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As the built environment is among the main contributing sectors to climate change, it is needed to investigate new paradigms to push decarbonization efforts towards the ambitious objectives defined internationally. It is a shared understanding that shifting the perspective from the single building to the district perspective is required to fully take into consideration the complexity of all interactions undergoing within the built environment, thus the concept of Positive Energy District emerged as a district with annual net zero energy import and net zero CO 2 emission working towards an annual local surplus production of renewable energy. In this framework, this paper explores the investigation of the potential for achieving the level of Positive Energy District in a group of non-residential buildings in Balaguer, Catalonia, Spain. These buildings, occupying 8,825 m2 in the city centre, require significant refurbishment for improved energy performance. The analysis includes building energy modelling and simulation, renovation studies, several alternative balance calculations, and carbon emissions assessment. The paper also considers mobility and embodied energy and their impact on energy/carbon balances. The results show that Positive Energy Districts carbon and primary energy balances are not met with rooftop PV installations when retrofitting an existing district towards the Positive energy target but further significant PV areas (roughly + 50%) are required to meet merely the use stage balances: negative results are traced when mobility and embodied energy are computed. A formulation alternative to the simple mathematical balance to facilitate the diffusion of Positive Energy District as catalyst of urban decarbonisation could be needed, including context factors and alternative systems (e.g., rating systems). [ABSTRACT FROM AUTHOR]

[Display omitted] • In this paper, we report on the process of quantifying carbon emissions for construction projects, including the source and flow of information required from cradle-to-cradle. Among the highlights: • This paper reports common materials and typical stages studied in carbon quantification. • The paper outlines the data needed and data sources for carbon quantification at all stages. • Assumptions made at each stage of the lifecycle were presented. • Transparency in carbon emission quantification is stressed. • The paper suggested adopting technology (BIM, IoT, etc.) to improve carbon quantification. blockchain: The paper suggested adopting technology (BIM, IoT, blockchain, etc.) to improve carbon quantification. Climate change has raised awareness on the need to achieve net-zero carbon emissions and improve the sustainability of buildings. To reduce the complexity of quantifying carbon emissions, there is a need for practical guidance on the quantification of lifecycle carbon emissions from buildings. Existing reviews appear to only focus on part of carbon emissions quantification and are therefore deemed unable to provide an overview of how to quantify the building's whole lifecycle carbon emissions. Hence, this study aims to review the quantification process of carbon emissions from cradle to cradle in the construction industry, which included trends in the materials studied, lifecycle stages studied, quantification methods, common data extraction practises, assumptions made and formulas used to quantify carbon emissions. A systematic review was conducted according to the PRISMA methodology. This study identified 699 publications from Scopus and Web of Science, and 65 full-text articles were included in the review. It can be concluded that the current practises lack transparency, which prohibits the comparison of different case studies. Also, all the information required for the quantification of carbon emissions during different stages was specified in detail to guide the carbon quantification process. The review further found that the production stage was the most commonly studied stage in previous research. In cases of missing information, assumptions were made, which were found to be common in practise. The underlying assumptions must be explicitly and thoroughly specified in order to avoid simplification and prevent inaccurate quantification of carbon emissions, and ultimately ensure the effectiveness of low-carbon design strategies. The review also highlighted the challenges in quantifying carbon emissions and proposed that these challenges be addressed by identifying appropriate solutions through the integrated use of digital technologies, such as Building Information Modelling (BIM), the Internet of Things (IOT), and blockchain technology. Adoption of these technologies can lead to better data collection and sharing, increased transparency, secure collaboration among stakeholders, and the potential establishment of standardised methodologies for accurate carbon emissions quantification, all of which can lead to improved energy efficiency management in the built environment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Regions where feed-in tariff higher than valley price should follow dual objective optimization. • The economy of the household PV-BES-EV system mainly depends on the purchase cost of EVs. • Decreasing electricity price will not undermine the effectiveness of the household PV-BES-EV system. • The energy bills and carbon emissions decrease significantly with the optimal scheduling schemes. The household PV-BES-EV system (photovoltaic - battery energy storage - electric vehicle system) connected to the grid can guarantee the electricity demand of the household and facilitate the flexible trade with the grid to achieve the goals of cutting energy bills and reducing carbon emissions. In related issues, past studies often assume that renewable energy is both economical and environmentally friendly, and thus regarded it as the primary power source. While in fact, in some regions where the feed-in tariff is higher than the sales price at a certain time, households may be driven by arbitrage opportunities to frequently purchase electricity from the grid at the certain time to gain benefits, resulting in far greater carbon emissions than expected within the household measurement boundary. To avoid the environmental burden caused by pure economic incentives and to provide practical and sustainable solutions consistent with various energy price policies, the optimal scheduling schemes of the household PV-BES-EV system that considers both economic and environmental incentives for different scenarios solved by the genetic algorithm is proposed in this paper. Household data in Shanghai, China and Hamburg, Germany were selected for modelling, representing the dual-objective optimization scenario with arbitrage opportunities and the single-objective optimization scenario with sales price higher than feed-in tariff, respectively. Results show that for urban and rural residents in Shanghai, the energy bill and carbon emission would decline about 105%, 48% and 88%, 62%, respectively. As for Hamburg, the accordingly results would be 69% and 64%. In addition, based on the cost-effectiveness of the system in long-term, this paper puts forward policy recommendations that align with local conditions to further improve the economy of the system. [ABSTRACT FROM AUTHOR]

As most promoted solution of climate change, green buildings become more popular and widely promoted in China recently. This paper compared the carbon emissions of green buildings with non-green buildings; therefore, a life cycle carbon emission assessment approach (LCA) was attempted. In the present paper, we have integrated existing database Building Environmental Load Evaluation System (BELES) developed by Tsinghua University and twenty-six real existing buildings (nine residential and seventeen commercial buildings). Buildings located in two major climate zones were selected, namely, zone II and III. Five phases were defined for a whole life cycle of building: Phase 1 Raw Materials, Phase 2 Transportation, Phase 3 Construction, Phase 4 Operation & Maintenance and Phase 5 Demolishment. In each phase, the emissions were calculated separately. It is found that whole life cycle CO 2 (LCCO 2 ) of green buildings are lower than that of non-green buildings, i.e., 10% for residential and 32% for commercial buildings, respectively. For both residential and commercial buildings, Operational & Maintenance phase contributes the majority of emissions in the whole life cycle, about 69.2–89.3%. Moreover, green buildings have slightly higher embodied CO 2 emissions than non-green buildings, but with much lower operational emissions, and this phenomenon is significant in residential buildings. This indicates that the LCCO 2 of green buildings start to match with LCCO 2 of non-green buildings after operating for certain years, which is the turning point. Furthermore, China implemented Standard for Energy Consumption of Buildings in December 2016, which listed two values for energy efficiency in operational phase, which represents requested and optional. It can be expected that the emissions in Operational & Maintenance phase of green buildings will be further reduced in the future. Consequently, in the future, the dynamic flow of turning point of residential buildings will be shifted downwards from existing 14 years found in this paper. [ABSTRACT FROM AUTHOR]

To meet the goals established by the 2015 Paris Accord, scientists say that we will need to achieve zero emissions between 2030 and 2050, which will require a drastic departure from current practices in the building industry, as buildings are a primary contributor of carbon emissions and a major consumer of natural resources. However, building technology research is often driven by disciplinary 'experts' and end-users have little opportunity for involvement in the design process. As buildings become more technologically complex, users must rely on industry professionals with specialized knowledge to design, manufacture and manage these increasingly complex environments Instead, this paper provides an alternative attitude to approachable research methods that open up building technology innovation opportunities to untraditional innovators. When the user has control of the design/innovation process, it opens up a new realm of possibilities rich with lived experience. Understanding the movement of heat, or thermal transmittance , through materials and assemblies is critical in controlling energy consumption in buildings. Despite recent advances in computational technologies, physical testing is still the industry standard to determine a material's thermal properties. However, this process can require expensive equipment, a controlled environment for testing and deep technical knowledge to create a degree of accuracy that is not necessary for all phases of the innovation process and can even act as a barrier to the early stages of design. In this paper we propose the Approachable Hot Box (AHB), a low-cost, low-tech and accessible testing apparatus that can quickly and easily evaluate the impact of simple building materials and assemblies on ambient environmental conditions. By reducing unnecessary complexity for early-level design decisions, the AHB is consistent and reliable at an affordable price. Not only does the AHB rapidly and affordably test small material samples, it helps to articulate potentially complex concepts in a tangible and understandable way, which helps to lower the barrier to innovation. By creating a non-disciplinary, iterative design approach that uses conventional materials and accessible concepts, this work demonstrates that rapid experimentation can be used as a tool to study building assemblies or systems by non-traditional innovators. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in electricity consumption and carbon emissions from households in smart buildings. This increase has had a profound impact on the economic aspects of residential electricity consumption and the achievement of the national dual carbon goal. In this paper, an optimal scheduling model for household loads in smart buildings is established. It considers the user demand side, grid-side supply, and the impact of the PV energy storage system (PESS) on carbon emissions. The optimization objectives are the economy of household electricity consumption and the total deviation of electricity consumption. Second, the adaptive mixed inverse learning strategy multi-objective beluga optimization algorithm (AMOBWO) is adopted to enhance its overall dynamic optimization. This optimization addresses challenges such as the uneven distribution of electricity consumption, load timing constraints, power limitations, and uncertainty in electricity consumption during the scheduling of smart building loads. Finally, the results demonstrate that AMOBWO decreases the total cost of household electricity consumption in smart buildings by 59.32% (based on the selected maximum PV capacity). Additionally, it reduces the total deviation by 14.28% after optimal scheduling. As the PESS capacity increases, there is a significant reduction in the indirect carbon emissions from smart buildings, decreasing from 881.279 kg CO 2 to 431.299 kg CO 2. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

Planning and managing energy production, transmission, and distribution face new challenges as renewable energy sources become more widely used. These sources enhance existing issues of grid operation due to their unpredictability and intermittency. As a result, sophisticated energy system control techniques and technologies that offer novel flexibility solutions to the inelastic demand side are necessary to ensure the power system's stability. This paper reviews the feasibility of demand response as a tool for effective grid management and a measure for properly sized renewable energy systems (RES) capacities, both of which could accelerate the phase-out of fossil fuels. Research also focuses on tapping into the building stock's demand response capacity in an effort to decrease operational CO 2 emissions. In this line of approach, current status and goals of the respective European policies are analyzed. The role of market based decarbonization is studied and presented along with the status of demand response market implementation in several countries. [ABSTRACT FROM AUTHOR]

[Display omitted] • Transform office buildings towards whole-life minimum carbon. • Integrated optimisation of retrofitting plan and operating schedules. • 44%, 74% and 68% decline in whole-life costs, carbon and energy after retrofitting. • 4–51% saving in whole-life carbon emission compared to design optimisation strategy. • 10% saving in whole-life carbon emission compared to operating optimisation strategy. The state-of-the-art retrofitting strategies generally use either passive or active measures to reduce carbon emissions during its operating stage. The coordination among a range of passive and active energy devices is not considered while the concept of whole-life carbon emission minimisation is not introduced. To overcome these three research gaps and to transform existing office buildings toward minimum whole-life carbon emissions, an integrated passive and active retrofitting approach is proposed. Through two inter-related design optimisation and operating optimisation processes, the set of retrofitting options can be identified to achieve overall optimal economic, energy, and environmental performance. The first research gap, lack of simultaneous consideration of various active and passive retrofitting measures, is solved by the whole system simulation of a range of active and passive refurbishment measures. The second research gap, lack of coordination among a range of active energy devices, is solved by iteratively determining the optimal operating schedules of active energy devices with overall retrofitting plan at the design stage. The third research gap, lack of whole-life carbon emission minimisation, is solved by simultaneously minimising both embodied and operating carbon emissions. A real three-floor office building acquiring retrofitting is used to test the effectiveness of this integrated passive and active retrofitting approach. Compared to the building at its current status, there could be 44%, 74% and 68% reduction in lifelong costs, carbon emissions and energy usages if the proposed retrofitting strategy is adopted. Compared to retrofitting the building using the state-of-the-art "design optimisation only" strategy, the proposed retrofitting approach can reduce 5.36%-34.37% whole-life energy consumption and 4.31%-51.10% carbon emissions. Compared to retrofitting the building using the state-of-the-art "operating carbon emission only" strategy, there is 11.92%, 10.55%, and 10.48% reduction in whole-life cost, energy usage and carbon emissions, respectively. Therefore, this paper is innovative in an aspect that minimum whole-life carbon emissions can be reached through integrated design of passive and active retrofitting measures. It can provide building owners, energy engineers and decision-makers with insightful building retrofitting solutions to tackle the energy crisis and climate change problems. This proposed retrofitting approach can also be modified to provide guidance in designing new low-carbon buildings. [ABSTRACT FROM AUTHOR]

• A 5th-generation district heating and cooling system in business district is studied. • Design and operation strategies are based on load analysis and load forecasting. • Load predictions are based on machine learning algorithms and historical loads. • Larger flow rate in water loop than that on source-side makes system more efficient. • Source-network-load-storage collaboration in a district energy system is explored. The fifth-generation heating and cooling system (5GDHC) is a bidirectional low temperature network, which is a good solution for decarbonization and energy-saving in building cooling and heating. Because of its complex configurations, 5GDHC requires specific advanced control strategies for different scenarios. This paper aims to investigate 5GDHC with multiple sources in the business district in hot-summer and cold-winter zone through modelica simulation. The analysis and forecasting of district loads were used to study the design and operation strategies of 5GDHC. A suitable heat pump performance curve was presented for 5GDHC after comparing several heat pumps. And the larger the total flow in the network, the more beneficial it is for users. In this study, 5GDHC for the business district performed best when it adopted the strategy of continuous operation of the ground heat exchanger, nighttime operation of the surface-water coil, and supplemental cooling of the cooling tower upon it is needed, resulting in a 16.6% reduction in CO 2 emissions compared to the strategy that all sources operated continuously. Besides, carbon emission analysis showed the importance of balancing operational cost with carbon emission. This study will help optimize the design and operation of 5GDHC in business district scenarios. [ABSTRACT FROM AUTHOR]

Glued Laminated Bamboo (GluBam) has been innovated under the support of modern industrial technology, and this renewable material can drive the development of building structural system in a fashion of low carbon footprint. From the perspective of carbon emission, energy consumption and cost-based economy, this paper presents a comprehensive life cycle assessment (LCA) of steel-GluBam hybrid truss and virtually designed steel truss for a comparison. A steel-GluBam hybrid truss constructed at the Nanjing Tech University is used to carry on this study. The system boundary (i.e., production phase, transportation phase, construction phase, operation phase and disposal phase) of life cycle are fist determined. The mechanical properties of the truss structure are considered as the functional equivalence. The inventory of construction materials and the elements in each phase in the life cycle is compiled from the SimaPro and the available literature/specification. Based on the inventory analysis, the Monte Carlo method is employed to conduct the uncertainty analysis of carbon emission of the truss. The assessment results show that the life cycle carbon emission, energy consumption and cost of the steel-GluBam hybrid truss are equal to 4572.5 kgCO 2eq , 71.15 GJ and 15626.6 CNY, respectively. The production phase is the largest contributor to the carbon emission, energy consumption and cost, and the following one is the operation phase. Whereas the transportation phase, the construction phase and the disposal phase together contribute to only the small parts of emissions and cost. GluBam has the function of carbon sequestration leading to the reduction of carbon emission and energy consumption in the production phase, and other phases have no advantage on the emissions and cost of GluBam. The 95% confidence interval of life cycle carbon emission based on the Monte Carlo simulation is estimated as [4290,6370] kgCO 2eq for the steel-GluBam hybrid truss. With respect to the whole life cycle, using GluBam to replace the steel pipe in the upper chord pole and the diagonal web pole of the truss has a little larger cost but its environmental impact and energy consumption reduce a lot. The railway transportation of GluBam reduces 36.5 kgCO 2eq carbon emission, 0.68 GJ energy consumption and 83.7 CNY cost in the life cycle with reference to the road transportation. The steel-GluBam hybrid truss optimized based on the functional unit occurs in the case of reducing the cross-section of steel pipe from 42 mm × 4 mm to 32 mm × 2.5 mm. [ABSTRACT FROM AUTHOR]

• The new solution for the façade integrated photovoltaic system, En-ActivETICS was proposed and described in detail, including technical recommendations. • The calibrated numerical model was used to determine hygrothermal performance and identify the most crucial issues of En-ActivETICS. • The positive effect of PCM and diffusion channels was revealed based on a numerical study using calibrated thermoelectrical and hygrothermal models. • The En-ActivETICS was investigated considering local climatic and economic conditions among 38 European countries. • The roadmap 2030 for the En-ActivETICS advancement was developed and presented. The main goal of the European building market transformation regards the reduction of CO 2 emissions and energy demand in the built environment towards net zero carbon buildings. This drives research and building practice to search for economically justified solutions that contribute to achieving these objectives. The work presented in this paper is concerned with the technological and economic context. The original solution of photovoltaic integration with the external thermal insulation composite system named the En-ActivETICS was developed, tested and analysed. The energy potential of the En-ActivETICS across Europe, considering south oriented façade is from 88.3 to 195.8 kWh/(m2⋅a), with the efficiency of solar energy conversion of around 13–14%. The problem of system overheating was solved by applying PCM mortar beside the PV panel, which allowed to keep the PV temperature below 70 °C. The risk of moisture load (from driven rain or water vapour condensation) was avoided by diffusion channels pressed in the mortar. Furthermore, the economic analysis of system implementation in Europe is also promising. Considering the availability of solar energy and electricity prices around Europe the payback time of the En-ActivETICS varies between 12 and 44 years for analysed countries. According to the presented roadmap for the En-ActivETICS advancement a payback period of <10 years is possible with a maximum cost of the system <275 EUR/m2 and electricity price >0.25 EUR/kWh. [ABSTRACT FROM AUTHOR]

• Investigation of EKC within 36 Asian countries. • Analyses of access to electricity's impact on CO2 damage within 36 Asian countries. • Panel Quantiles via Moments methodology following Machado and Silva [85]. • The reducing effect of access to electricity on CO2 damage. • The increasing effect of agricultural activities on CO2 damage. Energy poverty and environmental degradation are two main important issues in the literature of energy and environmental degradation. Energy poverty might affect adversely the health, productivity the environment. In this study, the effects of energy access on the environment are examined. Although there exist some similar studies in the related literature, our study differently (a) uses CO 2 damage data, (b) performs parameter estimations corresponding to different quantiles instead of fixed-parameter estimations. This paper hence aims at analyzing the impacts of access to electricity on CO 2 damage in Asian countries through panel quantile regression estimations by employing the panel data for 36 Asian countries for the period 1997–2017. CO 2 damage is the cost of damage caused by CO 2 emissions stemming from fossil fuel use and the manufacture of cement. While the main interest was to investigate the influence of access to electricity on CO 2 damage, the variables of renewable energy and agricultural activities were also employed as control variables in the quantile estimations. The findings reveal that (i) Environmental Kuznets Curve hypothesis holds in panel data which in turn implies that as economies develop, the CO 2 damage will decrease, (ii) as access to electricity increases, the CO 2 damage will decrease as well, (iii) the renewable energy use also lowers the CO 2 damage and (iv) agricultural activities on the other hand increase the CO 2 damage in panel data. Finally, this paper suggests that the authorities increase access to electricity to diminish indoor and outdoor pollution. [ABSTRACT FROM AUTHOR]

• An exergetic approach and a new understanding of the holistic performance of buildings in terms of sustainability and decarbonization. • Taking into account the exergy mismatches among supply and demand points, leading to avoidable yet unaccounted for CO 2 emissions responsibilities. • The green building definitions must be re-examined and upgraded to an exergy basis. • Buildings may not qualify for zero-energy buildings because high exergy of electric power is destroyed by much lower-exergy heating demand. According to the second law of thermodynamics, all human activities cause exergy destructions, adding to additional root causes for carbon dioxide emissions responsibility. It means that current carbon dioxide concentrations are accurately observed, but the root causes and their potential solutions against global warming fall short of achieving the goals of the Paris agreement by almost 45% in terms of decarbonization efforts, as shown in this paper. This result applies to all activities, including the green facility concept. In this respect, the primary aim of this paper is to raise awareness about the essence of the Second Law of Thermodynamics in expanding the green facility concept to reach more effective and sustainable rating methodologies concerning the climate crisis. A new evaluating and rating model with a set of exergy-based green building metrics that relate additional carbon dioxide emissions to irreversible exergy destructions has been developed. Examples about apparently green buildings according to the First Law of Thermodynamics are given by showing that these buildings are not green due to additional carbon dioxide emissions responsibility due to exergy destructions. An airport terminal building case is elaborated. It has been shown that although part of the electricity comes from a third-party wind energy provider, it ends up with carbon dioxide emissions responsibility because it is not entirely used in exergy-rational demand points and compares less favorably with an on-site cogeneration system using natural gas by about 30% more emissions responsibility. The results and derivations of new metrics are discussed, which shed light on adding new criteria to existing green building certification programs. [ABSTRACT FROM AUTHOR]

Abstract In the UK, housing has been identified as a major sector for contributing to the 80% reduction in carbon emissions over the 1990 baseline by 2050, required by the Climate Change Act 2008. However, pre-1919 housing stock is the least energy efficient and consequently poses challenges to meeting this target. Using a mixed methods approach, the current study demonstrates that, in actuality, there is a significant potential for reducing emissions among this sub-sector of housing, and that the major barriers to energy efficiency retrofits concern a lack of funding, the payback period for the investment, disruption to home life and finding a trustworthy and skilled installer. Moreover, this study finds that homeowners are motivated primarily by the desire to improve home comfort and aesthetics along with a reduction in energy bills rather than in reducing carbon emissions. The paper concludes with recommendations for improving the viability of retrofitting pre-1919 homes through enhanced financial resources, policy support and the promotion of social and economic benefits. [ABSTRACT FROM AUTHOR]

[Display omitted] The school building sector has a pivotal role to play in the transition to a low carbon UK economy. School buildings are responsible for 15% of the country's public sector carbon emissions, with space heating currently making up the largest proportion of energy use and associated costs in schools. Children spend a large part of their waking life in school buildings. There is substantial evidence that poor indoor air quality and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and school staff. Maintaining high indoor environmental quality whilst reducing energy demand and carbon emissions in schools is challenging due to the unique operational characteristics of school environments, e.g. high and intermittent occupancy densities or changes in occupancy patterns throughout the year. Furthermore, existing data show that 81% of the school building stock in England was constructed before 1976. Challenges facing the ageing school building stock may be exacerbated in the context of ongoing and future climate change. In recent decades, building stock modelling has been widely used to quantify and evaluate the current and future energy and indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. Building stock models commonly use building archetypes, which aim to represent the diversity of building stocks through frequently occurring building typologies. The aim of this paper is to introduce the Data dRiven Engine for Archetype Models of Schools (DREAMS), a novel, data-driven, archetype-based school building stock modelling framework. DREAMS enables the detailed representation of the school building stock in England through the statistical analysis of two large scale and highly detailed databases provided by the UK Government: (i) the Property Data Survey Programme (PDSP) from the Department for Education (DfE), and (ii) Display Energy Certificates (DEC). In this paper, the development of 168 building archetypes representing 9,551 primary schools in England is presented. The energy consumption of the English primary school building stock was modelled for a typical year under the current climate using the widely tested and applied building performance software EnergyPlus. For the purposes of modelling validation, the DREAMS space heating demand predictions were compared against average measured energy consumption of the schools that were represented by each archetype. It was demonstrated that the simulated fossil-thermal energy consumption of a typical primary school in England was only 7% higher than measured energy consumption (139 kWh/m2/y simulated, compared to 130 kWh/m2/y measured). The building stock model performs better at predicting the energy performance of naturally ventilated buildings, which constitute 97% of the stock, than that of mechanically ventilated ones. The framework has also shown capabilities in predicting energy consumption on a more localised scale. The London primary school building stock was examined as a case study. School building stock modelling frameworks such as DREAMS can be powerful tools that aid decision-makers to quantify and evaluate the impact of a wide range of building stock-level policies, energy efficiency interventions and climate change scenarios on school energy and indoor environmental performance. [ABSTRACT FROM AUTHOR]

• A coupled scheme to integrate urban building energy model and physical-based BIPV potential estimation approach. • Demonstrate carbon neutrality assessment workflow for commercial building stock at multiple scales. • Spatiotemporal assessment of energy use intensity, reduction potential and peak loads of commercial building stock. • 84% reduction potential with the simultaneous implementation of all the measures. • Decarbonization potential of BIPV is less than efficiency measures in commercial building stock. The transitional pathway to carbon neutrality in commercial building stock requires improvement of energy efficiency, use of renewable sources and implementation of non-technological mitigation strategies. However, several methods have been developed to assess the carbon neutrality of commercial building stock but they mainly lack the ability of spatiotemporal quantification of energy demand and decarbonization potential which hinders the evaluation of carbon neutrality at multiple scales. This paper presents a GIS-synthetic hybrid urban building energy model (UBEM) coupled with a physical-based approach of building integrated photovoltaics (BIPV) potential estimation to incorporate a building-level energy model at a large scale that could further evaluate the feasibility of carbon neutrality of commercial building stock at a multi-scale level. As a case study, the proposed coupled scheme is applied to the commercial building stock of Tokyo to evaluate the cofound influence of active and passive design measures, and BIPV on the overall decarbonization potential. The results indicate the following findings: the annual CO 2 emissions can be reduced by 84% with the simultaneous implementation of all the measures; focusing on passive design measures is not enough to achieve carbon neutrality in commercial buildings that only contribute 10% of the overall reduction potential; 16% to 40% of the decarbonization potential is contributed by BIPV that is less than efficiency measures; and the scale-bounded comparative analysis shows that total BIPV potential changes in the order of magnitude of 29 to 54 with the variation of scale (with reference to district scale) and 4–16% more self-sufficiency observed at the building-by-building level in comparison to district and city scales. This demonstrates that this coupled approach can provide a purpose-driven perspective for the energy transition of commercial building stock at multiple scales with reduced computational time. Overall, this analysis provides a multi-level perspective to energy modelers and policymakers on how to achieve carbon neutrality in the commercial building stock. [ABSTRACT FROM AUTHOR]

Energy studies of buildings are becoming more widespread as stakeholders strive to improve energy efficiency and reduce carbon emissions. As a result, there is an increased need for novel numerical techniques to automatically calibrate building energy models (BEMs) for these energy studies. In this paper, a new automated building calibration methodology was developed, which uses a surrogate (i.e. , meta) multilayer perceptron artificial neural network (ANN) to infer unknown building parameters. Typically, in the field of BEM calibration, surrogate models are used as a time-saving technique. Instead of running the building simulation software during each iteration of an optimization search, a surrogate model can approximate the output of the BEM very quickly, leading to much faster optimization of the unknown building parameters. However, we show that, once trained, the surrogate model itself can be used to find the unknown building parameters. Since the surrogate model is differentiable, gradient descent can be used to find the building parameters that minimize the error between true and predicted metered energy consumption. Previous surrogate modeling approaches for calibrating BEMs map only the unknown building parameters to the BEM's output. As a result, they are blind to the effects of other crucial variables like weather and the building's schedules. On the other hand, our surrogate ANN model accounts for these other predictors of energy consumption. With this advantage, our method was able to outperform a powerful black box optimizer when finding 14 unknown building parameter values in a controlled case study with hourly energy data. In a real metered data case study, our ANN method and the black box optimizer performed similarly on average, but our method had less variance in performance across trials. [ABSTRACT FROM AUTHOR]

Life cycle assessment (LCA) is considered to be the most systematic methodology that is widely used in the area of energy analysis. However, embodied energy (EE) and carbon (EC) analysis requires significant time and effort to ensure the reliability of the LCA results. Therefore, a more comprehensive model of conducting the energy analysis is required to provide more realistic EE and EC analysis in turn. Hybrid LCA has been identified as the best model in improving the completeness of EE and EC inventory data. However, such a benefit was not empirically verified extensively, especially in the Malaysian construction industry. This paper demonstrates an extended application of hybrid LCA to Malaysian building design systems, and further investigates the completeness of the model. Finally, the potential for EE and EC reduction through the allocation of low EE and EC intensities of alternative materials, products or components has been evaluated. The results revealed that the hybrid LCA improved the completeness of the EE and EC inventory data compared with other models. By using low EE and EC intensity materials, products or components, a total EE and EC reduction of 43% and 41%, respectively was achieved. The results showed that the proposed methodology can assist designers practically during the early stage of the design process in the Malaysian construction industry. [ABSTRACT FROM AUTHOR]

Energy retrofit technologies can significantly reduce global energy requirements and carbon emissions and support policy makers achieve net zero targets. The installation and implementation of these technologies is mostly quite straightforward, however the assessment of their benefits and impacts across the technical, economic, and environmental domains can be very complex and often requires a high degree of stakeholder engagement. The purpose of this paper is to propose a clear and easy-to-follow methodological framework for conducting a techno-economic analysis of energy system retrofit technologies to help reduce this complexity. The proposed framework involves four main stages that involve identifying stakeholders and defining key performance indicators (KPIs), fact and knowledge generation and alignment, decision-making support and finally reviewing and refining the outputs. Two case studies, carried out in the context of the Horizon 2020 Integrated Smart GRID Cross-Functional Solutions for Optimized Synergetic Energy Distribution, Utilization Storage technologies (inteGRIDy) project, were considered to illustrate application of the framework. Associated relevant technical and economic evaluation of performance parameters carried out in accordance with the proposed framework demonstrated that implementation of retrofit technology in these case studies significantly impacted identified stakeholder relevant KPIs, including reduces total energy consumption, peak load, and carbon footprint. Likewise, they improved wider grid adaptability and energy security. The cost-benefit analysis also identified several stakeholder benefits, such as revenues from demand response operations, cost reductions due to local generation, revenues from energy export, and decreased expenses related to reduced carbon emissions. The article concludes that the proposed methodological framework can assist in focusing efforts related to the technical and economic evaluation of energy retrofit technologies onto meaningful indicators which have relevant real-world interpretation for key stakeholders. Overall, it is suggested that the proposed framework can be used as an additional tool to evaluate the impacts and benefits of energy retrofit technologies in a more meaningful way, giving policy makers better insights into deployment and scale-up of retrofit technologies to achieve net zero targets. [ABSTRACT FROM AUTHOR]

Emission reduction in buildings is essential to combat climate change. However, current strategies failed to balance development and emissions reduction goals. This paper selects a public building in China and simulates its initial energy consumption and carbon emissions. Then it establishes a multi-objective optimization model to explore cost-effective and emission-reduction strategies, considering photovoltaic and ground-source-heat-pump (GSHP) systems. Finally, NSGA-Ⅱ is used to solve, and sensitivity analysis is carried out. Results show that: (1) Energy consumed by the air conditioning system is the largest in January for heating and in July for cooling, validating the accuracy of the energy simulation model. (2) Economic efficiency and emission reduction effect are better when photovoltaic and GSHP systems are implemented simultaneously. (3) Electricity price, initial investment cost, annual solar peak hours, and the proportion of shallow geothermal energy significantly impact carbon emissions and cost. (4) The photovoltaic and power grid substitution ratio will exceed 8% every five years, and all substitutions will be completed in 2050. After adopting the GSHP system, the complete replacement will be advanced to 2045. Setting subsidies significantly shortens the payback period of investment and ensures firms' economic benefits. In summary, using photovoltaic and shallow geothermal energy is conducive to reducing emissions and saving costs in the long term. [ABSTRACT FROM AUTHOR]

School buildings have a great potential for carbon emission reduction since their annual emission is about 72 million metric tons. Currently, more than 30 % of school buildings were built before 1960 and are underperforming. To effectively reduce carbon emissions via school building retrofits, it is critical for policymakers to understand the carbon intensity reduction potential of retrofitting school buildings in different regions. Hence, this study develops a method to comprehensively assess the long-term carbon intensity reduction potential of aggregated commercial buildings on a county-by-county basis in the continental U.S. We apply this method to the K-12 school buildings including primary and secondary school buildings. This paper predicts the carbon intensity reduction potential of K-12 school buildings with eight building retrofit measures from 2022 to 2050 in the continental U.S. The results reveal several interesting findings: (1) In the approximately 3,000 counties of the U.S. from 2022 to 2050, the carbon intensity reduction potential of retrofitting K-12 school buildings in each county ranges from 0.41 kg/m2 to 40.00 kg/m2. (2) Even in the same climate zone, the trends of carbon intensity reduction potential from 2022 to 2050 are different depending on their electricity sources. For example, in a hot and humid climate zone, the carbon intensity reduction potential in Florida will decrease from 2044 to 2048. However, in Mississippi, the carbon intensity reduction potential from 2044 to 2046 will increase due to the termination of the nuclear energy usage. (3) Generally, reducing lighting power density leads to more carbon intensity reduction in most states, but it might not be applicable for states with high clean energy penetration, such as Washington. [ABSTRACT FROM AUTHOR]

This paper presents a micro energy grid to a community and estimates the effect of the urban micro energy grid on the reduction of energy demand and carbon emissions. Micro energy grid enables to share various energy sources generated at local plants and renewable sources for multiple buildings with different energy profiles. A community in China was selected for the implementation of the micro energy grid. A number of key performance indicators(KPIs) were developed to act as a framework for the overall community micro energy grid design. Site-wide strategies were selected to meet the KPIs and minimize the capital cost of the project. Financial analysis on the community micro energy grid model was performed and different scenarios were set up in order to find the optimalconditions for the government incentive, the investment discount rate, system capacity and development (demand) size of the project. It was found that a community in China adopting micro energy grid can achieve 26% carbon emissions reduction and 25% energy consumption savings compared to the conventional building energy systems and its payback period is 51 years with 10% discount rate and a government incentive of $0.052 per kWh. [ABSTRACT FROM AUTHOR]

• We present soft linking of energy system capacity expansion models. • Zero emission neighbourhoods make European decarbonization more cost-efficient. • Neighbourhood energy systems replace investments in nuclear, wind, and fossil gas. • Politically decreasing EU ETS emission caps earlier could avoid CO 2 price spikes. Climate policy is transforming the energy system and the building sector. Since these sectors overlap, we need to understand how the short-term operational link between them impact their long-term development subject to overlapping climate policies. This paper investigates how the integrated development of the European heat and electricity system is influenced by net-zero emission neighbourhoods that compensate own carbon emissions with local renewable energy. The study is made in the context of EUs emission trading system. In our approach, we soft-link two mathematical programming models to couple energy transition policies at the European level with the neighbourhood scale. Results suggest that zero emission neighbourhoods make European decarbonisation more cost-efficient. When low carbon energy technologies in neighbourhoods become competitive, investments in large-scale technologies are reduced on the European level, including nuclear and fossil gas power and heating. Thus, early policy support to neighbourhood technologies could prevent stranded assets later in the transition. Further, results imply that more stringent emission caps earlier could help avoiding CO 2 allowance price spikes later. [ABSTRACT FROM AUTHOR]

• Implementation and benchmarking of five advanced control methods. • Comparison of black-, gray-, and white-box MPC with RL and approximate MPC. • Introduction of qualitative KPIs to assess the applicability. • Application in a one-year simulation to evaluate adaptability. Advanced building control strategies like model predictive control and reinforcement learning can consider forecasts for weather, occupancy, and energy prices. Combined with system and domain knowledge, this makes them a promising approach to reduce buildings' energy consumption and CO 2 emissions. For this reason, model predictive control and reinforcement learning have recently gained more popularity in the scientific literature. Nevertheless, publications often lack comparability among different control algorithms. The studies in the literature mainly focus on the comparison of an advanced algorithm with a conventional alternative. At the same time, use cases and key performance indicators vary strongly. This paper extensively evaluates six advanced control algorithms based on quantitative and qualitative key performance indicators. The considered control algorithms are a state-of-the-art model-free reinforcement learning algorithm (Soft-Actor-Critic), three model predictive controllers based on white-box, gray-box, and black-box modeling, approximate model predictive control, and a well-designed rule-based controller for fair benchmarking. The controllers are applied to an exemplary multi–input–multi–output building energy system and evaluated using a one-year simulation to cover seasonal effects. The considered building energy system is an office room supplied with heat and cold by an air handling unit and a concrete core activation. We consider the violation of air temperature constraints as thermal discomfort, the yearly energy consumption, and the computational effort as quantitative key performance indicators. Compared to the well-tuned rule-based controller, all advanced controllers decrease thermal discomfort. The black-box model predictive controller achieves the highest energy savings with 8.4 %, followed by the white-box model predictive controller with 7.4 % and the gray-box controller with 7.2 %. The reinforcement learning algorithm reduces energy consumption by 7.1 % and the approximate model predictive controller by 4.8 %. Next to these quantitative key performance indicators, we introduce qualitative criteria like adaptability, interpretability, and required know-how. Furthermore, we discuss the shortcomings and potential improvements of each controller. [ABSTRACT FROM AUTHOR]

• An interactive framework of outdoor paving and indoor ventilated atrium are proposed. • The balance of thermal comfort and carbon abatement is considered. • Outdoor environment and indoor atrium have various effects on comfort and emission. • Water pavement and 135° atrium skylight direction can reduce 14% emissions. Large-scale public buildings usually use active means to improve indoor thermal comfort, such as cooling and heating by centralized air conditioning, which can increase building carbon emissions. It is urgent to balance the comfort and carbon abatement. Passive means have the potential to reduce building carbon emissions, such as the atrium. However, the effect of atrium on comfort and carbon abatement is influenced by outdoor environment, which is ignored in the traditional research. Therefore, this paper proposes an interactive design framework for outdoor environmental paving (O-EP) and indoor ventilated atrium skylight orientation (I-VA). Taking a large-scale public building in Xinghua city as an example, three common outdoor pavement forms (hard paving, shrub greenery, water bodies) and five building atrium skylight orientations (0°, 45°, 90°, 135°, 180°) are selected. Carbon abatement rate and adaptive predicted mean vote (aPMV) are used as evaluation indicators for carbon abatement and comfort respectively. The couple of O-EP and I-VA on building carbon abatement and comfort is obtained by analysis of correlation and ANOVA. Numerical simulations are validated by experimental data. The results show that (1) different combinations vary significantly, annual carbon abatement rates and comfort are 17.5% and 15% higher for the combination of water bodies of O-EP and 135° of I-VA than for the worst; (2) correlation analysis shows that carbon abatement rate is correlated with O-EP at the 0.01 level and not with I-VA; (3) in the warmer seasons, comfort is correlated with O-EP at the 0.01 level and not with I-VA; in the cooler seasons, comfort is correlated with I-VA at the 0.01 level and not with O-EP. This study can provide an important reference for design strategies for low carbon development and green buildings. [ABSTRACT FROM AUTHOR]

• Building envelope-enhanced phase change material is studied in a severe hot climate. • Average indoor temperature and thermal load levelling are reduced by 2 °C and 8.71 %. • CO 2 emissions by 1.35 kg/day and electricity cost by 80.64 IQD/day.m3 could be saved. • Phase change material is more beneficial in the roof than walls. Phase change materials (PCMs)-enhanced building envelope has received much attention in recent years as an effective solution to enhance building thermal performance. Nevertheless, minimal experimental studies considering PCM influential aspects in full envelope arrangement are found in the literature against many numerical studies. This paper aims to quantify the indoor temperature improvement and energy-saving when PCM is passively-incorporated into a building envelope under non-ventilated conditions. The average indoor temperature reduction (AITR), thermal load levelling reduction (TLLR), average heat gain reduction (AHGR) and associated CO 2 emissions saving (CO 2 ES) and energy cost saving (ECS) are presented and discussed for two test rooms, with/without PCM, constructed and examined in extremely hot summer days. The outcomes exhibited PCM effectiveness to stabilise the indoor temperature, showing an AITR of 2 °C during the day and a maximum TLLR of 8.71 %. Besides, AHGR by up to 56 W, CO 2 ES by 1.35 kg/day and ECS of 80.64 Iraqi dinar (IQD)/day are attained. The study concluded that the PCM is more effective in the roof than walls, and the PCM amount should vary in walls considering their orientation and peak outdoor conditions. [ABSTRACT FROM AUTHOR]

In the tourism industry, hotels and homestay facilities account for considerable amounts of energy consumption and CO 2 emissions. Unlike other types of buildings, occupancy has significant fluctuations over time, while mostly being ignored or using a simple assumption based on energy use intensity or setting the occupancy levels. Due to the lack of occupancy rate information, great uncertainties exist in hotel operations, which leads to erroneous estimates of energy consumption in existing hotel buildings. This paper examines hotel operation practices in China with real occupancy rate data which is critical for reducing the uncertainty of estimating energy consumption patterns. Specifically, this study proposes a two-stage comprehensive and quantitative performance assessment approach for the homestay hotel building considering the system's energy and economic performance simultaneously. Regarding energy performance, there are two key facets to consider: renewable energy penetration and grid impact performance. Additionally, the economic performance (annual income and extra annual investment) of various energy portfolios is evaluated using break-even analysis. The impacts of large fluctuation in occupancy rate on electrical loads are considered and assessed in typical homestay hotels. The proposed assessment approach can comprehensively quantify the impacts of the photovoltaics (PV) areas and battery capacities on the system performance in terms of energy and economics. According to the results of the occupancy-based assessment, the ideal PV area and battery capacity are 400 m2 and 16 kWh, respectively, as opposed to the optimal energy portfolios (PV area 600 m2 and battery capacity 24 kWh) determined from conventional assessment results. [ABSTRACT FROM AUTHOR]

• Embodied and operational carbon tradeoffs in building envelopes are studied. • Envelope variables include wall assemblies, WWRs, glazing and shading. • Energy decarbonization models are used to determine the 30-year operational carbon. • Results show the importance of a total carbon approach to envelope design. • Over or under insulation can result in waste of 10–150 kgCO 2 e/m2. The building envelope has a substantial influence on a building's life cycle operational and embodied carbon emissions. Window-to-wall ratios, wall assemblies, shading and glazing types, have been shown to have a significant impact on total emissions. This paper provides building designers, owners, and policy makers with actionable guidance and a prioritization framework for establishing co-optimized lifecycle carbon performance of facade assembly components in a broad spectrum of climate contexts and energy carbon intensities. A large parametric study of building envelopes is conducted using building performance simulation and cradle-to-gate embodied carbon calculations in 6 US cities. The authors derive the total carbon emissions optimization for commercial office and residential space types using standard code-reference models and open-source lifecycle data. Comparisons between optimal total carbon solutions and (i) optimal operational carbon and (ii) minimum required assemblies, show the impact of under and over investing in envelope-related efficiency measures for each climate. Results show how the relationship between embodied and operational carbon is highly localized, that optimal design variables can vary significantly. In low carbon intensity energy grids, over investment in envelope embodied carbon can exceed as 10 kgCO 2 e/m2, while under investment in high carbon intensity grids can be higher than 150 kgCO 2 e/m2. [ABSTRACT FROM AUTHOR]

• A model-free low-carbon management strategy for home energy is proposed. • The proposed strategy accelerates the dynamic operation through deep Q network. • The strategy can achieve the unified effect of economy, emission and satisfaction. • The model adapts to random environment guaranteeing robustness and stability. This paper presents a model-free dynamic optimal management strategy for a low-carbon home energy management system (HEMS) based on deep reinforcement learning (DRL). The method can ideally handle the uncertainties and dynamics of renewable energy and demand-side load. Firstly, the load model is established by a deep Q network (DQN) algorithm with the advantage of ignoring traditional forecasting steps on stochastic environments such as renewable energy generation, load demand, price, etc. Then multi-agents are established for dynamic management based on the DRL. Through "dynamic acquisition, dynamic decision" mechanism, the proposed model-free strategy achieves real-time energy management that can adaptively respond to stochastic environments. Secondly, considering the constraints of system carbon emissions and carbon trading, the proposed strategy can minimize the energy consumption cost, carbon trading cost, and user satisfaction penalties. Ultimately, the effectiveness of the proposed strategy is verified through case studies. Experimental results demonstrate that the strategy can significantly reduce the overall cost, including a 36.7% reduction in carbon trading. At the same time, user satisfaction penalties are reduced by 50.2%. Further, the agent hyperparameter could also be adjusted to capture the trade-off between cost savings and satisfaction penalties. And compared with the traditional forecast-based management strategy, it overcomes the problem of uncertainties and avoids forecasting errors to better accommodate the stochastic environment. [ABSTRACT FROM AUTHOR]

Building load forecasting is critical for energy saving and carbon emission reduction, as building loads account for a rising percentage of energy consumption. Existing load forecasting methods only target a single building and do not consider the spatial characteristics of different building loads in an architectural complex, making it impossible to effectively forecast loads for all buildings in an architectural complex simultaneously. In this paper, considering the spatial correlation among building loads in an architectural complex, a novel short-term load forecasting method is proposed to improve the load forecasting accuracy for the architectural complex. First, Pearson correlation analysis is carried out to determine the key influencing factors of load, which are treated as multi-information. Then, to realize the load forecasting of all buildings in an architectural complex at the same time, a multi-information fusion model combined with a graph convolutional network and a long-short term memory network is proposed, and spatio-temporal attention modules are included to extract the dynamic spatio-temporal correlations of load. The performance of the proposed model is evaluated using actual load data from a public university in Beijing. When compared to other current methods, the experimental results show that the proposed model not only achieves the best results for architectural complex load forecasting (the largest MAPE is only 6.86%, the smallest R2 and Accuracy reach 0.87 and 0.85, respectively), but also maintains forecasting stability to some extent over a longer forecast period. The proposed method is a meaningful step towards achieving fast and accurate architectural complex load forecasting. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in the world, China's carbon emissions and the time of carbon peak have always been a hot topic at home and abroad. However, in previous studies, the predicted period of carbon emissions is relatively short. In order to obtain the predicted data of China's carbon emission and the specific time of carbon peak, the carbon emissions in 30 provinces of China are predicted and analyzed. For 16 provinces with increasing carbon emissions, a novel grey model is proposed to predict the limit of growth data. This model improves the structure of the traditional grey prediction model based on the Gompertz's law and the differential information principle. Its predicted period is longer than that of the traditional grey model. The predicted trend is more in line with the law of natural development. Moreover, this model can predict the limits of a variety of growth data, such as the emissions of various air pollutants. After the prediction, the carbon emissions in these 16 provinces from 2020 to 2032 are obtained. According to the forecast results, eight of the 16 provinces will reach the carbon peak by 2030, namely Jiangsu, Guangdong, Shanxi, Liaoning, Hubei, Guizhou, Guangxi and Jiangxi. The five provinces namely Shandong, Hebei, Anhui, Shaanxi and Fujian will reach the carbon peak in 2031 or 2032. The three provinces namely Inner Mongolia, Xinjiang and Ningxia will not reach their carbon peak by 2032. Based on the above forecasts and analysis, it can be inferred that China will reach the carbon peak in 2032, with emissions of 11.8 billion tons. Scientific predicted data will play a guiding role in carbon emission control. At the end of the paper, the current situations of carbon emissions in 30 provinces are analyzed and suggestions on carbon emission control are put forward. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Simulation of residential building energy supply with heat pump or hydrogen systems. • 2050: Hydrogen economically-viable if H 2 -/Elec.-price is less than 34–61 % per kWh. • For conservative price predictions: Electric heat pumps are most economical solution. • Energy carrier switch for single-family houses: H 2 -/Elec.-price below 44 % per kWh. • Energy carrier switch for multi-family houses: H 2 -/Elec.-price below 58 % per kWh. • Fuel cells are emerging as an economically-viable option for multi-family houses. Fossil-fueled heating in the building sector is responsible for 16 % of Germany's total CO 2 emissions. Options for the climate-neutral heating of buildings include renewable electricity or renewable hydrogen. In this paper, we conduct a bottom-up study to investigate the role of hydrogen in the climate-neutral energy supply of ten selected residential buildings in comparison to electricity-based systems. Based on a demand simulation and linear optimization of the supply system, sensitivity analyses identify the threshold values of the hydrogen price for the use of hydrogen technologies (hydrogen boilers or fuel cells) in building energy systems and make the quantities of hydrogen consumed visible. The results specify the first installations of hydrogen-operated fuel cells in multi-family houses if the hydrogen price reaches 0.17 €/kWh H2 in 2050 at an electricity price of 0.31 €/kWh el. Generally, for different building types and electricity supply prices, it indicates that the use of hydrogen becomes economically-viable if the price of hydrogen supply is in the range of 34–61 % of the price of the electricity supply per kWh and below. For the case of green hydrogen obtained using renewable electricity, it is highly questionable whether hydrogen supply will be that much cheaper than direct electricity supply, making its economical use in buildings uncertain. [ABSTRACT FROM AUTHOR]

[Display omitted] • The study of old and new building development in energy and environment scope. • The trade-offs between carbon emission and energy saving in old and new architecture. • The study of virgin material consumption growth in the architecture development. • Surveying the sustainable architecture development towards the Circular Economy. • Extend the potential of Circular Economy toward Regenerative design development. Nowadays, the construction industry has turned to the consumption of large amounts of natural resources in line with global population growth, which has led to the shortage of resources, and consequently increases in the construction debris; therefore, the present article has studied the positive and negative points of the architectural development process. The results have indicated that being compared to the former architecture; the development of architecture has reduced energy consumption by 78%. Hence, the scarcity of virgin resources and consequently the increase of environmental effects such as Global Warming Potential (GWP) have been measured based on the Life Cycle Assessment (LCA). It has been illustrated that the architecture trend has increased the environmental impact of new materials by 5 times the old ones in GWP. To optimize and increase resource productivity, a review of buildings by the principles of Circular Economy (CE) has shown that 10% of old house materials and 3% of new house materials could be returned to the chain based on the CE concept. Other than reducing the GWP emissions of the construction industry and the development of zero waste systems, this paper, by replacing conventional materials with biocompatible, has been able to increase the Building Circularity (BC) by 27% in the old house and 3% in the new one, which emphasizes a regenerative approach. As a result, with this solution, more integrity would be observed between the construction environment and nature, both in the development of past architecture and in the improvement of future architecture. [ABSTRACT FROM AUTHOR]

• Residential sector accounts for a quarter of consumption and a fifth of CO 2 emissions. • HVAC accounts for a third of residential consumption, equivalent to 8% of final energy. • Collecting and reporting information is crucial to target residential energy policies. • Retrofitting of residential stock and adopting conservation behaviours are mandatory. • Residential electrification is far away and needs to be accompanied by the decarbonisation of the electricity sector. The residential sector is a major contributor to climate change, accounting for almost a quarter of global energy consumption and a fifth of CO 2 emissions in 2019. Since 2000, residential consumption has grown at a sustained rate of 1%/year, driven by the development of emerging economies, despite stagnation in developed countries. The increasing demand for living space, energy services and comfort levels seems difficult to curb, especially in the developing world on its fair attempt to reduce inequality. To understand these trends, this paper analyses the trajectories of key indicators of activity and efficiency in this sector, for emerging and developed regions, as well as for major consuming nations, mainly China, United States, European Union, Russia, India, Japan and Brazil. Despite data limitations, meaningful cross-country comparisons are presented for fuel mixes, energy services and dwelling types. Heating, ventilation and air conditioning (HVAC) systems account for a third of residential consumption and will grow rapidly as increasing wealth in emerging economies allows for satisfying the thermal comfort demand. Economic development will naturally increase housing size and equipment level and reduce household size, and could close the per capita consumption gap between developing and developed regions. Efficiency improvements could reduce the energy use intensity to around 10 koe/m2 but will not be enough to curb residential consumption. International cooperation, policy support and funding are essential to accelerate development and efficiency gains in developing countries without compromising environmental targets. In the meantime, politicians should focus on decarbonising the energy mix and promoting energy efficiency, while citizens focus on energy conservation to avoid irreversible environmental damage. [ABSTRACT FROM AUTHOR]

[Display omitted] • The influencing factors on energy efficiency of data center are reviewed. • Energy efficiency metrics are classified according to different priorities. • Appropriate metrics should be selected according to data center function for optimization. • Metrics are analyzed by hierarchy according to the degree of sustainable development. • Challenges and gaps are highlighted and suggestions are given for future works. The rapid development of the Internet requires data center infrastructures to be extended to a large scale with a higher power capacity and a reduction in energy consumption and carbon emissions. It is of great significance for this application to reduce energy consumption, capital cost and carbon emissions while ensuring a safe and reliable data center operation. Evaluation metrics have been considered an effective method to assess the energy efficiency of data centers and have been widely used in various data centers for many years. This work reviews the latest progress of data center evaluation metrics development in recent 20 years. Energy efficiency metrics are summarized based on energy conservation, eco-design and data center security, with the advantages and disadvantages and their correlations discussed. The applicability of each metric is analyzed. The influencing factors of energy efficiency of data centers discussed include site selection, IT equipment, power supply and distribution systems, cooling systems, building structure, and temperature control. The results show that the current evaluation metrics are valuable for the assessment of energy saving of data centers. However, more comprehensive and multi-scale evaluation metrics combining energy consumption, eco-design and data center security are needed to accelerate the progress towards carbon neutrality. In this paper, the hierarchy analysis of metrics is carried out according to sustainability, and metrics in line with sustainable development should be used preferentially. [ABSTRACT FROM AUTHOR]

Synopsis of the hypotheses: H 1 A : Institutional quality Granger-causes foreign aid. H 2 A : Institutional quality Granger-causes CO 2 emissions. H 3 A : CO 2 emissions Granger-cause foreign aid. Superscript B (in place of A) indicates Granger causality in reverse order. [Display omitted] • Considers temporal links among foreign aid, CO 2 emissions and institutional quality. • Panel Granger causality test establishes results for poorer countries. • Results are different in the short run compared to the long run. • A myriad of complex and non-uniform dynamics exists in the short run. • Institutional quality and CO 2 emissions uniformly source aid in the long run. It is widely acknowledged that poorer countries experience the brunt of deleterious impacts of CO 2 emissions and climate change. Deteriorating environmental quality has a negative spillover impact on the health and wellbeing of the economy and individuals in these countries. In this study, we examine whether there are temporal (Granger) causal links between foreign aid (which many developing countries depend on), CO 2 emissions, and the quality of the institutions of governance in poorer countries. We use the vector error-correction model (VECM) to study the links. The study was conducted for low-income and lower middle-income countries from 2005 to 2019. Results indicate that there exist complex and varied endogenous dynamics amongst all three variables in the short run. Over the longer period, the results are more uniform: the level of institutional quality and the level of CO 2 emissions both Granger-cause foreign aid. Based on the results, the paper outlines key co-development policies on foreign aid, institutional reforms, and CO 2 emissions to transition poorer countries onto a path of enhanced environmental development (lower CO 2 emission), as envisioned in the United Nations Climate Change Conference in Glasgow (COP26) [United Nations, 2021]. [ABSTRACT FROM AUTHOR]

This paper presents the energy and water use of 4 social houses certified to the Code for Sustainable Homes Level 5 in Gainsborough, UK. The houses were monitored over 2 years, from July 2012 to September 2014. As the houses have the same construction and energy efficiency characteristics, the study offered a unique opportunity to investigate the effects of occupant behaviour on the dwellings performance. Electricity, gas and water consumptions were measured through data logging and meter readings. Surveys and interviews were conducted throughout to gain insights into tenants understanding and interactions with low energy features in their homes. Significant differences were observed in the amount of energy and water used. The annual space heating consumptions differentiated by a factor of 2.2 per square metre of floor area. Hot water heating demands varied by a factor of 3.5 per square metre of floor area or by 2.5 per person per year. Mains water consumptions varied by a factor of 2.2 litres per person per day in 2013. [ABSTRACT FROM AUTHOR]

Using energy conservation measures (ECMs) for building retrofit can significantly reduce building operational carbon emissions (BOCEs) and contribute to Chinese carbon neutrality by 2060. This paper involves 11 feasible ECMs for commercial buildings in hot-summer and cold-winter zone, China, and proposes a quick assessment approach to BOCEs reduction. Prototypical models are simulated for ECMs using EnergyPlus and the emission intensity is corrected by the building shape factor and window-to-wall ratio. Based on pre-simulated results, effects on reducing emissions of individual measures and packages of them are studied to develop regression models in SPSS. The results show that decreasing the U-factor of external walls, lighting power density (LPD), or shading coefficient can reduce BOCEs linearly. BOCEs are most sensitive to LPD and using daylighting control can reduce emissions by 5–15%. In addition, increasing the boilers' efficiency reduces emissions linearly, while performance improvement of chillers or heat pumps reduces emissions logarithmically. Furthermore, utilizing variable speed pumps, heat recovery ventilation, and air-side economizers can reduce emissions by 3.8%, 6.6%, and 15.2%, respectively. Finally, significant interactions exist among measures of enhancing glazing U-factor, adding external shading, using energy-saving lamps, and improving cooling/heating system efficiencies. The developed regression models are validated in a retrofit case in Shanghai. Through assessment, the case can reduce BOCEs by 15.9 kgCO 2 /m2, with a reduction rate of 20.8%. Compared with recorded data, the relative error of assessing emission reduction is −13.0% and that of assessing reduction rate is 0.5%, which are acceptable in the decision-making stage of retrofit strategies. [ABSTRACT FROM AUTHOR]

• The outdoor environment indexes are integrated by simulation and empirical method. • Quantitatively study the interaction between green space and water bodies. • The proper layout of landscape planning can reduce the building carbon emissions. The rapid urban construction has made urban residential buildings become the main source of greenhouse gas emissions. So far, the existing studies on the impact of urban micro-climate on building energy carbon emissions have shown that green space (GS) and water bodies (WB) play positive roles in regulating outdoor thermal environment and reducing building energy consumption. Accordingly, this paper quantitatively explores the influence of the interaction between GS and WB on reducing building carbon emissions. First, the building's micro-climate is simulated by Computational Fluid Dynamics (CFD) to obtain outdoor thermal environment indexes, which are used as inputting data to calculate carbon emissions by software HDY-SMAD. Then, we utilize Geographic Information System (GIS) and Remote Sensing (RS) techniques to explore the natural surroundings of buildings, such as GS and WB distribution within the administrative scope of Dujiangyan. Next, the linear regression method is applied to analyze the relationship between GS, WB, and residential building carbon emissions, in which the residential carbon emissions data is obtained by social survey. Finally, the simulation results are verified by empirical research method. The findings demonstrate that the GS and WB have area, accessibility and seasonal differences in regulating local thermal environment and reducing building carbon emissions, and the overall regulation ability of WB for micro-climate is more significant than that of GS. In addition, the ratio area between GS and WB has the most significant influence on reducing building carbon emissions when it is 3:1 in winter, but this optimal ratio is 1:2 in summer. These conclusions can provide benchmark information for landscape planning and building energy conservation in the future. [ABSTRACT FROM AUTHOR]

Recent global commitments towards net-zero 2050 have resulted in an increased interest within a number of industries. The built environment has been identified as a major culprit contributing to the ongoing complex problem of carbon emissions. In an attempt to reveal the efforts, put into alleviating this challenge, this paper aims to provide a comprehensive, quantitative analysis of the literature on net-zero (energy and GHG emissions) in the built environment over the last two decades. In this study, well-established bibliometric and scientometric techniques are deployed to map the scientific domains by developing and analysing the resulting co-citation and keyword co-occurrence network developed from the bibliometric data from 1934 peer-reviewed articles retrieved from the SCOPUS database. The most significant contributions in net-zero research have originated primarily from UK, USA, and China. The results of the network analysis identified seven foundational themes of research - greenhouse gas emission, deep decarbonisation, earth material, residential building, high-rise building, displacement, ventilation, and walling element. The burst analysis revealed how a number of emerging digital technologies in the sector present opportunities to optimise future developments towards the attainment of a net-zero emission-built environment. To address the complexity associated with emissions caused by the built environment, the findings suggest that there is a need to expand the current LCA assessments to a broader, industry-wide scale, beyond the predominant 'single building case study' as the unit of reference. Moreover, the national net-zero pathway studies should aim to extend beyond the operational emission scenarios, and into assessing the impacts on materials and embedded emissions, which has grown exponentially. [ABSTRACT FROM AUTHOR]

Being increasingly insulated, new buildings are more and more sensitive to variations of solar and internal gains. Due to an important use of electrical heating systems, especially in housing, France is facing a growing problem of peak load on its electricity grid. Controlling the heating system often constitutes an efficient solution to shift heating loads while maintaining indoor comfort. The proposed energy management is a predictive set of optimal commands issued from a dynamic programming optimization knowing in advance the weather, occupancy and internal gains for the next 7 days. This method is tested on a low energy house situated in France with an annual heating demand of 14 kWh/m 2 . In this paper, load shifting according to utility rate incentives and carbon emissions are studied. The importance of building models as well as envelope insulation and thermal mass on energy management results is shown. [ABSTRACT FROM AUTHOR]

• Review identified 29 unintended impacts post residential energy retrofits. • Moisture and dampness are common issues reported in post retrofitted housing. • The indoor environment is significantly affected by airtightness and over-insulation. • Pre retrofit assessment is essential to avoid hygrothermal failure. Improving energy efficiency of existing buildings is currently among the most diverse and extensive mitigation opportunities to reduce energy consumption and CO 2 emissions worldwide. However, the implementation of energy-saving measures has caused unintended impacts, often correlated with dampness and mold growth connected to poor hygrothermal behavior in residential buildings. The focus of this paper is research on the impacts of energy efficiency measures (EEMs) in regard to the hygrothermal behavior resulting from the interaction of building's envelope, indoor environment, and occupants. The results show that dampness and mold growth are by no means exclusive to neglected houses, since the occurrence of these pathologies actually depends upon a complex set of conditions, including indoor and outdoor conditions, occupancy, maintenance, ventilation, mechanical systems, and quality of the envelope. We found that building envelope post-retrofit may suffer from higher levels of moisture and dampness, higher condensations risks, and a faster structural degradation caused by higher humidity levels. We also found that measuring hygrothermal behavior may play a role in more accurately predicting both overall energy consumption and occupant comfort. While hygrothermal behavior may be problematic, we found evidence that retrofits may moderately improve thermal comfort. [ABSTRACT FROM AUTHOR]

[Display omitted] • In the US, carbon savings are readily achievable by transitioning to heat pump technologies for the vast majority of homes. • The heat pump performance required to achieve carbon and cost neutrality varies by a factor of four across the US. • Energy cost neutrality is much harder to achieve than carbon neutrality. • Achieving carbon and energy costs savings is much easier when replacing older, low efficiency equipment. In order to meet climate goals, it will be necessary to significantly reduce the greenhouse gases emitted by homes. A key factor in the US is to reduce the on-site combustion of fossil fuels for heating end-uses and to replace this with use of electric heat pump technologies connected to a low-carbon grid. The replacement of natural gas furnaces with electric heat pumps is a key home decarbonization strategy. However, the potential for space heating electrification to reduce greenhouse gas emissions depends on the carbon dioxide equivalent (CO 2 e) content of the electricity used by the heat pump. This varies considerably depending on the source of electricity, with large state to state variability. Furthermore, household energy costs are likely to be impacted by the electrification of space heating, because retail energy prices for both natural gas and electricity in each state vary by factors of seven and four, respectively. Contractors, energy programs, government and building code officials, as well as consumers need clear indications of the likely CO 2 e and energy cost impacts of proposed electrification projects, because these will affect decarbonization choices and rationales around scaled heating electrification. Government and utility programs also need to be aware of the likely outcomes of any supported/incentivized measures. In this paper, we investigate these effects by looking at new metrics to analyze the change in CO 2 e emitted and the cost to meet home heating loads when switching from a natural gas furnace to a heat pump for the contiguous 48 states of the mainland US. [ABSTRACT FROM AUTHOR]

• The environmental performance of PU-gypsum ceiling tile and standard gypsum ceiling tile has been investigated. • Several forms of environmental impact have been analysed. • A comparative cradle-to-grave LCA of two gypsum ceiling tiles has been carried out, the PU-gypsum ceiling tile having better results. • The LCA includes the production and construction phases, use and end of life, the production stage being the main contributor to the environmental impact. In this paper, the LCA of two gypsum ceiling tiles is compared, the first one is a traditional gypsum tile and the second is a new eco ceiling tile in which polyurethane foam waste has been incorporated. Both tiles were made at one of the largest gypsum tile factories in Europe. The life cycle assessment has been considered from cradle to grave for which the corresponding production stages have been defined. This includes the extraction and transportation of raw materials, the manufacturing process, transportation to the client, the use of the product and the end of its useful life. The results show that the tile with polyurethane has a better environmental performance than the standard commercial ceiling tile. This is quantified as a 14% reduction in energy consumption, a 14% reduction in CO 2 emissions and a 25% reduction in water consumption compared with the standard tile, all the while maintaining the technical performance. An analysis of the results suggests that the new eco product has a competitive advantage on the market thanks to its environmental improvements and good technical performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multimodal occupancy detection framework for residential buildings. • Two variants of Occ-STPN models with feature level fusion and decision level fusion. • Feature extraction and occupancy detection models for various data modalities. • Transferability of a trained occupancy detection model from one building to another. • Occupancy prediction performance evaluation on three open-sourced datasets. For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This paper proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed. [ABSTRACT FROM AUTHOR]

In order to reduce CO 2 -emissions it is necessary to reduce the energy use in the existing building stock significantly. Gadehavegård – a social housing built-up area consisting of 19 similar blocks of flats with nearly 1000 dwellings situated in Denmark – needed renovation and therefore a block was selected for testing an ambitious renovation that would result in a significant reduction in energy use and CO 2 emissions. The ambition was to reach the German Passivhaus standard for the building, i.e. a very strict requirement, especially for a renovation project. The renovation included insulating the facades from the outside, replacing all windows, insulating the roof, installing decentralized mechanical ventilation systems with efficient heat recovery and a photovoltaic system on the roof. In addition, the balconies were included in the apartments by installing foldable glass façades. This paper gives a detailed description of the renovation project along with measurements of the energy use and indoor climate before and after renovation. Comparing the achieved results to the Passivhaus requirements show that the original goal is not achieved, however, the building fulfils the less strict requirements of the Passivhaus renovation certification EnerPHit and is still a very good example on how significant reductions in energy use can be achieved for these types of buildings. Results before and after renovation are compared using the energy signature and shows that heating energy consumption has been reduced by more than 50% even though indoor temperature on average has increased from 21.7 °C to 23.3 °C. [ABSTRACT FROM AUTHOR]

• A framework for optimizing the design of underground spaces is established. • The relationship between underground space and travel CO2 emissions is clarified. • Factors affecting underground space travel are quantified through multi-source data. The utilization of underground space plays a vital role in saving land, alleviating traffic pressure, and improving the utilization of resources. The combination of walking and metro instead of cars is an effective way to reduce energy consumption and CO2 emissions. However, transfer inconvenience, poor accessibility, lack of vitality, and other phenomena in the underground hinder this low-carbon transportation utilization. This paper aims to improve travel quality and efficiency by optimizing underground space design to reduce CO2 emissions and raise energy efficiency. Taking a typical underground space in Nanjing as an example, multi-source methods such as field measurement, POI, and space syntax are used to quantify the factors affecting underground space travel. Correlations between each factor and the density of passenger flow distribution are discussed. The results show that catering and shopping are the most correlated factors of the pedestrian flow distribution on weekdays and weekends, respectively. Through simulation, the optimized design can increase the passenger flow and reduce CO2 by 277.9 g/Km and 119.1 g/Km per minute on weekdays and weekends, respectively. The design is consistent with the result of 219 questionnaires. This research method has positive significance for developing underground space in other Chinese cities under low carbon background. [ABSTRACT FROM AUTHOR]

Today, about 35% of global energy consumption and related carbon dioxide emissions are caused by the construction sector. This paper evaluates and compares the life cycle energy consumption (LCEC) and carbon dioxide emissions (LCCE) of a heritage building (BT1) constructed in 1875, a new building (BT2) constructed with modern constructional elements with similar plans of the heritage building and the heritage building after the restoration and refurbishment (BT3) by using real data from the construction site of a real project in Gaziantep, Turkey. It is calculated that, the operational phase was dominant over the buildings lifespan and BT1 has the highest operational energy consumption. LCEC and LCCE of the BT1, BT2 and BT3 are calculated to be 102.63, 70.13, 78.07 GJ/m2, and 14.18, 9.75 and 10.06 tons of CO 2 per m2 (tCO 2 /m2), respectively. With current techniques and methodologies the refurbishment and restoration of the heritage building increases the embodied energy (EE) by 56.6%. Selection of appropriate construction materials for refurbishment of heritage buildings is an important procedure that prevents excessive increment of EE and related emissions. Sustainable structural restoration of heritage buildings should be performed by using appropriate methodologies observing the conservation principles of history, energy and environment. [ABSTRACT FROM AUTHOR]