“…We focus on improving the diurnal variation of surface PM 2.5 in UI-WRF-Chem in Ethiopia by updating its emissions inventory. The fidelity of any CTM simulation is limited by many factors, such as the parameterization accuracy for physical and chemical processes, the time lag of emission inventories, and the accuracy of estimation of model initial and boundary conditions. − In the past decade, as one of the countries with a fast urbanization rate and the highest urban population growth rate in Africa, Ethiopia has experienced rapid growth in the anthropogenic PM 2.5 emission rate. , The primary contributors to air pollutant emissions in Ethiopia include motor vehicles, industrial sources, biomass burning, waste incineration, and dust. , In particular, in its capital city, Addis Ababa, anthropogenic emissions account for over 95% of total aerosol and trace gas emission and contribute 85 to 93% to PM 2.5 mass concentration (based on the model sensitivity results for the time period of study, see Figure S1 in Supporting Information). However, due to the temporal lag in the bottom-up estimates of emissions, the emissions inventory of PM 2.5 in Ethiopia has not considered the growth of these anthropogenic sources in recent years and therefore is expected to be a large source of uncertainty for the simulation of UI-WRF-Chem in that region.…”