Search

At present, the energy and environmental crisis is increasingly prominent, and how to solve the global energy and environmental problems is one of the challenges facing the world today. China is a major producer and consumer of organosilicon, so it is necessary to explore the stage of high energy consumption and high pollution in the organosilicon industrial chain. In 2022, the proportion of submerged arc furnaces of 25000 kVA and higher in China reached 40%. Further expansion of these furnaces in the future is inevitable. However, research on the life cycle assessment of organosilicon manufactured using large-capacity submerged arc furnaces is still blank.Therefore,in this paper, the life cycle assessment method is used to evaluate the synthesis process of chemical grade silicon-organosilicon monomer prepared by large capacity (33000 kVA) submerged arc furnace, and the dominant process in various environmental impacts is defined.At the same time, the measures to improve the production process of organosilicon monomer were put forward. In the production process of 1000 kg organosilicon monomer, global warming potential (GWP) contributed the most (73.43%) to the comprehensive environmental impact, followed by chronic public health impact (HTI, 10.55%). Energy consumption (EN) accounted for 8.50%, while resource consumption (RU) accounted for 7.43%. The contributions of other environmental factors were relatively small (0.09%).The energy consumption and environmental pollution in the production of organosilicon monomer can be reduced by strictly controlling the quality of raw materials into the furnace, using heat pump technology in the distillation unit, and comprehensively utilizing the heat of reaction by-products and steam condensate. [Display omitted] • This study is the first one in China to conduct LCA for the preparation of chemical grade silicon-organosilicon monomer synthesis process in 33000 kVA submerged arc furnace. It provides the best improvement suggestions for reducing the environmental load of the product life cycle process and achieving cleaner production. • In response to the national development policy of large-scale submerged arc furnace, the dominant process of preparing organosilicon monomer based on 33000 kva submerged arc furnace in various environmental impacts was clarified. • The main technical improvement directions are: Strictly control the quality of raw materials for submerged arc furnace; Strictly control the sulfur content and nitrogen content of carbonaceous reductant, and adopt the most suitable flue gas treatment technology route; Smelt with large submerged arc furnace; Use heat pump technology for distillation unit; Optimize the monomer synthesis device. [ABSTRACT FROM AUTHOR]

Heat storage is a critical measure to realize the utilization of waste heat and to enhance the heating capacity of the medium-deep U-type borehole heat exchanger (MDUBHE) system. However, the effects of heat storage on the operation of the MDUBHE system remain unclear. The effects of heat storage measures on the building and the environment have not been assessed. In this paper, the effects of heat storage measures on system performance are revealed and assessed using the numerical heat transfer model. The results show that heat storage measures are particularly necessary in severe cold regions of China. The minimum value of the storage inlet temperature in this study should be more than 42.25 °C, and the flow rate is recommended at no more than 15 kg/s. Although increasing the inlet temperature of heat storage enhances the MDUBHE system's heating performance, the storage system's energy and exergy efficiencies are attenuated. Heat is mainly stored in the underground region within 6 m from the MDUBHE and at a depth of up to 2000 m, and the shape of the thermal plume is an inverted funnel. After adopting heat storage measures, the heating area supplied to buildings by the MDUBHE system increases, and reduces environmental pollution. Compared with the no heat storage measure, the heating area of the MDUBHE system is increased by 6770 m2 when the storage inlet temperature is 80 °C, and the corresponding solar collector area needs to be 756.1 m2. When T i n s increases from 45 °C to 80 °C, the reduction of CO 2 emissions increases by 12.43 tons, 21.05 tons, 38.26 tons, 55.41 tons, and 72.50 tons, respectively. This study could promote the application of the MDUBHE system and the heat storage system in severe cold regions. [Display omitted] • A heat storage system based on the medium and deep U-type borehole heat exchanger is proposed. • The energy efficiency and the exergy efficiency of the heat storage system are clarified. • The effects of heat storage on the temperature field of rock and soil are revealed. • The effects of heat storage on system performance and the environment were assessed. [ABSTRACT FROM AUTHOR]

In the era of accelerated globalization, the issue of technology blockade in complex product supply chains has taken centre stage, making the resilience and security of these chains a focal point in the strategic manoeuvres of major nations. This paper presents a tripartite evolutionary game model encompassing main manufacturers, domestic suppliers, and foreign suppliers. The aim is to delve into the internal mechanisms of transnational supply chain enterprises dealing with complex products, utilizing the "double cycle" framework to address technological blockade. The study's findings reveal a progression in the evolutionary system linked to the technological innovation capabilities of domestic suppliers. The system evolves from the independent innovation of domestic suppliers to cooperative innovation within domestic enterprises and ultimately culminates in joint ventures and cooperation involving multinational suppliers. Additionally, a noteworthy technology gap exists between domestic and foreign countries, suggesting that introducing foreign advanced technology initially and mimicking innovation can effectively mitigate research and development risks. Furthermore, the study underscores the role of Chinese government subsidies in incentivizing technological innovation among domestic suppliers, particularly pronounced when facing significant technology gaps. Simultaneously, the foreign government's imposition of penalties on premium sales by foreign suppliers serves as a catalyst for internal innovation within Chinese enterprises. These actions also motivate multinational enterprises to invest and cooperate, fostering the development of an international cycle. This study provides a fresh perspective on overcoming foreign technological blockades. Its positive implications extend to the advancement of technology in China's complex product landscape and the bolstering of supply chain resilience. • Evolutionary Game Theory Research on the Dynamic Impact of Technology Blockade on China's Complex Product Supply Chain. • Improving the level of technological innovation capability helps to break the foreign technological blockade. • The increase in fines imposed by foreign governments helps break the technological blockade through international circulation. • Domestic government subsidies are beneficial for breaking the technological blockade in domestic circulation. • Significant technological gap between domestic and foreign countries should be introduced first, and innovation should be based on imitation. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Throughout the imminent water crisis era and stringent water environment management, enterprises play a vital role in environmental governance. However, there is seldom analysis on how the water environment regulation influences an enterprise's innovation due to data deficiency. Using our database from 2000 to 2022, we combine geographic information from water quality monitoring stations with the data on listed companies in China to pinpoint what distance firms are exposed to the monitoring stations. Results from a spatial regression discontinuity design along the geographic distances demonstrate that water environmental regulation has a significant positive impact on the quantity and quality of enterprise innovation. This paper found that it is primarily driven by the decreased usage of intermediate goods, rising industry profits from the exit of low-productivity firms, and enhanced enterprise research and development (R&D) investment. Furthermore, the positive impact is more pronounced for privately-owned firms, firms closer to suppliers, polluting firms, and politically unaffiliated firms. Our study offers scientifically valuable insights for emerging market countries in formulating effective water environmental regulation policies to incentivize firms to innovate in environmental protection. Additionally, it provides novel ideas on synergizing water environmental regulation and firm innovation to foster a mutually beneficial relationship between environmental protection and sustainable development. [ABSTRACT FROM AUTHOR]

With the comprehensive progression of China's electric power reform, the participation of hydropower in the spot market has become inevitable. For hydropower-dominated power grids, the tight hydraulic and electric coupling relationship between cascade hydropower plants and the policy requirement of clean energy consumption greatly increase the challenge of optimal scheduling. Based on the market characteristics and actual demand of the hydropower-dominated power grids, this paper discusses the day-ahead spot market trading mechanism to promote the guaranteed consumption of renewable energy. On this basis, a day-ahead optimal scheduling model is established which aims to minimize the comprehensive power purchase cost of the power system. The nonlinear factors in the scheduling model, such as the relationship between the water level and storage capacity of hydropower plants, the relationship between the water level and water consumption rate, and the constraints on the start-up and shutdown durations of thermal power units, are linearized through multiple linearization techniques. The original nonlinear model is transformed into a mixed integer linear programming (MILP) model and is then solved using a CPLEX solver. The developed model is verified by taking 10 thermal power plants and 22 hydropower plants in Yunnan Power Grid as a case study. The calculation time is 183.6s, the comprehensive power purchase cost of the system is 155.35·million CNY, and no abandoned water is generated in the three basins. The simulation results show that the proposed model has high solution accuracy and efficiency, and maximizes the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost. The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grids. [Display omitted] • A day-ahead spot market trading mechanism to promote consumption of renewable energy. • Day-ahead optimal scheduling of hydropower-dominated power grids under a spot market environment. • A novel MILP approach is employed to solve the model. • Proposed model has high solution accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The accurate prediction of China's CO 2 emissions provides a reference and early warning for the implementation of the government's environmental strategy and has far-reaching significance for the world's environmental protection. The carbon emission system is a nonlinear dynamical system influenced by multiple factors with multiple data features. This paper establishes a novel grey differential dynamic multivariate prediction model with recurrent neural network. It uses the grey differential dynamic multivariate prediction model to describe the dynamic characteristics of the nonlinear system. And it uses recurrent neural network to extract data features. The new model is used to compensate for the shortcomings of the grey prediction model that use the least squares method to solve the model parameters affecting the accuracy of the model. The numerical solution of the whitening equations of the new model visualizes the hidden layer state function of the recurrent neural network. The optimal parameters of the new model are obtained through repeated training to improve the prediction accuracy of the model. Finally, the new model is applied to the prediction of China's CO 2 emissions to verify the validity of the new model from four different perspectives. The results show that the simulation and prediction errors of the new model for data of different lengths are less than 5%. The average simulation error in the optimal scheme is 3.01%, and the average prediction error is 0.78%. The results of the new model are better than the results of the other models. This indicates that the new model has better prediction results. Applying the scenario in forecasting the amount of carbon dioxide in China from 2020 to 2026 yields a forecast that matches the actual trend, further illustrating the validity and feasibility of the model. Finally, the forecast results are analysed, and relevant policy recommendations are provided. • A novel neural network grey prediction model is developed. • The model uses neural networks to deeply explore the time-series type data features. • The dynamic nature of the system is reflected using multiple differential grey models. • Successful prediction of CO2 emissions in China. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

Temperature shocks can cause various adverse effects on manufacturing firms, such that the adaptation activities of manufacturing firms to temperature shocks need to be focused on. Accordingly, this paper aims to investigate whether and why temperature shocks could be an accelerator for digital transformation of manufacturing firms. Empirical results suggest that extreme heat waves can propel manufacturing firms to strengthen their digital transformation orientation, while cold waves cannot. The effect of extreme heat waves on digital transformation orientation is likely to be performance-driven, rather than pro-environmental responsibility-driven. In addition, we indicate that there exist temperature adaptation effects, such that manufacturing firms located in areas with long-term exposure to extreme temperatures are less likely to strengthen digital transformation orientation after extreme temperature shocks, relative to those located in long-term temperature comfort regions. [ABSTRACT FROM AUTHOR]

Existing studies on water resource issues focus on water scarcity while largely lacking an integrative water balance health assessment and ignoring the combined impacts of water quality, water transfer, and unconventional water resources on water balance. Here, we proposed a novel framework for assessing regional water balance health considering three dimensions of water problems about imbalances: water scarcity, water inequality, and systems incoordination. This paper first quantified the levels of water balance health at multiple geographic and temporal scales in China, and then investigated the critical components and the impacts of improved surface water quality, inter-basin water transfer, and unconventional water use on the local water balance health. Results showed that China was under an unhealthy water balance due to multiple imbalances based on the annual average assessments during 2014–2018. More than 45% of the national population (∼615 million people) was affected by an unhealthy water balance. Hotspots with unhealthy water balance exhibited spatial heterogeneity and temporal variability, with Northern China experiencing unhealthy water balance throughout the year, while Southern China usually faced this issue during the winter. Unhealthy water balance in Northern China was primarily driven by water scarcity, while in the west of the Hu-Huanyong Line, water inequality exacerbated the situation. Southeastern China faced systems incoordination, particularly vulnerable during extreme events, such as severe droughts. More than 400 and 150 million people benefited significantly from improved surface water quality and inter-basin water transfer, respectively, relieving unhealthy water balance. However, the effectiveness of unconventional water use was found to be limited. This study contributed to a better understanding of water balance health and facilitated the development of policies for integrated water resources management in China. [Display omitted] • A novel method is proposed to quantify water balance health level at a basin scale. • China is experiencing an unhealthy water balance with multiple imbalances. • Over 45% of the national population is affected by an unhealthy water balance. • Geographic patterns of the critical components responsible for unhealthy water balance are determined. • Effectiveness of multiple measures in improving water balance health level is evaluated. [ABSTRACT FROM AUTHOR]

In response to the global call for biodiversity conservation and sustainable development, China plans to reform its protected areas (PAs) system. Despite positive progress, there are still challenges in defining PAs boundaries, allocating management authority, and securing sustainable funding. This paper reviews the current state and challenges of China's PAs management and advocates a paradigm shift towards comprehensive public governance. This shift aligns with the Ecological Conservation Redline (ECR) and integrates PAs into the National Territorial Spatial Planning, for a coordinated layout of Ecological-Productive-Living Spaces. The current study emphasizes the need for a refined assessment of PAs, including ecosystem services, to balance human development rights and environmental sustainability. It also advocates for multi-stakeholder consultation mechanisms to ensure broader social participation, particularly for indigenous peoples and local communities. The current investigation highlights the importance of valuing ecological products to harmonize environmental protection with community welfare. This review contributes to the discourse on balancing ecological integrity with socio-economic progress and provides insights into the difference between human rights, ecological conservation, and sustainable development, marking a significant stride towards global sustainability goals. [Display omitted] [ABSTRACT FROM AUTHOR]

Given the worsening environmental pollution and China's carbon peak and carbon neutrality goals, it is imperative to study the low-carbon travel behavior of urban residents. Previous research has mainly focused on objective environmental factors, subjective behavioral factors, and low-carbon travel behavior. However, the evolving decision-making of local governments, community residents, and individuals within the low-carbon travel system still needs to be explored. Tripartite evolutionary game theory is an effective method for studying the dynamic changes in strategies among limited rationality multiple actors in long-term repeated games, making it applicable to this study. Therefore, this paper simulates participants' behavior using evolutionary game theory, conducts stability analysis of equilibrium points of the replicator dynamic system using the Lyapunov first method, derives evolutionarily stable strategy combinations under different conditions, and finally performs simulation analysis using Matlab. The simulation results indicate: (1) By implementing reasonable incentive mechanisms, Local governments can encourage citizens to adopt low-carbon travel and community transformation. They should pay attention to their expenditures and subsidies, manage their spending to reduce consumption, maximize efficiency, and strive to achieve carbon emission reduction goals. (2) The likelihood of residents choosing low-carbon travel is mainly influenced by direct advantages such as health and economy in the initial stages, and later, it is more affected by the indirect benefits brought about by subsequent objective environmental changes. (3) The cost of renovation significantly affects the built environment of communities, leading to a reduction in renovation costs and the adoption of uniform standards and, consequently, stimulating enthusiasm for community transformation. The research findings suggest that the government can collaborate with the public to reduce carbon emissions by implementing specific environmental changes and providing incentives to encourage citizens to participate in low-carbon transportation. Simultaneously, the government can cooperate with the public, considering the quality of environmentally friendly transportation for citizens, formulating uniform regulations, reducing renovation costs, and achieving the highest low-carbon goals with minimal financial expenditure. [ABSTRACT FROM AUTHOR]

Battery electric industrial vehicles (BEIVs) offer significant environmental protection and decarbonization potential for rapidly growing logistics and transportation sectors in China. However, the limited driving range remains a major obstacle to the widespread adoption of BEIVs. Eco-driving is an effective solution that can improve energy efficiency and extend the driving range of vehicles by controlling driving behavior and speed. Therefore, this paper introduces an energy efficient speed planning method for BEIVs, in which data-driven models are developed to estimate energy consumption. Real-world driving data collected from a BEIV are used to model the energy consumption by curve fitting, random forest, and LSTM. The speed planning process is considered a Markov Decision Process, which is solved using Dynamic Programming and Q-learning, respectively. The case study of a battery electric forklift shows that speed planning can reduce energy consumption by 13%–27% compared to time-optimal speed, while only increasing the driving time by 10%–20%. • Energy efficient speed planning methods for electric industrial vehicles are proposed. • The speed planning method uses data-driven vehicle energy consumption models. • The energy consumption models are developed using random forest and LSTM. • The speed planning problem is formulated as a Markov decision process. • The speed planning problem is solved by Dynamic Programming and Q-learning. [ABSTRACT FROM AUTHOR]

Under the research background of China vigorously promoting the planning and construction of multi-energy complementary energy bases as well as the steady advancement of the electricity market, how to better promote the participation of large-scale multi-energy complementary bases in the electricity market has become a new research focus. In this paper, a joint optimization model for the participation of multi-energy systems in the electric energy market and auxiliary service market is proposed based on the Nash negotiation theory with coordinated wind-photovoltaic-pumped-storage-hydropower (WPPSH) generation systems as the research objects. Further, the joint optimization model is equated into two subproblems, namely, maximizing the net return of the alliance and negotiating the payment of the multi-energy complementary transaction, and the alternating direction method of multiplier algorithm (ADMM) is used to solve the above two subproblems separately. The simulation results show that the revenue of WPPSH increased by 25.82%, 30.67%, 49.35% and 3.78% respectively after joint operation, and the absorption rates of wind power (WD), photovoltaic (PV) and hydropower (HY) increased by 17.69%, 21.87% and 9.01% respectively. Through the cooperation of WPPSH generation systems, the income of each entity and the alliance can be improved, the fair distribution of incremental income is basically realized, and the consumption of clean energy can be promoted. In addition, the capacity allocation cap ratio of pumped storage (PS) units in the energy market and auxiliary service market will have a certain impact on the returns of WPPSH generation systems in multi-principal cooperation. [Display omitted] • The WPPSH can improve the profits of the alliance and individuals. • The WPPSH can improve the consumption rate of all kinds of clean energy. • The capacity allocation ceiling ratio of PS will have a certain impact on the cooperative benefits of WPPSH. • Nash negotiation theory is helpful for each agent to achieve the optimal trading strategy. [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]

The aim of the paper is to evaluate empirically the main implications of digital technology (DT) on carbon emissions (CE). Our sample focuses on 283 cities of China over the period from 2003 to 2019, and the effect of DT on CE is examined with a threshold spatial effect model. Empirical results show that DT has a negative impact on carbon emissions and the transmission mechanism contains both a direct impact on local region and a spillover effect across regions. There is empirical evidence of a threshold effect in the relationship between DT and CE, with stronger carbon reduction effect for DT values larger than the established threshold. Moreover, CE reduction effect of DT appear to be amplified by the level of marketization. Regions with a higher level of marketization thus show a more significant manifestation of CE reduction effect attributed to DT. Our results provide empirical evidence that DT development may contribute to achieving carbon neutrality at least partially. [ABSTRACT FROM AUTHOR]

Australia is a long-term key partner of China in coal trading, which is famous for high-quality coal and its price advantage. However, affected by the evolution of international political and economic situation, China has issued a coal ban on Australian coal since the end of 2020. The potential environmental consequences of this coal ban remain unclear. So, this paper quantifies the ban's impact on air pollution, human health and climate change by simulating the emission difference between the port scenario (simulating the emissions due to Australian coal import under business as usual) and the mine scenario (simulating the emissions due to domestic coal mining that converted from import share of Australian coal), and monetizes the losses into economic costs for direct comparison. The results illustrate the emission of SO 2 , VOCs and GHG in mine scenario grows up to 102, 12 and 6 times the amount of that in port scenario, mainly deriving from coal mining process in the North China Plain and Yunnan-Guizhou Plateau. It shows that the potential alternative of replacing import with mining leads to PM 2.5 pollution exacerbation and O 3 pollution abatement, which causes 148 (95 % CI: 101–183) non-communicable diseases and respiratory disease-related deaths in total. As for GHG, the emission of BC in transportation process and fugitive methane in coal mining process contribute to an impressive effect on warming potential with few quantities, which is worth noting in control process. In total, the environmental deterioration resulted in an economic loss of approximately 934 million yuan. The undiminished demand for high-quality industrial coal as well as growing carbon tax could make the economic value of the coal ban's environmental consequences more considerable in the near future. This research emphasizes the contradiction between economic development and environmental improvement caused by excessive dependence on coal and addresses a critical knowledge gap in assessing the ban's environmental impact by economic value. The result directly demonstrates the environmental consequences of the potential mining-replacing-import alternative and helps better understand environmental influences on the Chinese government's decision. [ABSTRACT FROM AUTHOR]

In the dynamic landscape of rapid change and the pervasive influence of the digital revolution, the discussion surrounding the impact of digital transformation on the innovation performance of firms has become a focal point of intense debate. This paper aims to contribute to the evolution and advancement of traditional organizations toward high-quality development by addressing this issue through the integration of technology into the framework, leveraging the resource-based theory. The study seeks to explore the influence of digital transformation on innovation performance, specifically examining the role of supplier concentration in this relationship. Additionally, we investigate the moderating effect of CEO financial experience on the association between digital transformation and innovation performance. Utilizing multiple regression methodologies and analyzing data from Chinese listed firms spanning the period from 2007 to 2022, our empirical findings reveal a direct positive relationship between digital transformation and innovation performance. Furthermore, the study uncovers an indirect pathway through which digital transformation enhances innovation performance by mitigating supplier concentration. Notably, the positive impact of digital transformation is amplified by a CEO's background in finance. Finally, the effect of digital transformation on innovation performance is particularly pronounced in sectors such as state-owned entities, advanced technology companies, large-scale businesses, and those in their maturity phase. These insights provide valuable contributions to addressing concerns related to digital transformation, particularly in emerging economies like China. The findings offer essential lessons for navigating the transition to Industry 4.0 and fostering sustainable innovative practices. By emphasizing the role of supplier concentration and the moderating influence of CEO financial experience, this research contributes to a nuanced understanding of how digital transformation can positively impact innovation performance across diverse sectors. [ABSTRACT FROM AUTHOR]

Being one of the significant conduits linking international and domestic markets, agricultural trade is an area of study that commands attention. While it may bring about transnational carbon emission transfers, it begs the question: does it promote carbon reduction in a country's agricultural sector? Such an inquiry holds profound implications for optimizing agricultural trade and promoting low-carbon agricultural advancement. Utilizing two-way fixed effect model, mediating effect model and dual-fixed spatial Durbin model, this paper examines the impact effects, mechanisms and spatial characteristics of agricultural trade openness (ATO) on agricultural carbon reduction using panel data from Chinese provinces spanning 2000 to 2021. The main findings include: (1) ATO markedly and positively influences the reduction of agricultural carbon emissions (ACE), this conclusion maintains its validity under endogeneity treatment and robustness tests. (2) ATO contributes to reducing ACE through three intermediary channels: scale effect, technological effect, and structural effect. (3) From a spatial perspective, a notable positive spatial spillover effect is observed from agricultural trade openness to agricultural carbon reduction, with the spatial carbon reduction effect being more apparent. (4) The spatial carbon reduction effect of agricultural trade liberalization exhibits heterogeneity across different natural geographical locations and levels of ATO. The study confirms the vital role of ATO in promoting agricultural carbon reduction in typical countries, underscoring the urgency and importance of bolstering cross-border agricultural trade cooperation and domestic agricultural product circulation in the domain of climate change. • The impact of agricultural trade openness (ATO) on agricultural carbon reduction is investigated in China. • The scale, technological, and structural effect of ATO serve as intermediary channels in reducing carbon emissions. • ATO engenders positive spatial spillover effects on agricultural carbon reduction. • Bolstering cross-border agricultural trade cooperation are of importance and urgency in the domain of climate change. [ABSTRACT FROM AUTHOR]

Modern agriculture involves the cooperation of stakeholders in multi-fields where their interaction significantly impacts the planning and operation of rural power systems. However, the traditional planning and operation for rural power systems assumes the power consumption as a given input without considering its unique feature caused by human factors. Particularly in China's rural areas, power consumption will rapidly increase and decrease due to the human-factor-based activity of farmer households' off-farm employment in urban and their home-returning during some important festivals. Therefore, this work proposes a multi-agent decision-making framework to realize the planning and operational optimization of power systems in a human-factor-based rural community. The framework integrates multiple agents' decision-making models including various stakeholders in modern agricultural systems and analyses their interaction. The meteorology-load and meteorology-generation models of power are materialized and embedded in the intensive agriculture and power system agent's decision-making models, which are used by the two agents to estimate the power consumption and photovoltaic (PV) generation, respectively. This work first quantizes the macro choice process of human-factor-based farm and off-farm employment and the numbers innovatively. Further, the farmer behavior for farm employment is simulated by the agent-based modeling system, and the power consumption of the farmer household group is estimated. Based on the overall agents' power consumption in the community, the planning and operation model of the power system is proposed to decide the optimal size and dispatch of the electrical devices. A multi-agent rural community is conducted for the case study to verify the effectiveness of the proposed decision-making framework. The results show that the farmer households who choose off-farm employment account for 66 % of the total households and their power consumption in most of the daytime on weekends is higher than on weekdays. The transportation system agent decides to purchase the electric truck with 5 tons of struck capacity for crop transportation. The power system agent decides to construct a hybrid system of PV, battery energy storage, and a transmission line of less transmission capacity, which can reduce its total system cost. Additionally, this paper finds that the solar radiation obtained by the greenhouse, which is considered the intensive agriculture agent, and its power consumption show opposite variation tendency, and the power consumption of the farmer household group in the Spring Festival is the largest. • A multi-agent decision-making framework of a rural community is proposed. • A meteorology-load and meteorology-generation models are materialized. • A macro choice process of human-factor-based farm/off-farm employment is quantized. • A bottom-up estimation method of power consumption is established by farmer behavior. [ABSTRACT FROM AUTHOR]

Understanding how municipal solid waste (MSW) classification influences the physiochemical properties and incineration emission characteristics of MSW is imperative for sustainable waste management. To investigate how long-term changes in the composition and physical properties of MSW resulting from MSW classification affect the emissions of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and multiple flue gas pollutants, a five-year experiment (2018–2022) was conducted in a full-scale MSW incinerator in Shenzhen City, China. After MSW classification, the food waste in MSW was substantially reduced while the paper, textile, and wood components were notably increased. MSW classification also remarkably decreased the water and chlorine contents of MSW while concomitantly increasing the wet-based calorific value, sulfur content, and nitrogen content. Consequently, the PCDD/Fs emissions declined from 106.7 ng I-TEQ/t MSW in 2018 to 26.0 ng I-TEQ/t MSW in 2022. Moreover, a process-tracing experiment demonstrated noticeable decreases in PCDD/F synthesis in the post-combustion area, with mass-reduction efficiencies of 23.6 %–95.4 %. In a correlation analysis, the PCDD/F emissions were significantly positively correlated with food waste, water content, and chlorine and negatively correlated with the wet-based calorific value and nitrogen content. Furthermore, MSW classification reduced the emissions of conventional flue gas pollutants (SO 2 , CO, and HCl) and multiple heavy metals (total sum of Sb, As, Pb, Cr, Co, Cu, Mn, and Ni). In summary, the long-term study demonstrated that MSW classification can feasibly separate incombustible waste, improve combustion quality, and reduce pollutant emissions from sources. These findings offer practical guidance for promoting MSW classification. [Display omitted] • MSW classification remarkably changes composition and physical properties of MSW. • MSW classification mitigates PCDD/F emission from 106.7 to 26.0 ng I-TEQ/t MSW. • MSW classification effectively reduces the emission of various flue gas pollutants. • The long-term experiment demonstrated the feasibility of MSW classification. [ABSTRACT FROM AUTHOR]

A sustainable economy through the rational spatial expansion of coastal areas is an increasingly essential global topic. This paper aims to explore the mechanism by which supporting cities influence the spatial expansion of economic development zones (EDZs) in 264 coastal EDZs of China during 1995–2020. Meanwhile, the effects of variations in the distance between supporting cities and coastal EDZs and different city scales are considered. The results provide new explanations for realizing the sustainable development of the coastal economy by planning EDZs at a suitable location from the supporting city. The supporting cities' economic strength can significantly contribute to the spatial expansion of coastal EDZs. The influence shows a distance decay law when the distance is less than 47.692 km, between 47.692 and 58.039 km, and greater than 58.039 km, with impact coefficients of 0.479, 0.393, and 0.212, respectively. The average spatial scale of coastal EDZs varies in an "inverted U–shape" with increasing distance. The average spatial scale of the urban general radiation type (47.692 km ≤ distance <58.039 km) is the largest. Supporting cities' scale affects the economic radiation range of supporting cities. The results suggest three implications for the future development of coastal EDZs. 1) Building the EDZ while incorporating practical development needs; 2) Scientifically planning the spatial layout of EDZs; 3) The synergistic development of supporting cities, transportation hubs, and EDZs. [Display omitted] • Supporting cities can promote coastal economic development zones' expansion. • The contribution of supporting cities to zone expansion shows a distance decay law. • The average spatial scale of coastal zones shows an "inverted U-shaped" change. • Supporting cities scale affects the economic radiation range by supporting cities. [ABSTRACT FROM AUTHOR]

Carbon trading is an important market instrument and policy tool to promote China's practice of low-carbon energy conservation and strive to achieve carbon peaking by 2030 and carbon neutrality by 2060. To improve market flow and respond to the national strategy to support the development of carbon trading in China, a smart carbon trading process optimization framework based on blockchain technology is developed in this article. First, the paper analyzes the current state of carbon trading in China's power sector and identifies the future development trend and barriers to carbon trading in China. Second, a framework for a smart carbon trading system based on the structure and traits of blockchain technology is created to optimize the carbon trading process. Third, the smart contract for the smart carbon trading system is built (including execution logic, transaction matching, contract fulfillment, and other elements). This mechanism measures the reputation of trading users. Finally, policy suggestions are provided to solve the current issues and challenges. According to the research conducted for this paper on "blockchain + carbon trading in China," carbon trading supported by blockchain technology can guarantee transaction security and efficiency, accurately preserve transaction records, and offer a high level of automated settlement. [ABSTRACT FROM AUTHOR]

From the perspective of the agricultural circular economy, rebuilding the crop-livestock integration system contributes a lot to improving the recycling rate of livestock manure, and reducing the application of synthetic chemical fertilizers, thereby fundamentally curbing agricultural pollution. In this paper, we use the latest provincial statistical data of China (2000–2020) to assess the circulation linkage between crop and livestock production. It can be concluded that livestock manure nitrogen and nitrogen requirements of crops both show an increasing trend from 2000 to 2020. Cropland Carrying Capacity of Breeding Livestock (CCCBL) has risen significantly by 37.34%, with an increase of 0.97 × 109 heads (unit: pig equivalent, which is used to measure livestock manure emission). Cropland Carrying Capacity Index (CCCI) exhibits a decreasing trend with the index being 0.47 in 2020, which further indicates that China's cropland has a great potential for carrying more livestock manure. Furthermore, through the scenario simulation, it can be projected that the livestock manure nitrogen will be 18.91 Tg and nitrogen requirements of crops will be 36.14 Tg in 2050. Thereby, rebuilding the crop-livestock integration system is necessary to achieve the dual goal of economic development and environmental conservation. Finally, this paper proposes that the government should optimize the crop-livestock geographical distribution and promote the upgradation of circular agriculture. [ABSTRACT FROM AUTHOR]

E-commerce has emerged through digital platforms and Internet construction as an important way to achieve low-carbon development in China. To evaluate the mitigation effect of e-commerce, this paper conducts a quasi-natural experiment in terms of the pilot policy of national e-commerce demonstration cities (NEDC) to explore the changes in CO 2 emissions of 270 cities from 2004 to 2017 in China. We also check the asymmetry, mechanism effects and heterogeneity. The results show that the treated cities reduce CO 2 emissions by 4.1% due to the NEDC pilot policy compared to the untreated cities. The estimated results pass the parallel trend test, robustness tests, and the Goodman-Bacon decomposition. Moreover, the NEDC pilot policy increases the CO 2 emissions of treated cities by promoting economic growth (scale effect), and decreases the carbon emissions of treated cities by upgrading the industrial structure (structural effect) and increasing the technological innovation level (technical effect). Furthermore, the CO 2 mitigation effects of the NEDC pilot policy are significantly concentrated in the higher quantiles. Finally, the NEDC pilot policy has significantly negative effects on CO 2 emissions in "postage-free regions," southern China, and cities with large e-commerce sales. The results of this paper provide theoretical and practical references for China to achieve low-carbon development. • Evaluating the impact of pilot policies of national e-commerce demonstration cities (NEDC) on carbon emissions in China. • The NEDC pilot policy reduces carbon emissions of treated cities by 4.1%. • The NEDC pilot policy reduces carbon emissions through structural and technical effects. • The emission-reduction effects are significant at the higher quantiles. • The impact of the NEDC pilot policy on carbon emissions is obviously heterogeneous. [ABSTRACT FROM AUTHOR]

Under the trend of global low-carbon development, reasonable and accurate prediction of electricity consumption plays an essential role in vigorously adjusting power system structure, promoting electrification, and other energy-saving and emission reduction measures. Considering the development trend of energy consumption, this paper introduces the Logistic model of energy structure into the system structure, and establishes a novel grey prediction model with system structure. According to the division of energy factors with similar attributes, this model seeks the internal relationship of the development of electricity consumption and describes the interaction between related factors and multiple main factors in the form of equations, which makes the model have better applicability and stability. In the validation part, the ten types of energy are divided according to their attributes, and the main factor group and the related factor group are distinguished. The model proposed in this paper is used for simulation and prediction, and is compared with the three types of models (six models). In the two cases, the simulation error of the new model is as low as 3.9790%, and the prediction error is 0.5645%. Compared with other models, the new model has shown good performance in the case of electricity consumption forecasting in China. The effectiveness of the optimization of the model in structure, background, and application is verified. At the same time, based on the analysis and prediction of China's consumption data, this paper gives relevant policy suggestions for developing China's power structure. • A novel model based on energy background (EPMGM(1,M,N)) is established. • The relationship of factors in the system are characterized by the equations. • A Logistic model based on energy structure is introduced to the new model. • China's electricity consumption is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

The green transformation of economic growth mode is one of the keys to promote high-quality development. This paper starts with the collaborative agglomeration of manufacturing and producer services, demonstrates the impact of collaborative agglomeration on industrial pollution emission through theoretical analysis, and then uses panel data of 285 prefecture level cities in China from 2004 to 2019 to verify the relationship between them. The results show that collaborative agglomeration significantly increased industrial pollution emission, but the effect mainly existed in small and medium-sized cities, cities with more development zones, cities with provincial high-tech industrial parks and the observation range from 2009 to 2015. The results of subdividing producer services show that transportation, warehousing and postal services, finance, information transmission, computer services and software industries have intensified industrial pollution emission in the collaborative agglomeration with the manufacturing industry. Mechanism analysis shows that collaborative agglomeration fosters the city's "low-level innovation preference" and promotes the expansion of the number of enterprises characterized by the entry and extension of the duration of highly polluting enterprises. It objectively forms a "quantity-priority orientation", thus increasing industrial pollution emission. The above conclusions mean that the development of urban industry at this stage should be based on quality and efficiency, rather than pursuing the disordered expansion of quantity. This paper provides beneficial policy implications for reducing local governments' blind behavior and awakening the awareness of environment-friendly economic growth. • Collaborative agglomeration increases industrial pollution emission. • The effect of emission increase varies with different urban and industrial characteristics. • "Low-level innovation preference" and "quantity-priority orientation" are important mechanisms. • The entry and long-term existence of high polluting enterprises led to "quantity-priority orientation". [ABSTRACT FROM AUTHOR]

Accelerating the energy transition of rural households in mountainous areas is an important step to improve energy poverty and mountain ecosystems and to help achieve carbon peaking and carbon neutrality. This paper explores the transformation of rural cooking energy in mountainous areas based on field investigation data from six villages in Chongqing. It systematically reveals the transformation process, driving factors and carbon emission changes in household cooking energy consumption in mountainous areas in the past 20 years by using mathematical statistics, multinomial logit models and the emission coefficient method. The results are as follows. (1) There has been a significant transition in the consumption of rural household cooking energy in mountainous areas. There has been a significant change in the proportion of different energy sources, including fuelwood (59.2%–1.9%), coal (16.5%–0%), gas (12.6%–15.5%), natural gas (6.8%–51.5%) and electricity (4.9%–31.1%). (2) The main driving factors of the household cooking energy transition in mountainous areas are income per capita, householder age, and householder education level. (3) The average annual household carbon emissions from rural household cooking energy decreased remarkably. The average annual household carbon emissions decreased from 6.80 t to 2.62 t in fuelwood (5.40–0.91 t), electricity (0.19–1.28 t) and natural gas (0.03–0.25 t) emissions during the study period. The contribution of this study is to investigate how the household cooking energy transition contributes to carbon peaking and carbon neutrality from a micro perspective. At the same time, this paper explores the mechanisms between the cooking energy transition and the ecological dividend of urbanization and proposes future reform initiatives for rural energy in mountainous areas to help achieve the goals of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

Competition and cooperation in the environmental governance of cities are popular around the world. However, empirical research based on the prefecture-level city level in China is rare. Since the central government of China proposed to strengthen the construction of ecological civilization, whether there are strategic interactions of "race to the bottom" or "race to the top" among local governments is an important issue of academic and public interest. This paper constructs a game-theoretic model to reveal the strategic interactions of environmental governance among local governments. And then, based on the data of 221 prefecture-level cities collected from 2007 to 2018, the spatial econometric model is used to conduct multi-dimensional testing "race to the bottom" behavior of environmental protection expenditure among local governments. Moreover, this paper further analyses the impact of performance assessment indicators on the strategic interactions of local governments, so as to provide policy reference for improving environmental public welfare. Empirical results suggest that local governments in China show strategic imitation in environmental protection spending decisions, which is manifested as "race to the bottom", and this behavior is gradually weakening with the strengthening of environmental protection assessment. Furthermore, environmental performance indicators relieve the government's strategic imitation, while economic performance indicators intensify the government's strategy imitation. Thus, reasonable performance evaluation indicators are conducive to benign strategic interaction among governments. Finally, the current environmental protection expenditure has not yet significantly affected pollution reduction, providing new evidence for the "race to the bottom" behavior of local governments. Based on the findings of our study, the central government should optimize the performance evaluation system of local officials and strengthen the implementation of the environmental supervision system and accountability mechanism. Meanwhile, the local governments should further increase environmental protection expenditure, and enhance the supervision and utilization efficiency of environmental protection funds. • Strategic interaction among 221 prefecture-level cities in China was multi-dimensionally studied. • It has been found that China's local governments have strategic imitation as "race to the bottom". [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has profoundly changed the pattern of economic and social development, which is of great significance for the realization of the harmonious coexistence between humans and nature and for the promotion of sustainable development. This study measures the state of China's provincial ecological footprint from 2011 to 2019, combines the characteristics of digital financial development, and explores whether such development can promote sustainable development from an ecological footprint perspective. The results show that (1) China's provincial ecological footprint per capita, which was continuously aggravated, increased by an average of 29.15% during the sample period. Digital financial development is shown to be able to effectively suppress the ecological footprint, and an environmental inclusion effect is also observed, which helps achieve a win‒win solution for economic development and ecological conservation while promoting environmental equality. Endogeneity tests and other robustness tests indicate that causality holds. (2) Bridging the digital divide, the improvement of environmental constraints and government digital governance capacity can help amplify the marginal effects of digital finance and mitigate the ecological footprint. (3) Green technological innovation and green finance are critical paths to achieve sustainable development. Digital financial development can facilitate green-biased technological innovation and increase the scale of green credit effectiveness, thereby reducing the ecological footprint. In the future, digital technology should be used to achieve the precise sinking of financial resources, while the government's role in guiding sustainable development should be enhanced, the digital divide should be narrowed, and the role of digital finance in supporting sustainable development should be strengthened. • Using the latest improved methodology, this paper measures the provincial ecological footprint in China. • This paper investigates the impact of digital finance development on the ecological footprint. • Digital finance development can effectively mitigate the ecological footprint and has an environmentally inclusive effect. • The reasons for this are the green bias push of digital finance towards technological innovation and the increase in the scale of green credit effectiveness. [ABSTRACT FROM AUTHOR]

In recent years, green innovation has become an important means of achieving sustainable development, but the impact of peer firms on green innovation is less discussed. To fill this research gap, this paper explores the effect of peer firms on the green innovation activities of the Chinese A-share listed firms in the manufacturing industry from 2011 to 2020 and investigates influencing factors of peer effect. The main findings are as follows. First, there is a peer effect in making green innovation decisions. Second, industry competition has a positive moderating effect on the peer effect of green innovation. Third, digital financial inclusion and government intervention both promote the peer effect of green innovation. The peer effect is more significant with a high degree of digital financial inclusion. But the peer effect has no significant difference between different degrees of government intervention. This paper aims to explore the influencing factors of a firm's green innovation from the perspective of peer effect. The research results can provide a guide for the government to better promote green innovation activities of firms and benign competition in the industry. • A firm's green innovation activities are positively affected by industry peers. • Industry competition has a positive moderating effect on green innovation peer effect. • Digital financial inclusion and government intervention both promote the peer effect. • The peer effect is more significant with a high degree of digital financial inclusion. • The peer effect has no significant difference between different degrees of government intervention. [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEVs) have been recognized as a sustainable eco-innovation to address China's energy and environment problems. As a strategically emerging industry, China's NEV manufacturing industry has been prioritized by governments and manufacturers, significantly impacting its spatial distribution pattern and stimulating the goals of carbon peaking and carbon neutralization. China, the largest NEV producer and consumer and with distinctive regional diversity, has experienced a new round of capacity expansion. Therefore, the literature on the spatial distribution patterns and influencing factors of NEV industry in provincial level is vital for the transformation of manufacturing industry and transportation sector, while to date, the related studies is few. In this paper, considering the number and location of key enterprises/production bases, the spatial distribution and influencing factors of China's NEV industry were discussed by an empirical study. The results are gained from a spatial perspective. Firstly, in general, China's NEV industry presents a "T" spatial distribution pattern. Secondly, a point-axle spatial exploration pattern is proposed, which includes "four points and one axle" namely Bohai rim, Yangtze River Delta (YRD), Pearl River Delta (PRD), Hubei-Chongqing clusters and Eastern Coastal NEV industrial belt. Thirdly, different types of NEV enterprises show various location preferences and spatial distribution characteristics. Fourthly, the influencing factors on China's NEV spatial distribution are concluded from five aspects of supporting policy, infrastructure condition, economic drivers, technical capacity, and industrial foundation, and the degree of factors is different considering varying enterprise classification and industrial development stage. The findings of this paper provide a reference for rational layout in China's NEV industry, and are expected to stimulate the sustainable development of NEVs. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has profoundly changed the pattern of economic and social development, which is of great significance for the realization of the harmonious coexistence between humans and nature and for the promotion of sustainable development. This study measures the state of China's provincial ecological footprint from 2011 to 2019, combines the characteristics of digital financial development, and explores whether such development can promote sustainable development from an ecological footprint perspective. The results show that (1) China's provincial ecological footprint per capita, which was continuously aggravated, increased by an average of 29.15% during the sample period. Digital financial development is shown to be able to effectively suppress the ecological footprint, and an environmental inclusion effect is also observed, which helps achieve a win‒win solution for economic development and ecological conservation while promoting environmental equality. Endogeneity tests and other robustness tests indicate that causality holds. (2) Bridging the digital divide, the improvement of environmental constraints and government digital governance capacity can help amplify the marginal effects of digital finance and mitigate the ecological footprint. (3) Green technological innovation and green finance are critical paths to achieve sustainable development. Digital financial development can facilitate green-biased technological innovation and increase the scale of green credit effectiveness, thereby reducing the ecological footprint. In the future, digital technology should be used to achieve the precise sinking of financial resources, while the government's role in guiding sustainable development should be enhanced, the digital divide should be narrowed, and the role of digital finance in supporting sustainable development should be strengthened. • Using the latest improved methodology, this paper measures the provincial ecological footprint in China. • This paper investigates the impact of digital finance development on the ecological footprint. • Digital finance development can effectively mitigate the ecological footprint and has an environmentally inclusive effect. • The reasons for this are the green bias push of digital finance towards technological innovation and the increase in the scale of green credit effectiveness. [ABSTRACT FROM AUTHOR]

To achieve the 2030 carbon peak target and promote the development of renewable energy, China introduced the renewable portfolio standard (RPS) and tradable green certificate (TGC) trading mechanism in 2017. However, for several years, its TGC market remained depressed. To solve this issue, this paper creatively introduced social influence and complex networks into the evolutionary game model between generators to analyze the evolution of power producers' behaviors, and to study the impacts of social influence, key institutional parameters, and network influence. The main results show that: (1) The positive intervention of public opinion is important to the vulnerable early TGC market, but its efficiency shows a marginal decline. (2) The evolution process can be accelerated through social interactions, and the strategies adopted by central firms in the network significantly influence the evolution result, especially when "TGC alliances" are formed. (3) According to the preference of social influence and profit, participants can be divided into two types: "changeable" (who favors interests), "firm" (who values social approval), and the latter has a greater market pulling effect. This paper provides implications for policymakers from new perspectives and extends the research scope of the RPS scheme and the TGC market. • Both economic and non-economic factors influence power producers' strategies. • Public opinions are important to strategy evolution. • Network topology plays a significant role in strategy evolution. • "Changeable" and "firm" producers have different market pulling effect. [ABSTRACT FROM AUTHOR]

In recent years, green innovation has become an important means of achieving sustainable development, but the impact of peer firms on green innovation is less discussed. To fill this research gap, this paper explores the effect of peer firms on the green innovation activities of the Chinese A-share listed firms in the manufacturing industry from 2011 to 2020 and investigates influencing factors of peer effect. The main findings are as follows. First, there is a peer effect in making green innovation decisions. Second, industry competition has a positive moderating effect on the peer effect of green innovation. Third, digital financial inclusion and government intervention both promote the peer effect of green innovation. The peer effect is more significant with a high degree of digital financial inclusion. But the peer effect has no significant difference between different degrees of government intervention. This paper aims to explore the influencing factors of a firm's green innovation from the perspective of peer effect. The research results can provide a guide for the government to better promote green innovation activities of firms and benign competition in the industry. • A firm's green innovation activities are positively affected by industry peers. • Industry competition has a positive moderating effect on green innovation peer effect. • Digital financial inclusion and government intervention both promote the peer effect. • The peer effect is more significant with a high degree of digital financial inclusion. • The peer effect has no significant difference between different degrees of government intervention. [ABSTRACT FROM AUTHOR]

In response to the water crisis, recycled water policy framework has been formulated by the central since 2000. Given the significant differences across China, local adaptive implementation under the central policy framework is allowed. Without consideration of the local performance, the previous studies less concerned on the impact from local performance and resulted in the biased evaluation on the implementation effectiveness. To fill the knowledge gap and support to mobilize adaptive implementation, this paper revisits the local implementation effectiveness according to the local adaptiveness. The paper examines the local implementation logics under top-down intervention and local conditions using text data from policy documents and the Cox Regression Model. The modified ambiguity-conflict theory was used to identify the local adaptiveness and the key constraints. The results suggest that local implementation is shaped by the dominant force of central intervention, the secondary influence of local capacity, and the minor effect of policy problems. Local adaptiveness varies across cities due to differences in local capacity. Cities with better fiscal capacity chose to innovative implementation in the face of weaker intervention, and remained adaptively implement polices with tightened central intervention. Cities with undeveloped economy preferred to perform as the central designed, with little regard for local specifics, while did not act even with enough discretion. To mobilize adaptive implementation, it is suggested that the intervention system should be divided into categories based on economic capacity. As a supplement to the target assessment system, a flexible performance assessment system should be designed. [Display omitted] • Implementation effectiveness is assessed by adaptiveness. • Central intervention plays a significant role and local policy problem not. • Economic-developed city responded slowly under stronger central intervention. • Mechanical implementation more likely emerged in undeveloped cities. • Classified interventions should be designed according to the economic capacity. [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

Constructing an eco-civilization is crucial in achieving green, low-carbon development, and thus bridging the gap between theory and practice is imperative to better promote urban ecological transformation. At present, there are inconsistencies and imbalances between theoretical research and practical efforts to achieve an eco-civilization. This paper uses bibliometric analysis and Latent Dirichlet Allocation to analyze China's progress towards an eco-civilization at the theoretical and practical levels. The 'theory' is analyzed using 632 articles, while the 'practice' is analyzed using 100 eco-civilization pilot zone reports. The two are compared, with results showing: from 2015 onwards, the theory is moving in an interdisciplinary direction, with seven themes focusing on macro topics. eco-civilization construction projects have multiple overlapping themes, and the growing connection between energy consumption, economic growth and environmental impacts driven by significant projects is the key to improving the level of regional ecological development. the theory and practice are similar in that both are concerned with environmental protection, ecological education, and ecotourism. However, eco-civilization construction projects lack forward-looking and dynamic development tracking of low-carbon research. the paper proposes that dynamic evaluation and project tracking methods should be applied to monitor critical indicators to achieve a solid link between the theory and practice during eco-construction projects. This paper also proposes academia should do more research on townships and other micro level phenomena to promote climate change and energy revolution in the construction of a Chinese eco-civilization. • Analysis of the similarities and differences between theoretical research and practical measures of eco-civilization. • Academic research focuses on sustainability, while practical activities lack attention to climate change. • Optimizing the energy-economy-environment integration project is the key to improving China's ecology. • Environmental protection, eco-civilization education, and eco-tourism are common concerns in the theory and practice. • Suggestions include focusing on crucial indicators and micro-level activities. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEVs) have been recognized as a sustainable eco-innovation to address China's energy and environment problems. As a strategically emerging industry, China's NEV manufacturing industry has been prioritized by governments and manufacturers, significantly impacting its spatial distribution pattern and stimulating the goals of carbon peaking and carbon neutralization. China, the largest NEV producer and consumer and with distinctive regional diversity, has experienced a new round of capacity expansion. Therefore, the literature on the spatial distribution patterns and influencing factors of NEV industry in provincial level is vital for the transformation of manufacturing industry and transportation sector, while to date, the related studies is few. In this paper, considering the number and location of key enterprises/production bases, the spatial distribution and influencing factors of China's NEV industry were discussed by an empirical study. The results are gained from a spatial perspective. Firstly, in general, China's NEV industry presents a "T" spatial distribution pattern. Secondly, a point-axle spatial exploration pattern is proposed, which includes "four points and one axle" namely Bohai rim, Yangtze River Delta (YRD), Pearl River Delta (PRD), Hubei-Chongqing clusters and Eastern Coastal NEV industrial belt. Thirdly, different types of NEV enterprises show various location preferences and spatial distribution characteristics. Fourthly, the influencing factors on China's NEV spatial distribution are concluded from five aspects of supporting policy, infrastructure condition, economic drivers, technical capacity, and industrial foundation, and the degree of factors is different considering varying enterprise classification and industrial development stage. The findings of this paper provide a reference for rational layout in China's NEV industry, and are expected to stimulate the sustainable development of NEVs. [ABSTRACT FROM AUTHOR]

Mining industry emission reduction is an important way to achieve the 2060 carbon neutrality target in China. Decoupling economic development from CO 2 emissions is the main strategy to reduce emissions from the mining industry. However, no studies have investigated the decoupling state and drivers of the Chinese mining industry. This paper is based on panel data of the mining industry and its subsectors during 2002–2016. The Tapio decoupling model was constructed to analyze the decoupling state of economic development and CO 2 emissions. The LMDI model was developed to decompose the drivers of the decoupling state. The results show that: (1) The CO 2 emission intensity of the mining industry decreased significantly from 1.63 tons per 10,000 yuan in 2002 to about 0.27 tons per 10,000 yuan in 2016. (2) The Chinese mining industry shows an inverted U-shaped decoupling relationship between CO 2 emissions and economic growth. Specifically, the change trend of decoupling state of Mining and Washing of Coal (MWC) also presents an inverted U-shape. Mining and Processing of Nonmetal Ores (MPNO) performs the best during the study period. Extraction of Petroleum and Natural Gas (EPNG) shows the largest change in decoupling state and the worst performance. (3) Overall, the economic output effect (CG) is the most important factor that promotes CO 2 emissions and inhibits decoupling. The energy intensity effect (EI) is the main contributor to suppressing CO 2 emissions and promoting decoupling. The energy structure effect (ES) is the most promising influencing factor. (4) There is variability in the role played by different 21 factors in the five subsectors. Specifically, EI inhibits decoupling in MWC but promotes decoupling in EPNG、Mining and Processing of Ferrous Metal Ores (MPFMO) and MPNO. ES inhibits decoupling in MWC and MPFMO but promotes decoupling in MPNFMO, while it has little effect on decoupling in EPNG and MPNO. Based on the results, comprehensive policy recommendations are made to achieve decoupling economic growth from CO2 emissions in the Chinese mining industry. The Research framework. [Display omitted] • The decoupling relationship and the driving factors between CO 2 emissions and economic growth in the Chinese mining industry were analyzed for the first time. • The methodology of this paper was based on three aspects: CO 2 emissions calculation, decoupling analysis, and factorization. • The results of the study were compared and described in the mining industry and its subsectors. • The decoupling state of the mining industry performs well during 2002–2012 and poorly during 2012–2016. • The energy intensity effect was the main contributor to decoupling and reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

This paper evaluates the relative weight of local contextual factors (including environment-related factors, labor market, social services, housing market, and migratory patterns) in shaping the "relative stickiness" of migrants at the city level in China. Previous studies focused on the volume, ratio, and pattern of migration while ignoring the complexity of the place-bound "political-industrial ecology" (PIE) that would reinforce or stiffen the migrants' "stickiness" to the destination city. This paper uses the city-level data of migrants' intention ratios of permanent urban settlement and home-buying, respectively, as a pair of proxy measures of the city's relative stickiness and attractiveness. We use Multi-Scale Geographically Weighted Regression (MGWR) to detect the variation of migrants' sensitivity to environmental reconstruction-related factors at the city level in China. Our analysis reveals a north-south divide in migrants' stickiness in China, which is opposite to the conventional understanding that the migrants are stickier to the high-wage and high-quality ecological environment. Different PIE in North China and South China can explain why migrants are stickier to North China that have negative environmental externalities, while rapidly flowing into and frequently out of the south-southeast coast which has richer environment-related amenities. It is revealed that the relative stickiness of migrants is also attributable to the specific migratory pattern, institutional context, and cultural distance, as embedded in the varied PIE in a country as geographically diverse as China. The findings support the notion of PIE where an uncertain and nonlinear relationship exists between the environment and migration. The social services and migratory pattern usually outweigh the environmental factors in the migrants' settlement and home-buying decision-making in China today. [ABSTRACT FROM AUTHOR]

This paper investigates consumer upcycling behavior, a consumer-determined Circular Economy (CE) practice. Consumer upcycling involves transforming or repurposing unwanted object(s) to an object which has equal or higher value than the current value of its component(s). Although it is one of the most beneficial practices for environmental sustainability, more so than other practices such as recycling, and it constitutes a concrete exemplar of how consumers can participate in the Circular Economy, literature on consumer upcycling is rather underdeveloped. Performing inductive content analysis on in-depth interviews of 34 consumers mainly from China, this paper develops a holistic framework representing the internal motivations and consequences of consumer upcycling. Specifically, three distinct dimensions of internal motivations for consumer upcycling are identified: core-self oriented, social-self oriented, and object-self oriented motivations. Further, consequences of consumer upcycling at three levels (social, environmental, and economic) are identified. We find that consumer upcycling may spur other consumer-focused pro-environmental behaviors (i.e., spillover effect) and engender positive attitude and behavior toward purchasing of upcycled products (i.e., switchover effect). All in all, this research contributes to the CE literature by providing insight on how consumers could take initiative to enable the Circular Economy. • Internal motivations and consequences of consumer upcycling behavior are explored qualitatively. • Communication appeals based on internal motivations promote consumer upcycling behavior and purchase. • Consumer upcycling engenders other pro-environmental behaviors and support for upcycling business. • Consumer upcycling behavior advances the Circular Economy. [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]

Multi-area coal extraction can cause aquifer depressurisation and subsurface dewatering, in which the mechanism of overburden permeability and shallow water responding to underground gob keeping extending is the key. This paper focuses on the water resource protection in ecologically fragile mines in western China. With the equivalent permeability coefficient(EPC) and subsurface hydraulic responses as basis, the paper conducted mathematical statistics and theoretical analysis to construct a decision-making model for multi-panel longwalls and a longwall design methodology that considered subsurface water stability. Firstly, fitting the field measurement data produced an empirical equation regarding the height of water-conducting fracture zone (HWCFZ), and a model for quantifying the correlation between the damage values of effective soil units and effective bed rock units was established, by which the EPC was quantified. Secondly, the paper developed a subsurface water quantification model that considered infiltration recharge to study the subsurface piezometric evolution with varying geometry, range, and number of longwall units, further revealing the subsurface water responses to varying mining zones. Finally, a model for evaluating the subsurface water depressurisation was proposed and applied to study the subsurface water responses to multi panels in Zhuanlongwan Coal Mine. The longwall design obtained via the decision-making model agreed with the piezometric variation in the mine, suggesting that this research can provide theoretical and technical supports for green mining. [ABSTRACT FROM AUTHOR]

We try to expand the political promotion tournaments in Chinese local governments from raising GDP to the level of increasing fiscal revenues. From the vantage point of officials' performance appraisal, we investigate the impact of local government officials' political ambitions, represented by the ex-ante commitment level of fiscal revenue targets, on carbon emission intensity (CEI). Utilizing a sample of 209 prefecture-level cities in China spanning 2006 to 2019, this paper empirically scrutinizes the influence of local government political ambition on CEI. The findings reveal that the greater the political ambition of local government officials, the more pronounced the reduction in CEI. Furthermore, our study demonstrates that political ambition contributes to the decline of CEI by elevating the levels of environmental attention and green innovation. This research not only aids in comprehending the rationale and necessity of the political promotion tournaments implemented by the Chinese central government but also offers valuable insights for other developing countries seeking to mitigate CEI. [ABSTRACT FROM AUTHOR]

With the rising awareness of green and sustainable development, corporate environmental, social, and governance (ESG) performance has become an essential topic in academia. Existing studies have focused on the driving role of formal institutions on corporate ESG performance while ignoring the motivational role of informal institutions such as culture. Based on the data of Chinese A-share listed companies from 2009 to 2021, this study adopts textual analysis to quantify corporate culture and discusses the impact of corporate culture on ESG performance and its internal mechanism. We find that corporate culture significantly enhances ESG performance. Mechanism test indicates that corporate culture can promote green innovation and improve information transparency through resource and information effect, enhancing ESG performance. We further demonstrate differences in the impact of corporate culture dimensions on ESG performance, with innovation culture and quality culture being the most prominent. In addition, there is heterogeneity in the impact of corporate culture on ESG performance. In the context of non-state-owned property rights, low market attention, and high economic policy uncertainty, the impact of corporate culture on ESG performance is more significant. This paper enriches the related research on ESG performance drivers from the informal system perspective and provides decision-making references for enterprises to promote ESG practices and achieve sustainable development. [ABSTRACT FROM AUTHOR]

Green credit is a new financial instrument that has emerged in response to the call for the transformation of the "green economy" model. It aims to utilize financial means to support green industries and environmental projects, serving as a crucial lever for the integration of social and economic benefits. It also represents a significant developmental direction for the future credit business of banks. Leveraging microdata from 36 banks spanning the years 2007–2022, this study explores the correlation between green credit and the risk-taking behavior of commercial banks in China, building upon the DID model. Meanwhile, Granger causality tests are employed to investigate the bidirectional relationship between these two core objects. The research results indicate that green credit has a short-term mitigating effect on the risk-taking behavior of commercial banks. This risk-mitigating effect is more pronounced among banks with smaller assets and lower profitability. However, this effect diminishes over time, ultimately resulting in an increased propensity for risk-taking in the long run. Moreover, this highlight posits that the credit risks of banks do not influence the implementation of green credit policies. Consequently, this paper offers essential reference value for the risk management practices of commercial banks in the emerging economies and other global countries. • We conduct policy evaluation to analyze the effect of GCP on risk-taking of commercial banks. • We adopt the Granger causality test to explore the two-way relationship between key variables. • We support the mitigation effect of GCP , especially in banks with fewer assets and lower profitability. • We conduct robustness tests to verify the credibility of preliminary regression results. • We further analyze potential effect of GCP from dual perspectives in short-term and long-term. [ABSTRACT FROM AUTHOR]

This paper chooses 98 mining cities in China from 2007 to 2021 as research samples. It investigates the policy practice of green development in mining cities according to the point of view of policy combination. We establish a super-efficiency model considering undesirable output to measure the green development level of mining cities and further construct a dynamic panel model based on the Gaussian mixture model (GMM) to test the transmission mechanism and heterogeneous effect of different types of environmental regulation to promote the green development of mining cities. The findings demonstrate that environmental regulations about command control, market incentives, and public participation can all help mining cities develop more sustainably. Additionally, there is a nonlinear relationship of an inverted "U" shape between the degree of green development in mining cities and environmental regulations related to command control. Combining policies can encourage the green development of mining cities, but there are crowding-out and substitution effects when environmental regulations are combined with market forces. Environmental regulation promotes urban green development by improving the energy consumption structure of mining cities. In this process, the level of digital development positively regulates the impact of environmental regulation on urban green development. Therefore, the government should choose environmental regulation tools and combinations according to local needs to achieve a multi-pronged effect of energy structure improvement and urban green development and use digital technology to support the green development of mining cities. • Command-controlled, market-motivated, and public-participating environmental regulations can significantly promote urban green development by promoting the improvement of energy structure. • There is an inverted' U' -shaped nonlinear relationship between the intensity of command and control environmental regulation and the green level of mining cities. • The level of digitization can positively regulate the relationship between environmental regulation and urban green development. • The combination of environmental regulations have a significant positive impact on urban green development. • The combination of environmental regulations has heterogeneity in urban green development due to factors such as regional resource endowment. [ABSTRACT FROM AUTHOR]