Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics

Author:

Yerramilli Anjaneyulu1,Challa Venkata Srinivas2,Dodla Venkata Bhaskar Rao1,Dasari Hari Prasad3,Young John H.1,Patrick Chuck1,Baham Julius M.1,Hughes Robert L.1,Hardy Mark G.1,Swanier Shelton J.1

Affiliation:

1. Trent Lott Geospatial and Visualization Research Centre, Jackson State University, 1230 Raymond Road, Jackson, MS 39217-204, USA

2. Radiological Safety Division, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, India

3. Centro de Geophysica de Evora, University of Evora, Evora, Portugal

Abstract

The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry) model is used to simulate air quality in the Mississippi Gulf coastal region at a high resolution (4 km) for a moderately severe summer ozone episode between 18 CST 7 and 18 CST 10 June 2006. The model sensitivity is studied for meteorological and gaseous criteria pollutants (O3, NO2) using three Planetary Boundary Layer (PBL) and four land surface model (LSM) schemes and comparison of model results with monitoring station observations. Results indicated that a few combinations of PBL and LSMs could reasonably produce realistic meteorological fields and that the combination of Yonsei University (YSU) PBL and NOAH LSM provides best predictions for winds, temperature, humidity and mixed layer depth in the study region for the period of study. The diurnal range in ozone concentration is better estimated by the YSU PBL in association with either 5-layer or NOAH land surface model. The model seems to underestimate the ozone concentrations in the study domain because of underestimation of temperatures and overestimation of winds. The underestimation of NO2by model suggests the necessity of examining the emission data in respect of its accurate representation at model resolution. Quantitative analysis for most monitoring stations indicates that the combination of YSU PBL with NOAH LSM provides the best results for various chemical species with minimum BIAS, RMSE, and high correlation values.

Funder

U.S. Department of Commerce

Publisher

Hindawi Limited

Subject

Atmospheric Science,Pollution,Geophysics

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