The effects of different solar radiation intensities, heat flow density of indoor heat sources, outdoor wind speed, and the relative location of indoor heat sources on the natural ventilation performance of solar chimneys are investigated through three-dimensional numerical simulations. The mechanism of the mutual coupling of the solar chimney effect with the outdoor wind and indoor heat source heat plume is explored. The results of the study show that when the structural parameters of the solar chimney are the same, the heat flow density on the surface of the indoor heat source, the outdoor wind speed and the solar radiation intensity all have a gaining effect on the ventilation performance of the solar chimney and the effects of the three on the ventilation of the solar chimney promote each other, when the solar radiation intensity is 200 W/m², the outdoor wind speed is 1.0 m/s, and the indoor heat source heat flow density increases from 0 to 1 500 W/m², the solar chimney ventilation volume increases from 0.393 m³/s to 0.519 m³/s, the maximum value of the increase is 32.1%. In the other two cases, the maximum increase in solar chimney ventilation is 176.7% and 33.1%, respectively. Under the same conditions, solar chimney ventilation is optimal when the heat source is in the middle of the room. The presence of outdoor wind, however, affects the optimum design parameters of the solar chimney. Compared to the case where no outdoor wind is taken into account, the optimum inlet width of 0.2–0.3 m for the solar chimney no longer applies with outdoor wind, with the optimum value rising to 0.5 m.

Topography is one of the important factors influencing the distribution of rural settlements, as the natural environment in plateau-mountain areas is more complicated and harsher and the forces of various natural influences are more obvious. Analyzing the correlation between settlement distribution and topography would help understand the influence of topography on human activities. This paper takes rural settlements in Yunnan Province as the research object, introduces the concept of the distribution index, and integrates the methods of GIS spatial analysis and mathematical statistics to analyze the correlation between them. The results show that (1) the distribution pattern of rural settlements in Yunnan Province is dense in the northeast, sparse in the northwest, dense in the middle, and sparse in the south; the overall pattern shows low density, fragmentation, and a dotted distribution of high-value areas, showing three typical core areas with very obvious spatial differentiation. (2) The distribution of rural settlements is influenced by three key topographic factors: Relief amplitude, incision depth, and surface roughness. The dispersion index of rural settlements drastically declines as the value rises. (3) Each topographic factor influences the natural resources and climatic characteristics of the region, and by coupling them with the production and life of the rural settlements and the psychological needs of the inhabitants, they form an intrinsic mechanism that influences the distribution of rural settlements. (4) Topography is an important factor when developing and constructing in plateau-mountain areas. The environmental protection and construction of human settlements should be in accordance with nature and adapted to the terrain, which can reduce the damage to the natural environment. The study provides effective data support for quantifying the relationship between the distribution of rural settlements and topography in the plateau-mountain area and optimizing the layout of rural settlements.

To effectively combat environmental challenges, it is necessary to evaluate urban residential building carbon emissions and implement energy-efficient, emission-reducing strategies. The lack of a specialized carbon emission monitoring system complicates merging macro- and micro-level analyses to forecast urban residential emissions accurately. This study employs a system dynamics (SD) model to examine the influence of social, economic, energy, and environmental factors on carbon emissions in urban residences in Kunming, China. The SD model forecasts household carbon emissions from 2022 to 2030 and establishes three scenarios: a low-carbon scenario (LCS), a medium low-carbon scenario (MLCS), and a high low-carbon scenario (HLCS) to assess emission reduction potentials. It predicts emissions will climb to 4.108 million tons by 2030, significantly surpassing the 2014 baseline, with economic growth, urbanization, residential energy consumption, and housing investment as key drivers. To curb emissions, the study suggests enhancing low-carbon awareness, altering energy sources, promoting research and development investment, and expanding green areas. The scenarios indicate a 5.1% to 16.1% emission reduction by 2030 compared to the baseline. The study recommends an 8.3% to 11.4% reduction in MLCS as a practical short-term target for managing urban residential emissions, offering a valuable SD approach for optimizing carbon strategies and aiding low-carbon development.

Rapid population aging in developing countries has intensified demand for accessible nursing home services, yet spatial disparities in service distribution remain insufficiently examined in secondary cities. This study investigates spatial distribution and multi-dimensional accessibility of nursing homes in Kunming, China, using comprehensive spatial analytical methods to inform sustainable urban development. We analyzed 205 nursing homes with 47,600 beds, evaluating spatial distribution patterns, economic accessibility, and spatial accessibility across different transportation modes. Our analysis reveals a pronounced monocentric pattern with nursing resources concentrated within central urban districts, creating a “primary core-multiple satellite” structure and spatial mismatch between service supply and older adult population needs. A distinct institutional dichotomy exists between publicly and privately operated facilities, establishing a dual-track system with different accessibility implications for social equity. Economic accessibility analysis demonstrates significant barriers in central urban and tourism-oriented districts dominated by higher-priced private facilities, where minimum prices frequently exceed average monthly pension. Spatial accessibility remains inadequate across all transportation modes, with only 24.3% of communities achieving normal or higher accessibility via private car, 21.5% via public bus, and merely 13.9% via walking. These limitations primarily stem from insufficient service capacity (34 beds per 1000 older adults) relative to demographic needs rather than transportation constraints. We recommend three sustainable interventions: implementing demand-based planning mechanisms, establishing progressive pricing policies, and developing older adult-friendly transportation networks. This framework supports sustainable urbanization by promoting spatial equity and efficient resource allocation, providing valuable insights for secondary cities pursuing sustainable development goals.

Achieving carbon emission reductions in the residential building sector while maintaining economic growth represents a global challenge, particularly in rapidly developing regions with internal disparities. This study examines Jiangsu Province in eastern China—a economic hub with north-south development gradients—to develop an integrated framework for differentiated carbon reduction pathways. The methodology combines spatial autocorrelation analysis, logarithmic mean Divisia index (LMDI) decomposition, system dynamics modeling, and Tapio decoupling analysis to examine urban residential building emissions across three regions from 2016–2022. Results reveal significant spatial clustering of emissions (Moran’s I peaking at 0.735), with energy consumption per unit area as the dominant driver across all regions (contributing 147.61%, 131.60%, and 147.51% respectively). Scenario analysis demonstrates that energy efficiency policies can reduce emissions by 10.1% while maintaining 99.2% of economic performance, enabling carbon peak achievement by 2030. However, less developed northern regions emerge as binding constraints, requiring technology investments. Decoupling analysis identifies region-specific optimal pathways: conventional development for advanced regions, balanced approaches for transitional areas, and subsidies for lagging regions. These findings challenge assumptions about environment-economy trade-offs and provide a replicable framework for designing differentiated climate policies in heterogeneous territories, offering insights for similar regions worldwide navigating the transition to sustainable development.