Assessment of WRF-Chem model simulations of particulate matter in West Africa: a systematic review

Abstract Particulate matter (PM) pollution is an escalating environmental and public health challenge in West Africa, which is often linked to respiratory diseases, cardiovascular morbidity, driven by Saharan dust transport, biomass burning, and rapidly increasing urban-industrial emissions. Chemical transport models, particularly the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), offer valuable tools for understanding and predicting PM dynamics where observational data remain sparse. This study presents a systematic review and bibliometric analysis of WRF-Chem applications for PM₁₀ and PM₂.₅ simulation in West Africa. A structured search of Scopus and Web of Science identified 12,119 records, of which six met all inclusion criteria. The bibliometric analysis confirmed a global expansion of WRF-Chem research but revealed that West Africa remains critically underrepresented in both thematic focus and regional linkages. Synthesis of the selected studies showed that WRF-Chem performs well for large-scale dust transport and seasonal PM trends but struggles with fine-scale urban and mixed-aerosol events, particularly where emission inventories lack spatial and chemical detail. Model performance depended on both grid resolution and emission data quality, indicating that finer grids require equally detailed input datasets. These findings emphasize the urgency of developing region-specific emission inventories, expanding surface monitoring networks, testing alternative dust and chemistry schemes, and integrating health-relevant metrics. Collectively, this review provides a consolidated evidence base and a strategic roadmap for improving PM modelling capacity in West Africa, thereby supporting research, public health, and policy development in a region facing complex and intensifying air quality challenges.