| Particulate matter (PM) in the atmosphere originates from a variety of sources, both natural and anthropogenic, and is of concern due to the adverse affects to human health and visibility caused by particulate air pollution. To determine the major sources of PM in an area, trace element concentrations in PM2.5 can be measured and used as tracers in source-receptor models. In this thesis, a method for sampling and analysis of trace elements in PM2.5 is described. Samples are collected on cellulose filters using high volume samplers. The filters are then microwave-digested in a solution of nitric acid, hydrogen peroxide, and trace hydrofluoric acid and are analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Trace element concentrations are then used, along with other components of PM2.5, in two source-receptor models: Unmix and Positive Matrix Factorization (PMF). The eleven major sources determined by PMF are secondary sulfate; nitrate; crustal material; vehicle emissions and road dust; steel production; specialty steel production and processing; wood combustion, vegetative detritus and cooking; a gallium-rich source, and sources of lead, cadmium, and selenium. The conditional probability function (CPF) and the potential source contribution function (PSCF) were used with the PMF-modeled source contributions and wind direction or HYSPLIT back trajectories to determine the most probable directions and locations of the sources. Findings are compared with another measurement technique, the RSMS III, a laser ablation time-of-flight mass spectrometer. Several convergent conclusions reinforce hypotheses regarding PM2.5 in Pittsburgh. |
