Modeling air quality during a wintertime cloudy stagnation period in Boise Idaho using the WRF-CMAQ framework

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Tuesday, 4 February 2014: 9:00 AM
Room C113 (The Georgia World Congress Center )
RUI zhang, Washington State University, Pullman, WA; and S. Chung, T. M. VanReken, and B. K. Lamb

During wintertime, emissions from wood burning and other sources can lead to significant air quality concerns in urban valleys of the Pacific Northwest. An unexpected phenomenon was observed near Boise, Idaho during the Treasure Valley PM2.5 Precursor Study in Dec. 2008 to Jan. 2009. Relatively low pollutant concentrations persisted during a multi-day cloudy stagnation period that occurred after a build-up of pollutants during a typical clear sky inversion period. The WRF-CMAQ modeling framework was applied to evaluate how well it can capture the air quality evolution during these clear and cloudy stagnation periods. The simulations were carried out using two nested domains with horizontal resolution of 12 km and 4 km and 38 vertical layers, with the first model layer height around 39 m. To improve the performance of WRF, 2-m temperature, 10-m wind speed and ground relative humidity from 104 stations in the region were assimilated into WRF. Different land-surface, radiation and cumulus physical modules in WRF were used to assess which options best reproduced the observed meteorological conditions during the cloudy stagnation period. Without observation nudging using surface observations, the WRF model did not simulate the observed cloudy stagnant conditions. Comparing with sounding and four channel net radiation sensor data, WRF with observational nudging was able to simulate low-level clouds in some days, but not for the whole duration of the cloudy stagnation period. Using the RUC land surface model and RRTMG shortwave radiation scheme can further improve the predicted bias in ground temperature associated with the bias in clouds. Combined with the CMAQ chemical transport model, the modeling framework performed reasonably in capturing the range of observed primary pollutants concentrations such as those of CO during clear-sky conditions, but persistently and significantly overestimated the concentrations during the cloudy stagnation period. The results indicate that the CMAQ model is unable to simulate the low pollutant concentrations associated with wintertime cloudy stagnation conditions. These results have implications for air quality management during such periods.