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Climate change presents a substantial impediment for the global community and prompts policymakers worldwide to prioritize environmental goals when defining national development strategies. Prioritizing these goals is particularly challenging for governments of developing economies still relying on fossil fuels, foreign capital, and industry contribution to GDP. This study examines the relationships between carbon dioxide emissions, industry value added, financial development, and electricity generation in 15 Central and Eastern European countries from 1995 to 2021. To achieve this objective, we examined stationarity and cointegration and employed a vector error correction model to investigate causalities between the variables, along with a variance decomposition analysis. Our findings suggest that the short-run unidirectional causalities exist from industry value-added to carbon dioxide emissions and from carbon dioxide emissions to financial development and electricity generation. Long-term causality exists between carbon dioxide emissions and industry value added. The findings shed light on the challenges and opportunities these countries face in transitioning to climate neutrality and meeting the decarbonization targets. Within this context, the findings underscore the significance of crafting customized strategies for these economies to navigate the complex landscape of climate change while promoting sustainable industrial, electricity and financial sector development. [ABSTRACT FROM AUTHOR]

Over the last twenty years, there has been swift growth in industrialization and technological advancements, driving economic progress. Nevertheless, it is inevitable that these sectors will bring about environmental shifts. Thus far, endeavors have been undertaken to assess the influence of industrialization and technological advancements on environmental deterioration. Additionally, the extensive discussion surrounding the impact of financial development, trade openness, and technological innovation on the environment has not yielded conclusive empirical findings. Studies often operate under the assumption of symmetric relationships, potentially leading to biased results. Adding to the discussion on the drivers of carbon neutrality, the time-dependent effects of critical aspects such as financial development and technological innovation should inform meaningful policies for environmental management. This article explores the time-varying causal association between trade openness, industrialization, financial development, technological innovation, and CO2 emissions in Thailand using novel time-varying Granger causality tests. The time-varying causality outcomes demonstrate that the associations change significantly over time, in contrast to the results of Toda-Yamamoto causality. Overall, there exists a bidirectional relationship between industrialization, financial development, trade openness, technological innovation, and CO2 emissions over different time sequences. These outcomes have implications for both policy and research. [ABSTRACT FROM AUTHOR]

China's industrial sector generally relies on electricity as its main source of energy, and industrial production can be affected if there are problems with the electricity supply. In order to deal with the uncertain electricity supply and achieve the "dual carbon" target, the industrial sector needs to take effective measures to enhance carbon total factor productivity (CTFP). We use the biennial Luenberger productivity index (BLPI) to try to provide strategies for low-carbon industrial development in China. The results indicate that the overall CTFP of China's industrial sector showed an increasing trend from 2006 to 2019. Technology change was the main contributor to the change in CTFP, but fluctuations in efficiency change remained a challenge. Differences were observed between the light industry sector (LIS) and the heavy industry sector (HIS) in terms of changes in CTFP, with LIS showing more stable changes and HIS experiencing larger fluctuations. Most sub-sectors showed increased CTFP during the sample period. R&D investment and R&D personnel have a positive impact on CTFP, while energy structure is found to hinder CTFP. According to the research results of this study, we offer the corresponding policy implications. This study is the first to explore the balance between low-carbon goals and industrial production from the perspective of improving CTFP, providing a new viewpoint on the contributions of technological innovation to solving socio-economic issues. [ABSTRACT FROM AUTHOR]

Purpose: This study has incorporated competitiveness by considering it a significant factor behind determining as well as moderating industrial value added in the environmental Kuznets curve (EKC) framework. This study aims to explore the moderating role of competitiveness policy in EKC with an aim to promote business led sustainability at national level. Design/methodology/approach: Considering the environmental deterioration aspect of industrialization, this study tests the existence of EKC for SAARC countries using the data from 1996 to 2021 using second-generation static panel data model. Findings: Estimated results have validated that moderating effect is responsible for improving environmental sustainability in SAARC countries. Furthermore, population density is responsible for increasing while trade openness is responsible for decreasing carbon emissions. Originality/value: Higher industrial activities are a symbol of upward-moving economic growth. But its other impact is in the form of environmental deterioration. However, the relationship between industrialization and environmental quality can be identified through EKC. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is vital for addressing climate change and reducing carbon emissions in emerging economies. Financial development (FD) is crucial for economic growth, and its environmental impact and the adjustment of the industrial structure (IND) is a crucial lever in China's economic transition period. This study explored the relationship between FD, IND, and China's green total factor productivity (GTFEE) from 2000 to 2020 using the super-efficiency SBM-undesirable model, which estimates China's GTFEE. The ARDL results suggest that FD and IND enhance GTFEE in the long term, with FD promoting GTFEE by facilitating industrial structure adjustments. The Dumitrescu–Hurlin panel causality tests supported this finding. The QRPD panel quantile regression and heterogeneity analysis revealed significant heterogeneity in the effects. With increasing GTFEE, FD exerts a restraining effect, gradually weakening and transitioning into a promoting effect, while the IND consistently plays a promoting role. [ABSTRACT FROM AUTHOR]

This paper summarized and analyzed the scope of carbon emission accounting in industrial parks and the decoupling relationship between carbon emission and economic development in industrial parks based on one-dimensional or two-dimensional decoupling models, and discussed the influence of various factors on the decoupling relationship in the decoupling effect model based on LMDI decomposition method and Tapio decoupling model, with a view to providing reference for carbon emission inventory establishment, decoupling degree analysis, driver identification and comprehensive assessment. On this basis, it is suggested that industrial parks should formulate a carbon emission inventory reasonably, consider carbon emission drivers in multiple dimensions and build a more comprehensive indicator system. [ABSTRACT FROM AUTHOR]

In response to the underutilization of energy and insufficient flexible operation capability of rural energy supply systems in China, this study proposes an optimal dispatch approach for a rural multi-energy supply system (RMESS) considering virtual energy storage (VES). First, to enable the flexible utilization of rural biomass resources and the thermal inertia of residential building envelopes, this study constructed VES-I and VES-II models that describe electrical-thermal and electrical-gas coupling from an electrical viewpoint. Subsequently, an RMESS model encompassing these two types of VES was formulated. This model delineates the intricate interplay of multi-energy components within the RMESS framework and facilitates the precise assessment of the adjustable potential for optimizing RMESS operations. Based on the above models, a day-ahead optimal dispatch model for an RMESS considering a VES is proposed to achieve optimal economic performance while ensuring efficient energy allocation. Comparative simulations validated the effectiveness of the VES modeling and the day-ahead optimal dispatch approach for the RMESS. [ABSTRACT FROM AUTHOR]

The development of the tertiary industry is of great significance for promoting industrial structure, optimizing and upgrading it, and achieving regional energy conservation and emission reduction goals. This study adopts a quantitative method to analyze the spatio-temporal pattern of carbon emissions from China's tertiary industry from 2004 to 2019. In order to analyze emissions from aspects such as energy structure, energy intensity, energy carrying capacity, industrial structure, level of industrial development, income level, consumption capacity, energy consumption intensity, and population size, this study establishes a hybrid factor decomposition model called the "energy-industry-consumption" research framework. The study shows that carbon emissions from China's tertiary industry have been increasing year by year from 2004 to 2019, with a growth rate of 353.10%. Transportation is the largest contributor to the increase in carbon emissions from China's tertiary industry. The carbon emissions from the tertiary industry in each province show four types: high-speed growth, low-speed growth, fluctuating growth, and stable growth. During the study period, carbon emissions produce a spatial heterogeneity with the highest emissions in the south and lowest in the northwestern part of China. The spatial pattern of per capita carbon emissions is not significant. Guangdong has the highest carbon emissions, and Shanghai and Beijing have higher per capita carbon emissions. Industrial factors and consumption factors have a positive effect on carbon emissions in China's tertiary industry, while energy factors have a negative effect. The leading factor of carbon emissions in China's tertiary industry has gradually shifted from energy to industry. [ABSTRACT FROM AUTHOR]

Since the "double carbon" target was proposed in 2020, emissions reduction has become the focus of the Chinese government's work. Industrial development is a crucial factor contributing to the increase in carbon emissions. Therefore, implementing carbon reduction in the industrial sector is an important part of China's goal of "double carbon." In this context, this paper uses a three‐stage data envelopment analysis model to calculate the green total factor productivity (GTFP) of 18 industry sectors in Shanxi Province. The results show that: (1) the external environment has influence on the GTFP of energy revolution reform pilot area industrial sectors, and the efficiency value of two industries is overestimated before excluding environmental factors; (2) the industry difference of GTFP is significant, among which pharmaceutical manufacturing industry has the greatest promoting effect on GTFP, and ferrous metal mining and dressing industry has the greatest inhibiting effect on GTFP; (3) there is a serious redundancy in R&D investment of energy revolution reform pilot area in China, and only six industries belong to zero redundancy. (4) To reflect the GTFP of various industrial sectors more clearly, this paper divides four industries: "Double‐high" industry, "High‐low" industry, "Low‐high" industry, and "Double‐low" industry. [ABSTRACT FROM AUTHOR]

The article discusses the ongoing green re-industrialization in the northern parts of Sweden in response to the climate crisis. The investment of up to SEK 1.1 billion aims to develop basic industries like mining and steel production to reduce carbon emissions and achieve fossil-free operations. However, this transition also presents challenges such as the need for a larger workforce, population growth, and its impact on indigenous Sami communities. The study focuses on analyzing media discourses and the role of news media in shaping narratives and understanding the ongoing transition towards more sustainable and just communities in the Swedish North. [Extracted from the article]

The present study highlights the importance of renewable energy investment in achieving the goal of sustainability. Several studies have been conducted to explore the factors affecting environmental quality. However, the literature on the importance of renewable energy investment in affecting environmental quality is scant. Thus, this study investigates the impact of renewable energy investment on carbon emissions for 24 China provinces from 2005 to 2020, along with green finance, income per capita, technical innovations, and industrial structure. The co-integration test results show a stable long-run association between renewable energy investment and sustainable development with other factors. However, the results of AMG and CCE-MG estimators show the significant contribution of renewable energy investment, technical innovations, and green finance to environmental sustainability. Besides, economic development and industrial infrastructure show an adverse effect on environmental sustainability and cause to increase in carbon emissions. In addition, the moderate role of renewable energy investment in technical innovation and industrial infrastructure significantly contributes to a sustainable environment. On behalf of obtained outcomes, the current study proposes some imperative policy implications to attain the desired level of a sustainable environment. • Renewable energy and sustainable growth. • Research and development, renewable energy, and sustainability. • Impacts of financial development and renewable energy on socioeconomic indicators. [ABSTRACT FROM AUTHOR]

The relationship between industrialization and carbon emissions is incredibly complicated. Numerous academics have studied this subject in-depth and produced a wealth of research findings, but there has not been a comprehensive evaluation and analysis. As a result, the Web of Science Core Collection is used as the study's data source, and China is chosen as the research object. Visualization software CiteSpace and VOSviewer are utilized to conduct cooperation network analysis, co-citation analysis and cluster analysis to analyze the research progress and frontier of the impact of industrialization on carbon emissions in China (IICEC). The results indicate that: (1) Since 2007, the research enthusiasm for IICEC has grown and gone through three stages; (2) Most research institutions and authors are from China, and significant transnational research teams have not yet been established; (3) The most popular journal for this research is Journal of Cleaner Production, whereas Energy Policy has the most citations; (4) The overall research hotspots can be divided into five clusters. Based on these findings, possible future research frontiers were identified, including carbon emission decoupling analysis and carbon transfer, life cycle analysis and life cycle cost analysis of the industry, and embodied carbon measure. [ABSTRACT FROM AUTHOR]

The arrival of the dual-carbon era indicates that it is imperative to reduce industrial carbon emissions with high carbon emissions. The implementation of carbon emission reduction will inevitably have an impact on industrial development. Three different carbon emission scenarios were established. Based on the average annual carbon emission growth rate of the past decade, it is set as a medium carbon scenario. According to the economic development stage and actual social development situation of each region, the corresponding annual average carbon emission growth rate is increased and decreased to set up high carbon and low carbon scenarios. The adjacent accumulation gray multivariate model for industries is established based on different scenarios. The results indicate that the carbon emission scenarios most suitable for industrial development in various regions are different. Heavy industrial provinces and cities such as Beijing, Tianjin and Hebei have the highest industrial output value under high carbon scenarios; Provinces and cities with high levels of industrialization, such as Jiangsu, Shanghai, Guangdong and Chongqing have the highest industrial output value under low-carbon scenarios. The industrial output value of Hebei is expected to grow the fastest under the high carbon scenario, reaching 2.15 trillion yuan by 2030. The industrial output value of Guangdong achieves the greatest improvement under low-carbon scenario. It is expected that the industrial output value of which will reach 6.86 trillion yuan by 2030, ranking first in the country. Therefore, the setting of carbon emission scenarios needs to be tailored to local conditions, increase technological innovation efforts, and further promote industrial development. [ABSTRACT FROM AUTHOR]

This research investigates the intricate relationships between economic variables and how they affect South Asian nation's ability to develop sustainably. Given the growing concerns about climate change and global warming brought on by emissions of greenhouse gases, this study looks into the connection between emissions of CO 2 , green energy, industrialization, foreign direct investment, economic globalization, and financial development from 1995 to 2022. Second-generation panel techniques were employed in this study to look at the relationship between variables because of the potential of residual cross-sectional dependency and heterogeneity. The empirical outcomes display that green energy, economic globalization, and financial development reduce CO 2 emissions by 1.839%, 1.223%, and 3.902% respectively. Industrialization and foreign direct investment degrade the environment by 4.302% and 1.893% respectively. A bidirectional causality link between green energy, industrialization, economic globalization, and CO 2 emissions was found by Dumitrescu and Hurlin (D-H). Based on our findings, we recommend legislative support for renewable energy, cleaner technologies, and strict environmental regulations, aligning with the Sustainable Development Goals (SDGs). Encouraging FDI, sustainable practices, and financial development can drive economic growth while preserving the environment. As we approach COP28, this holistic approach to sustainable development becomes increasingly vital for South Asian countries to achieve their SDG targets and combat climate change. • Analyzed economic factors' impact on CO2 emissions in South Asia (1995-2022). • Used advanced panel methods on green energy, FDI, and industrialization. • Highlighted the need for renewable energy laws and strict environmental rules. • Advocated for sustainability incentives to support COP28 goals. [ABSTRACT FROM AUTHOR]

The rise in carbon emissions linked to the tourism industry has challenged its long-standing reputation as an eco-friendly sector. In parallel, the digital economy's evolution has introduced a series of transformations within tourism. This necessitates a thorough examination of the intricate interplay between the digital economy and carbon emissions in the tourism sector. With the help of Chinese provincial panel data, this study uncovers a compelling relationship marked by an inverted "U" curve through two-way fixed model, moderated effects model and threshold regression analysis. Intriguingly, an increase in road density shifts the inflection point of this curve to the lower left. As road density reaches a critical threshold of 0.361, it not only amplifies the elasticity of the inverted "U" curve but also accelerates the timeline to reach peak tourism-related carbon emissions. This study underscores a significant practical implication: while digital technology exacerbates carbon emissions from tourism at this stage, the dampening effect of digital technology is to be expected as the development of industrial manufacturing brings better transportation. However, the timing of the tipping point may be earlier or later for different regions, depending on whether the local level of industry is sufficiently developed. • The inverted "U" curve relationship between digital economy growth and tourism carbon emissions at the provincial level in China is validated. • Transportation accessibility is a key mechanism by which the digital economy affects carbon emissions from tourism. • This paper predicts the conditions for an inflection point in tourism carbon emissions within digital economy. [ABSTRACT FROM AUTHOR]

The recycling of spent lithium iron phosphate batteries has recently become a focus topic. Consequently, evaluating different spent lithium iron phosphate recycling processes becomes necessary for industrial development. Here, based on multiple perspectives of environment, economy and technology, four typical spent lithium iron phosphate recovery processes (Hydro-A: hydrometallurgical total leaching recovery process; Hydro-B(H 2 O 2 /O 2): hydrometallurgical selective lithium extraction process; Pyro: Pyrometallurgical recovery process; Direct: Direct regeneration process) were compared comprehensively. The comprehensive evaluation study uses environment, economy and technology as evaluation indicators, and uses the entropy weight method and analytic hierarchy process to couple the comprehensive indicator weights. Results show that the comprehensive evaluation values of Hydro-A, Hydro-B (H 2 O 2), Hydro-B (O 2), Pyro and Direct are 0.347, 0.421, 0.442, 0.099 and 0.857, respectively. Therefore, the technological maturity of Direct should be further improved to enable early industrialization. On this basis, this study conducted a quantitative evaluation of the spent lithium iron phosphate recycling process by comprehensively considering environmental, economic and technical factors, providing further guidance for the formulation of recycling processes. [Display omitted] • The multi-perspective model is established by environmental, economic and technical aspects. • Four typical spent lithium iron phosphate recovery processes were compared. • Direct produce carbon dioxide emissions less than 30% of those from Pyro. • The final CEV ranking is direct regeneration twice higher than Hydro-B process. [ABSTRACT FROM AUTHOR]

In order to explore effective ways for energy conservation and emission reduction, seven correlated variables are selected in this paper according to the government statistics with the extended STIRPAT model, and the impact of China's industrialization and urbanization on carbon emission intensity of energy consumption is studied. The study found that urbanization rate and urban population employment rate are the main factors affecting per capita carbon emission of energy consumption in China;the industrialization has a reverse impact on per capita carbon emission of energy consumption, indicating that China's industrialization is relatively low and is not the main factor affecting per capita carbon emission of energy consumption; the service industry added value rate and the agricultural industry added value rate also have reverse effects on China's per capita carbon emission of energy consumption, and the degree of impact is relatively small. Therefore, China is supposed to develop industry vigorously in the future, to appropriately control the development speed of urbanization and to increase the agricultural industry added value rate moderately, so as to achieve effective control of per capita carbon emission intensity of energy consumption. [ABSTRACT FROM AUTHOR]

Environmental pollution is a principal concern for all countries. In particular, the issue is alarming for Australia as the country has been suffering from various environmental disasters for some recent years. Therefore, examination the roles of some variables that are related to environment are vital. To this end, this work endeavors to ascertain the impacts of industrialization, non-renewable and renewable energy use, and financial development on environmental pollution in Australia. Using the data period of 1990–2020, a series of econometric techniques such as the Augmented Dickey-Fuller test, Phillips-Perron test, Autoregressive Distributive Lag (ARDL) bounds test and the pairwise Granger causality test are applied. The findings reveal that industrialization and non-renewable energy use increase while the square of industrialization, renewable energy use, and financial development reduces CO 2 emissions in Australia. The validation of the environmental Kuznets' curve (EKC) hypothesis is also found. Bidirectional and unidirectional causal association of the studied variables with CO 2 emissions are attained. All the outcomes are theoretically and empirically relevant and have important policy implications. [ABSTRACT FROM AUTHOR]

On the way towards carbon emission peaking, the influence of the interactions within urbanization, industrialization and energy consumption on the peaking process from the perspective of system evolution remains exclusive. Herein, targeting 30 Chinese provincial regions, we design an integrated framework consisting of 21 indices to represent a coupled urbanization-industrialization-energy (UIE) system. The coupling and coordination within the UIE system are measured and linked to regional carbon emission trajectory during 2000–2021 to explore the influence mechanism on its peaking process. The findings reveal levels of the coupling and coordination ranging from 0.30 to 0.99, with an inverted U-shaped pattern for the coupling and a progression from rapid to gradual growth for the coordination. The comprehensive coupling-coordination degree for regions has not yet reached the state beneficial for achieving the emission peak. The development quality of urbanization subsystem and industrialization subsystem is progressively relieving reliance on the energy subsystem, while a complete decoupling from carbon emissions has not been achieved. The influences of driving forces of the coordination exhibit spatiotemporal variations. The region-specific insights into steering the UIE system towards peaking carbon emissions with emphasis on the key driving forces are of practical significance. • A framework of coupled urbanization-industrialization-energy (UIE) system is designed. • Coupling within UIE system is measured and linked to carbon emission trajectory. • Influence of development of coupled UIE system on carbon peaking process is revealed. • Comprehensive coupling-coordination hasn't allowed for achieving the emission peak. • Influences of driving forces of the coordination exhibit spatiotemporal variations. [ABSTRACT FROM AUTHOR]

The funding statement for this paper is incorrect. The correct funding statement is: This research is funded by the University of Economics and Law, Ho Chi Minh City, Vietnam, and Vietnam National University, Ho Chi Minh City, Vietnam.By Nguyen Thi Quy; Nguyen Chi Hai and Ha Thi Thieu DaoReported by Author; Author; Author [Extracted from the article]

The carbon emissions in BRICS countries (Brazil, Russia, India, China and South Africa) account for nearly half of global carbon emissions. To explore the future carbon emissions in BRICS countries and the carbon peak in China and India, the grey Gompertz model with new information priority accumulation is proposed. Intelligent algorithms are used in the parameter optimization. The new model not only increases the influence weight of new information on the predicted results, but also changes the predicted trend of traditional grey prediction model. The effectiveness of the new model for the carbon emission forecast is verified through the known data set. According to the predicted results, the carbon emissions in Russia, Brazil, South Africa tend to stabilize over the long term. The carbon emissions in China and India are rising slowly. China will achieve the carbon peak in 2029 with 10.2 billion tons of carbon emissions. India will not achieve the carbon peak by 2030. The current situations of the carbon emissions in BRICS countries are analyzed. It is concluded that the energy structure, industrial development and the urbanization need to be paid attention to. Detailed policies and suggestions are given in the fourth section. The above research results indicate that the new model can predict the limit value of the carbon emission. The predicted results can provide data support for the policy formulation in carbon reduction. [Display omitted] [ABSTRACT FROM AUTHOR]

The carbon emissions in BRICS countries (Brazil, Russia, India, China and South Africa) account for nearly half of global carbon emissions. To explore the future carbon emissions in BRICS countries and the carbon peak in China and India, the grey Gompertz model with new information priority accumulation is proposed. Intelligent algorithms are used in the parameter optimization. The new model not only increases the influence weight of new information on the predicted results, but also changes the predicted trend of traditional grey prediction model. The effectiveness of the new model for the carbon emission forecast is verified through the known data set. According to the predicted results, the carbon emissions in Russia, Brazil, South Africa tend to stabilize over the long term. The carbon emissions in China and India are rising slowly. China will achieve the carbon peak in 2029 with 10.2 billion tons of carbon emissions. India will not achieve the carbon peak by 2030. The current situations of the carbon emissions in BRICS countries are analyzed. It is concluded that the energy structure, industrial development and the urbanization need to be paid attention to. Detailed policies and suggestions are given in the fourth section. The above research results indicate that the new model can predict the limit value of the carbon emission. The predicted results can provide data support for the policy formulation in carbon reduction. [Display omitted] [ABSTRACT FROM AUTHOR]

High level of carbon emissions is still a policy agenda because of its detrimental effect on environment. CO 2 emissions are growing quickly in emerging countries with the high energy consumption, industrial activities, and rapid globalization. So, it is important to examine the roles of emission-inducing factors in these countries. To this end, this research investigates the dynamic effects of energy intensity, renewable energy, industrialization, urbanization and international trade on carbon intensity in the 25 largest emerging economies of the world. The study is based on the data period of 1990–2018, where the Pool Mean Group (PMG) estimation technique of the panel Autoregressive Distributed Lag (ARDL) approach is used, along with different diagnostic tests. The findings are, in the long-run, carbon intensity is increased by energy intensity and industrialization, and decreased by renewable energy use and urbanization. An increase of one unit in energy intensity and industrialization increased carbon intensity by 2.616 unit and 0.002 unit, respectively. Conversely, carbon intensity reduced by 0.003 unit with an increase of one unit in renewable energy and urbanization. In the short-run, carbon intensity is positively associated with energy intensity only with a coefficient value of 0.811. Therefore, an increase in renewable energy production and use, and enhancement of green technology for industrial production can be viable options for carbon reduction. [Display omitted] • Renewable energy, energy intensity, industrialization, and carbon intensity. • Panel ARDL approach is applied on the 25 largest emerging economies. • Energy intensity and industrialization increase carbon intensity. • Renewable energy use and urbanization decrease carbon intensity. • An increase in renewable energy production and use is a viable policy option. [ABSTRACT FROM AUTHOR]

The author reflects on historic patterns of slavery and empire, industrialisation and consumption. Topics discussed include awareness of deep structural racism that came about as a result of the murder of George Floyd, in Minneapolis, Minnesota; 26th Conference of the Parties (COP26), organised by United Nations Framework Convention on Climate Change (UNFCCC) and banking on new strategies for economic growth by making pledges based on commitments to deliver Net Zero carbon emissions by 2050.

This paper analyzes the time-varying impacts of Chinaʼs economic growth, energy efficiency, and industrial development on carbon dioxide (CO2) emissions from 1970 to 2019. First, we examined and found that there are two significant structural changes in the CO2 sequence over the years, and there was a significant nonlinear relationship among the four. The first nonlinear structural model constructed is the TVP regression model. According to the Bayesian model comparison criterion, TVP-SV-VAR was selected as the second constructed model from four types of VAR models containing nonlinear structures. The results show that the conduction intensity value of energy use efficiency to CO2 emissions has increased year by year, from 0.45 in 1971 to 0.97 in 2019. The short-term transmission mechanism of energy use efficiency to carbon emissions is the most significant. The conduction intensity of Chinaʼs economic growth on CO2 emissions increases year by year. Chinaʼs economic growth plays a major role in long-term CO2 emission reduction. The impact of industrial development on CO2 emissions reached a peak of 0.34 in 1977, and the intensity of the impact has basically stabilized at 0.26. [ABSTRACT FROM AUTHOR]

As the world's largest developing nation, China has emerged as the predominant carbon emitter due to its swift industrialization and urbanization. Achieving low-carbon development in China necessitates a tailored approach that accounts for each city's unique industrial phase, technological advancements, urbanization level, and resources. This research endeavors to elucidate the nonlinear mechanism influencing carbon emissions in Chinese cities using a machine-learning framework, drawing on panel data from 290 cities from 2000 to 2017. The result indicates that China is experiencing a transition in the primary drivers of carbon emissions from the agriculture sector to the industrial and service sectors. A city transitions to the carbon decoupling phase when the outputs of primary, secondary, and tertiary industries surpass 1500, 125,000, and 100,000 CNY per capita, respectively. Additionally, we observed that expanding the urban built-up area beyond 10% can significantly mitigate carbon emission intensity. However, the study also highlights a critical challenge: the initial emission-reducing effects of innovation in burgeoning high-tech industries are negated by the higher emissions from traditional industries. Moreover, our analysis indicates that R&D investments exceeding RMB 8000 per capita may paradoxically lead to an increase in emissions. With these conclusions of nonlinearity, we emphasize designing policies tailored to the specificities of each city, stressing the importance of adaptability in policy creation. • The carbon emission of the secondary sector is decoupled as output rises. • High tertiary sector output per capita will reduce carbon emissions. • Technological application limits the carbon-reducing effect of innovation output. • Traditional industries mask the low-emission from technological innovation. • Constructing accurate nonlinear driving patterns by ensemble learning algorithms. [ABSTRACT FROM AUTHOR]

• The impact of land finance on carbon emissions in China is quantitatively examined. • A specially designed two-stage regression method that could well address endogeneity is employed. • The direct and indirect influences of environmental effects of land finance are distinguished and evaluated. • The direct influences are estimated to dominate the total influences. • The total impact of land finance on carbon emissions is dependent on the level of GDP per capita. In the past two decades, land finance, a phenomenon of the financing arrangement based on land development, has gradually become a fiscal model that profoundly affects China's economic development. Based on the theory of fiscal decentralization and environmental federalism, this study employs a specially designed two-stage regression method to capture both direct and indirect (through economic development and industrial structure) influences of land finance on carbon emissions. Using the provincial panel data for the period of 1998–2016, the empirical results indicate that the direct influences are dominant, and the total impact of land finance on carbon emissions is non-linear and is dependent on the level of Gross Domestic Product (GDP) per capita. After 2003, the total effect is that carbon emissions increase continuously along with the economic development. To balance economic development and environmental protection and to enhance sustainable development, the traditional style of land finance should be changed as soon as possible. [ABSTRACT FROM AUTHOR]

This paper spotlights whether gross domestic product (GDP), energy consumption and urbanization affect Carbon dioxide (CO2) emissions covering the time span 1972-2014 in Pakistan. The empirical estimates of autoregressive distributed lag (ARDL) affirmed that energy consumption and GDP are the main drivers of the pollutant environment in Pakistan, and also quantitatively determine the definite impact percentage of each dynamic force in Pakistan. Specifically, the empirical findings determine that in the long run, energy consumption and GDP intensify CO2 emissions showing significant impact; however, industrialization and urbanization are found to be insignificant. Based on empirical findings, this suggests that the constricting economic gap implementation between urban and rural areas, amendments to the energy erection and mechanical novelty will offer a treasured reference for Pakistan in exertions to diminish carbon emissions. [ABSTRACT FROM AUTHOR]

Environmental regulation affect industrial agglomeration, which in turn influences CO 2 emissions. However, the impact of the stage of industrialization on the emission reduction effects of environmental regulation on industrial agglomeration has not been sufficiently studied. This study explores the effect of industrial agglomeration on CO 2 emissions using panel data from 286 prefecture-level cities in China from 2003 to 2020 from the perspective of environmental regulation. The results of the extended STIRPAT model showed a U-shaped relationship between industrial agglomeration and CO 2 emissions, whereas industrial agglomeration was closely related to the degree of environmental regulation. Tightening environmental regulation hinders the emission reduction effect of industrial agglomeration, especially in the early stages of industrialization. The threshold model indicated that the larger the ratio of industrial output to GDP, the greater the effect of environmental regulation on emission reduction from industrial agglomeration. These findings suggest to reduce emissions in cities, the level of industrial agglomeration and stages of industrialization should be considered to implement effective environmental regulation policies. The timetables to achieve low-carbon development and carbon neutrality can differ and governments should adapt environmental regulation policies to local conditions as much as possible. [ABSTRACT FROM AUTHOR]

Combating climate change and reducing carbon dioxide emissions are serious challenges shared by countries around the world. In the current era, digitalization has a significant impact on CO 2 emissions. However, prior studies have not assessed the synergy between digitalization and industrialization on carbon emission performance. The principal component analysis and non-radial directional distance function (NDDF) are used to measure the digitalization and total factor carbon emission performance of Chinese 245 prefecture-level cities from 2003 to 2019. This study establishes a fixed effects model to study the panel data. The findings are as follows: (1) Digitalization can significantly promote Chinese cities' CO 2 emission reduction. This result still holds after several robustness checks. (2) The heterogeneity results indicate that digitalization mainly improves central cities' carbon emission performance. Meanwhile, the impact of digitalization is more obvious after 2011. (3) Digitalization improves urban carbon emission performance through energy efficiency, industrial transformation, and technological innovation. (4) It is worth noting that digitalization synergizes with industrialization to improve carbon emission performance in Chinese cities. This study provides empirical evidence and some constructive policy recommendations for the government to push the collaborative development of the digitalization and low-carbon economy. [Display omitted] • This paper uncovers the synergistic effect of digitalization and industrialization on cities' carbon emission performance. • We measure urban digitalization level and total factor carbon emission performance. • There are three influencing mechanisms including energy efficiency, industrial transformation, and technological innovation. • Digitalization synergizes with industrialization to enhance carbon emission performance in Chinese cities. • Some constructive policy recommendations are proposed for pushing the cities' low-carbon transformation. [ABSTRACT FROM AUTHOR]

The study aims to examine lagged causal effect of economic development policies on the carbon footprint of Southeast Asia. This study employs unit root test, cointegration test and panel data analysis methods to examine endogeneity concerns in observational data. The study applies panel data analysis methods to address unobserved country effect in the model. The balanced panel data includes a total of 240 observations with five cross sections of five nations in Southeast Asia and with 48 time-specific periods of 1970–2017. The results indicate that (1) exports, industrialization, urbanization and economic growth have lagged negative effect on the carbon footprint of the region in the short-run, and (2) there exists a long-run equilibrium relationship among exports, industrialization, urbanization, economic growth and carbon footprint in the region. The findings suggest that the economic growth, exports, industrialization and urbanization of the developing countries in Southeast Asia have been achieved at the cost of increasing the carbon footprint of the region. The findings imply that the environmental policy of the export-led growth countries never have been effective so far since the nations have achieved their economic growth at the high cost of harming the environment of the nations. [ABSTRACT FROM AUTHOR]

This paper examines long-run and short-run dynamics of renewable energy consumption on carbon dioxide (CO2) emissions and economic growth in the European Union. This study employs cointegration tests, Granger causality tests and vector error correction estimates to examine the direction of Granger causality, the long-run dynamics of economic growth and energy variables on carbon emissions. This study analyses time series data from the World Development Indicators over the period from1961 to 2012. The results of this study support a link between renewable energy consumption, economic growth, industrialization, exports and CO2 emissions in the long-run and short-run. The results support that the sign of the long-run dynamics from the endogenous variables to the CO2 emissions variable is negative and significant, which implies that the energy and environmental policies of the European Union aimed at curbing CO2 emissions must have been effective in the long-term. Furthermore, renewable energy consumption and exports have significant negative impact on CO2 emissions in the short-run. However, industrialization and economic growth have positive impact on CO2 emissions in the short-run. The results suggest that both economic growth and industrialization must have been achieved at the cost of harming the environment. The finding suggests that the increasing consumption of renewable energy tends to play an important role in curbing carbon emissions in the region. [ABSTRACT FROM AUTHOR]

China has experienced a remarkable economic progression since the implementation of its reform and opening-up policy. Yet, it is crucial to confront the challenge of achieving sustainable and high-quality economic growth while concurrently enhancing environmental quality. This study adopts the nonlinear autoregressive distributed lag (NARDL) approach to explore how economic structure adjustments impacted China's carbon dioxide (CO 2) emissions from 1980 to 2020. The empirical results reveal some asymmetries in the influence of agricultural progression, industrial development, and foreign direct investment (FDI) on CO 2 emissions in short and long-term contexts. Specifically, in the long run, a 10% positive change in agricultural development increases CO 2 emissions by 1.55%, nearly double the mitigation effect of a negative change (0.78%); a 10% positive (negative) change in industrialization is associated with a 0.6% decrease (0.23% increase) in CO 2 emissions; a 10% positive change in FDI results in a 2.30% increase in CO 2 emissions, supporting the "Pollution Haven" hypothesis, while a 10% negative change contributes to a 4.51% increase. In the short run, a 10% negative change in agricultural and industrial sectors increases CO 2 emissions by 0.27% and 0.21%, respectively, while a 10% negative change in FDI leads to a 2.0% increase in CO 2 emissions. Additionally, short-term positive changes in agricultural and industrial sectors and positive shocks in FDI exert negligible influence on CO 2 emissions. These findings highlight the necessity of economic structure transformation and refinement of current environmental policies. [Display omitted] • The asymmetric response of CO 2 emissions to some critical variables is analyzed. • Agricultural growth cannot reduce CO 2 emissions in both the short and long run. • Industrial development can mitigate CO 2 emissions in the long run. • The "Pollution Haven" hypothesis on FDI is validated in China. • Foreign trade positively correlates with CO 2 emissions in China. [ABSTRACT FROM AUTHOR]

This study empirically explored the nexus of wind energy (with regards to the effect of the drought), industrial-economic development, and emitted CO 2 in 41 World's top countries in wind energy consumption from 1997 to 2018. Cross-sectional augmented distributed lag estimators (CS-DL, CS-ARDL, CCE-P) and newly updated estimation packages to effectively assess the relationships between variables. Our results are the following: First, severe droughts were not a significant matter in wind energy, and consuming wind energy reasonably contributes to reducing emitted CO 2 , while industrial and economic development positively promotes CO 2 emissions in sampled countries. Second, industrial development significantly promotes economic growth, while wind energy use has an insignificant positive effect on economic growth. Moreover, wind energy negatively affects industrial development. Third, two-way directional causal relationships were noted between CO 2 and other covariates, this hypothesis was also noted between industrial development and economic growth and wind energy use. We, therefore, suggested policy implications to reduce CO 2 across the globe and country-specific and consider the positive effect of wind energy on growth. • Wind energy-industrial-economic development-CO 2 nexus investigated for 25 years. • Most recent estimators employed in 41 top global consumers of wind energy. • Wind energy use negatively affects CO 2 , while positively affecting growth. • Industrial and economic growth positively affects CO 2. [ABSTRACT FROM AUTHOR]

Industrial structure adjustment is one solution for responding economic slowdown and environmental problems occurred during China’s rapid industrialization. Such an adjustment may also lead to carbon emission reduction since it encourages industrial innovation and resource efficiency. However, few studies have been conducted on examining the effect of industrial structure adjustment on carbon emission reduction. Under such a circumstance, this study develops an integrated evaluation model based on Input-Output Analysis and Social Network Analysis to quantify the evolutionary trends of industrial structure, demonstrate the inner-relationship between different sectors and investigate the industrial structure-related carbon emissions. China and Japan were selected as case study countries. Results show that industrial structure was gradually improved in China and various connections were established between different sectors. For Japan, the industrial network densities were lower than for China and exhibited a downward trend that reflected the weakened relationship between different industries. Service sectors dominated the Japanese economy, as shown by the relatively higher degree centrality and betweenness centrality of service sectors. The electricity and heat production sector was further investigated to illustrate the industrial structure-related carbon emissions. Finally, this study concluded that compared to the industrial structure features in a developed country, such as Japan, China’s industrialization is still in its infancy. Thus, it is crucial to prepare industrial structure adjust policies so that the overall social-economic performance can be improved. [ABSTRACT FROM AUTHOR]

• Energy use positively affects carbon emission intensity. • Urbanization has positive impact on carbon emission intensity. • Technological innovation negatively affects carbon emission intensity. • Data was analyzed by Quantile-on-quantile model. In recent years, policy experts have engaged in a spirited discussion over the relationship between environmental quality and energy use. This association is critical for the mitigation of climate change and achieving Sustainable Development Goals (SDGs). Furthermore, current studies have not given enough consideration to this relation, notably in the case of the Kingdom of Saudi Arabia (KSA). Therefore, this study examines the KSA case, focuses on the connection of industrialization, foreign direct investments, and technological innovation with carbon emissions intensity (CEI) by also considering urbanization and energy use, examines the period between 1991 and 2020, and uses quantile-on-quantile (QQ) regressionand quantile regression (QR) approaches for empirical examination. The empirical outcomes revealthat (i) urbanization and energy usehave an increasing impact on CEIin all quantiles; (ii) industrialization, foreign direct investments, and technological innovation have a generally decreasing impact on the CEI in most quantiles; (iii) power of the factors' impact on the CEI change according to quantiles; (iv) the robustness the findings is also validated. Hence, theresults highlight the importance of quantile-based analysis and suggest that KSA authorities need to embrace environment-friendly policies while managing environmental pollution to develop industrialization level and technological innovation as well as increase foreign direct investments. [ABSTRACT FROM AUTHOR]

Technological advancements have played a key role in improving energy efficiency and reducing emissions, and industrial robots are important carriers of intelligent manufacturing and industrial upgrading. Although various countries and regions are under pressure to reduce their carbon emissions, a consensus has not been reached on whether industrial robots can help. This study investigates how industrial robots affect carbon emissions by categorizing industry data from the International Federation of Robotics (IFR, 2010–2018) into city-level variables. The empirical finding revealed that cities' carbon emissions have been significantly reduced by the application of industrial robots. By using the penetration of robots in Chinese cities as an instrumental variable constructed through the combination of employment level and robot imports, the beneficial role of robots is further verified by a plausibly exogenous test. The mechanism analysis revealed that industrial robots contribute to cities' decarbonization by enhancing energy efficiency and green technology efficiency. The heterogeneity analysis showed that the effect of industrial robots on decarbonization is more pronounced in megacities, advanced manufacturing bases, and low-carbon pilot cities. This study empirically confirms the positive role of industrial robots in carbon emission reduction, provides evidence for industrial robots' technical characteristics of decarbonization, and proposes novel ideas for achieving net-zero carbon emissions. [Display omitted] • Industrial robots help to reduces carbon emissions in Chinese cities. • Instrumental variable is applied in the treatment of potential endogenous problems. • The mechanisms of decarbonization by industrial robots are explored. • Heterogeneity exists in the impact of robots on cities' carbon emission reduction. [ABSTRACT FROM AUTHOR]

Shrinking cities are a category of cities characterized by population loss, and the environmental problems of these cities are often neglected. Using panel data from 2012 to 2019, this paper investigates the spatial and temporal distribution characteristics of carbon emissions in shrinking cities in China and the driving factors. The results find that: (1) From 2012 to 2019, carbon emissions tend to increase in shrinking cities and decrease in non-shrinking cities. Due to earlier industrial development and ecological neglect, shrinking cities in Northeast China have higher carbon emissions than other regions. (2) Population size, industrial structure and public services promote the growth of carbon emissions in shrinking cities. The influence of living environment on carbon emissions in shrinking cities is not significant. There is an environmental Kuznets curve (EKC) relationship between economic level and carbon emission. (3) In shrinking cities, the increase in commuting time and distance due to spatial expansion promotes the growth of carbon emissions. Foreign investment decreases with the loss of population, which reduces carbon emissions. Technological progress gradually declines as investment in science and technology decreases, which makes carbon emissions grow. This paper clarifies the driving factors of carbon emissions in shrinking cities in China, and therefore, the findings of this paper have important reference value for the formulation of carbon reduction policies in shrinking cities in developing countries. • Carbon emissions in shrinking cities tend to grow. • Shrinking cities have higher carbon emissions compared to non-shrinking cities. • The characteristic factors of shrinking cities affect carbon emissions. • Carbon emissions from shrinking cities have spatial effects. [ABSTRACT FROM AUTHOR]

• Ambarli Project is a full repowering by conversion to a combined cycle power plant. • Ambarli Repowering Project is a first of its kind in Turkey. • Official performance test results are used to validate the accuracy of the model. • Overall repowered combined cycle block is modeled using Cycle-Tempo. • Repowering has economic and environmental benefits while increasing power output. Increasing electricity demand as a result of industrial development brings with it the need for larger installed power generation capacity. However, existing regulations, capital costs of new equipment, time-dependent constraints, and public opposition against building new power plants pose a strong challenge for greenfield power generation projects. These compelling factors have caused the repowering concept to gain importance again in recent years. Ambarli Repowering Project is a "Full Repowering by Conversion to Combined Cycle Power Plant" project that is the first of its kind in Turkey and is equaled in magnitude and complexity by only a handful of worldwide examples. In this context existing heavy fuel–oil fired steam power plant was repowered by conversion to natural gas fired combined cycle power plant. Here, in this paper, initial performance calculations of the existing steam turbine and achievable power output after rehabilitation are presented. Parameters such as inlet temperature, pressure, and steam mass flow are defined as boundary conditions for the model of the repowered Ambarli Power Plant that allows a comprehensive evaluation of the performance of the combined cycle power plant. An in-depth real case study is conducted to validate the outputs of the developed model by comparing them with the official performance test results. Results show that the total capacity of a conventional steam power plant can be increased by 203%, while the increase in heat rejection from the condenser is only 25%. Moreover, it is found that repowering has significant positive environmental effects such as reduction of NO X , SO X , and CO 2 emissions in addition to economic benefits. Therefore, it is expected that this unique study, which has been validated with official performance tests, will shed light on similar projects to be made in the future. [ABSTRACT FROM AUTHOR]

• The average carbon reduction performance increases year by year. • The policy has an immediate impact on CO 2 reduction in demonstration cities. • The policy has follow-up impact on carbon emission reduction. • Less thermal power and more research investment are the paths to policy effect. The Energy-saving and Emission Reduction Demonstration City (ESERD) Policy brings more favorable development conditions and opportunities for the cities selected, but the carbon reduction effect of the energy-saving policy is not clear which needs to be quantified and evaluated. By measuring the Total Factor/Energy Carbon Performance Index (TCPI /ECPI) of 286 prefecture-level cities in China from 2003 to 2019 and by constructing a quasi-natural experiment, this paper contributes in three aspects. (1) we are committed to a method of calculating the energy consumption and carbon emission of prefecture-level cities in China; (2) we provide evidence to the CO 2 reduction effect of the ESERD policy in a more comprehensive way; (3) we probe the paths of the policy effects. The main findings are: (1) TCPI and ECPI has been rising since 2011, the eastern cities have more outstanding achievement while the performance of the western region has been at a relatively high level during the time period of the study, and the performance of cities have diverged in recent years. (2) The policy's contribution to the demonstration cities' carbon reduction performance is significant, immediate and far-reaching, a lower share of electricity consumption due to indirectly reducing the use of coal, and higher investment in scientific research for improving the technology level of industrial development are both paths to achieve carbon emission reduction in the demonstration cities. [ABSTRACT FROM AUTHOR]

• Developing countries face the dual challenges of industrialising and 'catching up' while mitigating CO 2 emissions. • Medium- and high-technology manufacturing is associated with lower emissions than low-technology manufacturing, with differences varying by the income levels of countries. • A shift to more technology-intensive manufacturing could be one aspect of environmentally sustainable industrialisation in developing countries. Industrialisation is an important engine of growth and 'catch up', but also associated with harmful carbon dioxide emissions and hence with climate change. This poses a challenge for sustainable industrial development, particularly for late industrialisers on how to industrialise while also mitigating carbon dioxide emissions. This paper investigates the effect of technology intensity across manufacturing industries on carbon dioxide emissions: are medium- and high-technology manufacturing industries less emissions-intensive than low-technology manufacturing industries in developing countries? The paper analyses this relationship for a panel of 68 developing and emerging economies over the period 1990–2016, by adapting the environmental Kuznets curve and the stochastic effect by regression on population, affluence and technology approaches. Using two alternative measures of emissions and estimating generalised method of moments model, the results show that medium- and high-technology manufacturing industries are associated with lower carbon dioxide emissions than low-technology manufacturing industries. The results also show that these differences vary by the income levels of countries. These findings have important policy implications, suggesting that a shift towards more technology-intensive manufacturing production processes may be a more environmentally sustainable industrialisation path for developing countries. [ABSTRACT FROM AUTHOR]

• PAH records in Liaodong Bay provides the first detailed reconstruction of industrial activities;. • PAH variations can be divided into four episodes linked to industrialization process since 1815. • Dominant PAH sources of Northeast China shift from wood to coal and petroleum over time;. • PAH fluxes could be used to track the trend for regional anthropogenic CO 2 emissions. Polycyclic aromatic hydrocarbons (PAHs) are excellent tracers for fossil fuel combustion, natural fires and petroleum contamination, and have been widely used for reconstructing past wildfires and industrial activities at a variety of time scales. Here, for the first time, we obtain a high resolution (annual to decadal scale) record of PAHs from two parallel marine sediment cores from the Liaodong Bay, Northeastern China to reconstruct the industrial activities, spanning the past ∼ 200 years from 1815 to 2014. Our data indicate that PAH variations can be divided into four episodes: I) low (probably near background) PAHs from natural fires and domestic wood combustion during the pre-industrial period from 1815 to 1890; II) slightly increased (but with large fluctuations) PAH concentrations derived from intermittent warfare during the World War (1891–1945) and increased industrial activities after 1946 (1946–1965); III) a period of stagnation and, in some cases, reduction in PAHs during the "Cultural Revolution" (1966 to 1979); and IV) a rapid and persistent rise in PAHs post 1979 linked to fast economic development, with PAH concentrations doubled from 1979 to 2014. Changes in PAH distributions demonstrate major shifts in the dominant types of fuels over time from vegetation/wood, to coal and wood, followed by coal and petroleum (including vehicle emissions) over the past 200 years. We find that PAH records also show similar trend to domestic economy and the estimated regional Anthropocene CO 2 emissions from industrial activities, suggesting sedimentary PAH fluxes could be used as an indirect and qualitative proxy to track the trend for regional anthropogenic CO 2 emissions. [Display omitted] [ABSTRACT FROM AUTHOR]

Based on the two-level Logarithmic Mean Divisia Index (LMDI) method and Tapio index, this paper constructed an expanded decomposition model for decoupling elasticity and effort index of industrial carbon emissions, and further quantitatively analyzed the delinking indicators on industry growth and environmental pressures in Beijing–Tianjin–Hebei (BTH) economic band from 1996 to 2010. The results indicate that: (1) together with the rapid economic growth, industrial energy-related carbon emissions in BTH region rose from 44477.43 × 10 4 t in 1996 to 105602.33 × 10 4 t in 2006 and then declined to 64426.71 × 10 4 t in 2010, with an average annual growth rate of 2.94%. Our results also show that carbon emissions in BTH region were dominated by the secondary industry, which accounted for about 80% of total carbon emissions. (2) “Weak decoupling” was the main characteristic during the 9th Five-Year Plan period (1996–2000) and 11th Five-Year Plan period (2006–2010), particularly “strong decoupling” in 2007; while “weak coupling” was the main characteristic during the 10th Five-Year Plan period (2001–2005). (3) The rapid economic growth was the main factor responsible for industrial decoupling blocking. The energy structure and energy intensity made significant contributions to the industrial decoupling progress. The industrial structure effect had varied considerably over the years without showing a clear trend. [ABSTRACT FROM AUTHOR]

The bottleneck of China's industrial carbon efficiency improvement is that the contribution of carbon emission technology is less than that of energy technology, and that of neutral technology is less than that of capital-based technology. The key to breaking through this bottleneck is to clarify how heterogeneous technological progress enhances carbon efficiency through industrial structural upgrading. The effects of four levels of technological progress on carbon efficiency under two technical classifications based on technology sources and carbon emission processes from energy consumption are studied by using the DEA method. The suitable choice of the path of technological progress to promoting China's industrial carbon efficiency is provided accordingly. The panel data model is used to deeply investigate the effects of these four levels of technological progress on industrial carbon efficiency in China's 30 provincial industries. The main results are as follows: First, in terms of direct effects, progress in energy technology is more conducive to improving carbon efficiency than progress in carbon emission technology, and progress in neutral technology is more effective in improving carbon efficiency than progress in capital-embodied technology. Second, in terms of indirect effects, progress in capital-embodied technology is effective in upgrading industrial structures and enhancing carbon efficiency; and, through green upgrading of industrial structures, progress in energy technology has a positive and significant impact on carbon efficiency. Third, the level of industrial development and government environmental governance have a positive impact on carbon efficiency, and the energy structure has a negative impact on carbon efficiency. • Different technologies impact carbon efficiency through different paths. • NT and CET promote industrial structure grading and carbon efficiency. • Industrial structure grading promotes ET and CT progress. • Promoted by industrial structure grading promotes carbon efficiency. • ET and CT progress promotes carbon efficiency. [ABSTRACT FROM AUTHOR]

This study aims to explore the relationship between industry value added, renewable energy, and CO2 emissions in a sample of 44 Sub-Saharan African countries over the period 2000–2015. This study makes several important contributions to extant research. While existing research was focused on the renewable energy-CO2 emissions nexus, the current study assesses the moderating role of the renewables sector in the industrialization-CO2 emissions relationship. In addition, this study considers whether EKC relationships will hold after accounting for structural transformations (including industrial contributions to GDPs). Moreover, we are revising the existence of the EKC framework for the Sub-Saharan African countries. Using a two-step system GMM estimator, we found that the share of industry in GDP has a significant positive impact on CO2 emissions, while renewable electricity output reduces CO2 emissions. If causal, a one percentage point increase in renewable electricity output reduces carbon emissions by 0.22%. Moreover, the renewable energy sector then mediates the positive effect of industry value added on CO2 emissions. We also find evidence for the statistical significance of the inverted U-shaped relationship between GDP per capita and CO2 emissions. [ABSTRACT FROM AUTHOR]

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic and environmental processes. Specifically, improvement in public services, indicated by education and cultural developments, reduces the increase in carbon emissions during urbanization, while economic growth and urban construction reinforces the growth in carbon emissions. Second, we examined the impact of various urbanization processes on carbon dioxide emissions using a unique dataset of 182 prefecture-level cities that covers a wide span of regions in China. The results of our analyses on the city level have important implications for the formulation of comprehensive policies aimed at reducing carbon dioxide emission in urban areas, focusing on different urbanization processes in economic, social, and environmental phases. [ABSTRACT FROM AUTHOR]

China is the world's largest carbon emitter, and the Beijing-Tianjin-Hebei metropolitan region is an energy-intensive area in China. Under the requirements of the national policy of regional green development, the Beijing-Tianjin-Hebei region needs to shift to a low-carbon development mode to achieve regional emission reduction targets. The varying characteristics of industrial carbon emissions resulting from differences in the industrial development and resource endowment of each city make it difficult to implement the same emission reduction policy, so different cities need to be treated differently. Based on data from three provinces and eight cities in the region from 2002 to 2016, this study used the multi-regional (M-R) spatial decomposition method to compare the carbon emissions and the effects of their influencing factors in each city, so as to provide a targeted emission reduction policy for each city. The estimation results revealed that carbon emissions in the Beijing-Tianjin-Hebei region peaked in 2012, and energy intensity and population size are the main reasons for the differences in carbon emissions at the provincial level. At the city level, Tangshan, Handan and Shijiazhuang are high carbon emission cities, while Hengshui, Baoding, Langfang, Qinhuangdao and Xingtai are low carbon emission cities. The total amount of carbon emission in all industries in Tangshan ranks the first, and economic scale and energy intensity are the main reasons for the high carbon emissions in its manufacturing and transportation sectors. Energy intensity and energy structure are the main reason why the carbon emission of Handan is higher than that of Baoding, a city with the same economic level. Shijiazhuang has high energy efficiency, but its economic development and carbon emissions have not yet been decoupled. Hengshui's high energy intensity is an obstacle to emission reductions in all industries. Xingtai's energy structure contributes to carbon emission reduction. The current industrial structures of Qinhuangdao, Langfang, and Shijiazhuang may help these cities reduce emissions. Lastly, we offer recommendations for urban emission reduction policies. • The CO 2 emissions of the Beijing-Tianjin-Hebei differ, the spatial differences in factors that affect industrial CO 2 emissions. • At the provincial level, energy intensity and population were the primary reasons for higher CO2 emissions in some sectors. • At the prefecture-level, the cities of Tangshan, Handan, and Shijiazhuang had higher CO 2 emissions. [ABSTRACT FROM AUTHOR]

Industrialization and urbanization have aggravated the contradiction between environmental protection and economic growth, leading to health issues. While there are considerable interests in understanding the health effects of carbon emissions in the context of climate change, little is observed at regional scale and by econometric methods. Applying regression analysis on 2002–2017 Chinese provincial-level panel data, this study explores the intermediary mechanisms and regional differences of carbon emissions on residents' health. The results indicate that: (1) Carbon emissions have a long-term adverse impact on residents' health—a 1% rise in carbon emission adds 0.298% more outpatients and 0.162% more inpatients; (2) The rise in carbon emissions impairs residents' health mainly by raising the temperature; (3) In areas with high levels of industrialization and urbanization, increased carbon emissions bring greater health risks; and (4) In terms of China's unique "leading industrialization and lagging urbanization" situation, only by upgrading industrial structure, improving urbanization quality, and promoting coordinated industrialization and urbanization can the harm of carbon emissions to residents' health be reduced. Therefore, the "one-size-fits-all" policy model is not suitable for China's current situation. To address global "climate change" issues, China must act according to local conditions by applying mitigating (adaptive) measures in economically developed (less developed) regions. Simultaneously, the authorities must focus on the interaction and synergy between industrialization and urbanization. Unlabelled Image • The interplay among industrialization, urbanization, climate change, and health is investigated. • Carbon emissions have a long-term adverse impact on residents' health. • Increases in carbon emissions impair residents' health through the rise in temperature. • Highly industrialized and urbanized areas cause greater health risks. • China must apply mitigating measures in developed regions and adaptive measures in less developed areas. [ABSTRACT FROM AUTHOR]

This paper is a pioneering endeavour to investigate the determinants of environmental degradation in Australia through a comprehensive framework of EKC and STIRPAT. Specifically, the impacts of multiple factors of socio-economic development including economic growth, trade openness, industrialization, energy consumption on CO 2 emissions are analysed. Furthermore, the influences of financial development through different dimensions (financial efficiency, access and depth) in two subsectors (financial markets and institutions) and other proxies of financial development are focused over the period 1980–2014. Empirical results show short as well as long-run differences in the association among the variables. Short-term bidirectional causality prevails between economic growth, energy consumption, industrialization, and stock market development with carbon dioxide (CO 2) emissions. However, there is no significant evidence found on EKC. This is due to the long-run positive impact of financial development, energy consumption, and trade openness on CO 2 emissions. Interestingly, the industrialization process is found to does not affect CO2 emissions. Empirical findings provide insight into why the quality of the Australian environment is truncated with frequent and widespread bushfires and suggest policymakers to have selective and strict environmental-friendly strategies to fulfil a sustainable development goal. • Study analysis determinants of environmental degradation in Australia. • Economic growth, trade openness and energy consumption contribute to CO 2 emissions. • Industrialization process has no statistically significant impact on CO 2 emissions. • Financial efficiency, financial access and financial depth affect the CO 2 emissions. • Financial markets and institutions play a vital role in increasing CO 2 emissions. [ABSTRACT FROM AUTHOR]