The article analyses the spatial and temporal differences in the environmental quality of production, living and ecology of 285 cities in China from 2010 to 2020 by using the entropy method, the Theil index and correlation analysis. The study concludes the following: (1) in terms of overall differences, the overall differences in the “production, living and ecological” environmental quality indices of 285 cities during the study period undergo a process of “narrowing–widening–narrowing”. The differences within the four major zones of the country are higher than those between the four major zones, and the differences within the zones show an increasing trend year by year. (2) In terms of temporal differences, the combined scores of “production, living and ecological” environmental quality of the 285 cities in the study period show a decreasing trend, and the contribution of the PLE subsystem scores are, in descending order, production environmental quality > living environmental quality > ecological environmental quality. (3) In terms of overall ranking, the head effect of the combined production, living and ecological environmental quality (PLE) scores of cities in the study period is significant, and the top 10 cities in terms of combined scores are all small and medium-sized cities with significant regionalization characteristics. (4) In terms of spatial pattern, there is a significant spatial gradient in the east, central and western regions, with the overall PLE scores of the four major regions in descending order: eastern region > central region > western region > northeastern region. The regions with high scores in the “production, living and ecological” environmental quality of cities can be divided into three types: multi-core, dual-core and single-core. (5) In terms of influencing factors, there is a logarithmic curve relationship between the combined production, living and ecological environmental quality (PLE) score and the built-up area (BUA) of cities. The study proposes to optimize the layout of urban production, strengthen the industrial links of urban clusters, improve the level of public services, ensure the equalization of urban public services, strengthen the management of ecological environment and improve the quality of ecological environment in order to optimize the quality of urban “production, living and ecological” environment.
Although the development of tourism has a positive impact on local employment and economic growth, the high level of energy consumption and emissions generated by tourism have also attracted increasing attention. Based on the concept of tourism eco-efficiency, this article constructs a comprehensive evaluation system for tourism eco-efficiency in China, and the study concludes that (1) China’s tourism eco-efficiency as a whole was in a fluctuating upward trend from 2002 to 2018, but different provinces of tourism eco-efficiency varied greatly, and the range of tourism eco-efficiency on spatial spill-over increased significantly; (2) the impact of tourism economic development on tourism eco-efficiency was not significant over time, and the impact of tourism eco-efficiency on the sustainable development of the tourism economy in the western region was weaker; (3) the contribution of tourism economic development to tourism eco-efficiency was low at the national level, with regional levels ranging from large to small for the western region, the central region, and the eastern region. The contribution of tourism eco-efficiency to the tourism economy was also low at the national level, with the central, eastern, and western regions ranked in descending order at the regional level.
With rapid urbanization, more and more rural young adults are moving into towns and cities on a large scale, while the elderly are largely left behind in rural areas. The number of elderly people living alone, disabled and handicapped in rural areas is increasing, adding to the already weak rural elderly problem and increasing the pressure on the governance of rural elderly risks. The sustainable development of elderly care institutions is an important element in tackling the rural elderly problem and a key aspect of managing the rural elderly problem. The article uses data on rural aged-care institutions in 276 Chinese cities from 2010–2016 to construct comprehensive evaluation indicators for the development of rural aged-care institutions, and uses a combination of hierarchical analysis, composite score method, Theil index and coupling coordination model to reveal the spatial and temporal patterns and coupling characteristics of the development of rural aged-care institutions. The study concludes that: (1) From the time series change, the comprehensive score of rural elderly institutions shows a “fluctuating” change process, and there are significant differences in the development of each secondary indicator. (2) In terms of spatial and temporal patterns, the overall scores of rural elderly institutions, hard environment scores, soft environment scores and service recipients scores show a clear “gradient” in the east, middle and west. (3) In terms of regional differences, the Theil index for rural elderly care institutions is from high to low: Hard environment > service recipients > soft environment > overall score. From the decomposed Theil index, the intra-group differences of rural aged-care institutions are much larger than the inter-group differences, and the intra-group differences of the Theil index of the four major regions generally show a narrowing trend, with the intra-group differences of the eastern region being higher than those of the western region, those of the western region being higher than those of the central region, and those of the central region being higher than those of the northeastern region. (4) In terms of coupling coordination, the coupling degrees of the four major regions all exceed the low-level coupling stage index and are in the antagonistic stage or the grinding stage, and the coupling degrees of the four major regions are, in descending order, central region > eastern region > northeastern region > western region. The coupling coordination degree of the four major regions from high to low is: Eastern region > central region > northeastern region > western region. Based on the empirical analysis, the article proposes a model path for the sustainable development of rural elderly institutions in three aspects: Coordinated development, coupled development and sustainable development, in view of the unbalanced regional development of rural elderly institutions and the low degree of coupling and coordination between the soft and hard environments.
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