Abstract

Abstract. Plume-in-grid (PinG) models incorporating a host Eulerian model and a subgrid-scale model (usually a Gaussian plume or puff model) have been used for the simulations of stack emissions (e.g., fossil fuel-fired power plants and cement plants) for gaseous and particulate species such as nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter (PM) and mercury (Hg). Here, we describe the extension of a PinG model to study the impact of an oil refinery where volatile organic compound (VOC) emissions can be important. The model is based on a reactive PinG model for ozone (O3), which incorporates a three-dimensional (3-D) Eulerian model and a Gaussian puff model. The model is extended to treat PM, with treatments of aerosol chemistry, particle size distribution, and the formation of secondary aerosols, which are consistent in both the 3-D Eulerian host model and the Gaussian puff model. Furthermore, the PinG model is extended to include the treatment of volume sources to simulate fugitive VOC emissions. The new PinG model is evaluated over Greater Paris during July 2009. Model performance is satisfactory for O3, PM2.5 and most PM2.5 components. Two industrial sources, a coal-fired power plant and an oil refinery, are simulated with the PinG model. The characteristics of the sources (stack height and diameter, exhaust temperature and velocity) govern the surface concentrations of primary pollutants (NOx, SO2 and VOC). O3 concentrations are impacted differently near the power plant than near the refinery, because of the presence of VOC emissions at the latter. The formation of sulfate is influenced by both the dispersion of SO2 and the oxidant concentration; however, the former tends to dominate in the simulations presented here. The impact of PinG modeling on the formation of secondary organic aerosol (SOA) is small and results mostly from the effect of different oxidant concentrations on biogenic SOA formation. The investigation of the criteria for injecting plumes into the host model (fixed travel time and/or puff size) shows that a size-based criterion is recommended to treat the formation of secondary aerosols (sulfate, nitrate, and ammonium), in particular, farther downwind of the sources (beyond about 15 km). The impacts of PinG modeling are less significant in a simulation with a coarse grid size (10 km) than with a fine grid size (2 km), because the concentrations of the species emitted from the PinG sources are relatively less important compared to background concentrations when injected into the host model with a coarser grid size.

Highlights

  • An Eulerian air quality model calculates concentrations of pollutants in a three-dimensional (3-D) grid and the modeled concentrations are spatially uniform within each grid cell

  • A PinG treatment for volume sources was developed and a PinG simulation was conducted for the first time for industrial sources of SO2, nitrogen oxides (NOx), and volatile organic compound (VOC)

  • The results show the importance of source characteristics for the surface concentrations of primary pollutants emitted aloft (e.g., NOx, SO2, and primary particulate matter (PM)) simulated with PinG

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Summary

Introduction

An Eulerian air quality model calculates concentrations of pollutants in a three-dimensional (3-D) grid and the modeled concentrations are spatially uniform within each grid cell. PinG modeling, compared to a standard grid-based Eulerian model simulation, typically leads to a spatial redistribution of O3 concentrations due to its interaction with nitrogen oxides (NOx), but a negligible effect on the domain-wide O3 budget (e.g., Seigneur et al, 1981; Kumar and Russell, 1996; Karamchandani et al, 2002). Vijayaraghavan et al (2006) compared concentrations simulated with a subgrid-scale puff model (SCICHEM) used in a PinG model (CMAQ-APT) with aircraft measurements of power plant plumes. Model performance is evaluated by comparison to measurements and the impact of the PinG model on air pollutant concentrations due to emissions from the industrial sources is presented

Model development
Description of the simulations
Simulation setup
Longitude
Emissions
Results
BDQA network
Megapoli campaign
Impacts of PinG modeling on pollutant concentrations
Impacts of the volume source treatment in the PinG model
Sensitivity to the criterion for puff injection
Sensitivity to the horizontal grid size
Conclusions
Full Text
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