@article{zhang_wang_wu_wang_minoura_wang_2014, title={Impacts of updated emission inventories on source apportionment of fine particle and ozone over the southeastern US}, volume={88}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2014.01.035}, abstractNote={As the U.S. Environmental Protection Agency updates the National Emission Inventory (NEI), the source contributions (SC) of major source sectors to major pollutants based on source apportionment techniques should be periodically reassessed to reflect changes in SCs due to changes in emissions. This work assesses emission updates from the 1999 NEI version 2 (NEI99v2) and the 2005 NEI (NEI05) and the resulting differences in SCs using the two inventories. Large differences exist in the emissions of nitrogen oxide, formaldehyde, ammonia, terpene, and primary PM2.5 between NEI99v2 and NEI05. Differences in emissions lead to differences in model performance and source appointment. SCs of ten major source categories to fine particulate matter (PM2.5) are estimated using the Community Multiscale Air Quality modeling system with the Brute Force Method (CMAQ/BFM) andNEI05and compared with those obtained previously using CMAQ/BFM with NEI99v2. In January, compared to CMAQ/BFM (NEI99v2), CMAQ/BFM (NEI05) shows that miscellaneous areas, biomass burning, and coal combustion remain the top three contributors to PM2.5 but with different ranking and higher SCs (17.7%, 16.0%, and 14.1% for NEI05 vs. 11.8%, 13.7%, and 10.8% for NEI99v2, respectively). In July, coal combustion, miscellaneous areas, and industrial processes remain the top three with higher SCs (41.9%, 14.1%, and 8.8% for NEI05 vs.30.8%, 8.9%, and 6.9% for NEI99v2, respectively). Those changes in SCs are attributed to increased primary PM2.5 (PPM) emissions in NEI05 and increases in relative contributions of miscellaneous areas and coal combustion to the emissions of PPM, NH3, and SO2.SCs from diesel and gasoline vehicles decrease in both months, due to decreased contributions of gasoline vehicles to SO2 and NH3 emissions and those of diesel vehicles to NOx and PPM emissions. Compared with CMAQ/BFM (NEI99v2), SCs from other combustion and biomass burning are higher in Florida, due to substantial increases in formaldehyde and PPM emissions in NEI05, resulting from higher wildfire emissions and state emission updates. SCs from industrial processes increase and those from diesel and gasoline vehicles decrease in urban areas. SCs of O3 from most sources in both months increase due to a large increase in their contributions to NOx emissions, except for diesel vehicles in July, which decreases over domainwide due to a relative decrease in NOx emissions. These results provide valuable information for policy makers to formulate and adjust emission control strategies as the NEI is continuously updated.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Zhang, Yang and Wang, Wei and Wu, Shiang-Yuh and Wang, Kai and Minoura, Hiroaki and Wang, Zifa}, year={2014}, month={May}, pages={133–154} }
 @article{zhang_sartelet_zhu_wang_wu_zhang_wang_tran_seigneur_wang_2013, title={Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 2: Evaluation of chemical concentrations and sensitivity simulations}, volume={13}, ISSN={["1680-7324"]}, DOI={10.5194/acp-13-6845-2013}, abstractNote={Abstract. An offline-coupled model (WRF/Polyphemus) and an online-coupled model (WRF/Chem-MADRID) are applied to simulate air quality in July 2001 at horizontal grid resolutions of 0.5° and 0.125° over Western Europe. The model performance is evaluated against available surface and satellite observations. The two models simulate different concentrations in terms of domainwide performance statistics, spatial distribution, temporal variations, and column abundance. WRF/Chem-MADRID at 0.5° gives higher values than WRF/Polyphemus for the domainwide mean and over polluted regions in Central and southern Europe for all surface concentrations and column variables except for the tropospheric ozone residual (TOR). Compared with observations, WRF/Polyphemus gives better statistical performance for daily HNO3, SO2, and NO2 at the European Monitoring and Evaluation Programme (EMEP) sites, maximum 1 h O3 at the AirBase sites, PM2.5 at the AirBase sites, maximum 8 h O3 and PM10 composition at all sites, column abundance of CO, NO2, TOR, and aerosol optical depth (AOD), whereas WRF/Chem-MADRID gives better statistical performance for NH3, hourly SO2, NO2, and O3 at the AirBase and BDQA (Base de données de la qualité de l'air) sites, maximum 1 h O3 at the BDQA and EMEP sites, and PM10 at all sites. WRF/Chem-MADRID generally reproduces well the observed high hourly concentrations of SO2 and NO2 at most sites except for extremely high episodes at a few sites, and WRF/Polyphemus performs well for hourly SO2 concentrations at most rural or background sites where pollutant levels are relatively low, but it underpredicts the observed hourly NO2 concentrations at most sites. Both models generally capture well the daytime maximum 8 h O3 concentrations and diurnal variations of O3 with more accurate peak daytime and minimal nighttime values by WRF/Chem-MADRID, but neither model reproduces extremely low nighttime O3 concentrations at several urban and suburban sites due to underpredictions of NOx and thus insufficient titration of O3 at night. WRF/Polyphemus gives more accurate concentrations of PM2.5, and WRF/Chem-MADRID reproduces better the observations of PM10 concentrations at all sites. The differences between model predictions and observations are mostly caused by inaccurate representations of emissions of gaseous precursors and primary PM species, as well as biases in the meteorological predictions. The differences in model predictions are caused by differences in the heights of the first model layers and thickness of each layer that affect vertical distributions of emissions, model treatments such as dry/wet deposition, heterogeneous chemistry, and aerosol and cloud, as well as model inputs such as emissions of soil dust and sea salt and chemical boundary conditions of CO and O3 used in both models.  WRF/Chem-MADRID shows a higher sensitivity to grid resolution than WRF/Polyphemus at all sites. For both models, the use of a finer grid resolution generally leads to an overall better statistical performance for most variables, with greater spatial details and an overall better agreement in temporal variations and magnitudes at most sites. The use of online biogenic volatile organic compound (BVOC) emissions gives better statistical performance for hourly and maximum 8 h O3 and PM2.5 and generally better agreement with their observed temporal variations at most sites. Because it is an online model, WRF/Chem-MADRID offers the advantage of accounting for various feedbacks between meteorology and chemical species. However, this model comparison suggests that atmospheric pollutant concentrations are most sensitive in state-of-the-science air quality models to vertical structure, inputs, and parameterizations for dry/wet removal of gases and particles in the model.
                    }, number={14}, journal={ATMOSPHERIC CHEMISTRY AND PHYSICS}, author={Zhang, Y. and Sartelet, K. and Zhu, S. and Wang, W. and Wu, S. -Y. and Zhang, X. and Wang, K. and Tran, P. and Seigneur, C. and Wang, Z. -F.}, year={2013}, pages={6845–6875} }