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With the acceleration of urbanization and profound socioeconomic changes, the influx of people from various social strata into cities has led to the phenomenon of residential segregation. Currently, the international community has accumulated profound theoretical foundations and rich practical experiences in the study of residential segregation. This research, primarily based on the WOS literature database, sorts and summarizes relevant studies on residential segregation in recent years (focusing on publications from 2020 to 2024), emphasizing the following four key aspects: (1) tracing the evolution of the theory of residential segregation and analytical methods; (2) analyzing the main characteristics of urban residential segregation; (3) exploring the driving mechanisms and effects of urban residential segregation; and (4) summarizing research trends and providing future perspectives. This study aids urban planners in more accurately identifying areas and characteristics of residential segregation, optimizing urban layouts, and providing richer and more in-depth theoretical support and practical guidance for the field of urban planning science. [ABSTRACT FROM AUTHOR]

The evaluation of housing conditions is a crucial aspect of determining the well-being of residents and the sustainable development of settlements. Assessing housing conditions at a macro-level is imperative to understand the differences in well-being and livability among residents in various regions within a country. Unfortunately, the spatial variation characteristics of housing conditions in China have not been extensively studied at the county scale. Thus, this study examines the housing conditions in China by using 2846 counties as the basic research unit. A housing condition evaluation index system, comprising seven indicators, is constructed based on three aspects: housing spaciousness, internal facilities, and elevator configuration. The entropy value method is used to determine the weights of the indicators, and the spatial difference patterns and spatial autocorrelation characteristics of the housing conditions and types of housing conditions in China are analyzed. The correlation analysis method is used to analyze the correlation between the subtypes of housing conditions and county fundamentals (population density, urbanization, foreign population, and rental housing). The results show that: (1) the configuration of elevators is the most important indicator of the differences in housing conditions in China; (2) the better housing conditions in China are distributed on the southeast side of the "Hu Line", while the worse areas are distributed on the northwest side of the "Hu Line", showing significant spatial clustering characteristics, while the distribution of the different subtypes of housing conditions and their distribution in the H–H and L–L zones also have significant variability; (3) housing conditions in China's urban areas are generally better than those in non-urban areas, and the internal infrastructure conditions of urban housing and the degree of elevator configuration are better than those in non-urban areas; and (4) the correlation between housing conditions and county fundamentals varies depending on the regional level. At the national and urban levels, a negative correlation exists between county fundamentals and housing spaciousness, although a positive correlation exists with internal infrastructure and elevator configuration. Urbanization has the greatest impact on housing conditions in these areas. In non-urban areas, there is significant variability in the correlation between county fundamentals and housing conditions. [ABSTRACT FROM AUTHOR]

• Assess the contribution of ecological land structure in reducing PM 2.5 pollution. • The dust suppression efficiency of the ecological land composite structure is higher than that of the single structure. • There are significant differences in the role of different types of ecological land. • Compares the suitability of different models and the accuracy of the results. In the context of serious urban air pollution and limited land resources, it is important to understand the environmental value of ecological land. Previous studies focused mostly on the effectiveness of a particular type of green space or the total amount of ecological land on PM 2.5 and have rarely analyzed the association between ecological land structure and PM 2.5 systematically and quantitatively. Therefore, we took 277 cities in China as an example, comprehensively compared the results of different models, and selected a spatial Durbin model using time-fixed effects to dissect the degree of influence of ecological land and different land types within it on PM 2.5. The urban ecological land use structure was closely related to PM 2.5 , and the higher the proportion of ecological land use was, the lower the PM 2.5. The degree and direction of influence of different types of land functions within ecological land on PM 2.5 differed, with forests, shrubs, and grasslands causing a weakening impact on PM 2.5 , while wetlands and waters did not have a weakening role. The degree of reduction of PM 2.5 by a single type of ecological land was significantly smaller than that by a composite type of ecological land. Green space should be comprehensively considered, designed and adjusted in urban planning to continuously optimize the ecological spatial structure, increase landscape diversity and maximize ecological benefits. The findings of this study help with exploring the effects of land use structure under the goal-oriented control of air pollution and provide theoretical reference and decision-making support for formulating precise air pollution control policies and optimizing the spatial development of national land. [ABSTRACT FROM AUTHOR]