Africa has been undergoing a rapid urbanization process, which is critical to the achievement of the 11th Sustainable Development Goal (SDG11). Using population density data from LandScan, we proposed a population density-based thresholding method to generate urban land and urban population data in Africa from 2001 to 2019, which were further applied to detect the spatiotemporal characteristics of Africa’s urbanization. The results showed that urban land and urban population have both grown rapidly in Africa, which increased by about 5.92% and 4.91%, respectively. The top three countries with the most intense urbanization process in Africa are Nigeria, the Democratic Republic of the Congo, and Ethiopia. The coupling relationship index of urban land expansion and population growth was 0.76 in Africa during 2001–2019. Meanwhile, the total proportion of uncoordinated development types at the provincial level was getting higher, which indicated an uncoordinated relationship between urban land expansion and population growth in Africa. Cropland, grassland, rural land, and forests were the most land-use types occupied by urban expansion. The proportion of cropland, grassland, and forests occupied was getting higher and higher from 2001 to 2019. The extensive urban land use may have an impact on the environmental and economic benefits brought by urbanization, which needs further research.

Africa’s PM_2.5 pollution has become a security hazard, but the understanding of the varying effects of urbanization on driven mechanisms of PM_2.5 concentrations under the rapid urbanization remains largely insufficient. Compared with the direct impact, the spillover effect of urbanization on PM_2.5 concentrations in adjacent regions was underestimated. Urbanization is highly multi-dimensional phenomenon and previous studies have rarely distinguished the different driving influence and interactions of multi-dimensional urbanization on PM_2.5 concentrations in Africa. This study combined grid and administrative units to explore the spatio-temporal change, spatial dependence patterns, and evolution trend of PM_2.5 concentrations and multi-dimensional urbanization in Africa. The differential influence and interaction effects of multi-dimensional urbanization on PM_2.5 concentrations under Africa’s rapid urbanization was further analyzed. The results show that the positive spatial dependence of PM_2.5 concentrations gradually increased over the study period 2000–2018. The areas with PM_2.5 concentrations exceeding 35 μg/m³ increased by 2.2%, and 36.78% of the African continent had an increasing trend in Theil–Sen index. Urbanization was found to be the main driving factor causing PM_2.5 concentrations changes, and economic urbanization had a stronger influence on air quality than land urbanization or population urbanization. Compared with the direct effect, the spillover effect of urbanization on PM_2.5 concentrations in two adjacent regions was stronger, particularly in terms of economic urbanization. The spatial distribution of PM_2.5 concentrations resulted from the interaction of multi-dimensional urbanization. The interaction of urbanization of any two different dimensions exhibited a nonlinear enhancement effect on PM_2.5 concentrations. Given the differential impact of multi-dimensional urbanization on PM_2.5 concentrations inside and outside the region, this research provides support for the cross-regional joint control strategies of air pollution in Africa. The findings also indicate that PM_2.5 pollution control should not only focus on urban economic development strategies but should be an optimized integration of multiple mitigation strategies, such as improving residents’ lifestyles, optimizing land spatial structure, and upgrading the industrial structure.

Air pollution is a challenge for many cities. The digital economy enhances support for environmental pollution management, while the mechanisms and scaling heterogeneity remain unclear. This study explored the contribution of digital economy development to PM_2.5 concentrations control in China and driving mechanisms in different economic subregions and urban agglomerations. Results show that the spillover transfer effect on air pollution mitigation far exceeded the direct effect at different scales. At the national scale, the air pollution mitigation effect of digital economy was mainly through empowering industrial structure optimization and green technology innovation, while it also affected economic subregions and urban agglomerations through varying scenario combinations of pathways with structural optimization, green production, resource allocation, and technology innovation. Research findings provide support for cross-regional joint management strategies of digital economy and air quality and designing regionally differentiated pollution control pathways in the digital economy dimension.