Urbanization and air pollution are major anthropogenic impacts on Earth’s environment, weather, and climate. Each has been studied extensively, but their interactions have not. Urbanization leads to a dramatic variation in the spatial distribution of air pollution (fine particles) by altering surface properties and boundary-layer micrometeorology, but it remains unclear, especially between the centers and suburbs of metropolitan regions. Here, we investigated the spatial variation, or inhomogeneity, of air quality in urban and rural areas of 35 major metropolitan regions across China using four different long-term observational datasets from both ground-based and space-borne observations during the period 2001–2015. In general, air pollution in summer in urban areas is more serious than in rural areas. However, it is more homogeneously polluted, and also more severely polluted in winter than that in summer. Four factors are found to play roles in the spatial inhomogeneity of air pollution between urban and rural areas and their seasonal differences: (1) the urban–rural difference in emissions in summer is slightly larger than in winter; (2) urban structures have a more obvious association with the spatial distribution of aerosols in summer; (3) the wind speed, topography, and different reductions in the planetary boundary layer height from clean to polluted conditions have different effects on the density of pollutants in different seasons; and (4) relative humidity can play an important role in affecting the spatial inhomogeneity of air pollution despite the large uncertainties.

The hierarchical healthcare system is widely considered to be a desirable mode of the delivery of healthcare services. It is expected that the establishment of a hierarchical healthcare system can help provide better and more equal healthcare accessibility. However, limited evidence has been provided on the impacts of a hierarchical healthcare system on healthcare accessibility. This study develops an improved Hierarchical two-step floating catchment area (2SFCA) method, which incorporates variable catchment area sizes, distance friction effects and utilization efficiency for facilities at different levels. Leveraging the Hierarchical 2SFCA method, various scenarios are set up to assess the accessibility impacts of a hierarchical healthcare system. The methods are applied in a case study of Shenzhen. The results reveal significant disparity and inequality in healthcare accessibility and also differences between various facility levels in Shenzhen. The overall healthcare accessibility and its equality can be significantly improved by fully utilizing existing facilities. It is also demonstrated that allocating additional supply to lower-level facilities can generate larger accessibility gains. Furthermore, allocating new supply to primary facilities would mitigate the inequality in healthcare accessibility, whereas inequality tends to be aggravated with new supply allocated to tertiary facilities. These impacts cannot be captured by traditional accessibility measures. This study demonstrates the pivotal role of primary facilities in the hierarchical healthcare system. It can contribute to the literature by providing transferable methods and procedures for measuring hierarchical healthcare accessibility and assessing accessibility impacts of a hierarchical healthcare system in developing countries.

Equal accessibility to healthcare services is essential to the achievement of health equality. Recent studies have made important progresses in leveraging GIS-based location–allocation models to optimize the equality of healthcare accessibility, but have overlooked the hierarchical nature of facilities. This study developed a hierarchical maximal accessibility equality model for optimizing hierarchical healthcare facilities. The model aims to maximize the equality of healthcare facilities, which is quantified as the variance of the accessibility to facilities at each level. It also accounts for different catchment area sizes of, and distance friction effects for hierarchical facilities. To make the optimization more realistic, it can also simultaneously consider both existing and new facilities that can be located anywhere. The model was operationalized in a case study of Shenzhen, China. Empirical results indicate that the optimal healthcare facility allocation based on the model provided more equal accessibility than the status quo. Compared to the current distribution, the accessibility equality of tertiary and secondary healthcare facilities in optimal solutions can be improved by 40% and 38%, respectively. Both newly added facilities and adjustments of existing facilities are needed to achieve equal healthcare accessibility. Furthermore, the optimization results are quite different for facilities at different levels, which highlights the feasibility and value of the proposed hierarchical maximal accessibility equality model. This study provides transferable methods for the equality-oriented optimization and planning of hierarchical facilities.