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This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Traditional buildings will lead to a series of problems such as high energy consumption, high pollution, and serious waste of resources and environmental damage. It is of great significance to construct a green building evaluation system based on the physical building framework to achieve energy saving and consumption reduction and to fit the sustainable development. In this study, a building greenness evaluation system combining BIM data model and prior knowledge of experts is constructed and the applicability of the method has been verified. IFC information is expressed and transmitted in terms of components, materials, equipment, environmental quality impact, etc., and BIM based building performance design data information conversion and greenness evaluation process is constructed; Based on the comparison and summary of the existing green building evaluation systems at home and abroad, the evaluation model of building greenness is determined; Based on the ideas and steps of establishing the index system proposed in the research, the index system of building greenness evaluation is established from the aspects of environmental quality (Q) and building load (L) on the basis of questionnaire, prior knowledge of experts and other methods; Combined with the mathematical model of greenness evaluation, the paper analyzes the indexes of different levels, determines the structural calculation methods of different indexes, and carries on the quantitative classification of the overall greenness evaluation. Finally, taking a citizen's house as an engineering case, the paper makes an empirical analysis on the greenness evaluation of green buildings. The results show that the green degree of the building is excellent(class A), which is consistent with the project positioning, and provides the basis for the efficient and accurate evaluation of green building. [ABSTRACT FROM AUTHOR]

Globally, the interaction among innovation, tourism, and climate change has become a point of focus recently. This study examines the impact of innovation and tourism development on the sustainable development of the G7 economies. Panel data from 2000 to 2019 was analyzed for cross-sectional dependency, and a series of panel unit root tests were used to confirm the variables' unit root properties. Pedroni and Kao's tests confirm the cointegration relationship among the variables. The fully modified OLS and dynamic OLS results show that higher economic prosperity and lower environmental pollution are associated with innovation as measured in scientific publications and patents, highlighting the importance of innovation. The results highlight the positive significant impact of tourism arrivals on pollution reduction and economic expansion, which mark the steps for sustainable development. The study finds further evidence that asylum refugees did not positively contribute to economic prosperity, nor were they active in the environmental correction plans of the countries. The level of education provides strong evidence supporting sustainable development by encouraging economic growth and discouraging environmental degradation. Overall, the results recommend raising the level of innovation, tourism development, and higher technical education for the sustainable development of the G7 economies. These findings offer important contributions to firms, policymakers, and UN sustainable development agendas. [Display omitted] • The paper assesses the impact of innovation and tourism on sustainability. • The results show that innovation helps improve environmental quality. • The results reveal that innovation helps foster economic prosperity. • The paper finds that tourism helps in pollution reduction and economic expansion. • The results show that the level of education is important for sustainability. [ABSTRACT FROM AUTHOR]

Globally, the interaction among innovation, tourism, and climate change has become a point of focus recently. This study examines the impact of innovation and tourism development on the sustainable development of the G7 economies. Panel data from 2000 to 2019 was analyzed for cross-sectional dependency, and a series of panel unit root tests were used to confirm the variables' unit root properties. Pedroni and Kao's tests confirm the cointegration relationship among the variables. The fully modified OLS and dynamic OLS results show that higher economic prosperity and lower environmental pollution are associated with innovation as measured in scientific publications and patents, highlighting the importance of innovation. The results highlight the positive significant impact of tourism arrivals on pollution reduction and economic expansion, which mark the steps for sustainable development. The study finds further evidence that asylum refugees did not positively contribute to economic prosperity, nor were they active in the environmental correction plans of the countries. The level of education provides strong evidence supporting sustainable development by encouraging economic growth and discouraging environmental degradation. Overall, the results recommend raising the level of innovation, tourism development, and higher technical education for the sustainable development of the G7 economies. These findings offer important contributions to firms, policymakers, and UN sustainable development agendas. [Display omitted] • The paper assesses the impact of innovation and tourism on sustainability. • The results show that innovation helps improve environmental quality. • The results reveal that innovation helps foster economic prosperity. • The paper finds that tourism helps in pollution reduction and economic expansion. • The results show that the level of education is important for sustainability. [ABSTRACT FROM AUTHOR]

Excessive energy-related carbon emission intensity will lead to deterioration of environmental quality and hinder green economic growth. This paper proposes a novel self-adaptive fractional order grey generalized Verhulst model (SAFGGVM) to predict energy-related carbon emission intensity in China, America, India, Russia, and Japan with nonlinear and complex characteristics effectively. Firstly, self-adaptive fractional order and dynamic background value coefficient are introduced to capture the nonlinear evolutionary trends. Subsequently, the optimal nonlinear parameters are determined using Grey Wolf Optimization algorithm through comprehensive comparison. Furthermore, the flexibility of SAFGGVM is verified by presenting its relevance to existing models. Finally, the validity, applicability, and robustness of SAFGGVM are confirmed by comparing with two machine learning models and four grey prediction models. The empirical results exhibit that the overall precision of SAFGGVM model significantly prevails over the others in five cases, with MAPE values less than 6% in both the simulation and prediction intervals. The out-of-sample forecast results indicate that the energy-related carbon emission intensity of five countries will fall into 5.7024, 1.6030, 7.3668, 8.1633, 2.0399 tons/10,000 USD by 2025, and the decreasing rate of developing countries tends to catch up with, or even exceed, developed countries. Projection results can serve as a reference point for countries to achieve green and sustainable development. • A novel self-adaptive grey generalized Verhulst model is proposed. • Energy-related carbon emission intensity (ECEI) of five countries is predicted. • Optimal nonlinear parameters are determined by Grey Wolf Optimization algorithm. • The novel model is superior to other competing models in accuracy and roubutness. • Decline rate of ECEI in developing countries will catch up with developed countries. [ABSTRACT FROM AUTHOR]

Regional collaborative governance has become one of the most significant trends in environmental protection due to its importance in suppressing pollution transfer. This paper employs panel data from 285 cities in China during 2003–2019 and a multi-period difference-in-differences (DID) method to evaluate the influence of regional collaborative governance on air pollution. Results show that regional collaborative governance significantly reduces air pollution. Heterogeneity assessment suggests that the inhibiting impact of regional collaborative governance on air pollution is long-term and increases temporally, whereas the spillover effect of regional collaborative governance is only significant in a specific range and decays spatially. In addition, the mechanism analysis reveals that regional collaborative governance reduces air pollution by increasing environmental regulation intensity, improving environmental governance efficiency, and promoting environmental protection technology. This study provides useful policy insights for policymakers seeking green and sustainable development to curb air pollution and improve environmental quality. • The impact of regional collaborative governance on air pollution is examined. • We employ a multi-period difference-in-differences approach. • Regional collaboration significantly reduces air pollution emissions. • Local effects increase temporally whereas spillover effects decay spatially. • The strongest inhibition comes from promoting environmental protection technology. [ABSTRACT FROM AUTHOR]

In today's world, environmental concerns are at the forefront of countries' considerations, along with economic priorities. In this context, countries face the challenge of developing and directing their investments in clean energy technologies to achieve the Sustainable Development Goals, particularly affordable and clean energy. Does the development and diffusion of clean energy technologies contribute to improving environmental quality? This study addresses this question by examining the effects of clean energy technologies on sustainable environmental quality as expressed by the load capacity factor (LCF). In this context, the study explores the United States (US), as the largest economy and one of the leading countries investing in clean energy, considering the role of human capital, urbanization, and economic growth. To this end, this paper applies the novel augmented autoregressive distributed lag (ARDL) model to annual data from 1974 to 2018. The long-term empirical results show that (i) Clean energy technologies have no effect on the LCF; (iii) human capital supports environmental quality; (iv) urbanization has an adverse effect on environmental quality; (v) increasing economic growth worsens environmental quality. Overall, the empirical results suggest that while clean energy technologies should support sustainable environmental quality, this is unfortunately not the case in the US. Therefore, the US policymakers need to take improvement actions to ensure that clean energy technologies contribute to sustainable environmental quality and that the community reaps the environmental benefits of human capital. [Display omitted] • Applies the Augmented ARDL approach with smooth structural shifts. • Tests the impact of clean energy technologies on environmental quality. • Clean energy technologies do not affect the environmental quality. • Income and urbanization reduce the load capacity factor. • Human capital improves environmental quality. [ABSTRACT FROM AUTHOR]

Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the "carbon peaking and carbon neutrality" goal. [Display omitted] • Evaluation system of Balanced Green Development Index is constructed. • The system was applied to balance green economic growth with environmental equity. • Emission trading scheme has significantly improved the level of balanced green development. • The promotion effect is more obvious in western China. [ABSTRACT FROM AUTHOR]

In the social context of enhancing environmental quality and mitigating climate change, the improvement of carbon emission efficiency has emerged as a hot topic recently due to its promise as an approach to reduce emissions and improve environmental quality. A large volume of studies has identified technological progress as a critical factor affecting energy efficiency and pollution emission levels. From the perspective of national differences, the contributions of our study lied in constructing a system to measure technological progress based on the outputs and transformations of a country's technical progress level. Secondly, this paper examined the direct effect of technological progress on carbon emission efficiency, and the interaction effect between technological progress and energy intensity on carbon emission efficiency. Thirdly, we taking into account differences in the effect that technological progress can have on carbon emission efficiency in different national contexts. For this purpose, we evaluated the carbon emission efficiency of 59 countries in the period 1998–2016 using a super-SBM model, subsequently employing a national panel quantile regression method to explore the multiple effects of technological progress on the carbon emission efficiency of countries with different levels of efficiency. Our main findings indicate that the national carbon emission efficiency steadily increased across the study period, albeit with slight fluctuations, and that generally countries' carbon emission efficiency still exists great potential of enhancement. Technological progress will drive carbon emission efficiency to improve significantly, while this effect varies between countries with different levels of efficiency. Further, the interaction effects of technological progress and energy intensity are shown to exert complex effects on carbon emission efficiency, providing evidence that scientific and technological achievements need to be converted into productivity in time to offset the negative environmental effects of pollution and emissions. Governmental departments should, as a result, strengthen environmental supervision and urge enterprises to eliminate backward production capacity, introduce new technologies, and improve energy efficiency. Countries may realize the development of low-carbon sustainable societies by transforming their economic growth mode and adopting energy-saving production techniques. [ABSTRACT FROM AUTHOR]

Among the main components of a smart city, the energy system plays a vital and core role in the transition towards a sustainable urban life. Furthermore, the utilization of renewable energy sources has been demonstrated as a significant contribution to reducing pollutant emissions and enhancing the quality of the living environment. Therefore, designing the energy systems based on clean and renewable criteria is considered a sustainable solution for smart cities. Indeed, the deep and rapid penetration of renewable energy-based technologies have been believed to very well fit into a smart city under various scales, this could supply a secure basis for a modern society with a low-carbon economy. In this review paper, the main components and roles of renewable energy resources (such as solar, wind, geothermal, hydropower, ocean, and biofuels) for the smart city were fully introduced. Besides, integrating the renewable sources form into the energy systems of smart cities was thoroughly analyzed on the basis of technical and economic criteria. Finally, existing challenges and future scenarios were also discussed in detail to clarify the progress and perspective of smart renewable energy systems for the smart city. In general, the integration of renewables into energy systems of the smart city is a sagacious perspective and solution aiming to achieve cleaner process and more sustainable development. However, the optimization issues of the energy system for integrating of renewable components, ensuring good stability, maximizing the operating range, and minimizing the investment costs should be critically evaluated in the future works. • Designing tools and key criteria for smart renewable energy systems. • Efficiency and prospect of integrating renewables into energy system for smart city. • Existing problems and challenges for renewable-based energy system in smart city. • Future scenarios for the sustainable development of energy system in smart city. [ABSTRACT FROM AUTHOR]