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Due to the high density of users hosted everyday, public buildings are important producers of waste and emissions of greenhouse gases (GHGs). Public restrooms play an underrated role in waste generation and GHG emissions, especially if paper towels are used as the hand-drying method. The choice of the hand-drying method (i.e., paper towels vs. electrical hand dryers) also affects the economic balance of a public institution, involving costs for the purchase of hand-drying materials/apparatuses, energy and waste disposal. The present paper aims at evaluating the economic and environmental impact of the introduction of electrical hand dryers (alternative scenario) in place of paper towels (reference scenario) in a public building. The paper presents a solid methodology, based on a numerical experiment approach, to identify a decision criterion for establishing the economical convenience of adopting the alternative scenario in public restrooms. Key factors affecting the choice between the proposed alternatives are presented and discussed in a dedicated sensitivity analysis. From the environmental point of view, this study evaluates the impact of each scenario in terms of GHG emissions, related to multiple waste treatment options and different electric grid mixes. Based on the experimental assumptions, the method allowed concluding that the alternative scenario becomes economically convenient when the number of daily usages (N) is > 57 ± 4. The environmental convenience of the alternative scenario is visible even at N < 10. The method here described can be successfully used to support strategic decisions for cost optimization and environmental mitigation in institutional buildings. [ABSTRACT FROM AUTHOR]

Energy shortage and excessive carbon emissions have become the main constraints to the sustainable development of China's logistics industry. Improving the efficiency of the logistics industry is crucial to promoting regional ecological environment protection and sustainable development of the logistics industry. In this paper, the efficiency of China's logistics industry in 2013–2019 is evaluated by using the non-oriented EBM model considering the unexpected output, and then the influencing factors of the efficiency of the logistics industry in the central region are analyzed by using the panel Tobit model. The results show that the logistics industry in the central region is at a low efficiency level. Factors, such as the level of economic development, industrial structure and technical level have a significant positive impact on the efficiency of the logistics industry in the central region, while factors such as government support and logistics infrastructure have a significant negative impact on the efficiency of the logistics industry in the central region. Finally, the paper puts forward some targeted recommendations for the sustainable development of the logistics industry in the central region. [ABSTRACT FROM AUTHOR]

Trying to understand how the interdependence relationship among the sectors of a given economy and its impacts on the environment is fundamental to the identification of sectors that are more polluting and those that are considered key in the sense of being less polluting. In order to describe this relationship, this work has as general objective to measure the level of CO2 emission from the level of production in function of the consumption of electric energy in the state of Mato Grosso do Sul. In order to meet the general objective, from the state energy balance and the input–output matrix of 2010, a hybrid input–output matrix was derived. Thus, it was possible to identify that the service sector, although is the engine of the state GDP, represents only 16% of the emissions, agriculture and cattle raising 6% and industry 78%. The main sectors in CO2 emission are rubber and plastic articles and the pulp and paper production sector. Considering the estimates of growth of the state, the concern with the environment is emphasized as the driving sectors of the expansion being precisely those that emit more CO2. [ABSTRACT FROM AUTHOR]

Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

Food consumption has resulted in great carbon emissions in recent years. China has been facing the new mitigation challenge of carbon emissions with its emerging middle-income groups, especially in urban areas. This paper analyzes and predicts carbon emissions from food consumption (CEFC) of middle-income groups in the Yangtze River Economic Belt (YREB), which has a higher emerging middle-income group and the highest economic corridor in China. Few studies address CEFC analysis from middle-income groups perspective; thus, this paper calculates urban–rural CEFC of middle-income groups spanning 2010–2018 and predicts them in 2025, 2030 and 2035 using the extended IPAT model. Results are as follows: (1) YREB's urban–rural CEFC of middle-income groups show an upward trend and present a spatial pattern of "low–high–low–high" from the western region to the eastern region. Urban CEFC of middle-income groups are significantly higher than that of rural areas; (2) rural CEFC of middle-income groups in the YREB will first increase in 2025 and then decrease in 2030 and 2035. The growing trend of urban CEFC of middle-income groups will show a significant downward from 2025 to 2035. The growing proportion of urban CEFC of middle-income groups will exhibit an objective growth in 2035. Understanding the changing trend of CEFC of middle-income groups provides governments with differentiated and forward-looking suggestions toward coordinating middle-income groups' expansion and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

An extended STIRPAT model was constructed to explore the impact of green consumption behaviors on carbon emission. Based on the panel data of 30 provinces in China from 2005 to 2019, this paper analyzed the effect of green consumption behaviors, regional population size, economic development level and technological level on carbon emission, and then forecasted the carbon emission in eastern, central and western China from 2020 to 2035. The results demonstrate that carbon emission increases with the expansion of population size; green consumption behaviors have a significant moderating effect on carbon emission and alleviate the pressure of population growth on carbon emission; instead of following the environmental Kuznets curve, the trend of carbon emission shows an inverted "N" curve with economic growth; There is a positive correlation between technological progress and carbon emission; the increase in the level of consumers' expenditure and the ratio of the secondary industry output value over the total GDP lead to an increase in carbon emission, while the improvement of the urbanization level reduces carbon emission. Policy implications and prospects are also discussed. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions has become an urgent task in China. As the category with the largest economic and emissions contribution to the industry, the carbon emissions research of the manufacturing industry is particularly important. This paper uses the LMDI method to decompose manufacturing carbon emissions into seven influencing factors (i.e., population, urbanization, economic development, investment share, energy intensity, energy structure and emission intensity), in order to explore the factors driving manufacturing carbon emissions during 2003–2018. Then, the paper analyzes the decoupling relationship between manufacturing investment and carbon emissions in 30 provinces. Finally, three scenarios are developed to project future manufacturing emissions at the provincial level up to 2035, and whether manufacturing emissions in 30 provinces can realize peak is discussed. The paper results in three main findings. First, we find that energy intensity played the most important role in decreasing the manufacturing emissions during the whole study period, while the economic development and investment share were the main effect promoting manufacturing carbon emissions. Second, China experienced a process from weak decoupling to strong decoupling between manufacturing invest and emissions. Third, China's manufacturing carbon emissions can only achieve the carbon peaking target in 2030 under the High scenario, and 7 provinces cannot reach the peak before 2035 under the three scenarios. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

Global climate changes evoked by carbon emissions have stimulated genuine interest in sustainable technology apropos the marine transportation sector. Offshore charging infrastructure for electric vessels is one of the focal areas for sustainable marine transportation. Pervasive deployment of electric vehicles is restrained by travel range and battery energy capacity. This paper brings to bear the exigency of offshore floating charging stations (FCSs) that charge/recharge electric vessels at sea. This work underscores the feasibility of implementation and energy management of reliable offshore recharging stations with renewable energy sources, energy storage systems, and backup energy sources. A realistic study was performed at a North Sea offshore location for an appraisal of the viability and operational profile of an FCS. A reconfigurable energy management strategy was developed to fulfill real-time energy demands with balanced energy flows, ensuring minimal dependency on backup energy sources. The validation results revealed that the time duration of the FCS's need for a backup energy source was reduced by 96%, and the energy consumed from the backup energy source showed a 97% decrease. This investigation laid the groundwork for systematic follow-on studies that ratify sustainable electrified transportation in the maritime sector. The authors recommend further research in the following areas: vessel traffic analysis at dispersed offshore locations, FCS siting, and marine spatial planning for FCS implementation. [ABSTRACT FROM AUTHOR]

This paper employs the panel nonlinear autoregressive distributed lag model to investigate the asymmetric effects of environmental taxes on CO2 emissions embodied in domestic final demand (CDFD) in 23 developing economies. The results indicate that a reduction in environmental tax has a more adverse effect on CDFD than an increase in tax, implying that environmental taxes alone may not be sufficient to reduce CO2 emissions, especially in the context of rapid economic growth. Additionally, the study finds that fluctuations in GDP and population growth are associated with changes in CDFD. The findings further reveal that environmental tax has a positive association with CDFD, which suggests that to achieve emission reduction targets, policymakers need to consider other measures such as incentives for clean technology and regulations on high-emission industries. Furthermore, the robustness test results suggest that technological innovation is significantly linked to a decrease in CO2 emissions embodied in domestic final demand and greenhouse gas (GHG) emissions, while trade openness is positively associated with CDFD but negatively correlated with GHG emissions. This research provides crucial implications for policymakers on the effectiveness of environmental taxes and the need for supplementary measures to decrease CO2 emissions in developing economies. [ABSTRACT FROM AUTHOR]

To respond to the goal of "carbon peaking and carbon neutrality," reducing carbon emissions in the construction industry is urgent and necessary. A sound profit allocation based on carbon emission reduction is essential to promote low-carbon initiatives implementation by construction supply chain enterprises. In this paper, considering the potential impact of an effective emission reduction scheme (ETS), the Stackelberg game models are established to explore the carbon emission reduction decisions and profit allocation mechanism under decentralized, collaborative and centralized decision-making scenarios between developers and contractors. By conducting a comparative analysis, we obtained insights into the level of enterprises' carbon emission reduction effort, the profit allocation proportion and the impact of ETS. The main findings can be summarized as follows. (1) The proportion of carbon emission reduction profit allocation in the collaborative scenario is higher than that in the decentralized one. (2) For contractors, carbon emission reduction efforts are the highest in the centralized scenario, followed by the collaborative one. For developers, the carbon emission reduction effort is highest in the centralized scenario, but is followed by the decentralized one. When the carbon emission reduction effectiveness of the contractor is greater than a certain level (about 0.52), the carbon emission reduction volume in the collaborative scenario is larger than that in the decentralized scenario. (3) Total profits are most sensitive to carbon trading prices in the centralized scenario, followed by the collaborative scenario. This research provides valuable reference for the government and construction enterprises to promote carbon emission reduction initiatives and low-carbon development in the construction sector. [ABSTRACT FROM AUTHOR]

The digital economy has played a vital role in changing economic and social development patterns and has had a multifaceted impact on carbon neutrality. This paper strives to contribute to the existing research by analyzing the relationship between the digital economy and electricity consumption intensity and providing a comprehensive understanding of the mechanisms that influence the digital economy and energy consumption, particularly focusing on electricity consumption intensity through the construction of a theoretical model. To fulfill this objective, this study introduces the development level of the digital economy into the production function of representative power enterprise, constructs a partial theoretical equilibrium analysis framework, calculates provincial digital economy development indices for Chinese provinces from 2013–2021 using the CRITIC method, and examines the impact of the digital economy on power consumption intensity. The results show that the digital economy can reduce the intensity of power consumption. A unit standard deviation increase in the digital economy development level reduces power consumption intensity by 0.1008 standard deviations. The study also conducts a mechanism analysis with economic growth as the mediating variable, which shows that the digital economy promotes economic growth and reduces electricity consumption intensity. The moderating effect of the digital economy on power consumption is further examined using local government fiscal pressure as the moderating variable. The results show that the impact of the digital economy on reducing power consumption intensity decreases with the increase of government fiscal pressure. This study not only contributes to practical applications but also enhances our comprehension of the interplay between the digital economy and power consumption. On the one hand, the development of the digital economy can reduce power consumption, thus reducing carbon emissions and achieving low-carbon growth. On the other hand, central governments can promote the development of the digital economy by reducing the fiscal pressure on local governments through transfer payments. [ABSTRACT FROM AUTHOR]

Health and the environment are complex components of the countries, influenced by several factors, especially transport, and economics. Thus, this paper assesses the role of transportation and economic complexity in the environment and public health for the Organization for Economic Co-operation Development (OECD) countries from 2001 to 2020. This study also focuses on the relationship between transport and economic complexity with environmental and healthcare expenditures. Precisely, transport and economic activities stimulate healthcare expenditures through multiple channels. The current study employs the STIRPAT model to investigate the association with transportation, economic complexity, transport–carbon intensity, and healthcare expenditure. Besides, the current research confirms the plausible cross-sectional dependency across countries, and it adopts a second-generation technique. Analytical findings suggest that transportation-carbon intensity is positively and significantly associated with healthcare expenditures. Healthcare and transport–household expenditures increase transport–carbon intensity (TCI) by 75% and 45%, respectively, in the long run. In the contrast, TCI and transport–household expenditures have also a remarkable impact on healthcare expenditures and are estimated approximately 95% in the long run. Moreover, economic growth also upsurges TCI and healthcare expenditures through multiple economic activities. Besides, transport–household expenditures (THE) drastically impact transport–carbon intensity and healthcare expenditures (HEX) through passenger traffic (PTF). Diagnostic upshots unveil that the joint effect of THE and PTF increases TCI and HEX by 4 and 3%, respectively. Finally, findings recommend some policy implications and future research directions for the countries based on empirical outcomes. Countries should regulate economic activities to reduce transport carbon emissions. [ABSTRACT FROM AUTHOR]

There is a significant time lag in the process of sectoral interactions, thus, it is necessary to identify the sectoral carbon emissions in time series. This paper calculates the time lag of sectoral carbon emissions of China's industrial sectors and constructs the monthly consumption data of sectors of 24 months, then simulates the monthly carbon emissions in the year 2022, the results are as follows: The terminal manufacturing industries receive carbon emissions from many sectors, and the energy supply industry generates carbon inflows to all sectors. Due to the time lag effect, some of the carbon emissions generated in the current period come from carbon accumulation in the previous periods. There are great differences in the time lag of sectoral carbon emissions, the carbon emissions of the energy supply industry are concentrated in the early stage while the time lag of the communication equipment manufacturing industry is long. Sectors show differences of carbon emissions in time series due to their different final consumption. In the whole year, the degree of carbon emissions in January and February is low and that in December is high. [ABSTRACT FROM AUTHOR]

With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance. [ABSTRACT FROM AUTHOR]

Many countries have launched the carbon emission trading scheme (ETS), attempting to limit carbon emissions through total amount control, and thus accelerating the improvement of emission reduction technology. However, the role of the ETS in emission reduction technical change (ERTC) is still controversial. To clarify the role of the ETS in ERTC, this paper firstly proposes an endogenous growth equilibrium model to theoretically analyze how the ETS induces ERTC, and extracts the corresponding influencing factors. Then, the emission reduction technology is further decomposed into the source, process and end-of-pipe emission reduction technologies by the whole process decomposition method. Last, taking China's carbon pilot market as a sample, we use the time-varying difference-in-difference method to empirically estimate the impacts of the ETS on ERTC. Results show that: (1) the ETS is conducive to ERTC, but whether the effect is significant is depends on the technology accumulation in the early stage, research efforts, success probability of technology research, and carbon trading effect; (2) China's ETS significantly improved the process emission reduction technology, but has no obvious effects on the source and end-of-pipe emission reduction technology. (3) China's ETS has heterogeneous impacts on technical change concerning different regions. Accordingly, three suggestions are provided, including laying out new technologies for energy conservation and emission reduction, expanding the industry coverage of the ETS, and correcting the distortion of carbon trading price. [ABSTRACT FROM AUTHOR]

It has been a crucial challenge for countries worldwide to reduce carbon dioxide (CO2) emissions. China is developing policies among various industries to peak CO2 emissions as soon as possible and expects the reduction of CO2 emissions through financial development. This paper explores the influencing mechanism of financial development on CO2 emissions based on panel data from provinces in China, considering constraints of technological innovation and fossil energy dependence among provinces and periods. Empirical results consistently indicate that the effect of China's financial development on CO2 emissions per capita is significantly negative, and it also presents an inverted U-shaped pattern. In those provinces or periods witnessing lower technological innovation and higher fossil energy dependence, the financial development has more significant effect on carbon emission reduction. This result suggests that regions with deficiencies in the development of technology industries, lower proportions of the tertiary industry, and a higher percentage of the secondary industry need to focus more on the value of financial development. [ABSTRACT FROM AUTHOR]

Climate change and its effects are one of the main concerns of both administrations and citizens in many countries. One of the most important causes of climate change is greenhouse gas emissions, especially CO2, and its reduction is a target for governments around the world. In this sense, the article aims to measure the regional imbalances in CO2 emissions, through the use of a spatial shift-share analysis of the variable intensity of emissions. This methodology will be applied to the regional emissions of Chile for the year 2014, which will be obtained from the application of a multi-regional input–output model. The results of the paper have been structured in two parts: firstly, regional imported and exported emissions have been estimated, from which the responsibilities of the producer and the consumer were determined. Secondly, the Shift Share analysis has been applied to determine regional imbalances in emissions. Large imbalances have been found in the distribution of the intensity of emissions at a regional level. These imbalances may be due to differences in regional economic and production systems, which are manifested through the components that represent the sectoral structure, the localization economies and the regional effect. [ABSTRACT FROM AUTHOR]

To solve the problem of excessive carbon emission and protect the environment, the government has put forward cap-and-trade (CAT) policy to limit the greenhouse gas. In order to testify the efficiency of the CAT policy and different coordinating contracts, this paper develops a closed-loop supply chain (CLSC) model consisting of a single manufacturer and retailer under various coordination scenarios. We establish a Stackelberg game model for the manufacturer and the retailer to explore the impact of the CAT policy on pricing, profits and social welfare under different contracts. Our research finds the following conclusions: (1) The CAT policy outperforms the situation with no CAT policy regarding environment, collection quantity and profit; (2) for the profits of manufacturers and CLSC, the profit-sharing contract is optimal, while the retailers may obtain the lowest interest compared with other contracts; (3) the environment benefits and the consumer surplus present contradictory relationships in the contracts. The research objectives are to find out the most appropriate strategies of CAT policy for enterprises in CLSC and improve society's utility at the same time. These findings provide instructive and practical insights for equilibrium supply chains. [ABSTRACT FROM AUTHOR]

The paper explores the impact of the green–blue revolution on environmental sustainability proxied by production-based carbon emission and agro-environmental footprint in Pakistan between 1976 and 2020. The basic objective of this study is to evaluate and compare the impact of green–blue revolution on sustainable environment in different quantiles. Johansen co-integration test with trace and max eigenvalues determines the long-run relationship between green–blue revolution and environmental degradation in Pakistan. Using median quantile regression analysis, we find that agricultural machinery, pesticides, and aquaculture production are positive and significant factors of production-based carbon emissions with 0.49, 0.1, and 0.09 coefficient values, respectively, while fertilizers, agricultural credit, and HYV (high yield variety) seeds are not major determinants of production-based carbon emission. At the same time, high variety seeds and fertilizers enhance the agro-environmental footprint in Pakistan with 0.23 and 0.28 coefficients, respectively, by applying median quantile regression. Similarly, agricultural machinery, pesticides, agricultural credit, and aquaculture production are not the major determinants of agro-environmental footprint by using median quantile regression. However, the response of exogenous variables varies from quantile to quantile in the case of both environmental proxies. These results discuss implications for fruitful and effective policies and recommendations for a sustainable environment. [ABSTRACT FROM AUTHOR]

To reduce industrial carbon emissions, various industries have been seeking ways to reduce their own emissions. Implementing carbon trading system measures is one way to effectively control industrial carbon emissions. However, in different industrial sectors, carbon trading systems have different impact. The 14-year provincial panel data (2005–2019) were analyzed by using the propensity score matching and the difference-in-difference model to evaluate the role of the emission trading system (ETS) in reducing emissions from different industries. According to the study, ETS has reduced carbon emissions from the agricultural production sector by 1.6876%. Secondly, it also had a significant inhibitory effect on the manufacturing sector, about 24.0489. Mining, electricity production, wholesale and other industrial sectors are insignificant disincentives, and construction and transportation are insignificant facilitators. China's ETS, therefore, mainly acts as an inhibitory force for different industries, which can effectively reduce their carbon emissions. [ABSTRACT FROM AUTHOR]

This paper explores the issues involved in delivering an item from a manufacturer to a retailer in a closed-loop two-echelon supply chain model. Two types of safety factors are maintained in the hands of the retailer to avoid stock-outs during the lead time. This model considers carbon emission from material production and supply chain-related transportation. If products are found to be defective during the inspection or screening process, they are returned to the manufacturer, and the defective items are reworked for resale. Moreover, the transportation costs incurred during the return of such defective items found through the screening process are added to the manufacturer as a penalty. All essential inventory costs of the supply chain are considered uncertain. Furthermore, this uncertainty is handled with an intuitionistic triangular fuzzy number and the corresponding defuzzification process is dealt with the signed distance method. The main objective of this research is to maximize the total expected profit of the supply chain with realistic factors. Distinct from the existing literature, two different solution techniques are employed to provide the optimal solution for the decision variables. In addition, two special cases are specialized in this study. Three numerical experiments are considered to validate the proposed model. Finally, sensitivity analysis, managerial insights, and conclusions are provided. [ABSTRACT FROM AUTHOR]

This paper studies how interaction between economic decision-making and environmental awareness affects US business cycle and GHG emissions in a two-sector DSGE model. We emphasize the mechanisms that relate carbon emissions dynamics, consumer behavior, and environmental awareness in a framework incorporating two classes of goods (i.e., "clean" and "dirty"). This paper offers three main results. First, green consumption preferences play a key role in emissions reduction when they internalize emissions concentrations. Second, a green preference shock is the second source of fluctuation in many sectoral variables and stabilizes the business cycle. Third, a pollutant supply shock leads to sustainable consumption procyclicality documented in US data, only if households are environmentally aware. [ABSTRACT FROM AUTHOR]

Haze pollution is a major cause of serious respiratory health problems, and reducing haze has become increasingly necessary. Additionally, China is the largest carbon emitter worldwide, and the need to improve the country's energy conservation and emission reduction strategies has become increasingly urgent. To reduce CO2 emissions, China launched an emissions trading system (ETS) pilot program in 2011. Whether this system reduces haze pollution remains unclear and is the focus of this paper. Based on data from 31 provinces and autonomous regions in Chinese mainland from 2000 to 2017, using haze pollution as the dependent variable, this paper uses the difference-in-differences (DID) and propensity score matching-difference-in-differences (PSM-DID) approaches to conduct empirical analyses of the effects of the ETS on haze pollution in pilot provinces and their neighboring provinces. The results show the following. (1) In the pilot areas, the estimated coefficient of PSM-DID is "− 6.29," indicating that the ETS can alleviate haze pollution in the pilot areas and achieve a win–win situation of controlling haze pollution and promoting CO2 emission reduction. (2) In the provinces adjacent to the pilot areas, the estimated coefficient of PSM-DID is "− 1.98." The ETS effectively alleviated local haze pollution, providing a "spillover effect." (3) Although the ETS was equally effective in controlling haze pollution in the provinces surrounding the pilot areas, its impact on the particulate matter (PM2.5) concentration in the provinces surrounding the pilot areas was weaker than that in the pilot areas, and there was a certain lag period. [ABSTRACT FROM AUTHOR]

The empirical link between governance and illegal logging is widely accepted amongst scientist, although a minority still purports that illegal logging does not necessarily prevail because of poor governance. However, the nexus linking governance, illegal logging and carbon emission is not well enshrined in scientific literature. This paper seeks to review the literature on illegal logging and governance and empirically investigate the effect of illegal logging and governance effectiveness on carbon emission. Using panel dynamic ordinary least square method on data covering three Congo Basin timber-producing countries and three Asian timber-producing countries, this paper further investigates disaggregated effects between these two groups of countries. The empirical evidence underscores that Congo Basin timber-producing countries are characterised by increasing trend of illegal logging, poor governance effectiveness and corruption. Panel regression reveals a positive and significant impact of illegal logging, governance effectiveness and corruption on carbon emission. Asian producing countries depict a reducing trend in illegal logging and improvements in governance and corruption. There is a positive but not significant impact of illegal logging on carbon emission, and governance effectiveness reduces carbon emission. Thus, the dynamics of governance, illegal logging and carbon emission is not the same between timber-producing countries in Asia and Congo producing counties, thus suggesting the ability of institutions to curb illegal logging and enforce laws to reduce the effects of carbon emission. Multi-stakeholder consultations, government engagement, partnerships and training of control staff can help curb corruption. Legality checks should go beyond having legal documents to effectively check and control of timber concessions and small-scale logging. [ABSTRACT FROM AUTHOR]

Since the 18th National Congress of Chinese Communist Party, ecological civilization construction has been incorporated into Five-sphere Integrated Plan, that is, to promote coordinated progress in the economic, political, cultural, social, and eco-environmental fields. The Chinese government has proposed the goal of "carbon peak" and "carbon neutrality". Low-carbon transportation becomes the mainstream. To achieve carbon peak and carbon neutrality in public transport, this paper takes Beijing's public transport sector as a case study, using system dynamics model with relevant policies and the current situation. It calculates and predicts carbon emissions under electric vehicle substitution scenario, clean energy generation, and carbon capture, utilization and storage scenario for the period of 2020–2060. The following main conclusions are obtained: Direct carbon emissions have peaked and started to decline based on the current measures, while indirect carbon emissions have peaked and started to decline under the suggested intervention. The direct carbon emissions peaked at 2.58005 × 106 tons in 2014. The indirect carbon emissions peaked at 1.59027 × 106 in 2025. They all achieved carbon neutrality under the suggested intervention. Electric vehicle substitution and carbon capture, clean energy generation, utilization and storage are the main factors of carbon emission reduction. The outcomes of this study can provide essential information for policy-makers to advance Beijing's future low-carbon development in public transport. The electric vehicle substitution, clean energy generation and carbon capture, utilization and storage provide a new perspective to research carbon emissions in the transport sector. [ABSTRACT FROM AUTHOR]

Carbon neutrality, being a 'new normative' around the world, is required home and abroad, and such requirement is based on real check of embodied carbon emissions in the international trade. In response, based on the environmental extended multi-regional input–output tables, carbon emission inventories from IEA, and decomposition analysis, this paper comprehensively analyzed the evolution of production- and consumption-based carbon emissions from 2000 to 2014 in Indonesia, explored their disparities in imports, exports, and household demand, and explored main drivers to changes in carbon emission flows. Moreover, historical development patterns over time were measured based on decoupling analysis. The results showed that Indonesia possessed net carbon emission inflows, where China contributed the largest. Increasing trends in carbon emission inflows were found in those embodied in industrial sectors. Dividing the final demand induced emissions, exports accounted for nearly one-third of Indonesia's final demand carbon emission, while domestic consumption took account of 50% of the total emission, of which local industrial products have increased from 2.6 to 1.5 Mt CO2 from 2000 to 2014, taking account of more than 40%. Export is inevitable if a country peruses a higher level of economic development's growth rate. The decomposition analysis showed that the economic development effect has increased carbon emission outflow, while the energy emission intensity effect has the opposite impact on carbon emission increase. Striving to achieve a decoupling and sustainable situation, those results pointed out consumers' responsibilities for future consumption and suggested the sustainable development pattern for emerging economy–Indonesia can be greatly facilitated by international trade control as well as carbon emission intensity mitigation measures. [ABSTRACT FROM AUTHOR]

Production systems are subject to imperfect processes among other factors that may produce items of imperfect quality. To avoid further losses, regular preventive maintenance, and system breakdowns, firms can make changes in their production planning decisions or invest in a green inventory management. Every manufacturing system generates some harmful by-products which are the causes of environmental pollution, and it is increasing day by day. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled pollution. Moreover, permissible delay in payment is a popular payment method and important proportion of company finance. This research proposes a manufacturing plan for products by controlling pollution through sustainable and smart production under warranty and preventive maintenance performed with trade credits. Two different sustainable production models are presented here by considering pollution control costs. A sustainable production model with variable pollution costs is examined under the influence of three pollution control mechanisms to improve the model's applicability. The paper's novelty lies in introducing pollution control costs and pollution control mechanisms together in a flexible, sustainable production system. In comparison with the other models, the model with a variable pollution cost appears to be more sustainable as, in this case, there is a 27.76% reduction in the pollution level compared to the other models. Implementing three pollution-controlling strategies, such as pollution cap, pollution cap & trade, and pollution tax, resulted in reductions of 32.52%, 1.72%, and 0.84% in pollution levels, respectively. A sensitivity analysis of the obtained results is also carried out to show the model's strength and robustness. [ABSTRACT FROM AUTHOR]

How to reduce carbon emission intensity is a common challenge facing in various countries, particularly in developing countries. We identify three literature gaps: theoretical framework of a novel perspective of intelligent manufacturing (IM) influencing carbon intensity, empirical tests by solving endogeneity with cross country and industry data to answer why IM influences carbon intensity, and mediation analysis to explain how IM influences carbon intensity. By applying the World Input–Output Database (WIOD) and environmental account database with panel data of 13 manufacturing sectors in 39 economies from 2000 to 2011, we reveal that IM has a significant reduction in carbon intensity after considering endogeneity and robust check. Our mechanism test demonstrates that energy consumption structure and position in global value chains (GVCs) are main channels. Heterogeneity analysis reveals that developing countries have larger carbon restraining influence by IM. The contributions of this study are: First, this study investigates restraining influence on carbon intensity from novel perspective of IM, which enriches theoretical analysis. Second, this study takes advantage of cross country and industry data to test and adopts Generalized Method of Moments (GMM) model to solve endogeneity, which answers why IM influences carbon intensity. Further, this paper performs heterogeneity analysis and explores the mediating effects played by improving energy consumption structure and enhancing position in global value chains (GVCs), which answers how IM influences carbon intensity. [ABSTRACT FROM AUTHOR]

As the world's largest carbon dioxide emitter, China is curbing coal consumption and increasing natural gas and renewable energy consumption to curb the increase in carbon emissions. At the same time, China is still the largest developing country in the world. Therefore, it is very important to investigate the links between different types of energy consumption, economic growth, and carbon emissions. In this paper, impulse response functions and Granger causality test based on time-varying parameters vector autoregressive model are used to explore the time-varying relationship among CO2 emissions, economic growth, and heterogeneous energy consumption (coal, gas, oil, and renewable energy) in China over the period 1980–2019. The results show that reducing coal and oil consumption and increasing natural gas and renewable energy consumption will not significantly hinder economic growth. In addition, in the long run, reducing coal and oil consumption and increasing renewable energy consumption can significantly reduce carbon emissions. However, after 1998, increasing natural gas consumption will significantly increase carbon emissions. This study reveals the time-varying relationship between heterogeneous energy consumption, economic growth, and carbon emissions, and provides suggestions for China to achieve low-carbon economic growth. [ABSTRACT FROM AUTHOR]

This study aims to investigate why some countries are cleaner than the others with reference to macroeconomic governance (MEG) in order to explain how major macroeconomic aggregates should be governed to mitigate environmental pollution at the level of economic systems. Using per capita carbon dioxide emissions (CPC) as the proxy for air pollution, and macro-non-financial governance (MNFG) and macro-financial governance (MFG) as the proxies for MEG, the study introduces the systemic and fragmented governance of green complementarities (GCMs) and dirty complementarities (DCMs) as analytic concepts to compare the MEG models for managing pollution in 13 high-income countries (HICs), 10 upper-middle-income countries (UMICs), and nine lower-middle-income countries (LMICs) for the period 1994–2014. The paper concludes that (i) HICs reduced their CPC levels thanks to adopting green systemic governance by creating GCMs between both MNFG and MFG variables in the long run; (ii) UMICs experienced a remarkable increase in their CPC levels due to adopting dirty systemic governance by creating DCMs between the MNFG variables, but prevented pollution from being higher through creating GCMs between the MFG variables; and (iii) LMICs experienced the highest comparative increase in CPC due to adopting a fragmented governance in managing both MNFG–pollution and MFG–pollution nexus. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the effectiveness of environmental taxes and environmental stringent policies in reducing CO2 emissions in a panel of 20 European countries for the period 1995–2012. As mounting global environmental and climate challenges are becoming great cause for concern, environmental stringency policies and environmental taxes are becoming the cornerstones for a sustainable environment. Applying panel cointegration tests, we found a negative and a statistically significant relationship between environment taxes (disaggregated into total, energy and transport taxes) and CO2 emissions on the one hand and also a negative and a statistically significant relationship between environmental policy stringent and CO2 emissions on the other. The robustness of the evidence is also supported by a quantile regression model. The higher the environmental stringency policy, the lower the CO2 emission. Similarly, the higher the revenue from total environmental tax, energy and transport tax, the higher the reductions in CO2 emissions. Both these two policy instruments were effective in reducing CO2 emissions. The positive impact of environmental tax on improving environmental quality should encourage policy makers to increase environmental tax as the current level of environmental tax is believed to be low relative to levels required to achieve climate change objectives and is also low relative to the social cost of carbon and relative to the prices of taxed fuels. [ABSTRACT FROM AUTHOR]

Household energy consumption has been one of the most critical factors to climate change. We conducted bibliometric research on household energy consumption by using CiteSpace and HistCite. The Web of Science was used to identify and visualize the evolution of paper citation diagram, the collaboration network, the cocitation network and emerging trends by mapping the knowledge domain of 2984 academic publications between 2011 and 2018 related to household energy consumption. The results showed that the number of academic articles published in the field of household energy consumption and carbon emissions was on the rise, but the number of highly cited articles decreased. The most productive authors and institutions in this subject are in Australia, the USA, China, Britain and Germany. Much of the research has focused on electricity consumption and heat supply, while there have been few studies on other subdomains in the area of energy consumption. The impact of greenhouse gases produced by energy consumption on the environment was the focus of this study. Here, we present an in-depth analysis of household energy consumption and carbon emission research to better understand global trends and hot topics in this field which have emerged over the last few years. [ABSTRACT FROM AUTHOR]

E-waste represents a rapidly expanding category of solid waste, with mobile phones being particularly noteworthy contributors to the global waste stream. The substantial consumer demand for mobile phones, coupled with their relatively short lifespan, limited repair options, and the absence of efficient recycling methods, significantly contributes to the generation of e-waste. In order to address this pressing concern, a sustainable circular inventory model that promotes green industrial practices without compromising profitability is a need in this era. This paper aims to develop an integrated sustainable circular model for a mobile industry that incentivizes the end-of-life processing of used mobile phones. The model explores the idea of the retailer's inspection to segregate defectives and the manufacturer's remanufacturing and product recovery initiatives to identify e-waste as a valuable secondary source of raw materials. The ultimate objective of this study is to determine the optimal expected average integrated total profit of the system with optimal order quantity and shortage quantity. An algorithm is designed to get the local maximum of the expected average integrated total profit using Mathematica 9.0 software. The practicability of the suggested model in the mobile industry is verified numerically and theoretically. The effect of investment in emission reduction technology and waste minimization technology with a carbon cap policy is studied, and it is found that the industry benefits from investments in green technology and waste minimization technology by generating 7.076% more profit while lowering emissions by 48.6336% and waste by 97.9758%. The study concludes that the implementation of the reuse, recycle, and rework concept of circularity for the end-of-life processing and product recovery of discarded mobile phones enhances the supply chain profit without contributing to pollution, which is the ultimate goal of a sustainable economic model. [ABSTRACT FROM AUTHOR]

This study investigates the degree of spatial correlation between carbon emissions and ecological support coefficients among cities in the middle reaches of Yangtze River (MRYR) region by using social network analysis method and spatial autocorrelation analysis. The actual carbon compensation quota (ACCQ) of each city in MRYR is also calculated based on the carbon revenue and expenditure method, and the theoretical carbon compensation quota (TCCQ) is obtained by introducing technology level and ecological value factors. The results show that (1) carbon sinks in the MRYR region increased very little, while carbon emissions increased significantly during the study period, resulting in an overall carbon deficit in 2015. (2) Wuhan and Changsha, as regional economic centers, are at the center of the carbon emission spatial network, with significant carbon emission spillover. (3) The ecological carrying capacity of the MRYR region showed a spatial and temporal pattern of decline at the center and stability at the periphery. (4) The TCCQ is more convergent in revenues and expenditures than the ACCQ and is more suitable for government policymaking. Based on these findings, we recommend that governments establish regional carbon emission quota systems and horizontal carbon compensation mechanisms based on carbon budget accounting. [ABSTRACT FROM AUTHOR]

Economic agglomeration has played a key function in China's economic transformation. Meanwhile, structural adjustment and external pressure to reduce carbon emission necessitate a deeper investigation into its relationship with carbon productivity. This paper measures economic agglomeration and carbon productivity of 281 cities in China in 2003–2017. With the purpose of exploring the spatial effect of economic agglomeration on carbon productivity, a spatial Durbin model is constructed. In addition, the mediation effect model is also adopted for examining the transmission mechanism of economic scale and technological progress on economic agglomeration as well as carbon productivity. A heterogeneity test is also carried out to uncover the varying effects of economic agglomeration on carbon productivity. The empirical results suggest that economic agglomeration raises carbon productivity not only in the local cities but also in the neighbouring ones. The impact of economic agglomeration on carbon productivity becomes more potent as the level of economic agglomeration increases. For cities with low level of economic agglomeration, the effect is mainly achieved through the expansion of economic scale, but for cities with high level of economic agglomeration, the effect is mainly achieved through technological progress. Therefore, we suggest encouraging carbon productivity improvement through technology effect in cities with high economic agglomeration level, while enhancing carbon productivity through scale effect in cities with low economic agglomeration level. [ABSTRACT FROM AUTHOR]

The goal of carbon peak and carbon neutralization puts forward higher requirements for the energy and electricity industry development in China. Jing-jin-ji region (short for Beijing, Tianjin and Hebei Provinces) as an important economic growth pole in China, its electric power industry realizing low-carbon transformation can play a good exemplary role nationwide. To clarify the key factors affecting carbon dioxide emission from electric power industry and analyze the relationship between emission and regional economic growth, the paper established decoupling effort model based on LMDI two phases decomposition model and Tapio decoupling index. Firstly, we collected the data of Jing-jin-ji region from 2000 to 2017 and conducted factors decomposition. The results show that: among the ten key factors affecting electric power industry CO2 emission, power generation and consumption ratio, fossil energy consumption coefficient and industrial structure have the most significant effect on CO2 emission reduction, with contribution rates of − 23.27, − 16.50 and − 11.91%, respectively. Per capita GDP and total population are the main positive driving factors, with contribution rates of 132.20% and 23.38%, respectively. Then from the perspective of decoupling relationship, the electric power industry in Jing-jin-ji region has entered a weak decoupling state since the Eleventh Five Year Plan with the decoupling index declined from 0.85 in 2004 to 0.38 in 2017. Excluding the influence of economic development, there are six driving factors to realize the weak decoupling, including (1) Power generation and consumption ratio effect, (2) Industrial structure effect, (3) Industrial power consumption intensity effect, (4) Fossil energy consumption coefficient, (5) Thermal power proportion effect and (6) Fossil energy power generation structure effect, in which the decoupling degree decreases in turn. The total population effect, transmission and distribution loss effect and resident power consumption intensity effect have not achieved decoupling status. At last, based on the model calculation results, we put forward suggestions to promote the low-carbon development of power industry in Jing-jin-ji region, for example, accelerate industrial structure upgrading and the adjustment of power generation structure; Strengthen electricity demand side management; Promote the construction of ultra-high voltage and smart grid as a whole. [ABSTRACT FROM AUTHOR]

The streetscape of any city reflects the natural built fabric of the street and adds to the experiential quality of that space. A sustainable streetscape ensures that the spaces are long-lasting and functional as a part of the greater sustainable eco-system. Over the past two centuries, mankind has increased the concentration of carbon dioxide (CO2) in the atmosphere from 280 to more than 380 parts per million by volume, and it is still increasing every day. If Earth continues to emit carbon without control, the surface temperature is expected to rise by 3.4 °C by the end of this century. Climate change of that magnitude would likely have serious, long-lasting, and, in many cases, devastating consequences for the planet Earth. Egypt has become one of the biggest emitters of atmospheric pollutants from the transportation sector. The level of carbon emissions and its effect on air quality are placed high on the research agenda. The transportation sector has a great impact on increasing CO2 emissions. The transportation and traffic sectors produce a quarter of the global CO2 emissions due to the heavy use of fossil fuels. This research aims to study the effects of street shape and design on CO2 production. This paper presents an analysis of road transportation in Egypt, taking Helmiet EL-Zaitoun as the main case study, with a focus on energy demand and carbon dioxide (CO2) emissions. Carbon emissions are measured using "Testo 315-3" as a measuring instrument to identify the relationship between street design and quality on the amount of carbon emissions produced. The results of this research suggest that street quality affects the amount of CO2 emissions produced. A car moving at a constant speed will produce fewer CO2 emissions than a car forced to start–stop every while because of external factors such as cracks in the roads occurring from bad streetscape elements. The presented research provides a set of guidelines to enhance the quality of the streetscape and design in order to reduce the amount of CO2 produced in the streets. [ABSTRACT FROM AUTHOR]

Chinese Green Climate Fund (GCF) is expected to launch by the government in the foreseeable future to support local governments in climate change adaption and mitigation. Lessons from experiences of international financing and allocating mechanisms provide valuable references for establishing the Chinese GCF. This study aims to explore the feasibility of several well-recognized schemes for financing and allocating the Chinese GCF among China's 30 provinces. These include: financing schemes of historical emission responsibility (HR), ability-to-pay (AP) and preference score compromises (PSC); as well as allocating schemes of carbon emissions intensity (CI), carbon emissions per capital (CC), GDP per capital (GC) and PSC. This study derives several important findings. Firstly, given different financing schemes, the coastal economically developed provinces including Shandong, Jiangsu, Guangdong, and Zhejiang would collectively shoulder most of the financing responsibility (almost 70% in total) and play central roles in climate financing. Shandong province presents high financing responsibilities mainly due to its export trades of primary products which rely on the development of high-polluted industries. Other three provinces show high financing responsibilities mainly due to the rapid growth of their industries (petrochemical, steel, building materials, electric power, etc.) for economic development. Secondly, the inland economically backward provinces including Shanxi, Ningxia, Guizhou, Xinjiang, and Gansu would be the top five largest recipients of the funds, obtaining more than 30% of total disbursements. The innovations and contributions of the present study are as follows: Firstly, this paper systematically explored the feasibility and alternative schemes for Chinese GCF for the first time. Further, it introduces PSC methods based on diversified approaches to explore suitable financing and allocating schemes. The schemes proposed would establish theoretical foundations for the Chinese GCF and would also promote the development of other kinds of financing for China and countries with similar economic features. [ABSTRACT FROM AUTHOR]

Cold chain logistics has become one of the main sources of carbon emissions. Meanwhile, the implementation of low-carbon economy has become an inevitable way to promote sustainable development. However, previous studies on the cold chain inventory routing problem (IRP) paid less attention to the cost of carbon emissions. In this paper, a linear programming (LP) model is established, which takes the costs of vehicle transportation, time window and carbon emission into consideration. Although the simple LP model is easy to be solved, it cannot handle the problems with uncertainty. Therefore, in order to overcome the influence of uncertainty, the proposed LP model is developed into three low-carbon robust optimization (RO) models. In addition, this paper takes a cold chain logistics enterprise in Yangtze River Delta as an example for empirical analysis. The results of the case study prove that the RO models can quickly solve the problems with uncertainty and still maintain robustness, while the LP model has failed. Specifically, the R-ellipsoid model produces the best result among the three RO models. It is suggested that when the carbon emission tax increases, the decision makers tend to choose a better path planning scheme, which will not only reduce the total cost, but also obtain environmental benefits. Finally, the findings of this paper generate some implications for the low-carbon transformation of cold chain logistics enterprises. [ABSTRACT FROM AUTHOR]

With the steady increase in urbanization that has occurred, China has begun to suffer from serious urban sprawl. Both the increase in urbanization and the subsequent urban sprawl have led to major changes in CO2 emissions. In this paper, we expand the STIRPAT model to empirically analyse the effects of China's urbanization and urban sprawl on CO2 emissions from 1997 to 2018, with regression results showing that both urbanization and urban sprawl have increased CO2 emissions. Further analyses of the mechanisms indicate that urbanization can increase overall CO2 emissions by not only increasing industrial CO2 emissions, but also by increasing construction CO2 emissions and residential consumption CO2 emissions as well. Urban sprawl can increase overall carbon emissions by increasing CO2 emissions from transport, construction and industry. We then make specific suggestions for China's carbon reduction and low-carbon development based on these findings. [ABSTRACT FROM AUTHOR]

The dual objectives of air pollutant control and carbon emission reduction highlight the importance of determining investment methods in end-of-pipe (EOP) technology to achieve cost optimization goals. This paper aims to bridge the gap between the cooperative control theory and practical applications. We propose a framework using optimal control theory to obtain a technology investment path while considering the two-way synergy effect. To verify the effectiveness of the model, we considered three typical technologies in ultra-low emission transformation of a certain steel process. The used case in the study set the emission reduction of SO 2 , NO x and CO 2 as 55%, 70% and 80% compared to their basic cases, respectively. Considering the synergy effect, the peaks of the installed capacity of three technologies including carbon capture, denitrification, and desulfurization were obtained as 0.12 million tons, 5 million tons, and 15 million tons. Also, the related net emissions for the pollutant were 300, 400, and 1000 million tons. We found that terminal desulfurization and denitrification technology increase CO 2 emissions accounting for about 2% due to the negative synergy. However, the negative emission contribution from carbon abatement technology is greater accounting for about 40%. We also found that different policy objectives and emission factors have a greater impact on the investment path. These results demonstrate that we cannot completely ignore the negative emission reduction effects when adopting these EOP technologies. It is necessary to reevaluate these negative effects to the greatest extent so as to develop a more reasonable technological path, which is a guarantee for achieving the expected emission reduction targets. [ABSTRACT FROM AUTHOR]

This paper explores the nonlinear effect of outward foreign direct investment (ODI) and Export Trade Structure on CO2 emissions in China. A national panel of 30 provinces and two sub-national panels for the time span 2003 to 2016 have been estimated by using SGMM estimator and panel threshold regression model. The results indicate that GDP has a positive and significant impact on carbon emissions and that the scale effect of ODI will increase the CO2 emissions. Additionally, ODI and Export Trade Structure are generally conducive to the reduction of carbon emission intensities, except that the impact of Export Trade Structure is not significant the in northern region. Moreover, GDP, ODI, and Export Trade Structure contribute to the reduction of CO2 emissions via the technical effects of energy efficiency, and ODI will help reduce CO2 emissions even as the output of energy-intensive industries grows. Therefore, regions should develop a more effective opening-up strategy based on their industrial distribution characteristics and development stages against the background of trade protectionism affecting the evolution of global value chains, use the spillover effects generated by various channels to effectively mitigate CO2 emissions, and seek sustainable economic growth accompanied by clean technologies and faster development of energy efficiency. [ABSTRACT FROM AUTHOR]

Carbon sink is the process of absorbing CO2 from the atmosphere, through forests, wetlands, grasslands, and oceans. Through this process, greenhouse gases can be absorbed from the atmosphere. In order to analyze the contribution of carbon sinks to carbon neutrality, three parts of works were carried out on carbon sinks in Beijing-Tianjin-Hebei. Firstly, the regional carbon sinks were calculated based on actual data. Secondly, the macro-factors were selected related to carbon sinks, on which the econometric analysis was carried out. Finally, a carbon sink prediction model was constructed based on partial least squares regression. After that, three carbon sink development scenarios with different intensities were set up. Under these three scenarios, the carbon sink potential of the Beijing-Tianjin-Hebei region was forecasted from 2020 to 2030. The results show that under the strong carbon sink scenario, the carbon sink in Beijing-Tianjin-Hebei can neutralize 388.6901 million tons/a of carbon emissions by 2030, whose contribution rate to China's carbon emission reduction can reach 10.48%. Compared with the baseline scenario and weak carbon sink scenario, the strong carbon sink scenario can achieve greater carbon sink potential and contribute more to China's carbon neutrality. As a conclusion, the target of carbon neutrality of China can be easier to achieve under the strong carbon sink scenario. [ABSTRACT FROM AUTHOR]

Although energy supply is not the only factor of the production function, it remains an important driver for any economy despite its negative environmental impacts. This paper examines the determinants of carbon dioxide emissions in a sample of 35 African countries from 1980 to 2016. It uses several econometric methods to ensure robust and reliable findings. Results from Mean group (MG) and Dynamic common correlated effects mean group (DCCEMG) models prove that the environmental degradation in the selected sample is caused mostly by economic growth and non-renewable energy consumption. Moreover, the results confirm that the Environmental Kuznets Curve hypothesis is not significant when consider cross sectional dependence. These finding are contradictive to those obtained from similar studies that used traditional panel estimators. This means that energy consumption and economic growth will continue to increase emissions in the future. Furthermore, the study provides evidence of bidirectional causal relationships between carbon dioxide emissions and economic growth, non-renewable energy consumption and economic growth and between non-renewable energy consumption and carbon dioxide emissions. These findings imply that a hard work must to be done by the African policymakers and a long corrective measure series have to be adopted to ensure more efficient and clean energy. [ABSTRACT FROM AUTHOR]

This paper is aimed at examining the short- and long-run relationships among consumption of renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico during the period 1973–2018. Data were obtained from the World Bank and the British Oil Company BP. A cointegration model together with a fully modified ordinary least squares (FMOLS) is used to estimate possible associations among all variables. Subsequently, the Granger causality test is applied to empirically verify the environmental Kuznets curve (EKC) hypothesis. The main empirical results are that the variables under study explain CO2 emissions in the short and long run, with economic growth having the greatest influence on CO2 emissions, which provides empirical evidence of an EKC for Mexico. Moreover, consumption of renewable and non-renewable energies and economic growth causes in the Granger sense the current levels of CO2 emissions. Moreover, lagged GDP and lagged non-renewable energy consumption do influence (Granger cause) current CO2 emissions. Long-term policies should encourage the use of renewable energies in the electricity, transport, manufacture, and construction sectors. [ABSTRACT FROM AUTHOR]

Improving carbon emission efficiency (CEE) would promote the development of the green and low-carbon economy in the Beijing-Tianjin-Hebei (BTH) region, China. This paper uses the EBM model of unexpected output to measure the city-level CEE of the BTH region from 2007 to 2016. The spatial distribution characteristics and evolution law of CEE are analyzed with respect to overall and local aspects, and the spatial quantile regression model is used to verify the influencing factors of CEE. The main findings are as follows: (1) The carbon emission in the BTH region is considered to be of medium efficiency, and there are eight cities within the region at middle- and high-efficiency levels. The overall efficiency values show a downward trend. Beijing, Cangzhou, Baoding have high-CEE values, whereas Handan, Tangshan, and Zhangjiakou have low-CEE values. (2) The CEE values for BTH show significant spatial agglomeration characteristics at both the global and local levels. The "H–H" agglomeration areas are primarily distributed in the central region, and the "L-L" agglomeration areas are chiefly distributed in the southern and northern regions. The spatial pattern change is generally stable. (3) The selected factors, URB, PGDP, DS, ISG, FDI, and TEL, have different regression coefficients on CEE at different quantiles. [ABSTRACT FROM AUTHOR]

The carbon emission of the energy industry is mainly generated by power generation. Adjusting the power generation structure of multiple energy sources, so as to control the carbon emission of the power generation industry and measure its emission reduction space, is the key for power generation industry to achieve the goal of "dual carbon targets." This study develops a regional multi-energy generation simulation model, which is based on the core algorithm of generation dispatching approach. The established model can simulate the dispatching of all types of generating units in the region and output the data of power generation and emissions. Considering taking Shanxi Province as example, the output results under the benchmark scenario are obtained to verify the efficiency of the model. The error of renewable energy generation and other generation is less than 4%, which shows that the model has enough credibility. The results of the scenario analysis show that every 5% increase in the utilization rate of wind turbine units will increase almost 20% of the renewable energy power generation, reduce almost 15% of the thermal power and reduce at least 10% of the CO2 emissions. This proves that China's regional power generation industry has certain emission reduction potential. The proposed model has important application value for energy conservation and emission reduction of regional power generation industry. [ABSTRACT FROM AUTHOR]

This paper proposes the projected gradient algorithm to find a solution that allows economic restructuring to minimize carbon emission intensity and not hinder targeted economic growth. It develops a general formula to calculate how much each sector should change its share in gross domestic products and its emission intensity such that the economy can have a lower aggregate emission intensity without hindering economic growth. Used data for 30 nations during 1997–2009, the study indicates that if a country follows this proposed optimal restructuring solution, it experiences a lower carbon emission intensity than its initial scenario. This solution is helpful to (1) find the optimal direction and quantitative solutions of a low emission economic structure; (2) continuously check and quantify the differences between the optimal and actual directions of economic structuring for adjusting economic and environmental policies. [ABSTRACT FROM AUTHOR]

Using the calculation method of the United Nations World Tourism Organization (UNWTO), this paper measured the carbon emissions of tourism traffic and their evolution process in Beijing from 2005 to 2017. The Tapio model and Logarithm Mean Divisia Index (LMDI) approach were used to discuss the decoupling relationship between economic development and the change of tourism traffic carbon emissions and the influencing factors. There are six major indicators in our analysis, including (1) tourists scale, (2) per capita tourism consumption level, (3) contribution rate of tourism industry to Gross Domestic Product (GDP), (4) passenger traffic volume per unit GDP, (5) energy consumption per unit passenger traffic volume, and (6) energy structure. The results showed that: the main positive drivers are tourists scale, per capita tourism consumption level and energy consumption per unit of passenger traffic volume. In addition, per unit GDP passenger traffic volume is an effective factor to restrain the growth of carbon emissions. And the economic development of Beijing is developing in step with the change of carbon emissions in Beijing's tourism traffic. The research results have important theoretical and practical significance for Beijing to formulate emission reduction policies and develop low-carbon economy. [ABSTRACT FROM AUTHOR]