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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]

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.

Although Taiwan proposed 2020 to achieve net-zero carbon emissions by 2050, it has encountered difficulties making this transition. This research argues that climate issues involve epistemic politics and competition and those different discourses require the construction of socially robust knowledge (SRK) in reflexive, contextual confrontation, and competition. A society with strong SRK can lead the country's net-zero carbon emissions decision, system, and transformation. This article analyses the types of environmental movements and the strength of their production of SRK with two cases that discusses the current lag of net-zero transition. The study found that the elements of successful transition include the same object of resistance, based on rational risk knowledge debate, and multi-level social mobilisation, which constitutes a strong SRK. A solid SRK package successfully reframes the development thinking of Taiwanese society. The net-zero movement needs a transparent object of resistance; environmental groups need to familiarise themselves with the issue of climate warming, resulting in a gap in appeals, mobilisation strategies, stages, and dominance. Although the latter still presents a certain degree of SRK and constitutes a policy of confrontation or competition with the government, the issues of appeal are pretty diverse, showing scattered initiatives. Folk-focused issues and discourses cannot build a strong agora, thus failing to reframe the social development framework and create more elements or opportunities for social transformation to a green path; as a result, Taiwan's sluggish climate governance and net-zero transition have encountered dilemmas both at home and abroad. • Socially robust knowledge (SRK) could challenge the authority's discourses in the current developmental state. • The Strong SRK of the anti-petrochemical movement has successfully overturned the major governmental industrial project. • The weak SRK of Net Zero is far from mobilising public support, leading to the delay of the Net Zero climate policy. • This study can provide a reference for other East Asian countries to promote net-zero carbon emissions. [ABSTRACT FROM AUTHOR]

Climate change and environmental sustainability assessment are essential in city planning, design, and smart city advancement. Despite Saudi Arabia's high global greenhouse gas (GHG) emissions ranking, a comprehensive review of extant studies revealed insufficient tools enhancing the policymaking and comprehension of climate change and environmental performance. This paper developed a hybrid green city index (GCI) and grey relational analysis (GRA) composite index for appraising national environmental sustainability via a robust, efficient, effective, and replicable grading process. The index is designed based on two primary considerations. The first is the selection of quality underlying indicators/categories, while the second is the adoption of GRA for conducting the normalization, weighting and aggregation process. These two considerations influenced the proposed composite index, which was later applied to Saudi Arabia as a study area. The results revealed that the environmental sustainability of Saudi Arabia is not significant, with the most outstanding of 0.3127 for 2010. At the category level, the favourable environmental sustainability ranking is between the 2010 and 2012 assessment period, with a gradual decline till 2018. This study's findings are unique as no studies within the context of Saudi Arabia and the Gulf region have utilized this study's research approach. Although not all indicators of the proposed index were used in the study area, this study's methodology and outcomes have the beneficial impact of assisting Saudi Arabia's decision-makers across the cities in monitoring the status and progress of implementing its net zero carbon emissions by 2060.

This research aims to find the best carbon tax regime for the achievement of net-zero carbon emissions and promotion of social welfare level. We discuss two regimes in this study, including carbon tax on total social welfare level (CTTW) and carbon tax on single social welfare level (CTSW). Findings show that the best regime depends on product substitution and product price elasticity of demand. Industrial transformation not only causes changes in product substitution and product price elasticity of demand, but also makes these two regimes have different effects on the achievement of net-zero carbon emissions and promotion of social welfare level. [ABSTRACT FROM AUTHOR]

This study uses the tree stumps of the three representative trees in Taiwan (Leucaena leucocephala, Syzygium samarangense, and Ziziphus jujuba) as the material source and recyclable oyster shell powder as an activator. A carbonization process for upgrading and recycling the tree stumps was developed with our homemade, digital-controlled, energy-saving carbonization system. First, the tree stumps are carbonized at a medium temperature of 500 °C and then heated to 900 °C for high-temperature carbonization, followed by the activation procedure as required. With our method, we can produce biochar with a high proportion of fixed carbon and a high proportion of meso- and macropores while maximizing the yield of wood vinegar. The specific surface area of the meso- and macropores can reach up to 70 m2/g or more. The effect of different activation materials on the pore characteristics and specific surface area of biochar was carefully examined. It was found that both KOH and oyster shell powder is the ideal activator for producing biochar with a high proportion of meso- and macropores. The FTIR spectrum, CEC, and contents of the ordinary elements and heavy metals of the biochar were also reported. It is clear from the FTIR data that the absorption peaks of the overall spectrum of the three types of biochar after carbonization at high temperature are cleaner than those of biochar carbonized at low temperature. This research can promote the recycling of agricultural residues, enhance soil carbon sequestration, preserve fertilizers, and suppress diseases and pests, moving towards approaching the goal of net-zero carbon emissions. [ABSTRACT FROM AUTHOR]

This research aims to find the best carbon tax regime for the achievement of net-zero carbon emissions and promotion of social welfare level. We discuss two regimes in this study, including carbon tax on total social welfare level (CTTW) and carbon tax on single social welfare level (CTSW). Findings show that the best regime depends on product substitution and product price elasticity of demand. Industrial transformation not only causes changes in product substitution and product price elasticity of demand, but also makes these two regimes have different effects on the achievement of net-zero carbon emissions and promotion of social welfare level.

[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]

In this study, three industrial by-products (ultrafine fly ash, ground granulated blast-furnace slag (ggbs) and circulating fluidized bed co-fired fly ash) were used to produce ternary cementless composites without using alkali activators. The finenesses of ultrafine fly ash, ggbs and co-fired fly ash were 33,800, 5830 and 5130 cm2/g, respectively. The composite material was developed by mixing supplementary cementing materials of different particle sizes and exploiting the high-alkaline properties of the co-fired fly ash to develop a substantial hardening property like cement. The test specimens were made in the form of pastes and the water-to-cementitious-material ratio for the test was fixed at 0.55. The test results show that the flowability of the six different mixtures could be up to 120% and the setting time could be controlled within 24 h. At 60% of the ggbs proportion, the setting time could be held for 8 h. The compressive strength of each proportion reached 7 MPa at 7 days and 14 MPa at 28 days. The water-cured specimens exhibited better strength behavior than the air-cured specimens. Scanning electron microscopy found the main components of strength growth of the specimens to be hydrated reactants of C-A-S-H or ettringite. The results of the XRF analysis show that the specimens responded to higher compressive strengths as the Ca/Si and Ca/Al ratios increased.

Extensive studies have examined the financial performance of green buildings in recent years. The results have frequently observed that the premium of green buildings is time-varying and dependent on the study period and markets being examined. Further, virtually no dedicated study has been devoted to examine the role of mandatory building energy rating disclosure policies on green building price premium. This raises the question of whether the mandatory energy rating disclosure policies would have an influence on the financial performance of green buildings. This study assesses the premium of green buildings by considering the role of mandatory energy efficiency of commercial building disclosure program (CBDP) using the MCSI/IPD NABERS data over 2005–2020. The results of the study showed that, in Australia, buildings with NABERS rating of 4 stars and above delivered a higher total return compared with buildings with lower NABERS ratings. This also supports the Freeman's (1984) social impact hypothesis in which favorable social performance will ultimately lead to favorable financial performance. In addition, our empirical modelling results also demonstrated the premium of green buildings is stronger since the launch of CBDP, reflecting the importance of mandatory building efficiency disclosure. The policy implications of our studies have also been discussed as buildings play a crucial role in achieving the United Nations Sustainable Development Goals (SDGs), particularly net-zero carbon emissions. [ABSTRACT FROM AUTHOR]

Renewable energy sources such as wind farms and solar power plants are replacing conventional coal-based synchronous generators (SGs) to achieve net-zero carbon emissions worldwide. SGs play an important role in enhancing system strength in a power system to make it more stable during voltage/frequency disruptions. However, traditional coal-fired SGs are being decommissioned in many parts of the world, owing to stringent environmental regulations and low levelized cost of energy of renewables. Consequently, maintaining system strength in a renewable energy-dominated power system has become a major challenge, and without adequate mitigation techniques, low system strength can potentially cause widespread power outages. This paper provides an overview of system strength and its measurement techniques in a power system with a large number of renewable energy sources (RESs), for example solar and wind farms. The review includes the system strength measurement techniques, mitigation approaches, and future challenges. • A comprehensive review on system strength for Australia. • Integration of power systems with large number of renewable energy sources. • Measurement and mitigation techniques for system strength shortfalls. • Analysis of future challenges and research directions on system strength. [ABSTRACT FROM AUTHOR]

Climate change and environmental sustainability assessment are essential in city planning, design, and smart city advancement. Despite Saudi Arabia's high global greenhouse gas (GHG) emissions ranking, a comprehensive review of extant studies revealed insufficient tools enhancing the policymaking and comprehension of climate change and environmental performance. This paper developed a hybrid green city index (GCI) and grey relational analysis (GRA) composite index for appraising national environmental sustainability via a robust, efficient, effective, and replicable grading process. The index is designed based on two primary considerations. The first is the selection of quality underlying indicators/categories, while the second is the adoption of GRA for conducting the normalization, weighting and aggregation process. These two considerations influenced the proposed composite index, which was later applied to Saudi Arabia as a study area. The results revealed that the environmental sustainability of Saudi Arabia is not significant, with the most outstanding of 0.3127 for 2010. At the category level, the favourable environmental sustainability ranking is between the 2010 and 2012 assessment period, with a gradual decline till 2018. This study's findings are unique as no studies within the context of Saudi Arabia and the Gulf region have utilized this study's research approach. Although not all indicators of the proposed index were used in the study area, this study's methodology and outcomes have the beneficial impact of assisting Saudi Arabia's decision-makers across the cities in monitoring the status and progress of implementing its net zero carbon emissions by 2060., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

[Display omitted] • Bioenergy potential was Saccharum bengalense was explored through pyrolysis. • Pyrolytic products were studied using coupled TG-FTIR-GCMS. • ANN, M−DAEM machine learning was applied to elucidate the pyrolysis process. • Evolved gases contained green chemicals for industrial and energy applications. • MLP-based ANN regression model demonstrated perfection in training, test, and validation. Saccharum bengalense grows on non-arable lands throughout the world. Its oven-dried biomass showed 18.05 ± 0.37 (MJ kg−1) of High Heating Value (HHV), 76.47 ± 0.58 % of volatile matter, and very low content of sulfur (0.46 ± 0.04 %). Here, its oven-dried biomass was pyrolyzed at four heating rates (β: 10, 20, 40, 80 ℃min−1) in a thermogravimetric analyzer. The thermogravimetric data were subjected to isoconversional models including Friedman, KAS, and FWO to understand the pyrolysis process. Pyrolysis reaction occurred in three consecutive stages where main pyrolysis reaction happened during the second stage. The average values of activation energy were shown to be 186.01 kJ mol−1, 169.56 kJ mol−1, and 170.99 kJ mol−1 as assessed through Friedman, KAS, and FWO methods, respectively, which indicated the suitability of the biomass for pyrolysis. The TG-FTIR-GCMS analysis showed that pyrolytic gases contained acetone, aromatic compounds, hydrocarbons, phenols, ketones, alcohols, esters, and aldehydes. The MLP 3–6-1 network model was shown to be the best which was used to understand the conversion process. Activation energies were accurately determined using the MLP-based ANN regression model, where values of R2 (0.999) indicated perfection in training, test, and validation. The data from the ANN model were consistent with the TG-based interpretation of the pyrolysis and represented the first-order thermal degradation. The M−DAEM model had a good fit with the experimental data because the dα/dt and R2 of α were higher than 99.98 % and 99.99 %, respectively. The pyrolytic products were copious because of the high percentage of carbon atoms. The data demonstrated that S. bengalense biomass has promising potential to become a biorefinery feedstock to produce chemicals and energy from renewable biomass while keeping the energy-water-environment nexus sustainable. [ABSTRACT FROM AUTHOR]

This study investigates the optimal design of carbon capture, transport and storage (CCTS) supply chains for decarbonizing industrial emitters. It builds upon previous analyses, which determine the cost-optimal design of CCTS supply chains while complying with specified emissions reduction scenarios, and determines optimal designs in terms of minimum cost and maximum resilience. The resilience of a supply chain is defined as its ability to permanently store the captured CO 2 during the time horizon of interest, and it is quantified in terms of expected amount of carbon not stored under a fixed number of possible simultaneous failures. A mixed-integer linear program is developed to design CCTS supply chains that ensure a specified level of resilience while minimizing total system costs and CO 2 emissions. The model is illustrated by determining the optimal decarbonization strategy in terms of costs and level of resilience for the Swiss waste-to-energy sector from 2025 to 2050. Overall, resilience is achieved with a cost increase with respect to the cost-optimal solution ranging from about 5% (backup truck connections to minimize the cost of the supply chain) to about 70% (backup pipeline connections to minimize the emissions of the supply chain) when the storage site is in the North Sea. When the storage site is available in Switzerland, the cost increase is much reduced and ranges from about 1% to 10% with respect to the cost-optimal solution. • Definition of resilient carbon capture, transport, and storage supply chains. • Two resilience perspectives, from infrastructure and environment standpoints. • Design and multi-objective optimization of cost-optimal and resilient CO 2 networks. • Trucks are the most cost-effective solution for improving network resilience. • Redundant pipelines have lowest CO 2 emissions for improving network resilience. [ABSTRACT FROM AUTHOR]

• Multi-objective optimization of carbon capture, transport, and storage supply chains. • Cost-optimal infrastructure rollout to decarbonize Swiss waste-to-energy sector. • Pipelines are the most cost-effective transport mode for large volumes of CO 2. • Ship and barge connections are competitive with pipeline connections. • Rail and truck transport is competitive for short time horizon or small CO 2 volumes. This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO 2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the supply chains while complying with different emissions reduction pathways over a deployment time horizon of 25 years. All design decisions are time-dependent and are taken with a yearly resolution. Whereas the model is general, here its features are illustrated by designing optimal supply chains to decarbonize the Swiss waste-to-energy sector, for various emission reduction pathways, when up to two storage sites are considered, namely one in the North Sea assumed to be already available and a hypothetical one in Switzerland assumed to be possibly available in the future. Findings show that, unless a domestic storage site becomes available soon, the transport cost is the greatest contribution to the overall costs, followed by the capture cost, while the storage cost plays only a minor role. Pipelines are the most cost-effective mode of transport for large volumes of transported CO 2 , especially when considering multi-year time horizons for the planning of the supply chains. Ship and barge connections are competitive with pipeline connections, whereas rail and truck connections are cost-optimal only when considering shortsighted time horizons or small volumes of CO 2 transported. [ABSTRACT FROM AUTHOR]

This article provides a framework for conceptualizing climate action needs grounded in the nationally determined contributions (NDCs) of the least developed party countries (LDPCs) of the Paris Agreement (PA). It examines the NDCs of 35 LDPCs recorded in the NDC public registry of the United Nations Framework Convention for Climate Change (UNFCCC). A grounded theory approach is adopted to assess what these countries need to materialize their NDCs under the PA. A conceptual framework of needs is figured out through an iterative process of data collection and analysis in three cycles: (1) open and in vivo coding; (2) axial coding; and (3) theoretical or selective coding. The data are analyzed with the help of NVIVO software. The results provide a verifiable framework of needs for climate action, which includes 55 saturated need factors extracted from the writing excerpts of NDCs, 17 sub-categories (axial codes) with climate finance and technology transfer as the most prominent, and 7 theoretical or selective categories with mobilize, educate, governmental, synergic, levels, equity, and public health. It provides a baseline for policy, research, and action from the developed party countries to uphold their PA obligations.

The single life cycle assessment on advanced vehicle technologies and clean construction supply chains offers the potential for reducing carbon dioxide emissions from vehicle operation and road infrastructure separately. However, the impact of the combination of these two aspects on CO 2 emissions mitigation of road life cycle is less known even though it is critical to the longer-term road transportation decarbonization and long-range policy making for transportation sector, especially under latest worldwide net-zero carbon emission goal. In this study, taking a real project-level asphalt pavement freeway with 15-year life span in China as a case, the amount and hot spots of CO 2 emissions of road transportation were evaluated by considering emissions abatement measures of advanced vehicle technologies and construction supply chains which are theoretically practicable in near-, mid-term and long-term future (from 2020 to 2035). Furthermore, a scenario-based sensitivity analysis on different increasing scope together with various increasing degree of abatement levels over time for these measures is provided. Results demonstrate that the timely implementation of combined decarbonation measures of advanced vehicle technologies and construction supply chains by 2035 could reduce 16.3% of total CO 2 emissions from a road life cycle. In detail, for maintenance activities and use phase, total CO 2 emissions reduce 32% and 16.2% separately. The construction equipment still is the top emissions contributor for maintenance activities. The hybrid electric vehicles (HEV), not battery electric vehicles (EV), replaces conventional internal combustion engine vehicles (ICEV) and becomes the largest source for passenger-related CO 2 emissions from use phase by 2035. Findings are sensitive to assumptions regarding cleaner fuel-produced cement, construction equipment and asphalt, and the market penetration of new energy vehicle. The tight and accelerating pace of primary abatements assist in alleviating the infrastructure carbon lock-in effects caused by maintenance activities with 15% additional CO 2 emissions saving, but not bring about a significant additional reduction (no more than 2.0%) for total road life cycle CO 2 emissions. Current abatement measures are effective but obvious emissions mitigation substitutes of a road is still required, especially innovative road structure and cleaner supply chains inputs as well as deeper decarbonized electrified vehicle. [ABSTRACT FROM AUTHOR]