Using Local and Regional Air Quality Modeling and Source Apportionment Tools to Evaluate Vehicles and Biogenic Emission Factors
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Carbon Monoxide (CO), oxides of nitrogen (NO_(x)) and volatile organic compounds (VOCs) affect human health, and can also play a significant role in tropospheric ozone and secondary particulate matter formation. Correctly estimating the anthropogenic emission rates of these species is important for their effective control. Additionally, isoprene from biogenic sources also plays a key role in tropospheric ozone and secondary organic aerosol (SOA) formation. In this study, emission factors and inventories of CO, NO_(x) and VOCs from on-road vehicles estimated by vehicle emission factor models and biogenic emissions of isoprene estimated by a popular biogenic emission model are evaluated using local and regional scale air quality modeling and source apportionment tools supplemented by concentration and flux data collected at surface and in the upper air. The USEPA’s Motor Vehicle Emission Simulator (MOVES) model is evaluated. Local scale analysis indicates over-estimation of NO_(x) by approximately 15%, based on the curbside data collected near a high diesel traffic rural highway and the predicted NO_(x) by the TAMU Near-Road Model. The regional scale analysis conducted using the observed NO_(x) at a number of surface air quality monitoring sites in southeast Texas (ST) and a source-oriented Community Air Quality Model (SCMAQ), a regional chemical transport model, suggests an over-estimation of NO_(x) emissions by approximately 35-55% using the MOVES-based NEI. The near-road analysis also reveals that NO_(2)/NO_(x) ratio at curbside is approximately 29%, much higher than the generally used 5% ratio. This increase in ratio resulted in predicted 8-hour ozone increase in ST by as much as 6 ppb. While the near-road analysis didn’t reveal significant overestimation in CO emissions due to high background concentrations and low emissions, the regional analysis showed that CO emission were overestimated by approximately 60% by the MOVES model. Finally, VOC emissions estimated by the MOVES model were evaluated using fluxes of 18 VOCs measured on a tall tower in urban Houston during 2008. Vehicle contributions to the observed flux were determined using the Multilinear Engine (ME-2), a receptor-oriented source apportionment model. Emission factors of vehicle exhaust and evaporative emissions were estimated using a flux footprint model and the contributions resolved by ME-2. The MOVES model estimates vehicle exhaust emissions well, but severely under-estimates evaporative emissions from parked vehicles. The Model of Emissions of Gases and Aerosol from Nature (MEGAN) estimations of isoprene, the dominant biogenic VOC, in ST were also evaluated using SCMAQ. Comparison of predicted and observed isoprene concentrations at the surface layer and upper layers revealed a significant over-prediction of isoprene in urban areas and necessity of decreasing biogenic emission reduction by 2/3rd. The over-predictions of isoprene had negligible effects on predicted ozone concentrations in ST, but the isoprene generated SOA can be overestimated by as much as 50%.
Kota, Sri H (2014). Using Local and Regional Air Quality Modeling and Source Apportionment Tools to Evaluate Vehicles and Biogenic Emission Factors. Doctoral dissertation, Texas A & M University. Available electronically from