Hospital buildings provide healthcare services at the costs of significant amounts of energy consumption and carbon emissions, further exacerbating the environmental load. Because of the limited research on the life cycle carbon emissions of Chinese hospitals, this study conducted a detailed carbon-accounting and comparative study. Firstly, BIM and LCA were used to quantify the carbon emissions of the inpatient building in each stage of the life cycle. Secondly, the differences in carbon emissions by stage were compared on the basis of 20 cases of public buildings. The results show that the whole-life carbon emissions of the inpatient building was 10,459.94 kgCO₂/m². The proportion of operational carbon emissions was 94.68%, with HVAC (52.57%), equipment (27.85%), and lighting (10.11%) being the main sources. Embodied carbon emissions accounted for 4.54%, and HRB400 steel and C30 concrete were the main sources of carbon emissions. Hospitals are second only to emporiums in terms of operational carbon intensity, being 1.71 and 1.41 times that of schools and office buildings, with inpatient buildings being 3 and 1.7 times that of medical complexes and outpatient buildings, respectively. The future sustainable development of hospital buildings should promote efficient building performance and good environmental quality, both in terms of energy efficiency and carbon reduction.

The building sector contributes to 50.9 percent of China’s carbon emissions. Due to the complexity of the assessment process, it is difficult to predict the entire life cycle carbon emissions of a building at the early stage of design. In this study, a whole-life carbon emission estimation model for the early stage of building design is developed based on comparison of the standard calculations and an analysis of stock cases. Firstly, the standard calculation methods in China, Japan and Europe were compared, and the boundary of the model was defined in three parts: production, construction and demolition and operation. Second, information on 68 examples of Chinese buildings was collected and divided into a training set and a test set at a ratio of 7:3. In the training set, the relationship between carbon emissions and the design parameters was searched, and a carbon emission estimation model applicable to different stages was constructed. Finally, the model was applied to the test set for validation. The results show that the calculation error of the model is within ±15%, and it can quickly estimate carbon emissions based on the design factors, which is helpful for carbon emission assessment work in the early stages of design.

Airborne fine particulate matter (PM2.5) is an important factor affecting indoor air quality and is significantly related to human health. A lot of research has been done on PM2.5 pollution control in buildings, but there is lack of systematic indoor PM2.5 pollution control for engineering applications. In this study, first, we propose an outdoor calculated concentration of PM2.5 in 74 cities, in China, using the “not guaranteed for five days” method, which is based on outdoor PM2.5 concentration monitoring data from 2016 to 2018. Then, different levels of indoor calculated concentrations of PM2.5 (25 μg/m³, 35 μg/m³, and 75 μg/m³) are put forward. Secondly, methods for selecting air purification equipment in centralized, semi-centralized, and decentralized air conditioning systems are proposed. Finally, PM2.5 pollution control measures and system energy-saving operation strategies in buildings are put forward. This study stipulates the calculation of PM2.5 concentration, unifies design methods, proposes control measures, and standardizes operations management. The aim of this study is to provide technical guidance for engineering design, construction and operation, and therefore to reduce the risk of indoor diseases caused by exposure to PM2.5.

To promote green and low-carbon transformation in the transportation sector and achieve the national “dual-carbon” targets, this study examines rooftop photovoltaic (PV) deployment at 12 representative railway stations located on the Qinghai–Tibet Plateau. Using high-resolution solar radiation data, building spatial information, and regional electricity pricing, we develop an integrated analysis framework that combines a PV power-generation simulation, life-cycle cost assessment, and carbon emission reduction evaluation. The model systematically evaluates the power output, economic performance, and emission reduction potential of rooftop PV systems installed on railway station buildings. Two PV array configurations—horizontal angle and optimum tilt angle—together with three business models (T1: all-consumption; T2: all-feed-into-grid; T3: self-consumption with surplus feed-in) are compared. The results indicate that the Qinghai–Tibet Plateau possesses substantial solar energy advantages. Rooftop arrays installed at a horizontal angle significantly increase both installed capacity and lifetime electricity generation, with stations XN and LS producing 523.12 GWh and 300.87 GWh, respectively, values that exceed the corresponding optimum tilt scenarios. In terms of economic performance, the T1 model yields the highest returns, with several stations achieving a lifetime return on investment exceeding 300% over a 25-year period. The T3 model demonstrates strong profit potential at stations such as RKZ and ZN, whereas the T2 model shows the weakest economic viability due to feed-in tariff constraints. Regarding carbon reduction, horizontal systems perform the best, with cumulative CO₂ emission reductions at station XN exceeding 300,000 tonnes of CO₂-equivalent. Overall, the findings highlight the substantial PV development potential of railway station rooftops on the Qinghai–Tibet Plateau. By selecting appropriate installation angles and business models, significant economic benefits and carbon emission reduction outcomes can be achieved, providing practical guidance for renewable-energy utilization in high-altitude transportation infrastructure.