One significant challenge in lightweight modular integrated construction (MIC) is to determine the optimal performance of external wall to minimize life-cycle energy consumption, economic costs, and environmental impact (3E). This study compares 3E-objective and single-objective optimization methods for determining the optimal thickness of MIC across five distinct climatic zones in China. Additionally, it analyzes how factors like heating, ventilation, and air conditioning (HVAC) operational duration, climate change, grid emission factors, and building lifespan affect the optimal thickness. Results reveal that the 3E-objective optimization method achieves the highest cost-benefit ratio in carbon reduction, outperforming the energy or environmental method. Lightweight external walls, with low thermal mass, have an optimal thickness deviating from the current nearly zero-energy building standard, with deviations reaching up to 200 mm in optimal thickness. Reduced HVAC operational duration, global warming, decreased grid emission factors, and extended building lifespan contribute to a potential reduction in the optimal wall thickness by up to 140 mm. These deviations in the configuration of these factors, although they may lower life-cycle cost investments compared to the optimal thickness, could potentially be unfavorable or detrimental to reduce life-cycle energy consumption and carbon emissions. The deviation in HVAC operational duration exhibits the most significant impact on life-cycle 3E results, reaching up to 8.4 %. Climate change has a relatively minimal impact on the life-cycle 3E results. This research can advance the cost-benefit ratio in carbon emission reduction of MIC and highlight the need for flexible building standards to accommodate climatic and operational variations.

Climate change and extreme weather events are imposing threats to city power systems with regional power shortages. To enhance urban power system's resilience amid climate change, photovoltaic (PV) and battery energy storage systems (BESS) are crucial for maintaining self-sufficient power during outages. However, the optimal installation location and capacity sizing of BESS remain uncertain when considering multi-criteria, including safety, energy flexibility, accessibility and energy resilience. This study proposes a new approach, i.e., Geographic Information System (GIS) integrated with Multi-Criteria Decision-Making (MCDM) and capacitated p-median problem, to identify optimal installation locations and capacity allocation of BESS. This approach comprehensively considers geographical conditions (such as slope, land use, open space), safety, energy flexibility, accessibility and energy resilience, while accounting for the entire distribution network's granularity, intermittent solar supply, and unstable electricity demand. The methodology can guide the optimal BESS siting and sizing for energy resilience under future climate change and associated extreme weather events. Results indicate that suitable installation locations based on the proposed GIS-MCDM method are concentrated in central and southern regions in Yau Tsim Mong. Subsequently, BESS with the optimal and specific installation location and capacity allocation is in districts with high electricity demand and favourable safety geographical conditions. Compared to BESS without GIS-MCDM, the optimal BESS deployment with GIS-MCDM decreases the power shortage from 13,184 MWh to 12,931 MWh. Additionally, it increases the maximum power shortage reduction density from 176.04 kWh/m2 to 364.2 kWh/m2, and the area with a power shortage reduction above 100 kWh/m2 expands from 1.24 × 105 m2 to 2.17 × 105 m2. This study contributes a new approach to determine optimal BESS installation locations and capacity allocation in urban-scale information modelling, planning and deployment, with frontier guidelines for system designers and urban planners to collaboratively develop resilience and survivability of urban power systems under extreme events.

Zero-carbon community (ZCC) is essential in addressing critical social and environmental challenges, particularly in reducing energy consumption, lowering carbon emissions, and decreasing reliance on fossil fuels. However, several issues are still unclear, including inconsistent definitions of ZCC, the lack of detailed policy analyses, and limited exploration of implementation challenges and solutions persist. This study addresses these gaps by conducting a comprehensive analysis of the drivers and barriers to ZCC development in China. It begins with a detailed review of the definitions of ZCC, comparing and contrasting them from both domestic and international perspectives. Then, it evaluates existing incentives, categorizes them into policy documents, laws, and standards while assessing their evolution and real-world applications. This study also presents case studies of exemplary ZCC, including the Beddington Community in the UK and the Zero Carbon Pavilion at the Shanghai World Expo Park in China. These cases offer insights into practical approaches, societal impacts, and advanced practices, proposing a ZCC construction model tailored to China’s unique economic and policy environment. Furthermore, the study identifies key barriers to adopting ZCC in China and proposes targeted recommendations across five domains: administrative, economic, technological, socio-cultural, and environmental. A “macro-meso-micro” implementation pathway is developed, emphasizing stakeholder collaboration as a core element for successful execution. This study systematically reviews and critically analyzes current policies and practices related to ZCC, and offering valuable theoretical guidance for developing regulations and standards, along with practical solutions to address current implementation challenges.

The thermal performance of cylindrical latent heat storage units (C-LHSUs) in hot water tanks can be improved by using a hollow geometry structure, which effectively reduces the average distance between the heated/cooled wall and the solid-liquid interface during the charging and discharging process. To comprehensively evaluate this improvement, an unconstrained melting model for phase change materials (PCMs) was developed, enabling detailed investigation of the thermal behavior of hollow geometry LHSUs (H-LHSUs). Moreover, the impact of the ratio between the inner hollow tube radius (r) and outer tube radius (R) on the charging/discharging performance of H-LHSUs was analyzed. The results demonstrated substantial enhancements in heat transfer performance for H-LHSUs compared to conventional C-LHSUs. Specifically, the average heat transfer coefficient increased by 82.9 % during charging and 176.47 % during discharging. This improvement translated to a charging rate that was 2.46 times and a discharging rate that was 3.9 times higher than those of the C-LHSU. Furthermore, the study revealed that as the r/R ratio increased, both charging and discharging rates improved significantly, with the rate of heat transfer enhancement becoming more pronounced at higher r/R values. This research provides actionable insights for optimizing the design of LHSUs in practical applications. It underscores the importance of balancing thermal performance gains with the associated capital costs when selecting the optimal r/R ratio. The findings contribute to the advancement of energy storage technologies, offering a robust framework for improving the efficiency of thermal energy systems in hot water tanks.

The internal temperature of proton exchange membrane fuel cells significantly influences their shutdown purge process a key factor for ensuring operational stability and longevity. This study explores how cell temperature impacts water removal mechanisms during shutdown purge, emphasizing its importance for the operational stability of fuel cell. High-temperature purge experiments were conducted using an integrated stack experimental platform, revealing that prolonged high-temperature purging increased the high frequency resistance of a single cell to 639.44 mΩ∙cm2 and caused severe perforation of the membrane electrode assembly. To delve deeper into the mechanisms of cell temperature influence and the cause of perforation, an isothermal, transient, two-phase flow fuel cell model was developed. The cell temperature during purge was incrementally raised from 303.15 K to 358.15 K in 5 K steps. Detailed analyses of membrane desorption and water phase changes during purge processes were performed. At cell temperatures ranging from 338.15 K to 358.15 K, a 120-s purge reduced the membrane water content to below 4.8, with only a 5 % variation in residual membrane water. When the cell temperature exceeded 323.15 K, water activity increased with temperature, intensifying evaporation and leading to desorption of vapor from the membrane. Consequently, higher temperatures facilitated the removal of liquid water, with no liquid water remaining within cell above 323.15 K. Elevated cell temperatures accelerated the purge, resulting in lower liquid water content and increased vapor, but with minimal difference in membrane water content. The intense evaporation process and rapid purge at high temperatures were identified as direct causes of membrane electrode assembly perforation. This study highlights the critical role of cell temperature in the shutdown purge process, providing innovative insights into optimizing proton exchange membrane fuel cell operations for enhanced performance and durability.

Proton exchange membrane fuel cells offer promising clean energy solutions for various applications. However, their performance relies heavily on the properties of the microporous layer, which plays a crucial role in transporting and distributing the components in the fuel cell. To date, the potential for optimising the microporous layer material structural parameters to enhance the fuel cell performance remains largely unexplored. This study aims to fill this research gap by conducting a comprehensive investigation of the effects of different microporous layer material structural parameters on the heat and mass transfer in the membrane electrode assembly. MATLAB was used for optimising the performance of the fuel cell components. The results show that increasing the microporous layer thickness from 5 to 50 μm significantly affects the species transport, leading to a substantial reduction in the molar fraction of H₂ and O₂ at the electrochemical reaction sites. Furthermore, the distribution of the liquid water saturation inside the fuel cell is influenced by the porosity and permeability of the microporous layer. By increasing the porosity from 0.3 to 0.6, the liquid water saturation at the interface of the catalyst layer and microporous layer decreases by 0.52 % and 1.12 % at output voltages of 0.5 V and 0.7 V, respectively. This reduction enhances the efficiency of internal water transport. Moreover, reducing the permeability of the microporous layer from 2 × 10^-12 to 1 × 10^-13 at 0.5 V and 0.7 V leads to an increase in liquid water saturation at the interface of the proton exchange membrane and the catalyst layer by 1.49 % and 0.74 %, respectively, causing hindrance to the transport of internal liquid water. This study provides valuable insights into the interplay between the properties of the microporous layer material properties and heat and mass transfer characteristics in proton exchange membrane fuel cell.

This paper comprehensively investigates the purge mechanism of proton exchange membrane fuel cells during the shutdown process, which qualitatively examines the effect of purge parameters (including current density, stoichiometric ratio, and relative humidity) on water content variation, and further quantitatively investigates the remaining water content post-purge. In contrast to previous studies, this paper offers a novel perspective on analyzing the purge process and conducts a thorough examination of residual water content. This study presents a transient, isothermal, two-phase flow model for proton exchange membrane fuel cells, which is subsequently validated experimentally. Results indicate that the significance of purge parameters follows the descending order: stoichiometric ratio, relative humidity, and current density. During the purge, the stoichiometric ratio should be rapidly increased to above 9. Each incremental rise in the stoichiometric ratio from 6 to 14 leads to a respective reduction in residual membrane water content after purge of 2.19 %, 1.57 %, 1.18 %, 0.93 %, 0.76 %, 0.63 %, 0.53 %, and 0.46 %. Similarly, it is recommended to swiftly decrease relative humidity to below 40 %. Elevating the purge current density from 20 to 200 mA/cm2 decreases the time required to completely remove liquid water from 20.24 s to 6.59 s. Hence, employing a higher current density at the onset of the purge facilitates quicker removal of liquid water, albeit resulting in an increase in residual membrane water content post-purge, from 3.17 to 3.70. In summary, optimizing the purge strategy requires adjusting purge current densities according to the specific purge stage.

Energy piles, a technology integrating the heat exchange component within building pile foundations for shallow geothermal energy utilization, have proven economically efficient. They outperform conventional ground source heat pumps by mitigating additional borehole costs and space requirements. This paper systematically examines low-carbon considerations and optimization measures throughout the planning, design, construction, and operation stages of energy piles, considering the entire lifecycle. Furthermore, this paper discusses potential challenges associated with decarbonizing energy piles, offering solutions based on case studies and environmental impact assessments. Through a comprehensive critical review and analysis of existing knowledge, this paper presents a systematic theory and methodology for optimal decarbonization of energy piles, serving as a valuable resource for building practitioners and researchers in this field. The findings not only contribute to a solid theoretical foundation but also provide technical support for the advancement and application of energy pile systems.

To explore factors that influence the likelihood of committing fraud in the construction industry, this study concentrated on senior executives and tested whether some characteristics at the individual and firm levels have impacts on the likelihood of fraud committed by top management. Based on social network theory, this study first proposes that intrafirm alumni networks may increase the probability of senior executives engaging in corrupt behavior. Then the study explored whether the effect of executives' alumni networks on their wrongdoings is influenced by external and internal corporate governance measures. To verify the hypotheses, this study collected data on 2,017 senior executives from 118 construction companies in China from 2013 to 2021. Because of the multilevel structure of the data, hierarchical linear modeling was used. The results show that alumni networks have a significant positive effect on top management fraud. The effect is weakened by external auditing, altered by board independence, and strengthened by the size of the board of directors and the size of the supervisory board. This multilevel research contributes to advancing the understanding of managers' fraudulent behavior within an organization and extends the literature on social networks and corporate governance in the construction industry.

This chapter addresses Social Innovation. It describes conditions, methods, and procedures to optimize engagement and strengthen people's and the community’s position in affordable energy renovations in buildings and on the district level. We focus on the lower- and middle-income occupants being tenants of not-for-profit or public housing associations and owner / occupiers in apartment buildings. [...]

Rooftop photovoltaic (PV) with battery storage offers a promising avenue for enhancing renewable energy integration in buildings. Creating microgrids with backup power from closely spaced solar buildings is widely recognized as an effective strategy. Nevertheless, a notable gap exists between the preferences and priorities of electricity consumers residing in these solar-powered buildings and the interests of microgrid investors. The electricity consumers focus on decreasing the levelized cost of energy, while the microgrid investors focuses on achieving high net profit. This study proposes a novel game theory-based microgrid optimal design approach for designing power generations of the microgrid system and PV installation with battery storage on the building roofs, considering the different requirements and interests of electricity consumers and microgrid investors. The design optimization is framed around the Nash Equilibrium of the Stackelberg game, incorporating a bi-level optimization cycle that addresses the conflict and cooperation of electricity consumers and microgrid investors. A win-win situation can be yielded using the developed optimal design approach compared to conventional optimal design approaches. The results demonstrate a significant improvement, with the microgrid power generation yielding a large net profit (up to 0.08 USD/kWh) and concurrently reducing the levelized cost of energy by approximately 14 %.

The increasing greenhouse gas (CO2) emissions constitute one of the most significant global environmental issues. CO2 emissions from buildings and transportation are responsible for the largest proportion of total global carbon emissions from various sectors. Therefore it is necessary to utilize clean energy sources (e.g., renewable energy, energy storage systems, and electric vehicles) to decarbonize the building and transportation sectors. The integrated building transportation energy system (IBTES) is a system that combines the energy demands of buildings and transportation in an integrated manner. However, this integrated system has many issues in its practical applications, especially considering the social and economic aspects. A social and economic analysis of IBTES will consider the impacts on various stakeholders, including building owners and users, transportation users, energy suppliers, etc. This study will systematically summarize the current application and development status of IBTES from both social and economic perspectives. In terms of the social perspective, IBTES can improve energy efficiency and reduce CO2 emissions, which will have a positive impact on the environment and public health. From an economic perspective, IBTES has the potential to decrease the energy costs of buildings and transportation users. In addition, it has the potential to create new jobs in the energy and transportation sectors, and potentially attract new businesses and investments to a region. This study also summarizes several issues and challenges of IBTES, including the cost of implementing and maintaining the system, social acceptance, and inadequate related regulations. Based on this, the study proposes recommendations to effectively promote the implementation of IBTES. This study can provide some theoretical guidelines and suggestions for policymakers.

Urban sustainability is a pressing challenge that intertwines energy efficiency, social equity, technological innovation, and community involvement. With the growing global emphasis on reducing carbon footprints and addressing climate change, the need for sustainable urban housing and communities has become increasingly critical. This Research Topic, “Sustainable Transition for Urban Housing and Community,” brings together a Research Topic of research that examines the multifaceted issues surrounding sustainable development in urban contexts. By analyzing the interplay of energy consumption, governance, technological innovation, and digital transformation, the articles in this Research Topic present a holistic view of how urban sustainability can be achieved. [...]

The local climate zones (LCZs) classification system has emerged as a more refined method for assessing the urban heat island (UHI) effect. However, few researchers have conducted systematic critical reviews and summaries of the research on LCZs, particularly regarding significant advancements of this field in recent years. This paper aims to bridge this gap in scientific research by systematically reviewing the evolution, current status, and future trends of LCZs framework research. Additionally, it critically assesses the impact of the LCZs classification system on climate-responsive urban planning and design. The findings of this study highlight several key points. First, the challenge of large-scale, efficient, and accurate LCZs mapping persists as a significant issue in LCZs research. Despite this challenge, the universality, simplicity, and objectivity of the LCZs framework make it a promising tool for a wide range of applications in the future, especially in the realm of climate-responsive urban planning and design. In conclusion, this study makes a substantial contribution to the advancement of LCZs research and advocates for the broader adoption of this framework to foster sustainable urban development. Furthermore, it offers valuable insights for researchers and practitioners engaged in this field.

In response to the growing global demand for clean and sustainable energy solutions, proton exchange membrane fuel cells (PEMFCs) have emerged as vital components in diverse decarbonization strategies. Despite their increasing importance, a comprehensive synthesis of recent advancements, challenges, and future prospects in thermal and water management within this domain remains notably scarce. This paper aims to bridge this gap by conducting a meticulous literature review focused on thermal and water management in PEMFCs. Primarily, this study encapsulates the underlying mechanisms governing thermal and water generation in PEMFCs, intricately analyzing thermal and water generation analyses. Secondly, a multifaceted exploration of thermal and water transfer mechanisms, alongside their pivotal influencing factors, is presented. Furthermore, the discourse delves into sophisticated strategies for refining water and thermal management in PEMFCs. As well as delving into the complexities of high-power heat dissipation and water balance, especially water management for cold start and high temperature operating conditions. The culmination of this investigation yields valuable insights into the intricate dynamics of thermal and water management within PEMFCs, thereby culminating in forward-looking recommendations for future research trajectories. These findings not only offer scholars a vantage point to discern emerging research frontiers and trends but also extend theoretical precepts and reference points for technology innovators and product developers.

Advanced controls have attracted increasing interests due to the high requirement on smart and energy-efficient (SEE) buildings and decarbonization in the building industry with optimal tradeoff strategies between energy consumption and thermal comfort of built environment. However, a state-of-the-art review is lacking on advanced controls for SEE buildings, especially considering advanced building energy systems, machine learning based advanced controls, and advanced occupant-centric controls (OCC). This study presents a comprehensive review on the latest advancement of advanced controls for SEE buildings, which covers recent research on data collection through smart metering and sensors, big data and building automation, energy digitization, and building energy simulation. Machine learning based advanced controls are comprehensively reviewed, including supervised, unsupervised and reinforcement learning, together with their roles and underlying mechanisms. In addition, advanced controls for energy security, reliability, robustness, flexibility, and resilience are further reviewed for energy-efficient and low-carbon buildings, with respect to fault detection and diagnosis, fire alarming and building energy safety, and climate change adaptation. Moreover, this study explores the advanced OCC systems and their applications in SEE buildings. Last but not the least, this study emphasizes the challenges and future prospects of the trade-off between complexity and predictive/control performance, AI-based controllers and climate change adaptation, OCC in thermal comfort and energy saving for the SEE buildings. This study offers valuable insights into the latest research progress concerning the underlying mechanisms, algorithms and applications of advanced controls for SEE buildings, paving the path for sustainable and low-carbon transition in building sectors.

Ocean thermal and power energy systems are promising driving forces for seashore coastal communities to achieve net-zero energy/emission target, whereas energy planning and management on ocean thermal/power and distributed building integrated photovoltaic (BIPV) systems are critical, in terms of serving scale sizing and planning on geographical locations of district building community, and cycling aging of battery storages. However, the current literature provides insufficient studies on this topic. This study aims to address this research gap by transforming towards zero-energy coastal communities from the district level in subtropical regions, including centralised seawater-based chiller systems, distributed BIPVs and coastal oscillating water column technologies, as well as multi-directional Vehicle-to-Building energy interaction paradigms. Advanced energy management strategies were explored to enhance renewable penetration, import cost-saving, and deceleration of battery cycling aging, in response to relative renewable-to-demand difference, off-peak grid information with low price, and real-time battery cycling aging. Furthermore, in accordance with the power generation characteristic of two wave stations (i.e., Kau Yi Chau (KYC) and West Lamma Channel (WLC)) in Hong Kong, energy system planning and structural configurations of the coastal community were proposed and comparatively studied for the multi-criteria performance improvement. Research results showed that, compared to an air-cooled chiller, the water-cooled chiller with a much higher Coefficient of Performance (COP) will reduce the energy consumption of cooling systems, leading to a decrease in total electric demand from 134 to 126.5 kWh/m²·a. The scale for the net-zero energy district community with distributed BIPVs and oscillating water column was identified as 5 high-rise office buildings, 5 high-rise hotel buildings, 150 private cars and 120 public shuttle buses. Furthermore, the geographical location planning scheme on the Case 1 (office buildings close to KYC, and hotel buildings close to WLC) was identified as the most economically and environmentally feasible scheme, whereas the Case 3 (only office buildings are planned close to all power supply with oscillating water column) showed the highest flexibility in grid electricity shifting, together with the highest value of equivalent battery relative capacity. This study demonstrates techno-economic performances and energy flexibility of frontier ocean energy technologies in a coastal community under advanced energy management strategies, together with technical guidance for serving scale sizing and planning on geographical locations. The research results highlight the prospects and promote frontier ocean energy techniques in subtropical coastal regions.

Energy, water, and the environment have remarkably complex interrelationships, with these linkages being both direct and indirect. The innovative development of artificial intelligence (AI) technologies brings significant opportunities for investigating renewable energy (RE), water, and the environment and presents a multitude of challenges. Using AI to promote sustainable production and consumption of RE and water and protection of the environment has become a hot research area that enables AI to empower sustainable human development and promote its own sustainable development. However, there are few summaries and analyses of studies on the application of AI to RE, water, and environment (REWE) nexus. The objective of this chapter is to discuss the application of AI to the REWE nexus. First, this chapter presents and analyzes the AI techniques that are applicable to RE, water, and the environment fields, respectively, and categorizes and integrates them. Also, the chapter summarizes AI application in the REWE nexus. Furthermore, the chapter analyzes the application feasibility of AI for establishing city-level REWE nexus studies and identifies challenges and barriers to their implementation. Finally, the chapter presents the future perspectives for the application of AI to urban-level REWE nexus.

The cooperative behavior of residents is complex and influenced by their complicated social relationships. This complexity is especially noticeable in neighborhood renewal, so the government does not know how to promote residents' cooperative behavior. Therefore, this study proposes an agent-based model (ABM) to investigate the development of residents' cooperative behavior in neighborhood renewal. Based on a questionnaire survey among residents of old neighborhoods in China, the parameters of ABM were determined in this study. Then, controlled experiments were conducted to investigate the effects of general trust among residents and government control of neighborhood renewal on cooperation patterns in renewal projects. In addition, this study examines the effects of different types of social network structures (small-world, scale-free, and random networks) on the evolution of residents' cooperative behaviors. The simulation results show that when residents' initial willingness to agree to renewal projects is high, their close social relationships need to be managed by the government to achieve better outcomes. Conversely, if initial willingness is low, residents' close relationships may pose a challenge to the government. In addition, government-led renewal projects should be encouraged to a greater extent. This study confirms that the different social network structures have an influence on the development of residents' cooperative behavior. The results of this study provide concrete evidence for understanding the factors that contribute to the emergence of residents' cooperative behavior and for studying the effects of government intervention on neighborhood renewal projects. In addition, the results of this study provide theoretical support for future studies of residents' social network structures.

Past studies reveal that air infiltration through the building envelope and its impact on the indoor environment and energy consumption are significantly influenced by climate characteristics. However, little relevant information is available for buildings in southern China, where the building design traditionally follows a philosophy of being open and shaded. The present study employs both experimental measurements and numerical simulations to investigate the airtightness of buildings in Hot Summer and Cold Winter (HSCW) climate region of southern China and the associated energy consumption. The measurements and simulations are based on a typical office building in Changsha. Measurement results show that the air infiltration rate of six tested spaces at the natural pressure difference ranges from 0.10 to 0.30 h⁻¹ with an average of 0.17 h⁻¹ in summer, and from 0.09 to 0.32 h⁻¹ with an average of 0.16 h⁻¹ in winter. The operation of the air-conditioning system affects largely air infiltration, and each unit change in setpoint air temperature can result in an average of one-third or more change in air infiltration rate. Simulation results show that a decrease in air infiltration rate from 0.17 h⁻¹ to 0.01 h⁻¹ reduces the infiltration-related cooling energy consumption from 14.29 to 0.75 kWh/m²·year and heating energy consumption from 8.20 to 0.39 kWh/m²·year. The same change in the setpoint air temperature of air-conditioning system in summer and winter results in different infiltration-related energy consumption. The findings would contribute to an improved energy simulation and assessment of buildings in southern China.