The pollution problem caused by urban black and odorous waters has received much attention from the Chinese government. Our research aims at systematically identifying the characteristics and the influential factors of spatial differentiation of urban black and odorous waters across China. The research, based on the data of 2100 black and odorous waters in China, was conducted with the spatial analysis tool of ArcGIS. We found that the amount of Chinese urban black and odorous waters varied in spatial distribution, which was an agglomerated type with significant agglomeration. The kernel density was characterized by independent single kernel centers with ribbon-like and sporadic distributions of subcenters. The cold and hot spots showed a gradient distribution pattern of cold in the southwest and hot in the central east. These spatial distribution characteristics could be attributed to the following core factors, total wastewater discharge, length of urban drainage pipelines, municipal solid waste collection, daily urban sewage treatment capacity, and investment in urban pollution treatment of wastewater. The findings reveal the current geospatial distribution of black and odorous waters pollution and provide reference for the Chinese government to treat the pollution from several key points. Lastly, it is suggested that the Chinese government should establish joint control, joint prevention, and joint treatment mechanisms in the black and odorous waters areas and improve the safety standards of the whole water environment, so as to promote the treatment and elimination of urban black and odorous waters.

A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing countries. Taking Wuhan as the case study, this paper developed an index system including rural settlement, land, industry and human settlement environment for evaluating the level of rural development. Then, using the exploratory spatial data analysis, the principal component analysis and the cluster analysis, this paper analyzes the spatial differentiation and correlation and categorizes the types of rural development. The results are as follows. (1) The spatial differentiation of the level of rural development in Wuhan City’s new urban districts is obvious and the areas with a high level of rural development are mainly distributed at the intersection of the new and central urban areas and gradually decrease outward. (2) There is a significant spatial agglomeration of the developed rural areas and the structure of the spatial change in these areas resembles a certain continuity, specifically a circle of “central heat surrounding cold”. (3) Rural development in the new urban areas can be divided into the following five types: the ecological leisure type, the traditional farming type, the balanced development type, the industrial-and-agricultural mixed type and the industrial promotion type. The corresponding development path is proposed in combination with different types of rural development to provide a theoretical basis and decision-making reference for rural revitalization.

The public health level in a country is closely related to national development and quality of life. In order to appraise the level of health services in the western region of China, panel data of 124 prefecture-level units covering the period 2011 to 2021 was used together with a health evaluation index system based on four dimensions: quality of life, environmental situation, the level of health services and longevity. To assess this, we used entropy weights, standard deviation and coefficient of variation together with the geographical detector model that measures the stratified spatial heterogeneity. The results show that although public health services have improved overall, the various dimensions are still not balanced as longevity did not match up everywhere. While the developmental level of the various health dimensions presents a pattern of a relatively smooth increasing gradient in the west-central- east direction, the situation with respect to the north-centralsouth is more uneven with both ups and downs. However, a trend of continuous enhancement of all health dimensions was found with a significant positive correlation of spatial clustering, with hotspots and ‘sub-hotspots’ contracting from north to south, while coldspots and ‘sub-coldspots’ expanded from west to east. This can be seen as the result of multiple factors, with the level of urbanization and economic level as the dominant factors and government guidance, agglomeration capacity and industrial structure being auxiliary.