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Considering how crucial environmental quality is to development, production often takes precedence over the development process when certain macroeconomic policies are being implemented. This phenomenon has been the subject of several studies conducted in various regions and nations. In this context, the recent article explores the nonlinear effects of industrial output, renewable energy, technological innovations, energy efficiency, and urbanization on CO 2 emissions in the top ten industrialized countries. It recommends contradictory policy approaches due to its reported conflicting outcomes, opening up new research directions. To this end, the study relies on advanced econometric tools such as panel QARDL (Quantile Autoregressive Distributed Lag) and the nonparametric quantile Granger causality (NPQGC) test to attain robust results. The findings suggest that industrial output and urbanization significantly deteriorate environmental quality by increasing CO 2 emissions across various time horizons. However, renewable energy, technological innovations, and energy efficiency have a significant influence towards enhancing environmental quality. Notably, industrialization and urbanization become environmentally friendly when energy efficiency is integrated with these variables. Additionally, the NPQGC test supports the main results by confirming the Granger causality between the modelled series. Based on the outcomes, the study suggests that the integration of energy efficiency with industrialization and urbanization can significantly contribute to achieving a sustainable environment. • Renewable energy and tech innovations enhance environmental quality. • Energy efficiency mitigates negative effects of industrialization. • Integrating energy efficiency aids sustainable urban and industrial growth. [ABSTRACT FROM AUTHOR]

This study investigates the impact of recent Artificial Intelligence (AI)-driven technological innovations on carbon prices across different quantiles, assessing the influence of AI stock prices on energy prices based on European carbon allowances while controlling for other macroeconomic factors. Using robust methods such as quantile-on-quantile regression, wavelet analysis, and transfer entropy, the research quantifies the information flow between the AI market and carbon allowances. Using daily data with four alternative AI stock prices from September 14, 2016, to December 29, 2023, the findings reveal a strong effect of AI returns on carbon prices, with significant fluctuations across price quantiles and consistent long-term average growth in market returns. The quantile-on-quantile regression analysis indicates that the short-term changes in carbon prices significantly impact the AI stock returns, with the most pronounced impact occurring below the 20th and above the 80th quantiles of carbon prices, indicating larger responses to extreme events. Additionally, large positive AI price shocks lead to substantial changes in carbon prices, particularly when the carbon prices are near their long-term average. Compared to the short term, the long-term responses are about 15 times smaller. Insights from the Rényi transfer entropy confirm these findings, while the Shannon transfer entropy estimates indicate a discernible and statistically significant information flow from the AI prices to the carbon prices. These findings offer critical insights for investors and policymakers, deepening the understanding of AI's influence on carbon market dynamics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

As a strategic resource, big data has become a key force affecting carbon emission reduction in agriculture. However, its impacts remain controversial, and relevant empirical evidence remains to be explored. Based on quasi-natural experimental analysis, this study explored the impact and mechanism of the construction of the National Big Data Comprehensive Pilot Zone (NBDCPZ) on agricultural carbon emissions (ACE) in China and adopted a difference-in-difference (DID) model using China's provincial panel data from 2003 to 2020. The results showed that the ACE in the NBDCPZ establishment area was significantly reduced by 11.91%, a finding that remained robust following the parallel trend test and the placebo test, among others. Mechanism analysis showed that the ACE was reduced through industrial upgrading and technological innovation. Heterogeneity analysis showed that more pronounced policy gains were achieved in China's central-eastern regions as well as in non-major grain-producing areas compared to western and major grain-producing areas. This research provided supporting evidence for the prospect of big data application in ACE and provided useful guidance regarding the promotion of green and sustainable agricultural development. • The DID method was used to confirm the causal relationship between big data development (BDD) and agricultural carbon emissions (ACE). • The BDD can reduce ACE by upgrading the industrial structure and technological innovation. • The policy had a larger impact in the central-eastern regions as well as in food non-producing regions. [ABSTRACT FROM AUTHOR]

The path toward sustainable development is closely related to the intensification of renewable energy sources and the continual innovation of technologies. To evaluate the role of renewable energy consumption and technological innovations on carbon emissions in Australia, this study uses the Morlet wavelet approach. This study identified temporal and frequency variations by applying wavelet correlation, continuous wavelet transforms, and partial and multiple wavelet coherence methods on data from 2000 to 2021. The wavelet correlation revealed that non-renewable energy, globalization, and economic growth are positively correlated with carbon emissions at all scales. In contrast, carbon emissions are negatively correlated with renewable energy and technological innovation at all scales. Meanwhile, the wavelet coherence analysis shows that non-renewable energy contributes to increased CO 2 emissions from the short to long term, whereas renewable energy usage negatively affects CO 2 emissions across all frequency scales. The study findings indicate that increasing the proportion of renewable energy usage in the total energy mix will curb CO 2 emissions over the long run. Accordingly, the way to achieve sustainable development is shifting to a low-carbon economy centered on renewable energy sources, enhancing energy efficiency, and using carbon storage and capture technologies. • Technological innovation and CO 2 emissions have an anti-cyclic impact. • Renewable energy and CO 2 emissions are out of phase; thus, emissions are been reduced. • The relationship between CO 2 emissions and oil is in the positive co-movement. • Carbon storage and capture technologies is the path to sustainable development. [ABSTRACT FROM AUTHOR]

Achieving sustainable development goals (SDGs) has garnered significant attention from academia and policymakers worldwide. In this study, we examine the impact of ICT, technological innovation (TI), and environmental policy stringency (EPS) on SDI, considering the moderating role of governance quality (GQI) and transport infrastructure (TIS). A comprehensive dataset of 17 advanced nations is utilized from 1996 to 2021. To capture the dynamic and extreme marginal impacts of these policy instruments on SDG attainment, we employ the advanced technique of Feasible Generalized Least Square (FGLS). The results demonstrate that ICT has a positive and significant effect on SDGs, particularly when combined with high levels of governance quality (GOV) and transport infrastructure (TIS). Likewise, TI has a positive impact on SDGs, especially in the presence of strong governance. Furthermore, EPS exhibits a positive association with SDGs. The findings also reveal that while governance hurts SDGs, this effect diminishes when combined with higher levels of ICT, TI, and EPS, and when TIS positively moderates the relationships. The robustness estimations using DOLS and PCSE methods validate the FGLS findings. These results underscore the importance of ICT, TI, and EPS in advancing sustainable development. Moreover, they highlight the significance of good governance and robust transport infrastructure in maximizing the positive effects of these factors. These findings hold implications for policymakers and stakeholders involved in promoting sustainable development. • Investigates the impact of ICT, TI, and EPS on achieving SDGs in 17 advanced nations from 1996 to 2021. • Our research captures the impact of policy instruments on SDG attainment, with moderating effects of GQI and TIS. • Positive link for all the explanatory factors on SDGs. • Governance shows a negative impact on SDGs, this effect diminishes in the presence of higher levels of ICT, TI, EPS. • Robustness estimations using DOLS and PCSE methods validate the FGLS findings. [ABSTRACT FROM AUTHOR]

Although the literature predominantly emphasises the crucial role of technological innovation in alleviating resource dependence, limited attention has been given to the pivotal role of capital in driving such innovation. As a critical factor in technological advancements and productivity enhancement, venture capital has a substantial function in the utilisation of resources and the development of sustainable energy sources. Drawing upon panel data from 30 provinces in China, this study explores how venture capital and resource dependence are interrelated. Our research reveals that venture capital effectively mitigates regional resource dependence by facilitating increased investment in innovation channels. However, the weakening of regional human resources mitigates venture capital's diminishing impacts on resource dependence. These findings provide valuable insights for countries seeking to reduce their dependence on natural resources and achieve long-term economic sustainability. • Venture capital effectively mitigates regional resource dependence. • Technological innovation inputs and outputs are the channels. • Human capital plays a moderating role. [ABSTRACT FROM AUTHOR]

The question of whether environmental regulation fosters technological innovation and green development, as a nuanced extension of the Porter hypothesis, constitutes a focal point in contemporary research. Despite this attention, the literature often omits a multifaceted evaluation framework for green development and fails to consider multiaspectual environmental regulation and technological innovation. This study develops a comprehensive model of green total factor productivity (GTFP), situating the Chinese economy within an economy–environment–health nexus. The extended Crépon–Dugeut–Mairesse model is employed to revisit the "strong", "weak", and "narrow" Porter hypotheses. The analysis reveals that formal environmental regulation exerts a crowding-out effect on research and development (R&D), whereas informal environmental regulation exhibits a facilitating effect, corroborating the narrow version of the Porter hypothesis. Both categories of regulation contribute to substantial innovation. Following the incorporation of R&D factors, heterogeneity in the "weak" Porter hypothesis emerges in the Chinese context, contingent upon specific types of environmental regulation and technological innovation. Environmental regulation positively influences GTFP, affirming the "strong" Porter hypothesis, primarily through the vector of technical progress change. A developmental trajectory to enhance GTFP is thus articulated: judicious environmental regulation leads to R&D, which in turn fosters innovation quality, subsequently affecting the technical progress change index and ultimately GTFP. Correspondingly, policy recommendations are delineated across three dimensions: judicious environmental regulation, targeted innovation support, and regional coordination. [Display omitted] • A GTFP evaluation framework within the economy–environment–health is constructed. • The "strong", "weak" and "narrow" Porter hypotheses are retested by the CDM model. • Multidimensional regulation, innovation, and productivity are investigated. • There are innovation-driven interactions and regional heterogeneity. • Reasonable regulation–R&D–innovation quality–GTC–GTFP is a key development path. [ABSTRACT FROM AUTHOR]

The air pollution-induced health effects of energy consumption remain a grey area in the extant literature. As of yet, there are very limited studies on the subject matter for countries in the Organisation for Economic Co-operation and Development (OECD). To this end, we employ panel data from 1990 to 2019 for 37 OECD countries and panel estimation techniques that control for distributional asymmetry. We also utilize a composite variable of mortality and morbidity to capture the full spectrum of air pollution-induced health burdens. Our findings reveal that renewable energy ameliorates the health burden of air pollution in indoor spaces, evidence for the ameliorating effects of renewable energy in outdoor and occupational spaces was however weak. We also show that income has an ameliorating effect on air pollution-induced health burdens across all spaces and that the effect of non-renewable energy is asymmetric and disparate across all spaces. Furthermore, while technological innovation ameliorates the health burden of air pollution in indoor spaces, it exacerbates the health burden of air pollution in both occupational and outdoor spaces. These findings thus show that the positive health implications of renewable energy policy interventions have more traction in indoor spaces. Capacity needs to be built in the renewable energy sector to reduce the pollution-inducing health burdens emanating from ambient and occupational spaces. [Display omitted] • Heterogeneous effects across indoor, outdoor and occupational spaces uncovered. • Innovation has positive and negative effects for indoor and outdoor spaces respectively. • Strong evidence exists for the positive effect of renewable energy only in indoor spaces. • Effect of non-renewable energy is asymmetric and disparate across all spaces. • Quantile regression uncovers results not detected by mean based estimators. [ABSTRACT FROM AUTHOR]

Most researchers consider CO 2 emissions to be the primary indicator of environmental degradation. Similarly, ecological footprint appears to be a significant proxy for environmental degradation in recent research due to its multifaceted impact on the natural environment. With this in mind, this study investigates fluctuations in CO 2 emissions and ecological footprint as indicators of environmental degradation in Bangladesh from 1980 to 2020, and how they are influenced by net savings, natural resource depletion, technological innovation, and democracy. The non-linear ARDL (NARDL)-based asymmetric analysis finds that positive changes in net savings, natural resource depletion, and democracy positively impact both parameters of environmental degradation in the long run. On the other hand, a positive change in technological innovation reduces these parameters in the long run. Likewise, negative changes in net savings and technological innovation reduce environmental degradation. In contrast, negative changes in natural resource depletion and democracy exacerbate these two parameters and degrade environmental quality in the long run. However, there are some variations in the short-run influence of the predictors on the predicted variable. Overall, the findings of this study suggest that policymakers must strategically exploit natural resources, net savings, technology diffusion, and democratic principles to preserve the natural environment in Bangladesh. [ABSTRACT FROM AUTHOR]

To achieve the carbon peaking and neutrality targets in China, carbon price and technological innovation will play increasingly important roles in recent future. It is widely-known that carbon price and technological innovation can contribute significantly to emission reduction, respectively; but it is still unclear whether the cooperation effects of carbon price and technological innovation would be positive or negative. In this paper, we assume that there are 3 types of emission reduction measures in China's industrial enterprises, which are improvement of energy efficiency, adjustment of energy structure, and substitution of pollution inputs and non-pollution inputs; then we introduce carbon price and technological innovation respectively and simultaneously, and establish 12 scenarios based on the Data Envelopment Analysis models combined with material balance principal (DEA-MBP), and estimate the additional emission reductions and additional production costs of China's industrial enterprises when carbon price and technological innovation exist respectively or simultaneously. The counterfactually estimating results show that there would be significant regional and sectorial heterogeneities in carbon emission reduction characteristics for China's industrial enterprises. If low-carbon technologies in some sectors have the ability to reduce carbon emissions at the expense of high additional production cost, carbon pricing policies would encourage enterprises to adopt new mitigation technologies and increase additional emission reduction by more than 20%, especially technologies focusing on the adjustment of energy structure and the substitution of pollution inputs by non-pollution inputs. However, in some sectors which have already been covered by carbon pricing policies, the additional carbon pricing policy may not have a significant effect on emission reduction, and the emission reduction would decrease by 10%. [Display omitted] • Cooperation effects of carbon price and technological innovation are estimated. • DEA-MBP models and multiple emission reduction measures/scenarios are applied. • Introduction of carbon price would encourage the adopting of new mitigation technologies. • Carbon price and technological innovation would have overlapping effects. • Significant regional and sectorial heterogeneities exist in emission reduction features. [ABSTRACT FROM AUTHOR]

COP27 has provided a new direction in overcoming the issue of climate change. In the world of growing environmental degradation and climate change issues, the South Asian economies are playing a vital role in tackling these issues. Still, the literature focuses on industrialized economies while ignoring the newly emerging economies. This study evaluates the technological factors' influence on carbon emission in the four small South Asian economies (Sri Lanka, Bangladesh, Pakistan, and India) from 1989 to 2021. This study found the long-run equilibrium relationship between the variables using second-generation estimating tools. Employing the non-parametric and robust parametric approach, this study found that economic performance and development are substantial emissions drivers. In contrast, energy technology and tech innovation are the region's key environmental sustainability factors. Further, the study found that trade positively yet insignificantly impacts pollution. This study suggests further investment in energy technology and technological innovation to improve the production of energy-efficient products and services in these emerging economies. • COP27 perspective of South Asian countries is analyzed. • The role of trade and economic growth is examined during 1989 and 2021. • Method of moment quantile regression and robust regression are used. • Economic growth and trade drives climate change and environmental degradation. • Technological innovation and energy technology reduces carbon emission. [ABSTRACT FROM AUTHOR]

International organizations have emphasized the importance of global economies supporting efforts to combat climate change. The Paris Agreement or Agenda 2050 urges nations to ensure that the increase in global temperature is limited to 1.5 °C. Studies have analyzed the factors that contribute to harmful emissions, particularly carbon dioxide emissions, in order to limit temperature rise. However, since there are other equally harmful pollutants, this study evaluates the impact of financial inclusion and green investment on reducing greenhouse gas emissions. The study uses data from West Africa, where environmental pollution has significantly increased. The study employed regression analysis while controlling for economic growth, foreign direct investment (FDI), and energy consumption. The study's key findings reveal that financial inclusion and green investment have a monotonic effect on reducing greenhouse gas emissions. Additionally, the study confirms the environmental Kuznets curve hypothesis and the pollution haven effect for the region. Technological innovation reduces pollution, but green investment and financial inclusion reinforce this effect. Therefore, the study recommends that governments in the sub-region commit to supporting green investment and environmentally friendly technological innovations. It is also crucial to strictly enforce laws regulating the operations of multinational corporations in the region. • Determinants of environmental degradation is estimated. • Financial inclusion reduces pollution. • Green investment reduces pollution. • Environmental Kuznets Curve Hypothesis holds. [ABSTRACT FROM AUTHOR]

As an emerging form of agriculture, urban facility agriculture is an important supplement to traditional agriculture and one of the ways to alleviate the urban food crisis, but it may generate a high carbon footprint. A comprehensive assessment of urban facility agriculture is a necessity for promoting its low-carbon development. In this study, the carbon footprint of urban facility agriculture under four different technological innovation models was simulated by life cycle assessment and a system dynamics model for a carbon footprint accounting without considering economic risk. Case 1, as the basic case, is Household farm facility agriculture. Case 2 is the introduction of vertical hydroponic technology based on Case 1, Case 3 is the introduction of distributed hybrid renewable energy micro-grid technology based on Case 2, and Case 4 is the introduction of automatic composting technology based on Case 3. These four cases demonstrate the gradual optimization of the food–energy–water–waste nexus in urban facility agriculture. This study further uses the system dynamics model for carbon reduction potential considering economic risk to simulate the diffusion (promotion) scale and carbon reduction potential of different technological innovations. Research results show that with the superposition of technologies, the carbon footprint per unit land area is gradually reduced, and the carbon footprint of Case 4 is the lowest at 4.78e+06 kg CO 2 eq. However, the gradual superposition of technologies will further limit the diffusion scale of technological innovation, thereby reducing the carbon reduction potential of technological innovation. In Chongming District, Shanghai, under theoretical circumstances, the carbon reduction potential of Case 4 is the highest at 1.6e+09 kg CO 2 eq, but the actual carbon reduction potential is only 1.8e+07 kg CO 2 eq due to excessive economic risks. By contrast, the actual carbon reduction potential of Case 2 is the highest with 9.6e+08 kg CO 2 eq. To fully achieve the carbon reduction potential of technology innovation, it is necessary to promote the scale diffusion of Urban facility agricultural technology innovation by raising the sales price of agricultural products and the grid connection price of renewable electricity. • Tech innovation optimizes urban agri's food-energy-water-waste nexus: 4 case studies show the process. • We simulate carbon footprint accumulation & reduction potential in facility agri under 4 cases. • Quantitatively assess the economic risks bring about by excessive technological innovation. • Tech innovation's potential for carbon reduction is limited due to significant economic risks. • Policy measures can mitigate economic risks of tech innovation and unlock its carbon reduction potential. [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]

Through the transition of novel ideas, products, technologies, and business models, info-globalization facilitates the flow and expansion of cross-border information and resources. In the meantime, this stimulates the potential of informational globalization and the internet for environmental and other technological advancements, and assists to the realization of cleaner and greener production and consumption. However, prior studies have completely disregarded this facet of globalization. Thus, this novel study evaluates the role of technological innovation (TIN) and information globalization (ING) in predicting ecological footprints (EFP) and carbon emissions (CO2) in the world's top ten greenest economies. Besides, this study also unveils the moderating role of TIN and ING for environmental sustainability. The novel research employs non-parametric causality-in-quantiles approaches on quarterly data from 1994Q1 to 2019Q4 in order to quantify for causality-in-mean and causality-in-variance, since there may be no causation at first moment, but higher-order interdependencies may exist. The findings revealed that TIN and ING possess significant predictive potential for both ecological footprint and carbon emissions, indicating asymmetric predictability over environmental sustainability. Moreover, TIN and ING asserted a significant interaction role when it comes to predicting pollution levels in chosen countries. Overall, it is essential to note that natural resource conservation and pollution mitigation via green and technical innovation become a dilemma since pollution has no boundaries and will always stoke fires beyond them. The provision of financial and R&D assistance, as well as the use of mass and social media to raise awareness not only in their own regions but also in neighboring countries, might contribute to the achievement of SDG 13 and Cope26's ambition of cutting pollution by 2030. • The predictability power of information globalization and technological innovation for environment stewardship is examined. • The quarterly data of top 10 greenest economies are studied from 1994Q1 to 2019Q4. • Technological innovation and information globalization have strong predictive power for environmental footprint. • The information globalization and technological innovation interaction is significantly predicting environmental quality. • Several policy pathways have been proposed to safeguard the environment by 2030. [ABSTRACT FROM AUTHOR]

As flagship climate policy instruments, emission trading schemes (ETSs) are spreading, accelerating and strengthening globally. This study aims to explore whether the Porter hypothesis is present in China's ETS. Using the most recent data from 351 thermal power enterprises, the proposed agent-based model (ABM) creates a virtual decision-making and trading mechanism to identify ETS policy effects on enterprise technological innovation and competitiveness. Numerous findings and managerial insights emerge from the results. First, the weak Porter hypothesis cannot be realized in the early stages of China's ETS. However, when carbon price rises to 50–60 yuan/ton, the ETS spurs significant technological innovation. More importantly, the ETS-induced innovation effect is not associated with penalties or subsidies but is driven by allowance allocation and carbon price. Second, enterprise economic performance exhibits an inverted U-shaped trend. Specifically, innovation offsets may enhance enterprises' initial economic performance, while further tightening the allowance may have the opposite effect on competitiveness. Third, enterprise heterogeneity results in polarization, and the group of enterprises that proactively embrace technological innovation earn a higher profit. This work disentangles the dynamic effects of the weak and strong Porter hypotheses and provides empirical references for optimizing ETS design. • The dynamic effects of ETS on low-carbon technological innovation and competitiveness is analysed. • A certain price of carbon (50–60 yuan) can significantly spur technological innovation. • Enterprise economic performance exhibits an inverted "U-shaped" trend. • Enterprise heterogeneity results in polarization of profits. • This study test the "weak Porter hypothesis" and "strong Porter hypothesis" in the context of the ETS. [ABSTRACT FROM AUTHOR]

In recent years, China has focused its development on technological innovation, trying to achieve a win–win situation between environmental protection and economic growth, and it has formulated a series of policies to promote technological innovation. Taking China's national independent innovation demonstration zone (NIIDZ) policy as an example, this paper empirically investigates the impact of China's innovation policy on haze pollution by using a difference-in-differences (DID) model. The results show that the NIIDZ policy promotes the governance of urban haze pollution and confirms the applicability of the experimentalist governance model in the practice of innovation policy in developing countries. Dynamic analysis shows that the NIIDZ policy has an experience accumulation effect. This policy can continue to promote haze control for at least 6 years, and the policy effect increases year by year. Action mechanism analysis shows that the NIIDZ policy can inhibit urban haze pollution by promoting urban technological innovation and high-tech industrial agglomeration. The estimation results of the spatial DID model show that the NIIDZ policy not only inhibits haze pollution in NIIDZ cities but also has an inhibitory effect on haze pollution in the surrounding non-NIIDZ cities and the NIIDZ cities, which confirms the positive externality characteristics of policy diffusion theory and environmental governance. The conclusions of this paper have important theoretical value for understanding the ecological effect of innovation policy and provide experience for developing countries to implement an experimentalist governance model. • The NIIDZ policy significantly inhibits urban haze pollution. • The haze control effect of the NIIDZ policy shows a characteristic of increasing year by year. • Technological innovation and high-tech industrial agglomeration play a mediation role. • The NIIDZ policy has spatial spillover effect. [ABSTRACT FROM AUTHOR]

Abstract: This study advances contemporary ideas promoting the importance of managing wastes as resources such as closed-loop or circular material economies, and sustainable materials management by reinforcing the notion of a resource-based paradigm rather than a waste-based one. It features the creation of a quantitative tool, the “reuse potential indicator” to specify how “resource-like” versus how “waste-like” specific materials are on a continuum. Even with increasing attention to waste reuse and resource conservation, constant changes in product composition and complexity have left material managers without adequate guidance to make decisions about what is technically feasible to recover from the discard stream even before markets can be considered. The reuse potential indicator is developed to aid management decision-making about waste based not on perception but more objectively on the technical ability of the materials to be reused in commerce. This new indicator is based on the extent of technological innovation and commercial application of actual reuse approaches identified and cataloged. Coal combustion by-products (CCBs) provide the test case for calculating the reuse potential indicator. While CCBs are often perceived as wastes and then isolated in landfills or surface impoundments, there is also a century-long history in the industry of developing technologies to reuse CCBs. The recent statistics show that most CCBs generated in Europe and Japan are reused (90–95%), but only 40–45% of CCBs are used in the United States. According to the reuse potential calculation, however, CCBs in the United States have high technical reusability. Of the four CCBs examined under three different regulatory schemes, reuse potential for boiler slag and flue-gas desulfurization gypsum maintains a value greater than 0.8 on a 0–1 scale, indicating they are at least 80% resource-like. Under current regulation in the United States, both fly ash and bottom ash are 80–90% resource-like. Very strict regulation would remove many reuse options decreasing potential for these two CCBs to 30% resource-like. A more holistic view of waste and broad application of the new indicator would make clear what technologies are available and assist public and private decision makers in setting quantitative material reuse targets from a new knowledge base that reinforces a resource-based paradigm. [Copyright &y& Elsevier]

Eco-efficiency analysis at multi-levels can address the disconnection between its macro-level necessity and micro-level contribution. This cross-level analysis helps policymaking on systematically improving the sustainability of industry. Therefore, in this study, the dual-level eco-efficiency evaluation combing with interactive econometric analysis was applied for contributing a more holistic view of sustainable management in the heavy pollution industry. The empirical study was based on 12 international clothing brands and retailers' textile supply chains and their 202 major upstream manufacturers in China from 2015 to 2019. The dual-level evaluation uncovered a significant improvement in eco-efficiency both at the textile manufacturer and supply chain levels during the five years. The manufacturers' average eco-efficiency increased by 54%. The dyeing and finishing companies' efficiency of emissions to air, energy use, GHG emissions, and water use averagely increased by 165%, 39%, 28%, and 19%, respectively; discharges to water did not change significantly. Meanwhile, the interactive econometric analysis revealed the effects of green management certification, technological innovation, and the number of buyers/suppliers on dual-level eco-efficiency. The influencing mechanism of the same factor on eco-efficiency was demonstrated heterogeneous at manufacturer and supply chain levels. Adopting green management certification was an efficient facilitator to promote textile manufacturers' eco-efficiency, but not sufficient to advance supply chain's ecological performance until 2018. Conversely, inducing technological innovation can promote industry sustainability benefitting from knowledge search and absorption at the supply chain level. Depending on the multi-level lens, this study underlines that the same factor may have heterogeneous impacts at different levels and provides a drawable approach that can support decision-making on improving overall eco-efficiency for stakeholders such as companies, brands and retailers, and the government. [Display omitted] • Multi-level analysis for supply chains and manufacturers targeting textile industry. • A dual-level eco-efficiency evaluation method was developed and applied. • Clothing brands and related 202 manufacturers in China were observed. • The same factors have heterogeneous impacts at different levels. • Influencing mechanisms of GMC and TI were discussed. [ABSTRACT FROM AUTHOR]

The ecological compensation (EC) mechanism is an innovative institutional arrangement which can effectively realize the coordinated development of social-economic growth and ecological protection. The current research on the evaluation of the implementation effect of EC mechanism mainly focuses on its environmental performance, how the EC mechanism guides the economically underdeveloped areas in the upper reaches of the basin to embark on the road of high-quality economic development, especially the mechanism of how EC triggers the optimization and upgrading of industrial structure, it is a topic worthy of in-depth discussion. This study takes China's first cross-provincial horizontal EC mechanism pilot (Xin'an River Basin EC) as the research object and regards it as a quasi-natural experiment. This paper selects the annual panel data of the 11 cities involved from 2009 to 2019 and builds a DID model to study the mechanism of EC affecting industrial structure adjustment systematically. The results show that the EC mechanism mainly promotes the adjustment of the industrial structure in the pilot area through two paths, this is achieved by triggering the transfer of backward or highly polluting industries and promoting the upgrading of the industrial structure. At the same time, technological innovation plays a part intermediary role in the impact of EC to promote the upgrading of industrial structure. Further analysis found that the larger the funds of compensation input, the higher the assessment intensity, the better the effects are. Finally, this study puts forward relevant policy recommendations to further release the potential of the horizontal EC for the reference of decision-makers. • We evaluated the mechanism of ecological compensation (EC) on industrial structure. • EC affects the adjustment of industrial structure through industrial transfer and industrial upgrading. • Technology innovation plays a vital role in the process of EC mechanism guiding industrial upgrading. • The compensation amount and standard play a key role in the effectiveness of EC. [ABSTRACT FROM AUTHOR]

China's economy is changing from high-speed growth to high-quality development. Now its development is green and sustainable, characterized by low energy consumption and high innovation. Under the circumstance, it is vital to research on the threshold effects of energy consumption, technological innovation, and supply chain management on enterprise performance in China's manufacturing industry. This study selects data from 115 manufacturing companies listed in the Stock Exchange of Shanghai and Shenzhen from 2010 to 2019 as samples. We adopt the panel threshold model to analyze the impact of energy consumption, technological innovation, and supply chain management on enterprise performance. Our results show that energy consumption, technology innovation and supply chain management all have non-linear relationship on enterprise performance. There is an inverse S-shaped relationship between energy consumption and enterprise performance, and a significant threshold effect of technology innovation. Moreover, technological innovation has a two-sided effect on enterprise performance. In addition, supply chain management has a significant positive impact on enterprise performance. According to the project of China's carbon peaking by 2030, we put forward some methods for energy conservation, emission reduction, cost saving, and efficiency improvement for China's manufacturing industry. We also provide some suggestions for enhancing enterprises' technological innovation and supply chain management. • We established a panel threshold model for data from 115 manufacturers in China. • Energy consumption and enterprise performance have an inverse S-shaped relation. • Technological innovation has a two-sided effect on enterprise performance. • Supply chain management has a significant positive effect on enterprise performance. [ABSTRACT FROM AUTHOR]

Carbon emissions are the main factor in environmental degradation, associated with climate change and global warming, which puts environmental sustainability at risk. Carbon dioxide is the main element to mitigate to achieve climate neutrality on the planet, which is present in fossil fuels highly demanded power generation. This environmental concern, which entails all economic agents' responsibility, has not gone unnoticed, so in 2015 the Paris Climate Conference (COP: 21) was held, whose main objective is to reduce carbon emissions on the planet. Post Paris agreement generates pressure on the signatory countries since the objectives set are a real challenge to achieve environmental sustainability. Thereby, this research aims to examine the long-term determinants of carbon emissions in 19 countries of the European Union that were part of the COP: 21. The Method of Moments' Quantile Regression approach is used, which considers the effects of location and scale in the conditional distribution of carbon emissions. The results show that clean energy, technology and environmental taxes contribute to mitigating carbon emissions; however, economic activity and industrialization causes an increase in environmental degradation. From the results obtained, the findings suggest some policy measures aimed at offsetting carbon emissions. • Renewable energy reduces carbon emissions in all quantiles. • Technological innovation reduces carbon emissions to medium-high quantiles. • Carbon tax contributes to the reduction of carbon emissions in the lowest quantiles. • In MMQR approach present novel results compared to FMOLS, DOLS, and FE-OLS. • Econometric methods are used to control cross-sectional dependency on the results. [ABSTRACT FROM AUTHOR]

Since the Paris Agreement, countries around the globe have been striving to achieve their carbon neutrality targets. However, because China has one of the largest economies in the world, to achieve its targeted carbon neutrality, the roles of foreign direct investment (FDI), technological innovation (TI), and trade are crucial. Therefore, this study aims to introduce the level of trade, renewable energy consumption (REC), and FDI from the years 1995–2017 as new determinants in promoting a sustainable environment in China. The study employs advanced panel methods based on slope homogeneity and a cross-sectional dependence test. The results confirm a cointegration relationship for all models in this study, suggesting that gross domestic product and FDI positively affect carbon emissions. By contrast, foreign trade, REC, and TI are inversely associated with carbon emissions. Moreover, according to Chinese provincial data, the joint term for FDI with REC and TI is negatively associated with carbon emissions. The policy implications of this study suggest that to achieve sustainable FDI, TI should be encouraged to mitigate the pollution caused by FDI. There is a dire need to implement green practices and eco-friendly policies at a national scale. • Foreign direct investment and trade effect on CO2 emission is examined. • It employs robust panel methods suitable for the data. • GDP and foreign direct investment positively affect carbon emissions. • Foreign trade, renewable energy and technology are inversely associated with CO2. • Positive impact of FDI on CO2 is less in provinces with more innovation. [ABSTRACT FROM AUTHOR]

The greatest contribution to global CO 2 emissions comes from the BRICS countries (Brazil, Russia, India, China, and South Africa). The building sector in these countries is one of the sectors that increases CO 2 emissions significantly. Increasing CO 2 emissions in the building sector adversely affects sustainable development. Therefore, measures to mitigate environmental damage become substantially important. Improvements in technological innovation can be among the measures considered to mitigate CO 2 emissions. In this study, the effects of technological innovation on the carbon emissions caused by the building sector are examined by panel data methods for the BRICS countries in the period 1992–2018. It has been observed that there is a long-term relationship between the series. As the results of Dynamic Common Correlated Effects indicated, increased technological innovation reduces carbon emissions. This result is meaningful to encourage investments related to technological innovation. • The building industry is one of the most contributing sectors to global carbon emissions. • The greatest contribution to global carbon emissions comes from BRICS countries. • Urban population growth increases carbon emissions in Brazil, China, India and Russia. • Technological innovation has a negative effect on building sector carbon emission. [ABSTRACT FROM AUTHOR]

To verify how does the development of technological innovation effectively mitigate carbon dioxide (CO 2) emissions in Organization for Economic Co-operation and Development (OECD) countries, this study first investigates the direct impacts and moderating effects of technological innovation, measured by the development of patents on CO 2 emissions by employing a balanced panel dataset for 35 OECD countries covering 1996–2015. Also, to examine the potential heterogeneity and asymmetry, the panel quantile regression approach is utilized. The empirical results indicate that technological innovation directly reduces CO 2 emissions; however, this impact is significantly heterogeneous and asymmetric across quantiles. Furthermore, through analyzing the influencing mechanism, the technological innovation affects the impacts of economic growth and renewable energy through its moderating effects. Moreover, the moderating effects of technological innovation is also heterogenous. Accordingly, the main contribution of this study is that the potential heterogeneity and asymmetry of both the direct impact and moderating effect of technological innovation on CO 2 emissions in OECD countries are systematically analyzed by employing the panel quantile regression approach. • Effects of technological innovation (TI) on CO 2 emission are analyzed for OECD. • Potential heterogeneity and asymmetry within the data are considered. • TI directly reduces CO 2 in a heterogeneous and asymmetrical way. • TI indirectly affects emissions by offsetting positive impact of economic growth. • TI indirectly affects emissions by enhancing negative impact of renewables. [ABSTRACT FROM AUTHOR]

The objective of this study was to explore the roles of technological innovation, environmental regulations, and urbanization in ecological efficiency within the context of the 2015 Paris agreement. Initially, the study employed the super-efficiency DEA model to estimate the ecological efficiencies of 30 regions in China. Following this, the system GMM method was used to explore the impacts of technological innovation, environmental regulations, and urbanization on ecological efficiency. We used annual data from 2008 to 2018. The results indicate that, in terms of ecological efficiency, the eastern region was the highest ranked, followed by central and western regions, respectively. The urbanization index has a negative impact on ecological efficiency at a national level. However, in the context of regions, it is positively significant in the eastern region, while the results in the central and western regions are insignificant. The influence of technological innovation on ecological efficiency is found to be significantly positive at both national and regional levels. It is generally perceived that environmental regulations are pivotal for sustainability. Our results verify this argument and indicate that environmental regulations have a positive impact on ecological efficiency in the central and eastern regions. However, their impact is found to be negative in the western region. Policy suggestions are discussed, in order to further strengthen environmental laws and sustainability. Image 1 • Super Efficiency DEA and System GMM methods are used. • Environmental regulations are essential for sustainability. • Technological innovation can play a pivotal role toward ecological efficiency. • Eastern region is found high ecological efficient compared with other regions. [ABSTRACT FROM AUTHOR]

This study analyses the dynamics of carbon emissions for N-11 countries from 1990 to 2017. We introduce some innovative factors such as financial development, human capital, renewable energy consumption, and gross domestic product as determinants of carbon dioxide (CO 2) emissions. The empirical estimations are based on Pesaran (2007) unit root test, common correlated effect mean group, and augmented mean group. The findings reveal a positive relationship between carbon emissions and financial development as well as a gross domestic product. In contrast, technological innovation and renewable energy consumption are adversely related to carbon emissions. These findings have important implications, and we recommend the promotion of technological innovation and the use of renewable energy consumption. This will help in achieving the goals set by COP21. • This paper provides broader policy to achieve the goals laid down in COP21. • We investigate the role of determinants of CO2 emissions in N-11 countries. • Financial development and GDP seem to make climatic situations adverse. • Renewable energy consumption and innovation help reduce CO2 emissions. • Human capital development may also help to reduce CO2 emissions. [ABSTRACT FROM AUTHOR]

Following the adaptation of the Paris Agreement at COP21, it was noted that the traditional measures of carbon emissions have several limitations; and a reliable and relevant carbon emissions measurement is important to formulate a response to the challenge of climate change. This study, therefore, explores the relationship between international trade and consumption-based carbon emissions, which is a trade adjusted indicator; and measures the outflow and the inflow of emissions through exports and imports separately. We also include technological innovation in the model to understand its impact on consumption-based carbon emissions. The results show that exports and consumption-based carbon emissions are negatively associated, and technological innovation helps reducing the adverse effect of CO 2 growth. In contrast, Imports and gross domestic product are positively linked with consumption-based carbon emissions. The findings also suggest the countries which embraced the Paris Climate Agreement must focus on consumption-based carbon emissions rather than the production-based carbon emissions. • We employ ARDL bound test and error correction model to analyze consumption based carbon emission in USA. • Consumption-based carbon emission is a reliable and more appropriate measure of climate change. • Technological innovation is an important factor in formulating policy response to combat climate change. • Exports play a positive role and help reducing carbon emission. • United States of America (USA) is the net importer of carbon emission. [ABSTRACT FROM AUTHOR]

Against a backdrop of accelerating digital innovation in nature conservation and environmental management, a real-world experiment was conducted with the research aims of assessing: 1) the effects of introducing a digital data-entry platform on volunteer data submission; and 2) the extent to which coordinators influence digital platform use by their volunteers. We focussed on a large-scale volunteer-based initiative aimed at eradicating the non-native American mink (Neovison vison) from northern Scotland. This geographically dispersed conservation initiative adopted a digital platform that allowed volunteers to submit records to a central database. We found that the platform had a direct and positive effect on volunteer data submission behaviour, increasing both the number and frequency of submissions. However, our analysis revealed striking differences in coordinator engagement with the platform, which in turn influenced the engagement of volunteers with this centrally introduced digital innovation. As a consequence, the intended organisation-wide rolling out of a digital platform translated into a diversely-implemented innovation, limiting the efficacy of the tool and revealing key challenges for digital innovation in geographically-dispersed conservation initiatives. • Digital innovation is often enthusiastically employed but effects poorly studied. • We build a data-entry platform to assist a geographically-dispersed organisation. • The centralised platform increased data submission by volunteers. • The digital orientation of project coordinators influenced volunteer platform use. • Digital tools need be introduced with caution and attention for mediating effects. [ABSTRACT FROM AUTHOR]