Qinghai Province is a very fragile area of ecological environment. While paying attention to economic development, we should pay more attention to the change trend of ecological environment. According to the urban statistical yearbook, the energy consumption of construction industry accounts for a large proportion of urban energy consumption. In the concept of sustainable development, we should pay attention to the problem of resource consumption and environmental pressure of urban construction industry. This paper takes Xining construction industry as the research object, based on the material flow analysis method, analyzes the material flow of newly built and demolished buildings in Xining city from 2011 to 2015, and reveals the material consumption status of Xining construction activities and the pressure on the environment.

Buildings account for 39% of global carbon emissions, making the construction sector a pivotal contributor to climate change. In ecologically fragile plateau regions, the tension between urban development and environmental sustainability poses a significant challenge. This study examines the spatiotemporal characteristics and influencing mechanisms of building carbon emissions (BCEs) in plateau cities using an empirical analysis of 13-year panel data (2010–2022) from two municipalities and six prefectures in Qinghai Province, China. By employing the eXtreme Gradient Boosting (XGBoost) model, we comprehensively assess drivers across four dimensions: socioeconomic structure, demographic and urban environmental factors, urban expansion patterns, and climatic topographic attributes. Key findings include: (1) The XGBoost model exhibits robust predictive performance (R² > 0.9, MSE < 0.1, RMSE < 0.3), validating its effectiveness for plateau urban systems. (2) Socioeconomic structure and urban expansion characteristics significantly positively influence building carbon emissions, with GDP, per capita GDP, and built-up areas being particularly influential. (3) The interaction between climate and terrain increases carbon emissions in urban buildings. (4) While socioeconomic structure is a common factor affecting BCEs across different types of plateau urban buildings, other factors, such as urban population density, the housing construction area, and the urban shape index, exhibit variability. These insights inform policy recommendations for cross-regional carbon flow balancing and adaptive low-carbon planning strategies tailored to plateau ecosystems.

Guangzhou is the capital city of Guangdong Province, which is currently in a stage of transformation and development. This paper takes Guangzhou’s ecological economy, ecological society, ecological environment as the research objects and constructs an evaluation index system for Guangzhou’s ecological liveability. It takes social progress, economic development and environmental protection as the primary indicators. The index system is used to construct the ecological livability evaluation index system of Guangzhou through the entropy method.

Quantitative research and evaluation of ecological carrying capacity in Qinghai Province is in line with the requirements of the 13th five-year plan, and is of practical significance to the construction of ecological civilization in Qinghai Province. Based on the PSR model, this paper constructs the evaluation index system of ecological carrying capacity from three aspects of pressure, state ,and response, uses the entropy method to determine the index weight coefficient, and comprehensively evaluates the changing trend of ecological carrying capacity since the 12th Five Year Plan of Qinghai Province from the perspectives of economy, society, resources, and environment. The results show that: from 2011 to 2019, the comprehensive evaluation of ecological carrying capacity in Qinghai Province shows a trend of first decreasing and then increasing, the response index evaluation increases greatly, the state index evaluation shows a fluctuating growth, and the pressure index is relatively stable. Based on this, the PSR model and entropy method are typical and quantifiable, which can provide a reference for Qinghai provincial government to control the ecological environment, study ecological sustainability and delimit the ecological red line.

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin.

Under the pressing imperative of achieving “dual carbon” goals and advancing urban low-carbon transitions, understanding how neighborhood spatial environments influence carbon emissions has become a critical challenge for enabling refined governance and precise planning in urban carbon reduction. Taking the central urban area of Xining as a case study, this research establishes a high-precision estimation framework by integrating Semantic Segmentation of Street View Images and Point of Interest data. This study employs a Geographically Weighted XGBoost model to capture the spatial non-stationarity of emission drivers, achieving a median R² of 0.819. The results indicate the following: (1) Socioeconomic functional attributes, specifically POI Density and POI Mixture, exert a more dominant influence on carbon emissions than purely visual features. (2) Lane Marking General shows a strong positive correlation by reflecting traffic pressure, Sidewalks exhibit a clear negative correlation by promoting active travel, and Building features display a distinct asymmetric impact, where the driving effect of high density is notably less pronounced than the negative association observed in low-density areas. (3) The development of low-carbon neighborhoods should prioritize optimizing functional mixing and enhancing pedestrian systems to construct resilient and low-carbon urban spaces. This study reveals the non-linear relationship between street visual features and neighborhood carbon emissions, providing an empirical basis and strategic references for neighborhood planning and design oriented toward low-carbon goals, with valuable guidance for practices in urban planning, design, and management.