Due to global warming, the overheating risk in the severe cold region of China has attracted attention, but so far, no studies have examined summer overheating in this region. This paper aims to reveal the overheating risk in recent and future climates in the severe cold region of China. An 18-storey residential building in the severe cold region of China was monitored from May to September 2021 to validate the simulation data of the indoor temperature. Weather files of the typical meteorological year (TMY) from 2007 to 2020, observations in 2021, and forecasts for the climate in different carbon emission scenarios (2030, 2060) were used to simulate the indoor temperature and assess the overheating risk. The results revealed the severity of the overheating risk; the overheating hours in the south-facing bedroom were recorded as 884 h (24.07%) with the TMY weather data and 1043 h (28.40%) in 2030 and 1719 h (46.81%) in 2060 under the RCP8.5 carbon emission scenario. Thus, the low carbon emissions policy may significantly alleviate overheating. Moreover, to cope with climate change, it is suggested that the Chinese local design standards should consider the summer overheating risk and make the necessary adjustments.

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

Global warming is resulting in higher summer indoor temperatures in the severe cold region and cold region of China, and this is affecting thermal comfort. Local building design codes consider these regions as cool in summer, and do not consider the phenomenon of overheating or propose countermeasures. This paper studied the possibility of overheating in residential buildings in these areas. It suggested alleviating this phenomenon using external horizontal shading, and discussed how to integrate thermal comfort into the building design and save energy consumption. The IESVE software was used to simulate 18-storey residential buildings with natural ventilation in Yichun, Harbin, Shenyang, Dalian, and Beijing, and to calculate the change in indoor operative temperature. Horizontal shading was designed for case study building to attempt to alleviate the overheating phenomenon in summer. The results showed that the case study building in the five cities experienced different degrees of overheating. External horizontal shading was successful in reducing indoor overheating, especially in the severe cold B and C zones and the cold A and B zones. The relevant building codes should be modified to take this into account. Reasonable design of horizontal shading can effectively reduce energy consumption, particularly when compared with air-conditioned buildings.

Given the prediction of global warming, there is a growing concern about overheating in the severe cold and cold regions of China. In the past decades, indoor thermal comfort has been neglected in building practice, while efficiency-oriented improvements have been developed, such as increased insulation of building envelope. An extensive literature review shows contradictory conclusions about whether increased insulation can alleviate overheating. The aim of this research is to conduct simulations based on measured data to reveal the influence of insulation on overheating in dwellings in these regions of China. An unoccupied residential flat was monitored to determine the extent of overheating while eliminating the effects of other contributors, such as natural ventilation. Validated building performance simulations were carried out with altered insulation layer thickness in Integrated Environmental Solutions-Virtual Environment IESVE software to examine its influence on overheating during summertime in five representative cities. The results showed clear evidence of summer overheating in these regions. In Yichun, Harbin, Shenyang, Dalian and Beijing, walls with increased insulation were found to exacerbate overheating in the bedrooms without natural ventilation by 22.5%, 16.6%, 20.3%, 11.8% and 6.9%, respectively, compared to the uninsulated walls. This study provides useful information for building regulations on energy efficiency and thermal comfort.

The building sector is a major source of global carbon emissions, with embodied carbon playing an increasingly critical role. This study quantitatively compares the life-cycle embodied carbon of three residential building design patterns (cast-in situ, CIS; design for disassembly, DfD; and skeleton–infill, SI) under a unified scenario of a 90-year service life with functional renovations every 30 years. A total of 36 cases, derived from twelve prototypical residential designs implemented in each pattern, were evaluated via life-cycle assessment following the EN 15978 standard. The results show that the SI pattern reduces embodied carbon by 45–55% compared to CIS, while the DfD pattern achieves a 35–45% reduction (with SI pattern consistently performing best). Structural system selection also influences outcomes, with shear wall structures reducing emissions by 7–14% compared to frame systems. Plan layout effects were marginal. The analysis indicates that the design pattern is the dominant factor influencing embodied carbon outcomes. SI pattern yields the largest carbon reduction by pairing a long-lived structural frame with flexible infill that extends service life and adaptability, while DfD lowers material demand via component reuse. These findings highlight the substantial benefits of circular design strategies and support a shift toward more adaptable, long-lifespan, and low-carbon residential design.

Rapid urbanization has exacerbated urban-stormwater challenges, highlighting the critical need for coordinated surface-water and groundwater management through rainfall recharge. However, current sponge city construction methods often overlook the crucial role of underground aquifers in regulating the water cycle and mostly rely on simplified engineering approaches. To address these limitations, this study proposes a spatial optimization framework for urban-scale sponge systems that integrates a hydrodynamic model (FVCOM), geographic information systems (GIS), and Monte Carlo simulations. This framework establishes a comprehensive evaluation system that synergistically integrates surface water inundation depth, geological lithology, and groundwater depth to quantitatively assess sponge city suitability. The FVCOM was employed to simulate surface water inundation processes under extreme rainfall scenarios, while GIS facilitated spatial analysis and data integration. The Monte Carlo simulation was utilized to optimize the spatial layout by objectively determining factor weights and evaluate result uncertainty. Using Shenzhen City in China as a case study, this research combined the “matrix-corridor-patch” theory from landscape ecology to optimize the spatial structure of the sponge system. Furthermore, differentiated planning and management strategies were proposed based on regional characteristics and uncertainty analysis. The research findings provide a replicable and verifiable methodology for developing sponge city systems in high-density urban areas. The core value of this methodology lies in its creation of a scientific decision-making tool for direct application in urban planning. This tool can significantly enhance a city’s climate resilience and facilitate the coordinated, optimal management of water resources amid environmental changes.