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As China's demand for paper products increases, China's paper industry faces enormous pressure to reduce greenhouse gas emissions. By using material flow analysis in combination with input–output analysis, this study measured the waste paper recovery rate in a more accurate method and analyzed the impact of waste paper recycling on the carbon emissions from China's paper industry. China's waste paper recovery rate estimated in this study was close to 70% in 2017, much higher than that of 48% obtained with the traditional method. The regression results displayed a negative relationship between waste paper recovery rate and CO2 emissions per unit of paper consumption during 2000–2017 in China. The rolling regression results further indicated that the impact of waste paper recycling was becoming stronger on reducing CO2 emissions per unit of paper consumption in China. Since an inverted "U" shape relationship exists between waste paper recovery rate and its reduction effect on carbon emissions from the paper industry, the regression results suggested that China's waste paper recovery rate has not reached the optimal level with regard to carbon emissions from China's paper industry. Thus, although China's waste paper recovery rate has reached a relatively high level, currently waste paper recycling is still an effective method to reduce carbon emissions from China's paper industry. [ABSTRACT FROM AUTHOR]

China's pulp and paper industry (CPPI) has been always the main carbon emission source in recent years. However, the analysis on influencing factors of carbon emissions from this industry is insufficient. To address the issue, the CO2 emissions from CPPI are estimated in the period of 2005–2019, the driving factors of CO2 emissions are investigated by the logarithmic mean Divisia index (LMDI) method, the decoupling state of economic growth and CO2 emissions is determined by Tapio decoupling model, and finally, future CO2 emissions are predicted under four scenarios by the STIRPAT model to explore the potential of carbon peaking. The results show that CPPI exhibits a rapid increase and a fluctuating downward trend in CO2 emissions during the period of 2005–2013 and 2014–2019, respectively. The main promoting and inhibiting factors to the increase of CO2 emission are per capita industrial output value and energy intensity, respectively. There are five decoupling states of CO2 emissions and economic growth during the study period, and the CO2 emissions exhibit a weak decoupling state with the industrial output value growth in most years of the study period. It is very difficult to realize the carbon peaking goal by 2030 under the baseline and fast development scenarios. Therefore, efficient low carbon and strong low-carbon development policies are necessary and urgent for the realization of carbon peaking goal and the sustainable development of CPPI. [ABSTRACT FROM AUTHOR]

Recycling is emerging as both a viable alternative to extraction in many industries and a cornerstone of the circular economy. In this paper, we assess the role of paper and cardboard recycling on the forest sector, from both an economic and carbon perspective. For this purpose, we add the recycling industry to an existing forest-sector model in an attempt to capture its effects on other wood products and the overall forest resource. As the forest sector has an important potential for climate change mitigation, this model allows us to assess the effects of increased paper and cardboard recycling on the availability of the natural resource and the carbon balance of the forest sector. We show that these results are strongly linked to the hypotheses of substitutability and/or complementarity of recycled pulp and virgin pulpwood. Although we find increased emissions at the pulp sector level, the effects on emissions in other wood products are small. When pulp products are considered substitutes, we find the impact on total net sequestration to be positive. In the case where pulp products are considered complements, we find the impact on total net sequestration to be negative. [ABSTRACT FROM AUTHOR]

China's carbon market is an important way to achieve carbon peak by 2030 and carbon neutrality by 2060. Blockchain technology can solve the problems of low trading efficiency, poor liquidity and regional heterogeneity in China's current carbon market. this paper explores the scenario of applying blockchain technology to China's carbon market. Firstly, this paper considers the allocation of carbon quota in the carbon market based on blockchain technology under policy regulation. The study found that the development of carbon trading pilots was uneven, and some pilot carbon trading volumes were low, presenting a situation of "no market price". Secondly, it describes the enhancement effect of blockchain technology on the carbon market from the perspective of technology and multiple factors. Considering only the technical factors, the enhancement process is an "inverted L" shape, while considering the superposition factors, the enhancement effect is approximately an "S" shape. Finally, based on the social learning model of major technological changes, the paper describes the process of dynamic utilization of blockchain technology by carbon trading enterprises and simulates the evolution law. The government should introduce relevant policies to guide the implementation of blockchain technology in the carbon market to strengthen the vitality of the carbon market and meet the expectation of carbon emission reduction. This paper provides theoretical support for the integration of blockchain technology into China's carbon market. [ABSTRACT FROM AUTHOR]

Climate change and the resulting higher frequency of extreme weather events have a direct negative impact on mental health. Natural disasters are particularly associated with an increase in the prevalence of depression, anxiety and posttraumatic stress disorder. Indirect consequences of climate change, such as food shortages, economic crises, violent conflicts and forced migration, additionally represent severe psychological risk and stress factors. Climate anxiety and solastalgia, the distress induced by environmental change, are new psychological syndromes in the face of the existential threat posed by the climate crisis. Accordingly, a sustainable psychiatry must prepare for increasing and changing demands. The principles of psychiatric treatment need to focus more on prevention to reduce the overall burden on the healthcare system. Waste of resources and CO2 emissions in psychiatric treatment processes as well as infrastructure must be perceived and prevented. Psychiatric education, training and continuing education concepts should be expanded to include the topic of climate change in order to comprehensively inform and sensitize professionals, those affected and the public and to encourage climate-friendly and health-promoting behavior. More in-depth research is needed on the impact of climate change on mental health. The DGPPN becomes a sponsor and aims for climate neutrality by 2030 by committing to climate-friendly and energy-saving measures in the area of finance, in relation to the DGPPN congress as well as the DGPPN office. [ABSTRACT FROM AUTHOR]

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]

Improving carbon emission efficiency is crucial for achieving carbon peak and carbon neutrality. This paper analyzes the carbon emission efficiency of Chinese cities using panel data from 275 prefecture-level cities between 2006 and 2020. The super-efficiency SBM (undesirable slacks-based measurement) model of undesired output, combined with kernel density estimation and exploratory data analysis, is employed. This study finds, firstly, from 2006 to 2020, the average efficiency of carbon emissions in Chinese cities declined from 0.53 to 0.48, indicating a downward trend. Secondly, from a temporal perspective, the level of dispersion in urban carbon emission efficiency has become increasingly distinct over time, coupled with a decrease in polarization. Thirdly, in terms of spatial analysis, urban carbon emission efficiency in China shows a positive correlation in a global context. In terms of local spatial correlation, it primarily exhibits high-high and low-low clusters, with a few instances of low–high and high-low clusters. Finally, based on the research findings, this paper proposes suggestions to improve urban carbon emission efficiency. [ABSTRACT FROM AUTHOR]

Carbon abatement efforts in China are penetrating to sub-national level. Zhejiang province, as the 4th wealthy region in China and important player in global market (e.g., textiles, cloth, petroleum, and chemical products), lacks in-depth study of its climate change mitigation efforts, especially after China's accession to the WTO in 2001. This paper analyzed carbon emissions and intensity in Zhejiang province using most comprehensive and time-series dataset available to date since 2002. Its carbon emissions were growing at a declining speed, and carbon intensity was almost halved. The leading emitters largely agglomerate around Hangzhou Bay, close to Zhoushan Port and Shanghai Port. The growth in absolute emissions primarily arose from higher investment (323.1 Mt) and exports (280.6 Mt), while the slower growth was mainly due to efficiency improvements (− 245.7 Mt) stemming from energy and carbon abatement policies and inflows of emission-intensive products from the rest of China. Similarly, declined carbon intensity was mainly attributed to efficiency improvement. Major contributors were sector S13-Non-metallic minerals, S12-Chemicals, S26-Transport, storage and post, S07-Textiles, and S10-Paper. Economic restructuring played different roles on emissions and intensity during various development stages. Policy implications of the findings are discussed for future developments. [ABSTRACT FROM AUTHOR]

China plans to arrive at its peak in the emissions of carbon dioxide and reach carbon neutrality by 2030 and 2060, respectively. What role does internet technology, as a key twenty-first-century technology, play in China's achievement of its two carbon goals? Based on datasets about Chinese prefecture-level cities collected mainly from statistical reports released by the China Internet Network Information Center (CINIC), China City Statistical Yearbook, and China Energy Statistical Yearbook in 2006–2019, this paper empirically examines how the development of the internet influencing energy efficiency. This paper uses the policy of "network power nation" strategy and "internet plus" (NPNIP) as a policy impact to construct a continuous difference-in-difference (DID) model for an empirical investigation, and use a mediating effect analysis to test the transmission mechanism involved in industrial structure upgrading, technological innovation, and economic agglomeration. Empirical findings show that energy efficiency is improved by the development of internet. But this result has significant regional heterogeneity. Internet development can significantly reduce energy intensity in the eastern region and mature resource-based cities, but not the central and western regions and other resource-based cities. The mediating effect results show that the internet improves energy efficiency in three ways: upgrading industrial structure, stimulating technological innovation, and economic agglomeration. The empirical findings in this paper lead to many policy recommendation, including strengthening the formation of new infrastructure, deepening the organic integration of the internet across industries, and exploring the legal regulations on internet technology in specific application areas. [ABSTRACT FROM AUTHOR]

With the establishment of the "double carbon" goal, various industries are actively exploring ways to reduce carbon emissions. Cloud data centers, represented by cloud computing, often have the problem of mismatch between load requests and resource supply, resulting in excessive carbon emissions. Based on this, this paper proposes a complete method for cloud computing carbon emission prediction. Firstly, the convolutional neural network and bidirectional long-term and short-term memory neural network (CNN-BiLSTM) combined model are used to predict the cloud computing load. The real-time prediction power is obtained by real-time prediction load of cloud computing, and then the carbon emission prediction is obtained by power calculation. Develop a dynamic server carbon emission prediction model, so that the server carbon emission can change with the change of CPU utilization, so as to achieve the purpose of low carbon emission reduction. In this paper, Google cluster data is used to predict the load. The experimental results show that the CNN-BiLSTM combined model has good prediction effect. Compared with the multi-layer feed forward neural network model (BP), long short-term memory network model (LSTM), bidirectional long short-term memory network model (BiLSTM), modal decomposition and convolution long time series neural network model (CEEMDAN-ConvLSTM), the MSE index decreased by 52 % , 50 % , 34 % and 45 % respectively. [ABSTRACT FROM AUTHOR]

The Web of Science Core Collection platform was used to withdraw the papers included in this study. The studied period comprised from inception till 2018. Trends in research, journals of publication, subject areas of research, keywords most frequently used, countries of publication, international collaboration, and trends of funding research were also analyzed. A total of 3902 articles were published, most of them (52.5%) during the five-year period 2014–2018. The area with the highest number of papers was environmental sciences (41%), followed by energy fuels (16.6%) and engineering environmental (15.7%). "Nitrous oxide emissions" was the most frequent word, followed by "Carbon dioxide emissions" and "Methane emissions". Other words that stood out were "Life cycle assessment", "Climate change" and "Environmental impacts". The United States was the country with the highest productivity (27.9%), followed by China (12.8%) and the United Kingdom (9.6%). There was a concentration of research in recent years, as more than 80% of the papers were published in the last 10 years. The journals that published the largest number of publications were devoted mainly to environmental studies (sciences and engineering), sustainable and green science and technology, energy and fuels, economics, and agriculture. Half of the works were published in Europe and the other half between North America and Asia. Two thirds of the works (67%) were financed compared to a third that were not financed. The percentage of funded works has been increasing over the last decade, which is seen as an indication of the importance of GHGE. [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]

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]

Most of the current studies on carbon emission reduction have been focusing on the urban and industrial levels, overlooking policy assessment studies on the carbon emissions of construction enterprises in the Yangtze River Economic Belt (YREB). To explore the impact of smart city policy (SCP) on the carbon emissions of construction enterprises, this paper constructs a theoretical framework model for evaluating SCP based on the Political-Economic-Sociocultural-Technological-Environmental-Legal (PESTEL) model and the perspective of the pollution halo hypothesis. In addition, this paper adopts panel data of 110 cities covered by the YREB from 2004 to 2021 and verifies the SCP impact mechanism on the carbon emissions of construction enterprises in the YREB through the difference-in-differences (DID) method, the propensity score matching (PSM) method, and the analysis of mediating effects and moderating effects. The conclusions are as follows: (1) the SCP significantly curbs the carbon emissions of the construction enterprises in the YREB pilot cities; (2) the SCP has a regional qualitative effect on the carbon emissions of the construction enterprises in the YREB and it curbs the carbon emissions of the construction enterprises in the upstream and downstream regions; (3) R&D and FDI are important transmission mechanisms; and (4) new urbanization construction has a positive moderating effect on the carbon emission reduction effect of the SCP on construction enterprises. As a research precedence, this paper reveals for the first time the mechanism of the SCP on the carbon emissions of construction enterprises in the YREB through the lens of the PESTEL model and the pollution halo hypothesis; the paper not only enriches the research related to urban policies but also provides new evidence from Chinese construction enterprises for assessing the impacts of pilot cities. [ABSTRACT FROM AUTHOR]

This paper explores the creation, development, and dissemination of prefabricated concrete rural houses in Jiangsu Province in East China from 1961 to the 1980s, an example of the technological transition provoked by the depletion of forest and timber in China. Through archival research, fieldwork and interviews, the paper examines the two waves of design and dissemination of prefabricated concrete rural houses between 1961 and 1965 and their subsequent 'vernacularisation' in the 1970s and the 1980s. This research provides a twofold insight into the current scholarly debates surrounding built heritage and global climate change. On one hand, it addresses a historical context of concrete overuse in contemporary China, a matter of critical importance in relation to carbon emissions and global climate change. On the other hand, it offers a counter-argument to today's call for reintroducing timber structures in many places, as evidenced by the case of East China, where the widespread use of materials like concrete was primarily a consequence of the ecological crisis following decades of deforestation and timber resource depletion. In addition, the 'vernacularisation' of concrete structures manifested by this case still provides lessons for today's efforts to popularise more eco-friendly construction materials and technologies, especially in rural areas, and the prefabricated concrete houses possess potential heritage values as trackers of ecological changes. [ABSTRACT FROM AUTHOR]

Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries' technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector's potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector. [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]

This paper investigates how National Eco-industrial Demonstration Parks (NEDP) in China affects carbon emission efficiency. The difference-in-differences (DID) strategy is used for analysis. This paper finds that the construction of NEDP is conducive to the improvement of carbon emission efficiency, and the findings remain robust through placebo tests and propensity score matching. Heterogeneity analysis shows NEDP construction has greater utility on carbon efficiency in non-resource-based cities as well as in environmentally friendly cities. The mechanism analysis found that green technology innovation, industrial restructuring, and the relocation of industrial enterprises are effective ways to improve carbon efficiency in NEDP. Finally, this paper finds that the construction of NEDP has obvious spatial spillover effects on carbon efficiency, which can effectively heighten the carbon efficiency level of this locality and nearby areas. [ABSTRACT FROM AUTHOR]

Low-value recyclable waste (LVRW) is an essential component of municipal domestic waste. Due to the lightweight and high quantity characteristics, the main disposal methods of LVRW are incineration and landfill, which are not conducive to the environmental protection requirements and the goal of carbon neutrality and emission peak. The paper focuses on the delicate separation of LVRW to realize a cost-effective solution for waste sorting. Firstly, a machine vision (MV) pneumatic sorting equipment was designed based on the MV detection system. Then, a large number of authentic waste images were captured and labeled to train a high accuracy LVRW prediction model through semi-automatic labeling and transfer learning. Subsequently, the LVRW waste sorting solution was designed and constructed, and a comparative experimental study about the MV sorting method and the whole solution was conducted. The experimental results show that the MV sorting method achieves 92% sorting accuracy, and the solution can dispose of 65 tons of LVRW per day with a waste recycling rate of 37.7%. The sorting equipment and solutions developed in the paper can effectively improve the resource utilization of LVRW at a lower cost. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is crucial for mitigating global climate change, and green fiscal policies, through providing economic incentives and reallocating resources, are key means to achieve carbon reduction targets. This paper uses data covering 248 cities from 2003 to 2019 and applies a multi-period difference-in-differences model (DID) to thoroughly assess the impact of energy conservation and emission reduction (ECER) fiscal policies on enhancing carbon emission (CE1) reduction and carbon efficiency (CE2). It further analyzes the mediating role of Green Innovation (GI), exploring how it strengthens the impact of ECER policies. We find that: (1) ECER policies significantly promote the improvement of carbon reduction and CE2, a conclusion that remains robust after excluding the impacts of concurrent policy influences, sample selection biases, outliers, and other random factors. (2) ECER policies enhance CE1 reduction and CE2 in pilot cities by promoting green innovation, and this conclusion is confirmed by Sobel Z tests. (3) The effects of ECER policies on CE1 reduction and the improvement of CE2 are more pronounced in higher-level cities, the eastern regions and non-resource cities. This research provides policy makers with suggestions, highlighting that incentivizing green innovation through green fiscal policies is an effective path to achieving carbon reduction goals. [ABSTRACT FROM AUTHOR]

The construction industry occupies a high proportion of the global economy. However, with the energy consumption of construction enterprises, it still brings a series of serious environmental problems. Construction enterprises should take active green development behavior to respond. Based on enterprises' green development behavior, this paper explores the influencing factors of green development behavior adopted by construction enterprises in China. Through literature analysis, this paper identifies that construction enterprises' adoption of green development behaviors is influenced by technological, organizational and environmental factors. Then this paper constructs an index system of the influencing factors of green development behaviors adopted by enterprises. According to the data of construction enterprises from 2000 to 2020 of National Bureau of Statistics, an artificial neural network is used to construct the prediction model of influencing factors of green development behavior adopted by construction enterprises. The conclusions are as follows. (1) Construction enterprises' adoption of green development behavior shows an upward trend over time. (2) Market share of construction enterprises is the most important factor to promote construction enterprises' adoption of green development behavior. (3) The prediction model of influencing factors constructed in this paper is verified to be effective by the technology-organization-environment framework. This paper provides a reference for construction enterprises and the government to promote enterprises to adopt green development behavior, which is beneficial for construction enterprises to achieve green development faster. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is an important means of achieving climate policy goals. However, the literature has neglected consideration of the carbon emission reduction mechanism from the perspective of technology risk spillovers in international trade. To explore this mechanism, this paper expands the classical linear model of foreign trade technology risk spillovers into a nonlinear spatial Durbin model. We construct a novel technology risk spillover index to forecast the magnitude of carbon emissions in agricultural trade across different regions. To validate our model, we consider the dual connotation of the spatial diffusion of disembodied technology communication (DTC) to map the relationships between different geographic and economic regions that are adjacent. The results suggest that disembodied technology risk spillover could promote carbon emission reductions. Specifically, technology risk spillovers from agricultural trade reduce agricultural carbon emissions by 0.79–1.16% in the local region. Disembodied technology risk spillovers also reduce agricultural carbon emissions by 2.85–11.57% in geographically adjacent regions and 4.9% in economically adjacent regions. Based on these conclusions, this paper proposes improving the closed and backward situation of rural areas in China's central and western regions, promoting the transition toward the high end of the global agricultural industry chain and developing productive agricultural services and the rural cultural tourism industry to expand rural employment channels and stabilize farmers' income. [ABSTRACT FROM AUTHOR]

The carbon emission trading pilot policy is an important initiative to achieve synergistic economic-environmental development. Based on the data of 268 cities in China from 2006 to 2020, this paper analyzes the impact of carbon emission trading pilot policy on urban innovation capacity by using a time-varying difference-in-difference model. The study shows that, first, the implementation of the CETP improves the innovation capacity of cities, and the robustness test confirms the above findings. Second, the effect of the policy on enhancing urban innovation capacity is heterogeneous between the type of innovation and city type: the promotion of innovation capacity is stronger for utility model patents and non-capital cities. Third, there is a positive spillover effect of the implementation of the CETP on the promotion effect of the urban innovation capacity, which can lead to the improvement of the innovation capacity of neighboring cities. This paper has some reference value for building a unified carbon emission trading market and promoting low-carbon economic development within China. [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]

The construction of high-speed railways and the smart city pilot (HSR-SCP) demonstrates the synergy of traditional and new infrastructure upgrades, which has a significant influence on the economic transition and green economic growth. However, little study has been conducted on the impact of HSR-SCP synergy on carbon emissions. Applying China's prefecture-level panel data, this paper, therefore, attempts to investigate the effect of HSR-SCP on carbon emissions and uncover its in-depth mechanism through the multi-period difference-in-differences model. Notably, an appropriate instrumental variable for HSR-SCP is introduced to address possible endogeneity. The main conclusions indicate that the construction of HSR-SCP plays an essential role in cutting carbon emissions, which is still valid after adopting the instrumental variable method and some robustness tests. Furthermore, green technology innovation plays a crucial intermediary role in that relationship. Finally, the carbon reduction effect of HSR-SCP is significant in Mid-Eastern China and cities with high population sizes and administrative levels, but not in other cities or regions. The research conclusions demonstrate the significant synergy of traditional and new infrastructure upgrades on carbon reduction and provide an empirical foundation for developing countries to realize low-carbon development through optimizing smart infrastructure and promoting green technology innovation. [ABSTRACT FROM AUTHOR]

How the transformation of trade patterns affects carbon emissions is an important topic in the field of trade and the environment. Based on the panel data of Chinese cities from 2000 to 2016, this paper uses fixed effect model, instrumental variable model and threshold estimation model to investigate the impact of the transformation of export trade patterns on carbon emissions and its internal mechanism. We find that during the investigation period, the transformation of export trade pattern has a significant "U"-shaped nonlinear impact on carbon emissions, and the research results still hold after a series of robustness checks and instrumental variable estimation; through the mechanism analysis of the threshold effect, it is found that in the process of the impact of trade patterns transformation on carbon emissions, there are double thresholds for energy structure transition; the nonlinear impact of export trade pattern transformation on carbon emissions has significant heterogeneity in different regions, city categories, and different periods; the mechanism analysis results show that industrial structure upgrading, industrial co-agglomeration, and green technology innovation are the main paths that the transformation of export trade patterns affects carbon emissions. Under the dual goals of fulfilling China's commitment to "carbon peak in 2030 and carbon neutrality in 2060" and implementing corporate social governance to promote green and sustainable development, this paper will provide suggestions for realizing the goal of low-carbon emission reduction from the perspective of the transformation of export trade patterns. [ABSTRACT FROM AUTHOR]

Currently, collaborative distribution models have not reached the optimal state of carbon emissions. The cost of additional low-carbon expenditures and the problem of carbon data verification have led to the lack of motivation for reducing emissions among collaborative distribution enterprises. Therefore, how to incentivize them to adopt the low-carbon model is crucial for achieving low-carbon goal. By relying on a government-led digital platform, this paper designs a dual low-carbon incentive strategy to encourage enterprise-alliance to adopt a low-carbon distribution model. In this paper, we first construct an evolutionary game model of the government, enterprise-alliance and end-users; then we explore the conditions of the three-party equilibrium evolution strategy by solving the model and analyzing the stability; and finally, we conduct simulation validation and results analysis with the help of MATLAB. In summary, we found that government punishment is more effective at regulating enterprise-alliance than reward. End-users' behavior is affected by the costs they need to bear, and they no longer support enterprise-alliance to carry out collaborative low-carbon distribution above a certain threshold. [ABSTRACT FROM AUTHOR]

The marine ecological compensation (MEC) policy is a scheme for protecting and restoring marine ecology. The previous studies have verified that the policy has improved the marine environment, ignoring the comprehensive performance of the economy and environment. Is the MEC policy actually effective for reducing marine carbon emission considering resource input and economy output? To address the question, this paper evaluates the impact of MEC policy on marine carbon emission efficiency by introducing the multi-stage difference-in-difference with propensity score matching. The results show that the MEC policy significantly improves marine carbon emission efficiency, and the positive effects dynamically enhance over time. Low-carbon technology innovation is confirmed to play a mediating role by which the MEC policy improves marine carbon emission efficiency. Therefore, gradually popularizing the MEC policy and accelerating low-carbon technology innovation are crucial measures to improve marine carbon emission efficiency and achieve sustainable marine development. [ABSTRACT FROM AUTHOR]

A carbon emission factor (CEF) database is required for the basis of carbon emission calculation in construction projects. However, the default values for existing CEF databases cannot cover the complex resources involved in a construction project. Therefore, this paper proposes a three-step method to guide the establishment of an extensible CEF database for the construction industry, including (1) data collection and parser, (2) data extension, and (3) data encoding and storage. The data extension mechanisms provide the supply chain perspective considering temporal issues and the accounting perspective to streamline the process. Aiming to address the lack of a comprehensive CEF database for the construction industry in China, this paper uses this method to establish a carbon emission factor database for the Chinese construction industry (CEFD for CCI). This database is open and free with 646 CEFs, including five parts: energy, human, material, machinery, and greenspace. This paper provides a way for developing and less developed countries to establish an expandable CEF database, which benefits the parser, extension, encoding, and storage of new resources, as well as computer access. [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]

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Buildings are energy- and resource-hungry: their construction and use account for around 39% of global carbon dioxide emissions; they consume around 40% of all the energy produced; they are responsible for over 35% of the EU's total waste generation; and account for about 50% of all extracted (fossil) materials. Therefore, they present a significant challenge to meeting national and international Net Zero targets of reducing greenhouse emissions and fossil resource use. The CircularB Project, is at the heart of this issue, which will underpin synergies of multi-scale circular perspectives (from materials, to components, to assets and built environments), digital transformation solutions, data-driven and complexity science, stakeholder behavioral science, and interdisciplinary capabilities towards achievable, affordable and marketable circular solutions for both new and existing buildings, for sustainable urban design, and for circular built environments across Europe. This paper contributes to the project by deriving new insights into the stakeholders' influences, inter-relationships, and obstacles in the implementation of circular economy concepts on existing building stocks in Europe, which represent over 90% of whole building assets. In order to identify and derive the insights, our study is rigorously based on (i) a robust critical literature review of key documentations such as articles, standards, policy reports, strategic roadmaps and white papers; and (ii) interviews with relevant stakeholders and decision makers. Uniquely, our work spans across all scales of CE implementation from materials, to products and components, to existing building stocks, and to living built environments. The findings point out the current challenges and obstacles required to be tackled. Inadequacies of financial incentives and governmental enforcement (via policy, legislation, or directive) are commonly found to be the most critical obstacles found throughout Europe. Circular economy is the global challenge and not just a single country can resolve the climate issue without the cooperation of other countries. The insights thus highlight the essential need for harmonized actions and tactical/pragmatic policies promoted and regulated by the European Commission, national and local governments who can dominate the influence, promote inter-relationship, and overcome the barriers towards circular economy much more effectively. [ABSTRACT FROM AUTHOR]

Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China. [ABSTRACT FROM AUTHOR]

Accurately identifying changes in carbon trading prices can provide reasonable reference indicators for a government's macrocontrol and can also help companies more effectively avoid risks brought by carbon emissions and increase the income of carbon assets. Based on the Prophet model, LSTM neural network model, and backpropagation (BP), this paper proposes a method to predict carbon trading prices using the ensemble learning model and uses the Hubei carbon trading market data to predict carbon trading prices. Results show that in terms of accuracy, the Prophet-LSTM-BP ensemble learning model achieves better predictive ability than existing models; its RMSE, MAE, and MAPE are 1.479, 0.951, and 2.135, respectively, which are markedly smaller than the Prophet model's 5.631, 4.471, and 9.661, and the LSTM model's 3.352, 3.105, and 6.880, respectively. Compared with the traditional time series ARIMA model, the MAPE of ARIMA reaches 12.933, which is nearly 1.5 times that of the Prophet model, nearly 2 times that of the LSTM model, and nearly 7 times that of the ensemble learning model. In terms of applicability, when the model is applied to the national carbon trading market, the difference in MAPE compared with the Hubei carbon trading market is only 0.6%, and the other parameters are not more than 16%. The model improves the relevant research on carbon trading price predicting, and concurrently, this method provides ideas for carbon trading price predicting in other carbon trading markets and promotes the sustainable development of the national carbon trading market. [ABSTRACT FROM AUTHOR]

The integration of the advanced manufacturing industry and the modern service industry is an important direction for the transformation and upgrading of China's manufacturing industry. However, the existing research focuses more on the level, motivation, and economic effects of the integration of manufacturing and producer services, and less on its environmental effects. In this paper, based on the panel data from 30 provincial regions in China from 2005 to 2019, an evaluation system for the integration of manufacturing and producer services (IMP) is constructed, and the carbon emission efficiency (CEE) is calculated through the super-efficiency SBM model. Based on the analysis of the influence mechanism of IMP on CEE, the mediation effect model and the spatial Durbin model are used to test the influence of the IMP on CEE. The results show that the IMP can significantly improve CEE, and indirectly promote CEE through four intermediary factors: value addition, cost reduction, industrial agglomeration and structure upgrading. Finally, we found the level of economic development, property rights structure and regional innovation can promote CEE to varying degrees. The intensity of environmental regulation, opening level and the energy consumption structure inhibit the efficiency of carbon emissions. The total impact of the IMP on CEE is greater in the western region than in the eastern and central regions, and the western region shows a more significant spatial spillover effect. The IMP has a greater effect on improving CEE, and shows a strong spatial spillover effect. [ABSTRACT FROM AUTHOR]

Multimodal transportation is a modern way of cargo transportation. With the increasing demand for cargo transportation, higher requirements are being placed on multimodal transportation multi-objective routing optimization. In multimodal transportation multi-objective routing optimization, in response to the limitations of classical algorithms in solving large-scale problems with multiple nodes and modes of transport, the limitations of directed transportation networks in the application, and the uncertainty of transport time, this paper proposes an optimization framework based on multi-objective weighted sum Q-learning, combined with the proposed undirected multiple-node network, and characterizes the uncertainty of time with a positively skewed distribution. The undirected multiple-node transportation network can better simulate cargo transportation and characterize transfer information, facilitate the modification of origin and destination, and avoid suboptimal solutions due to the manual setting of wrong route directions. The network is combined with weighted sum Q-learning to solve multimodal transportation multi-objective routing optimization problems faster and better. When modeling the uncertainty of transport time, a positively skewed distribution is used. The three objectives of transport cost, carbon emission cost, and transport time were studied and compared with PSO, GA, AFO, NSGA-II, and MOPSO. The experimental results show that compared with PSO, GA, and AFO using a directed transportation network, the proposed method has a significant improvement in optimization results and running time, and the running time is shortened by 26 times. The proposed method can better solve the boundary of the Pareto front and dominate the partial solutions of NSGA-II and MOPSO. The effect of time uncertainty on the performance of the algorithm is more significant in transport orders with high time weight. With the increase in uncertainty, the reliability of the route decreases. The effectiveness of the proposed method is verified. [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]

The impact of the carbon emission trading system (ETS) on firms' market competitiveness has been a controversial issue with no consistent theoretical conclusions. The aim of this paper is to explore the impact of the carbon emission trading system on firms' markups using the latest robust staggered difference-in-difference estimation method. The results show that China's carbon emission trading system greatly contributes to the enhancement of firms' market power, as evidenced by a series of robustness tests. In addition, the analysis of the impact mechanism shows that the carbon emission trading system enhances the market power of firms through the low-carbon innovation effect and the market integration effect, while the impact of the environmental cost effect is not obvious. Moreover, the heterogeneity analysis shows that the impact of China's carbon trading system policy on firms' market power is more pronounced, especially for those firms that are actively involved in low-carbon transformation and upgrading, have a stronger cost-shifting capacity, and are more efficient in production. This study provides empirical evidence on how environmental regulations affect firms' market power and offers theoretical guidance for the construction of China's carbon market. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions is the key to fulfilling the "double carbon commitment" and promoting the green transformation of the economy. The financial sector is the forerunner of change in economic development. The rapid development of digital finance has disrupted the traditional financial operation mode and has had a significant impact on economic development and environmental quality. This paper explores the impact of digital finance development on carbon emissions using carbon emission data from 2011 to 2017 in China's counties and combining it with the Digital Inclusive Finance Index of Peking University. The findings are as follows: (1) The development of digital finance can curb carbon emissions, and this causal relationship still holds through a series of robustness tests. The greater the carbon emissions, the better the carbon suppression effect of the development of digital finance. (2) When regions face strict financial regulation and environmental constraints, the development of digital finance can be more effective in reducing carbon emissions. The existence of a digital divide in general can weaken the disincentive effect of the development of digital finance on carbon emissions. (3) The development of digital finance can promote the development of green finance, enhance the level of green technological innovation, improve green total factor productivity, and transform energy structures, thus curbing carbon emissions. This paper not only enriches the literature on the development of digital finance and the environment but also provides a reference for government departments to improve the development strategy of digital finance and achieve "carbon peaking and carbon neutrality." [ABSTRACT FROM AUTHOR]

This paper aims to encourage power generation enterprises to actively carry out emission reduction activities by studying the impact of carbon emission reduction investment on long-term development. The existing literature mainly studies the interaction between national economic development and energy consumption at the macro level, and the impact of environmental protection investment by enterprises at the micro level on the short- and long-term economic consequences. However, there is still a large space for research on how specific emission reduction measures lead the long-term development of enterprises. Therefore, this paper chooses to introduce enterprise competitiveness, government subsidy, and management shareholding ratio respectively to conduct intermediary test and grouping regression, and empirically studies the mechanism of carbon emission reduction input of Chinese power generation enterprises on the cost of equity capital from 2013 to 2020. The results show that management shareholding can enhance the initiative of enterprises to reduce emissions. At the same time, carbon emission reduction investment can effectively reduce the cost of equity capital by improving the competitiveness of enterprises and forming a reputation mechanism faster. This study reveals the significance of carbon emission reduction investment as an important part of enterprise environmental protection investment, and emphasizes that the government and enterprises can effectively avoid the short-sighted tendency of enterprises and improve the long-term development power of enterprises by adjusting government subsidies, management shareholding ratio and other policies. [ABSTRACT FROM AUTHOR]

Climate policies could improve air quality, thereby generating health benefits and thus increasing labour input for economic growth. Nevertheless, health benefits are usually overlooked in evaluation frameworks of climate policies. In this paper, a dynamic recursive computable general equilibrium (CGE) model is adopted to define how climate policies are related to air pollution, namely PM 2.5 concentrations. Health benefits of climate policies are divided into reduction of PM 2.5 -related morbidity and mortality. The CGE model results show that both carbon tax and emission trading scheme (ETS) decrease morbidity and mortality; therefore, under climate policies, PM 2.5 -related labour loss decreases, and thus increasing labour input triggers an economic boom. Carbon tax generates more health benefits in short term, while health benefits of ETS policy will gradually increase in long term. Hence, we conclude that regarding health benefits, a long-term ETS policy is preferable to a long-term carbon tax. This finding implies that the recently established nationwide ETS market in China is meaningful, as it will generate more health benefits in future. Nevertheless, the quantified health benefits in this paper still cannot compensate GDP loss induced by climate policy implementations, implying that it is a challenging task to unbiasedly model health benefits of climate policies. Hence, we have recommended that the scopes and contents of health benefits should be expanded in evaluations of climate policies. [ABSTRACT FROM AUTHOR]

With increasing pressure to cut carbon emissions and develop sustainability plans, companies need carbon credits to offset emissions that cannot be eliminated from their operations, new global carbon exchange to launch in Singapore by 2021 end, the high-quality credit can bridge this gap and play an important role in the overall climate change mitigation strategy. The purpose of this research is to use the production data (including carbon emissions) of paper-making companies in Taiwan to establish a circular economy mathematical programming model and the concept based on the activity cost method (ABC) to explore the impact of different carbon emissions costs (such carbon tax, carbon cap-and-trade, etc.) on the company's production structure and profitability impact. The research results show that different carbon emission cost models have different effects on the company's optimal product-mix and profitability. The managerial implication is to combine the extensive application of the carbon emission credit mechanism, which can offset the carbon emissions in the production process and have a significant impact on the company's sustainable competitiveness. In addition, this study can also enable decision makers to understand the impact of different carbon emission cost models on the profitability of the company's product mix, which can be used as a reference for production planning decisions. [ABSTRACT FROM AUTHOR]

A major environmental concern today is the carbon emissions caused by rapid urbanization. As the largest developing country and carbon emitter, China has controlled the urban growth boundary (UGB) as a quasi-experimental policy to achieve carbon neutrality. Therefore, this paper employs the difference in differences (DID) method, for panel data from 2000 to 2019 in China to shed light on the effects on carbon emissions. Results show that the UGB can reduce carbon emissions considerably. After the implementation of the policy, the carbon emissions of the pilot cities decreased by 23.91%. Additionally, a series of robustness tests such as PSM-DID and Placebo tests support the conclusions. Moreover, the greater influence is reflected in the scope of the whole city and the intensity of the permanent plan. The UGB is more susceptible to cities in the central and western areas and cities with weak environmental regulations. Through the mechanism tests, the emission reduction effect of the UGB will be greater in cities with larger vegetation coverage and advanced industry structure. Furthermore, our analysis suggests the UGB needs to be adequately promoted as a policy to achieve carbon neutrality in cities. To make the policy more effective, vegetation cover and industrial structure ought to be taken into consideration. [ABSTRACT FROM AUTHOR]

As the issue of global climate change caused by carbon emissions is of great concern, China has proposed achieving its achieve carbon peak goal by 2030. Building carbon emissions account for approximately 50% of China's total carbon emissions. It is crucial to study the time and values of building carbon peaks. In this paper, based on a system dynamics model, logarithmic mean Divisia index model and Monte Carlo simulation, we predict the building carbon peak in China. The following conclusions are obtained: 1) in the baseline scenario, China's building carbon emissions will peak at 5,427 million tons in 2027. In the high-speed development scenario, China's building carbon emissions will peak at 6,298 million tons in 2032. In the coordinated development scenario, the green development scenario, the low-carbon development scenario, and the low-speed development scenario, the peak occurs in 2030 at 5,972 million tons, 5,991 million tons, 5,657 million tons, and 6,329 million tons, respectively. 2) According to the comprehensive simulation, China's building carbon emissions will reach the peak in 2030, with an 80% probability of reaching 5,729–6,171 million tons. [ABSTRACT FROM AUTHOR]

A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development. [ABSTRACT FROM AUTHOR]

Provinces (cities and districts) with identifiable boundaries are under intense pressure to reduce emissions as a fundamental unit and research object of carbon peaking and carbon-neutrality goals. Due to the significant variability of regional development, achieving equilibrium between carbon emissions and carbon absorption is challenging, contributing to the difficulty of developing carbon emission reduction and relevant green strategic initiatives in China. Therefore, this paper explored the spatial effect of carbon balance with carbon pressure as the starting point. First, this paper defined the "carbon pressure index" (CPI) of 30 provinces (cities and districts) in China from 2000 to 2019. Second, this paper validated the CPI agglomeration evolutionary characteristics in global and local aspects based on the Moran's index. Third, this paper identified and decomposed the spatial heterogeneity of CPI using the kernel density estimation method and the Theil index, then extracted typical cities to analyze the specific causes. Finally, this paper classified the seven regions in China into four types according to a comprehensive analysis of CPI. The results indicated that China's ecological carbon cycle system was in a serious "carbon overload" state. Thirty provinces (cities and districts) showed significant spatial agglomeration characteristics. The spatial gap of CPI was gradually decreasing nationwide, and the intra-regional differences were the leading cause of CPI levels in China. This can provide policy basis for the improvement of China's balanced development system of regional carbon emission reduction. [ABSTRACT FROM AUTHOR]

Taking the data of 30 provinces (excluding Hong Kong, Macao, and Taiwan regions and Tibet) at the provincial level from 2010 to 2019 as the research object, this paper analyzes the current situation and characteristics of China's agricultural modernization and response to carbon emissions. Agricultural modernization is decomposed into production modernization, management modernization, and ecological modernization. This study uses the spatial Dobbin model to demonstrate the impact of agricultural modernization on carbon emissions and analyzes the impact of agricultural modernization on carbon emissions in the East. The direct effect and spatial spillover effect of the three western regions are to different degrees. The results show that agricultural carbon emissions are spatially dependent. The development of agricultural modernization and transportation of neighboring provinces and cities will have an impact on agricultural carbon emissions in this region. Therefore, under the background of rural revitalization and low-carbon agriculture, this paper further analyzes the impact of agricultural modernization on the spatial distribution of carbon emissions in the eastern, central, and western regions. Recommendations are proposed with a view to giving better play to the process of agricultural modernization. [ABSTRACT FROM AUTHOR]

The shadow price of carbon emissions can measure the marginal output effect under the carbon emission regulation and is also one of the key indicators to construct a low-carbon development path for production units. Currently, international research on shadow price is focused on the industrial and energy sectors. However, in the context of carbon peaking and carbon neutrality targets in China, the use of shadow price to study the cost of reducing emissions from agricultural production, especially forestry fruit industries, is significant. In this paper, we use a parametric approach to construct the quadratic ambient directional distance function. Using the input–output data of peach, we then calculate the environmental technical efficiency and shadow price of carbon emissions from peach production in Guangxi, Jiangsu, Shandong, and Sichuan provinces, and further estimate the values of green output in each province. The results show that (i) the environmental technology efficiency of peach production in Jiangsu province, located in the coastal plain area of eastern China, is the highest among the four provinces, while that in Guangxi province, located in the hilly area of southeast China, is the lowest. (ii) Guangxi province has the smallest carbon shadow price of peach production among the four provinces, while Sichuan province, located in the mountainous area of southwest China, has the largest. (iii) The green output value of the peach production in Jiangsu province is the highest among the four provinces, and that in Guangxi province is the lowest. In order to effectively reduce carbon emissions in peach production without affecting economic benefits, the paper puts forward the following suggestions: for peach-producing areas in the southeast hills of China, it is necessary to increase the application of green environmental technology while reducing the input of production factors in peach production. For peach-producing areas in the northern plains of China, the input of production factors should be reduced. It is not easy for peach-producing areas in the southwest mountains of China to reduce the input of production factors while increasing the application of green technologies. Finally, for peach-producing areas in China's eastern coastal plain, the implementation of environmental regulations for peach production should be gradual. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

As a major part of global development governance, G20 countries account for 80% of global carbon emissions. In order to achieve the goal of "carbon neutrality" proposed by the United Nations, it is important to compare and analyze the drivers of carbon emissions in G20 countries and provide recommendations for their carbon emission reduction. Based on the data of 17 G20 countries in the EORA database, this paper compares the drivers of carbon emissions of each country from 1990-2021 using weighted average structural decomposition and K-mean model. This paper focuses on four drivers, including carbon emission intensity, final demand structure, export structure, and production structure. Carbon emission intensity and final demand structure are the main factors of carbon emission reduction, and the other two factors have little influence. Among the G20 countries, the UK is in the first category because it does the best job on the four factors of carbon emissions, yet Italy is in the last category because it does not take full advantage of the four factors. Therefore, improving supply energy efficiency and adjusting demand, export, and industrial structure have become important tools for countries to transform and achieve carbon neutrality. [ABSTRACT FROM AUTHOR]