Households are an important sector in carrying out human development activities, accounting for more than 30% of the total global energy consumption. The continued growth of household energy consumption (HEC) and carbon emissions is threatening economic and environmental sustainability. This review focuses on the research in the field of HEC and conducts a bibliometric analysis of research articles from the Web of Science Core Collection since 2000. The results show that: 1) HEC research has undergone rapid development since 2014, and interdisciplinary fusion and collaborative research have become dominant trends. 2) Keyword co-occurrence analysis clearly identifies the current urgent themes, including energy demand and its determinants, environmental impact factors and assessments, and energy-saving technologies and emission reduction measures. 3) The analysis of citations reveals that economic models, such as input-output models and life cycle assessment, are frequently employed in the field of HEC. Based on a summary of household energy-saving and emissions reduction work, this paper critically discusses the limitations of existing measures such as smart home technology, sustainable energy systems, and behavioral interventions. The main directions for promoting household energy-saving development in the future are identified: including improving the security and customer engagement of smart home technology, focusing on the availability and stability of sustainable energy, and paying more attention to low-income and aging households in behavioral intervention measures. One of the important obstacles facing research is how to reduce energy management efficiency and usage costs through technology and policy.

Building operations account for a large amount of energy use and CO₂ emissions, and the morphology of buildings in residential clusters strongly impacts energy efficiency performance. However, little research has focused on the morphology and energy electricity usage of high-rise residential clusters in hot summer and cold winter (HSCW) regions. We investigated 96 residential clusters in Hangzhou, China, and established a corresponding morphology database. Additionally, we obtained annual electricity consumption for 16 of these residential clusters. With this database, we performed optimization of morphological parameters upon energy use intensity (EUI) using a genetic algorithm (GA). Specifically, the cooling, heating, and lighting EUIs of high-rise residential clusters were studied. After implementing the optimized morphological parameters, there was a reduction of up to 7.73% in EUI. According to regression analysis, the average aspect ratio was the most significant factor influencing EUI (r = −0.907), followed by floor area ratio (r = −0.755), average orientation (r = 0.502), and average number of floors (r = −0.453). These results indicate that a higher intensity of land development with a greater floor area ratio, average aspect ratio, and average number of floors can reduce total energy consumption. Additionally, we found that an average building orientation of southwest 15° (with respect to south) is optimal. The findings of this study can assist urban planners and designers in developing more sustainable residential clusters, leading to decreased energy costs and CO₂ emissions.

The construction industry, characterized by high energy consumption and carbon emissions, plays a pivotal role in climate change mitigation. This paper employs bibliometric analysis, based on 282 articles from the SCIE and SSCI in the Web of Science spanning 1992–2022, to explore research trends and themes in Carbon Emissions of Construction Industry (CECI). A manual review was conducted to identify challenges and possibilities concerning accounting scales, objects, boundaries, and methods in CECI research. Key findings include (1) temporal and thematic evolution, with a notable increase in research activity since 2015, primarily focusing on energy efficiency, sustainable development, green building technologies, and policy evaluation; (2) scale-specific gaps, as 80.7% of studies are conducted at macro (national/regional) or micro (building/material) levels, while city-scale analyses are significantly underrepresented, with only 13 articles identified; (3) object granularity deficiencies, with 74.8% of studies not distinguishing between building types, resulting in rural residential, educational, and office buildings being significantly underrepresented; (4) system boundary limitations, as few studies account for emissions from building demolition or the disposal and recycling of construction waste, indicating a substantial gap in life-cycle carbon assessments. Furthermore, the predominant reliance on the carbon emission factor method, along with embedded assumptions in accounting processes, presents challenges for improving carbon accounting accuracy. This review synthesizes insights into prevailing research scales, object classifications, system boundaries, and methodological practices, and highlights the urgent need for more granular, lifecycle-based, and methodologically diverse approaches. These findings provide a foundation for advancing CECI research toward more comprehensive, accurate, and context-sensitive carbon assessments in the construction sector.

Household energy consumption is one of the major drivers of carbon emissions, and an in-depth analysis of its influencing factors, along with forecasting carbon emission trajectories, is crucial for achieving China’s carbon emission targets. This study reviews the research progress on urban household energy-related carbon emissions (HErC) in China since 2000, with a focus on the latest developments in influencing factors. The study categorizes these factors into five major groups: household characteristics, economic attributes, energy consumption features, awareness and norms, and policies and interventions. The findings indicate that income levels, energy efficiency, and household size are the key determinants of urban HErC of China and are commonly used as core assumptions in scenario-based forecasts of emission trends. In addition, although environmental awareness and government services have increasingly garnered attention, their specific effects require further investigation due to the challenges in quantification. A synthesis of existing forecasting studies suggests that, without the implementation of effective measures, HErC will continue to rise, and the peak emission period will be delayed. Enhancing building and energy efficiency, promoting low-carbon consumption and clean energy applications, and implementing multidimensional coordinated policies are considered the most effective pathways for emission reduction.

Rapidly increasing household energy consumption poses significant challenges to global warming mitigation and the transition to low-carbon economies, particularly in China. This paper addresses this issue by introducing a comprehensive segmentation model which effectively subdivides household energy usage into five end-uses: cooking/hot water, heating, cooling, lighting, and power. The segmentation model uncovers compelling insights into urban end-use energy consumption patterns across China and variations among provinces. We observe a consistent increase in urban household end-use energy consumption and per capita energy consumption levels over the past decade. Heating and cooking/hot water emerge as the dominant contributors to household energy consumption, accounting for 26% and 40% of the total, respectively. Furthermore, it is found that higher levels of urbanization and improved living conditions are positively correlated with increased power energy consumption. The declining number of household members, primarily due to the prevalence of nuclear families, has resulted in higher energy end-use, particularly in both developed and underdeveloped economic areas. This paper serves as a valuable foundation for understanding and quantifying household end-use energy consumption. The findings contribute to a more comprehensive understanding of energy consumption patterns, facilitating a cleaner and more sustainable transformation of energy consumption structures.