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Artificial intelligence (AI) has emerged as an effective solution to alleviate excessive carbon emissions in sustainable building projects. Although there are numerous applications of AI, there is no state-of-the-art review of how AI applications can reduce net-zero carbon emissions (NZCEs) for sustainable building projects. Therefore, this review study aims to conduct a systematic literature and science mapping review of AI applications in NZCEs for sustainable building projects, thereby expediting the realization of NZCEs in building projects. A mixed-method approach (i.e., systematic literature review and science mapping) consisting of four comprehensive stages was used to retrieve relevant published articles from the Scopus database. A total of 154 published articles were retrieved and used to conduct science mapping analyses and qualitative discussions, including mainstream research topics, gaps, and future research directions. Six mainstream research topics were identified and discussed. These include (1) life cycle assessment and carbon footprint, (2) practical applications of AI technology, (3) multi-objective optimization, (4) energy management and energy efficiency, (5) carbon emissions from buildings, and (6) decision support systems and sustainability. In addition, this review suggests six research gaps and develops a framework depicting future research directions. The findings contribute to advancing AI applications in reducing carbon emissions in sustainable building projects and can help researchers and practitioners to realize its economic and environmental benefits. [ABSTRACT FROM AUTHOR]

Internet-of-Things (IoT) technologies have been steadily adopted and embedded into energy infrastructure following the rapid transformation of energy grids through distributed consumption, renewables generation, and battery storage. The data streams produced by such energy IoT infrastructure can be extracted, processed, analyzed, and synthesized for informed decision-making that delivers optimized grid operations, reduced costs, and net-zero carbon emissions. However, the voluminous nature of such data streams leads to an equally large number of analysis outcomes that have proven ineffective in decision-making by energy grid operators. This gap can be addressed by introducing artificial intelligence (AI) chatbots, or more formally conversational agents, to proactively assist human operators in analyzing and identifying decision opportunities in energy grids. In this research, we draw upon the recent success of generative AI for optimized AI chatbots with natural language understanding and generation capabilities for the complex information needs of energy IoT infrastructure and net-zero emissions. The proposed approach for optimized generative AI chatbots is composed of six core modules: Intent Classifier, Knowledge Extractor, Database Retriever, Cached Hierarchical Vector Storage, Secure Prompting, and Conversational Interface with Language Generator. We empirically evaluate the proposed approach and the optimized generative AI chatbot in the real-world setting of an energy IoT infrastructure deployed at a large, multi-campus tertiary education institution. The results of these experiments confirm the contribution of generative AI chatbots in simplifying the complexity of energy IoT infrastructure for optimized grid operations and net-zero carbon emissions. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as an effective solution to alleviate excessive carbon emissions in sustainable building projects. Although there are numerous applications of AI, there is no state-of-the-art review of how AI applications can reduce net-zero carbon emissions (NZCEs) for sustainable building projects. Therefore, this review study aims to conduct a systematic literature and science mapping review of AI applications in NZCEs for sustainable building projects, thereby expediting the realization of NZCEs in building projects. A mixed-method approach (i.e., systematic literature review and science mapping) consisting of four comprehensive stages was used to retrieve relevant published articles from the Scopus database. A total of 154 published articles were retrieved and used to conduct science mapping analyses and qualitative discussions, including mainstream research topics, gaps, and future research directions. Six mainstream research topics were identified and discussed. These include (1) life cycle assessment and carbon footprint, (2) practical applications of AI technology, (3) multi-objective optimization, (4) energy management and energy efficiency, (5) carbon emissions from buildings, and (6) decision support systems and sustainability. In addition, this review suggests six research gaps and develops a framework depicting future research directions. The findings contribute to advancing AI applications in reducing carbon emissions in sustainable building projects and can help researchers and practitioners to realize its economic and environmental benefits.

This study aimed to verify the role and feasibility of co-fired fly ash (CFA) as an alternative construction material. It also demonstrated the engineering properties of CFA mortar and compared them with those of pulverized coal fly ash (PCFA) mortar. Further, CFA-PCFA-cement mortar specimens were mixed to produce ternary eco-binder mortars and find the optimal application proportion. The results pointed out that the pozzolanic strength activity index of CFA was 76 %, with only a slight pozzolanic reaction. The sum of the chemical composition (SiO2+Al2O3+Fe2O3) of CFA was insufficient to meet ASTM C618 requirements, and it was deduced that a small amount of CFA should be used as the substitute for cement or fine aggregates. Specimens with CFA replacing fine aggregates contributed to lower water absorption, improved sulfate resistance, and increased compressive strength; Specimens with CFA replacing cement reduced shrinkage and improved sulfate resistance but decreased compressive strength and increased absorption. Blended CFA-cement mortars consisting of 5 % CFA as a replacement material for cement and fine aggregates had excellent engineering properties. Ternary blended CFA-PCFA-cement mortar exhibits superior engineering properties. The optimum proportion is an economy-friendly binder composed of 10 % CFA (5 % as cement and 5 % as fine aggregates) and 10% PCFA (as a replacement for cement).

Internet-of-Things (IoT) technologies have been steadily adopted and embedded into energy infrastructure following the rapid transformation of energy grids through distributed consumption, renewables generation, and battery storage. The data streams produced by such energy IoT infrastructure can be extracted, processed, analyzed, and synthesized for informed decision-making that delivers optimized grid operations, reduced costs, and net-zero carbon emissions. However, the voluminous nature of such data streams leads to an equally large number of analysis outcomes that have proven ineffective in decision-making by energy grid operators. This gap can be addressed by introducing artificial intelligence (AI) chatbots, or more formally conversational agents, to proactively assist human operators in analyzing and identifying decision opportunities in energy grids. In this research, we draw upon the recent success of generative AI for optimized AI chatbots with natural language understanding and generation capabilities for the complex information needs of energy IoT infrastructure and net-zero emissions. The proposed approach for optimized generative AI chatbots is composed of six core modules: Intent Classifier, Knowledge Extractor, Database Retriever, Cached Hierarchical Vector Storage, Secure Prompting, and Conversational Interface with Language Generator. We empirically evaluate the proposed approach and the optimized generative AI chatbot in the real-world setting of an energy IoT infrastructure deployed at a large, multi-campus tertiary education institution. The results of these experiments confirm the contribution of generative AI chatbots in simplifying the complexity of energy IoT infrastructure for optimized grid operations and net-zero carbon emissions.

[Display omitted] • A novel cryogenic energy storage unit based on air liquefaction process was developed. • Wind renewable energy was supplied the required power of the system in off-peak time. • Integrated post-combustion & gas turbine/Rankine power cycles during on-peak hours. • Pinch study used to achieve heat exchanger networks on multi-stream exchangers. • Storage and round-trip efficiencies of the system were 67.97 % & 62.50 %, respectively. Given the rising global energy demands and the fluctuating nature of load demand, advancing various energy storage systems to enhance their efficiency is essential. Moreover, the increase in greenhouse gas emissions from various industries has prompted governments to implement carbon dioxide (CO 2) capture systems and invest in renewable energy sources. In this research, a cryogenic energy storage configuration is developed according to the air liquefaction process, liquefied natural gas (LNG) regasification operation, CO 2 capture cycle, and organic Rankine plant. During off-peak times, the air entering the energy storage system is compressed and liquefied using wind energy and the cold energy from LNG vaporization, producing 83.12 kg/s of liquid air. During on-peak times, the liquid air and LNG after recovering the cold energy enter the power generation cycle, generating 119 MW of electrical power. This power generation cycle includes a combustion chamber, gas turbine power plant, and organic Rankine cycles. Flue gases from the power generation cycles enter the amine-based CO 2 capture and then the output CO 2 is stored in liquid form. The storage and round-trip efficiencies of the present energy storage configuration are 67.97 % and 62.50 %, respectively. The results of exergy analysis show that the exergy efficiency of the whole system, off-peak, and on-peak sections are calculated as 64.88 %, 82.40 %, and 74.03 %, respectively. The pinch method for multi-stream exchangers (HX6, HX7, and HX8) is accomplished and the exchanger network related to each one is determined. Three-dimensional sensitivity analysis indicates that storage and round-trip efficiencies increase up to 80.45 % and 66.20 %, respectively when the power generation section pressure increases up to 110 bar and compressed air pressure decreases to 135 bar. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

This study aimed to verify the role and feasibility of co-fired fly ash (CFA) as an alternative construction material. It also demonstrated the engineering properties of CFA mortar and compared them with those of pulverized coal fly ash (PCFA) mortar. Further, CFA-PCFA-cement mortar specimens were mixed to produce ternary eco-binder mortars and find the optimal application proportion. The results pointed out that the pozzolanic strength activity index of CFA was 76 %, with only a slight pozzolanic reaction. The sum of the chemical composition (SiO 2 +Al 2 O 3 +Fe 2 O 3) of CFA was insufficient to meet ASTM C618 requirements, and it was deduced that a small amount of CFA should be used as the substitute for cement or fine aggregates. Specimens with CFA replacing fine aggregates contributed to lower water absorption, improved sulfate resistance, and increased compressive strength; Specimens with CFA replacing cement reduced shrinkage and improved sulfate resistance but decreased compressive strength and increased absorption. Blended CFA-cement mortars consisting of 5 % CFA as a replacement material for cement and fine aggregates had excellent engineering properties. Ternary blended CFA-PCFA-cement mortar exhibits superior engineering properties. The optimum proportion is an economy-friendly binder composed of 10 % CFA (5 % as cement and 5 % as fine aggregates) and 10% PCFA (as a replacement for cement). • Development and application of ternary economic binders in this study. • Ternary eco-binder consists of co-fired fly ash (CFA), pulverized coal fly ash (PCFA) and cement. • CFA is classified as a low pozzolanic reactive material. • Eco-binder consists of 5 % CFA as cement, 5 % CFA as fine aggregates and 10 % PCFA as cement. [ABSTRACT FROM AUTHOR]