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Paper mill sludge (PMS) is featured with a high content of cellulose and hemicellulose, and using its characteristics to make paperboard can achieve a high-value utilization of PMS, which has attracted growing interest. In this study, currently prevalent landfill, incineration technologies (generating heat and electricity by incineration), and three paperboard technologies (medium density fiberboard, pulp board, and corrugated paper) were evaluated and compared via life cycle assessment (LCA) and life cycle costing (LCC) methods. LCA results show that the PMS-to-pulp board outperforms others with an energy conservation and emission reduction (ECER) value of − 2.86 × 10−8, while the landfill exhibits the highest overall environmental impact with an ECER value of 4.80 × 10−9. LCC results reveal that the PMS-to-pulp board delivers the highest economic profit with $257.357, while the landfill is the lowest with $ − 35.63. The PMS paperboard technologies are more economically friendly than the incineration technologies due to additional electricity/steam consumption during the PMS pre-drying process in incineration. In addition, different scenarios were set up to explore national GHG emission reduction potential by increasing paperboard technologies application rate and reducing the proportion of landfill and incineration. The scenario analysis suggests that replacing 90% of landfill and incineration ratio with PMS paperboard technologies could tremendously improve the overall emission reduction performance with − 9.08 × 1010 kg CO2 eq. This result indicates that the PMS treatment technology transformation has a significant favorable impact on the achievement of the "carbon neutrality" target. [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]

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]

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]

China, being the world's largest exporter, has now certain environmental commitments such as to achieve carbon neutrality before 2060. These commitments of China has raised a reasonable concern regarding the expected reduction in the production and export of pollution intensive goods in the future. Besides China, the most efficient countries in the region to produce these goods are most of the member countries from ASEAN. The current study therefore aims to analyze if in the future, China reduces the production and export of these goods, whether the selected ASEAN countries can be the next choice for the export of pollution intensive goods. Based on the data availability for the period 1990–2019, this study considers five selected ASEAN countries (ASEAN-5). The results are based on the Auto Regressive Distributive Lag (ARDL) bound testing approach to cointegration and Error Correction Modeling (ECM). The aggregate analysis of five pollution intensive goods (pulp and paper (341), industrial chemicals (351), non-metallic minerals products (369), iron and steel (371) and non-ferrous metals (372)) suggests that Foreign direct investment (FDI) inflow can significantly increase the export of pollution intensive goods only in case of Indonesia, Malaysia and Thailand. However, there is no significant effect of FDI on the export of pollution intensive goods in case of Philippines and Singapore. The disaggregate analyses of the five pollution intensive goods suggest that in each of the ASEAN-5 countries, FDI inflow can significantly increase the export of pollution intensive goods in some of these industries rather than in all of them. In nutshell, it is concluded that ASEAN-5 countries can be a potential choice for the export of pollution intensive goods in some of the pollution intensive industries but not in all of them. [ABSTRACT FROM AUTHOR]

The paper by Kiss and Szalay ([12]) titled I Sensitivity of buildings' carbon footprint to electricity decarbonization: a life cycle-based multi-objective optimization approach i examines how changes in electricity mix impacts GHG emissions. The Intergovernmental Panel on Climate Change (IPCC) emphasizes the need to immediately tackle climate change by significantly reducing greenhouse gas (GHG) emissions and capping global warming at 1.5 °C above pre-industrial levels (IPCC, [8]). The study found that total GHG emissions from maize production were on average 429 ± 27 kg CO2-eq/ton grain, with the highest emissions occurring during the dry season. This SI further contributes to raising awareness to the topic of measuring GHG emissions, decarbonization measures as well as climate neutrality. [Extracted from the article]

The COVID-19 pandemic exacerbated and highlighted the problems and opportunities within the book publishing industry's distribution practices. This is a summary of the Publishing Distribution Practices report, researched and produced in collaboration with Portland State University, Independent Book Publishers Association, and PubWest. This article addresses research and recommendations for becoming carbon neutral, delivering books cost effectively, utilizing print-on-demand, minimizing returns, and examining supply chain issues raised by the pandemic. Findings include starting with paper and emissions assessment for more eco-friendly publishing; emphasizing pre-orders, local and discounted delivery, trade organization membership, and POS systems for cost-effective delivery; limiting outsourcing to restrict supply chain disruptions; reducing print runs and promoting books more effectively to minimize returns; and utilizing print-on-demand for proof copies and gap runs. [ABSTRACT FROM AUTHOR]

This paper investigates the role of digitalization in enhancing wastewater treatment processes, emphasizing its potential to optimize resource utilization, reduce energy consumption, and improve water quality. By examining the implementation of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), the study demonstrates how these tools enable real-time monitoring, predictive maintenance, and intelligent decision-making in wastewater treatment operations. The paper provides a comparative analysis based on key performance indicators (MAPE, RMSE, R2) to evaluate the effectiveness of these digital solutions. Additionally, it discusses the benefits and challenges associated with integrating digital tools in wastewater treatment plants (WWTPs), including cost, complexity, and data security concerns. The study also addresses the impact of digitalization on carbon neutrality goals, highlighting how data-driven approaches can enhance resource allocation and management. By offering insights into current practices and future directions, this paper aims to contribute to the advancement of sustainable wastewater treatment and support the achievement of UN SDG#6, ensuring clean water and sanitation for all. [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]

Energy efficiency (EE) plays an important role in achieving the dual-carbon goal, and improving EE is thus indispensable. This paper evaluates the impact of carbon emission trading policy (CETP) on EE based on a difference-in-difference (DID) method, using 16-year data of 30 provinces and cities from 2005 to 2020. Conclusions are as follows: (1) CETP significantly promotes EE, and this conclusion still appears valid after robustness tests. (2) The positive impact of CETP on EE is more effective in regions of high foreign direct investment (FDI) and high government intervention (GOVI). (3) The positive impact of CETP on EE is through impact mechanisms of energy structure adjustment (ESA), green innovation (GI), and industrial structure upgrading (ISU). The findings in this paper may enrich current research in CETP and offer more pragmatic suggestions for policy advancement as well. [ABSTRACT FROM AUTHOR]

This paper firstly uses the DEA-based Range Directional Model (RDM) and the Global Malmquist–Luenberger (GML) index to calculate the Green Efficiency Index (GEI) of China's cities under the constraints of pollution emissions, energy consumption, and natural resource occupancy. The GEI shows that the average green efficiency of the 285 sample cities achieved a total improvement of 10.1% from 2003 to 2019. The average cumulative improvement rate of green efficiency in the 110 cities in Pollutants Emission Trading Pilot Scheme (PETPS) from 2003 to 2019 was 14.9%, which was higher than the average of non-pilot cities (8.6%). Subsequently, this paper constructs a spatial difference-in-differences model (Spatial-DID) to empirically test the green efficiency promotion effect of PETPS from two aspects: local and spatial spillover. It is found that PETPS can promote the progress of local green efficiency in pilot cities, but there is a spatial spillover effect that is not conducive to the green efficiency progress in surrounding areas. The results of the mediation effect analysis show that the launch of PETPS will significantly reduce the clustering of industrial production activities in the pilot cities, thereby accelerating the green efficiency progress. However, PETPS can also promote clustering of industrial production activities in surrounding areas, thereby inhibiting the green efficiency progress in surrounding areas. These analysis results can fully explain the cause of the negative spatial spillover effect of PETPS. [ABSTRACT FROM AUTHOR]

Energy-saving and environmental protection enterprises (ESEPEs) are one of the most important national green enterprises, and their sustainability has become critical to achieving the goals of carbon peaking and carbon neutrality. Analyzing an enterprise's sustainability over time allows leaders to better adjust the operating plan for the next stage. From both optimistic and pessimistic double frontier perspectives, this paper proposes a double frontier incremental data envelopment analysis (DEA) model based on the traditional DEA-CCR model. The proposed model allows a direct assessment of whether the stage efficiency of the ESEPE is efficient or inefficient. To better understand the ranking of each enterprise in the industry, this paper uses a stage cross-efficiency model based on Shapley value from the perspective of a cooperative game, which ranks the enterprises from a neutral standpoint. The proposed double-frontier incremental DEA model is applied in a stage sustainability assessment for 15 ESEPEs. The results show that the proposed DEA model is more direct than the traditional DEA-CCR model in reflecting the enterprise's stage efficiency. In the three stages, 2012–2015, 2015–2018, and 2018–2021, the majority of the selected 15 ESEPEs have efficient stage efficiency, whereas several enterprises are stage inefficient. The reasons for stage inefficiency stem more from within the enterprise, where the enterprise's working capital is unstable, goodwill is impaired, and so on, resulting in stagnation of various revenues and funding and investment rounds. [ABSTRACT FROM AUTHOR]

Data centers are a major source of carbon emissions and are subsequently contributing to global carbon footprints. Keeping in view of providing a sustainable solution to society, we have analyzed various factors that can help to achieve carbon neutrality and maximum sustainability. Our study pointed towards the need to follow a sustainable approach for incoming workflow throughout the life-cycle of Data centers. We analyzed that workloads need to be segregated before assigning them to the data centers so that energy-efficient resource allocation could be done. This paper demonstrates unsupervised learning techniques to cluster the incoming cloud workloads. The heterogeneous workloads were characterized using machine learning approaches and appropriate clusters were crafted. For analysis, Google Cluster Dataset is used. In order to improve the accuracy, data were normalized, and random samples of data were selected for clustering. The machine learning algorithms applied were able to successfully determine the appropriate clusters that can further be used for energy-efficient resource scheduling. [ABSTRACT FROM AUTHOR]

As the severity of global climate change escalates, carbon peak and carbon neutrality have emerged as international imperatives. Green taxation, a crucial fiscal strategy promoting the transition to a green low-carbon economy, demands thorough investigation regarding its efficacy and operational mechanisms. Predominantly, existing research has concentrated on the macroeconomic implications of green taxes, while their influence on regional green growth and innovation remains underexplored. This paper delineates green taxation in both a broad and narrow sense, elucidating its essence and potential in stimulating regional green progress and innovation. Utilizing panel data from 30 provinces in China spanning 2004 to 2021, a bidirectional fixed-effects model was developed for empirical analysis. Moreover, an impact mechanism model was constructed to delve into how green taxation specifically affects regional green development and innovation. Findings reveal that green taxation significantly fosters regional green growth and markedly enhances green innovation. Nonetheless, due to the resource crowding-out effect, it adversely impacts the comprehensive innovation capabilities of regional enterprises. This insight offers a fresh perspective on the paradoxical effects of green taxation, underscoring the necessity for a balanced approach in policy design and implementation. Drawing on these conclusions, the paper presents tailored policy recommendations. [ABSTRACT FROM AUTHOR]

Copyright of Low-Carbon Materials & Green Construction is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

At the 75th United Nations General Assembly, China formally proposed the goals of achieving carbon peak by 2030 and carbon neutrality by 2060, which is referred to as the "double carbon" strategic goal. And energy revolution is the key to achieve this goal. More and more energy enterprises seek to promote the "double carbon" goal through the digital platformization. However, the mechanism of digital platformization promoting the realization of "double carbon" goal is still unclear. Based on the perspective of platform ecosystem and organization structure, this paper deeply analyzes the key intermediary role of energy production mode change and energy trading mode change in energy transformation. This paper also studies the regulatory effect of policy environment, digital platform characteristics, platform leverage, value chain changes, and the ability of digital technology practice and innovatively puts forward the theoretical model. This model reveals the transmission path and internal mechanism of digital platformization of energy companies to promote the realization of dual-carbon goal. Through the established model, this paper analyzes a case that present the commercial digital platformization process developed by Chinese energy company. Such an innovative process in China context has been developed in order to contribute to achieve "double carbon" goals for the future. [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]

The first paper of this special issue, "Climate Policy and Wealth Distribution" by Dao, [[1]] develops a model with intergenerational bequest transfers and climate damage on the wealth of heterogeneous households. A sound climate policy would have to reduce this "option value of waiting" due to commodity price uncertainties. According to scientific data, climate change and environmental deterioration have become severe issues threatening human society and sustainability. [Extracted from the article]

China is planning to introduce carbon tax policy to control the carbon emissions of the country better and achieve the "3060 goals", but there is still widespread discussion about how to introduce it and how to combine it with cap and trade. China has already established a national carbon emission trading market; however, there is also disagreement on whether to impose the carbon tax on companies and projects that have been included in scope of cap and trade. This paper adopts the research method of experimental economics to study the effect on social economy and social emission reduction under cap and trade, carbon tax, and carbon tax-carbon trading policies, and analyzes average prices of carbon market under cap and trade and carbon tax-carbon trading policies. The study finds that under the carbon tax-carbon trading policy, carbon emissions cannot be reduced significantly; but the profits of manufacturers will be reduced significantly; meanwhile, this reduction effect is even more severe for high consumption manufacturers; and it will be resulting in a lower average carbon market price under the carbon tax-carbon trading policies than under the cap and trade policy. This paper will provide theoretical suggestions for introducing carbon tax policy into China in the future and make policy recommendations for the better development of China's carbon market. [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]

Carbon neutrality has attracted widespread attention as a key strategy for mitigating environmental degradation, but there is little research on whether the development of green finance can contribute to the process of carbon neutrality. This paper proposes a hypothesis based on the relationship between green finance and carbon–neutral performance and empirically tests it using a spatial Durbin model and combining it with a threshold panel model utilizing Chinese provincial sample data from 2011 to 2021. The study found that (1) green finance development would promote carbon–neutral performance; (2) there are notable spatial characteristics of green finance and carbon neutrality performance, with local green finance impacts both local and neighboring carbon–neutral performance; and (3) green finance impacts carbon–neutral performance at a single threshold and different levels of green finance development affect carbon–neutral performance differently. In the eastern, central, and western regions, the contribution of green finance to carbon–neutral performance gradually decreases. Thus, Chinese authorities should strengthen the green sustainable financing system, promote regional green finance, and enhance the carbon–neutral performance of green finance. [ABSTRACT FROM AUTHOR]

Controlling agricultural carbon emissions contributes to achieving peak carbon emissions and carbon neutrality. However, as a conservation management practice of farmland, the impact of No-tillage management (NTM) on agricultural carbon emissions needs to be further discussed. The main purpose of this paper is to assess the direct effect and spatial spillover effect of NTM on agricultural carbon emissions, revealing the regulating mechanism of NTM on agricultural carbon emissions and the combined application of NTM. Results indicate that NTM reduces agricultural carbon emissions, which is significant in the central and western regions, along with the primary grain, corn, and rice production areas, as well as the northern regions of the Huai River. Furthermore, the spatial spillover analysis reveals that the implementation of NTM increases agricultural carbon emissions in neighboring regions, but financial support and cross-regional services can negatively regulate the relationship between NTM and space agricultural carbon emissions. This paper also finds that combining straw-returning technology and NTM reduces agricultural carbon emissions. Building a cross-regional coordination mechanism, an incentive mechanism, and innovating the conservation tillage model is essential for promoting the NTM and achieving agricultural carbon reduction. [ABSTRACT FROM AUTHOR]

Using panel data for 277 Chinese cities, this paper applies a time-varying difference-in-differences (DID) model to empirically test the impact of China's carbon emissions trading scheme (ETS) on urban air quality, and further explores its heterogeneity and the mechanisms involved. The results show that ETS can improve urban air quality. This conclusion remains robust through a series of robustness tests, including PSM-DID estimation, varying window periods, exclusion of significant events, lag phase, and placebo tests. The dynamic effect test indicates that ETS has a continuous and effective effect on improving urban air quality. Mechanism analysis reveals that the degree of marketization can enhance the improvement effect that ETS has on urban air quality. Meanwhile, industrial structure upgrading and green technology innovation are important mechanisms by which pilot ETS policy improves urban air quality. Regional heterogeneity analysis finds that ETS only improves urban air quality in eastern and central regions. [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]

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]

The double-carbon goal proposal has made it imperative for China's power industry to address the urgent issue of reducing greenhouse gas emissions from coal-fired power plants and promoting their clean and efficient use. A new approach to achieving peak-shaving and improving grid stability is the combination of carbon capture and storage (CCS) facilities with coal-fired power plants, which offers a strategic solution for mitigating climate change. Nonetheless, the viability of CCS retrofitting for coal-fired power plants in China hinges on its economic feasibility. The technical characteristics, economic analysis, and policy implications of clean coal-fired power plant equipped with CCS (CCP-CCS) technologies are evaluated in the paper. A comparison of the characteristics of different clean coal power generation technologies, including capacity, efficiency, coal consumption, and environmental performance, is conducted. The paper analyzes the economic feasibility of four typical clean coal power generation technologies, namely Supercritical (SC), Ultra-supercritical (USC), Integrated Gasification Combined Cycle (IGCC), and Circulating Fluidized Bed (CFB), both with and without CCS, using the levelized cost of electricity (LCOE) model. Financial parameters, investment parameters, operation and maintenance parameters, tax parameters, and capacity parameters are all considered in the LCOE model. The results indicate: (1) If CCS is not installed, the LCOE of USC power plants is the lowest at 0.37 yuan/kWh, while the LCOE of IGCC power plants is the highest at 0.44 yuan/kWh. (2) If CCS is installed, the LCOE of CFB units is the highest at 0.74 yuan/kWh, while the LCOE of USC units is the lowest at 0.60 yuan/kWh. (3) In sensitivity analysis, coal prices have the most significant impact on LCOE, followed by expected annual operating hours, while the cost of carbon capture equipment is the least sensitive. (4) The cost of retrofitting CCS on clean coal-fired power plants (CCP) is currently high, with an LCOE increase of around 40 to 70%, which is comparable to that of renewable energy electricity. This paper presents policy recommendations, including preferential loans, tax incentives, and R&D funding, to promote the development of CCP in China based on the economic analysis results and challenges faced by CCP. Additionally, the paper proposes relevant policy implications such as preferential loan policies, a diversified financing system, R&D and innovation, and the establishment of a carbon trading market for CCS in China to provide practical guidance for the promotion of CCP-CCS technologies in China. [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]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The state of New York admitted 143 million metric tons of carbon emissions from fossil fuels in 2020, prompting the ambitious goal set by the CLCPA to achieve carbon neutrality. The paper focused on analyzing and predicting carbon emissions using four different machine-learning algorithms. It examined emissions from fossil fuel combustion from 1990 to 2020 and validated four different algorithms to choose the most effective one for predicting emissions from 2020 to 2050. The analysis covered various economic sectors including transportation, residential, commercial, industrial, and electric power. By analyzing policies, the paper forecasted emissions for 2030 and 2050, leading to the identification of different pathways to reach carbon neutrality. The research concluded that in order to achieve neutrality, radical measures must be taken by the state of New York. Additionally, the paper compared the most recent data for 2021 with the forecasts, showing that significant measures need to be implemented to achieve the goal of carbon neutrality. Despite some studies assuming a trend of decreased emissions, the research revealed different results. The paper presents three pathways, two of which follow the ambitious plan to reach carbon neutrality. As a result, the emission amount by 2050 for the different pathways was projected to be 31.1, 22.4, and 111.95 of MMt CO2 e, showcasing the need for urgent action to combat climate change. [ABSTRACT FROM AUTHOR]

Traction power systems (TPSs) play a vital role in the operation of electrified railways. The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target. On the basis of sorting out the power supply structures of conventional AC and DC modes, this paper first reviews the characteristics of the existing TPSs, such as weak power supply flexibility and low-energy efficiency. Furthermore, the power supply structures of various TPSs for future electrified railways are described in detail, which satisfy longer distance, low-carbon, high-efficiency, high-reliability and high-quality power supply requirements. Meanwhile, the application prospects of different traction modes are discussed from both technical and economic aspects. Eventually, this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system, speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode, employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy. [ABSTRACT FROM AUTHOR]

Low-carbon policies are essential for facilitating manufacturing industries' low-carbon transformation and achieving carbon neutrality in China. However, recent studies usually apply proxy variables to quantify policies, while composite indices of policy intensity measured by objectives and instruments focus more on the national level. It is deficient in direct and comprehensive quantification for low-carbon policies. Hence, having extended the meaning of policy intensity, this paper constructs a low-carbon policy intensity index quantified by policy level, objective and instrument via phrase-oriented NLP algorithm and text-based prompt learning. This process is based on the low-carbon policy inventory we built for China's manufacturing industries containing 7282 national-, provincial- and prefecture-level policies over 2007–2022. Lastly, we organize the dataset in two formats (.dta and.xlsx) for multidiscipline researchers. Apart from the inventory and intensity for each policy, the policy intensity is also aggregated to national-, provincial- and prefecture-level with sub-intensity for four objectives and three instruments. This dataset has potential uses for future studies by merging with macro and micro data related to low-carbon performances. [ABSTRACT FROM AUTHOR]

In order to realize the intelligent energy management of the complex ship energy system, achieve the carbon peaking and carbon neutrality goal and reduce the ship carbon emissions and ship operating costs, this paper proposes a distributed energy management method for ships entering and leaving ports based on polymorphic network considering computing power resources. Firstly, a polymorphic network-based energy management system for ships entering and leaving ports is proposed to enhance the information exchange between ship computing power, power and port power, simultaneously improve the communication quality and communication security among different modes. Secondly, in order to reduce the ship operating costs and port carbon emissions, the energy management model of ships entering and leaving ports is constructed considering computing power resources. Then, according to the ship's berthing and departing operation modes, this paper uses the distributed algorithm to solve the energy management problem, and explores the impact on the ship microgrid when the ship's data load changes. Finally, simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Carbon emission trading has been actively applied in many countries, and its operational effect has received widespread attention. However, previous studies mostly focused on single environmental effect, and the investigation of the comprehensive environmental effect needs to be further supplemented. Based on this, this paper explores the comprehensive environmental effect of carbon emission trading with eco-efficiency as the starting point. First, this paper measures eco-efficiency using the super-efficient minimum distance to strong efficient frontier (MinDS) model with undesirable outputs. Second, this paper uses the propensity score matching difference in difference (PSM-DID) model to quantify the effect of carbon emission trading on eco-efficiency. Finally, this paper examines the mediating mechanism of the effect of carbon emission trading on eco-efficiency based on the mediating effect model. The results show that carbon emission trading can improve the level of urban eco-efficiency. Energy savings and increased efficiency effectively mediate the promoting effect of carbon emission trading on eco-efficiency. The mediating push effect of R&D innovation and industrial structure restructuring has not yet appeared. This paper can not only provide policy basis for the improvement of carbon emission trading market but also provide reference for the construction of carbon emission trading market in developing countries. [ABSTRACT FROM AUTHOR]

The collection of papers in this special issue examines empirical evidence from Asia, Europe, and North America, analyzes how climate change affects the spatial economy, and explores the feasibility of carbon neutrality as a countermeasure to climate change. It begins by discussing the research background, the motivation for emphasizing spatial considerations, and the analysis in climate change studies. Each accepted paper is then elaborated upon regarding topic selection, methodology, and findings. The issue highlights the crucial role of spatial elements in climate studies and aims to inspire further research in this direction. By leveraging regional science and analytical tools, the goal is to develop more effective and equitable policies for carbon abatement. [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]

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]

With the acceleration of urbanization and industrialization, carbon neutrality and peak carbon dioxide emissions have become common sustainability goals worldwide. However, there are few literature statistics and econometric analyses targeting carbon neutrality and peak carbon dioxide emissions, especially the publication trends, geographic distribution, citation literature, and research hotspots. To conduct an in-depth analysis of existing research fields and future perspectives in this research area, 1615 publications from the Web of Science Core Collection, between 2010 and 2020, were evaluated by using three analysis tools, under the framework of the bibliometrics method. These publications are distributed between the start-up (2010–2015) and the stable development (2016–2020) phases. Cluster analysis suggests three areas of ongoing research: energy-related carbon emissions, methane emissions, and energy biomass. Overall, future trends in this field include cumulative carbon emissions, the residential building sector, methane emission measurement, nitrogen fertilization, land degradation neutrality, and sciamachy satellite methane measurement. Finally, this paper further examines the most comprehensive coverage of nitrogen fertilization and the most recent research of the residential building sector. In view of the statistical clusters from 1615 publications, this paper provides new insights and perspectives for climate-environment-related researchers and policymakers. Specifically, countries could apply nitrogen fertilizer to crops according to the conditions of different regions. Additionally, experiences from developed countries could be learned from, including optimizing the energy supply structure of buildings and increasing the use of clean energy to reduce CO2 emissions from buildings. [ABSTRACT FROM AUTHOR]

This paper explores the spatial impact effects and spatio-temporal heterogeneity of the digital economy on urban carbon emissions (CO2). Specifically, firstly, the Digital Economy Index (DEI) system of 285 cities in China was constructed and the Global Principal Component Analysis (GPCA) was applied to evaluate the digital economy level of Chinese cities. Based on spatial correlation and spatial heterogeneity, the paper explores the global spatial impact and spatio-temporal heterogeneity of the impact of digital economy on CO2 using spatial Durbin model (SDM) and geographic time-weighted regression (GTWR), respectively. And the mechanism variables are used to further demonstrate the mechanism effect and nonlinear characteristics of the impact of digital economy on CO2. The findings indicate that (1) the advancement of the digital economy is beneficial for achieving carbon abatement goals, and the impact of the digital economy on CO2 mitigation remains stable across several robustness tests. (2) The spatial spillover effect of the digital economy on the impact of carbon reduction is not significant. And there is significant temporal and spatial heterogeneity in the impact of the digital economy on carbon emissions. (3) According to the mechanism analysis, the digital economy reduces carbon emissions by encouraging the development of green technologies and promoting the modernization of industrial structures. And there are non-linear characteristics of this effect. This study concludes that the digital economy can support China's goal of achieving "carbon peak and carbon neutrality." However, it is important to consider the differences in urban development over time and space. Leveraging the city's strengths to develop a digital economy in a unique way that will help achieve China's carbon reduction goals. [ABSTRACT FROM AUTHOR]

Based on the background of carbon neutrality targets, panel data of 30 Chinese provinces during 2000–2019 were selected in this paper to explore the nonlinear correlation mechanism among transportation, tourism development, renewable and non-renewable energy consumption and economic growth. Firstly, by employing a fixed effects model as the base model, we confirmed the existence of correlations among these variables. And the nonlinear moderating effects were also verified by setting interaction terms in the model. Secondly, we further discussed the characteristics of the nonlinear relationship among the variables by employing a threshold effects model. Our results demonstrated that the effect of transportation on economic growth is positive and significant if and only if renewable energy consumption surpasses a certain threshold. Meanwhile, we also found that the effect of tourism development on economic growth is positive when non-renewable energy consumption is under a certain threshold. Finally, our study indicated that transportation maintains a positive and significant effect on economic growth within any threshold of tourism development, and the positive effect gradually increases as the threshold rises. The findings of this paper suggested that for China, the contribution of transportation and tourism to economic growth can be expanded by further expanding the substitution of renewable energy for non-renewable energy. [ABSTRACT FROM AUTHOR]

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment. [ABSTRACT FROM AUTHOR]

This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period. [ABSTRACT FROM AUTHOR]

The renewable energy+energy storage model has an important role to play in achieving China's proposal of the carbon peaking and carbon neutrality goal. In order to study the development mechanism of renewable energy+storage cooperation with government participation, this paper constructs a three-party evolutionary game model among government, renewable energy generators, and energy storage service suppliers, based on the data of a renewable energy+storage project in a Chinese province. In this paper, we analyze the game process and the factors affecting the behavioral strategies of the three parties through numerical simulation. The study shows that the government regulation has a positive effect on the cooperative development of renewable energy+energy storage, and it can effectively restrain the wasteful phenomenon of renewable energy generation by means of punishment and improve the operating income of cooperative projects by means of subsidies, which can help the enterprises to broaden the application scenarios of energy storage. The government can effectively promote the improvement of renewable energy+energy storage cooperation mechanism by formulating regulatory mechanism, controlling the cost of supervision, and dynamically adjusting the intensity of supervision. Therefore, the research in this paper not only enriches the research related to renewable energy+energy storage mode but also provides valuable reference for the government to formulate regulatory policies related to renewable energy+energy storage. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between digital finance and carbon emissions and explores the ecological effects of digital finance. Based on a panel data of 256 cities in China from 2011 to 2018, this paper investigates the impact of digital finance on carbon emissions and its intrinsic mechanisms. First, digital finance significantly suppresses the intensity of regional carbon emission, and the breadth of coverage, depth of use, and degree of digital support of digital finance together curb regional carbon emissions, with the strongest suppressive effect being the breadth of coverage. In addition, the regression results remain significant after a series of robustness tests. Second, it reveals the potential mechanism of digital finance to curb urban carbon emissions. These mechanisms include the three channels: promoting industrial advancement, green technology innovation, and optimizing labor resource allocation. Third, the heterogeneity test finds that the energy saving and emission reduction effects of digital finance are significantly stronger in non-low-carbon pilot cities with low urbanization rates, confirming the emission reduction utility of digital finance development. Therefore, we should take advantage of digital finance to improve the green development of financial services and adopt diverse policy measures according to local conditions to maximize the ecological effects of digital finance on energy saving and emission reduction. In the context of the development strategy of "carbon peaking and carbon neutral," this study has some implications for management in developing a regional green development system supported by digital finance. [ABSTRACT FROM AUTHOR]

Guiding individuals to adopt pro-environmental behaviors is critical to achieving carbon neutrality goals. Public policy targeted at a small number of people may be amplified by interpersonal interaction, making peer effect a potentially useful tool for accelerating problem solving. However, previous studies have paid insufficient attention to the influence of peers on university students' energy-saving behaviors. This paper attempts to examine the effect using a large-scale survey dataset conducted on students from Xiamen University in China and the classical linear-in-means model. The result shows that peers' pro-environmental behaviors have positive effect on individuals. The heterogeneity of the influence and the potential mechanisms are also explored. This paper contributes to very important and still growing literature dealing with contagion processes in pro-environmental behaviors. The policy implication is that the government should make full use of the peer effect to maximize the benefits of energy-conservation campaigns. [ABSTRACT FROM AUTHOR]

Utilizing a dynamic computable general equilibrium (CGE) model, this paper critically assesses the potential distortions and efficacy of various revenue-neutral carbon emission trading schemes (ETSs) in China, through government subsidies and value-added tax (VAT) relief strategies aimed at achieving peak carbon emissions before 2030. The analysis reveals that reallocating market revenues to the production sector, either through government subsidies or VAT reductions, can feasibly attain carbon peaking before 2030, with minimal impact on GDP. Notably, both government subsidies and VAT cuts foster output growth in the oil, gas, and ETS-covered sectors. Moreover, directing carbon market revenue toward ETS-covered industries via VAT relief emerges as the most effective approach to reducing income disparities. In contrast, redistributing carbon market revenue to non-ETS-covered industries via VAT relief is found to be the least effective in promoting social equity. The study emphasizes that the reallocation of carbon market revenues to ETS-covered sectors is paramount. This strategy not only regulates the overall energy consumption effectively but also steers the nation towards a more sustainable and optimized energy consumption pattern. In light of these findings, this paper offers detailed insights and tailored policy recommendations, aiming to assist policymakers in striking a balance between environmental goals and economic and social imperatives. [ABSTRACT FROM AUTHOR]

The challenges posed by climate change, biodiversity loss, and land-use are deeply interconnected and integrated solutions are needed. This paper presents results from 11 contributions to a special issue covering topics of integrated modeling and spatial prioritization, mass-balance studies, Earth Observation techniques, research infrastructure developments, and evaluation of policy measures and economic compensation schemes. The spatial scale of the studies ranges from detailed site-specific to a European scale. This paper briefly summarizes the main findings of these studies, makes some general overall conclusions, and identifies topics for further research and methods developments. [ABSTRACT FROM AUTHOR]

In recent years, excessive emissions of carbon dioxide have further intensified global warming, which poses a great threat to human society. The best way to reverse this situation is to take action to equalize the "carbon emissions" with the "carbon absorption," i.e., carbon neutrality (CN). To better understand the evolution and display a broad panorama of CN research, this paper provides a comprehensive bibliometric analysis of publications in the field of CN from 2006 to 2021. We use the Web of Science Core Collection as the data source, and a total of 633 publications have been retrieved. In the paper, we measure the productivity and influence of publications through recognized bibliometric metrics, and visually analyze publications using VOS Viewer and CiteSpace. The analysis results show that China is the most productive country/region. The study illustrates that in order to reach the goal of CN, it is necessary to reduce carbon emissions such as full using renewable energy. Simultaneously, it is also essential to enhance the "negative emissions" of carbon such as taking advantage of carbon sink and carbon capture, utilization, and storage. This paper provides some references for scholars who are interested or research in this field. [ABSTRACT FROM AUTHOR]