Estimation of the concentration of the atmospheric primary pollutants, using the global emissions dataset – A WRF-Chem case study for Tehran

In this study, the use of a global emission dataset of particulate matters is evaluated for air quality modelling in a residential region. The EDGAR-HTAP dataset of global emissions, updated in the year 2014, is used in the model WRF-Chem to simulate the concentrations of primary pollutants, including SO2, NO2, O3, CO, PM10, and PM2.5. The utilization of online meteorology-chemistry models has been more common in recent years. In this study, with the aid of WRF-Chem capability in online simulation of meteorology and chemistry processes and using the aerosol module MADE/SORGAM, the concentrations of the primary pollutants in Tehran for three days of 20, 21, and 22 June 2014 is estimated. In this study the latest version of EDGAR-HTAP dataset (updated in the year 2014) was applied along with the RETRO global dataset in the model. The HTAP dataset constitutes a grid network with the resolution of 0.1×0.1 which contains some compositions such as CH4, CO, SO2, NOx, NMVOC, NH3, PM10, PM2.5, BC, and OC. The HTAP emission inventory is based on the measurement of the years 2008 and 2010 which is prepared globally. The EDGAR-HTAP emission inventory gives the amount of emissions from gaseous sources such as industry, energy, transportation, and agriculture. The measurement unit of the flow of the pollution into the atmosphere is kilogram per cubic meter per second. The RETRO emission inventory includes the amount of the anthropogenic pollution as well as the gases from biological and natural processes. For the verification of the output simulated concentration, the measured data from the air quality stations in Tehran is used. The verification of the model output shows that for four pollutant agents, including SO2, NO2, PM10, and PM2.5, the simulated concentration have acceptable values in comparison with the measured data. But the simulation for the two pollutants of CO and NO2 shows a considerable under-estimation. The use of the chemistry schemes and global data has an important impact on the results. One of the approaches to obtain a better estimation from pollution concentrations is the enhancement in the amounts of the emissions dataset. The effectiveness of this approach can be verified by the repeated running of the model after modifying the emissions dataset. In the current study, the results of the model WRF/Chem for air pollution gaseous agents for certain particles such as PM2.5, PM10, SO2, and O3 were acceptable in comparison to the observed data from the air pollution stations in Tehran. Regarding the results achieved, using other chemistry schemes of the model WRF-Chem and change and rectification of the global emission dataset are some considerable methods for approaching a more accurate result with less under-estimation for the agents CO and NO2.