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.

The magnitude and distribution of China's terrestrial carbon sink remain uncertain due to insufficient constraints at large scales, whereby satellite data offer great potential for reducing the uncertainty. Here, we present two carbon sink estimates for China constrained either by satellite CO₂ column concentrations (XCO₂) within the Global Carbon Assimilation System or by remotely sensed soil moisture and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in addition to in situ CO₂ observations within the Carbon Cycle Data Assimilation System. They point to a moderate size of carbon sinks of 0.34 ± 0.14 (mean ± unc.) and 0.43 ± 0.09 PgC/yr during 2010–2015, which are supported by an inventory‐based estimate for forest and soil carbon sink (0.26 PgC/yr) and fall in the range of contemporary ensemble atmospheric inversions (0.25–0.48 PgC/yr). They also agree reasonably well on interannual variations, which reflect the carbon sink anomalies induced by regional droughts in southwest China. Furthermore, their spatial distributions are broadly consistent that of the forest inventory‐based estimate, indicating that the largest carbon sinks locate in central and eastern China. Their estimates for forest carbon sink coincide fairly well with the inventory‐based estimate across different regions, especially when aggregated to the north and south of China. Although enhanced recently by afforestation, China's carbon sink was also significantly weakened by regional droughts, which were often not fully represented in previous in situ CO₂‐based inversions due to insufficient observations. Our results suggest that satellite‐based atmospheric CO₂ and land surface observations are vital in characterizing terrestrial net carbon fluxes at regional scales.

Solar radiation significantly affects terrestrial gross primary productivity (GPP). However, the relationship between GPP and solar radiation is nonlinear because it is affected by diffuse radiation. Solar radiation has undergone a shift from darker to brighter values over the past 30 years in China. However, the effects on GPP of variation in solar radiation because of changes in diffuse radiation are unclear. In this study, national global radiation in conjunction with other meteorological data and remotely sensed data were used as input into a two-leaf light use efficiency model (TL-LUE) that simulated GPP separately for sunlit and shaded leaves for the period from 1981 to 2012. The results showed that the nationwide annual global radiation experienced a significant reduction (2.18 MJ m⁻² y⁻¹; p < 0.05) from 1981 to 2012, decreasing by 1.3% over this 32-year interval. However, the nationwide annual diffuse radiation increased significantly (p < 0.05). The reduction in global radiation from 1981 to 2012 decreased the average annual GPP of terrestrial ecosystems in China by 0.09 Pg C y⁻¹, whereas the gain in diffuse radiation from 1981 to 2012 increased the average annual GPP in China by about 50%. Therefore, the increase in canopy light use efficiency under higher diffuse radiation only partially offsets the loss of GPP caused by lower global radiation.