than other sites in Houston. The source characterization and remediation steps that have led to sustained reduced concentrations are described in this paper.

Implications:

With PM_2.5 exceedances it can be essential to have or develop chemical speciation data as part of the process of identifying the source types causing exceedances of an annual standard. Positive matrix factorization (PMF) analysis proved to be a powerful tool that identified the two locally emitted species contributing to exceedances, which did not occur at other sites in the region. They were calcium sulfate (gypsum), an industrial by-product, and soil minerals. Other data analysis approaches were necessary to distinguish North African dust events, which PMF failed to identify.