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Land-use change in the boreal forest region leads to agriculture to be carried out on acid, shallow and low fertility soils. To correct soil fertility and promote crop productivity, manure and inorganic fertilizers are added, increasing the risk for greenhouse gas emissions (GHGE). To reduce the reliance on synthetic soil amendments while taking advantage of locally relevant industrial by-products, wood ash (WA) and paper sludge (SL) have been proposed as soil amendments for a range of soil types. We posited that amending soils with WA , SL and biochar will improve soil health parameters and fertility of boreal soils. Microbial activity resulting to nitrogen losses and availability were assessed. WA had a stronger ameliorative effect on acid boreal soils compared to SL. Both WA and SL increased soil microbial biomass and basal respiration resulting in higher net mineralization and thus significant increases in CO 2 emissions. Co-application of urea with WA or SL further increased net mineralization compared to when used independently. Conversely, the biochar's effect was short-lived and not significant. Nevertheless, addition of biochar was shown to reduce CO 2 emissions in all cases except in WA amended soils. No significant differences were observed in CH 4 emissions across all treatments. WA and SL may improve soil fertility and quality but could also contribute significantly to GHG emissions in acid boreal soils. Further research is recommended to assess the mitigating effect of various biochar feedstocks on GHG emissions when co-applied with WA and SL. • The effect of wood ash and paper sludge on acid soils was tested in incubation tests. • Both increased the soil microbial biomass, respiration, and net mineralization. • Greenhouse gas emissions were larger for paper sludge amended soils. • Supplementing biochar to wood ash increased soil CO 2 fluxes. • Supplementing biochar to paper sludge or limestone ash reduced soil CO 2 fluxes. [ABSTRACT FROM AUTHOR]

Changes in material use, energy use and emissions profiles of industry are the result of complex interrelationships among a multitude of technological and economic drivers. To better understand and guide such changes requires that attention is paid to the time-varying consequences that technology and economic influences have on an industry''s choice of inputs and its associated (desired and undesired) outputs.This paper lays out an approach to improving our understanding of the dynamics of large industrial systems. The approach combines engineering and econometric analysis with a detailed representation of an industry''s capital stock structure. A transparent dynamic computer modeling approach is chosen to integrate information from these analyses in ways that foster participation of stakeholders from industry and government agencies in all stages of the modeling process—from problem definition and determination of system boundaries to generation of scenarios and interpretation of results.Three case studies of industrial energy use in the USA are presented—one each for the iron and steel, pulp and paper, and ethylene industry. Dynamic models of these industries are described and then used to investigate alternative carbon emissions and investment-led policies. A comparison of results clearly points towards two key issues: the need for industry specific policy approaches in order to effectively influence industrial energy use, fuel mix and carbon emissions, and the need for longer time horizons than have typically been chosen for the analysis of industrial responses to climate change policies. [Copyright &y& Elsevier]

Countries worldwide consider solid waste collection and recycling necessary due to the recent emphasis on conservation of resources and environmental protection. Due to the constraints from resource depletion and the need for sustainable economic growth, solid waste recycling has become a critical issue in China. Several indigenous researchers in China have studied the potential benefits of solid waste recycling. However, most studies limited the environmental assessment of solid waste recycling to greenhouse gas (GHG) emissions and considered only one type of solid waste (paper or plastic). Therefore, the present study analyzed the energy (electricity) and environmental (GHG and air pollutant emissions) benefits of recycling steel, nonferrous metal, plastic, and paper wastes from 2005 to 2017 in China. The study used the formulation of model equations method to estimate the electrical energy and environmental benefits. Prominent findings show that the total amount of electricity saved by recycling solid waste from 2005 to 2017 was 3743.3 Mtce. On average, solid waste recycling during the period led to a 43.2% saving on electricity. Solid waste recycling avoided 4765.9 billion kg of carbon dioxide emission and 22.502 billion kg of methane emission. It was also found that the recycling of solid waste saved a total amount of 10,669.8 M kg of NO X emission but had a burden of −6263.2 M kg of VOCs emission on the environment. Solid waste recycling avoided the emission of CO 2 , CH 4 , NO X , and SO X, but the recycling of steel, plastics, and paper waste had negative impacts on the environment in terms of VOCs and PM emissions. Proper measures such as installing air pollution control devices should be put in place to minimize the emission of pollutants during the recycling of these solid wastes. • The energy and environmental benefits of solid waste recycling is assessed. • The formulation of model equations method was used for the assessment. • On average, the recycling of solid waste saved 43.2% of electricity. • Recycling of waste avoided a significant amount of GHG and air pollutant emissions. • Solid waste recycling had no essential benefit on the emission of VOCs and PM. [ABSTRACT FROM AUTHOR]

In future decarbonised energy systems, residual carbon emissions require strategic planning and management. In environmental management, an evaluation of carbon removal considering local geographic frameworks is needed. This paper introduces a scalable and adaptable model for evaluating the economics and geography of future carbon capture and storage (CCS) configurations across geographical scales, covering capture, transport, and storage of carbon. The model is applied to the North Denmark Region, showing that future energy production carbon sources will be concentrated in Thisted and Jammerbugt, while industrial sources remain in Aalborg and Rebild municipalities. Carbon transport configurations, including truck, pipeline, and shipping are assessed, for the carbon to be stored in onshore and offshore geological storages. The regional scale findings suggest that pipelines and onshore storage provide the most economical configuration. However, a sensitivity study using a smaller geographical scope indicates potential for optimising carbon transport by evaluating both carbon volume and distance. The paper discusses how the model's flexibility and scalability enable the integration of alternate cost components, thereby supporting the calculation of the carbon repurposing potentials, including carbon capture, utilisation, and storage (CCUS) configurations. • Develops a scalable geographical cost model for CCS. • Quantifies CO 2 from future energy production and industrial facilities by 2045. • Estimates 2.45 million tonnes of annual capturable CO 2 for CCS by 2045. • Transport analyses show trucking and piping cost benefits for smaller CO 2 sources. • Locates infrastructure opportunities for CO 2 utilisation via CCS geographic routing. [ABSTRACT FROM AUTHOR]

Accurately identifying the historical causes of carbon emissions in the process of national economic development is an important basis for developing countries to achieve carbon emission reduction. This paper explores the intrinsic institutional causes of China's high CO2 emission growth based on the characteristic economic growth target system of China, and attempts to empirically test the environmental effects behind this system. The results of the study show that the setting of absolute economic growth targets significantly increases the carbon dioxide emissions of cities under horizontal competition, and the setting of relative economic growth targets exacerbates the above carbon emission effect under vertical competition. In addition, the heterogeneity analysis shows that the carbon emission effect of setting economic growth targets is stronger in resource-dependent cities and cities with a lower level of economic development. Mechanism tests show that economic growth targets not only significantly increases total fossil energy consumption and reduces energy efficiency at the firm level, but also leads to the increase of energy consumption and the reduction of energy efficiency at the industry level. The findings of this study provide an intrinsic institutional explanation for China's high carbon emissions and provide useful guidance for the design of mechanisms to achieve large-scale carbon emission reductions in developing countries. • This paper investigates the impact of economic growth targets on carbon emissions. • How economic growth targets setting system affects carbon emissions remains underexplored. • There are significant differences in the impacts of EGT setting regimes on carbon emissions in cities with different types of development. • The economic growth targeting system influences regional carbon emissions through two pathways: energy consumption levels and energy efficiency. [ABSTRACT FROM AUTHOR]

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government. [Display omitted] • Exploring the national carbon peaking path from a provincial perspective. • Expanding the STIRPAT model combined with scenario analysis to study provinces. • Adjusting industry and reducing energy intensity are key to carbon control. • China can achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. • Research on carbon peaking pathway based on provincial heterogeneity. [ABSTRACT FROM AUTHOR]

Strategic coordination between urbanization and carbon emission efficiency (CEE) is vital for promoting low-carbon urbanization and sustainable urban planning. In order to assess the coupled coordination degree (CCD) of urbanization and CEE and investigate the factors influencing the CCD, this research employs the Super slacks-based measure (SBM) model, the coupled coordination degree model (CCDM), and the Tobit model. Four key findings emerge from the analysis of the temporal and spatial evolution traits of the CCD based on data from 106 nations worldwide between 2005 and 2020. (1) The global CEE shows a significant downward trend, and the spatial disparity is unambiguous. high CEE countries hang in the north and west of Europe, while those in Asia, Africa and the east of Europe have lower CEE. (2) The combined urbanization level and demographic, economic and social urbanization are all on an upward trend. Singapore has the greatest degree of urbanization overall globally. (3) The CCD of urbanization and CEE shows a fluctuating upward trend, with particularly strong changes in 2018–2020. 2017 and 2018 are the years with better global coupling coordination status. During the study period, the CCD results of countries are mostly uncoordinated and low coordination, and the CCD of the United States, China, India and Japan is in the front. (4) The effect of urban electrification rate on the CCD is positive; the effect of foreign trade and net inflow of foreign direct investment is negative; while energy structure and industrial structure have no significant effect. A number of policy proposals are put forth in light of the outcomes of the research to enhance the coordination. • This paper constructs a comprehensive and scientific integrated system of urbanization from the demographic, economic and social aspects. • Using the Super-SBM model, this paper analyzes CEE more comprehensively and systematically from three perspectives: national, developed and developing countries, and regional. • The CCDM is utilized to assess the CCD of urbanization and CEE, and the spatial evolution of the CCD is analyzed, which enriches the research in the field of low-carbon urbanization. [ABSTRACT FROM AUTHOR]

The cement industry plays a significant role in global carbon emissions, underscoring the urgent need for measures to transition it toward a net-zero carbon footprint. This paper presents a detailed plan to this end, examining the current state of the cement sector, its carbon output, and the imperative for emission reduction. It delves into various low-CO 2 technologies and emerging innovations such as alkali-activated cements, calcium looping, electrification, and bio-inspired materials. Economic and policy factors, including cost assessments and governmental regulations, are considered alongside challenges and potential solutions. Concluding with future prospects, the paper offers recommendations for policymakers, industry players, and researchers, highlighting the roadmap's critical role in achieving a carbon-neutral cement sector. • Cement industry faces urgent need for net-zero transition due to high carbon emissions. • Roadmap spans phases: foundation, acceleration, net-zero, targeting emissions by 2050. • Innovations like alkali-activated cements offer promise for emission reduction. • Collective action and policy crucial for sustainable transformation of cement sector. [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]

The digital economy (DIE), a new economic form with digitalization at its core, has become an important driving force for promoting regional economy development. In the context of the COVID-19 pandemic, exploring the impact path of the DIE on carbon emission efficiency (CEE) is conducive to giving full play to the "carbon-reduction-and-efficiency-enhancement" role of the DIE, and to promoting the realization the "dual carbon" goal of carbon peak and carbon neutrality. In this paper, the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB) are taken as study areas, the panel Tobit model is used to explore the impact of the DIE on CEE, and the intermediary-effect model and threshold-effect model are constructed to test the intermediary and threshold effects of technological innovation, respectively. The results show that the DIE has a U-shaped nonlinear impact on CEE in both the YRB and the YREB and that the impact has regional heterogeneity. Technological innovation can play a mediating effect between the DIE and CEE, whereas the mediating effect in the YRB is stronger than that in the YREB. Technological innovation has a threshold effect on the DIE to improve CEE, while the threshold value in the YREB is higher than that in the YRB. Furthermore, this paper proposes some suggestions to guide regional low-carbon and sustainable development. Impact path of digital economy (DIE) on carbon emission efficiency (CEE) in the Yellow River Basin (YRB) and Yangtze River Economic Belt (YREB). [Display omitted] • The Super-SBM model is used to evaluate the urban carbon emission efficiency (CEE), and the entropy weight method is used to evaluate the development level of urban digital economy (DIE). • The DIE has a U-shaped nonlinear impact on CEE in the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB). • The intermediary model and threshold model are used to test the intermediary effect and threshold effect of technological innovation between DIE and CEE. • Technological innovation can play a mediating effect between DIE and CEE, whereas the mediating effect in the YRB is stronger than that in the YREB. [ABSTRACT FROM AUTHOR]

This paper interprets the implicit carbon flows in global industrial sectors from a network perspective. Using the SNA-IO integrated model, along with cross-border input-output data from Eora26 (2000–2020) and global energy balance data, the implicit carbon emissions of global industrial sectors and their evolution are analyzed. A carbon emission network structure from an industrial chain perspective is proposed. The results indicate that the carbon emissions responsibility of an industry is not only associated with its own energy consumption. It also involves the carbon emissions transfer resulting from the exchange of products and services between upstream and downstream industries. Block model analysis reveals the carbon emission transfer relationships and their interconnections among global industrial sectors, tending towards an industry clustering pattern where "production side" converges with "demand side" coexisting in supply and demand. There are noticeable inequalities in wealth gains and environmental burdens between these blocks. This paper can provide targeted carbon reduction policy recommendations for various industrial sectors to participate in global responsibility allocation and promote the formation of a low-carbon global industrial sector network. [Display omitted] • The implicit carbon flows in global industrial sectors are explored. • Carbon emission network structure from an industrial chain perspective is proposed. • Supply chains and logistics networks reduce implicit carbon emissions significantly. • Wealth gains and environmental burdens exist noticeable inequalities during blocks. [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]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

The proposal of the dual carbon goal and the blue economy in China has sparked a keen interest in carbon emissions reduction from sewage treatment. Carbon accounting in urban sewage plants serves as the foundation for carbon emission reduction in sewage treatment. This paper re-evaluated carbon accounting in the operational processes for urban sewage treatment plants to develop a novel carbon emission evaluation model for anaerobic-anoxic-oxic treatment plants. The results show that the carbon emissions generated by non-carbon dioxide gases far exceed the carbon emissions from carbon dioxide alone. Moreover, the recycling of sewage leads to carbon emissions reduction that offsets the carbon emissions generated during the operation of the sewage plant. Also, the carbon emissions generated by sewage treatment plants are lower than those generated by untreated sewage. The findings and insights provided in this paper provide valuable references for carbon accounting and the implementation of low-carbon practices in urban sewage treatment plants. [Display omitted] • A novel carbon emission evaluation model for AAO treatment plants was proposed. • Mechanical processes generated higher carbon emissions than energy and chemicals. • The determination of direct and indirect emissions of CO 2 from sewage plants. • Sewage recycling can offset carbon emissions from the operation of sewage plants. [ABSTRACT FROM AUTHOR]

Faced with increasingly severe climate and energy crises, promoting renewable energy development has become an inevitable choice for realizing carbon reduction strategy and energy structure transformation. This paper selects the panel data of 30 provinces in China from 2001 to 2021 and constructs a dynamic spatial Durbin model to study the effect of renewable energy development on carbon emission intensity. The study shows a significant positive spatial correlation between renewable energy development and carbon emission intensity in Chinese provinces. Renewable energy development can significantly reduce carbon emission intensity, and affect the carbon emission intensity of neighboring regions through spatial spillover effects in both the short and long term. In the central-western and southern regions, energy-rich regions, regions with high levels of environmental pollution, high levels of fiscal decentralization, and high levels of green finance, the inhibitory effect of renewable energy development on carbon emission intensity is more significant, suggests that its impact effects are characterized by heterogeneity. Enhancing energy use efficiency, promoting industrial structure optimization, and strengthening green technology innovation capability can significantly improve the inhibition effect of renewable energy development on carbon emission intensity. • Renewable energy development has a spatial effect on reducing carbon emission intensity. • Different types of renewable energy have different effects on reducing carbon intensity. • The impact of renewable energy development on carbon emission intensity has significant heterogeneity. • Energy use efficiency, industrial structure optimization and green technology innovation have moderating effects. [ABSTRACT FROM AUTHOR]

As an innovative financial model in the era of the digital economy, digital finance, with its inclusive characteristics, provides effective financial support for the realization of the carbon peak and carbon neutrality. To realize the "double carbon" goal, it is necessary not only to control the total amount and intensity of carbon emissions but also to consider the coordination and fairness of carbon emission reduction between regions. The existing literature has discussed the carbon reduction effect of digital finance, but few studies have focused on the impact and mechanism of digital finance on regional carbon emission inequality. On the basis of data from 287 prefecture-level cities in China from 2011 to 2021, this paper empirically examines the effect of digital finance on carbon emission inequality via a fixed effects model and convergence model. Digital finance not only reduces the Theil index of carbon emissions but also promotes the convergence of carbon emissions, which mitigates regional carbon emission inequality. The mechanism test shows that digital finance reduces the level of regional carbon emission inequality by promoting capital- and labor-biased technical progress in high-carbon emission regions. Heterogeneity analysis proves that digital finance can better exert its inhibitory effect on carbon emission inequality in regions with low financial agglomeration levels, weak industrial bases and small digital business scales. Further analysis indicates that digital finance can effectively reduce carbon emission inequality between regions, but the effect on carbon emission inequality within regions is not significant. The above findings provide a realistic reference for the formulation of differentiated digital finance policies to support carbon emission reduction. • Digital finance offers new opportunities to mitigate carbon emission inequality. • With the support of digital finance, regional carbon emissions show an apparent conditional convergence trend. • Digital finance alleviates carbon emission inequality by promoting capital-biased and labor-biased technical progress. • The impact of digital finance on carbon emission inequality varies regionally. [ABSTRACT FROM AUTHOR]

Existing literature continues to present divergent perspectives regarding how e-commerce development influences CO 2 emissions. The China's county-level e-commerce pilot program provides new evidence for researches in this subject. This study investigates the effects of China's rural e-commerce development on CO 2 emissions using panel data in 2142 counties from 2010 to 2021, as well as a staggered Difference-in-Differences (DiD) model based on the "Rural E-commerce Demonstration Counties " (REDC) pilot program. Considering the REDC preference towards poor areas, this paper adds the selection variable of pilot program into the model. The main purpose of the REDC is to foster e-commerce growth, but this study finds that the pilot program inadvertently significantly reduces county-level CO 2 emissions while promoting GDP growth in the county. The pilot program of e-commerce mainly achieves carbon reduction through two channels: encouraging the servitization of county industrial structures and the digital transformation of traditional industries. Emissions reductions have a greater impact on economically developed places, provinces with a stronger basis in e-commerce, and counties with better mobility options. This study accurately assesses the impact of e-commerce expansion on reducing emissions, providing new idea for digital carbon emissions reduction and offers policy implications for sustainable economic development in many developing countries (regions). • The development of e-commerce significantly reduces county-level carbon emissions while promoting GDP growth in the county. • E-commerce pilot policy reduces CO 2 emissions by boosting industrial servitization and digitalizing traditional industries. • The effects of emission reduction are more obvious in areas with better economy, e-commerce foundation and transport. [ABSTRACT FROM AUTHOR]

This paper conducted an in-depth study to elucidate the impact of corporate intelligence transformation and regional financial technology on green economic growth, particularly the role of credit resource allocation. We developed a multi-sector general equilibrium model, integrating the heterogeneity of intelligent transformation in production sectors and accounting for the influence of Fintech on financial institutions. Within this model framework, panel data from 2011 to 2021 at the provincial, municipal, and micro-enterprise levels in China were used to validate the theoretical model through a mixed regression approach. The findings indicate that as intelligent transformation firms receive more credit resources, their potential for green economic growth increases, contributing to reduced regional carbon emissions. Additionally, the excess productivity of intelligent transformation firms has a significant positive impact on regional carbon reduction efforts. Moreover, the advancement of Fintech reduces financial institutional costs, further optimizing credit allocation and lowering overall market interest rates, thereby promoting green development within the region. However, advancements in Fintech may also redirect more credit resources toward low-risk general enterprises, resulting in a credit crowding-out effect for intelligent transformation firms. These findings indicate that, while promoting intelligent transformation, policy measures should also balance the resource allocation effects of Fintech across different types of enterprises. • Modeling multi-sector equilibrium to evaluate intelligent transformation's impact on carbon emissions via credit allocation. • Using panel data and mixed regression model to validate the theoretical model's findings. • Higher enterprise intelligence level leads to lower carbon emissions. • Fintech alleviates carbon emissions but doesn't increase credit for intelligent transformation. • Advocating policy measures to optimize credit allocation for promoting regional green growth. [ABSTRACT FROM AUTHOR]

In recent years, with the increasing awareness of sustainable development, corporate ESG (Environmental, Social, and Governance) performance has garnered widespread attention from investors and has had a sustained impact on long-term business operations. The mechanisms by which ESG performance affects corporations primarily include the "governance effect" and the "window-dressing effect." Aimed at high-quality development goals, what kind of impact does ESG performance have on corporate competitiveness? This paper attempts to explore the economic relationship between corporate ESG performance and corporate competitiveness in China's capital market through theoretical analysis and empirical testing. The research results show that ESG performance significantly promotes corporate competitiveness, particularly through the "social" dimension (S) and "governance" dimension (G). ESG performance significantly enhances corporate competitiveness by increasing corporate philanthropic donations and improving total factor productivity, demonstrating the "governance effect" of ESG. However, in the "environmental" dimension (E), ESG performance instead leads to an increase in corporate carbon emissions, which may indicate that corporate efforts in environmental areas are more for superficial appearance, exhibiting the "window-dressing effect" of ESG. This study reveals the crucial role of ESG practices in enhancing corporate competitiveness, providing theoretical support and policy implications for promoting corporate competitiveness and achieving high-quality development goals. • Distinguishes between governance and window-dressing effects of ESG performance on corporate competitiveness. • Empirical analysis shows that social and governance dimensions of ESG significantly enhance corporate competitiveness, while the environmental dimension may exhibit a window-dressing effect. • Firms prioritize environmental window-dressing due to the minimal competitiveness impact of poor environmental performance, the difficulty in measuring environmental actions, and cultural factors favoring social contributions over environmental concerns. [ABSTRACT FROM AUTHOR]

With the emergence of digital transformation, China confronts the dual challenge of fostering sustainable economic and social development while fulfilling its "dual-carbon" commitments. Is the digital-real economy integration a blessing or a curse for inclusive green development? The study was conducted under this backdrop. This paper explores the impacts and mechanisms of digital-real economy integration on carbon emission efficiency, utilizing panel data from 274 Chinese cities over the period from 2011 to 2021. The results indicate that this profound integration significantly enhances urban carbon emission efficiency, although this relationship is partially mediated by industrial structure upgrading. Additionally, natural resources dependence may compromise efficiency gains, exhibiting varying effects across different contexts. The impact of digital-real economy integration on carbon efficiency (Cee) manifests as a non-linear U-shaped relationship that intensifies with increased integration. Heterogeneity analysis reveals that major, eastern, coastal, and resource-scarce cities experience the most profound benefits. These findings highlight the urgency of advancing digital carbon neutrality and offer strategies for emerging economies to transcend traditional constraints, thereby achieving green economic recovery and inclusive development. • The impact of digital-real economy intergration on carbon emission efficiency in China is explored. • The baseline results are robust under multiple econometric analyses. • The non-linear effect and the heterogeneity are supported. • The mediating channel and the moderating mechanism are identified. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS), a market-based environmental regulation, is critical for in combating climate change in China. According to the Porter effect, ETS can promote green innovation, while the specific impact of carbon price on a company's green innovation, and the role of price signals, remain unclear. This study examines the impact of carbon price on green innovation, utilizing a dataset of A-share listed companies spanning from 2010 to 2020. The difference-in-differences estimation results demonstrate that carbon price significantly increases green innovation, promoting both invention patents and utility model patents. Our findings further indicate that moderating variables such as ESG disclosure, larger institutional investor shareholding, local environmental penalties, price stabilization mechanisms, and free quotas allocation can all amplify the constructive influence of carbon pricing on sustainable innovation. Moreover, heterogeneity analysis suggests that state-owned and large-scale companies, particularly those in the power sector and polluting sector, are more sensitive to price signals impacting green innovation. Additionally, we discovered a spatial externality of carbon pricing on green innovation in a radius ranging from 150 km to 300 km. This paper provides specific policy recommendations to stabilize the carbon price signal. • Carbon pricing significantly increases green innovation in China. • ESG, price stabilization mechanisms, and free quotas enhance the positive impacts. • State-owned and large companies, especially in the power sector, are most sensitive. • Spatial spillover effect of carbon pricing observed within a 150–300 km radius. [ABSTRACT FROM AUTHOR]

This study aims to balance the dual objectives of improving environmental quality and achieving carbon peaking and carbon neutrality goals. Utilizing panel data from 274 Chinese cities between 2006 and 2020, this paper employs the difference-in-differences method to examine the impact of the Air Pollution Prevention and Control Action Plan (APPCAP) on urban carbon emissions. Empirical results indicate that the impact of the APPCAP on regional carbon emissions follows an inverted U-shaped curve, exhibiting a dual impact path. Although the implementation of the APPCAP increased the annual carbon emissions of the city by an average of 1.637 million tons, it showed a trend of inhibiting the growth of carbon emissions, although it was not significant. Specifically, the APPCAP is most effective in reducing carbon emissions during the "source prevention" stage, primarily by increasing industrial electricity consumption and reducing coal production and consumption. However, a rebound effect occurs at the policy period's end, with compensatory increases in crude oil and electricity consumption, thereby elevating regional carbon emission levels. The APPCAP's effect on carbon emissions is more pronounced in areas with lower population density and higher environmental regulation intensity. It notably raises carbon emission levels in non-industrial base and non-resource-based cities compared to other cities. Furthermore, the APPCAP positively impacts regional carbon emission intensity and economic growth, significantly driving the secondary industry while minimally affecting the primary industry. • Insufficient synergistic impact between pollution abatement and carbon reduction. • Short-term carbon increase from air policies counteracts emission reduction efforts. • Energy structure realignment is pivotal for attaining clean air and carbon neutrality. [ABSTRACT FROM AUTHOR]

A clean and healthy environment is necessary to achieve other Sustainable Development Goals. Policymakers must find ways to minimize carbon dioxide emissions and global warming before the Sustainable Development era expires. These ills are compounded by chronic inequalities in access to clean energy and the distribution of energy infrastructure, costs, and benefits. This underscores the importance of examining, addressing, and preventing various inequalities in the energy sector. Thus, this paper endeavours to examine probably for the first time the effect of economic complexity on energy justice in a panel of 62 countries over the past decade. The measure of energy justice in this study is a rarely used indicator constructed from a range of 21 sub indicators. We also use three sub-indices of energy justice: distributive justice, procedural justice, and restorative justice. The empirical analyses based on a range of robust estimation approaches consistently provide strong evidence that, on average, economic complexity improves energy justice and its three sub components. Finally, the results from the mediation analysis show that the positive effect of economic complexity on energy justice mediates through income, and human capital. Based on these results, some policy recommendations are made for the achievement of Sustainable Development Goals 7, 8, and 16. • A comprehensive index of energy justice is constructed from 21 sub indicators. • The effect of economic complexity on energy justice on 62 countries is examined. • Two stage Instrumental Variable Approaches are used. • Economic complexity fosters energy justice through human capital and income. • Economic complexity also fosters distributive justice, procedural justice, and restorative justice. [ABSTRACT FROM AUTHOR]

The synergy of digitalization and greening has emerged as a prominent means to achieve the goal of "carbon peaking and carbon neutrality". Given its significant contribution to carbon emissions, the impact of digital transformation on green innovation in manufacturing enterprises remains a longstanding research hotspot. Therefore, based on the data from China A-share listed manufacturing companies spanning from 2007 to 2022, this paper empirically analyzes the influence and mechanism of digital transformation on green innovation. Our findings reveal that digital transformation can significantly promote green innovation in manufacturing enterprises, with a particularly pronounced effect on substantive green innovation. These conclusions withstand rigorous robustness tests. Mechanism analysis shows that digital transformation can facilitate green innovation by improving internal control quality and fostering industry-university-research cooperation. Moreover, our moderation analysis reveals that both equity incentives and compensation incentives strengthen the positive relationship between digital transformation and green innovation in manufacturing enterprises. Heterogeneity analysis proves that digital transformation exerts a more pronounced impact on green innovation of state-owned manufacturing enterprises, non-heavily polluted manufacturing enterprises, and enterprises located in regions with strong intellectual property protection. Furthermore, the transformation of digital underlying technologies is more conducive to fostering green innovation compared to practical application transformation. Subsequent investigation into the economic and social effects of green innovation indicates that it effectively reduces pollution emissions from manufacturing enterprises without compromising their development. Additionally, the emission reduction and income-generating effect resulting from digital transformation primarily manifest through substantive green innovation. This research expands upon the theory regarding the impact of digital transformation on green innovation in micro-manufacturing enterprises, providing empirical support for facilitating low-carbon transformations among manufacturing enterprises under the goal of "carbon peaking and carbon neutrality". [ABSTRACT FROM AUTHOR]

This paper analyses the transition of Ethereum (ETH) from the energy-intensive Proof-of-Work (PoW) to the less energy-intensive Proof-of-Stake (PoS). We analyze returns, volatility, return correlations and volume of ETH, ETC and Bitcoin for all events in the lead-up to the actual change from PoW to PoS also labelled "the merge." The analysis suggests that some investors value the less energy-intensive mining mechanism and invest in ETH. However, since the overall effect is weak, we conclude that despite all the media attention and the stated concerns about the high energy-intensity of Bitcoin and PoW, most investors do not react to the change with an increased investment in Ethereum. • Financial effects of Ethereum's transition from energy-intensive Proof-of-Work to less energy-intensive Proof-of-Stake. • Analysis of returns, volatility, return correlations and volume of ETH, ETC and Bitcoin. • We identify no material financial effects for Ethereum, despite global concerns and media focus on Bitcoin's energy use. [ABSTRACT FROM AUTHOR]

This paper's objective is to investigate the validity of the Environmental Kuznets Curve (EKC) hypothesis utilizing three unique approaches in this era of accelerating climate change and economic volatility. The first step is to introduce and employ a new cointegration test which allows smooth and sharp structural changes through a dummy variable and a Fourier function. Using a time-varying causality approach, the second stage is to assess the EKC hypothesis's validity for each year of a given period, as opposed to the entire period. The third stage is to conduct time-varying analyses not only of the effect of Gross Domestic Product or aggregate income on environmental degradation but also of the effects of the four major economic units' incomes, namely those of the government, non-financial corporations, households, and the rest of the world. This research derives three conclusions using the United Kingdom as a case study from 1830 to 2016. The impacts of aggregate income and the incomes of the three economic units on carbon emissions are consistent with the EKC hypothesis. Second, each of these effects occurs at different times. Thirdly, the EKC hypothesis regarding the association between the nation's trade income and carbon emissions cannot be validated. To provide policymakers with a dynamic, unit-specific, and effective strategy for mitigating environmental degradation, the paper proposes testing the EKC hypothesis for each year over a specific time period, as well as for the effects of both aggregate income and the disaggregate income of four major economic units. • Explains why to estimate income-emissions nexus using disaggregate income data. • Introducing base models for estimating a disaggregate income-emissions nexus. • Illustrating how to make this estimation using time-varying causality analysis. • Aggregate and disaggregate incomes affect emissions differently over time. • Accurate, precise, and specific policy strategies require disaggregate income data. [ABSTRACT FROM AUTHOR]

As the global carbon emission problem is getting more and more serious, the European Union has proposed the Carbon Border Adjustment Mechanism (CBAM) to prevent carbon leakage, which will have an impact on China's foreign trade. Based on this background and the problems of current research that ignores factors such as commodity prices, long-term impacts, intertemporal substitution analysis, and changes in national strategies for foreign exports, this paper propose a Computable General Equilibrium (CGE) model based on an evolutionary game as a dynamic recursive basis to study the impact of the CBAM on the Chinese manufacturing industry. For the industries mentioned in the CBAM, 18 affected sectors are collated, and a CGE model containing multiple blocks such as production, trade, and carbon emissions is built. Meanwhile, we establish an evolutionary game model with EU suppliers, manufacturers, and the government, allowing Chinese suppliers to compete with EU suppliers. Based on the above model, the impact of carbon tariff policies from 2020 to 2050 is studied. The results indicate that under the intra-EU competition condition, carbon tariffs will reduce the price of Chinese exports and slightly decrease China's real GDP, as well as the carbon emission intensity of 18 sectors and fossil energy. However, the impact of carbon tariffs on overall carbon emissions is small and is essentially a protective policy. In addition, the evolutionary game-based CGE model takes into account the dynamic strategies of both sides and is therefore less affected by carbon tariff shocks and recovers more quickly and more realistically. Finally, the article argues that the advantage of carbon tariffs for local suppliers is unsustainable and Chinese suppliers will still dominate, and local suppliers need more subsidies from the EU government. On the other hand, the Chinese government needs to implement a stricter carbon tax regime and export subsidies to improve the competitiveness of Chinese products in terms of green levels and price advantages. The purpose of this paper is to examine the quantitative impacts of CBAM on China's related manufacturing industries and strategies to maximize the benefits to both governments. • A new dynamic recursive approach to CGE is proposed that uses evolutionary games. • The strategy of the importing country is taken into account in the CGE model and is changed according to the multi-stage game strategy to simulate reality better. • The influencing factors of export commodity prices are explored, including the effects of consumer sensitivity, green input coefficients, and carbon emission rights prices. • The impact of CBAM on the income and savings of firms in 18 sectors in China to 2050 was studied. • The impact of CBAM on the carbon intensity of China's fossil energy sources, Coal, Oil, and Gas, the carbon intensity of enterprises in 18 sectors, and the national carbon emissions to 2050 were studied. [ABSTRACT FROM AUTHOR]

With the aggravation of global warming and the increasing demand for energy, the development of renewable energy is imminent. Floating photovoltaic (FPV) is a new form of renewable energy generation. However, the impact of FPV on the aquatic environment is still unclear. By long-term empirical monitoring and data analysis, this paper reveals the shading effect of large-scale FPV power station on aquatic environment for the first time. The results show that: (1) Compared with the non-photovoltaic (NP) zone, FPV only significantly reduces the concentration of dissolved oxygen in the photovoltaic (P) zone. (2) The concentration of chlorophyll a , nitrate nitrogen and total phosphorus increase, while pH and ammonia nitrogen decrease. FPV only causes an effect of the same order of magnitude as the initial concentration, and has no significant adverse effects on the nutritional status of the water body at a coverage ratio less than 50%. (3) FPV has a cooling effect on the water body during the daytime and a thermal insulation effect at night, with the most pronounced impact on peak water temperature (T w). The heating and cooling process of T w in P zone usually lags behind the NP zone by 1–3 h. The diurnal fluctuation and vertical difference of T w as well as the stability of water body are reduced under the shading of FPV, alleviating the influence of climate change on T w and water body stratification. (4) If 10% of the water area larger than 1 km2 in China are used to develop FPV, more than 900 million tons of CO 2 emissions can be reduced, and about 5 billion m3 water can be saved, which is significant in the context of climate change. In general, this paper provides a reference for the future aquatic environmental impact assessment of FPV and the formulation of related policies. • The impact of FPV on aquatic environment has been assessed. • The scale effect of FPV and impact of "fish-photovoltaic integration" are revealed. • Spatial-temporal and object specificity of impact on aquatic environment is reviewed. • The responds of FPV to the challenges of global climate change are further discussed. [ABSTRACT FROM AUTHOR]

Increasing aluminum demand under the clean energy and low-carbon transformation background increases the fuzziness of relationships between economic growth and aluminum use or aluminum related carbon emissions. To figure this out, this paper established an aluminum use and carbon emissions integrated decoupling model within the framework of anthropogenic aluminum cycle. A material flow analysis (MFA) during 2000–2020 for China's aluminum cycle was firstly conducted to quantify both aluminum flow and carbon emissions in each aluminum life-cycle process. Then, this paper evaluated and decomposed the decoupling index of aluminum use-economy and carbon emission-economy via the LMDI decomposition model. Results show that: (1) secondary aluminum has not become effective supplement for primary aluminum in China; (2) the expansive negative decoupling state was the most prevalent state. The decoupling effects of carbon emission were better than that of aluminum use; (3) technology improvement was an important impactor to decoupling process but didn't offset the growth in aluminum consumption or carbon emissions at most of the time. The government and industry organizers should implement active countermeasures to stimulate aluminum companies developing technology to improve aluminum use efficiency and reduce carbon emissions. [Display omitted] • Secondary aluminum supply was limited because the scrapping period of BC and TE department did not come. • Promoting aluminum recycling and remelting are the key to decarbonize the aluminum industry. • The decoupling effects of carbon emission were better than that of aluminum use. • Technology improvement had rebound effect in aluminum consumption before the 13th Five Year Plan. [ABSTRACT FROM AUTHOR]

Economic efficiency gains in tourism are considered a crucial approach to reducing carbon emissions in the tourism sector, especially in tourism transport. However, as a significant source of carbon emissions from tourism activities, the total carbon emissions from tourism transport have not decreased proportionally to the reduction in the intensity, despite China's overall improvement in the tourism economic efficiency. This phenomenon is commonly known as the "rebound effect", which means that although technological progress can achieve emission reductions by efficiency improvement, but it can also indirectly stimulate socio-economic growth and creates new energy demands, results in expected emission reductions being offset by the additional economic growth effect. Based on the multi-source data structure, this paper takes Yangtze-river delta urban agglomeration as an example, quantitatively evaluated the carbon rebound effect of tourism transport through the rebound effect measurement model; simulated the spatiotemporal dynamics evolution pattern of the carbon rebound effect in tourism transport through the spatial kernel density; extracted and identified the dominant factors of carbon rebound effect in tourism transport by the geographic detector. The conclusions summarized as follow: (1) The overall carbon emissions from tourism transport in the agglomeration primarily exhibit a weak rebound effect. (2) The carbon rebound effect is significantly influenced by spatiotemporal factors, which impact its development trend and interaction relations. (3) The level of tourism consumption exerts the greatest influence on the carbon rebound effect of tourism transport, while environmental regulation intensity is commonly employed as a measure to address the rebound effect. This paper aims to enhance the diversity of research on carbon emissions in tourism transport while addressing the existing limitations in spatial-temporal extension. The objective is to restrain the spread of the carbon rebound effect at the regional level, thereby providing a novel decision-making reference for the sustainable development of regional tourism. • Quantitatively analyzed the carbon rebound effect in tourism transportation. • Revealed the influence of spatiotemporal factors on rebound effect. • Identified the dominant factors of carbon rebound effect. [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]

In May 2019, the Climate Change Committee (CCC) recommended that the UK adopt a net-zero target, aiming to reduce its greenhouse gas emissions (GHG) by 100% from the 1990s baseline by 2050. The government accepted the recommendation, and the UK became the first major economy to establish a net-zero emissions law. To progress towards its climate objectives, the government took several initiatives, such as increasing its reliance on renewable energy sources and investing in climate mitigation technologies, which are commonly referred to as process eco-innovation. This study examines the impact of eco-innovation, process eco-innovation, renewable energy consumption, and economic growth on CO 2 emissions in the UK using data from 1988 to 2020. We used the ARDL bound test with an error correction model (ECM) to examine the long-run and short-run cointegration between the variables of concern. We found that eco-innovation, process eco-innovation, and renewable energy consumption have significant roles in mitigating CO 2 emissions, while economic growth contributes to environmental degradation in the UK. We also found that the effect of eco-innovation on CO 2 emissions abatement is stronger than that of process eco-innovation in the short and long-run. Our robustness tests have confirmed the accuracy of those findings. In addition, the results from the Toda-Yamamoto causality revealed a one-way causality from process eco-innovation to CO 2 , renewable energy to CO 2 , and eco-innovation to CO 2 emissions. Further, a bidirectional causality was found between GDP and CO 2 emissions. The evidence presented in this paper provides great insight for shaping the energy policy in the UK and for establishing the climate budget in line with the country's net-zero target. • Process eco-innovation, eco-innovation and renewable energy consumption contribute to CO 2 emissions reduction in the UK. • Eco-innovation has a stronger CO 2 mitigation effect compared to process eco-innovation. • The Environmental Kuznets Curve is not valid for the UK. • There is a one-way causality from process eco-innovation to CO 2 , eco-innovation to CO 2 and renewable energy to CO 2. • There is a bidirectional causality between GDP and CO 2. [ABSTRACT FROM AUTHOR]

Environmental regulations such as the "dual carbon" target directly act on the restriction of the total amount of dirty capital to reduce carbon emissions. The change in factor endowment will have a range of effects on production and income distribution. To examine the effects of environmental regulations restricting dirty capital endowment on income distribution, this paper presents a general equilibrium model with two sectors and three factors. The unregulated clean capital-intensive sector is imperfectly competitive and features firm dynamics, using labor and clean capital as factors of production, while the regulated dirty capital-intensive sector is perfectly competitive using labor and dirty capital. We show that a decrease in the dirty capital endowment will reduce the output of the dirty capital-intensive sector and expand the clean capital-intensive sector in the long run, making society transition to green production. The tighter the restriction on the use of the dirty capital endowment is, the more firms will enter the clean capital-intensive sector, while the business-stealing effect will reduce the output of individual clean firms. We further show that the rents of both dirty and clean capital will rise while the wage of labor will fall due to the regulation. Changes in factor prices do not necessarily lead to inequality in income distributions. When the factor substitution effect in the regulated sector is large enough, clean production regulation will increase the share of labor income and decrease the share of capital income. • We study the effects of environmental regulations on firm dynamics and factor income distribution. • The tighter the restriction on the use of the dirty capital is, the more firms will enter clean sector. • The business-stealing effect will reduce the outputs of individual clean firms. • Changes in factor prices do not necessarily lead to inequality in income distributions. • Changes in the factor income share under regulation is relevant to the factor substitution effect. [ABSTRACT FROM AUTHOR]

Driven by the "dual carbon" goal, it is essential to investigate whether companies can enhance carbon emission efficiency by improving Environmental, Social, and Governance (ESG) performance. This study investigates the relationship between ESG ratings and carbon emission efficiency among Chinese A-share listed companies. The study reveals that a higher ESG rating significantly improves carbon efficiency. Mechanism studies indicate that the effect of ESG mainly comes from easing financing constraints, promoting green innovation, and strengthening supervision. Additionally, the study finds that the impact of ESG on carbon emission efficiency is more pronounced in non-heavy polluting and non-state-owned enterprises. Economic policy uncertainty diminishes the positive effects of ESG initiatives on carbon efficiency, while enhanced governmental concerns to environmental significantly bolsters these impacts. This paper offers empirical insights that can inform adjustment of policies concerning ESG performance and carbon emission. • The impact of ESG on carbon emission efficiency is studied. • The effect of ESG comes from easing financing constraints, promoting green innovation, and strengthening supervision. • Every 1% increase in ESG rating boosts firms' carbon efficiency by 0.0112. • The impact of ESG on carbon efficiency varies with firm type and policy uncertainty. [ABSTRACT FROM AUTHOR]

Severe global climate change has resulted in the focus of social attention shifting to the manufacturing industry's low-carbon transformation. Digital intelligent transformation (DIT) in enterprises is identified as a crucial driver in mitigating carbon emissions. An estimation of DIT's impact on manufacturing industries' carbon emission intensity (CEI) and its underlying mechanisms was conducted using data from Chinese A-share listed companies. Research findings indicate that DIT significantly reduces corporate CEI. Robustness tests, such as the instrumental variable method and variable substitution method, confirm this conclusion. By enhancing labor productivity and accelerating capital renewal, DIT indirectly lowers CEI. Furthermore, non-state-owned enterprises with superior market competitiveness have been observed to be markedly adept at harnessing DIT for CEI. The heterogeneity test found that DIT has a considerably significant effect on reducing CEI in enterprises that are not low-carbon pilots, non-broadband pilots, smart pilots, non-provincial capitals, and eastern cities. This study provides new evidence supporting the promotion of enterprise DIT for achieving green development, offering insights for corporate policy making. Fig. The graphical abstract of the paper. [Display omitted] • Establish comprehensive indicators for the digital intelligence transformation. • Digital intelligent transformation significantly reduced carbon emission intensity. • Labor productivity and capital renewal acted as mediating mechanisms. • Market competitiveness can positively moderate the carbon reduction effect. [ABSTRACT FROM AUTHOR]

Based on the panel data of 496 firms from 2013 to 2020, this paper empirically tests the synergistic emission reduction effect and its action path of carbon emission trading mechanism and green financial tools. The study found that carbon emission trading mechanism, green credit tool, and green bond tool all significantly inhibited corporate carbon emissions. At the same time, the synergy between the carbon emission trading mechanism and the two green financial tools further effectively reduces the carbon emissions of enterprises. Green innovation plays an intermediary role between the synergistic effect on the carbon emission reduction of enterprises. That is, the carbon emission trading mechanism and green financial tools jointly promote green innovation to achieve carbon emission reduction. The impact of synergistic emission reduction mechanism on corporate carbon emissions is heterogeneous due to differences in corporate ownership, industry and region. Accordingly, we should pay attention to the synergistic emission reduction effect of carbon emission trading mechanism and green financial tools based on the mediating role of green innovation in improving the performance of corporate carbon emissions. • Carbon emissions trading, green credit, and green bonds curb corporate emissions notably. • Synergy between emissions trading and green financial tools enhances carbon reduction. • Carbon trading and green credit boost green innovation for emission cuts. • Impact varies by ownership, industry, and region due to heterogeneity. [ABSTRACT FROM AUTHOR]

Food Supply Chains (FSCs) have become increasingly complex with the average distance between producers and consumers rising considerably in the past two decades. Consequently, FSCs are a major source of carbon emissions and reducing transportation costs a major challenge for businesses. To address this, we present a mathematical model to promote the three core dimensions of sustainability (economic, environmental, and social), based on the Mixed-Integer Linear Programming (MILP) method. The model addresses the environmental dimension by intending to decrease the carbon emissions of different transport modes involved in the logistics network. Several supply chain network characteristics are incorporated and evaluated, with a consideration of social sustainability (job generation from operating various facilities). The mathematical model's robustness is demonstrated by testing and deploying it to a variety of problem instances. A real-life case study (Norwegian salmon supply chain) helps to comprehend the model's applicability. To understand the importance of optimizing food supply networks holistically, the paper investigates the impact of multiple supply chain permutations on total cost, demand fluctuations and carbon emissions. To address fluctuations in retail demand, we undertook sensitivity analysis for variations in demand, enabling the proposed model to revamp Norway's salmon supply chain network. Subsequently, the results are thoroughly examined to identify managerial implications. • Food Supply Chains often lack economic, social, and environmental sustainability. • MILP model employed to optimize food supply chain networks' sustainability. • Modelling considers the effect of electrical vehicles on costs and carbon emissions. • Sensitivity analysis demonstrates the model's resilience. • Case study (salmon in Norway) helps comprehend the model's applicability. • Logistical operations can be reconfigured to improve sustainability outcomes. [ABSTRACT FROM AUTHOR]

The carbon emissions trading (CET) policy internalises the cost of carbon emission reductions borne by companies, which will affect the companies' investment and management decisions. From a micro perspective, this paper analyzes the impact on company investment expenditure and its transmission mechanism by implementing the CET policy. Based on panel data of China's A-share listed companies from eight carbon-intensive industries spanning 2010 to 2020, the time-varying difference-in-difference model and its extended model are used to evaluate the impact of the policy in the pilot areas. The results show that: first, based on the cost effect and legality theories, CET policy can reduce the investment expenditure of the companies by 71.95%. Second, CET policy reduces corporate investment expenditures by increasing corporate debt financing costs. When debt financing costs increase by 120.25%, the investment expenditures will reduce by 2.56% indirectly while the intermediary effect of equity financing costs is not significant. Finally, with the implementation of CET policy, the inhibitory effect on corporate investment expenditures has gradually increased. CET policy has a more significant inhibitory effect on investment expenditures of nonstate-owned companies and small-scale companies. The results have passed the robustness test and provide evidence for the policy-maker to balance microeconomic entity development and carbon reduction, and for companies to make optimization investment and financing decisions in response to policy shocks effectively. • The impact of policies is explored from the enterprise level. • A time-varying difference-in-difference model is used to evaluate the impact of China's CET policy. • Results reveal the inhibitory effect of carbon emission trading on corporate investment expenditure. • The mediation effects of debt financing costs and equity financing costs are discussed. • The focus on the discussion of dynamic heterogeneity is provided. [ABSTRACT FROM AUTHOR]

Countries have become increasingly concerned about the impact of their activities and their alignment with sustainable development goals. Consequently, it is necessary to examine their performance efficiency in a unified manner, accounting for economic, environmental, and social variables. A country's performance efficiency is defined as the ratio of observed output to frontier output, given the country's productive resources. In this paper, we use the frontier technique of Data envelopment analysis (DEA) to estimate the frontier output. The objective of this study is to assess the performance efficiency of 111 worldwide countries and to examine whether gender inequality, the share of renewable energy consumption, the government control of corruption and government expenditure on education could explain differences in performance. We employed the non-parametric DEA model using three inputs (capital, labor, and primary energy consumption) and one output (GDP). We also considered an additional output (CO 2 emissions); however, the results were identical to the one output model because CO 2 emissions and primary energy consumption are highly correlated (0.96). We find that there is a negative impact of gender inequality, a positive impact of the share of renewable energy consumption and government control of corruption on performance efficiency. Our results also indicate that reducing CO 2 emissions required transitioning towards renewable energy and using the energy efficiently. However, we did not find a positive relationship between government expenditures on education and country efficiency. • A comprehensive analysis at the country level between efficiency and sustainability. • Positive association between countries' efficiency and renewable energy use. • Positive association between countries' efficiency and control of corruption. • Negative association between countries' efficiency and gender inequality. • Interdisciplinary study that tackles the triple bottom lines of sustainability. [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]

Digitalization, as a crucial engine for promoting sustainable development, has created new prospects for enterprise green transformation. Utilizing panel data from enterprises registered in China's resource-based cities from 2010 to 2021, this study innovatively examines the role of digitalization in promoting green transformation across two key performance dimensions. The findings indicate that enterprise digitalization significantly enhances the green innovation performance, while its impact on environmental performance, although positive, is not statistically significant. Overall, enterprise digitalization greatly facilitates green transformation. Moreover, mechanism analysis reveals that enterprise digitalization promotes green transformation through the alleviation of financial mismatch and the increase of external market attention. In addition, heterogeneity analysis shows that the effectiveness of enterprise digitalization in promoting green transformation is significantly different in different opportunist risk scenarios, proving more effective in areas with low-marketization, high-competition industries, and high environmental regulation intensity. In terms of the policy level, the National Big Data Comprehensive Pilot Zone (NBDCPZ) and the Carbon Emission Trading Policy (CETP) played a positive stimulating role in the process of enterprise digitalization affecting green transformation. This paper broadens the scope of research on green transformation, offers new development philosophy for enterprises in resource-based cities, and provides new directions for the synergistic development of digitalization and greenization. • We explore the nexus between digitalization and green transformation. • We verify this positive effect by applying multiple fixed-effects models. • We identify the mechanism paths from the perspective of external market attention. • We implement heterogeneity analysis from three aspects. • We reinforce the reliability of this positive effect under considering policy interference. [ABSTRACT FROM AUTHOR]

In the context of global value chain, this paper uses world input-output table (2016) and CO 2 emission data to analyze domestic environmental cost of agricultural exports based on backward linkage MRIO model. The results show that average domestic value-added and domestic embodied emissions of China's agricultural export are respectively ranked 7th and 4th in the world during the sample period, which indicates that China's agriculture does not perform well in environmental cost; On the bright side, China's domestic environmental cost displays a downward trend over time. In terms of contributing factors, CO 2 emission coefficient is conducive to the reduction of domestic environmental cost, meanwhile the value-added coefficient, intermediate input structure, and agricultural export structure promote the increase of domestic environmental cost. Further, the cross-country decomposition results found that the emission coefficient and the intermediate input structure are the main reasons that lead China's domestic environmental cost to be higher than those of the main agricultural export countries. The value-added factor and the export structure have narrowed the gap of domestic environmental cost between China and other major agricultural economies. The research findings are still robust when scenario analysis is introduced. This study suggests that optimizing the structure of energy consumption and promoting cleaner production are most important ways to promote the sustainable development of China's agricultural exports. • Domestic environmental cost and its driving factors are analyzed in our paper. • Backward linkage MRIO model is used to measure the environmental cost. • SDA method is used to identify the change in domestic environmental cost. • International comparisons of environmental cost are investigated in this article. • Domestic environmental cost of China's agricultural export continues to decline. [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]

In the global effort to reduce CO 2 emissions, the concurrent enhancement of pollutant degradation and reductions in fossil fuel consumption are pivotal aspects of microalgae-mediated wastewater treatment. Clarifying the degradation mechanisms of bacteria and microalgae during pollutant treatment, as well as regulatory biolipid production, could enhance process sustainability. The synergistic and inhibitory relationships between microalgae and bacteria are introduced in this paper. The different stimulators that can regulate microalgal biolipid accumulation are also reviewed. Wastewater treatment technologies that utilize microalgae and bacteria in laboratories and open ponds are described to outline their application in treating heavy metal-containing wastewater, animal husbandry wastewater, pharmaceutical wastewater, and textile dye wastewater. Finally, the major requirements to scale up the cascade utilization of biomass and energy recovery are summarized to improve the development of biological wastewater treatment. [Display omitted] • The synergistic and antagonistic interactions between bacteria and microalgae are summarized. • Different stimulators that could regulate microalgal biolipid accumulation are also reviewed. • Wastewater treatment technologies that utilize microalgae and bacteria in the laboratory and open ponds are described. • The trends in microalgae-bacterial consortium in multistage energy production are proposed. [ABSTRACT FROM AUTHOR]

The fiscal system plays an important role in the government's environmental governance efforts. There is currently no consensus on how fiscal structure adjustments impact pollution and carbon reduction. This paper uses China's fiscal "province-managing-county" reform (FPMCR) implemented in 2004 as a quasi-natural experiment, utilizing panel data from 1670 counties in China from 2000 to 2020 to investigate the impact of fiscal decentralization on reduction pollution and carbon emissions (RPCE), as well as its underlying mechanisms. The results show that (1) from 2000 to 2020, China's RPCE shows an overall trend of fluctuating increase, with its value turning positive after 2013. China's RPCE exhibits a spatial pattern characterized by "lower in the north, higher in the south; higher in the east, lower in the west". (2) After implementing FPMCR , the RPCE levels in reformed counties decreased by −1.44%, showing that reformed county-level governments prioritize economic development over environmental protection. (3) The mechanism analysis found that after implementing FPMCR , reformed counties experienced a 9.16% increase in nighttime light intensity (NLI), and a 3.99% and 4.34% increase in the number of large-scale industrial enterprises (NLIE) and industrial agglomeration (IA), respectively. This suggests that FPMCR leads to radical urbanization and rapid industrialization in counties, which is detrimental to the improvement of RPCE levels. (4) The spatial heterogeneity analysis found that FPMCR's impact coefficient on RPCE levels in the eastern regions is −1.96%, while in the western regions it is −1.16%. This indicates that reformed counties in the eastern regions are more likely to invest expanded fiscal resources in economic development projects, leading to a decrease in RPCE levels. (5) The temporal heterogeneity analysis found that after the promulgation of the " Three-Year Action Plan to Win the Blue Sky Defense Battle " in 2018, the adverse impact of FPMCR on RPCE is completely reversed, leading to a 1.76% increase in RPCE levels. (6) Further analysis reveals that localizing leaders can slow down the promotion of county-level urbanization and industrialization by the FPMCR , benefiting the improvement of RPCE levels. In other words, "the outsider monk will not recite scriptures as well as a local one". This study has clarified the causal relationship and underlying mechanisms between fiscal decentralization and environmental governance, providing reliable theoretical support for optimizing grassroots fiscal systems and reducing environmental pollution in other transitional economies. It enriches the field of environmental economics related to fiscal decentralization. • Leader localization can shape government behavior following an increase in financial resources. • Enriched environmental economics research related to fiscal decentralization. • Increase more refined reduction of pollution and carbon emissions indicators to improve evaluability. • Clarify the causal relationship and internal mechanism between fiscal decentralization and environmental governance. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

Cities are one of the main sources of regional carbon emissions, and reducing urban carbon emission is the key to reducing emissions. The digital economy has transformed the economic operation mode, and it is a significant approach to support the "dual carbon goals" (carbon peaking and carbon neutrality). This article considers the externalities of the digital economy and carbon emissions. And we use spatial econometric models to analyze the effectiveness of digital economy in empowering carbon emissions reduction. Besides, we explore the static and dynamic spillover effects, and use spatial Durbin panel quantile model to analyze the digital economy's heterogeneity on carbon emissions. Research has shown that the digital economy has a remarkable carbon reduction effect, and the conclusion remains valid after considering robustness tests such as replacing the weight matrices, calculation methods, and proxy variables. The analysis of static and dynamic spillover effects indicates that the degree of the digital economy's impact on carbon emissions are significantly different. Heterogeneity analysis shows that as the digital economy develops from a low level to a high level, its impact on carbon emissions also shifts from positive promotion to negative suppression. This paper proposes a policy reference to help the development of digital economy and promote carbon neutrality in the face of severe environmental challenges. • Digital economy affects carbon emissions of local and surrounding cities after considering spatial correlation. • The dynamic and static spillover effects of digital economy on carbon emissions are significant and different. • Digital economy has heterogeneous impacts on carbon emissions. [ABSTRACT FROM AUTHOR]

Traditional manufacturing industry is in the early stages of transition to low-carbon innovative production, and is in urgent need of a low-carbon innovation system to achieve the goal of carbon neutrality. In order to realize the effective supervision of enterprise carbon emissions, this paper constructs a tripartite evolutionary game model among the corporate, government and public from the perspective of dynamic subsidies and taxes. The main results are as follows. First, the increase in government subsidies to a certain extent will help encourage companies to choose low-carbon innovative production strategies, but more subsidies are not always better. Excessive subsidies will increase the cost of government regulation and reduce the probability of government regulation. Second, the tripartite evolutionary game system does not converge under the static subsidies and taxes mechanism. But the system could quickly converges to the stable condition under dynamic subsidies and taxes. The stable point is the situation of corporate low-carbon innovation, government regulation, and public supervision. Third, the public intervention and supervision can effectively prevent the phenomenon of government misconduct and enterprises over-emission production. And the influence of public reward and punishment is more effective for the government than for enterprises. • A tripartite evolutionary game of low-carbon innovation system among enterprises, government and the public. • Dynamic subsidy and tax mechanisms drive the model to converge to the ideal state. • Increased government subsidies will promote low-carbon innovation, but it isn't the more the better. • The same degree of public supervision is more effective for governments than for enterprises. [ABSTRACT FROM AUTHOR]

Arts and Cultural Organisations (ACOs) have received significant attention over the last few years regarding their environmental performance. ACOs are often non-profit organisations, relying on government funding to implement various programmes to support societal development. Funding dependence can shift ACOs' focus from creating socio-cultural value to being more commercially driven. This paper explores factors influencing organisational changes in ACOs related to environmental performance measurement. Stakeholders in ACOs based in Nottingham, England, were interviewed and participated in a workshop to validate and collect additional data. Our research uncovered five interrelated factors that influence organisational change: the role of funding bodies; local policies and networks; organisational culture and leadership; lack of resources; and building proprietary-tenant relationships. This paper contributes to understanding ACOs responses to measuring environmental performance and the challenges they face as they move from measuring to implementation. Implications are explored for how funding is allocated and understood in terms of moving beyond merely measuring the carbon footprint of activities. ACOs' funding dependence indicates a focus on carbon measurement, omitting a more holistic approach towards the environment and sustainability. • Arts and cultural organisations based in Nottingham participated in the research. • Current ACE funding leads to the implementation of a dominant environmental agenda. • Environmental performance measurement is incomplete and focused on carbon emissions. • ACOs lack the wider support to adopt a whole systems approach to sustainability. • Further research should focus on the importance of place and context in ACOs behaviour. [ABSTRACT FROM AUTHOR]