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High-energy consumption and high-emission industries contribute a lot to economic development, but their carbon emissions are also huge. In order to achieve the dual-carbon target as early as possible, it is necessary to reduce the carbon emissions of high-energy consumption and high-emission industries. This paper selected five representative factors (population, per capita gross domestic product (GDP), energy intensity, energy structure and carbon emission coefficient) and adopted the logarithmic mean divisia index (LMDI) method to decompose the driving factors of carbon emissions. Therefore, this paper uses Tapio decoupling model to analyze the decoupling relationship between the two factors with the greatest impact on carbon emissions and carbon emissions. The results show that: (i) There is a good decoupling between high-energy consumption and high-emission industries and per capita GDP, and the impact of per capita GDP on carbon emissions will gradually decrease in the future; (ii) The decoupling relationship between carbon emissions and energy intensity is poor. For some industries, the reduction of energy intensity can help reduce carbon emissions. Finally, this paper puts forward some suggestions to promote carbon emission reduction. This paper provides theoretical support for studying how to reduce carbon emissions and formulate relevant emission reduction policies in the high-energy consumption and high-emission industries. [ABSTRACT FROM AUTHOR]

This paper constructs a unique dataset of clean energy and adopts static panel models and dynamic panel specifications to explore the correlation between clean energy and CO2 emissions. Furthermore, this paper employs the interaction term of pilot areas and pilot time as the proxy of emission trading policy to examine the effect of China's emission trading pilot on clean energy. Then, this paper conducts quasi-natural experiments on CO2 emissions. Our findings show a negative correlation between CO2 emissions and clean energy. We also find that China's emission trading pilot has a significant impact on promoting clean energy. In addition, empirical results affirm that emission trading market pilots can help decrease CO2 emissions. Finally, we put forwards relevant policy recommendations. [ABSTRACT FROM AUTHOR]

The carbon emission trading market (carbon market) is an important policy tool for China to achieve the goal of "carbon peak and carbon neutrality" through market mechanism. This paper uses panel data of 30 provinces in China from 2005 to 2019 to examine the emission reduction effect (ERE) of China's carbon market pilots using multi-period Difference-in-Differences (DID)method, and then analyzes the factors influencing ERE and the economic impact of carbon market. According to the Bacon decomposition and a series of robustness tests, the results reveal that China's carbon market pilots have significant ERE. Both the expansion of the carbon market scale and the improvement of market activity level can significantly boost the carbon market's ERE. Meanwhile, the establishment of carbon market has no negative impact on the economic growth. Therefore, we propose to accelerate the construction of the national carbon market, incorporating more industries in a systematic manner, expand the scale of the carbon market, steadily promote the innovation of carbon financial instruments, improve the activity of the carbon market, so as to promote the transformation of China's green and low-carbon economy and achieve the emission reduction target as scheduled. [ABSTRACT FROM AUTHOR]

The paper considers the causal relationship about CO2 emissions, traffic density and urbanization development in China's provinces by the quantile causality test The method can capture the structural breaks under different quantiles from the nonlinear perspective. The robust results don't find the causality relationship between traffic density and CO2 emissions. Urbanization will increase CO2 emission at the high quantile level while the impact of CO2 emissions on urbanization presents a symmetric relationship. The promoting effect of transportation on urbanization only occurs at the beginning of urbanization. It shows the environmental pollution is a key factor to the whole process of urbanization. With the advancement of urbanization, the increase of traffic line density has no significant impact on the urbanization process. The results can provide references for the government in the layout of local traffic lines and the improvement of urbanization. [ABSTRACT FROM AUTHOR]

Green port construction has a profound impact on China's international climate commitment to carbon neutrality by 2050. To examine the carbon emission reduction potential of 20 major ports in the Yangtze River Delta port cluster of China, this study takes the perspective of environmental efficiency and employs dynamic exogenous variable DEA in efficiency evaluation. The results show the increasing environmental efficiency of the ports in the Yangtze River Delta, rising from 0.5116 in 2013 to 0.7276 in 2019. Also, there are significant spatial differences in efficiency. After considering exogenous variable, the average efficiency has increased from 0.5537 to 0.6276, indicating that regional green development is a critical factor in port environmental efficiency evaluation. Finally, the overall efficiency of input and output have risen, the slackness of carbon emission shows a trend of decreasing, and there is great potential for reducing carbon emissions from the perspective of port environmental efficiency. The previous studies paid less attention to dynamic efficiency, exogenous variables, and carbon emission. Therefore, this paper is the first comprehensive examination on the carbon emission reduction potential of China's Yangtze River Delta port cluster from the perspective of dynamic environmental efficiency. [ABSTRACT FROM AUTHOR]

China has proposed ambitious goals of carbon peak and carbon neutrality, and will pay more attention to the relationship between economic development and carbon emissions. It's significant to assess the current environmental decoupling and prospect the future conditions in China. This article studies the decoupling status and influencing factors in Chinese provinces from 1996 to 2018 through Tapio decoupling index and decomposition model. The results show that most provinces are currently in a weak decoupling state. The growth of per capita GDP and population will affect the process of strong decoupling, while the optimization of energy intensity, energy structure and industrial structure will promote the realization of strong decoupling. Moreover, this paper prospects the decoupling scenarios of Chinese provinces from 2019 to 2035 and finds that all provinces will achieve strong decoupling before 2040, 2035 and 2030 under different carbon emissions scenarios respectively. To achieve the strong decoupling of economic output and carbon emissions as soon as possible, the government must improve energy efficiency, use renewable energy in large quantities, and promote the industrial transformation and upgrading. [ABSTRACT FROM AUTHOR]

This paper takes Jiangsu as an example to measure the carbon emissions from the electric power industry from 2002 to 2017, builds an extended STIRPAT model to quantify its driving factors, and uses the Monte Carlo method to simulate the evolution of carbon emissions in multiple scenarios from 2018 to 2030. The results show that: (1)Population scale, urbanization level, GDP per capita, industrial added value, and electricity consumption intensity promote the increase of carbon emissions in the electric power industry. (2)Trade openness and the transmission level of other provinces play a role in reducing carbon emissions. (3)Under the baseline scenario and the green development scenario, the carbon emissions of the electric power industry have shown a continuous growth trend, but the growth rate of carbon emissions has slowed down significantly under the green development scenario. [ABSTRACT FROM AUTHOR]

Consolidating the results of poverty alleviation and achieving carbon neutrality are serious challenges for global sustainable development, and it is essential to explore the relationship between these goals, and then offer scientific responses. Based on the panel data of 30 provinces in China from 2010 to 2019, this paper conducted the 2SLS model by compromising the merits of the Regression Discontinuity principle with the STIRPAT model to study the interaction between poverty alleviation and carbon reduction. The study found that: (1) the implementation of poverty alleviation aggravates the problem of carbon emissions, and the main mechanism is that poverty alleviation promotes consumption and production by increasing the wealth of farmers, thereby increasing carbon emissions. (2) Carbon reduction weakens the achievement of poverty alleviation significantly, but the mitigation effect presents an "inverted U"-shaped curve, which first increases and then wanes. (3) Farmers' income and the development of rural transportation play a role in acting on the negative effects of carbon reduction. By integrating poverty theory and energy management, this article reveals the complex relationship between two important policies in China and offers relevant policy recommendations, which will not only promote the advancement of rural revitalization but also promote global sustainable development. [ABSTRACT FROM AUTHOR]

Based on the panel data of 277 cities between 2003 and 2017 and a unique city-level dataset of green patent applications, this study employs the difference-in-differences (DID) method to evaluate the effect of China's carbon emission trading scheme (ETS) pilots on urban green innovation. The findings indicate that China's ETS pilots have a positive impact on urban green innovation, and that impact is more significant for municipalities than for prefecture-level cities. Furthermore, the impact on different categories of urban green innovation is heterogeneous. More specifically, China's ETS pilots have significantly spurred urban green innovation that is closely related to energy conservation and emission reduction, including alternative energy production, transportation, energy conservation and so forth. Moreover, the facilitating effect of China's ETS pilots on urban green innovation suffers from a lagging effect, which began to show a significant positive effect in 2016. Overall, this paper identifies the effect of China's ETS pilots on urban green innovation, and suggests that the government should consider the heterogeneity of urban green innovation when designing national ETS policies. [ABSTRACT FROM AUTHOR]

The aggravation of the greenhouse gas emission-resulted climate change poses a significant challenge to the world. In response to the urgent need for significantly more sustainable societies, this paper develops a protocol for the optimal design of residential balcony based on environmental benefits in the case study of China's hot summer and cold winter area. The study utilized ROI and AY as environmental performance indicators for decision-making scheme investment and EnergyPlus to simulate the A/C energy-saving potential of considered balcony design schemes. The literature and experiment validation results show that EnergyPlus with Shadow Algorithm is reliable for studying the energy consumption of residence with balcony. The added embodied environmental impact of the different design schemes was estimated, and the idea of life cycle assessment was used for quantitative evaluation of the carbon emissions of the balcony. The results show the depth of 1.2 m suits the south/north-facing balcony, and a big window-wall ratio of 0.6 was the most beneficial in the environmental performance of the balcony investment. When the balcony is attached to different rooms, the environmental profitability is influenced by the factors such as occupancy behaviour and balcony environmental investment. The attached room type of residence on a case-by-case basis should be analyzed. [ABSTRACT FROM AUTHOR]

Coal-fired power industry is under enormous pressure to accomplish carbon emission reduction targets. This paper proposes a bi-level multi-objective model for co-firing biomass with coal under carbon cap-and-trade regulation which considers a leader-follower Stackelberg game between the authority and the coal-fired power plants. The upper level regards social welfare maximization and allocation satisfaction maximization as its multiple objectives, while the lower level attempts to maximize the profits of each coal-fired power plant. The inherent uncertainty prompts the motivation for employing fuzzy set theory to characterize the uncertain parameters and determine their exact values. A case study from Shandong Province, China is provided to demonstrate the practicality and efficiency of the optimization model. ε -constraint method and interactive algorithm are used to solve the model, and furthermore the solutions associated with different free carbon emission quota levels and minimal allocation satisfactions have been generated to examine the influences. Based on the analysis and discussion, the methodology can meet the carbon emission reduction goals and transit to a lower-carbon power generation. It also assists the decision makers to develop desired quota allocation strategy in accordance with their attitudes and actual conditions. [ABSTRACT FROM AUTHOR]

This paper uses a sample of 1,867 firms that participate in the "Top-10,000 Energy- Consuming Enterprises Program" in China and aims to identify strategic traders in its pilot emissions trading scheme. Firms included in the ETS can exert their market power and manipulate allowance prices to achieve low compliance costs, which will consequently influence the effectiveness of this platform. This is of great importance to regulators or designers of this system in identifying these strategic traders and understanding their impact. We follow the basic principle proposed by Godal (2005) and develop a simple and implementable empirical procedure to study firm-level data from seven pilot programs in China. The results show that strategic traders exist with clear regional and sectoral differences. As a consequence of strategic trading by these firms, the overall volume of trading falls remarkably, with a clear increase in total compliance costs. [ABSTRACT FROM AUTHOR]

As a developing country and one of the world's largest carbon emitter, China has been facing significant pressure to reduce fossil fuel use while maintaining sustainable socio-economic growth. This paper proposes a multi-objective optimization method for a joint wind thermal generation system to reduce carbon emissions and increase wind power utilization while guaranteeing power supply demand risk and profitability. Wind and coal thermal power plant generation sources are scheduled into the joint system and connected to the same grid. The thermal power bears the basic load and the wind power seeks more chances to connect to the main grid. A model transformation method is applied and Lingo 13.0 software is used to solve the model. A case study from Ningxia, China is presented to demonstrate the practicality and efficiency of the optimization mode, the results from which showed that the proposed model was able to improve the emissions performance and increase the wind energy utilization, while guaranteeing power supply reliability and achieve maximum profitability, which could assist authorities when developing power generation plans. The results under different scenarios showed that a minimum and maximum wind power utilization rate existed in the joint wind-thermal power generation system, and that units with higher conversion efficiencies and lower emissions parameters were more reasonable when seeking to increase wind power utilization and reduce carbon emissions. The system generation profitability was found to increase for joint systems connected to the main grid when wind power utilization was increased. Lastly, several management proposals are given in this paper to ensure better joint system application. [ABSTRACT FROM AUTHOR]

Identifying the carbon emission characteristics, driving factors, and decoupling status of the industrial subsectors is important for developing effective policy measures. This allows for implementing industrial emission reduction that, eventually, decouple carbon emission and economic growth. Such an analysis is especially important for the case of China on its way towards sustainable development and increasing global interrelationships. However, the literature still lacks comprehensive analysis, especially, at the industry level. This study uses the Logarithmic Mean Divisia Index and decoupling indicator to analyze how different factors contribute to CO2 emissions in 28 industries in China during 2002–2017. The results reveal that the growth of industrial CO2 emissions has been positive but decreasing. The highest CO2 emission change is observed for production and supply of electric and heat power, processing of petroleum, coking, and nuclear fuel, and smelting and pressing of metals. These sectors also show high carbon intensity levels. The economic output (scale) effect and population effect comprise the two major factors promoting the CO2 emission. The energy intensity effect is the key inhibiting factor of the industrial energy-related CO2 emission in China. The suppressive effects of energy and industrial structure have been continuously increasing. The economic growth and CO2 emission has been gradually decoupling in the case of the 28 sectors analyzed. Manufacture of cloths, leather, fur, feather, and related products as well as production and supply of gas exhibit a relatively stable strong decoupling. Based on the decoupling analysis, this study shows that energy intensity has induced the decoupling, whereas the opposite effect has occurred due to economic growth, and the other factors showed little effect on CO2 emission decoupling. [ABSTRACT FROM AUTHOR]

Based on the instrumental variable method and the panel data of 283 prefecture-level cities in China from 2004 to 2016, we explore the relationship between carbon emission, air pollution, and total factor productivity (TFP). The results show that: (1) Both carbon emission-induced and air pollution-induced environmental regulations positively promote TFP. For every 1% increase in the two indicators of the intensity of environmental regulation, carbon emission, and air pollution, TFP will increase by 1.7150 percentage points and 0.6366 percentage points respectively. (2) Carbon emission-induced and air pollution-induced environmental regulation have similar coefficients on TFP, indicating that the effects of the two are synergistic. Carbon emission has a greater impact on TFP, so enhancing environmental regulation on carbon emission can better promote the improvement of TFP. (3) Financial scale and government intervention have a significant intermediary effect between environmental regulation in both aspects and TFP. [ABSTRACT FROM AUTHOR]

The rapid growth of foreign direct investment (FDI) has had a significant impact on rapid economic development and environmental pollution in China. Nonetheless, the underlying mechanism and empirical evidence of FDI impact on carbon emission efficiency have not been systematically explored. Therefore, this study investigates the impact of FDI on carbon emission efficiency via energy intensity, as well as the moderating role of the Low-Carbon City Pilot Policy (LCCP) in the process. We found that: (1) During the study sample period, the average carbon emission efficiency tends to rise, however, there remains a gap between the optimal carbon emission efficiency; (2) FDI is one of the key factors that inhibit the improvement of carbon emission efficiency, with a non-linear relationship between them; (3) FDI indirectly suppresses the improvement of carbon emission efficiency by promoting energy intensity. Nevertheless, the implementation of LCCP has a positive effect on carbon emission efficiency; (4) The implementation of LCCP has improved the negative impact of FDI on carbon emission efficiency, nonetheless, it cannot significantly influence the process that FDI affects carbon emission efficiency through energy intensity. Thus, we propose improvement measures from three aspects, i.e., increasing the introduction of foreign capital, adjusting the energy consumption structure, and expanding the scope of low-carbon cities. [ABSTRACT FROM AUTHOR]

In the last 20 years, China's steel production has proliferated, leading to increased environmental damage by releasing 574,000 tons of sulfur dioxide (SO2), 1,114,000 tons of nitrogen oxide (NOx), and 897,000 tons of particulate matter (PM) in 2020; therefore, the country is now struggling to reduce carbon emissions and tackle climate change because of the conflicting demands of economic growth and environmental protection. Given the global emphasis on decarbonization and sustainable production, China has prioritized achieving peak carbon emissions of 30% by 2030 and carbon neutrality by 2060. Likewise, China's steel industry is progressing toward attaining the maximum carbon dioxide (CO2) emissions by 2025. This study reveals that despite a 321 Mt increase in global energy-related CO2 emissions in 2022, CO2 emissions in China experienced a decline of 230 Mt during the same period. Notwithstanding enacting several pertinent statutes and directives, China's iron and steel sector has not advanced substantially. [ABSTRACT FROM AUTHOR]

Identifying the differentiated effects of different environmental regulations is the basis for promoting China's zero carbon emissions and carbon neutrality. We used Chinese provincial panel data from 2003 to 2017 to empirically test the impact of different environmental regulations on carbon neutrality through spatial measurement models. The highlights of the study are as follows: (1) Environmental regulations exert significant impact on carbon emissions, but different types of environmental regulations exert significantly different effect on carbon emissions. Public participation environmental regulation has a control effect on regional carbon emissions, while command-based and market-based environmental regulations had no significant effect on regional carbon neutrality. (2) The heterogeneity of the impact of different types of environmental regulations on carbon emissions can also be identified from the regional impacts heterogeneity and lags impact heterogeneity. (3) The combined mandatory and market-based environmental regulations and the combined mandatory and public-participatory environmental regulations significantly inhibited regional carbon neutrality. [ABSTRACT FROM AUTHOR]

A scientific assessment of the synergistic effect of the low-carbon city pilot policy in reducing air pollution and carbon emissions is needed to promote carbon peak and carbon neutrality. This study applied the Spatial Durbin Model-Difference in Difference technique to investigate the synergistic effect of air pollution and carbon emission reduction through the implementation of the low-carbon city pilot policy. The main results are as follows. (1) A spatial phenomenon was observed, in which there was a coexistence of urban carbon emissions and air pollution agglomerations. The spatial characteristics of the "symbiotic" carbon emissions and air pollution agglomerations were revealed. (2) The low-carbon city policy significantly reduced CO2, SO2, and PM2.5 concentrations, and the effect of the "co-governance" of air pollution and carbon emission reduction was obvious. (3) There was a clear regional heterogeneity in the synergistic effect of air pollution and carbon emission reduction in low-carbon cities. A stronger incentive effect was apparent in central and western cities, resource-based cities, and key environmental protection cities. (4) To achieve a synergistic governance "sharing" situation, the transmission mechanism of the low-carbon city pilot policy was the reduction of total energy consumption, the promotion of industrial restructuring, the optimization of the factor endowment structure, and the continuous improvement of the urban transport structure and green innovation. Our results not only help advance the research on synergistic reduction of air pollution and carbon emissions, but also can be of interest to low-carbon city policy makers in China. [ABSTRACT FROM AUTHOR]

This research examines the factor of causality between the variables of economic growth and carbon emissions in China, by conducting full, and sub-sample Granger causality tests for the period of 1965 to 2019. The full-sample Granger causality test is not considered to be authentic, and is rather unstable, as indicated by the parameter stability tests. Therefore, we consider the time variation using a causality test, and the results indicate that the causality exists from the Gross Domestic Product (GDP) growth to the Carbon Dioxide (CO2) emissions. This development essentially suggests that economic growth is critical for China's environment. It also implies that carbon emissions are mainly determined by the increase in economic growth, at some specific period in time. Thus, in this regard, the use of renewable energy sources should be encouraged by policymakers, in order to deal with rise in the energy demand, and promote industrial upgrading, so as to slow down the rate degradation that the environment have been experiencing. However, our empirical results indicate that CO2 emissions are not the Granger reason to GDP. In this case, the government can formulate more conservative reduction policies that pertain to carbon emissions, and will therefore, not impede the economic growth. [ABSTRACT FROM AUTHOR]

Introduction: Although forecasting electric vehicles' growth in China was frequently reported in the literature, predicting electric vehicles market penetration as well as corresponding energy saving and carbon dioxide mitigation potential in a more suitable method is not well understood. Methods: This study chose the double species model to predict electric vehicles' growth trajectory under mutually competitive conditions between electric vehicles and internal combustion engine vehicles. For comparison, it set two scenarios: with 200 and 300 vehicles per thousand persons at 2050. To give details on energy saving and carbon dioxide mitigation potential induced by electric vehicles' market penetration, it further divided electric vehicles into five subgroups and internal combustion engine vehicles into seven subgroups, therein forming respective measurement formulas. Results: This paper solved the double species model and thus got its analytical formula. Then it employed the analytical formula to conduct an empirical study on electric vehicles market penetration in China from year 2010 to 2050. Under scenario 300, electric vehicles growth trajectory will emerge a quick growth stage during 2021–2035, thereafter keeping near invariant till 2050. Meanwhile, current internal combustion engine vehicles' quick growth will continue up to 2027, then holding constant during 2028–2040, afterwards following a 10-year slowdown period. Scenario 200 has similar features, but a 2-year delay for electric vehicles and a 5-year lead time for internal combustion engine vehicles were found. On average, scenario 300 will save 114.4 Mt oil and 111.5 Mt carbon dioxide emissions, and scenario 200 will save 77.1 Mt oil and 73.4 Mt carbon dioxide emissions each year. Beyond 2032, annual 50.0% of road transport consumed oil and 18.6% of carbon dioxide emissions from this sector will be saved under scenario 300. Discussion: Compared with scenario 200, scenario 300 was more suitable to predict electric vehicle market penetration in China. In the short-term electric vehicle penetration only brings about trivial effects, while in the long-term it will contribute a lot to both energy security and carbon dioxide mitigation. The contribution of this article provided a more suitable methodology for predicting electric vehicle market penetration, simulated two coupled trajectories of electric vehicles and internal combustion engine vehicles, and discussed relative energy-saving and climate effects from 2010 to 2050. [ABSTRACT FROM AUTHOR]

Introduction: Although forecasting electric vehicles' growth in China was frequently reported in the literature, predicting electric vehicles market penetration as well as corresponding energy saving and carbon dioxide mitigation potential in a more suitable method is not well understood. Methods: This study chose the double species model to predict electric vehicles' growth trajectory under mutually competitive conditions between electric vehicles and internal combustion engine vehicles. For comparison, it set two scenarios: with 200 and 300 vehicles per thousand persons at 2050. To give details on energy saving and carbon dioxide mitigation potential induced by electric vehicles' market penetration, it further divided electric vehicles into five subgroups and internal combustion engine vehicles into seven subgroups, therein forming respective measurement formulas. Results: This paper solved the double species model and thus got its analytical formula. Then it employed the analytical formula to conduct an empirical study on electric vehicles market penetration in China from year 2010 to 2050. Under scenario 300, electric vehicles growth trajectory will emerge a quick growth stage during 2021-2035, thereafter keeping near invariant till 2050. Meanwhile, current internal combustion engine vehicles' quick growth will continue up to 2027, then holding constant during 2028-2040, afterwards following a 10-year slowdown period. Scenario 200 has similar features, but a 2-year delay for electric vehicles and a 5-year lead time for internal combustion engine vehicles were found. On average, scenario 300 will save 114.4 Mt oil and 111.5 Mt carbon dioxide emissions, and scenario 200 will save 77.1 Mt oil and 73.4 Mt carbon dioxide emissions each year. Beyond 2032, annual 50.0% of road transport consumed oil and 18.6% of carbon dioxide emissions from this sector will be saved under scenario 300. Discussion: Compared with scenario 200, scenario 300 was more suitable to predict electric vehicle market penetration in China. In the short-term electric vehicle penetration only brings about trivial effects, while in the long-term it will contribute a lot to both energy security and carbon dioxide mitigation. The contribution of this article provided a more suitable methodology for predicting electric vehicle market penetration, simulated two coupled trajectories of electric vehicles and internal combustion engine vehicles, and discussed relative energy-saving and climate effects from 2010 to 2050. [ABSTRACT FROM AUTHOR]

Environmental degradation has been recognized as a global issue due to high energy consumption and economic growth. This situation needs researchers to focus on, thereby, the current article examined the impact of renewable energy production (REP), energy import, renewable energy consumption (REC), gross domestic product (GDP), inflation, and foreign direct investment (FDI) on the carbon dioxide (CO2) emission in China. The study considered secondary data and extracted it from the World Bank database covering the period 1981 to 2018. The current article has examined the stationarity of the constructs using Augmented Dickey-Fuller tests and investigated the association among constructs using the quantile autoregressive distributed lag (QARDL) model. The data revealed that REP, energy import, and REC, had a significant and negative linkage with CO2 emission in China. In contrast, GDP, inflation, and FDI are linked with CO2 emission in a positive manner. The article also guided the policymakers regarding the policy development related to reducing carbon emissions using renewable energy production and consumption. [ABSTRACT FROM AUTHOR]

The dynamic stochastic effects regressions on population, affluence, and technology model used in this study reveals the nonlinear effects of urbanization routes on CO2 emissions in China, India, Indonesia, the United States, and Brazil during 1970–2020, using dynamic seemingly unrelated regression, dynamic ordinary least square, and fully modified ordinary least square techniques. The empirical analysis shows that urbanization and the proportion of small cities contribute significantly to CO2 emissions, while the square of urbanization and the square of the proportion of small cities significantly reduce CO2 emissions, thus supporting the inverted U-shaped relationship for the selected countries. However, the effect of the proportion of large cities significantly reduces CO2 emissions, while the square of the proportion of large cities significantly promotes CO2 emissions, supporting a U-shaped relationship for specific countries. Gross domestic product, industrial development, and transport infrastructure contribute significantly to carbon emissions, while renewable energy generation significantly reduces carbon emissions. The country-level augmented mean group estimator in the analysis supports an inverted U-shaped relationship between urbanization and carbon emissions and a U-shaped relationship between the proportion of large cities and carbon emissions in all selected countries. There is also an inverted U-shaped relationship between the proportion of small cities and carbon emissions in China, India, Indonesia, and Brazil. The causality test results acknowledge bidirectional causality between urbanization and carbon dioxide emissions; between urbanization squared and carbon dioxide emissions; between the proportion of the largest cities and carbon dioxide emissions, and between renewable energy and carbon dioxide emissions. This study recommends renewable energy options, green urban infrastructure, and digital technologies to improve the environmental quality of urban areas. [ABSTRACT FROM AUTHOR]

Cement production reportedly accounts for the largest global materials flow, thus achieving global environmental sustainability through responsible consumption and production is central to the sustainable development scenario. But even that China, the world's largest carbon emitter and largest cement producer, is under-studied. Thus, the current study employed the nonlinear ARDL and frequency domain causality methods to unearth the contributory or mitigating role of energy sources and economic progress in China's cement carbon emission (CCE) over the period 1971-2020. Overall, the study establishes long-run equilibrium relationship between the study variables of interest Subsequently, the baseline regression suggests that a positive shift in economic growth, energy from fossil fuel and primary energy consumption all increase emissions while a negative shift does not have a significant effect on emissions. Moreover, a positive (negative) shift in renewable energy decreases (increases) emissions in both the short and long-run. The result of the Frequency Domain causality analysis resonates with the results of NARDL regression. As a policy, this study infers energy development and economic-related measures are strategically important in achieving sustainable cement production and consumption. [ABSTRACT FROM AUTHOR]

Using panel data from 30 provinces in China from 1995 to 2017, this study explores the impact of natural resource rent, transportation infrastructure, innovation, financial development, green investment and energy investment on carbon emission and its role in achieving the sustainable development goals. In order to obtain long-term and short-term estimates, the auto-regression distribution lag model (ARDL) is used in this study. The results confirm that natural resource rent, transportation infrastructure, innovation, energy investment and carbon emission are significantly positively correlated in long-term and short-term. Financial development and carbon emission are not significant in short term, but in the long term, financial development will contribute to the rise of carbon emissions. Green investment will increase short-run carbon emissions, whereas it really can control carbon emissions, which is different from other studies. This research proposes to improve the level of innovation and reduce carbon emission in other fields through technological innovation, increase green investment and renewable energy investment and combine with financial development to invest more funds in low carbon environmental production industries and to build an environment friendly system. [ABSTRACT FROM AUTHOR]

China is the world's largest energy consumer and carbon emitter, but despite unbalanced growth among the eastern, central, and western regions, local financial expenditure on energy conservation and environmental protection has increased from 255.1 billion yuan in 2011 to 582.5 billion yuan in 2018. This research thus introduces financial expenditure like a new input into a dynamic meta-frontier non-radial directional distance function to evaluate China's energy and carbon emission efficiency over that period of time. Different from previous studies, after considering financial expenditure we find that most provinces have narrowed their gap with the benchmark frontier, reflecting that increasing financial expenditure does help improve energy and carbon emission efficiency. The results highlight that most provinces should increase their financial expenditure on energy conservation and environmental protection, especially in the central and western regions, so as to narrow their technology gap with the eastern region. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions have brought serious negative impacts on human beings and organisms, so energy saving and emission reduction have been recognized by more and more people. Traditional Milk-run model seldom considers the factors of energy saving and emission reduction, and its routing optimization cannot meet the current needs of low-carbon economic development. On the basis of traditional Vehicle Routing Problem research, considering the fixed cost, time penalty cost, energy consumption cost and carbon emission cost of vehicles, the Milk-run model of distribution routing considering carbon emissions under time window constraints is studied. Then the improved ant colony algorithm is used to solve the constructed model. Finally, the order and related data of a company are used to verify the validity and practicality of the model and algorithm. Compared to the scanning method, the results show that not only the total journey distance has been shortened but also the total cost and cost of carbon emissions have been reduced. The optimization of distribution routing considering carbon emissions can reduce the distribution cost of logistics enterprises, respond to the call of low-carbon development in China and help to achieve a win-win situation of social and economic benefits. [ABSTRACT FROM AUTHOR]