Maphanga, ThabangMuneri, Aluwani InnocentMadonsela, Benett Siyabonga2026-06-222026-06-222026Muneri, A.I., Maphanga, T. and Madonsela, B.S., 2026. Spatiotemporal Analysis and Future Projections of CO and O3 Concentrations in Gauteng Province Using Sentinel-5P and CMIP6 Models. Remote Sensing Applications: Society and Environment, p.101873.https://doi.org/10.1016/j.rsase.2026.101873https://hdl.handle.net/10566/24666This study is among the first to integrate high-resolution Sentinel-5P TROPOMI observations, ground-based SAAQIS measurements, and CMIP6 climate model outputs to generate long-term air quality projections for Gauteng Province. Gauteng, South Africa's economic hub, continues to experience severe air quality pressures driven by rapid urbanization, industrial emissions, and traffic density. However, long-term, multi-source projections for key pollutants such as carbon monoxide (CO) and ozone (O3) remain limited for the region. The objectives of this research were to: (1) characterize the spatiotemporal distribution of CO and O3 across Gauteng during the 2019–2020 baseline period using Sentinel-5P data (2) evaluate and validate CMIP6 climate model outputs against both satellite observations and SAAQIS ground-based measurements and (3) develop deterministic decadal projections for CO and O3 for the year 2030 under the SSP2-4.5 scenario. Model validation showed that CMIP6 outputs systematically underestimated pollutant levels, with consistently negative mean bias errors for CO (≈−101 ppb) and O3 (≈−18 ppb). Despite these biases, spatial correlations with observed concentrations were moderate to strong (r > 0.6). Under the SSP2-4.5 pathway, projections indicate a substantial decrease and increase in pollutants by 2030, with CO showing an increase (+4 to +7) on the other ha nd O3 showing the most pronounced decline (−7 to −95), likely driven by reductions in precursor emissions and associated chemical feedback. Spatial patterns suggest that existing pollution hotspots will shift eastward, away from the Johannesburg–Pretoria urban core. Overall, the findings demonstrate the value of an integrated satellite-ground-modelling approach for regional air quality assessment. While the magnitude of projected changes should be interpreted with caution due to model resolution and inherent uncertainties, the study provides critical evidence to support future policy development and long-term air quality management in Gauteng ProvinceenAir qualityCarbon monoxide (CO)Climate modellingGauteng provinceOzone (O3)Article