You are here:
Application of WRF/Chem over the Continental U.S. under the AQMEII Phase II: Part 2. Evaluation of 2010 Application and Responses of Air Quality and Meteorology-Chemistry Interactions to Changes in Emissions and Meteorology from 2006 to 2010
Citation:
Yahya, K., K. Wang, Y. Zhang, AND Tad Kleindienst. Application of WRF/Chem over the Continental U.S. under the AQMEII Phase II: Part 2. Evaluation of 2010 Application and Responses of Air Quality and Meteorology-Chemistry Interactions to Changes in Emissions and Meteorology from 2006 to 2010. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 8(2015):2095-2117, (2015).
Impact/Purpose:
The National Exposure Research Laboratory’s (NERL’s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA’s mission to protect human health and the environment. HEASD’s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA’s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
The Weather Research and Forecasting model with Chemistry (WRF/Chem) simulation with the 2005 Carbon Bond (CB05) gas-phase mechanism coupled to the Modal for Aerosol Dynamics for Europe (MADE) and the Volatility Basis Set (VBS) approach for secondary organic aerosol (SOA) (MADE/VBS) are conducted over a domain in North America for 2006 and 2010 as part of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 project. This Part II paper focuses on comparison of model performance in 2006 and 2010 as well as analysis of the responses of air quality and meteorology-chemistry interactions to changes in emissions and meteorology from 2006 to 2010. In general, emissions for gaseous and aerosol species decrease from 2006 to 2010, leading to a reduction in gaseous and aerosol concentrations and associated changes in radiation and cloud variables due to various feedback mechanisms. Compared to 2006, the performance for most meteorological variables in 2010 gives lower normalized mean biases (NMBs) but higher normalized mean errors (NMEs) and lower correlation coefficients (Corr). This indicates some compensation in over- and underpredictions against observations. The worse meteorological performance in 2010 is likely due to inaccurate chemistry feedbacks resulted from less accurate emissions in 2010 as the values of Corr are higher and NMEs are lower for the 2010 WRF only simulation than those for the 2010 WRF/Chem simulation. The model also shows worse performance for most chemical variables in 2010. This could be attributed to underestimations in emissions of some species such as primary organic aerosol in some areas of the U.S. in 2010, inaccurate meteorological predictions, as well as the use of a coarse grid resolution. The effects of the decrease in emissions and changes in meteorology between 2006 and 2010 result in complex changes in model predictions in 2010 due to chemistry-meteorology feedbacks. The inclusion of chemical feedbacks to meteorology, clouds, and radiation reduces model biases in meteorological predictions in 2010; however, it increases model errors and weakens correlations. Sensitivity simulations comparing WRF and WRF/Chem simulations for 2006 and 2010 show that for 2006, the performance of meteorological variables is comparable between both but for 2010, WRF/Chem performs slightly worse than WRF. These results indicate a need to further improve the accuracy of the model representations of SOA, meteorology for extreme events, and chemistry-meteorology feedbacks in the online-coupled models.
URLs/Downloads:
YAHYA ET AL_SUBMITTED MAY31 2014.PDF (PDF, NA pp, 12432.901 KB, about PDF)Geoscientific Model Development
