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Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

In response to the growing emphasis on green packing, e-commerce businesses actively pursue sustainable solutions that balance cost reduction with environmental conservation. Traditional research on three-dimensional bin packing has concentrated on maximizing spatial utilization under fixed box dimensions. However, in the practical context of e-commerce, packing boxes exhibit a wide range of sizes within a single warehouse. Customizing packing to prevent material and space wastage has become crucial for sustainable development. This paper innovates traditional three-dimensional packing research by introducing open dimensions instead of fixed ones. It addresses challenges in e-commerce packing, such as multiple orders and diverse bin shapes, to formulate a mixed-integer programming model. Focused on the carbon emission lifecycle's usage phase for packing boxes, the model aims to minimize associated costs while ensuring that items' weight, the center of gravity, sufficient support, and non-overlapping placement are maintained during the packing process. It also incorporates one-dimensional and two-dimensional fixed bin sizes. To solve this model, the paper proposes an improved hybrid genetic algorithm for stack sequence optimization. This algorithm systematically optimizes the dimensions for each box type. Building upon this, the study introduces an algorithm capable of estimating packing material consumption and the percentage reduction in carbon emissions during the packing process, given the known variability in packing box utilization. These two algorithms are integrated into an open-dimension packing box warehouse management ecological closed loop system designed for the B2B e-commerce context. In experiments with the proposed model and algorithms, the results demonstrate an average packing rate improvement of 10%–12% compared to alternative methods. Additionally, packing material consumption and carbon emissions are reduced by approximately 16.56%–19.85%, confirming the effectiveness of the proposed approach. • Open dimension model boosts green e-commerce packing efficiency. • Stacking algorithm lifts space use up to 12%. • Material and emissions cut 16%–20% on space gains. • Eco warehouse system enables box reuse and material recycle. [ABSTRACT FROM AUTHOR]

Because transport in the port hinterlands heavily depends on roads with negative externalities, much social interest has been in modal shifts (MSs) to rail and shipping with lower environmental impact. Currently, leading industry sectors to ambitiously embrace technological innovations to decarbonize—consequently, in line with these changes, the significance of MSs should change; however, no previous studies have comprehensively presented the overall CO 2 emissions and transport mode shares for future regional cargo transport. This paper presents a scenario analysis of CO 2 emission reductions in the Japanese domestic hinterland of international maritime container transport based on future scenarios of technological innovation and change in shipper behavior. The simulation results using the global logistics intermodal network simulation model showed that up to 87% CO 2 reduction is possible, and the primary driver for this is technological innovation. Moreover, the significance of MSs fluctuates depending on the advancement of technological innovation, suggesting that MSs hold a degree of import as a decarbonization measure during the transitional phase toward carbon neutrality (CN) as technological innovation advances. The results of this study, which fluctuated considerably by scenario and timing, have policy implications with respect to the path to be followed toward CN, including whether to promote MSs. • Scenario analysis of CO 2 emission reductions in Japanese maritime transportation. • Up to 87% CO 2 reduction possible using technological innovation. • Significance of modal shifts fluctuated with the degree of technological innovation. • Policy implications suggesting that the path toward carbon neutrality is crucial. [ABSTRACT FROM AUTHOR]

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance. • Green finance has significantly reduced China's provincial carbon emissions. • The upgrading of energy structure and industrial structure is a positive channel to reduce carbon emissions. • Green innovation strengthens the carbon reduction effect of green finance, but reveals the potential "greenwashing". • Green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. • Policymakers should develop flexible, dynamic and coordinated green finance development policies. [ABSTRACT FROM AUTHOR]

As a significant source of carbon emissions, road logistics operators are under increasing pressure from governments and customers to find ways to decarbonize as part of broader global efforts to reach net zero. Decarbonization of road logistics relies on the widespread diffusion of existing and emerging technological transport solutions. These include alternative fuel vehicles, battery technologies, renewable energy and charging solutions. All promise to reduce carbon emissions, but their implementation remains challenging, expensive, and risky. As early adopters of alternative fuel vehicles have reported, transitioning from fossil fuels poses challenges that must be prepared for and understood to minimize the obstacles to genuine emissions reductions in road logistics. A considerable volume of academic research has been published advocating emission reduction solutions and providing detailed analyses of their potential positive environmental impacts. However, to our knowledge, no frameworks integrate these analyses with practical insights into current and anticipated challenges for road logistics operators transitioning from fossil fuels to a decarbonized future. This paper analyses contemporary evidence and insights on current and future issues and presents an integrated framework for road freight logistics decarbonization challenges. The framework primarily focuses on decarbonization through alternative fuels and analyses three categories of challenges from socio-technical, economic, and environmental perspectives. The three categories of challenges relate to alternative fuel vehicles and fleets, alternative fuel distribution infrastructure and renewable energy generation. The underlying principle of the framework is to provide a practical tool that supports a more informed view of both the advantages and challenges of transitioning to alternative fuels. This research contributes to the body of knowledge by providing a framework to help direct future research into tackling these logistics decarbonization challenges. The insights presented in this paper may also inform practitioners by sensitizing them to potential roadblocks in the transition away from fossil fuels. • Framework integrating road freight logistics decarbonization challenges. • Analyse alternative fuels, alternative fuel distribution and renewable energy. • Three perspectives on decarbonization: socio-technical, economic, and environmental. • Highlight logistics services provider strategies to minimize risk and uncertainty. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether emission reduction commitments contribute to carbon risk premium. Therefore, based on a sample of Chinese listed companies that publicly disclosed questionnaires in the CDP from 2009 to 2021, this paper empirically examines the relationship between emission reduction commitments and carbon risk premium and their formation mechanism. The results show that emission reduction commitments can effectively hedge the carbon risk premium, which pass several robustness tests. Specifically, the more comprehensive and ambitious the commitment is, the greater the suppression of the carbon risk premium. The mechanism test shows that disclosing emission reduction commitment information can reduce carbon risk by improving investor confidence and attracting political resources. Differences in enterprise emission levels, regional environmental regulation intensity and green financial development result in different risk-hedging effects of emission reduction commitments. Moreover, the greater the substantial pressure from stakeholders, the greater the tendency for firms to set up emission reduction commitments. Finally, the heterogeneity analysis reveals that confidence level of commitments has a significant impact on risk premium. Specifically, enterprises with SBTi validation, higher CDP ratings and higher target completion are more helpful in curbing carbon risk premium. Our findings contribute to corporate commitment to climate change and complement the carbon risk premium hypothesis. [Display omitted] The possible highlights of this study are as follows. • With the help of forward-looking information on emission reduction commitments, we re-examine the conclusion of the carbon risk premium and find that emission reduction commitments can effectively hedge the risk premium, enriching and developing the carbon risk premium hypothesis • This paper brings commitment levels and carbon emission levels into a unified analytical framework to study the correspondence between emission reduction commitments made under pressure to reduce emissions and the carbon risk premium, providing micro evidence for solving the mystery of the carbon risk premium. • Measure emission reduction commitment indicators from various angles, making the data on emission reduction commitments more objective and scientific. [ABSTRACT FROM AUTHOR]

Existing studies on emission accounting in global value chains (GVCs) have not focused on the relational nature of GVC activities manifested as the interaction of intermediate goods between enterprises. This paper proposes a relational GVC emissions accounting framework based on an inter-country input-output (ICIO) model distinguishing between domestic-owned enterprises (DOEs) and foreign-invested enterprises (FIEs), which is classified as trade-based, investment-based and hybrid-based emissions. Using AMNE-ICIO tables from 2005 to 2016, this paper traces emissions and carbon intensity in relational GVC activities at the global, economic, and industry levels. We find the following: (1) Investment-based emissions accounted for about 94.15% of the increase in relational GVC emissions, of which more than half comes from the interactive activities between DOEs and FIEs. (2) For the United States, high-income economies, and high-tech manufacturing, investment-based emissions were higher than trade-based emissions, and the reverse was true for upper-middle and lower-middle income economies and China. (3) Although relational GVC carbon intensity was high, the trend of decline was significant. (4) Compared to trade activities, investment-based activities were less carbon intensity in China and upper-middle income economies due to the interaction of production between FIEs and DOEs. The findings add new insights into the coordination of global emissions reductions and the allocation of emissions responsibility. • Emphasize the interdependence between enterprises in cross-border production. • Combine GVC linkages with carbon emissions and carbon intensity. • Investment-based emissions are the main factor of relational GVC emissions growth. • The carbon intensity of relational GVC decreased significantly. • Developing countries can access green spillover through investment-based GVC links. [ABSTRACT FROM AUTHOR]

As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

The quest for sustainability and reduction of human impact on the planet has led to discussions about environmental efficiency in the manufacture and use of automotive vehicles. The advancement of environmental and government laws has encouraged the automotive industry to seek constant improvements in safety, fuel economy and reduction of greenhouse gas emissions. To achieve these goals, reducing the weight of vehicles has been considered a relevant strategy, with several research and development efforts in search of high-tech materials and innovative design. The assessment of the life cycle of vehicles, from the extraction of raw materials to the end of their useful life, is essential for estimating environmental impacts. In this context, this paper focuses on the life cycle analysis of vehicles with new generation steel structures (Body in White Solution) compared to current steels (Body in White Baseline), aiming at reducing greenhouse gas emissions by reducing of the thickness of the steel plates, maintaining the mechanical properties necessary to guarantee the safety of the vehicle. The methodology of this study was divided into the evaluation of Body in White (BIW) mass in current steels (Baseline) and in advanced high resistance steels (Solution); detailing the vehicular life cycle from the extraction of materials to its end of life; in the estimation of greenhouse gas emissions through simulation and in the comparison of vehicle emissions with BIW in current steels and in advanced high resistance steels. As a result, it was possible to observe that, in the comparison of the CO 2 footprint, modeled in the Eco Audit, there is a 15% reduction in emissions in the CO 2 footprint for the BIW solution, as well as a 7% reduction in the C eq total , in the on-site test and a saving of 260.40 L in fuel consumption, that is, the reduction in vehicle weight plays a significant role in reducing CO 2 emissions, providing a mitigation factor for global warming. [Display omitted] • There is a 15% reduction in emissions in the CO2 footprint for the BIW solution. • There is a 7% reduction in the Ceq total, in the on-site test. • Reduction in vehicle weight plays a significant role in reducing CO2 emissions. • Providing a mitigation factor for global warming. • There is a fuel economy of 260.4 L over the vehicle's life cycle. [ABSTRACT FROM AUTHOR]

It is crucial for long-term carbon emission reduction to analyze how the government affects enterprises and customers to reduce carbon emissions and purchase low-carbon products. A tripartite evolutionary game among the government, enterprises, and customers is constructed. In addition, the evolutionary courses of the game among the behaviors of government, enterprises, and customers are examined. On this basis, the influence of internal and external factors on the results is analyzed. MATLAB software is used for numerical simulation analysis to simulate the influence of some parameters on the decision-making of game players. The analysis demonstrates that: the subsidy for enterprises has a more significant influence on the behavior of the government than on those made by enterprises and customers. At this point, enterprises and customers will take more account of the government's decision, which will lead to the strategies of "low-carbon production mode" and "purchasing low-carbon products," respectively. This paper focuses on the impacts of the low-carbon consumption subsidy policy and the "carbon inclusion" system on the evolution of the three parties. When carbon credits are at a reasonable level and low-carbon consumption subsidies are combined with carbon inclusion mechanism, it may be observed that the former is more effective in encouraging customers to purchase low-carbon products. In other words, this is the situation where the two policy implementations are most effective. Simultaneously, it will motivate enterprises to reduce carbon emissions and the government to positively regulate. • This study adopts the research perspective of carbon emission reduction. • A tripartite evolutionary game model is proposed to study stakeholders' strategies. • Government subsidy policies and carbon inclusion mechanism favor game outcomes. • Governmental policies in low-carbon consumption must be strengthened. [ABSTRACT FROM AUTHOR]

The issue of carbon emissions has become increasingly urgent in tandem with the rapid growth of the economy in the Pearl River Delta region. This paper uses kernel density estimation and standard deviation ellipses based on Pearl River Delta data from 2012 to 2021 to explore the spatiotemporal evolution trends of green financing and carbon emissions. Additionally, it uses a spatial Durbin model to examine the spatial effects of green finance on carbon emissions. The results indicate the following: Firstly, over the years, green finance shows an overall increasing trend, with an internal spatial pattern characterized by higher levels in the northeast and lower levels in the southwest. In contrast, carbon emissions are decreasing, with an internal spatial pattern characterized by higher levels in the southwest and lower levels in the northeast. Secondly, more and more green financing initiatives are aiming towards the Pearl River Delta's northeast, suggesting a more significant concentration of such initiatives there than elsewhere. At the same time, carbon emissions seem to converge on the southwest of the Pearl River Delta, which could indicate that this area generally has greater carbon emission levels. Finally, the spatial effect results reveal that improving green finance levels can significantly inhibit carbon emission levels in the Pearl River Delta region. Evidence of spatial spillover effects indicates that the carbon emissions in neighboring areas are influenced to some extent. This study on green finance and carbon emissions' spatiotemporal characteristics and spatial impact gives a development path and theoretical support for sustainable development goals in the global economy. • Studied the spatial evolution direction of green finance and carbon emissions. • Studied the spatial spillover effects of carbon emissions. • Studied the impact of green finance on carbon emissions. • Provided decision-making reference for carbon emission reduction. [ABSTRACT FROM AUTHOR]

In 2022, Saudi Arabia's anthropogenic greenhouse gas emissions amounted to 810 million tons of CO 2 e. The country has pledged to cut its emissions by 278 million tons of CO 2 e per year by 2030. This paper contributes a modeling view on the climate-related effects of various energy policies on the Saudi energy system. We use an energy system model designed to represent seven sectors in the Saudi economy. In addition to a baseline, which entails the continuation of current domestic policies, we look at a scenario that incorporates some of the plans announced by the Saudi government. We also examine the baseline scenario with a cap on total CO 2 emissions equal to those exhibited with the announced plans. The model then makes the necessary decisions to abate CO 2. We find that the energy system contributes 130 million tons of CO 2 e to the nationally determined contribution amount in 2030. Also, a non-prescriptive scenario that caps energy-system CO 2 emissions produces the same emissions reductions as the announced plans while lowering the present cost by 2030 by $70 billion. The corresponding implicit marginal abatement cost of CO 2 approaches 35 $/tonCO 2 by 2045. This cost would displace around half of crude and fuel oil use in the Saudi energy system. • Saudi Arabia plans to cut annual greenhouse gas emissions by 278 million tonsCO 2 e. • We use a multi-sector model built from the ground up for Saudi Arabia. • The energy system can contribute 130 million tons of CO 2 e in reductions in 2030. • We find a scenario that achieves GHG abatement at a lower cost than official plans. • The marginal value attributed to CO 2 approaches 35 $ per tonCO 2 by 2045. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

China's industry is facing a carbon lock-in (CLI) dilemma. Based on the complexity and dynamics of CLI, exploring diversified unlocking paths is an important way to achieve emission reduction goals. This paper innovatively applies system dynamics (SD) to the study of CLI prediction and unlocking path, and systematically constructs an industrial CLI SD model, trying to break the positive feedback mechanism of CLI through multiple causality and feedback chains. This paper simulates and predicts the changing trend of the CLI level of China's industry and 8 major subsectors from 2020 to 2050. At the same time, the random forest algorithm is used to select the regulatory variables of policy analysis. Compared with the previous research methods, the accuracy and objectivity of the selection of regulatory variables are improved, so as to test the effectiveness of the unlocking path under each scenario. The results show that (1) the whole industry faces a serious CLI problem and is still in a deep lock-in state. From the perspective of subsectors, the light, electromechanical, and textile industries have achieved unlocking; the oil and extractive industries are in a moderately lock-in state; the chemical, steel, and power industries are in a deep lock-in state; and the CLI situation is serious. (2) The results of the random forest algorithm show that R&D investment, the proportion of fixed asset investments in the energy industry, car sales, energy structure, and carbon emission industry structure are the most significant factors affecting CLI in each subsystem. (3) Compared with the existing economic development model, the technological, institutional, social, and comprehensive unlocking scenarios can all enable industry to achieve carbon peak and carbon unlocking in advance. However, the effect of each scenario is as follows: comprehensive unlocking scenario > technological unlocking scenario > institutional unlocking scenario > social unlocking scenario. (4) The unlocking times of the oil, chemical, steel, and power industries are relatively late in each scenario. To realize carbon unlocking in industry, these four areas should be focused on in the future. This study helps policymakers formulate reasonable policies to accelerate industrial carbon unlocking and promote the implementation of the "dual carbon" strategy. • The whole industry faces a serious carbon lock-in problem. • The technological, institutional, social and comprehensive unlocking scenarios can all achieve carbon unlocking in advance. • The comprehensive unlocking scenario has the best effect, and the social unlocking scenario has the worst effect. • The oil, chemical, steel and power industries should be focused on in the future. [ABSTRACT FROM AUTHOR]

To mitigate climate change and achieve sustainable development, Chinese governments have introduced "1+N" "dual-carbon" policy system aimed at reducing CO 2 emissions, transforming energy structures and controlling pollution. An effective policy mix and synergy is crucial for achieving the emission reduction targets and for ensuring the effectiveness of the policies, and it is therefore of great practical importance to provide a pathway for policy synergy based on assessing policy effectiveness. This paper selects three policies, namely the carbon Emission Trading System (ETS), Coal Control and Clean Utilization (CCCU), and Green Financial Reform and Innovation Pilot Zone (GFPZ), sets up ten scenarios, adopts difference-in-differences (DID) models to evaluate the impact, and give a pathway for policy synergy. The results show that ETS, CCCU, and GFPZ policies have significant positive effects on carbon emission reduction, energy structure transformation, and industrial environmental pollution control, respectively; CCCU has synergistic effects with ETS and GFPZ policies in controlling coal consumption and increasing the completion of industrial pollution control investments, respectively; while GFPZ policies have conflicting effects with CCCU and ETS in reducing carbon emissions and coal consumption, the GFPZ policy has conflicting effects with CCCU and ETS in reducing carbon emissions and controlling coal consumption. Finally, the study proposes a phased policy support system around carbon emission reduction in the power generation industry, energy structure transformation, and industrial environmental pollution control before 2030 and from 2030 to 2060. [ABSTRACT FROM AUTHOR]

The sustained growth of global aviation emissions has highlighted the urgent need for using Sustainable Aviation Fuels (SAFs) to replace traditional aviation fuels to mitigate emissions. SAFs can potentially reduce greenhouse gas emissions by 50%–90% compared to conventional jet fuels. This paper collected aviation emissions data from South American routes between 2019 and 2021, and the GWP100 method was used to convert CH 4 and N 2 O emissions into CO 2 equivalents. Additionally, emissions from the South American route between 2023 and 2070 were predicted, as well as the amount of subsidy required to promote the use of SAFs under four different scenarios. The result shows that adopting SAFs could reduce approximately 69.3 million to 113.53 million tons of CO 2 -equivalent emissions in South America by 2070. However, the South American aviation industry will likely embrace using SAFs only if the carbon trading price exceeds 0.273 times the difference between SAFs and jet fuel prices. • This study calculates the emission reduction effects under four scenarios. • The GWP100 method is used to convert non-CO 2 emissions into CO 2 equivalent emissions. • SAFs can reduce 69.3–113.53 million tons of CO 2 -equivalent emissions by 2070. • Using SAFs is profitable when carbon price exceeds 0.273 times SAFs-kerosene price gap. • Using SAFs earlier will increase subsidies by $3.65–4.56 billion every five years. [ABSTRACT FROM AUTHOR]

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction. • It explores the impact of Broadband China Policy on carbon emissions reduction. • Digital infrastructure development has positive impact on reducing carbon emissions. • The reduction effect is heterogeneous in regions with different characteristics. • Carbon emissions can be reduced at both industrial and individual levels. [ABSTRACT FROM AUTHOR]

The significant carbon emissions generated by China's sludge treatment industry cannot be ignored. However, with only a few recent well-executed studies on carbon emission reduction in the sludge treatment field, the literature awaits a more comprehensive assessment and prediction whether the sludge treatment industry can achieve the dual-carbon target. This article aims to fill this gap, holistically examining the carbon emission reduction potential in the industry. Using the moving average method and IPCC method, the projected carbon emission value of sludge treatment in China from 2021 to 2030 indicates a total net carbon emission of 0.3 million tons by 2030. This suggests that the sludge treatment industry is on track to meet the carbon peak target, leaving surplus carbon quotas or credits available to assist other industries for carbon emissions reductions. The study also finds that only incineration and composting demonstrate the potential to be able to partially offset carbon emissions through resource utilization in certain stages or processes. Therefore, the current sludge treatment methods do not yield comprehensive emission reduction effects and cannot provide sufficient contribution to China's dual carbon goals. To address this issue, the paper explores a new scheme that focuses on improving the sludge treatment process. The scheme comparative analysis reveals that, even with all sludge treatment methods optimized, the total net carbon emissions of the industry could only be reduced to 0.058 million tons. This reduction falls short of significantly mitigating carbon emissions to achieve the carbon neutrality goal. Therefore, industries unable to achieve substantial net carbon reduction may need to explore alternative measures, such as carbon sinks, to ultimately attain carbon neutrality. [ABSTRACT FROM AUTHOR]

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO 2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO 2 equivalent (MMT CO 2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions. [Display omitted] • The coal-to-clean-energy policy in rural areas has a positive climate benefit. • Priority should be given to replacing coal with natural gas in policy execution. • Heating and cooking with electricity will maximize climate benefits from 2038. • Climate impact caused by CH 4 emission during the energy lifecycle can't be ignored. [ABSTRACT FROM AUTHOR]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

The vigorous development of the digital economy (DIEC) offers a substantial potential for China and global economies to realize the goal of "double carbon". This study attempts to analyze the heterogeneous effect of DIEC on carbon emission reduction (CERE), in order to extend a valuable reference for effectively achieving the dual-carbon goal. Accordingly, the effect of DIEC on carbon emission scale (CESC) and carbon emission intensity (CEIN) are examined in this paper by using dual fixed effect model and intermediate effect model, respectively. The study findings show that, at first, DIEC significantly supports the CERE while significantly constraining the uplift in CESC and CEIN. Simultaneously, the CERE effect of DIEC contains digital economy dimensional heterogeneity, industry heterogeneity, production and life heterogeneity, and urban-rural heterogeneity. Finally, the DIEC boosts the technological innovation (TEIN) and residents' income (REIN) levels, in order to heighten the CERE. Further, improving invention technology innovation and TEIN is more conducive to catalyzing the reduction of carbon emission in the whole society and the production field. Conversely, the improvement of non-invention technology innovation and rural- and urban residents' income impedes CERE in the field of life. Thus, the implications of this study are of vital significance for China and the rest of the world to foster CERE and achieve the "dual carbon" goal through DIEC development. [ABSTRACT FROM AUTHOR]

The gas-steam-power system (GSPS) optimization is a complicated optimization problem considering economic and environmental benefits. This paper presents a multiperiod mixed integer linear programming (MILP) model for the GSPS in iron and steel enterprises simultaneously optimizing total cost and carbon emission reduction. It was used to determine the optimal operating strategy for the GSPS under multiobjective conditions. The model considers the influence of a blast furnace with top-gas recycling (TGR-BF) technology on the by-product gas supply and steam and power cogeneration system (SPCS) operation. The results showed that after the optimization aiming at the minimum total cost (Scenario A) and the maximum carbon emission reduction (Scenario B), the system total cost was the lowest (7.78 billion CNY) when the top gas recovery rate was 4%, and the carbon emission reduction peaked at 465,296.76 tCO 2 when the top gas recovery rate was 12%. After multiobjective optimization (Scenario C), it was found that the system achieved carbon reduction only when the total cost attained a certain value. A sensitivity analysis revealed that a reduction in the grid emission factor and an increase in the green power increased the carbon emission reduction. When the coal price increased to 1800 CNY/t or the power price decreased to 0.2 CNY/kWh, the optimal system operation strategy was consistent under different optimization objectives. These research results provide guidance for steel enterprises to reduce carbon emissions and total cost. • The optimization objective considers carbon emission reduction and cost. • Carbon-reduction technology affects steam and power cogeneration system scheduling. • Energy prices significantly affect the optimal operation strategy. • Total cost is the lowest (7.78 billion CNY) when the top gas recovery rate is 4%. • Carbon emission reduction peaks at 465,296.76 tCO 2 when top gas recovery rate is 12%. [ABSTRACT FROM AUTHOR]

Under carbon cap and trade policy, engineering machinery firms have engaged in remanufacturing and invested in carbon emission reduction technologies. However, they often struggle with a lack of funding, but carbon quota financing offers a solution. Taking a capital-constrained engineering machinery remanufacturer as the research object, this paper first formulates four decision models, i.e. (no capital constraints, no financing), (capital constraints, no financing), (capital constraints, carbon quota repurchase financing) and (capital constraints, carbon quota pledge financing), then the equilibrium results are compared. Finally, the numerical simulations are performed to study the impact of carbon emission reduction and quality uncertainty of recycled products. The results show that if remanufacturers possess adequate carbon quotas, carbon quota pledge financing can always improve profits effectively, otherwise, the effectiveness of financing strategies depends on the difference between extra profits and financing costs. Both financing strategies can increase the output of new products and reduce that of remanufactured products. Increasing the quality threshold of recycled products is beneficial for remanufacturing, environmental protection and profits. Investing in carbon emission reduction benefits remanufacturing and the environment, however, it reduces remanufacturers' profits in the short term. [Display omitted] • Quality uncertainty of recycled products is considered in remanufacturing. • The importance of improving quality threshold is revealed. • Financing and carbon emission reduction investment are considered simultaneously. • The optimal carbon quota financing strategies are derived. [ABSTRACT FROM AUTHOR]

Supply chain enterprises can solve the cost problem caused by emission reduction through the pledge financing of carbon emission rights. This paper aims to optimize the pricing and ordering strategy and carbon reduction decision of the supply chain based on the pledge financing of carbon emission rights, establishes the expected revenue model of the manufacturer and the retailer, and analyzes the mechanism of the carbon reduction decision of the supply chain on its pricing and ordering strategy, expected revenue and revenue distribution strategy. The results illustrate that the optimal order quantity and the optimal wholesale price maximize the expected revenue of the retailer and the manufacturer, regardless of whether the pledge financing of carbon emission rights is introduced. With the adoption of the pledge financing of carbon emission rights, there is an optimal amount of carbon emission reduction per unit of the product to maximize the optimal order quantity. When both order quantity and wholesale price are optimal, the present value of expected revenue for the retailer and the manufacturer increases with the amount of carbon reduction per unit of product. The upper and lower limits of the retailer's share of sales revenue rise and fall as the amount of carbon reduction per unit of product increases, respectively. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

Beijing-Tianjin-Hebei metropolitan area is a significant carbon emission center. The region's early achievement of peak carbon targets is critical to the nation's achievement of peak carbon targets. In this paper, it is proposed to use different orders of grey models to classify into three scenarios. Based on three scenarios, the grey multivariate convolutional model with new information priority accumulation is adopted to predict carbon emissions in the Beijing-Tianjin-Hebei region and select the scenario suitable for local development. The results show that: (1) The Beijing region has already achieved peak carbon, the Tianjin region may not reach its peak carbon target by 2030, and the Hebei region is expected to reach its peak carbon target by 2030. (2) The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. The low-speed growth carbon emission scenario is more in line with the future development of Tianjin city. The low-rate carbon reduction scenario is more in line with the synergistic governance of pollution reduction and carbon reduction in Hebei Province. (3) Beijing's population policy in the most recent years has been conducive to improving the local environment. Tianjin's medium-term population policy is more in line with the local area. Hebei's medium-term industrial structure reform is favorable to local development. • Grey correlation analysis is used to analyze the factors affected carbon emissions in a region. • The factors with high correlation are predicted by using grey prediction models of different orders. • The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. [ABSTRACT FROM AUTHOR]

Forecasting the future emission trajectories and the relating sensitive driving factors of emissions for cities is of great significance to formulate realizable CO 2 mitigation policies. To proceed the forecasting, studies on peak prediction and quantification of reduction potential at the city level are essential. However, the studies in the area are very limited. Selecting the Beijing-Tianjin-Hebei urban agglomeration (BTH) as the study region, this paper aims to contribute to the research area and provides implications for other cities or urban agglomerations. The Kaya identity and multi-scenario simulation were employed to predict the dynamic evolution pathways of CO 2 emissions from 2021 to 2035 and explore the differential CO 2 peak time, peak value, and reduction potential for 13 cities in BTH. Monte Carlo simulation, Mann-Kendall trend test and Sen's slope estimation method are jointly used to reduce uncertainties in estimation. The Monte Carlo simulation results show that most cities in BTH have already reached their CO 2 emissions peak, while Tianjin, Langfang, Cangzhou and Tangshan are expected to reach their peaks between 2025 and 2030. Among them, 5 and 8 cities have the risk of not reaching their peak before 2035 in the high consumption scenario (HCS) and extensive development scenario (EDS) respectively. Comparative analysis reveals that low-carbon scenario (LCS) and sustainable development scenario (SDS) have significant effects on emissions reductions. The top three cities in terms of accumulative emission reduction in 2021–2035 are Tianjin, Tangshan and Cangzhou, estimated as 117.82–250.75 Mt CO 2 in LCS and 217.77–454.10 Mt CO 2 in SDS, respectively. The results of sensitivity analysis reveal that the most critical driver of CO 2 emissions in Beijing is population, while that is GDP per capita for Tianjin. Langfang and Hengshui showed the highest sensitivity to energy intensity. Accordingly, these cities have differentiated concerns and priorities to achieve their carbon peak goal as scheduled. • Kaya identity and scenario simulation are combined to predict future CO 2 emissions. • The BTH would reach CO 2 emission peak by 2025, but the time varies on city-level. • Tangshan, Langfang, and Cangzhou are at greater risk of not reaching the peak by 2030. • Tianjin, Tangshan and Cangzhou have the greatest potential to reduce emissions. • Differentiated priorities are suggested for specific city's CO 2 mitigation targets. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

This paper presents an energy-sharing market coupled with carbon emission trading to quantify peer-to-peer energy-sharing markets' economic and environmental influences. We establish a bi-level peer-to-peer energy sharing market considering the interaction between energy prosumers and the system operator. An interaction algorithm and generalized Nash game are thus applied in this work. With the simulation results, we find that the daily disutility of provincial systems is reduced by about 7 ¥ when time-of-use electricity rates are applied. This pricing strategy can encourage prosumers to participate in energy-sharing transactions. The subsidies of electricity rates, carbon prices, and renewable energy investments can improve the social welfare of the whole system. Considering the development of power generation technology and emission reduction targets, the change of optimization parameters in the next 30 years is analyzed in the example. It can be concluded that the total CO2 emission in 2050 will be reduced to almost half of that in 2020 in the energy-sharing markets. The subsidy of renewable energy generation and stricter CO2 emission constraints may accelerate the reduction of carbon emissions. [Display omitted] • It is the first time to assess the environmental effect of peer-to-peer energy trading with actual data. • We analyze the peer-to-peer energy trading impacts on the carbon emission amount in China. • We compare the market participants' revenue and CO2 emission considering the different scenarios. • We develop a bi-level coupled emission right trading market to verify whether total emission is reduced. • The development of technologies and various energy structures are considered quantitatively. [ABSTRACT FROM AUTHOR]

Reducing agricultural carbon emissions is an essential lever for mitigating climate change and promoting high-quality agricultural development. Environmental regulation in the form of resource agglomeration, represented by the high-standard farmland construction policy, plays a vital role in the emission reduction process. Using the panel data of 31 provinces in China from 2001 to 2019 and taking the high-standard farmland construction policy as a quasi-natural experiment, this paper constructs a continuous differences-in-differences (DID) model to explore the impact and mechanism of environmental regulation in the form of resource agglomeration (RAER) on agricultural carbon emission reduction. The results show that RAER significantly reduces agricultural carbon emissions by an average of 3.9%. This conclusion still holds after robustness tests such as endogenous tests, eliminating policy interference, and sample reprocessing. This abatement utility is mainly realized through the technique effect of promoting green technology innovation and the composition effect of optimizing crop cultivation structure. Based on the resource attribute characteristics, the agricultural carbon emission reduction effects of RAER are, in descending order, capital and facility. Further study found heterogeneity in four aspects of the effect of RAER on agricultural carbon emission reduction: regional, planted crops, carbon emission sources, and carbon emission intensity. Therefore, decision-makers should deepen environmental regulation reform through resource agglomeration, implement adapting to local conditions for the high-standard farmland construction policy, and promote policy innovation and system optimization of agricultural carbon emission reduction. [ABSTRACT FROM AUTHOR]

The carbon peaking and carbon neutrality strategy have become China's national strategy. Given the significant regional differences in China, the Chinese government has proposed "one policy for one province" guiding principle for carbon emission reduction. This study takes Tianjin as a representative of "a province-level city with high degree of industrialization and prominent emerging industries", and Gansu Province a representative of "a province with a low degree of industrialization but the potential for green energy". Using the integrated modeling frameworkthis study conducts a comparative analysis of the hidden flows generated by inter-provincial inward and outward transfers and extracts a feasible model for carbon neutrality transformation. The study also focuses on carbon emission, GDP changes, carbon hidden flow change in trade and carbon emission reduction path. By comparing the results, this study identifies the mechanism of the industrial spillover effect and carbon emission spillover effect between the two regions. Then it concludes the "cross-regional transfer mode of high-carbon industries" of industrial carbon neutral transformation: more carbon emission allowances are allocated to developing regions represented by Gansu Province, implement regionally differentiated carbon emission reduction constraint policies, and achieve industrial spatial transfer through more inter-provincial transfer. The paper found that in implementing a regionally differentiated carbon emission reduction constraint policy (DE scenario), the transfer of high-carbon industries can achieve the "superposition effect" through inter-provincial transfer. Accordingly, three carbon policy mechanisms for cross-regional transfer of high-carbon industries are summarized. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy Internet (EI) is typically characterized by digitalization and clean energy that seeks to revolutionize the energy system and reduce carbon emissions. Even though several scholars conclude that EI accelerates the clean energy transition of energy system, since the controversial relationship between digitalization and energy consumption in academia, current studies on the carbon emission reduction advantages of the EI are still in dispute. This paper employs the effect of EI's construction on the carbon emission peak goal of China's energy system based on the system dynamics model and different scenarios. The simulation results find that: (1) the construction of the EI could enable China's energy system to meet the carbon reduction commitment in 2028, with a carbon emission peak of 11.61 billion tons; (2) As digitalization and clean energy become more extensively employed, rising energy demand is satisfied by the manner of consuming low-carbon electricity energy. This is thought to be the primary factor that could promote China to achieve the carbon peak goal earlier than expected; (3) The advancement of digitalization has further promoted the decoupling of China's economic growth from carbon emissions. It is projected that China's energy system will still achieve the carbon peak goal by 2030 when the expected annual GDP growth rate is increased to 6.32%, 5.75%, and 4.6% for the years 2020–2025, 2026–2030, and 2031–2035, respectively. These findings might provide a new perspective for quantitative research on the environmental outcomes of the EI and the relationship between environmental improvement and economic growth. [ABSTRACT FROM AUTHOR]

The construction sector is one of the main contributors to carbon dioxide (CO 2) emission and causes of global warming. CO 2 mitigation solutions are vital. New technologies can facilitate and improve these efforts. Thus, the paper reviews how new technologies of artificial intelligence and machine learning have contributed to CO 2 emissions reduction in construction and what techniques have been applied in the literature to provide significant information that will be beneficial for the construction sector design and management. The paper provides the results of a content review, including their contributions and gaps. A total of 78 papers were identified to develop the dataset. The method was a combination of systematic reviews, including co-occurrence analytical map development of the main keywords, co-authorship network analyses, publication source analyses, and content analysis, including theme identification and review of the selected papers, which were divided into five conceptual clusters based on their scopes: (1) sustainable materials and components design/production, (2) on-site vehicles and equipment, (3) energy and life cycle assessment, (4) optimization, decision-making and solution-based platforms, and (5) real-world monitoring. The content of each cluster of papers was also reviewed, and the potential gaps were identified and discussed. A set of directions for future research investigations were presented that can be a valuable source for researchers in their future research. This paper contributes to the current knowledge base by presenting insights into intelligent techniques in the construction industry to mitigate CO 2 emissions. [ABSTRACT FROM AUTHOR]

Taiwan's per capita carbon emissions ranks first in Asia. Whether Taiwan's current "2025 Non-Nuclear Homeland" energy transition policy can achieve the goal of greenhouse gas reduction is an issue that needs to be studied urgently. On the basis of studying the status quo of energy supply and demand and carbon emissions in Taiwan, this paper first uses an econometric model to predict Taiwan's energy demand from 2021 to 2030, and then uses a Markov chain model to predict its energy structure changes and CO 2 emission trends under different scenarios, and evaluates the impact of its energy transition policies on carbon emission reduction goals. On this basis, by comparing the carbon trading markets on both sides of the Taiwan strait, the feasibility of and obstacles to the cross-strait cooperation in the carbon trading market are discussed in depth, and the opportunities for future cross-strait cooperation in the carbon trading market are proposed innovatively. The empirical results of this paper show that the carbon emissions in 2025 under the energy transition policy will be reduced by 59.8–61.1 million tons compared with those without planning constraints, but compared with the carbon reduction target (a reduction of 124.8–133 million tons), there is still a long way to go. The contribution potential of the annual carbon emission reduction target is only 45.9%–47.9%, and the contribution potential in 2030 is 57.2%–60.1%. The current "2025 Non-Nuclear Homeland" policy is not in line with Taiwan's current reality, and it is difficult to achieve the expected carbon reduction goal. In order to realize the energy transition in Taiwan in the future, it is necessary to make overall planning of energy policies, explore the cross-strait power cooperation model, and gradually try to build a cross-strait carbon trading market. [ABSTRACT FROM AUTHOR]

Carbon emission reduction in the shipping industry is both an external requirement of the government and an intrinsic sustainable development task for ports and shipping enterprises. This paper constructs a tripartite evolutionary game model involving the government, port enterprises, and shipping enterprises, analyzes the evolution of the carbon emission reduction strategy choice of the three parties, and studies the mechanisms driving the interaction and influencing the subjects' choices. The results show that (1) to promote carbon emission reduction in the shipping industry, the evolutionarily stable strategy of the three stakeholders is as follows: the government actively regulates, the port enterprises actively reduce emissions, and the shipping enterprises actively reduce emissions. (2) With an increase in the additional cost of government regulation and a decrease in rewards to port enterprises, the probability of the government actively regulating carbon emissions reduction will rise, and the probability of port enterprises actively implementing carbon emission reduction will increase following a reduction in the additional cost and an increase in the opportunity cost of passive emission reduction. (3) An increase in government subsidies for shipping enterprises will lead to a decrease in the additional costs of active emission reduction and an increase in the probability of active carbon emission reduction. This paper provides policy recommendations for carbon emission reduction in the shipping industry, which will help all parties choose the optimal strategy and achieve carbon emission reduction goals as soon as possible. [ABSTRACT FROM AUTHOR]

Cities are the main source and gathering place of carbon emissions. Therefore, it is an effective way to reach peak CO 2 emissions before 2030 to make carbon emission prediction and implement differentiated carbon emission reduction schemes according to local conditions at the urban level. Taking Shandong Province as an example, this paper comprehensively explored the impact of 16 socio-economic factors on carbon emissions of different cities through the extended STIRPAT model. In order to reduce the uncertainty of the research results and achieve "one city, one policy", firstly, the influencing factors of carbon emissions in different cities were screened through ridge regression equation, which were used as specific parameters of different cities in the scenario setting. Secondly, based on the actual development of different cities, this paper obtained the scenario combination scheme by freely combining different influencing factors to predict the peak time and peak value of carbon emissions. Based on the above measures, it could not only reflect the heterogeneous development of cities, but also ensure that the research results are close to the actual development of cities. The results show that 16 cities in Shandong Province show differential peak attainment. Among them, 8 cities have the best peak year around 2025, 5 cities have the best peak year around 2028, and 2 cities can achieve the peak before 2030. A comprehensive analysis of the timing and peaking of carbon emissions suggests that the best overall peaking year for Shandong Province could be 2028. In addition, according to the different influencing factors of carbon emission peak in each city, a set of carbon emission reduction scenarios with urban differentiation reaching the peak is proposed. This could provide a more comprehensive path choice direction for local governments to formulate carbon emission reduction action plans. Furthermore, this paper could be used as a reference for other provinces in China or other national regions to explore urban differentiated carbon peaking and to formulate operable carbon peaking solutions. [Display omitted] [ABSTRACT FROM AUTHOR]

Some agricultural industries such as livestock and poultry farming produce "growing items" whose weight and value constantly increase over time. Growing items and their related industries are vital in supplying the needed food and fiber for the world population. More importantly, concerns for the preservation of natural resources have led to sustainable goals of reducing greenhouse gas emissions (GHGEs) released by growing items. Recently, an inventory system called "economic growing quantity (EGQ)" was designed for growing items. This paper designs, develops, and optimizes a sustainable model for EGQ system, entitled "sustainable EGQ (SEGQ)", where the hidden costs and revenues associated with the sustainability of growing items are considered under a carbon tax policy. The cost function incorporates purchasing, transportation, feeding, shortage, setup, holding, and carcass disposal costs as well as the tax costs of greenhouse gas (GHG) emitted from manure, feed fermentation, carcasses, holding and transportation processes. The revenue function takes the earned income from the sale of grown items as well as their byproducts into account. Accordingly, a nonlinear program (NLP) is developed to maximize the total profit. The novelty of this paper resides in its consideration of the reproductive patterns and byproducts of growing items, gradual sales, shortage costs, major sources of GHGEs and their hidden costs, and finally a design of the main variables to mitigate the GHGs emitted by the growing items. Findings demonstrate that the SEGQ model with reproducible items and profitable byproducts increases the growth cycle and decreases the quantity of growing items needed at the start of the inventory cycle. [Display omitted] • Sustainable design of the related variables to inventory management of growing items. • The reproductive patterns of growing items under carbon emission considerations. • The profitable byproducts of growing items. • Identification and mitigation of other main sources of GHGEs in growing items. • An NLP model of hidden related costs and revenues to growing items under gradual sell. [ABSTRACT FROM AUTHOR]

As countries pay more attention to the issue of global warming, the solution of carbon emission reduction has important practical value. Most of the existing literature studied the driving factors of embodied carbon emissions. This paper creatively focuses on the impact of technological progress on embodied carbon emissions and on the embodied carbon emissions of different technology-intensive manufacturing industries, and aims to find out the important role of technological progress on embodied carbon emissions. This paper constructs a multi-regional input-output model based on the world input-output table, and analyzes and compares the changes in carbon emission intensity and export-implied carbon emissions of G7 countries from 2000 to 2014. This paper introduces the SDA model to investigate the impact of technology effects on the embodied carbon emissions of G7 countries' exports, and decomposes the technology effects into carbon emission technology effects and intermediate production technology effects. This study divides the manufacturing industries into low-tech, medium-low-tech, medium-high-tech and high-tech industries, and aims to examine the impact of technological progress effect on manufacturing with different levels of technology intensity. The empirical results reveal that, first, the carbon emission technical effect and the technical effect of intermediate production together constitute the technical effect. The carbon emission technology effect has a significant effect on suppressing the embodied carbon emissions of exports, while the impact of the intermediate production technology effect is relatively small, and the direction of action is uncertain. Second, the overall technological effect reduces the embodied carbon emissions of G7 countries' exports, and offsets the embodied carbon emissions brought about by the scale effect to a certain extent. That is, technological progress can effectively reduce the embodied carbon emissions of exports. Third, technological effect has the most significant effect on the low- and medium-tech industries, and the low- and medium-tech industries are also the manufacturing industries with the most embodied carbon exports in G7 countries. Relevant policy recommendations for global carbon emission reduction are put forward at the end of this paper. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Due to the severe problems caused by global warming, controlling greenhouse-gas emissions has become an emerging topic around the world. This situation has led to the implementation of legislations, forcing companies to implement innovations and strategies to prevent and reduce carbon emissions. Nevertheless, the effectiveness of implementing these strategies and the estimation to fulfill Kyoto Protocol's 2020 target Emission Trading Schemes needs to be further analysed and discussed. This paper reviews the existing greenhouse-gas-emission legislations, as well as carbon offset programs worldwide. A detailed analysis on carbon emissions trends related to emissions penalties is shown for six major countries. The optimal penalty for emissions trading schemes is also analyzed and discussed in this paper. Future changes that could be made to the existing programs for enhancing their effectiveness are also suggested. It was found that carbon emissions decreased around 1.58% per year since Emission Trading Schemes implementation. Around 23.43% of CO 2 reduction can be reached after 10 years of Emission Trading Schemes implementation, compared to the trend when Emission Trading Schemes was not implemented. Despite Emission Trading Schemes implementation is extremely recent, based on the existing data a first estimation of the optimal penalty in achieving the maximum carbon reduction it was found around US$90.22 per tonne. However, as the implementation period of Emission Trading Schemes is still limited for most countries, it is necessary to explore similar analysis as future work. [ABSTRACT FROM AUTHOR]

Buildings are responsible for more than 40% of global energy usage and as much as 33% of global greenhouse gas emissions in both developed and developing countries. However, the study of carbon emissions over a building's life cycle based on Ecotect and building information modeling in developing areas of Nanjing has yet to be conducted. Therefore, the results and recommendations of this paper represent a contribution to the literature on this topic. The scientific value of this paper is that Ecotect and building information modeling can be helpful in simplifying the estimation of carbon emissions over a building's life cycle because they can provide a majority of the information and calculation tools necessary for performing an life cycle assessment (LCA), which may alleviate the problem of insufficient information when executing an LCA of a building. A sensitivity analysis was performed by changing several parameters to identify the parameters that have the largest impacts on the performance a building. A comparison of the life cycle carbon emissions for each stage showed that the operational stage is the largest contributor to carbon emissions. Approximately 85.4% of the total carbon emissions were generated during operation. The construction stage accounted for 12.6% of the total carbon emissions. Approximately 2% of the total carbon emissions occurred during the demolition stage. Compared to the total carbon emissions over the entire life cycle of the building, carbon sequestration by vegetation was minimal. Thus, these findings indicate that governments can achieve the greatest reductions in carbon emissions by targeting the operational phase of buildings. However, the opportunity for addressing non-operational phases should not be ignored because the average carbon emissions per working area per year of non-operational stages are far greater than those of the use phase. [ABSTRACT FROM AUTHOR]

China has a high agricultural output and is a significant carbon emitter; thus, reducing carbon emissions in the agricultural sector is crucial for achieving carbon neutrality. To address this, China implemented the National Agricultural Sustainable Development Experimental Demonstration Zone policy in 2018, in which reducing agricultural carbon emissions (ACE) is a subject of concern. We explore the impact of the policy on agricultural carbon emissions reduction (ACER) using the propensity score matching and differences-in-differences (PSM-DID) methods with a series of robustness tests based on the panel data of prefecture-level cities in China from 2011 to 2020. The results indicate that: (1) the policy significantly reduces carbon emissions and impacts carbon emission sources, with the results passing the robustness tests. (2) According to the mechanism test, agricultural financial support mediates carbon emissions reduction, and the policy reduces these emissions by decreasing the intensity of fiscal support. (3) The heterogeneity analysis illustrates that the carbon emissions reduction effect is more evident in cities with a small urban-rural income gap and a high proportion of agricultural output value. Finally, we provide suggestions to reduce carbon emissions from the perspective of national and local governments. This paper is particularly relevant for achieving sustainable agriculture development. [ABSTRACT FROM AUTHOR]

Promoting low-carbon development in the iron and steel industry (ISI) is essential for China to achieve the carbon neutrality targets. This paper separately adopts the Logarithmic Mean Divisia Index (LMDI) technique and the Mean Impact Value (MIV) method to analyze the impact of driving factors on the CO 2 emissions of ISI in the historical and future dimensions. Furthermore, this paper establishes the extreme learning machine model optimized by the bat algorithm (BA-BP) to explore the carbon emission reduction pathways of ISI in the business-as-usual (BAU) scenario, the low-speed, medium-speed and high-speed development scenarios considering the constraints of carbon neutrality targets. The results reveal that: (1) Production capacity and energy efficiency are important drivers of CO 2 emissions in ISI; (2) The emission reduction situation is not optimistic under the BAU scenario, and it is difficult to accomplish the carbon neutrality goals by 2060; (3) Under the most ideal emission reduction pathway (corresponding to the high-speed development scenario), ISI will reach its peak in 2022 with the peak value of 2143.42 MtCO 2. Compared to the peak year, the CO 2 emissions will be reduced by 654.69 MtCO 2 and 1558.61 MtCO 2 in 2030 and 2050, respectively. Moreover, the achievement of short-term and long-term emission reduction targets depends on production capacity decline and technological progress, respectively. The optimal emission reduction pathway provides a reference for ISI to formulate periodic emission reduction targets. • The improved extreme learning machine is employed to predict the carbon emissions. • The emission reduction pathways are explored under the carbon neutrality target. • Controlling production capacity is a crucial reduction strategy. • The energy rebound effect is supposed to be weakened. • The application of advanced technologies will greatly promote emission reduction. [ABSTRACT FROM AUTHOR]

The digital economy is of great significant for carbon emission reduction. To estimate the impact on carbon emissions of digital economy, this paper conducts nonlinear analysis with the combination of spatial DURBIN model (SDM) and panel threshold model (PTM). Moreover, this paper decomposes the carbon emissions reduction effect into direct part and spatial spillover part, further analyzes the action mechanism from the perspective of technology progress, energy use and industrial structure. The empirical results indicate that the digital economy and carbon emissions have inverted U-shaped relationship. Similarly, the spatial spillover effect of digital economy on carbon emissions is also inverted-U shape. The digital economy increases first and then reduces the carbon emissions. The robustness tests and endogenous analysis both support above conclusions. Compared with the indirect effect, the direct effect of digital economy on carbon emissions is significantly greater. Moreover, the long-term effect of digital economy on carbon emissions is greater than the short-term effect. The impact of digital economy on carbon emissions exists regional heterogeneity. Different from the eastern and central regions, the digital economy in western region promotes carbon emissions monotonically. The impact of digital economy on carbon emissions faces significant resource endowment thresholds, urban scale thresholds and innovative capability thresholds. The increase of energy use and non-green technology progress are the main paths to influence local carbon emissions in short term, while the green technology progress and industrial structure upgrade become dominant paths in long term. The active demonstration of industrial structure upgrade and technology spillovers drive the spillover effect of digital economy on carbon emissions in long term. This paper suggests that, the realization of carbon peak and carbon neutral needs to strengthen the digital economy and promote the regional cooperation in environmental governance. The green integration of digital economy and traditional industries is of great significant for carbon emission reduction. [ABSTRACT FROM AUTHOR]

Food production consumes a large amount of water consumption and generates huge amounts of greenhouse gas emissions. Quantitative study of impact food wastage imposing on water and greenhouse gas emissions contributes to public awareness that food wastage will further worsen the resource shortage and climate warming, reducing food wastage accordingly. This paper evaluates the impacts of food wastage in the consumption stage on water resources and the environment in China. The result indicates that in the year 2010, the wastage of major food in China was around 62818 M kg in the consumption link, accounting for 14.5% of the total food production, of which the plant food wastage takes up the majority. The loss of water resources (blue water plus green water) caused by food wastage is 60502 Mm³, more than 10% of the country's total water use. Food wastage has a serious impact on agricultural non-point source pollution and greenhouse gas emissions, resulting in a grey water footprint of 16292 Mm³ and 60.85 M ton of carbon emissions. Taking regional differences of food consumption into consideration, the proportion of water footprints and carbon emissions in the eastern and southern developed areas is relatively higher, while the plant food takes a relatively larger share in water footprints and carbon emissions in the western and central provinces. Reducing food waste is important to remove unnecessary burdens on the environment and natural resources. The optimization of resource utilization in the process of food production is conducive to effectively reduce water footprints and carbon emissions of food; healthy diets shall be popularized among citizens so that the animal food consumption which causes more water footprints and carbon emissions can be decreased, alleviating resource and environmental burdens through reduction of the wastage in food consumption. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions cause climate changes, and their impact on the environment continues to increase. As a result, there is an urgent need to accelerate efforts to reduce GHG emissions. In industry, the majority of the current methods of reducing GHG emissions depend on technical enhancements of the facility and equipment. These methods focus on local optimization for carbon emission reduction in enterprises and may require additional time, money and effort for satisfactory implementation. Unlike technical approaches that focus on the equipment, this paper proposes an approach that combines carbon footprint analysis and production planning. The carbon footprint of the entire company’s operational process can be analyzed systematically using this approach. Subsequently, carbon emissions can be reduced significantly through production planning and optimization. To test the effectiveness of the proposed approach, a pharmaceutical enterprise is employed as an example. A production planning model is constructed based on the energy consumption analysis of different units and equipment. Using this model, the carbon emissions of the enterprise can be analyzed, and the corresponding production plan can be developed. To determine the optimal solution, a hybrid discrete particle swarm algorithm is developed and tested based on real data collected from the pharmaceutical enterprise. The experimental results demonstrate that the proposed novel approach is effective and carbon emissions of the enterprise can be reduced by an average of 6.77%, or a reduction in CO 2 emissions of 610.2 tons per year. [ABSTRACT FROM AUTHOR]

Interactions between government and industry have the characteristics of leader-follower games. To protect the environment, the government uses regulations and economic instruments to indirectly influence operational and investment decisions in industry. The government needs to calibrate its policies while considering industry's self-interested, cost-minimizing reactions. In this paper, a leader-follower model is developed as a bilevel mixed integer linear program for the selection of carbon emissions mitigation measures. It is assumed that the government sets the emissions reduction target, percentage subsidy for mitigation measures, and economic penalty for excess carbon emissions; in response to these policies, industry then chooses mitigation measures to be implemented. The model is demonstrated with a case study on maritime shipping emissions, where a heuristic solution is identified using a fuzzy interactive optimization algorithm. The solution achieves 11.5% reduction in emissions through the implementation of six mitigation measures, of which only one is subsidized. General implications of these results for decarbonization policy are also discussed. [Display omitted] • A bilevel optimization model for industrial decarbonization portfolios is developed. • Government-industry interaction is modelled as a Stackelberg game. • The model is demonstrated on a maritime carbon emissions reduction case study. • Implications for policy development and engineering decision-making are discussed. [ABSTRACT FROM AUTHOR]

Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [ABSTRACT FROM AUTHOR]

To alleviate the negative influence caused by curtailment of renewable energy resulting from the "power determined by heat" of CHP, recent studies have proposed hybrid concentrated solar power and combined heat and power (CSP-CHP) to provide additional flexibility to power system to reduce renewable energy curtailment. However, for the power system with high wind power penetration in the future, hybrid CSP-CHP can only partially absorb wind power, and the CO2 emission from isolated CHP can also cause environmental pollution. Therefore, this paper extends the coupled power to gas (P2G) and carbon capture and storage (CCS) technologies to the hybrid CSP-CHP integrated energy system (IES), aiming to accommodate more wind power and further reduce CO2 emissions. First, the operation mechanism and mathematical model of the proposed integrated energy system are developed. Second, considering the increase in wind power permeability, a low carbon economic dispatch model to minimize economic cost is presented to optimize the proposed IES operation. Finally, in order to verify the validity of the proposed IES, different cases are compared in the simulation. The simulation result shows that the proposed IES has an excellent performance in wind power absorption and CO2 emission reduction. The proposed model emission is less than the base case by 72.4%, and greatly improve the level of wind power absorption. • Hybrid concentrated solar power and combined heat and power is used in energy system. • Power-to-Gas technology and Carbon Capture System are coupled in proposed system. • The system is put into a day ahead dispatch considering electro-thermal-gas trade. • 100% wind power absorption and 72.4% CO2 emission reduction are realized. [ABSTRACT FROM AUTHOR]