Evaluation of the WRF and CHIMERE models for the simulation of PM_2.5 in large East African urban conurbations

Abstract

Abstract. Urban conurbations of East Africa are affected by harmful levels of air pollution. The paucity of local air quality networks and the absence of the capacity to forecast air quality make difficult to quantify the real level of air pollution in this area. The CHIMERE chemistry transport model has been used along with the Weather Research and Forecasting (WRF) meteorological model to run high-spatial-resolution (2 × 2 km) simulations of hourly concentrations of particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) for three East African urban conurbations: Addis Ababa in Ethiopia, Nairobi in Kenya, and Kampala in Uganda. Two existing emission inventories were combined to test the performance of CHIMERE as an air quality model for a target monthly period in 2017, and the results were compared against observed data from urban, roadside, and rural sites. The results show that the model is able to reproduce hourly and daily temporal variabilities in aerosol concentrations that are close to observed values from urban, roadside, and rural environments. CHIMERE's performance as a tool for managing air quality was also assessed. The analysis demonstrated that, despite the absence of high-resolution data and up-to-date biogenic and anthropogenic emissions, the model was able to reproduce 66 %–99 % of the daily PM2.5 exceedances above the World Health Organization (WHO) 24 h mean PM2.5 guideline (25 µg m−3) in the three cities. An analysis of the 24 h average PM2.5 levels was also carried out for 17 constituencies in the vicinity of Nairobi. This showed that 47 % of the constituencies in the area exhibited a poor Air Quality Index for PM2.5 that was in the unhealthy category for human health, thereby exposing between 10 000 and 30 000 people per square kilometre to harmful levels of air contamination.

Urban diagnostics and a systems approach to air quality management: Pathways towards sustainable economic development and a healthy nairobi, Kenya

“…The quantitative analysis of anthropogenic emissions from ECLIPSE projections for East Africa and Kenya, highlight how through the implementation of legislation and/or mitigation policies it is possible to greatly reduce emissions. The analyses only show the impacts that these measures could have on primary emissions of pollutants, and they should also be used for numerical simulations of chemistry-transport processes to understand the real-world consequences of primary reductions in the final concentrations of both primary and secondary PM 2.5 both for East Africa and Kenya (Mazzeo et al, 2022).…”

“…This paper has highlighted that with current available data, it is possible to capture the main level or PM 2.5 contamination in urban and rural areas but further efforts are required to identify additional local sources that are still misrepresented in existing inventories and to have a more accurate spatial distribution of the emissions by the creation of local higher resolution emission inventories (Mazzeo et al, 2022).…”

Modeling PM2.5 During Severe Atmospheric Pollution Episode in Lagos, Nigeria: Spatiotemporal Variations, Source Apportionment, and Meteorological Influences

“…The spatial distribution of the emission rate from anthropogenic sectors over Nigeria in January 2021 is illustrated in Figure S1 in Supporting Information . It is worthy to mention that the EDGAR emissions inventory had been used in numerous previous studies in India (H. Guo et al., 2017, 2018, 2019; Kota et al., 2018), China (Qiao et al., 2019), and Africa as a continent (Kumar et al., 2022; Mazzeo et al., 2022). In addition, biogenic emissions were estimated with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012).…”

Modelling PM2.5 during severe atmospheric pollution episode in Lagos, Nigeria: Spatiotemporal variations, source apportionment, and meteorological influences

“…The emissions sectors were subsequently classified into six categories (agriculture, residential, industry, energy, on-road transportation, and off-road transportation). It is worthy to mention that the EDGAR emissions inventory had been used in numerous previous studies in India (Guo et al, 2019(Guo et al, , 2018(Guo et al, , 2017Kota et al, 2018), China (Qiao et al, 2019), and Africa as a continent (Kumar et al, 2022;Mazzeo et al, 2022). In addition, biogenic emissions were estimated with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al, 2012).…”