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Pulp and paper mill biomass boilers generate large quantities of ash in Canada with British Columbia (BC) being the highest ash generating province followed closely by Quebec. Generally, the generated ash is landfilled, particularly in BC, with only a small amount being used beneficially. It is anticipated that the difficulty associated with the management of ash will worsen over time as the industry increases its reliance on green fuel. Thus, there is a strong need to identify beneficial uses of pulp and paper boiler ash for the sake of environmental and economic sustainability. The purpose of this report is to provide the first step in this direction, a review of proposed or implemented uses for coal and hog (or wood) ash around the world. Considering both the properties of the ash and local opportunities, this could be the first step toward screening the applications that may apply to individual mills. Several large-scale practices use ash, such as land application (as a nutrient source or as a liming agent), use in the construction industry (as a replacement for cement or as a fill material), and reclamation of mine sites and stabilization of unpaved forest roads. In some cases, relatively small-scale applications have been used which included uses such as a compost component, agent for pH adjustment of liquid streams and slurries, blasting abrasive, and source of quartz for glass manufacturing to name a few. It is important to note that the chemical nature of both fly and bottom ashes can be quite variable due to the type of wood residues combusted as well as combustion equipment used and must be considered in identifying beneficial applications. • General ash characterization is not enough to find useful applications of ash. • Ash use in the liming agent requires different properties than ash use in concrete. • Ash must be characterized according to its application requirements. • PPM ash can mainly be used for concrete, ag lands, liming agent, and forest roads. [ABSTRACT FROM AUTHOR]

Businesses embracing green innovation can encourage high-quality green economic development in addition to reducing emissions. In this paper, we use the Difference-in-Differences (DID) to investigate the influence of green investor behavior on the green innovation of companies, using the first-ever green investor investment in a company as a quasi-natural experiment. According to research, green investors have the power to accelerate corporate green innovation greatly. Three key strategies that green investors can use to do this include raising institutional investment levels, enhancing the green perception of executives, and bringing in top talent. Heterogeneity analysis shows that non-high-polluting, big, and state-owned enterprises (SOEs) are more likely to benefit from green investors' green innovation effects. Further analysis reveals that (ⅰ) green investors' influence on an enterprise's level of green innovation can help it improve its ESG ratings; (ii) green investors can encourage green innovation in source control but have little effect on green innovation in end-of-pipe treatment; (ⅲ) green investors can support both non-green and green innovation in enterprises, but have a greater influence on green innovation. This study strengthens the micro relationship between green investors and corporate green innovation. It also supports the theoretical underpinnings of corporate green innovation, which is significant for advancing green innovation, environmental protection, and high-quality economic development in emerging economies. • This paper explores the relationship between green investor behavior and corporate green innovation. • Green investors have the power to accelerate corporate green innovation greatly. • Green investors significantly accelerate corporate green innovation mainly through raising institutional investment levels, enhancing the green perception of executives, and bringing in top talent. [ABSTRACT FROM AUTHOR]

The development of digital finance provides new opportunities for improving energy efficiency and promoting green development. This paper calculates green total factor energy efficiency (GTFEE) using the super-efficiency SBM model and examines the impact of digital finance on GTFEE. Digital finance has a significant positive impact on GTFEE. Under a bank-dominated financial structure, the positive impact of digital finance on GTFEE is quite significant. In regions with intense banking competition, a large amount of green credit, and lower resource dependence, digital finance is conducive to enhancing GTFEE. Optimizing the allocation efficiency of production factors is an essential mechanism for digital finance to encourage improvements in GTFEE. Digital finance alleviates distortions in factor markets and enhances the matching of the marginal output and the price of capital, labor, and energy factors, thereby facilitating improvements in GTFEE. Further analysis indicates that digital finance has a significant, positive spatial spillover effect on GTFEE, enhancing GTFEE levels in both local and neighboring regions. This study enriches the research on the relationship between digital finance and energy efficiency and provides theoretical foundations and policy references for how digital finance can better serve the green transition of the economy. • This paper analyzes the impact of digital finance on green total factor energy efficiency (GTFEE). • Digital finance alleviates distortions in factor markets, thereby promoting GTFEE. • Digital finance's impact on GTFEE depends on financial structure, banking competition, green credit and resource dependence. • Digital finance has a significant positive spatial spillover effect on GTFEE. [ABSTRACT FROM AUTHOR]

This paper addresses the need to understand the structure of sustainability change in the face of the unpredictability of modern civilization. The aim of the paper is to examine the structure of sustainability change in relation to smaller spatial units such as the regions of the European Union and to compare these results with those achieved at the country level. For this purpose, the sustainable development indicators available in the Eurostat database were analyzed. Studies published to date have tended to focus on the performance of national economies or selected regions. In this article, the available data on regions are also analyzed. The study aims to compare the level of sustainable development achieved at the level of EU countries and regions located within them. Methodologically, the study uses advanced methods of comparative analysis, and the synthesis of the data enables the construction of a synthetic measure using taxonomic methods, facilitating the classification of EU countries and regions into clusters. The results highlight significant divergences in sustainability achievements between EU countries and regions. The study reveals the importance of studying sustainable development in smaller geographical cross-sections. The results highlight the need to expand access to data at the regional level (sustainability indicators) to facilitate more comprehensive analyses and inform targeted policy interventions. Looking to the future, the study recommends further research into the inter-linkages between sustainability and other critical areas in EU regions, such as innovation and competitiveness. • A new approach to studying sustainable development from a regional perspective has been proposed. • An in-depth analysis of the current level of sustainability in EU regions was carried out. • The diversity of sustainable development in the countries of the EU has been described. [ABSTRACT FROM AUTHOR]

The promotion of green intelligent buildings (GIBs) is regarded as an effective way to reduce carbon emissions and environmental pollution. How to formulate a reasonable and practical subsidy mechanism is crucial to promote the development of GIBs. However, there is still a lack of research on dynamic subsidy mechanism. To solve the research gap, based on consumer utility maximization theory, combining Hotelling model, the paper constructs an evolutionary game model between local governments and developers, and discusses the decision-making and evolutionary stable strategy (ESS) of both players under the dynamic subsidy mechanism. In addition, the paper defines a symbol event and analyzes in depth the possibility of effective diffusion of GIBs. Finally, the paper provides corresponding policy suggestions and draws the following conclusions: (1) ESS exists only after the introduction of dynamic subsidy mechanism, so it is necessary for local governments to formulate dynamic subsidy policies; (2) Under the dynamic subsidy mechanism, different subsidy adjustment rates will affect the evolutionary efficiency of the system; (3) The sensitivity of influence factors from high to low is as follows: subsidy adjustment rate, financial incentives for consumers, additional taxes for conventional buildings developers, carbon trading income for GIB developers and comprehensive residential benefits for GIB homebuyers. Improving these factors can increase the possibility of effective diffusion of GIBs. • This paper attemps to solve the gap in the existing literature which only considers static subsidy mechanism. • This paper reveals how consumers indirectly influence the behavioral strategies of developers and local governments. • This paper defines a symbol event about the diffusion of GIBs and optimizes the parameters. • This paper finds that some parameters have threshold effect. [ABSTRACT FROM AUTHOR]

Cooperative green technology innovation is potentially the answer to the lack of motivation for independent green innovation, which can effectively alleviate many difficulties faced by enterprises engaging in independent green innovation. Internet development provides new opportunities to stimulate innovative cooperation of enterprises. However, little literature has studied the impact of Internet development on enterprises' cooperative green technology innovation. Based on the data of Chinese A-share 3284 listed companies from 2010 to 2019, this paper uses a panel two-way fixed effects model to assess the effect of Internet development on enterprises' cooperative green innovation. The findings are: (1) Internet development significantly drives firms' collaborative green innovation behavior. The result remains robust even after performing a series of robust tests. (2) The Internet empowers green innovation cooperation among firms by improving information availability, including market information availability and technical information availability. (3) The heterogeneous results show enterprises use the Internet to accomplish high-quality collaborative green innovation. Internet development is more helpful in encouraging the cooperative green innovation of enterprises located in central cities and state-owned enterprises. This study provides novel and targeted policy implications to empower enterprises' green innovation cooperation and drive sustainable economic development through Internet development. [Display omitted] • This paper uncovers the role of Internet development on firms' cooperative green technology innovation. • Internet development significantly drives collaborative green innovation behavior of firms. • Market information availability and technological information availability are influencing mechanisms. • Some constructive policy recommendations are proposed for promoting cooperative green technology innovation. [ABSTRACT FROM AUTHOR]

In the context of global low-carbon emission reduction, how to achieve green and high-quality development has become a major issue for the Communist Party of China (CPC) and the Chinese government recently. Based on the data of China's listed companies from 2013 to 2020, this paper uses Python to implement text analysis of annual reports, and explores the relationship between political acuity and carbon-efficiency synergies (CES) from the perspective of enterprise initiative. We found that (1) political acuity positively affects carbon-efficiency synergies. (2) Increased political acuity can reduce carbon emissions, but the effect on economic efficiency is not obvious. That is, low carbon takes the lead in raising the level of carbon-efficiency synergies. (3) Environmental regulations can positively regulate the relationship between political acuity and carbon-efficiency synergies. (4) Political acuity in southern China, carbon neutral and non-state-owned enterprises (NSOEs) will have a more pronounced effect on carbon-efficiency synergies. From the perspective of the root causes of political linkages, we find the synergies between formal and informal institutions, and the key factors for policy implementation. This paper is helpful for enterprises to improve the synergies of emission reduction and efficiency promotion, and has practical implications for the government to promote green and high-quality development. • Assess the value of the low-carbon economy from its political roots. • We build a carbon-efficiency synergy evaluation system. • Political acuity and formal institutions are synergistic. • The influence of political acuity on CES can be replicated. • This paper expands the technical approach to low-carbon research. [ABSTRACT FROM AUTHOR]

Green innovation is important and beneficial for the green development of enterprises. The development of digital technology could improve the asymmetry of information and affect the enterprise's financing modes. Currently, a definitive conclusion about the relationship between the digital transformation and green technology innovation has not reached. Additionally, studies have not yet fully explored the impact pathways of corporate digital transformation on green innovation through corporate financing modes. To fill this void, this study collected data of Chinese A-share listed companies from 2010 to 2020. The empirical analysis results showed that digital transformation significantly enhanced enterprises' green innovation abilities. Furthermore, mediating models were utilized to explore how enterprise financing modes mediate the impact of digital transformation on the enterprise green innovation. Results indicated that through internal financing and bank loans as "bridges", digital transformation promoted enterprise green innovation. However, digital transformation did not have a significant impact on enterprise green innovation through venture capital. Moreover, heterogeneity analyses revealed significant differences among different groups of enterprises. This study expands the research field related to digital transformation and enterprise green innovation by providing empirical evidence to uncover the impact of digital transformation on enterprise green innovation. Findings of this study contribute not only to enterprise managerial decision-makers to better leverage digital transformation through corporate financing to accelerate green innovation, but also to government policymakers to design policies to stimulate enterprise green innovation. • Firstly, our paper empirically examines and validates the impact of digital transformation on enterprise green innovation again by using empirical data of biggest development counties, i.e., China. • Secondly, our paper combines enterprise digital transformation, financing modes, and green innovation within the same framework to study the "bridge" role of financing modes between digital transformation and enterprise green innovation. • Thirdly, Thirdly, heterogeneity analyses were carried out, the results of the different enterprises groups are significant different. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

Higher education institutes (HEIs) are important drivers for the development and implementation of best practices for environmental sustainability. However, reliable indicators are needed to objectively evaluate the environmental performance of HEIs and their policies. The present paper aims at identifying suitable indicators for unbiased comparisons among different HEIs and for the identification of temporal trends in terms of environmental sustainability performance. At this aim, sustainability reports made publicly available by 24 Italian HEIs over a 10-year period were considered. Normalization of sustainability variables such as the annual electrical and thermal energy consumptions, related greenhouse gas emissions, and water consumption, against context-specific factors such as the number of users of each university, latitude, illuminance, heating degree days (HDDs) and cooling degree days allowed identifying the actual possible disturbance of the same variables. HDDs were found to positively affect the thermal energy consumption and the related CO 2 emissions. Based on this, a novel indicator was formulated where the actual value of thermal energy consumption and the related CO 2 emissions are divided not only by the number of users but also by the HDDs of the HEIs' locations. Indeed, this is a remarkable finding that, prior to confirmation with data from world HEIs, could be implemented in world university green ranking systems for improved and less biased sustainability assessments. [Display omitted] • Context-independent indicators allow unbiased sustainability comparison among HEIs. • Context-independent indicators were identified through coefficients of variation. • Per capita thermal energy consumption needs to be divided by heating degree days. • Per capita CO 2 due to thermal energy needs to be divided by heating degree days. [ABSTRACT FROM AUTHOR]

Urban areas contribute 85% of China's CO 2 emissions. Green finance is an important means to support green energy development and achieve the low-carbon transformation of high-energy-consuming industries. The motivation of this article is to investigate the impact and mechanism of green finance on urban carbon intensity. Most existing literature uses linear models to investigate urban carbon intensity, ignoring the nonlinear relationships between economic variables. The nonparametric models can fill the inherent shortcomings of linear models and effectively simulate the nonlinear nexus between economic variables. Based on the 2011–2021 panel data of 237 cities in China, this paper applies the nonparametric additive model to survey the influence of green finance on urban carbon intensity. Empirical findings exhibit that green finance exerts an inverted U-shaped effect on urban carbon intensity, indicating that the carbon reduction effect of green finance has gradually shifted from inconspicuous in the early stages to prominent in the later stages. Then, from the perspectives of region, city size, and carbon intensity, this article conducts heterogeneity analysis. The results show that the impact of green finance on various carbon intensities all exhibits obvious nonlinear feature. Furthermore, this article employs a mediation effect model to conduct mechanism analysis. The results display that technological progress and industrial structure are two important mediating variables, both of which produce an inverted U-shaped nonlinear impact on urban carbon intensity. • The nexus between green finance and urban carbon intensity is a ∩-shaped pattern. • The high-carbon intensity cities receive a U-shaped impact from green finance. • Technological progress exerts a ∩-shaped effect on carbon intensity. • Green finance has a ∩-shaped impact on carbon intensity in the eastern and western regions. [ABSTRACT FROM AUTHOR]

Transboundary lakes are shared by multiple administrative regions. The key to balance the development and protection of transboundary lakes is to properly measure the value of water resources. Most of previous studies on the measurement of lake water resources value have not fully considered the ecosystem service function. This paper proposes a new concept "composite water value" to measure the value of transboundary lakes by integrating the external runoff value and the internal runoff value of water resources. The study constructs a composite water value measurement system for transboundary lakes, further analyzes its influencing factors,and applies the system to the case of Nansi Lake, a representative transboundary lake in eastern China. The results show that: (1) The composite water value of lakes is influenced by various factors, including industrial structure, water withdrawal, and water use methods, which impact the external runoff water value; meanwhile, the composite water quality and fluctuations in lake level are closely associated with the internal runoff water value. From 2008 to 2021, the average annual composite water value of Nansi Lake was 39.628 billion yuan, exhibiting a "rising-falling-fluctuating rising" trend due to pollution control policies, reduced precipitation, and enhanced water-saving technologies successively. (2) From a long-term perspective, it is necessary to focus on the internal runoff water use value of lakes. The internal runoff water value of Nansi Lake has been over 75% of the composite water value, and flood storage and water conservation are important manifestations of its ecosystem service value. (3) The external runoff water value of lake is closely related to the internal runoff water value, and relevant departments need to consider the balance between the water withdrawal of multiple cities along the lake and the retained water volume of the lake to achieve the maximum benefit of composite water value. [Display omitted] • Lake water value includes multiple values derived from external runoff water out of lakes and internal runoff water in lakes. • The ecosystem service value of internal runoff water is much higher than the economic value of external runoff water. • There is a tradeoff relationship between the internal runoff water and external runoff water. • Composite water value measurement can help balance transboundary lakes development and protection. [ABSTRACT FROM AUTHOR]

Promoting the formation of the green lifestyle (GL) is a crucial step in achieving comprehensive green transformation of urban economic and social development. The widespread adoption of GL is influenced by various environmental regulations. Previous research mainly focused on the impact of individual policies on GL from the single policy perspective. The mechanisms of the combined effects of policies have not been thoroughly explored, particularly the contributions of each policy during periods of overlap. This paper takes the dual-policy of the New-type Urbanization Policy (NUP) and Smart City Policy (SCP) in China as an example. It employs panel data collected from 271 cities in China during 2007–2019 and establishes a multi-period difference-in-difference model to identify the combined effects of the dual-policy on residents' GL. Additionally, the Shapley value decomposition method is utilized to identify the contribution magnitude of each policy when they act simultaneously. The following conclusions are yielded. Firstly, the combined effects of dual-policy are more effective than a single policy in influencing residents' GL. Secondly, the Shapley value decomposition method reveals that when both policies are simultaneously implemented, SCP contributes a greater weight compared to NUP. Thirdly, the dual-policy can promote residents' adoption of GL through mechanisms such as green technological innovation, public participation in environmental protection, and the agglomeration of tertiary industries. Fourthly, the impact of dual-policy on residents' GL varies across different types and sizes of cities. This study attempts to unseal the "black box" of how the dual-policy influences residents' GL during the green transformation of cities in China, providing theoretical references for relevant urban policies in other countries and contributing to Chinese solutions and experience to global urban green development. • The dual-policy of NUP and SCP can jointly promote residents' green lifestyle. • The weight of SCP's contribution is higher than NUP's by the Shapely value method. • It explored three potential channels between the dual-policy and GL. • There are heterogeneous effects of dual-policy on GL in different types of cities. [ABSTRACT FROM AUTHOR]

Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy". [Display omitted] • The staggered differences-in-differences method is employed to examine the direct and spatial spillover effects of NEPC on cities' GEE in China. • This paper uses NEPC as a quasi-experiment for digital transformation. • NEPC significantly improves green economic efficiency by 2.6%. • Green structural transformation, innovation, and environmental concerns are main channels. • Positive spillover effect of NEPC on green economy efficiency in non-pilot cities. [ABSTRACT FROM AUTHOR]

Modern project managers cope with significant challenges to schedule and control projects considering dynamic environments, frequent uncertainties, strict project deadlines, and stricter sustainable requirements above all. Sustainability taking into account resource utilization has been recently associated with project management. Hence, this paper presents a new mixed-integer linear programming (MILP) model with two objectives for a resource-constrained project scheduling problem (RCPSP) with multiple skills and multiple modes, assuming preemptive and non-preemptive activities in an uncertain environment. Given the importance of sustainable developments in projects, the considered objectives are to maximize job opportunities and minimize project duration, resource costs, and total energy consumption. To deal with the model, an AUGNMECON2VIKOR algorithm is utilized to create Pareto solutions. In this model, project activities can be crashed by allocating extra resources. Furthermore, multi-skill resources are used to perform project activities. This study also investigates the impact of these resources on project scheduling. To deal with uncertain circumstances, a fuzzy chance-constrained programming method is employed to develop a robust possibilistic programming model. With respect to the increasing significance of sustainability in project management, this study pioneers the examination of the impact of sustainable factors on project scheduling. Finally, the proposed formulation is validated using instances from the well-known PSPLIB and MMLIB test sets. Finally, a comparison is drawn between the presented solution method considering AUGMECON2VIKOR and AUGMECON2. Flowchart of the proposed AUGMECON2VIKOR approach. [Display omitted] • Develop a newly extended multi-objective mixed-integer linear programming model with sustainable development. • Consider a multi-skilled multi-mode resource-constrained project scheduling problem in a real-world condition. • Investigate the impacts of sustainability on a project scheduling problem with preemptive and crashing activities. • Investigate the impacts of multi-skilled resources on energy consumption and social dimensions. • Integrate a robust chance-constrained programming with an AUGMECON2VIKOR method to cope with uncertainty. [ABSTRACT FROM AUTHOR]

Ongoing urban expansion may degrade natural resources, ecosystems, and the services they provide to human societies, e.g., through land use and water changes and feedbacks. In order to control and minimize such negative impacts of urbanization, best practices for sustainable urban development must be identified, supported, and reinforced. To accomplish this, assessment methods and tools need to consider the couplings and feedbacks between social and ecological systems, as the basis for improving the planning and management of urban development. Collaborative efforts by academics, urban planners, and other relevant actors are also essential in this context. This will require relevant methods and tools for testing and projecting scenarios of coupled social-ecological system (CSES) behavior, changes, and feedbacks, in support of sustainable development of growing cities. This paper presents a CSES modeling approach that can provide such support, by coupling socio-economically driven land use changes and associated hydrological changes. The paper exemplifies and tests the applicability of this approach for a concrete case study with relevant data availability, the Tyresån catchment in Stockholm County, Sweden. Results show that model integration in the approach can reveal impacts of urbanization on hydrological and water resource, and the implications and feedbacks for urban societies and ecosystems. The CSES approach introduces new model challenges, but holds promise for improved model support towards sustainable urban development. • We present a tool for planning support by coupling social-ecological systems. • The tool helps identify and understand change drivers and feedbacks. • The tool was successfully tested in an urban-hydrological system in Sweden. • Model coupling can support better decisions for sustainable development. [ABSTRACT FROM AUTHOR]

China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006–2014 and 2015–2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed. Figure Geographical map of ETWP from 2014 to 2022. [Display omitted] • The concept of energy transition welfare performance was defined and accounted for. • The driving factors of energy transition welfare performance were assessed. • The spatial differences of energy transition welfare performance was studied. [ABSTRACT FROM AUTHOR]

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading. • We investigate the nexus between transportation facilities and green development. • We employ the double machine learning model to perform quasi-merge regression. • We affirm this positive effect from the micro enterprise level. • We verify the mediation channels of service industry agglomeration and green innovation level. [ABSTRACT FROM AUTHOR]

Numerous studies have discussed the economic impacts of the COVID-19 pandemic in recent years. However, the effectiveness and trade-offs of diverse countermeasures still need to be investigated, particularly under the long-term goal of low-carbon transition, which is crucial for understanding the potential impacts of the future public health emergency (PHE) related economic crisis. Given that China still faces big pressures from the potential PHE and carbon neutrality, this paper assesses the effectiveness of policy instruments in restoring the economy and advancing green development after the PHE using the Dynamic Stochastic General Equilibrium framework. Our findings reveal that the PHE imposes more constraints on the economy because of the decrease in productivity on the supply side and in consumption on the demand side. Compared to the other counterparts, the mixed stimulus can overcome the adverse impacts of the PHE while contributing to carbon reduction. Furthermore, all types of low-carbon policies investigated in this study can contribute to carbon reduction at the expense of economic growth. Meanwhile, the carbon tax realizes the target of reducing emissions with the smallest negative impact on economic growth. Thus, we suggest adopting the carbon tax policy as the most effective low-carbon measure to address uncertainties associated with the PHE. • This study explores pathways for advancing economic recovery and green development after the public health emergency. • We develop a scenario-based dynamic stochastic general equilibrium (DSGE) model. • We characterize public health emergency shocks from a supply and demand perspective. • The model introduces different carbon abatement mechanisms. [ABSTRACT FROM AUTHOR]

Agricultural and Rural Green Development (ARGD) and economic growth are major challenges prevalent in China, but also in other developing countries. A notable gap in current literature lies in the limited holistic approach to agriculture and rural areas, with scant attention being paid to the spatiotemporal evolution of ARGD and its coordination relationship with economic growth. This paper first offers a theoretical analysis of the interactive relationship between ARGD and economic growth and subsequently examines the policy implementation process in China in this regard. It observes 31 provinces in China from 1997 to 2020 to uncover the spatiotemporal evolution of Agricultural and Rural Green Development Efficiency (ARGDE). Using the coupling coordination degree (CCD) model and the local spatial autocorrelation model, this paper analyses the coordination relationship and spatial correlation between ARGDE and economic growth. The results show that ARGDE in China exhibited a phased growth trend and was greatly affected by policies during 1997–2020. The interregional ARGD produced a hierarchical effect. However, provinces with a higher ARGDE did not necessarily exhibit faster growth, leading to a differential pattern of optimization that involved continuous optimization, phased optimization, and continuous deterioration. Over a long period, ARGDE exhibited a trend of significant upward leaps or jumps. Finally, the CCD between ARGDE and economic growth improved, with a clear trend of high-high agglomeration characteristics that shifted from the eastern and northeastern provinces to the central and western ones. This suggests that promoting "quality agriculture" and "green agriculture" can have practical significance in accelerating the development of ARGD. In the future, it is vital to promote ARGD's transformation while mitigating the risk of degrading the coordinated relationship between ARGD and economic growth. • China's Agricultural and Rural Green Development Efficiency (ARGDE) increased. • Provinces with higher ARGDE did not necessarily have a faster growth rate. • ARGDE exhibits a leapfrogging improvement in a period of 4–5 years. • The coupling coordination degree between ARGDE and economic growth improved. • The High-High cluster have shifted to the central and western regions. [ABSTRACT FROM AUTHOR]

The detrimental effects of climate change are becoming pressingly apparent over the decades with policy-makers clumsily grappling with various policies to mitigate on its impacts on their respective economies. However, inefficiencies permeate in the implementation of these policies as they are being implemented only at the end of the process of economic activities. To resolve such a problem, this paper develops an innovative and novel approach to internalize CO 2 emissions by proposing a ramified Taylor rule which captures a climate change premium, the level of which is directly dependent on the extent of deviation of actual CO 2 emissions from its targeted level. The key benefits of the proposed tool are that not only effectiveness level is being bolstered by applying the tool right at the start of the process of economic activities but also that funds collected out of such a climate change premium could empower governments worldwide to vigorously green their economies. The model is tested for a given economy using the DSGE approach with findings attesting to the effectiveness of the proposed tool in curtailing the level CO 2 emissions, independent of the type of monetary shock under scrutiny. Most importantly, depending on the extent of aggressiveness in mitigating the pollutants level, the parameter weight coefficient can be fine-tuned accordingly. • This paper develops an innovative model to internalize CO 2 emissions by linking CO 2 emissions to the macroeconomic state of the economy through the Taylor rule. • The model is tested using DSGE technique on a given economy. • Many benefits emanating from the newly developed model such as policy effectiveness. • A climate change premium is incorporated in the model which can provide funding to green economic activities. • The parameter weight coefficient can be fine-tuned accordingly depending on the degree of aggressiveness of the economy in mitigating CO 2 emissions. [ABSTRACT FROM AUTHOR]

This paper contributes to the debate on the determinants of deforestation, a menace that is posing threat to sustainable development particularly in tropical developing regions. Specifically, the paper focuses on the effect of energy justice and democratization. The main contribution to the literature hinges on the emphasis on energy justice - operationalized as rural-urban equality in access to electricity and clean fuels and technologies for cooking - and its interaction with democracy. Using a panel data of 47 sub-Saharan African countries over the period 2000–2020 and the dynamic two-step generalized method of moment estimator, the results generally indicate that improvement in rural-urban equality in access to electricity and clean fuels and technologies for cooking is associated with a reduction in deforestation. Democracy is similarly found to be associated with reduction in deforestation. The conditional effect analysis largely depicts an intensified reducing effect of energy justice on deforestation in the presence of improved democratic practices. The results though robust to an alternative estimator, the Driscoll-Kraay estimator, differ when sub-regional analysis is considered. The paper aligns with the Sustainable Development Goals, particularly Goals 7, 13, 15 and 16. • How energy justice and democratization contribute to deforestation is examined. • Energy justice is measured by rural-urban equality in modern energy access. • Participatory, deliberative, egalitarian, liberal and electoral democracy are used. • Improving rural-urban equality in access to modern energy reduces deforestation. • Improving democracy reduces deforestation. [ABSTRACT FROM AUTHOR]

The adoption rate for Leadership in Energy and Environmental Design – Neighborhood Development (LEED-ND) projects has varied considerably across the United States. Local governments and developers face variation in the incentives and barriers while implementing LEED-ND projects across four key dimensions – economic, policy, public awareness, and organizational. This paper investigated the drivers of variation using a mixed-methods approach including a two-stage Heckman model, a survey of Texas subdivision developers and interviews with local planning officials. Results indicate that initial public funding may lead to more LEED-ND projects being completed, but with a diminishing return as these projects become established within the region. Support for local programs including tax abatement, public-private partnerships, and other incentives were also demonstrated to help facilitate LEED-ND project adoption. Overall this paper underscored the important role, especially early on, the public sector and local governments play in initiating local LEED-ND projects to inform and motivate the land development industry. • U.S. LEED-ND projects face variation in adoption rates, barriers, and incentives. • 4 key dimensions identified – economic, policy, public awareness, and organizational. • Initial public funding may lead to more LEED-ND projects being completed. • Local interviews find support for local programs to incentivize further projects. [ABSTRACT FROM AUTHOR]

The exponential growth of waste generation is posing serious environmental issues and thus requires urgent management and recycling action to achieve green sustainable development. Controlled low-strength material (CLSM) is a highly flowable cementitious backfill material with self-consolidating properties. The CLSM efficiency during construction and final performance at the site depends on its plastic properties. Plastic properties are responsible for workability, pumpability, stability, and lateral pressure on adjacent soils. This paper presents a critical review to date on the use of waste materials and/or by-products and their impacts on the plastic properties of the CLSM. Extensive previous studies demonstrated that the basic properties and content of waste materials as well as the amount of water in the mix design, play a dominant role in determining the plastic properties of CLSM. The discussed plastic properties of CLSM include flowability, bleeding, segregation, and hardening time, which are found to be inter-related. Proper mix design adjustment to accommodate the use of waste materials is possible to produce sustainable CLSM with acceptable plastic properties. Additionally, the discussion and analysis presented in this paper could provide a basis for future research advances and the development of sustainable CLSM prepared with waste materials. Image 1 • A critical review to date on effects of waste materials on the plastic properties of CLSM is presented. • The discussed properties include flowability, bleeding, segregation and hardening time. • A large volume of waste materials can be utilized in the production of CLSM. • Utilization of waste materials in CLSM holds great potential for sustainable development. [ABSTRACT FROM AUTHOR]

Abstract In the 1990s, the emergence of Integrated Management Approaches to water, land and waste established a widely accepted understanding on integration of environmental systems. Nexus Approaches try to often build on these. This paper assesses i) the intended goals and features of three Integrated Management Approaches (Integrated Natural Resources Management - INRM, Integrated Water Resources Management - IWRM and Integrated Solid Waste Management - ISWM) and two Nexus Approaches (Water-Energy-Food (WEF) Nexus and Water-Soil-Waste (WSW) Nexus), and ii) how target systems and their integration are viewed in each of the Integrated Management Approaches. From this we assess commonalities and some lessons-learned for the Nexus. The method is based on a systematic literature review and a document analysis. From 1652 articles 52 peer reviewed papers were analysed. The results show that in terms of goals the Nexus Approaches are very similar to Integrated Management Approaches with the addition of clearly wanting to address governance and policy aspects e.g. in the WEF Nexus. Nexus Approaches try to move away from a single-resource centric view (e.g. WSW Nexus) and intend to go beyond resources towards sectors (e.g. WEF Nexus). It cannot be confirmed, that integration is clearly addressed in the analysed Integrated Management Approaches and what integration means is hardly defined. To provide some clarity for Nexus Approaches we propose a concept to describe integration by using " categories of integration " and the term " aspect " which includes systems, subsystems and other aspects alike. Highlights • Successes and failures of integrated management approaches can help the Nexus. • All approaches strive to achieve sustainability, while embracing complexity. • The Nexus aims at addressing governance and policy aspects. • Integration is not clearly addressed in the analysed integrated approaches. • The WSW Nexus' target systems go beyond a single-resource centric view. [ABSTRACT FROM AUTHOR]

Abstract Tropical countries lie at the nexus of three pressing issues for global sustainability: agricultural production, climate change mitigation and biodiversity conservation. The forces that drive forest protection do not necessarily oppose those that drive forest clearance for development. This decoupling, enhanced by the stronger economic forces compared to conservation, is detrimental for the social-ecological sustainability of forested tropical landscapes. This paper presents an integrated, and spatially-explicit, Agent-Based Model that examines the future impacts of land-use change scenarios on the sustainability of the Wet Tropics region of tropical Queensland, Australia. In particular, the model integrates Bayesian Belief Networks, Geographical Information Systems, empirical data and expert knowledge, under a land-sharing/land-sparing analysis, to study the impact of different landscape configurations on trade-offs and synergies among biodiversity and two ecosystem services (sugarcane production and carbon sequestration). Contrary to most tropical regions, model simulations show that Business As Usual is helping to reconcile these contrasting goals in the forested landscape of the Wet Tropics. The paper analyses which combination of governance and socio-economic factors is causing these positive results. This is an outstanding achievement for a tropical region, considering that most tropical areas are characterized for having stronger economic-land clearing forces compared to conservation forces, which reduce important ecosystem services for human wellbeing and the health of ecosystems. Highlights • Integrated Agent-Based Model simulates a social-ecological system of the Wet Tropics. • BAU reconciles sugarcane production, carbon sequestration and biodiversity. • Results driven by different socio-economic, governance and environmental factors. [ABSTRACT FROM AUTHOR]

Abstract Air quality in European cities is still a challenge, with various urban areas frequently exceeding the PM 2.5 and NO 2 concentration levels allowed by the European Union Air Quality Standards. This is a problem both in terms of legislation compliance, but also in terms of health of citizens, as it has been recently estimated that 400 to 450 thousand people die prematurely every year due to poor air quality. Air quality in cities can be improved with a number of interventions, at different sectoral (industry, traffic, residential, etc ...) and geographical (international, European, national, local, etc.) levels. In this paper we explore the potential of city level plans to improve mobility and air quality (excluding electro-mobility options, not considered in this study). We applied the "Sustainable Urban Mobility Plans" (SUMPs) framework to 642 cities in Europe and modelled how the measures they include may impact at first on mobility and emissions at urban level, and then on urban background concentrations of PM2.5 and NO2. Results show that annual averages moderately improve for both pollutants, with reductions of urban background concentrations up to 2% for PM 2.5 and close to 4% for NO 2. The impact on NO 2 at street level (that will be higher than on urban background) is not evaluated in this work. The air quality improvement of the simulated SUMP would only partially alleviate air quality problems in urban areas, but such a reduction in the emissions of air pollutants should still be considered as a positive result of SUMPs, given that they correspond to a set of low-cost measures that can be implemented at local level. Furthermore, the introduction of electro-mobility options (not considered here) would increase the impact on air quality. Other types of benefits, such as reduced fuel consumption, greenhouse gas emissions, higher impact at street level or accident rates reduction further add to the overall positive impact. Highlights • SUMPs (Sustainable Urban Mobility Plans) concept have been applied to 642 cities In Europe. • Impact on modelled "urban background concentrations" has been evaluated. • Results show that this impact is limited for "urban background concentrations". • The impact of SUMPs on street level concentrations, and electro-mobility options, are not evaluated in this paper. • Other benefits of SUMPs (on greenhouse gases, reduced accident rates, etc ...) should be also considered. [ABSTRACT FROM AUTHOR]

Synergetic control of environmental pollution and carbon emissions (SCEPCE) is essential to green development. The emergence of the digital economy has become a significant component in regional economic growth. Investigating the digital driving mode for SCEPCE in developing countries is crucial. This paper empirically analyzes the effect of establishing big data comprehensive experimental areas (BDCEAs) on air pollutants and carbon emissions using panel data of prefecture-level cities from 2009 to 2020 and the time-varying difference-in-differences method. The research found that (1) BDCEA inhibits pollution and carbon emissions, and the policy effect is sustainable. (2) The synergistic effect is significant, particularly in small and medium-sized cities and old industrial-base cities. The benefit of reducing pollution is only significant in the east. The effect of reducing CO 2 emissions is only significant in the west. (3) The pollution reduction effect of digital economic development has the characteristics of an increasing marginal effect, and the marginal effect of its carbon reduction effect is not apparent. (4) The technological innovation and energy efficiency improvement effects are effective mechanisms. This paper enriches the studies on the factors influencing SCEPCE, which will help to realize SCEPCE and the harmonious coexistence of humans and nature in developing countries. However, policy incentives and green development strategies must be fine-tuned to achieve global SCEPCE. • Digital economy realizes synergistic effect of pollution and carbon emission mitigation. • The findings have significant implications for governments. • The pollution reduction effect has the characteristics of an increasing marginal effect. • The technological innovation and energy eficiency improvement effects are effective mechanisms. [ABSTRACT FROM AUTHOR]

An increasing number of countries and regions consider the bioeconomy transition a strategic policy priority. When approached through the lens of a circular economy perspective, investments in bioeconomy have the potential to enhance resource utilisation efficiency, preserve biodiversity and ecosystems, and foster sustainable development with low emissions. At the same time, if requirements and contextual factors of bioeconomy strategies are not formally analysed, bioeconomic investments might lead to unintended negative consequences. This paper proposes a decision support procedure to design, assess, prioritise, and monitor bioeconomy investments and policies. The flexibility and scalability of our decision support procedure is tested in Colombia to foster a regional and local transition to bioeconomy initiatives that consider the local capital assets and the stakeholders' views. The heterogeneous character of the Colombian environment, economy, society and culture represents an ideal condition to test the strength of the decision support procedure to promote bioeconomy in low and middle-income countries. Our empirical results highlight the benefit of adopting a formal assessment framework that includes strategic national indicators, regional features and stakeholders' views. In terms of the Colombian regional bioeconomy ambitions, we highlight the need for expanding knowledge hubs and participatory stakeholder networks and buttressing appropriate financial mechanisms. • Bioeconomy transition needs to be framed in an extended circular economy framework. • Bioeconomy strategies need to consider local context and stakeholders' engagement. • Scalable and replicable decision support procedures should guide bioeconomy implementations. • Balance sheet approach inform all stages of bioeconomy policies and projects. • Application of the balance sheet approach in Colombia highlights diverse local priorities. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

This paper analyses the impacts of trading partners' environmental regulation on the export volumes of the Russian regions, using panel data covering about 140,000 observations in 84 Russian regions and 204 countries for the period 2013–2020. We employ the Gravity Model of international trade and Heckman Sample Selection methodology, with the fixed effects and random effects Poisson Pseudo-Maximum Likelihood techniques to analyse two subsamples of the Russian regions with different shares of environmentally sensitive goods in regional exports. As a robustness check, we utilize the non-parametric Driscoll–Kraay approach. The results of the econometric estimation demonstrate that environmental regulations enhance the export of regions with a high share of environmentally sensitive goods in export structure, while for the rest of the regions the environmental regulations negatively affect export volumes. The promoting effect is associated with a higher level of innovativeness of the regions and the role of the global energy transition process. We conclude that the environmental agenda is a challenge for some Russian regional exporters due to the lack of own environmental regulation, and to the specific features of the commodity and geographic structure of exports. To transform the negative impact into the positive one for all Russian regions, policy measures are necessary on the federal, regional, and company levels, encompassing environmental regulations and green development strategies, along with innovation and cluster policies, and the development of human capital and infrastructure. • Environmental regulations affect exports differently across Russian regions. • Innovative potential of regions is a key for positive effect. • Global energy transition can stimulate environmentally sensitive exports. • Solar energy positively affects exports, while wind energy is neutral. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions. • This paper studies the effects of AI on China's GTFP from internal-structural perspective. • GTFP is decomposed into three internal factors by the global Malmquist index. • AI has positive effect on GTFP through different impacts on internal factors. • Improving resource allocation efficiency is the most critical channel of AI on GTFP. • AI plays a more significant role in promoting GTFP in less developed areas. [ABSTRACT FROM AUTHOR]

In today's world, where economic development and environmental sustainability are becoming increasingly important aspects of national strategy, attention to the impact of different economic sectors on climate change is becoming an integral part of scientific research. This article focuses on analyzing the impact of primary and secondary economic sectors development on carbon dioxide (CO 2) emissions at the sub-national level in Russia from 2005 to 2019. The aim of the study is to provide an in-depth understanding of the relationships between the dynamics of these sectors and CO 2 emission levels in different regions of the country. Weighted regression and panel data methods were applied to better identify the patterns of the impact. The results show that the size of population and electricity consumption have the highest impact on CO 2 emissions. So that, the expansion of nuclear and gas generation capacity, as well as significant improvement of energy efficiency, are of crucial importance to reduce the emissions. Other sectors have a heterogeneous impact and requires more differential approaches, considering the specifics of regions. Taking into account the significant differences between the Russian constituent entities, this paper emphasizes the low informativeness of assessments at the national level and their inadequacy in terms of improving the efficiency of domestic management, including decarbonization policies. • The impact of considered economic sectors on CO 2 emissions were analyzed in 80 Russian constituent entities in 2005–2019. • Weighted regression and panel data methods were used to catch the specifics of Federal districts and constituent entities. • Population size and electricity consumption have the highest impact on CO 2 emissions. • Increasing energy efficiency and modernization of energy facilities are the most promising solutions to reduce the emissions. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Developing an efficient strategy for managing nutrients in less-developed lake watersheds that can balance the need for socioeconomic progress with the protection of aquatic ecosystems has become an urgent research subject for achieving sustainable development. This paper improves the optimization method for environmental and economic management of lake watersheds proposed in our previous research. A spatiotemporal optimization method based on a coupling model consisting of the Soil and Water Assessment Tool, system dynamics model, and objective programming model was applied to an agricultural non-point source (ANPS) pollution control program and a rural sewage treatment program at the Yilong Lake watershed as a case study. A simulation evaluation showed that the efficiency of the previous scheme was significantly improved after conducting spatiotemporal optimization. This scheme was dynamic and distributed, demonstrating an annual and high-resolution control program that can provide a basis for the precise management of ANPS. Although it still requires improvement, a framework for coupling simulation and two-step optimization was achieved in this study. • A framework for coupling simulation and two-step optimization is completed. • Spatiotemporal optimization could significantly improve the scheme, which is output by an objective programming model. • A dynamic and high-resolution NPS control program for paddy fields is obtained. [ABSTRACT FROM AUTHOR]

Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO 2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction. • Analysis of placed-based policy on resource at the county-level. • Coordinated effects of green expansion and carbon reduction are tested. • Key areas of policy effects are identified. • Industrial structure transformation and its related mechanisms are discussed. [ABSTRACT FROM AUTHOR]

Practicing ESG concept is a necessary way for sustainable development of enterprises and an important hand in realizing high-quality economic growth. This paper introduces the hypothesis of "distance attenuation effect" of geo-economics into the research field of corporate ESG performance, and systematically examines the impact of neighboring the Environmental Protection Agency (EPA) on corporate ESG performance by using the data of China's listed companies in the manufacturing industry from 2011 to 2021. It is found that being a neighbor to the EPA has a significant inhibitory effect on corporate ESG performance, which was reduced by 0.196% when the distance between the two was reduced by every 1 km. And the inhibitory effect has a stepwise decreasing characteristic, i.e., it is the strongest at the level of county EPA, followed by municipal EPA, and the smallest at the level of provincial EPA. The mechanism analysis shows that the rent-seeking behavior caused by neighboring with EPA is an important reason for the decline of ESG performance, which verifies the "distance attenuation effect" of rent-seeking difficulty. Although neighboring the EPA improves firms' financial performance, it greatly harms firms' environmental, social and governance performance, which confirms the profit-seeking motive of firms' rent-seeking. In addition, the deterrent effect generated by third-party supervision and digital supervision can inhibit corporate rent-seeking to a certain extent, which helps weaken the negative impact of neighboring the EPA on corporate ESG performance. • Neighboring the EPA has a significant inhibitory effect on corporate ESG performance. • The rent-seeking behavior caused by neighboring with EPA is an important reason for the decline of ESG performance. • Neighboring the EPA improves firms' financial performance and greatly harms firms' environmental and social performance. • Public and media attention can helps to weaken the negative impact of being a neighbor of the EPA on firms' ESG performance. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore how Internet use affects an individual's environmental sustainability awareness. To this end, we adopt data from the 2021 wave of Chinese General Social Survey, measure the environmental sustainability awareness by 14 categories of items, and employ a treatment effect model to identify the relationship. The results reveal that Internet use is significantly associated with an increase in people's environmental sustainability awareness. Our study sheds light on the underlying mechanism of the positive correlation via an information-based channel. Furthermore, we also find that the facilitating effect is more pronounced in economically developed regions. This work provides a new insight into the determinants of environmental sustainability awareness and offers several implications to conduct sustainable development policies in the digital era. • Investigating the impact of Internet use on environmental sustainability awareness. • Estimating a treatment effect model to investigate the relationship between Internet use on environmental sustainability awareness. • Internet use is significantly associated with an increase in people's environmental sustainability awareness. • Revealing the underlying mechanism of the positive correlation via an information-based channel. • The facilitating effect is more pronounced in economically developed regions. [ABSTRACT FROM AUTHOR]

This paper is likely the first attempt to empirically investigate the direct effect of geopolitical risk on sustainable development goals (SDGs). We employ a newly developed SDG index along with its 17 sub-indices from the United Nations to capture various aspects of sustainable development. On a panel sample covering 41 countries from 2015 to 2021, we find that elevated geopolitical tensions can hinder the progress towards achieving sustainable development goals. This result is robust to various model specifications and estimation approaches. Further analyses show that the two dimensions affected are Decent Work and Economic Growth (SDG8) and Climate Action (SDG13). Heterogeneity test finds that the negative effect of geopolitical risks is only present in countries highly dependent on natural resources. More importantly, improvements in institutional quality could partially offset the detrimental effect of geopolitical risks on sustainable development goals. Therefore, this study provides important implications for policymakers in devising measures to maintain the progress to achieve SDGs in the era of rising global uncertainties. • Geopolitical tensions hinder the achievement progress towards sustainable development. • The two dimensions affected are Decent Work and Economic Growth and Climate Action. • Only countries highly dependent on natural resources are affected. • Improvements in institutional quality could offset the effects of geopolitical risks. [ABSTRACT FROM AUTHOR]

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM 2.5 data of 223 prefecture-level and above cities in China mainland during 2004–2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development. • Using spatial panel smooth transition autoregressive regression model for 2004–2016, we revisit the nonlinear effects of socio-economic factors on urban haze in China. • The ARAR-STAR model is estimated by quasi-maximum likelihood estimation. • We employ Monte Carlo simulation to obtain robust results. • The effect of population density, industrial structure, energy consumption, opening-up on haze emission has heterogeneity with the smooth transition between high and low regimes with economic development. [ABSTRACT FROM AUTHOR]

Green investment transformation is the main interval difference of the Belt and Road Initiative, however, its actual effects are still uncertain. Finding out its utility, mechanism and improvement on green economy may accelerate green development. In this paper, Slack Based Measure model is used to obtain original results, Super-Efficiency model is used to sort effective decision-making units for stronger efficient frontier and Minimum Distance to Strong Efficient Frontier model is used to narrow gaps between non-effective ones and real situations. Then Global Malmquist-Lunberger index makes results dynamisation. Samples of 51 countries joining the Belt and Road Initiative from 2008 to 2022 are used in above-mentioned models to portray green economic dynamics. Then utility, mechanism and improvement of green investment transformation on green economy are studied through econometric model. The findings show that (i) Green Belt and Road Initiative makes green economic development more stable. The standard deviation decreases by 96.53% and mean maintains in 1.5. However, disconnection between a 36.36% increase of pure technological change and a 24.83% decline of its scale effect inhibits technical advance. (ii) Share of countries obtaining green scale revenues reaches 56.86%, which realizes a 52.64% increase. Furthermore, gaps between countries with positive status and those with negative status narrow 68.42%. Positive group accounts for 50% in developed countries and 46.15% in developing countries. (iii) Performance of Green Belt and Road Initiative is better than the Belt and Road Initiative. A one standard deviation increase in green investment transformation increases green economic development by 0.2705 (0.2105), which is a 18.57% (14.45%) increase relative to average green economic development of 1.457. Former's strengths also reflect in different quantiles, lagging effect and heterogeneity analysis. (iv) Green investment transformation of Green Belt and Road Initiative broadens more reliable mechanism (Promote Innovation - Strict Regulation - Ensure Commercialization) based on original one (Improve Efficiency - Decrease Costs - Increase Revenues) of the Belt and Road Initiative. (v) For the green investment transformation with government subsidies, property rights protection, investment environment stability and exchange cooperation, magnitudes of its effects on green economic development have significant increases by 25.03%, 31.77%, 8.01% and 10.12% respectively. The findings not only help understand green economic status, but also support some policy insights for achieving green economy by discovering utility, mechanism and improvement of green investment transformation. [Display omitted] • Portraying green economic dynamics in countries joining the Belt and Road Initiative. • Analyzing interval difference, and then exploring the intrinsic driver. • Distinguishing technical performance and imitable benchmarks of individual characteristics. • Empirically testing effects of green investment transformation on green economic development. [ABSTRACT FROM AUTHOR]

Numerous studies have revealed that developing green technology innovation is extremely important for minimizing haze pollution. However, limited by serious endogenous problems, research rarely focuses on the effect of haze pollution on green technology innovation. Based on a two-stage sequential game model including both production and government departments, this paper mathematically deduced the effect of haze pollution on green technology innovation. Then China's central heating policy is considered a natural experiment in our study to verify whether haze pollution is the key factor affecting the development of green technology innovation. The result that haze pollution significantly inhibits green technology innovation is confirmed, and this negative impact is mainly concentrated on substantive green technology innovation. Robustness tests have been performed, and the conclusion is still valid. Moreover, we find that government behavior can significantly affect their relationship. Specifically, the government's economic growth target will increase the haze pollution's ability to block the development of green technology innovation. However, if the government has a clear environmental target, their negative relationship will weaken. Based on the findings, targeted policy insights are presented in this paper. • Introducing a two-stage sequential game model and mathematically deduced how haze pollution affects green innovation. • China's central heating policy is considered a natural experiment. • The result that haze pollution significantly inhibits green technology innovation is confirmed. • The economic and environmental target constraints affect the impact of haze pollution on green technology innovation. [ABSTRACT FROM AUTHOR]

Over the years, due to the climate crisis, sustainable economic growth and biodiversity protection have been increasingly promoted. Scientists, researchers, and experts in the field of sustainable development highlighted that bio-based restoration of ecosystems and responsible management of existing resources are needed to meet the needs of future generations. This paper discusses some of the latest developments in three main areas of sustainability, i.e., energy, water and environment, that emerged from the "16th Sustainable Development of Energy, Water and Environment Systems Conference – SDEWES 2021". The purpose of this introduction article is to briefly review the articles included in this Virtual Special Issue. As such, it acts as an editorial paper for the virtual special issue of the Journal of Environmental Management, dedicated to the SDEWES 2021 conference. [ABSTRACT FROM AUTHOR]

Policies directly or indirectly influence the development of industrial symbiosis (IS). Quantitatively analyzing the effects of policies on IS at a national level is necessary, but current research has lagged. Focusing on the symbiotic system that includes the thermal power industry, cement industry, iron and steel industry, and social sector in China, this paper assesses the efficacy of policies on this nationwide IS system between 2015 and 2022. A policy influence framework is proposed, combining a cost-benefit analysis, agent-based model, and comparative analysis. Results show: (1) the symbiosis probability of the nationwide IS system experiences a fluctuating increase. The maximum increments of the symbiosis probability are 5%, and the resulting environmental benefits are equivalent to an emission reduction of 6.99 Mt from blast furnace slag, 20.97 Mt from iron mine tailing, 36.02 Mt from household waste, 25.01 Mt from steel slag, and 22.95 Mt from fly ash. However, the stimulation effects of policies vary across different subsystems. (2) Thermal power-chemical subsystems, thermal power-environmental protection subsystems, iron and steel-environmental protection subsystems, and social sector-cement subsystems need policy support in the future. (3) Approximately 50% of fields in this nationwide IS system is insensitive to current policies; policy approaches should shift from economic stimulation to symbiotic guidance. This paper fills the research gap by quantitatively studying the IS policy efficacy from a national level. The findings can contribute to the improvement of the Chinese IS policy system. [Display omitted] • Quantitatively analyzing the effects of policy on industrial symbiosis at a national level. • Policy-sponsored incentive effects vary across different types of waste and subsystems. • Half of the symbiotic utilization fields are insensitive to current policy. • The policy should shift from economic stimulation to symbiotic utilization guidance. [ABSTRACT FROM AUTHOR]

Clean energy conversion is a core approach and development trend to tackle climate change, while the severe drawbacks such as supply deficiency and cost increase restrict regional sustainable development. This paper employs a natural experiment of coal-to-gas conversion of the Chinese government to study the effect of such policy on regional sustainable development, as well as the underlying mechanism. Based on a city-level dataset from 2006 to 2019, this paper measure green total factor productivity (GTFP) using data envelopment analysis (DEA) combined with the Malmquist‒Luenberger productivity index. Then, this paper evaluates the impact of the CTG policy in pilot cities using the Difference-in-Difference (DID) with Propensity Score Matching (PSM) approach. This paper finds that the CTG policy increased the GTFP of the pilot cities by 2.25% (0.0229/1.02). A series of robustness tests confirmed the findings. Subsequent mechanism analysis shows that the CTG policy increases the GTFP of pilot cities mainly by increasing technical efficiency. In addition, the mechanism of the CTG policy's impact differs between central and noncentral cities. In particular, the CTG policy increases the technological innovation indicator (TC) of provincial capital cities by 2.35% while it increases the technical efficiency indicator (EC) of other cities by 1.89%, which proves the Porter effect in provincial capital cities. Finally, several implications are provided for policymakers to promote other types of renewable energy. • A detailed energy conversion policy analysis is provided. • The GTFP is measured through DDF and MLI techniques. • Mandatory energy conversion can benefit regional sustainable development. • DID approach and various robustness checks support this finding. • Central and non-central cities developed differently in innovation. [ABSTRACT FROM AUTHOR]

Based on the unique perspective of local environmental regulations promulgated in Chinese prefecture-level cities from 2000 to 2018, this paper examines the impact of urban environmental legislation on green total factor energy efficiency (GTFEE). The results show that implementing environmental legislation significantly improves local GTFEE , with comprehensive protection regulations contributing to local energy efficiency improvements, while the impact of pollution prevention regulations is insignificant. This conclusion remains robust to multiple scenarios. Potential mechanisms through which environmental legislation can guide urban green transition include the industrial upgrading effect represented by "clean industry development" and "polluting industry exit", as well as the technical innovation effect achieved through "new technology generation" and "old technology upgrading". Furthermore, environmental legislation with a higher degree of regulatory effectiveness has a greater potential for energy saving. Environmental legislation has a more significant impact on improving GTFEE in cities in non-old industrial bases, with less frequent turnover of officials, and in central and western regions in China. This study evaluates the positive impact of urban environmental legislation on GTFEE , aiming to advancing the rule of law in local environmental pollution governance and thereby promote urban green transition. • Use a Difference-in-Differences model to explore the effect of urban environmental legislation. • Environmental legislation guides urban green transition development. • The impact of heterogeneous urban environmental regulations on green transition development. • Industrial upgrading and Technical innovation have positive mediating roles. • Environmental legislation policy has city attributes, official turnover and location heterogeneity. [ABSTRACT FROM AUTHOR]

Green power trading is an institutional innovation proposed by China to promote green and sustainable development. This policy aims to relieve the serious debt pressure of renewable energy generation enterprises, thus laying the foundation for achieving carbon reduction targets. This paper empirically examines the role of green power trading by constructing the difference-in-differences (DID) model. Our findings indicate that green power trading significantly reduces the debt levels of policy-covered generation enterprises. This effect is more pronounced for state-owned enterprises, companies with better ESG performance, companies in regions with higher degree of marketization and companies specializing in renewable energy power generation. Further research discusses the impact mechanism of green power trading in terms of external and internal environmental channels. We find that a strong green development atmosphere, especially the external atmosphere, will significantly reinforce the weakening effect of green power trading on corporate debt. Our research provides empirical evidence for the success of green power trading policy in its pilot phase. • Green power trading significantly alleviates the policy-covered firms' debt burden. • The role of green power trading presents heterogeneity in enterprise characteristics. • A better regional environment for green growth can stimulate the effect of green power trading. [ABSTRACT FROM AUTHOR]

The excessive use of fossil energy in industrialization has caused the frequent occurrence of global warming and environmental pollution issues, which seriously threaten the sustainable social and economic development of South Korea and other countries. In response to the international community's call to effectively address climate change, South Korea has announced achieving carbon neutrality by 2050. In this context, this paper takes the carbon emission of South Korea from 2016 to 2021 as a sample an d focuses on using the GM(1,1) model to predict the carbon emission change trajectory of South Korea in the process of achieving carbon neutrality. The results show: first, in the process of carbon neutrality, South Korea's carbon emissions show a downward trend, with an average annual rate of 2.34%. Second, by 2030, carbon emissions will decline to 502.34 Mt CO 2 e, down about 26.79% from the 2018 peak. By 2050, South Korea's carbon emissions will decline to 312.65 Mt CO 2 e, down about 54.44% from the 2018 peak. Third, it is difficult for South Korea to achieve its carbon neutrality target by 2050 based solely on its forest carbon sink storage capacity. Therefore, this study is expected to provide a reference for improving the carbon neutrality promotion strategy in South Korea and strengthening the construction of relevant systems of carbon neutrality, and so can provide some reference for other countries, including China, to improve policy design to promote the green and low-carbon transformation of the global economy. • A GM(1,1) model is used. • By 2050, South Korea's carbon emission will drop to 312.65 MtCO2e. • South Korea will achieve the carbon neutrality target in 2050. [ABSTRACT FROM AUTHOR]

This study analyzed the theoretical mechanism of the carbon emission effect embodied in the Sino-USA manufacturing trade. We constructed a trade and carbon emission input-output model for 16 manufacturing sub-sectors in China and the USA from 2000 to 2018. A comprehensive empirical test of the systematic emission reduction mechanism was conducted. There were four main findings: (1) indirect and direct carbon emissions indicators can comprehensively analyze the link between production and demand across sectors; (2) indirect carbon emissions are higher than direct carbon emissions in half of the sectors in both China and the USA, and other sectors bear part of the carbon emissions for these sectors; (3) compared to 2000, the change in net exports of both countries is the main reason for the change in indirect carbon emissions, while the change in net exports of intermediate goods is the main reason for the change in direct carbon emissions; and (4) the Sino-USA trade surplus comes at the expense of China's environmental losses, while the USA obtains environmental benefits. Overall, the theoretical analytical framework not only comprehensively considers the interlinkages between production and demand across sectors but also provides a more reasonable evaluation of the environmental effects of Sino-USA trade. Additionally, this study provides a solid theoretical and empirical basis for China to achieve its dual-cycle and dual-carbon goals, thus promoting the rapid transformation of China's economy toward green and high-quality development. [Display omitted] • The carbon emission effect mechanisms of Sino-US manufacturing trade are analyzed. • Carbon emissions indicators reveal production-demand linkages across sectors. • The economic and environmental gains and losses of Sino-USA trade are evaluated. • Sino-USA trade harmed China's environment and benefited USA. • This paper identifies the key path to cut China's manufacturing CO2. [ABSTRACT FROM AUTHOR]

Environmental taxation is an essential tool employed by governments to compel polluting enterprises to undergo green transformation, thereby achieving sustainable development. This paper uses Differences-in-Differences (DID) approach to assess the impact of the China's environmental tax law on the ESG performance of heavily polluting industries. Furthermore, it examines the moderating effect of stakeholder behavior on the relationship between the environmental tax law and the ESG performance of firms. The research findings indicate that the environmental tax law significantly enhances the ESG performance of heavy polluting enterprises by improving the environmental factor. However, heterogeneity is observed based on ownership characteristics and regional variations. Auditors, mass media and corporate ethical behavior exhibit a significant positive moderating effect on the causal relationship between the environmental tax law and the ESG performance of heavily polluting enterprises. This study contributes to a clearer understanding of the intrinsic relationship between environmental tax laws and ESG performance, and offers insights from the perspective of stakeholder behavior for formulating a path towards sustainable development in the country, thereby providing policy lessons for numerous developing countries worldwide. • Matching data of Chinese listed companies with Bloomberg ESG scores. • Environmental tax law boosts ESG in polluters (E-focused impact). • Auditors reinforce tax law's ESG effect via opinions. • Media shapes ESG by affecting social perception (S factor). • Ethics matter: corruption risks inflate ESG in targeted firms. [ABSTRACT FROM AUTHOR]