Search

Ports are essential and strategic nodes of international trade and economic activities. The integration of port resources helps enhance the optimal division of port functions to further promote economic development. This paper explores the evolutionary trends of port integration policy from 2011 to 2021 in China through a text-mining approach. We first used the Latent Dirichlet Allocation (LDA) topic analysis method to analyze the port integration policies and summarize the evolutionary trends of port policies. In addition, an association analysis was conducted to explore port integration policies' impacts by examining their relationships among the environmental protection, digitalization level, and port development scale. Our findings suggested that China's port integration policy has evolved from specific and simple to abstract and complicated at the managerial level. Port development has enriched from infrastructure construction to the ideology of economic development. Our findings show that China's port integration is gradually improving the port operation. The findings of the study contribute to the extant literature by analyzing the port integration policy evolution in China and can be referred to by other countries. • Text mining method was used to explore the port integration policy evolution. • Port integration policy evolved from specific and simple to abstract and complicated. • Port development enriched from basic infrastructure to the governance model. • The evolution of port integration policy was related to reducing carbon emissions in the port sector. • The evolution of port integration policy made the ports intelligent in association with digital technology such as big data and AI. [ABSTRACT FROM AUTHOR]

Climate change and the resulting extreme weather events bring significant economic losses and many unstable factors. It is an important means to actively seek environmental protection and climate governance countermeasures to meet severe challenges. As an environmental protection tool widely used by the Organization for Economic Cooperation and Development (OECD), environmental taxes are expected to play an important role in combating climate change and reducing extreme weather events. Based on public goods theory, collective cooperation theory, externality theory and double dividend theory of environmental taxes, this paper takes 36 OECD countries as research samples and empirically tests the role of environmental taxes in mitigating climate change process and reducing extreme weather events through the establishment of panel Auto-Regressive Distributed Lag (ARDL) model. The empirical results show that the environmental taxes on the whole is conducive to reducing the frequency of abnormal temperature weather and plays a positive role in reducing carbon dioxide emissions in OECD countries. Further research shows that environmental budget and environmental technologies play a positive role in the process of environmental taxes to delay climate change and reduce extreme weather events. In other words, we should attach importance to the investment of environmental protection funds and the research and development of environmental protection technology while carrying out environmental taxes. The robustness test shows that the main regression results of this paper have strong robustness. The research in this paper enriches theories and existing literature related to environmental taxes and climate change, and provides new research ideas and policy guidance for delaying the process of climate change and responding to extreme weather events. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions and climate change risk have become constraints on global economic sustainable development. Environmental regulation (ER) is a key method for achieving synergy in CO 2 and pollution reduction in China. This paper is the first study to explore the effects of ER on CO 2 emissions by exploiting the National Environmental Protection 11th Five-Year Plan (NEP11-FYP). The implementation of the NEP11-FYP significantly decreases CO 2 emissions by 19.73% in key environmental cities relative to other cities. Heterogeneity analyses suggest that this negative impact is larger in western cities and cities with more pressure to reduce CO 2 emissions. Scale effects, structural effects, and technical effects might be three potential influencing channels through which ER contributes to the CO 2 reduction effect. In addition, the results of the spatial externality of the NEP11-FYP demonstrate a positive spillover effect in neighboring cities within a distance of 300 km and a negative spillover effect in cities more than 500 km away. Our empirical findings provide policy implications for implementing low-carbon transition strategies and reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

In the context of China's carbon peak and carbon neutrality goals (the "dual carbon" goals), balancing economic development, environmental protection, and low carbon is a high priority. Therefore, exploring the impact of digital finance on carbon dioxide (CO 2) emissions is crucial. In this paper, we select the panel data of 241 cities in China from 2011 to 2020 and use the double logarithm model after verifying model forms to explore the impact of digital finance on urban CO 2 emissions. The results show a significant negative correlation between the level of digital finance and the intensity of CO 2 emissions. Heterogeneity analysis results show that the eastern region exhibits the greatest inhibitory effect, while the western region exhibits the lowest. The three sub-dimensions of digital finance can all reduce carbon emissions, but the usage depth dimension has the greatest reduction effect, while the coverage breadth dimension is slightly lower. Through mediating effect tests from two dimensions, we find that digital finance can achieve CO 2 emission reduction by promoting scientific and technological innovation. These findings have implications for understanding the carbon reduction effectiveness of digital finance and achieving the dual carbon goals. [ABSTRACT FROM AUTHOR]

This research study is one of the significant to offer an inclusive investigation of the impact of green finance correlated policies by applying text analysis approach and panel data from 28 states and 8 union territories between 2010 and 2020. The paper uses the SDID and illustrates that overall, India's green finance associated with policies have directed a substantial decrease in industrial CO 2 emissions during the study period. Furthermore, the paper determined that the Fintech growth pays to the reduction of SO 2 (sulfur dioxide) emissions and positively influences environmental safety and investment enterprises. India is a great competitor worldwide in green finance strategy operation, and controllers need to accelerate the design of green finance products and boost the volume of financial institutions to provide green credit facilities. Though minimalizing the risk fintech stances, policymakers should inspire fintech's to take part in environmental quality protection inventiveness that encourages green consumption actively. [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]

• A multi-objective model is proposed, which contains both the cost and carbon emission objectives. The sizing of the grid-connected converter is included. The carbon emission of the power from the grid is considered. The model can comprehensively describe the requirements of LVDC systems in the economy and environmental protection. • This paper considers the effect of EVs on the sizing of LVDC systems. Both the charging and discharging of EVs are fully used to reach better sizing and operation for the system. • A minimum fuzzy carbon emission method (MFCEM) is given to transform the multi-objective into a single objective. Compared with the linear weighting method, MFCEM is a useful method for finding a point on the Pareto front that balances cost and carbon emissions. Grid-connected low-voltage direct current (LVDC) systems offer a promising solution for achieving low-carbon buildings. However, a new challenge arises in sizing grid-connected LVDC systems, which is to fully utilize distributed renewable energy, energy storage, and load demand response to minimize both the economy and carbon emissions. To address this gap, this paper studies the sizing of grid-connected LVDC systems, considering the grid-connected converter, photovoltaic (PV), battery, and demand response of electric vehicles (EVs). Firstly, two objective functions are proposed, including the economy and carbon emissions. Secondly, constraints for sizing and operation are presented, with particular consideration given to the discharging of EVs and the corresponding cost of cycle-life loss. Finally, a minimum fuzzy carbon emission method (MFCEM) is proposed to solve the model, which can adaptively and objectively transform the multi-objective into a single objective. According to the case study, the proposed model comprehensively considers the cost and carbon emissions of grid-connected LVDC systems, and its feasibility and validity are verified. Compared with the linear weighting method, MFCEM is a useful method for finding a point on the Pareto front that balances cost and carbon emissions. [ABSTRACT FROM AUTHOR]

Forest carbon sink project (FCSP) has received growing attention for its outstanding advantages in carbon emission reduction, environment protection, and achieving the carbon neutrality objective. Using a government-social capital cooperation model, FCSP helps to revitalize the ecological and economic benefits of the forest with standard and efficient management. However, the management and operation barriers of FCSP implementation are complex, multiple and indefinite in the long run, which requires a comprehensive barrier evaluation framework. Hence, this paper is devoted to constructing a barrier evaluation framework for FCSP implementation in China with an integrated multi-criteria decision-making (MCDM) method. To this end, critical barriers are identified and the criteria system is constructed with a two-stage systematic literature review and interaction with the experts. Later, an applicable and comprehensive barrier evaluation framework is built, wherein the interval type-2 fuzzy set (IT2FS) is used to process fuzziness and uncertain information, the best-worst method (BWM) is adopted to determine the criteria weight, and the Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) is introduced for comprehensive barrier evaluation. The criteria weighting results indicate that FCSP implementation encounters challenges taking into account institutional and governance barriers (criteria weight: 0.3592), management barriers (0.2384), economic and market barriers (0.1637), knowledge barriers (0.0747), technical and infrastructure barriers (0.1639), C1 "Lack of clear leadership and policies" and C5 "Forest management performance" were determined the most significant criteria, A5 and A4 respectively performed the lowest and the highest barrier level. In sensitivity analysis, the ranking results were stable when the criteria changed, and Spearman's rank correlations of B2, B4, and B5 are significant. The results were validated by a comparative analysis with other methods with the help of Spearman's rank correlation coefficient, which reflects accepted high correlations (Spearman's pro values of BWM-IT2F-PROMETHEE II (Gaussian rule), BWM-IT2F-TOPSIS, and BWM-TFN-VIKOR are 1.00, 1.00, 1.00). The findings of the paper help the decision makers to develop more rational strategies and successfully implement the FCSP. [ABSTRACT FROM AUTHOR]

In the context of global warming and energy scarcity, regional integrated energy system (RIES) can effectively improve energy utilization efficiency and reduce carbon emissions. However, this leads to the increased complexity of the market transactions. To this end, based on the mixed game strategy, a multi-agent low-carbon optimal dispatch model of RIES is proposed in this paper. Firstly, to fully consider the low-carbon objective of the system, a reward and punishment ladder carbon trading mechanism and a ladder integrated demand response (IDR) model are developed. Then, the decision models of the energy management operator (EMO), multiple energy hub agents (EHAs) and the user load aggregator (ULA) are constructed respectively with the goal of economy, and carbon emission flows are introduced as constraints. The interactive trading process of various stakeholders is simulated by a mixed game with master-slave game nested bidding strategy. Finally, the economics and carbon emissions of the system in different scenarios are analyzed by examples, and the effectiveness of the proposed model is verified. Numerical simulation results show that the proposed method not only has good economic and low-carbon environmental protection benefits, but also ensures the interests of various stakeholders. • A multi-agent energy trading mechanism is proposed to realize low-carbon operation. • A ladder integrated demand respond model considering carbon compensation is developed. • A multi-agent optimization strategy based on mixed game is proposed. [ABSTRACT FROM AUTHOR]

National civilized city selection activity organized by Chinese government is a kind of policy taking both environmental protection and economic growth into consideration. It is of great importance to high-quality economic growth of China. This paper mainly selects data of 280 at and above prefecture-level cities in China from 2005 to 2016 and combines multi-stage difference-in-differences model to test the impacts of national civilized city selection on green total factor productivity (GTFP). The empirical results show that national civilized city selection activity can significantly promote the GTFP and have strong robustness. And the positive influence can be achieved through the mechanism of city innovation. In addition, heterogenous effects exist under different city administrative hierarchies and different regions. Finally, conclusions of this research for one thing provide empirical evidences for mutual development of economic growth and environmental protection; for another thing, this paper enriches policy evaluation researches of national civilized city by including environmental factors in total factor productivity calculation. • City carbon emission is used in evaluating green total factor productivity (GTFP). • National civilized city selection has positive impact on GTFP and is robust. • City innovation plays a vital role in the process of the policy promotes GTFP. • The policy effect varies in different city administrative hierarchies and regions. [ABSTRACT FROM AUTHOR]

• Integrated demand response mechanism (IDR) in the micro-energy grid can reduce the peak-valley difference of load, promote supply–demand balance and improve the economy of system operation. • Power to gas (P2G) and combined heat and power (CHP) devices can effectively improve the coupling relationship of electricity, gas, and heat in the micro-energy grid. • Through various devices in this paper, the inflexible operation strategy of the traditional micro-energy grid is decoupled, and the determining electricity by heat characteristic limitation of CHP units is relieved. • The simulation results show that the ladder-type carbon trading mechanism has a more potent binding force on carbon emissions and can effectively improve the environmental protection of the system. • In the process of solving, the sequence operation theory (SOT) methods can be used to solve the model quickly and accurately. The micro-energy grid can meet various load demands and realize the complementary advantages of different energy sources, which provides a new way to solve the problems of energy utilization efficiency and environmental pollution. However, how coordinating multiple energy sources and improving the flexibility of the micro-energy grid is an urgent problem to be solved. This paper proposes an optimal scheduling model based on chance-constrained programming (CCP), which considers electric vehicle (EV) charging characteristics, integrated electricity-heat demand response, and ladder-type carbon trading in the background of various renewable uncertainty. Firstly, this paper uses power to gas (P2G) technology and combined heat and power (CHP) technology to improve the flexibility of the system and realize the coupling between different energy sources. Secondly, integrated demand response (IDR) is used to explore potential interaction capabilities between electric-heat flexible load and micro-energy grid. Then, the ladder-type carbon trading mechanism is introduced in the optimization scheduling model to reduce the carbon emissions of the system. Finally, sequence operation theory (SOT) transforms the original CCP model into a conveniently solvable mixed-integer linear programming (MILP) model. The simulation results show that all subsystems are closely coupled due to the participation of P2G and CHP, which reduces the operation cost of the system by 3.9 %. The results also indicate that the IDR mechanism improves energy efficiency and reduces operating costs by 7.8 %. Finally, the results substantiate that the ladder-type carbon trading mechanism reduces the carbon emissions of the system by 18.1 % and improves the environmental benefits of the system. [ABSTRACT FROM AUTHOR]

• The optimal scheduling model for VPP to participate in carbon trading and green certificate trading is established. • The reverse search strategy and dimension mutation strategy of the proposed SCV-PSO algorithm can significantly improve the performance of the algorithm. • The proposed optimal scheduling model can significantly improve the economy and environmental friendliness of VPP operation. The grid connection of large-scale clean energy provides the possibility for the establishment of a clean energy system. The urgent problem that needs to be solved is how to improve the utilization efficiency of clean energy to reduce carbon emissions. First, the virtual power plant (VPP) operation mode under the carbon trading and green certificate trading mechanism is analyzed. Secondly, this paper incorporates carbon trading mechanism and green certificate trading mechanism into the optimal dispatch model of VPP including wind power generation, photovoltaic power generation, gas turbines and energy storage device. Taking the net profit of VPP as the optimization goal, which can take into account both economic and environmental protection. Based on whether VPP participates in carbon trading and green certificate trading, three schemes are established and compared and analyzed. In addition, to cope with the volatility of renewable energy, the utilization rates of the renewable energy output scenarios for four typical days under the three schemes were compared and analyzed. To solve this problem, this paper proposes the Self-Conclusion and Variational Particle Swarm Optimization (SCV-PSO) algorithm. The simulation results show that the VPP optimal scheduling model and solving algorithm proposed can effectively improve the utilization rate of renewable energy and reduce the carbon emission under the premise of ensuring economic efficiency. It can provide a useful reference for the low-carbon economic operation of the power system in the future. [ABSTRACT FROM AUTHOR]

• China's sustainable development relies on agricultural trade and carbon emissions. • Carbon emission transfer index in agricultural trade is measured. • Decoupling-recoupling model and integrated prediction model are constructed. • A unified framework for trade, environment and technology is established. Under the new development pattern of domestic and international "dual circulation" in China, studying the relationship among green technology innovation, agricultural trade deficit (ATD) and carbon emission transfer embodied in agricultural trade (ATCT) becomes crucial for achieving coordinated and unified high-quality economic development and efficient environmental protection. Based on this, the paper uses environmental input–output model, "two-stage" decoupling and recoupling model, panel vector auto-regressive model, spatial econometric model and "rolling" Grey-BP neural network prediction model to explore present status of ATD, ATCT and their relationship, driving role of green technology innovation, as well as whether that relationship will be improving in the future. The results reveal the following: (1) China's ATD and ATCT show an increasing trend year by year, and their inter-provincial differences are gradually significant over time. The overall relationship between ATD and ATCT does not display ideally, which makes it necessary to quickly transform that relationship into reasonable and ideal state. (2) Green technology innovation has significant positive "U-shaped" and inverted "U-shaped" local effects on ATD and ATCT respectively, with a reasonable range of ATD reduction while ATCT increase valuing from 0 to 0.290, and has significant positive "U-shaped" spatial spillover effect on both without any reasonable range. The short-term effect of green technology innovation on coordinated promotion between ATD and ATCT is superior to the long-term one. (3) Green technology innovation has a significant regional heterogeneity. Regional differences must be taken into consideration seriously, and the measures adapted to local conditions are crucial. The role of fundamental and progressive green technology innovation has heterogeneity, which means that targeted development and utilization of green technology products are important. (4) Regardless of the time horizon, the relationship between ATD and ATCT will improve, which can provide a key step for coordinated development of economy and environment in agricultural trade. Therefore, in order for China to implement and promote further opening-up, reduce agricultural trade dependence, ensure food security and important agricultural product supply, as well as achieve the unity of high-quality economic development and ecological efficient protection, it is necessary to reasonably reverse trade deficit and increase carbon emission transfer in agriculture. [ABSTRACT FROM AUTHOR]

With the current decreasing fossil resources and increasing carbon dioxide emissions, researchers are increasingly concerned about the development and utilization of biomass resources. The development of bio-based waterborne polyurethanes (BWPU) provides a new direction for the utilization of biomass resources and the protection of the environment. BWPU has attracted much attention from academia and industry due to their good physical and chemical properties, no volatile organic compounds (VOCs) emissions, exploitation of renewable substances, and structural design-ability. BWPU typically includes the polymerization of bio-based monomers, such as animal and vegetable oils, the addition of bio-based nanofillers, such as cellulose, lignin, and chitosan, and antimicrobial modifications, such silver nanoparticles and carvacrol, which can effectively replace traditional petroleum-based resources. At present, there are few reviews on the synthesis and applications of BWPU. Therefore, this paper reviews the recent progress in the synthesis of BWPU, and focuses on its applications in coatings, adhesives and antimicrobials, which is expected to provide reference and summarize research priorities and issues. [Display omitted] • Summarize bio-based waterborne polyurethanes (BWPU) recently produced from bio-based raw materials. • Summarize the current applications of BWPU, including coatings, adhesives and antimicrobials. • Suggestions are provided for further future research by BWPU in other areas. [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]

Hybrid shared energy storage based on electro-thermal coupling is an economical and effective way to solve the mismatch between the demand and supply of multiple multi-energy microgrids (MEMGs). However, its impact on the environment is often ignored. How to take into account economic development and environmental protection by optimizing its capacity configuration has become a key challenge. From the perspective of economy and environment, this paper explores the comprehensive benefits and capacity configuration of electro-thermal hybrid shared energy storage (ET-HSES) while considering the carbon trading mechanism and the coupling system of power to gas (P2G) and carbon capture system (CCS). Firstly, an energy sharing framework between the ET-HSES and the MEMGs is built. Secondly, a bi-level optimization model is constructed for the optimal scheduling problem of different stakeholders. Thirdly, Karush-Kuhn-Tucker (KKT) optimality conditions and Big-M method are used to transform the bi-level model into a single-level model. The results show that ET-HSES can effectively save the capacity of energy storage equipment, significantly reduce the operating costs and carbon emissions of MEMGs, and improve the income of ET-HSES operator (ET-HSESO). The combination of carbon trading mechanism and coupling system of P2G and CCS can effectively reduce the operating costs and carbon emissions of MEMGs. Meanwhile, it will also reduce the benefits of ET-HSESO. [Display omitted] • The coupling system of P2G and CCS is integrated into the MEMG system. • The energy trading mechanism between ET-HSES and MEMGs is presented. • A solution of the bi-level programming model based on KKT condition is proposed. • Realize a balance between economic development and environmental protection for MEMGs by introducing an ET-HSES. • The benefits of ET-HSESO are reduced by combining the carbon trading mechanism and coupling system of P2G and CCS. [ABSTRACT FROM AUTHOR]

• Heat integration and dynamic control of reactive pressure-swing distillation for separating tetrahydrofuran/ethanol/water were investigated. • Three generalized and robust control strategies that can resist ±20% feed disturbances were proposed for RPSD. • The TAC and exhaust emission (CO 2 , SO 2, and NO) were greatly reduced while the dynamic control performance was improved. In this paper, heat integration and dynamic control of reactive pressure-swing distillation (RPSD) for separating tetrahydrofuran/ethanol/water was investigated from the aspects of energy consumption, environmental protection and practical applications. By exploring the heat exchange between separating tetrahydrofuran and ethanol distillation columns, the full heat integration process (FHI) was designed. Robust control of heat and non-heat integrated processes was realized based on the dual temperature control structure. All processes were resistant to ±20% feed flow and composition disturbances. Finally, these processes were compared from three aspects: economy, environment and dynamic performance. The results show that compared with the non-heat integration process, the FHI process can reduce the total annual cost by 24.14%, the CO 2 emission by 20.21% and the SO 2 and NO emission by 34.38%, meanwhile, having the best dynamic performance. This study is valuable and instructive in promoting the integrated optimal and control design of the RPSD process. [Display omitted] [ABSTRACT FROM AUTHOR]

• The factors that affecting urban carbon emissions efficiency (CEE) are explored. • The carbon emissions of 282 cities are estimated with the aid of nighttime light data. • Urban CEE has significant and positive spatial spillover effects. • Industrial agglomeration and collaboration are key to green production efficiency. This paper explores the factors that improve the efficiency of urban carbon emissions. Based on nighttime light data, the carbon emissions of 282 cities in China from 2004 to 2018 are estimated, and the carbon emission efficiency (CEE) is measured. The spatial autocorrelation results show that CEE in Chinese cities has significant and positive spatial spillover effects. The LISA low-low type cluster area of CEE presents an evolutionary trend of westward migration, and eventually formed two low-efficiency centers in the Central Plains city group and the Sichuan-Chongqing city group. The empirical results of the spatial Durbin error model show that urban population expansion, economic growth and R&D investment have effectively improved CEE, but industrial scale and agglomeration adversely affect CEE. In addition, human capital investment and foreign investment have not exerted their due green growth effects. Manufacturing agglomeration had a negative impact on local CEE, but had a warning effect on neighboring regions. Different from the manufacturing industry, the agglomeration of producer services industry can bring significant improvement to CEE, accompanied by a demonstration effect which can promote the CEE in adjacent regions. Further, this paper finds that developing the synergy between manufacturing and producer services industries can significantly restrain the negative effects of industry on CEE. This paper enriches the performance evaluation framework of low-carbon city development in theory, and varies the situations that previous researches only concerned about carbon emissions while ignoring emissions efficiency. This paper is a beneficial policy practice of the coordinated development of economic growth and ecological environmental protection in the regional coordinated development mechanism, which indicates that strengthening industrial collaboration can effectively improve the efficiency of green production in cities. [ABSTRACT FROM AUTHOR]

Reducing CO 2 emission is particularly important for environmental protection. Much absorbed CO 2 in the conventional Rectisol process is discharged as tail gas due to the lacked attention to the by-product CO 2. In this paper, a novel CO 2 capture process, which is improved from the conventional Rectisol process, is proposed to reduce the emission of CO 2. The revised CPA model shows a good performance and is used for the process simulation. Spin-up method is employed to optimize the CO 2 capture process and uniform test method is used to further verify the optimization procedure. The results show that compared with the conventional Rectisol process, the system exergy consumption increases by 17.81%, but the exergy consumption per unit CO 2 is 64.57% lower in the optimized CO 2 capture process. The parameters in terms of the first-stage temperature T fi , second-stage pressure P se , and third-stage temperature T th are analyzed, which show similar influence rules for the CO 2 capture process. In addition, exergy distributions about the Rectisol process and the optimized CO 2 capture process are investigated for the further thermodynamic analysis. This paper may guide for the improvement and optimization of more profound CO 2 capture process. • A novel CO 2 capture process based on Rectisol process is proposed. • Major parameters in the capture process are optimized. • Compared with the Rectisol, exergy consumption per unit CO 2 is 64.57% lower in the novel process. • The whole exergy destruction of the novel process is 1932.63 kW lower than the Rectisol. [ABSTRACT FROM AUTHOR]

As China's largest source of carbon emissions, the power sector's transition to lower levels of carbon emission intensity is critical to achieving China's carbon emission (CE) reduction commitments. In this paper, the CE intensity of electricity generation (CEIE) in 30 provinces from 2000 to 2019 is calculated, and the temporal evolution and spatial distribution characteristics of CEIE are discussed. Then, the spatial spillover effect of each driving factor on CEIE is calculated using the spatial Durbin model. The CEIE reveals a first increasing and then decreasing trend, and the regional differences gradually decrease. Simultaneously, the CEIE has a significant positive spatial correlation, and the overall spatial distribution pattern is high in the northeast and low in the southwest of the country. Economic development and foreign trade both inhibit CEIE, while electricity consumption, research and development, unit operation level, and power structure all promote CEIE. Each driving factor's influence on regional CEIE exerts a spatial spillover effect. Among them, the spatial positive spillover effects of industrial structure and environmental protection investment are the most obvious, while the spatial spillover effects of other driving factors are not apparent. Furthermore, these findings provide practical insights into policy adjustments and the coordinated interregional development of low-carbon electricity. [ABSTRACT FROM AUTHOR]

In recent years, the green transformation of the traditional energy industry and the reduction of carbon emissions have attracted widespread societal attention. In the thermal recovery process of heavy oil, the low heat utilization rate has always been the bottleneck restricting its production. In addition, the associated flue gas emissions also pose a considerable challenge to environmental protection. In this paper, flue gas and SiO 2 aerogel were jointly applied to reduce steam heat loss while achieving exhaust gas sequestration. Condensation heat transfer experiments were carried out to explore the mechanism of the two affecting the heat dissipation process of steam liquefaction. A series of displacement experiments with different injection methods in a one-dimensional sandpack were performed to select combinations of developing heavy oil with high efficiency and low carbon. By detecting the temperature changes of the model and calculating the final storage volume, the effects of promoting steam chamber expansion and flue gas sequestration were evaluated. The results showed that the aerogel adsorption layer could change the wettability of the condensing surface, thereby showing the characteristics of film condensation. Flue gas molecules could be captured by aerogel nanofluids, further exerting a synergistic thermal insulation effect, and the temperature of the deep reservoir increased by 7.7 °C. Simultaneously, the crude oil recovery increased by 8.8% compared with pure steam flooding. Moreover, the numerous nanoparticle-stabilized foams generated via this method were noted as an essential way to sequester carbon in a high water-cut formation, and the final sequestration rate reached 77.4%. • The temperature of deep reservoir increased by 7.7 °C when simultaneously applying flue gas and SiO 2 aerogel nanofluids. • The oil recovery improved by 8.8% compared with steam flooding. • The carbon sequestration rate in thermal recovery reached 74.4%. [ABSTRACT FROM AUTHOR]

The rise in global carbon emissions has led to serious ecological problems and highlighted the need to better pursue the sustainable development of coal-fired power plants. To reduce environmental pollution, this paper proposes a hybrid dynamic coal blending method under an uncertain environment to achieve a trade-off between economic development and environmental protection. This method fully considers seasonal pollutant variations, a dynamic carbon emissions quota allocation mechanism. A practical case from the Jintang coal-fired powered plant is given to verify the efficiency and practicality of the proposed optimization method. The model allows decision-makers to promote cleaner production by developing coal blending schemes to suit relevant national and local carbon and inhalable particulate matter emissions reduction policies. The results of the sensitivity analysis also confirm this view and show that the model is stable and has emission reduction limits. Specifically, compared with the maximum emissions, the model can reduce carbon emissions by about 29.1% (2.625 × 106 tonnes) and inhalable particulate matter emissions by 29.7% (0.64 × 106 tonnes). The results demonstrated that the hybrid dynamic coal blending method was able to achieve carbon emissions and inhalable particulate matter emissions reductions and that appropriate environmental constraints can improve emissions performance and encourage sustainable CPP development. [Display omitted] • A hybrid dynamic multiple objectives coal blending method is built. • The conflict between economic, ecological, and carbon emission reduction targets has been fully analyzed. • A case study is adopted for illustrating the applicability of the proposed equilibrium approach. • The results found that the model achieved a trade-off between economic benefits and environmental impact. [ABSTRACT FROM AUTHOR]

Recent world events have put a spotlight on inclusive project financing models that tackle climate change and reduce carbon emissions in the construction and management of buildings. A cardinal example of such models is green finance, an inclusive term that integrates environmental protection and social justice with economic profits in green buildings. This paper probes into the terminology and links the concept of green finance to green buildings. The study utilizes a systematic literature review methodology to analyze and synthesize existing literature. The outcomes of the study show that increased economic returns, clear regulations, and awareness creation drive its acceptance in the built environment. However, as a developing concept, the major challenge is the contradictions of what constitutes green finance for green buildings. The results of this study draw the attention of key stakeholders to develop and merge the two concepts in research and practice to attain ecological balance in the financial market and the built environment. [ABSTRACT FROM AUTHOR]

Achieving the peak of carbon dioxide (CO 2) emissions requires a large amount of green and low-carbon investment. Whether the green finance system can efficiently support the capital need for achieving the CO 2 emissions target in the context of the COVID-19 epidemic is a matter of concern. This paper constructs a system dynamics model (SD model) to illustrate the quantitative relationship between the green finance system and CO 2 emissions and introduce the COVID-19 epidemic as a variable to analyze ten simulation scenarios regarding the carbon emissions commitment realization under different green finance and economic growth status. It is shown that: (1) Regardless of the impact of COVID-19, China can meet its commitment by reaching its CO 2 emissions peak in 2030 and realizing a 20% non-fossil energy proportion in 2025; (2) Under the impact of the epidemic, the goal can not be obtained in all energy consumption scenarios when the government expenditure on the environment is low. The target year of reaching CO 2 emissions peak becomes 2033, 2037, and 2040. The results indicate that reducing government expenditure on environment protection makes the CO 2 emissions peak target less likely to be achieved within a given time frame. We also concluded with important policy implications according to the result of the simulations. Overall, this study makes a reference for other economies and researchers to quantitatively predict the interaction relationship between the green finance system and CO 2 emissions in the context of COVID-19, which provides policymakers with insights into a joint power of energy consumption upgrading and green capital guidance. • Providing empirical studies regarding the mechanism of the inhibitory effect of green finance on CO 2 emissions. • Using systems dynamics model to address the missing data problem. • Making solid suggestions under COVID-19 Epidemic. • Building the relationship between the green finance system and CO 2 emissions and making forecasts for "3060" mission result. [ABSTRACT FROM AUTHOR]

By using Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, this paper explores the influence of electricity generation and technological innovation on CO 2 emissions, as well as that of population and economic growth, in China during the period of 1985–2019. Econometric methods of smooth transition regression (STR) are used to calculate the threshold effects of the linkage among the selected variables. The conversion function of LSTR(1) (logistic STR with one regime switch) is selected by F-statistics based on third-order Taylor approximation. The results of the diagnostic test indicate that when the growth rate of electricity generation exceeds 8.914%, the relationships become nonlinear. Moreover, 1% increases of electricity generation and technological innovation may lead to increases of 2.91664% and 0.31016% in China's CO 2 emissions, respectively, while a 1% increase in economic growth can decrease China's CO 2 emissions by 1.16441%. Finally, some implications are suggested, such as strengthening the publicity surrounding environmental protection to reduce the footprint of CO 2 emissions, extending the green GDP even further, and building a more diversified power supply structure. [Display omitted] • Nonlinear STR model is established based on STIRPAT model in China. • Positive impacts of population, electricity, and innovation on emissions are found. • Economic growth may lead to emissions reduction. • Translation of technological innovation should be advocated. [ABSTRACT FROM AUTHOR]

whether political resource endowment affect regional low-carbon economic development has attracted the attention of many relevant stakeholders. Given that, by using remote sensing data such as nighttime light data and introducing the spatial econometric models, this paper selected 519 counties covering 69 prefecture-level cities in China's 14 provinces to explore the impact of political resource endowment on carbon productivity at the county level. The results showed that regional carbon productivity along the Long March areas was more 12% higher than that along non-Long March areas. Moreover, a series of robustness tests also verify that political resource endowment can effectively promote regional carbon productivity. Additionally, regional industrial structure is the most significant influencing factor in reducing carbon productivity. Our results also showed economic benefits generated from per unit carbon emissions in these counties along the Long March areas were obviously higher than those of counties along the non-Long March areas, indicating that counties along non-Long March areas should pay more attention to improving the balanced development of economic growth and environmental protection. Finally, for counties along the Long March areas and their surrounding regions, their carbon productivity spatially presents the typical spatial autocorrelation trend. Therefore, it is necessary to combine the transformation of industrial structure with the optimization of industrial spatial layout, and formulate the targeted improvement plan on carbon productivity for counties along the Long March areas to achieve coordinated low-carbon development. • The impact of political resource endowment on regional carbon productivity is explored; • Carbon productivity of counties along the Long March areas is higher than that of other counties; • Industrial structure hindered the growth of carbon productivity along the non-Long March areas; • Carbon productivity of counties benefitted from the endowment of political resources. [ABSTRACT FROM AUTHOR]

Shifting from fossil-fuel (FF) to renewable energy systems, a process known as energy transition (ET ) , is crucial for developing countries as the ET brings new opportunities to accomplish leapfrog development for achieving carbon neutrality. Parallel to climate change, developing countries face energy security and independence issues with extra pressures such as the Covid-19 pandemic and increasing inequality. Taking Mexico as a case, four ET scenarios under "gradual" or "rapid" narratives are developed with the Kaya Identity. Gradual Transition Scenarios (GTS) present a business-as-usual scenario with natural gas as the most significant fuel in the supply mix due to economic and social concerns. Rapid Transition Scenarios (RTS) propose a combination of FF and renewables or a full deployment of Renewable Energy Sources (RES). The results show that GTS reach 491∼ 501 Mt CO 2 emissions in 2050, risking a carbon lock-in, stranded assets and economic losses. RTS reach 87∼103 Mt CO 2 in 2050 with RES prioritization, energy efficiency improvements and coal phase-out. In particular, following GTS would mean failing to join global efforts to limit warming temperature to 1.5 °C. Alternatively, following RTS brings Mexico closer to achieve carbon neutrality. Several strategies are proposed, including reducing the carbon intensity of the energy supply mix, increasing energy efficiency, prioritizing environmental protection, improving actions based on science, and promoting environmental education and awareness. This paper presents a consistent methodology to encourage ET in developing countries where the role of science is still not fully exploited under the goal of carbon neutrality. [Display omitted] [ABSTRACT FROM AUTHOR]