Modeling and Source Apportionment of Primary and Secondary PM_2.5 in the Atmosphere

Source apportionment of PM_2.5 is important to identify the source categories that are responsible for the concentrations observed at a particular receptor. Although receptor models have been used to do source apportionment, they do not fully take into account the chemical reactions (including photochemical reactions) involved in the formation of secondary fine particles. Secondary fine particles are formed from photochemical and other reactions involving precursor gases such as sulfur dioxide (SO₂), oxides of nitrogen (NO_x), ammonia (NH₃) and volatile organic compounds (VOC). The purpose of this research work was to model primary and secondary PM_2.5 concentrations in the state of Tennessee (TN) and to identify the major source categories contributing to ambient fine particles.

On-road mobile and point source inventories for the state of TN were estimated and compiled by the research group at the University of Tennessee (UT). The national emissions inventory (NEI) for the year 1999 was used for the other states. The Models3/CMAQ modeling system was used for the photochemical/secondary particulate matter modeling. The modeling domain consisted of a nested 36-12-4 km domain. The 4 km domain covered the entire state of TN. The episode chosen for the modeling runs was August 29 to September 9, 1999. Different scenarios were run to quantify the contribution of the various source categories. The overall model performance was found to be satisfactory. On average, the coal-fired power plants formed the major source category accounting for about 29 to 39% of the 24-hr average total PM_2.5 concentration. On-road mobile sources contributed around 17 to 24%, of which, about 60% was from fugitive dust on paved and unpaved roads. Non-road mobile sources contributed about 3 to 6%. Non-linearity issues were encountered and recommendations were made for further research. The results of this work will be helpful in addressing policy issues targeted at designing control strategies to meet the National Ambient Air Quality Standard (NAAQS) for PM_2.5 in TN and the surrounding states.