Search

Increased ecological land (IEL) such as forests and grasslands can greatly enhance ecosystem carbon sinks. Understanding the mechanisms for the magnitude of IEL-induced ecosystem carbon sinks is crucial for achieving carbon neutrality. We estimated the impact of IEL, specifically the increase in forests and grasslands, as well as global changes including atmospheric CO 2 concentration, nitrogen deposition, and climate change on net ecosystem productivity (NEP) in National Key Ecological Function Zones (NKEFZs) in China using a calibrated ecological process model. The NEP in NKEFZs in China was calculated to be 119.4 Tg C yr -1 , showing an increase of 42.6 Tg C yr -1 from 2001 to 2021. Compared to the slight contributions of climate change (-8.0%), nitrogen deposition (11.5%), and reduction in ecological land (-3.5%), the increase in NEP was primarily attributed to CO 2 (66.5%) and IEL (33.5%). Moreover, the effect of IEL (14.8 Tg C yr -1 ) surpassed that of global change (13.1 Tg C yr -1 ) in the land use change zone. The IEL-induced NEP is significantly associated with CO 2 fertilization, regulated by precipitation and nitrogen deposition. The high values of IEL-induced NEP occurred in areas with precipitation exceeding 800 mm and nitrogen deposition exceeding 25 kg N ha -1 yr -1 . We recommend prioritizing the expansion of ecological land in areas with sufficient water and nutrients to enhance CO 2 fertilization, while avoiding increasing ecological land in regions facing unfavorable climate change conditions. This study serves as a foundation for comprehending the NEP response to ecological restoration and global change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study provides first evidence on the effects of Chinese FDI (Foreign Direct Investment) outflows on host country environments. The study draws upon a comprehensive dataset covering aggregate Chinese FDI outflows and sector specific data into 65 host nations over the 2007-2019 period. Employing a STIRPAT (Stochastic Regression on Population, Affluence and Technology) model and several different techniques including DID (Difference-in-Difference), pooled OLS (Ordinary Least Squares), quantile regression, IV (Instrumental Variable) estimation, threshold and Tobit regression, the findings suggest that Chinese FDI leads to an increase in host country CO2 (Carbon Dioxide) emissions, aligning with the pollution haven hypothesis at the aggregate level. A closer investigation at the development regime and sectoral levels indicates that in the low development regime, FDI inflows into the financial and real estate sector increase emissions. Conversely in the high-income regime, Chinese FDI into the entertainment sector is associated with an increase in carbon emissions. Chinese FDI is further found to lead to an increase in emissions in countries with a per capita GDP (Gross Domestic Product) of below USD72041.7. However, as per capita income rises above USD72041.7, FDI leads to a fall in carbon emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Carbon dioxide (CO 2 ) production and emissions from inland waters play considerable roles in global atmospheric CO 2 sources, while there are still uncertainties regarding notable nutrient inputs and anthropogenic activities. Urban inland waters, with frequently anthropogenic modifications and severely nitrogen loadings, were hotspots for CO 2 emissions. Here, we investigated the spatiotemporal patterns of partial pressure of CO 2 (pCO 2 ) and CO 2 fluxes (FCO 2 ) in typical urban inland waters in Tianjin, China. Our observation indicated that pCO 2 values were oversaturated in highly polluted waters, particularly in sewage rivers and urban rivers, exhibiting approximately 9 times higher than the atmosphere equilibrium concentration during sampling campaigns. Obviously, the spatiotemporal distributions of pCO 2 and FCO 2 emphasized that the water environmental conditions and anthropogenic activities jointly adjusted primary productivity and biological respiration of inland waters. Meanwhile, statistically positive correlations between pCO 2 /FCO 2 and NH 4 + -N/NO 3 - -N (p < 0.05) suggested that nitrogen biogeochemical processes, especially the nitrification, played a dominant role in CO 2 emissions attributing to the water acidification that stimulated CO 2 production and emissions. Except for slight CO 2 sinks in waters with low organic contents, the total CO 2 emissions from the urban surface waters of Tianjin were remarkable (286.8 Gg yr -1 ). The results emphasized that the reductions of nitrogen loadings, sewage draining waters, and agricultural pollution could alleviate CO 2 emissions from urban inland waters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

China proposed establishing a carbon emission trading market in its 12th Five-Year Plan to reduce carbon dioxide emissions through market mechanisms, promote the development of science and technology and help China become an environment-friendly country. To examine the impact of carbon emission trading on green technology innovation in Chinese energy enterprises, data from 1993 to 2020 were collected from 494 A-share-listed energy enterprises. Enterprises located in the pilot area of carbon emissions trading were assigned to the treatment group, while those in the non-pilot area were assigned to the control group. The propensity-score-matching method was utilized to match the treatment group with the control group, and the resulting samples were used as the actual sample data. The difference-in-differences method was then employed to assess the net impact of carbon emission trading and investigate its effect on green technology innovation in energy enterprises. This empirical study suggested that carbon emission trading has a positive impact on green technology innovation in energy enterprises, particularly state-owned ones. Larger enterprises are more willing to engage in green technological innovation than small enterprises. Furthermore, when faced with a carbon emission trading system, 'mature' companies tend to pay more attention to green technology innovation than younger enterprises do. This study puts forward policy measures for establishing a national-level carbon emission market in China in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study investigates the influence of foreign direct investment (FDI), financial development (FD), and governance on carbon emissions in 15 emerging Asian economies (EAEs) from 2000 to 2021. It aims to assess how successful these nations have been in upholding ecological sustainability while promoting themselves as alternative manufacturing destinations to China and fostering domestic manufacturing through significant financial development. It creates a composite governance quality (GQ) measure and three subdimensions-EcoGov, InstGov, and PolGov-to assess its precise role in influencing the FDI-carbon dioxide (CO 2 ) and FD-CO 2 nexuses. Using fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) panel cointegration techniques, this study yielded findings revealing that FDI and FD significantly enhance carbon emissions. The overall GQ significantly moderates the FD-CO 2 nexus but fails to moderate FDI's detrimental environmental influence. More specifically, EcoGov significantly moderates FDI's and FD's influence on carbon emissions, whereas InstGov significantly enhances their influence on emissions. In contrast, PolGov is only found to moderate FD's impact on environmental quality since the Government frequently endorses liberal environmental regulations to facilitate FDI-led growth. The findings from this study are robust and carry distinct policy ramifications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In order to fully understand the carbon emission from different fuels in rural villages of China, especially in the typical atmospheric pollution areas. The characteristics of carbonaceous aerosols and carbon dioxide (CO 2 ) with its stable carbon isotope (δ 13 C) were investigated in six households, which two households used coal, two households used wood as well as two households used biogas and liquefied petroleum gas (LPG), from two rural villages in Fenwei Plain from March to April 2021. It showed that the fine particulate matter (PM 2.5 ) emitted from biogas and LPG couldn't be as lower as expected in this area. However, the clean fuels could relatively reduce the emissions of organic carbon (OC) and element carbon (EC) in PM 2.5 compare to the solid fuels. The pyrolyzed carbon (OP) accounted more total carbon (TC) in coal than the other fuels use households, indicating that more water-soluble OC existed, and it still had the highest secondary organic carbon (SOC) than the other fuels. Meantime, the coal combustions in the two villages had the highest CO 2 concentration of 527.6 ppm and 1120.6 ppm, respectively, while the clean fuels could effectively reduce it. The average δ 13 C values (-26.9‰) was much lighter than almost all the outdoor monitoring and similar to the δ 13 C values for coal combustion and vehicle emission, showing that they might be the main contributors of the regional atmospheric aerosol in this area. During the sandstorm, the indoor PM 2.5 mass and CO 2 were increasing obviously. The indoor cancer risk of PAHs for adults and children were greater than 1 × 10 -6 , exert a potential carcinogenic risk to human of solid fuels combustion in rural northern China. It is important to continue concern the solid fuel combustion and its health impact in rural areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The transition of the current fossil based chemical industry to a carbon-neutral industry can be done by the substitution of fossil carbon for defossilized carbon in the production of base chemicals. Methanol is one of the seven base chemicals, which could be used to produce other base chemicals (light olefins and aromatics). In this research, we evaluated the synthesis of methanol based on defossilized carbon sources (maize, waste biomass, direct air capture of CO 2 (DAC), and CO 2 from the cement industry) by considering carbon source availability, energy, water, and land demand. This evaluation was based on a carbon balance for each of the carbon sources. Our results show that maize, waste biomass, and CO 2 cement could supply 0.7, 2, 15 times the carbon demand for methanol respectively. Regarding the energy demand maize, waste biomass, DAC, and CO 2 from cement demand 25, 21, 48, and 45GJton MeOH separately. The demand for water is 5300, 220, 8, and 8m 3 ton MeOH . And lastly, land demand was estimated to 1031, 36, 83, and 77m 2 ton MeOH per carbon source. The high-demanding-resource production of defossilized methanol is dependent on the availability of resources per location. Therefore, we analyzed the production of defossilized methanol in the Netherlands, Saudi Arabia, China, and the USA. China is the only country where CO 2 from the cement industry could provide all the demand of carbon. But as we envision society becoming carbon neutral, CO 2 from the cement industry would diminish in time, as a consequence, it would not be sufficient to supply the demand for carbon. DAC would be the only source able to provide the demand for defossilized carbon., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Fast development of farming practices in China is projected to result in additional carbon emissions and thus affect farmland ecosystems' environmental performance. Based on 454 farm surveys on the North and Northeast China Plain, the carbon footprint (CF) of two farmland ecosystems (irrigated system for wheat and maize on the North China Plain and rainfed system for maize on the Northeast Plain) were assessed and emission reduction pathways explored by quantifying greenhouse gas emissions of agricultural inputs and farm practices during the entire crop growing seasons with an agricultural footprint model. The results demonstrated that the GHG emissions from wheat and maize rotation in the irrigated system were 7.63 t CO 2 eq ha -1 and 3.17 t CO 2 eq ha -1 for single season maize in the rainfed system. While energy consumption accounted for 12.5%-21.3% of the carbon footprint in both systems, the group assessment found that the largest difference in GHG emissions between the high and low emission groups came from mechanical energy consumption. Approximately 50.6% and 39.2% of the mechanical carbon footprint of wheat and maize, respectively, were caused by irrigation practices in the irrigated system. Regarding the rainfed system, where 46.6% of mechanical carbon emissions were generated by maize tillage operations. In addition, scenario analysis indicated that the mechanical carbon footprint could be reduced to 56 kg CO 2 eq t -1 for NCP-wheat and 26 kg CO 2 eq t -1 for NCP-maize, respectively, by optimizing yields and irrigation practices in irrigated systems and that the mechanical carbon footprint of NEP-maize could be reduced to 25 kg CO 2 eq t -1 by optimizing yields and tillage practices in rainfed systems. Therefore, improvement in mechanization in irrigation and tillage practices can contribute to reduce GHG emissions in China. Water-saving irrigation technology is recommended in irrigated area and conservation tillage is recommended in rainfed agricultural area to reduce carbon footprints., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dongyu Cai reports financial support was provided by the National Key Research and Development Program of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Population aging and global warming have become everyday concerns of all countries. Based on the panel data of 30 provinces in China from 2003 to 2019, this paper uses the panel fixed effect model and two-stage least square method to analyze the effect of population aging on domestic energy carbon emissions of urban and rural residents. On this basis, the threshold regression model is introduced to explore the heterogeneity of the effect under different aging levels. The results show that (1) the progress of population aging at the overall level will significantly increase the level of carbon emissions from household energy consumption. At the regional level, the effect of population aging on carbon emissions from household energy consumption in rural areas is higher than in urban areas. (2) Population aging has a nonlinear effect on the carbon emissions of residential energy consumption. For urban areas, when the level of population aging crosses the threshold, its marginal impact on living carbon emissions in urban areas is further enhanced. In contrast, the opposite is true in rural areas. (3) Heterogeneity analysis results show that the impact of population aging on residential energy carbon emissions differs in different regions at the national and rural levels but does not show regional heterogeneity at the urban level., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Soil respiration (Rs) is a crucial ecological process of carbon (C) cycling in the terrestrial ecosystems, and soil erosion has a significant impact on its C budget and balance. However, the variations of Rs rate and their CO 2 efflux induced by erosion are currently poorly understood. To this end, four landscape positions (top, up, middle and toe) with different erosional and depositional characteristics were selected on a typical eroded slope in southern China to conduct field experiments, aiming to explore the effects of erosion and deposition on Rs among various sites. From March 2021 to February 2022, the in-situ Rs were measured using an automated soil respiration system, together with soil temperature at 5 cm depth (T s5 ) and water content at 10 cm depth (SWC 10 ). We initially constructed various Rs models across a one-year period, based on its relationships with T s5 and SWC 10 . Subsequently, the seasonal changes of Rs at different erosional sites were simulated by the optimum models, and their annual CO 2 fluxes were further estimated. The results showed that Rs rates at all sites displayed a bimodal seasonal pattern, with the highest values in May and August. And the measured Rs of the eroding and depositional sites were 0.05-7.71 and 1.47-13.03 μmol m -2  s -1 , respectively. Also, remarkably higher T s5 and SWC 10 were observed in depositional sites versus the eroding sites (P < 0.05). Additionally, Rs rates at all sites were positively correlated with SOC and T s5 , but negatively correlated with SWC 10 . Herein, Rs models to single- and double-variable were established at different positions, and we found that the fitted R 2 and AIC differed on various sites, primarily in erosional and depositional sites. Furthermore, through the best-fitting models (higher R 2 and lowest AIC) we screened, the average Rs values of 3.03 and 4.46 μmol m -2  s -1 were quantitatively estimated for the eroding and depositional sites, respectively. Finally, it could be further assessed that the mean annual soil CO 2 -C efflux of eroded site (1104.14 g m -2 ) was significantly lower than that of depositional site (1629.46 g m -2 ). These findings highlighted the effect of erosion and deposition on Rs, which will facilitate a better understanding of C cycling in terrestrial ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Investigating the CO 2 abatement potential of urban residential building from systematic perspective is essential to reach the urban carbon neutrality target. However, previous studies on building CO 2 emission trend forecasting were mainly focused on the building operational phase. In this study, a new framework that includes four building stages under a system dynamic model is developed to simulate urban residential building carbon emission changes and the related reduction potentials under three scenarios in Jiangxi Province up to 2060. Results showed that the overall process carbon emission dynamic had already peaked in 2014 under the three scenarios, with a peak value of 38.52 Mt. It then fell to 9.56 Mt in 2060 under the baseline (BAU) scenario. More importantly, seven carbon abatement measures were adopted during four building activities in this study, and the total carbon reduction was not the sum of the carbon reduction potential of the individual measures. Some carbon abatement strategies displayed synergistic effects such as low-carbon electrification where the combination of electrification and clean energy power generation was the largest contributor to reduced carbon emissions during building operation as a comprehensive carbon reduction measure. By contrast, extending a building's lifetime restrained the carbon abatement potential during the demolition stage, and it inhibited the carbon emission reduction by 24.84 Mt. These results highlight the significant need for effective policy interventions for clean production and the need to improve prefabricated building proportions, promote electrification, improve energy efficiency, strengthen recycling practices, and extend building lifetimes to promote decarbonization of urban residential building system development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Household consumption carbon emissions (HCCEs) have become the main growth point of China's carbon emissions in the future. It is important to investigate the factors affecting the demand-side carbon emissions in order to find the accurate entry point of emission reduction and achieve carbon peaking and carbon neutrality goals. Different from previous studies, this study analyzed the spatial and temporal evolution characteristics of provincial HCCEs in China from a spatial perspective by using the Theil index and spatial auto-correlation and explored the key influencing factors and spatial spillover effects of HCCEs in different regions by using an econometric model. The results of the study showed that: (1) Per capita HCCEs increased by 11.90% annually, and the eastern region > northeastern region > western region > central region. (2) There were regional differences in per capita HCCEs, but the decrease was significant at 40.32%. (3) The spatial agglomeration effect of per capita HCCEs was significant, and the hot spots were mainly concentrated in the eastern coastal areas. (4) From the national level, every 1% increase in residents' consumption power would increase HCCEs by 2.489%. Which was the main factor for the growth of HCCEs, while the increase in fixed asset investment would restrain HCCEs. At the regional level, the change in population size significantly increased the HCCEs in the eastern and central regions. While for the western region, a 1% increase in population would reduce the HCCEs by 0.542%. For the eastern and central regions, the degree of aging and the consumption structure of residents could suppress regional HCCEs. However, the consumption structure of residents drove the growth of HCCEs in the western region. For the Northeast region, residents' consumption capacity and cooling degree days were the main factors for the growth of residents' consumption, while fixed asset investment could inhibit the growth of HCCEs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Since large carbon emissions are transferred through international trade, it is vital to explore the role country-specific trade policy has on carbon-intensive industries. The present study contributes to a deeper understanding of the connection between trade and environment in the literature, especially the impacts of trade barriers on carbon emissions. This topic has received little attention despite the importance of trade barriers to climate change and carbon emissions. Thus, we investigate the asymmetric trade barriers in carbon-intensive industries across different countries and describe the facts and motivations of these trade barriers in carbon-intensive industries. We list some political and trade explanations for the existence of trade barriers and empirically test the impacts of interest groups on trade barriers by the IV-2SLS method. Further, we have observed that certain highly developed countries, including Belgium, Switzerland, and Japan, are providing a notable implicit subsidy valued at over 200 USD per ton for carbon-intensive imported products. Our work carries essential implications for understanding how the manipulation of trade barriers could cause impacts on the environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Tidal rivers are key biochemical reaction channels along the land-ocean aquatic continuum, receiving carbon from wastewater and agricultural drains, which can considerably affect CO 2 emissions. We developed a two-dimensional hydrodynamic and ecological model coupled with an inorganic carbon module along the Tan River in southern China. The simulations of and observations regarding discharge, temperature, total organic carbon (TOC), total inorganic carbon (TIC), and other common water quality variables were generally in good agreement. Based on the validated model, we employed statistical and scenario analyses to evaluate the carbon distribution, TOC and TIC budgets, and the imbalances induced by climatic and anthropogenic changes, providing insights into their potential greenhouse effect. The Tan River was consistently supersaturated with CO 2 with an annual mean air-water CO 2 emission flux (FCO 2 ) of 226.1 ± 84.9 mmol m -2 d -1 , and significant temporal and spatial variations of FCO 2 , TOC, and TIC were observed. Urban small streams tended to emit additional CO 2 during wet seasons, and rural tributaries usually had an increase in TOC concentrations during the dry season. FCO 2 was significantly positively correlated with air temperature and negatively correlated with total nitrogen, total phosphorus, and TOC. The annual riverine input of carbon to the urban river network was 17.37 Gg C yr -1 , with 59.82% of TOC, and carbon output was 15.31 Gg C yr -1 , with 66.87% of TOC. The retention rates for TOC and total carbon were 50.7% and 11.8% in the urban branch, respectively. Furthermore, warming and wastewater treatment could prevent urban river networks and downstream rivers from becoming carbon sources. Therefore, our findings suggest that riverine management strategies change the global CO 2 release from tidal rivers and estuarine systems under climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

China's aims of achieving CO 2 emissions peak by 2030 and carbon neutrality by 2060 are crucial in guiding international efforts to mitigate climate change. Amine-based solvent technologies for capturing CO 2 on a large scale have been implemented as retrofits in various industrial facilities, with a particular focus on coal-fired power plants. Nonetheless, its implementation within the waste-to-energy (WTE) industry is considerably limited and non-existent in China. This work presents a technical and economic evaluation of retrofitting a generic WTE facility in China with a carbon capture system. A rate-based process simulation model of the capture plant was developed in Aspen Plus, and the effect of equipment installation factors on capital cost was evaluated via the enhanced detailed factor (EDF) method. A set of key performance indicators were evaluated. The findings indicate that the energy demand linked to the capture system caused a decrease in efficiency by 13.17%, 14.85%, and 16.56% at 85%, 90%, and 95% capture rates, respectively, and the overall exergy efficiency of the system was reduced by 5.5%, 8.27%, and 10.63%, respectively. The estimated CO 2 captured costs range from €56.41/tCO 2 to €58.95/tCO 2 , while CO 2 avoided costs range from €153.33/tCO 2 to €236.47/tCO 2 . Retrofitting a CO 2 capture unit at WTE facilities has the potential to substantially contribute to achieving the country's emission reduction targets. However, the successful implementation requires a comprehensive policy structure. This work offers some insights into the prospective integration of CO 2 capture technology in China's WTE industry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

To mitigate global climate change and achieve CO 2 emissions reduction goals, China proposed to shift to dual control of total CO 2 emissions (CE) and CO 2 emissions intensity (CEI) as early as possible. Accurately assessing provincial sectoral CE and CEI and developing reasonable regulatory strategies is a prerequisite for achieving the goal of dual control. However, there is a lack of comprehensive analysis from different perspectives of the supply chain. Therefore, this paper evaluates the CE and CEI in provincial sectors of China in 2017 from production-based and consumption-based perspectives according to multi-regional input-output (MRIO) model. Then, we analyze the supply chain of transmission sector by betweenness-based method as a supplementary perspective. The results show that: (1) The CE and CEI from different perspectives are different and can complement each other. (2) Production and distribution of electric power and heat power in Inner Mongolia (P5D24), construction in Jiangsu (P10D27), distribution of electric power and heat power in Beijing (P1D24) are the critical sectors for dual control of CE and CEI from production, consumption, betweenness-based perspectives, respectively. (3) Construction in Jiangsu (P10D27) and Shanxi (P4D27) have the highest embodied CE and CEI in China respectively. Energy and raw material sectors from upstream supply chain contribute large CE to construction sectors. This research suggests that paying attention to critical sectors from different perspectives of the supply chain and taking different measures to decrease CO 2 emissions. Taking both CE and CEI into consideration and allocating CO 2 emissions reduction pressures reasonably among provincial sectors. At the same time, taking care of relevant upstream sectors of the supply chain to help a single sector achieve CO 2 emissions reduction goals and promote China's transition to dual control of CE and CEI., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Combating climate change and reducing carbon dioxide emissions are serious challenges shared by countries around the world. In the current era, digitalization has a significant impact on CO 2 emissions. However, prior studies have not assessed the synergy between digitalization and industrialization on carbon emission performance. The principal component analysis and non-radial directional distance function (NDDF) are used to measure the digitalization and total factor carbon emission performance of Chinese 245 prefecture-level cities from 2003 to 2019. This study establishes a fixed effects model to study the panel data. The findings are as follows: (1) Digitalization can significantly promote Chinese cities' CO 2 emission reduction. This result still holds after several robustness checks. (2) The heterogeneity results indicate that digitalization mainly improves central cities' carbon emission performance. Meanwhile, the impact of digitalization is more obvious after 2011. (3) Digitalization improves urban carbon emission performance through energy efficiency, industrial transformation, and technological innovation. (4) It is worth noting that digitalization synergizes with industrialization to improve carbon emission performance in Chinese cities. This study provides empirical evidence and some constructive policy recommendations for the government to push the collaborative development of the digitalization and low-carbon economy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In the context of globalization, the role of the digital economy in carbon emissions may generate spatial spill over effects. This study comprehensively applies a spatial model to understand the nexus between the digital economy and carbon emissions in 67 economies from 2010 to 2019. Specifically, this study contributes by introducing a spatial panel threshold model, which helps to present the new evidence regarding decarbonization process. Empirical findings exemplify that the digital economy remarkably reduces local carbon emissions, with the positive spatial spill over effects being salient. The spatial moderating effect model uncover that globalization positively affects the nexus between the digital economy and carbon emissions. Interestingly, the spatial panel threshold model designates that the digital economy's reduction effect on local carbon emissions will be tightened, whereas the positive spatial spill over effects turn negative only when globalization surpasses a threshold. Our model has the potential to explain some results that traditional models cannot reach., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Global economies have recently been concerned about sustainable environmental management by reducing emissions and tackling ecological footprints. The rapid economic expansion and investment in traditional manufacturing further raises environmental degradation. China surpasses other emerging economies in the economic growth race yet has remained the top pollution-emitting economy for the last few decades, necessitating scholarly attention. This study examines the influencing factors of ecological footprints in China from the perspective of COP27. Using the extended dataset from 1988 to 2021, this study uses several time series diagnostic tests and verifies the existence of the long-run association between the study variables. Consequently, the non-linear scattered data leads to non-parametric (method of moment quantile regression) adoption. The empirical results indicate that only economic growth is a significant factor in environmental quality degradation in China. However, improving renewable energy usage, research and development, and foreign direct investment reduces the country's ecological footprint. Hence, the latter variables substantially lead to environmental sustainability. The robustness of the results is confirmed via a robust non-parametric estimator and causality test. Based on the empirical results, this study recommends increased investment in research and development, renewable production, and foreign direct investment enhancement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

A vast literature has examined the empirical link between gross exports and total carbon emissions for different country groups. However, countries' increasing participation in global value chains (GVCs) challenges this traditional approach since the gross measures neglect trade-embodied carbon emissions and intermediates-driven value-added trade. Therefore, this study scrutinizes how backward participation (foreign contents in domestic exports) and forward participation (domestic contents in foreign exports) in GVCs affect per capita net exports of trade-embodied carbon dioxide emissions. The study adopts input-output accounting and value-added decomposition framework for Group of Seven (G7) and Emerging Seven (E7) countries over the 1995-2018 period. (i) Pre-estimation analyses reveal that the net carbon importer G7 group had a comparative advantage in high-tech exports and a lower export product concentration level, while the net carbon exporter E7 group had a comparative advantage in resource-intensive exports and a higher export product concentration level, albeit significant within-group heterogeneities. (ii) The augmented mean group estimates reveal that increasing backward participation raises net carbon exports for both G7 and E7. The forward participation-net carbon exports nexus is negative for G7 but positive for E7. (iii) While economic growth reduces net carbon exports in both groups, the effects of comparative advantages in resource-intensive and high-tech exports differ. Practitioners should be aware of the GVCs-driven carbon circle when assessing decarbonization performances and obligations of countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Given that war can have a serious impact on the climate, this article is aimed to discuss the impact of warfare on carbon emissions by examining changes in CO 2 before and during the war in Syria based on the kaya constant equation and the LMDI decomposition method. In the decade before the war, population was the largest contributor, making up 32.64% of the total 51.02% increase in carbon emissions. The only factor that offsetting carbon emissions was energy intensity, making a 22.30% curbing effect. In the early stage of the war, carbon emissions decreased by 56.38%, in which per capita GDP contributed 37.55% of the total CO 2 decline. Carbon intensive of energy was the only factor promoting the carbon increase with a 4.67% contribution. In the late war, carbon emissions start to resume slow increase with energy intensity and economy turning negative to positive. It can be speculated that the impact of the war on CO 2 emissions: (i) in the first years of the war, CO 2 would drop significantly at the cost of significant population decline and economic recession, the least desirable and the worst way to reduce carbon emissions. (ii) if evolves into a prolonged war, it would reverse carbon emissions from decline to increase, although the population and the economy are both falling. This research, therefore contends that once war is triggered, there is no other solution to prevent this worst-case scenario of Population Decline - Economic Recession - Increased Carbon Emissions from happening, unless the war is stopped immediately., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This study analyzed the theoretical mechanism of the carbon emission effect embodied in the Sino-USA manufacturing trade. We constructed a trade and carbon emission input-output model for 16 manufacturing sub-sectors in China and the USA from 2000 to 2018. A comprehensive empirical test of the systematic emission reduction mechanism was conducted. There were four main findings: (1) indirect and direct carbon emissions indicators can comprehensively analyze the link between production and demand across sectors; (2) indirect carbon emissions are higher than direct carbon emissions in half of the sectors in both China and the USA, and other sectors bear part of the carbon emissions for these sectors; (3) compared to 2000, the change in net exports of both countries is the main reason for the change in indirect carbon emissions, while the change in net exports of intermediate goods is the main reason for the change in direct carbon emissions; and (4) the Sino-USA trade surplus comes at the expense of China's environmental losses, while the USA obtains environmental benefits. Overall, the theoretical analytical framework not only comprehensively considers the interlinkages between production and demand across sectors but also provides a more reasonable evaluation of the environmental effects of Sino-USA trade. Additionally, this study provides a solid theoretical and empirical basis for China to achieve its dual-cycle and dual-carbon goals, thus promoting the rapid transformation of China's economy toward green and high-quality development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Carbon emission is a central factor in the study of the greenhouse effect and a crucial consideration in environmental policy making. Therefore, it is essential to establish carbon emission prediction models to provide scientific guidance for leaders in implementing effective carbon reduction policies. However, existing research lacks comprehensive roadmaps that integrate both time series prediction and analysis of influencing factors. This study combines the environmental Kuznets curve (EKC) theory to classify and qualitatively analyzes research subjects based on national development patterns and levels. Considering the autocorrelated characteristics of carbon emissions and their correlation with other influencing factors, we propose an integrated carbon emission prediction model named SSA-FAGM-SVR. This model optimizes the fractional accumulation grey model (FAGM) and support vector regression (SVR) using the sparrow search algorithm (SSA), considering both time series and influencing factors. The model is subsequently applied to predict the carbon emissions of the G20 for the next 10 years. The results demonstrate that this model significantly improves prediction accuracy compared to other mainstream prediction algorithms, exhibiting strong adaptability and high accuracy., Competing Interests: Declaration of Competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Although saline aquatic ecosystems are significant emitters of greenhouse gases (GHGs), dynamic changes in GHGs at the sediment-water interface remain unclear. The present investigation carried out a total of four sampling campaigns in Daihai Lake, which is a eutrophic saline lake situated in a semi-arid area of northern China. The aim of this study was to investigate the spatio-temporal dynamics of carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes at the sediment-water interface and the influencing factors. The mean concentrations of porewater CO 2 and CH 4 were 44.98 ± 117.99 μmol L -1 and 124.36 ± 97.00 μmol L -1 , far exceeding those in water column of 11.14 ± 2.16 μmol L -1 and 0.33 ± 0.23 μmol L -1 , respectively. The CO 2 and CH 4 fluxes at the sediment-water interface (F S - W CO 2 and F S-W CH 4 ) exhibited significant spatial and temporal variations, with mean values of 9.24 ± 13.84 μmol m -2  d -1 and 3.53 ± 4.36 μmol m -2  d -1 , respectively, indicating that sediment is the source of CO 2 and CH 4 in the water column. However, CO 2 and CH 4 fluxes were much lower than those measured at the water-air interface in a companion study (17.54 ± 14.54 mmol m -2 d -1 and 0.50 ± 0.50 mmol m -2 d -1 , respectively), indicating that the diffusive flux of gases at the sediment-water interface was not the primary source of CO 2 and CH 4 emissions to the atmosphere. Regression and correlation analyses revealed that salinity (Sal) and nutrients were the most influential factors on porewater gas concentrations, and that gas fluxes increased with increasing gas concentrations and porosity. The microbial activity of sediment is greatly affected by nutrients and Sal. Additionally, Sal has the ability to regulate biogeochemical processes, thereby regulating GHG emissions. The present investigation addresses the research gap concerning GHG emissions from sediments of eutrophic saline lakes. The study suggests that controlling the eutrophication and salinization of lakes could be a viable strategy for reducing carbon emissions from lakes. However, further investigations are required to establish more conclusive results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Lakes are recognized as important sources of carbon dioxide (CO 2 ) emissions, which vary greatly across land use type. However, CO 2 emissions from lakes in urban landscapes are generally overlooked despite their daily connections to human activity. Furthermore, the role of management actions in CO 2 emissions remained unclear mostly because of the lack of long-term observations. Here, the CO 2 partial pressure (pCO 2 ) from two urban lakes (Lake Wuli and Lake Donghu) in eastern China were investigated based on 16-year (2002-2017) field measurements. This long-term measurements showed the annual mean pCO 2 were 1150 ± 612 μatm for Lake Wuli and 1143 ± 887 μatm for Lake Donghu, with corresponding estimated flux of 21.12 ± 19.60 mmol m -2 d -1 and 16.42 ± 20.39 mmol m -2 d -1 , respectively. This indicates significant CO 2 evasion into the atmosphere. Strong links between CO 2 and human-derived nutrients (e.g., ammonium) and dissolved organic carbon, dissolved oxygen, and trophic state index were found. Although pCO 2 was relatively uniform across sites and seasons in each lake, substantial inter-annual variability with significant decreasing trends were found. The decrease in annual CO 2 can be partly explained by the reduction of pollutant loadings with management actions, which held the hypotheses that management actions mitigated the CO 2 emission risks. Overall, management actions (e.g., ecological restoration and municipal engineering) should be considered for better understanding the roles of anthropogenic aquatic ecosystems in carbon cycle., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Globalization and the configuration of production processes around Global Value Chains (GVCs) have become key factors for explaining the recent evolution of environmental and economic indicators. Indeed, previous research found evidence on the significant impact of GVCs indicators (participation and position) on CO 2 emissions. Additionally, results obtained in previous literature vary depending on the time period and geographical areas considered. In this context, the main aims of this paper are to analyze the role the GVCs in explaining the evolution of CO 2 emissions, and to identify possible structural breaks. This study uses the Multiregional Input-Output framework to calculate a position indicator and two different measures of participation in GVCs (interpreted either as trade openness or international competitiveness). The analysis useS Inter-Country Input-Output tables (ICIO) as main database, which includes 66 countries and 45 industries and covers the period 1995-2018. It is first concluded that upstream positions in GVCs are associated to lower global emissions. Additionally, the effect of participation depends on the measure used: trade openness is linked to lower emissions, while a higher competitiveness in international trade leads to higher emissions. Finally, two structural breaks are identified in 2002 and 2008, revealing that position is significant in the two first subperiods, while participation becomes significant from 2002 onwards. Thus, policies to mitigate CO 2 emissions might to be different before and after 2008: currently, reductions in emissions can be achieved by increasing value-added embodied in trade while decreasing the volume of transactions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In the context of global value chain, this paper uses world input-output table (2016) and CO 2 emission data to analyze domestic environmental cost of agricultural exports based on backward linkage MRIO model. The results show that average domestic value-added and domestic embodied emissions of China's agricultural export are respectively ranked 7th and 4th in the world during the sample period, which indicates that China's agriculture does not perform well in environmental cost; On the bright side, China's domestic environmental cost displays a downward trend over time. In terms of contributing factors, CO 2 emission coefficient is conducive to the reduction of domestic environmental cost, meanwhile the value-added coefficient, intermediate input structure, and agricultural export structure promote the increase of domestic environmental cost. Further, the cross-country decomposition results found that the emission coefficient and the intermediate input structure are the main reasons that lead China's domestic environmental cost to be higher than those of the main agricultural export countries. The value-added factor and the export structure have narrowed the gap of domestic environmental cost between China and other major agricultural economies. The research findings are still robust when scenario analysis is introduced. This study suggests that optimizing the structure of energy consumption and promoting cleaner production are most important ways to promote the sustainable development of China's agricultural exports., Competing Interests: Declaration of competing interest We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Environmental pollution has become a global issue attracting ever-increasing attention. Green technology innovation (GTI) is considered an effective strategy in countering this problem and helping achieve sustainability goals. However, the market failure suggests that intervention from the government is necessary to promote the effectiveness of technological innovation and hence, its positive social impacts on emissions reduction. This study investigates how the environmental regulation (ER) influences the relationship between green innovation and CO 2 emissions reduction in China. Employing data from 30 provinces from the period 2003 to 2019, the Panel Fixed-effect model, the Spatial Durbin Model (SDM), the System Generalised Method of Moments (SYS-GMM) and the Difference-In-Difference (DID) models are applied to take issues relating to endogeneity and spatial impact into consideration. The results indicate that environmental regulations positively moderate the impact of green knowledge innovation (GKI) on CO 2 emissions reduction but have a much weaker moderation effect when green process innovation (GPI) is considered. Among different types of regulatory instruments, investment-based regulation (IER) is the most effective in promoting the relationship between green innovation and emissions reduction, followed by command-and-control-based regulation (CER). Expenditure-based regulation (EER) is less effective and can encourage short-termism and opportunistic behaviour among firms, who can accept the paying of fines as a cheaper cost over the short-term than investment in green innovation. Moreover, the spatial spillover effect of green technological innovation on carbon emissions in neighbouring regions is confirmed, in particular when IER and CER are implemented. Lastly, the heterogeneity issue is further examined by considering differences in the economic development and the industrial structure across different regions, and the conclusions reached remain robust. This study identifies that the market-based regulatory instrument, IER, works best in promoting green innovation and emissions reduction among Chinese firms. It also encourages GKI which may assist firms in achieving long-term sustained growth. The study recommends further development of the green finance system to maximise the positive impact of this policy instrument., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Process-related carbon emissions, which cannot be completely eliminated by the improvement of processes and energy structure, are recognized as an enormous challenge for in-depth decarbonization. To accelerate the achievement of carbon neutrality, the concept of 'artificial carbon cycle' is proposed based on the integrated system of process-related carbon emissions from high-emitting industries and CCU technology as a potential pathway towards a sustainable future. This paper conducts a systematic review on the integrated system with the case of China, which is the largest carbon-emitting and manufacturing country, to provide a clearer and more meaningful analysis. Multi-index assessment was used to organize the literature and draw the useful conclusion. Based on literature review, the high-quality carbon sources, reasonable carbon capture approaches and promising chemical products were identified and analyzed. Then the potential and practicability of the integrated system was further summarized and analyzed. Finally, key factors of future development including technology improvement, green hydrogen, clean energy and industrial cooperation were stressed to provide a theoretical reference for future researchers and policy makers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Although market-based CO 2 emission control measures (e.g., carbon tax and carbon trading market) have been deeply discussed, government-based measures have received limited attention. This has led to increased uncertainty regarding the formulation of targeted emission reduction policies. Using a unique dataset, the non-radial directional distance function, a proposed spatial meta-frontier analysis method, and the log t convergence model, this study comprehensively investigates the spatio-temporal trends in fiscal environmental expenditure efficiency (FE) and corresponding causes for in a case study for 106 Chinese cities over 2007-2019. The results show that city-level FE presented a slow upward trend at a relatively low level, with a clearly skewed distribution. The technology gap effect between city groups and the overall best production technology, and the efficiency gap effect within city groups were the main drivers widening the overall FE gap. Convergence analysis indicated that three convergence clubs of FE were found, which were distributed across the country. This study highlights that, when constructing fiscal environmental expenditure policies, the government should focus on balancing the regional gap of FE while comprehensively improving FE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The EU Carbon Border Adjustment Mechanism (CBAM) is regarded as the world's first carbon tariff regulation. Its consequential impacts on the trades of individual countries/regions at different development stages are crucial for climate justice while remaining unclear. By combining Multi-regional Input-output analysis and scenario analysis, this study analyzed the economic-carbon inequality in national/regional plastic exports and simulated CBAM's short-term impacts on plastic trade inequality under different scenarios. Our analysis shows that the maximum values of total carbon tariffs for all countries/regions levied on plastic exports to the EU will be 497.8, 859.1, and 1564.2 million euros under scenarios covering Scope 1, Scope 1&2, and Scope 1&2&3 emissions, respectively. The corresponding proportions of CBAM costs to national/regional plastic export volumes to the EU will be 0.6%, 1.0%, and 1.8% on average, respectively. China and the rest of Asia and the Pacific will burden the most CBAM costs in all cases, and Russia will be the country most affected. CBAM will exacerbate the economic-carbon inequality in the plastic trade by reducing the trade profits of developing economies with higher ratios than those of developed economies. Our analysis calls for practical initiatives to induce technological advances toward lower carbon technologies, increase trade diversification, exploit the domestic market's potential, and implement domestic carbon pricing mechanisms to alleviate the negative impact of CBAM., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Scientific assessment of the historical carbon peak situation of provincial buildings in China is the premise and basis for understanding the country's development trends and formulating carbon peak goals. The population size, urbanization stages, economic development levels, natural resources endowment, and energy structure characteristics vary significantly for the different provinces in China, resulting in significant differences in the peaking situation of building carbon emissions (BCE). The differences require more attention given the current environmental status. Based on the judgment function of carbon peaking conditions and the statistical Mann-Kendall (MK) trend test method, this study evaluates the historical peak situation of building carbon emissions at the provincial level in China. The peaking sequence of BCE, building carbon emissions per capita (BCEP), and carbon emissions per unit floor area (BCEA) were analyzed, and the driving factors that cause different carbon peak situations were discussed. Further, with reference to the experience of the United States, a peak strategy for building carbon emissions in China was proposed. The research results showed that BCE in Beijing and Yunnan have peaked, and the three provinces of Shanghai, Sichuan, and Hubei have plateaued. The most important factors that cause different peaking situations for BCE are the floor area per capita and carbon emissions per unit of energy consumption. In addition, the peak order of building carbon emissions was BCEA, BCEP, and BCE. A strategy that should be adopted in the promotion of buildings' carbon peak in China is to formulate phased peak goals for BCE, BCEP, and BCEA at a national level and differentiated echelon peak goals at a provincial level considering interprovincial differences. This study provides a scientific basis and decision-making reference for formulating a path to buildings' carbon peak at a provincial level in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

With the increasing affluence, the differences in CO 2 emission between urban and rural residential sectors are remarkable and show an increasing trend. In case of China, residential sector accounts for a substantial share of the national CO 2 emission, bringing greater pressure to achieve the goal of carbon peak. Analyzing the emission inequality trend and its drivers is essential for formulating effective CO 2 emission reduction policies. However, the existing literature lacks relevant analysis from the viewpoint of urban-rural disparity. Hence, this study decomposes the CO 2 emission inequality of China's urban and rural residential consumption into four factors by combining the Theil index and Kaya decomposition. The results suggest that, in 2005-2020, the per capita CO 2 emission of rural residential consumption increased to a higher extent than those of urban households, with large differences in spatial distribution. Decomposition of the per capita CO 2 emission inequality for residential sector shows that the primary source is the inequality within the groups, mainly from the urban intra-group inequality. Based on the static decomposition, energy intensity appears as the main factor of urban-rural inequality. The dynamic decomposition shows that there have been differences in the factors of the change in the Theil index between urban and rural areas across sub-periods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

A burgeoning literature has investigated the relationship between tourism and regional CO 2 emissions. However, the results are equivocal. Some scholars find that tourism induces more emissions, while others find that tourism benefits emission mitigation. Previous research suffers three deficiencies: (1) the CO 2 emissions induced by tourism beyond the tourism sectors are neglected; (2) the role of tourism agglomerations in sustainable destination development is underrated; (3) the tripartite mechanism of tourism agglomerations, household income, and urban direct residential CO 2 emissions (DRCEs) remains to be determined. Based on the theories of complex adaptive system and an empirical study of 30 provinces in China, we examine the relationship between the tripartite roles via multiple spatial econometric models. The results disclose that tourism agglomerations have dual effects on urban DRCEs and an inverted U-shaped effect on household income. The growth of tourism agglomerations has generally promoted urban DRCEs in many provinces of mainland China during the last fourteen years because its indirect effect (positive) outweighs the direct effect (negative). However, tourism agglomerations are feasible for low-carbon destinations once the emission-income decoupling happens. This study contributes to low-carbon destination management by presenting a more holistic image of the social-economic-environmental impacts of tourism agglomerations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Carbon compensation is an effective way of reducing carbon emissions. However, previous studies in this field have been limited and have not examined high-precision scientific carbon compensation under regional inequity. The present study examined initial carbon compensation in the grid and developed a new equitable carbon compensation model. Additionally, it modified the carbon compensation value for each province and analysed how land-use change affected carbon compensation. The results show that, after the modification, the entire carbon deficit reached 17.34 × 10 8  t C in 2015, representing a decrease of 14% compared with the initial carbon deficit. The area with negative carbon deficit values accounted for 36% of the whole area, concentrated mainly in the south, southwest and northwest. Without modification, the initial carbon compensation reached 537 × 10 8 USD, and only Yunnan, Sichuan and Hainan provinces being eligible to receive compensation. The final modified carbon compensation was approximately 20% of the initial values, and 11 provinces were eligible to obtain compensation. The other provinces responsible for paying the carbon compensation costs were typically concentrated in Central and Eastern China. Land-use changes in 2015 led to increases in the initial carbon compensation and modified carbon compensation of 3.74 × 10 8 and 0.13 × 10 8 USD, respectively. The per-unit land-use change caused greater increases in carbon emissions in China's big cities and the provinces in Central and East China. Some policies, such as macro-control by the central government, diversified forms and patterns of compensation, and auxiliary measures should be formulated/proposed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Revealing the complex correlation between population aging and CO 2 , and projecting their future dynamics are fundamentally necessary to inform effective policies toward a low-carbon and sustainable development in China. Differing from the existing studies, this study highlighted a quantitative investigation on the impact of aging on CO 2 emissions across the different stages of regional development in China through a STIRPAT model based on balanced provincial panel data from 1995 to 2019, and projected the demographic change and CO 2 emissions till 2050 by employing cohort model and scenario analysis. It is found that CO 2 emissions in China has witnessed a significant growth during 1995-2019, and will exhibit an inverted U-shaped growth till 2050 with its peak appears between 2030 and 2040. Statistically, every 1% growth of aging population will cause a 0.62% increase in CO 2 emissions in China. However, a big regional difference was also detected as aging contributed to CO 2 reduction in the eastern region, but stimulated CO 2 emissions in the central and western regions. Policy implications for achieving a low-carbon and aging-oriented sustainable development may include the integration of aging into the decision-making in industrial structure upgrading and CO 2 emission reduction at both national and region levels, the promotion of further transition to low-carbon consumption and green products in the eastern region, and strengthening the deep fusion of aging-oriented industries with local resource and environmental endowment in the central and western regions such as the development of eco-agriculture and green pension industries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The increasing environmental pressure of anthropogenic CO 2 emissions is impeding the sustainability of urban agglomerations (UAs). Recent research has shown that the spatial clustering of UA elements reduces CO 2 emissions but underestimates its impact on vegetation carbon sequestration. Using an extended IPAT equation analysis framework and the Logarithmic Mean Divisia Index decomposition approach, this study revealed the positive effects of the economy and population spatial clustering on carbon footprint pressure (CFP) mitigation. Specifically, improving economic spatial clustering mitigated the rise in UA's CFP caused by affluence and population growth. Furthermore, population clustering in core cities effectively mitigated CFP in neighboring cities. Additionally, we found that the efficiency improvement, i.e., the decrease in the ratio of carbon emissions and gross domestic product, should be the dominant driver of CFP mitigation, followed by improved vegetation carbon sequestration. However, these drivers have limited future potential. We believe that by improving UA's spatial clustering of the economy and population, future urban environmental pressures and climate risks will be mitigated., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The Belt and Road Initiative (BRI), which was first put forward by China in late 2013, has made a significant contribution to international economic activities and inevitably reshaped the pattern of carbon dioxide (CO 2 ) emissions. Considering the spatial spillover effects of CO 2 emissions among countries, this paper employs spatial difference-in-differences models in order to investigate the BRI's effects on total CO 2 emissions (TCE), per capita CO 2 emissions (PCE), and CO 2 emissions intensity (CEI), respectively. The results of global Moran's I index prove the existence of spatial correlations of CO 2 emissions. The BRI's effect on TCE is significantly positive, while the effects on PCE and CEI are significantly negative, suggesting the BRI has aggravated the amount of CO 2 emissions in the partner countries, but has promoted green development by decreasing PCE and CEI. Besides, the spatial effects of control variables on CO 2 emissions are also evaluated. Some tests, including placebo test and employing alternative weight matrices, are further conducted to verify the robustness of the model. The findings indicate the BRI has facilitated green economic growth, by eventually achieving emission reduction targets in the partner countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Since China's speedy economic development, the problems of energy consumption and environmental pollution have become increasingly prominent. A question worth in-depth study is whether ecological civilization (EC) construction, one of the main policies to solve China's severe environmental and ecological problems, affects carbon dioxide emissions (CDE). In this study, we use a novel method proposed by Hsiao et al. (2012) to estimate the average treatment effect by using panel data to study the impact of establishing the EC pilot zones of China on CDE. The results show that, although EC construction is effective in reducing CDE, the impact varies from region to region. The study findings can provide a scientific basis to promote the experience of EC construction better and improve its CDE effect., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Although the past twenty years have witnessed China's remarkable economic development, the cost in terms of greenhouse gas emissions and a deteriorating environment has been enormous. Numerous studies have revealed the influence of household factors on household carbon dioxide emissions (HCEs) and called for a reduction of HCEs to mitigate climate change, but few have focused on assessing the most significant household driving factors of HCEs. Using statistical data between 2005 and 2019 in Jiangsu, China, this study developed an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model to assess the most significant driving factors of HCEs. The results show that the most significant driving factors are household size, total population, unemployment, and urbanisation rate. The study found that HCEs are positively impacted by household size while negatively impacted by the unemployment rate. Based on the study's findings, the following suggestions are proposed to lower HCEs: (i) establish an optimal consumption concept to guide residents towards consuming reasonably; (ii) cultivate a low-carbon concept among residents and promote low-carbon emissions living; and (iii) pay close attention to population structure factors and formulate effective measures accordingly. The study provides insightful information on the key driving factors of HCEs, which can facilitate achieving carbon emissions neutrality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Identifying key drivers of manufacturing CO 2 emissions is critical to carbon reduction practices. For manufacturing, CO 2 emissions are mainly determined by production capacity and production scale. However, traditional production-theoretical decomposition analysis (PDA) fails to consider production-scale-related drivers. To better support policy development and implementation, this paper improves PDA based on industrial linkage theory. The improved model can identify seven production-capacity-related drivers and five production-scale-related drivers, allowing a comprehensive understanding of CO 2 emission drivers. Then this model is implemented to investigate CO 2 emission changes in 18 manufacturing sectors in Hubei Province, China, from 2012 to 2017. Results show that manufacturing CO 2 reduction efforts in Hubei Province have yielded some achievements, with reduced potential energy intensity and improved CO 2 emission technical efficiency in most sectors. Changes in external market demand and final demand structure have contributed to CO 2 reduction in most sectors. Results also reveal some problems in manufacturing in Hubei Province, such as the inability to improve CO 2 emission technical efficiency and CO 2 emission technology strength, the slow improvement of energy utilization technical efficiency and energy utilization technology strength, and the reduction of value-added rate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

With the rapid development of interregional power transmission, the redistribution of fossil and renewable energy resources has changed sharply, and its complexity poses a challenge to the evaluation of power carbon emission responsibility. This study constructs an interprovincial power transmission framework to measure the seasonal carbon emissions embodied in regional electricity consumption over the period of 2008-2015 based on quarterly data. Then, a structural decomposition approach was developed to identify the influential factors of carbon emissions embodied in provincial electricity consumption from a seasonal perspective. The results show that the assessment for embodied emissions of power consumption based on different levels of data may vary by as much as 20%, and the carbon emissions and carbon intensity of power consumption exhibit significant seasonal characteristics. Furthermore, it is revealed that the economic scale in the fourth quarter makes the most significant contribution to the emissions increment, especially in underdeveloped provinces, while the change in energy efficiency of power generation reduces more carbon emissions in the first and second quarters. In addition, the impact of the power transmission scale is more significant in the third and fourth quarters, and it has been close to or even more than the impact of traditional factors in some quarters. Finally, the impact of economic scale, power generation energy intensity, power generation mix and electricity utilization efficiency on the emissions of regional power grids shows a relatively stable increasing trend, but this trend of directional stability is not reflected in the effect of the power transmission structure and transmission scale. This study contributes to the identification of the impact of the power transmission structure and transmission scale. Moreover, this study highlights the importance of considering seasonal characteristics when estimating the carbon emissions of power consumption and formulating specific emission reduction policies. Additionally, it provides a more accurate evaluation of carbon emissions and proposes several prominent recommendations for policy makers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Low-carbon pilot cities can break the lock-in effect of living carbon emissions, which are an important strategic component of China's response to climate change. Current research on low-carbon pilot cities focuses on the production field. Insufficient attention has been paid to whether low-carbon pilot cities can promote the green transformation of residents' lifestyle. Using panel data of 285 cities in China from 2004 to 2016, this study explores the inducing effect of low-carbon pilot cities on residents' low-carbon choices from holistic and single-dual perspectives based on the difference-in-differences method and the synthetic control method. This study finds that low-carbon pilot cities can promote the green transformation of residents' lifestyle, and this policy has reduced living carbon emissions by approximately 15.3%. The transmission mechanisms are mainly green life consciousness and green habits. The conclusion considers the effects of multi-pilot policies and other living differences during the parallel period and is still valid after robustness testing using propensity score matching difference-in-differences. In addition, the policy has a snowball effect, and is stronger in larger cities. Ultimately, this paper provides useful information for the scientific implementation of carbon emission reduction plans in the field of residents' living and the improvement of the long-term mechanism of pilot cities with both quality and quantity guaranteed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

The reduction of carbon dioxide (CO 2 ) emissions and sustainable development in low-carbon ways are of great significance to urban agglomerations. However, few studies are exploring the relationship between CO 2 emissions and socioeconomic development at city levels from the perspective of clusters of regions. Based on the open data of inventory for anthropogenic CO 2 emissions, nighttime light data, and population dataset as a proxy for the socioeconomic development levels of urban agglomerations, we used Mann-Kendall trend test, Tapio decoupling analysis, and spatial autocorrelation analysis to explore the spatiotemporal association of CO 2 emissions and the impact of socioeconomic development on emissions in the nineteen urban agglomerations in China. Findings showed that the growth of CO 2 emissions in China was primarily concentrated in urban agglomerations. The CO 2 emissions in eastern coastal and northern urban agglomerations were much higher than those in other areas, while the emissions in western urban agglomerations were the lowest. The periodic characteristics of CO 2 emissions were consistent with China's five-year development plan. Urban agglomerations in the early stage from 2000 to 2002 or with developed and stable industrial structures tended to achieve decoupling. High-high (HH) clusters of socioeconomic development with CO 2 emissions were mainly distributed in urban agglomerations of the Beijing-Tianjin-Hebei region (BTH), the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), Yangtze River Delta (YRD), Huhhot-Baotou-Ordos-Yulin (HBOY), Shandong Peninsula (SP), and Central Shanxi (CS). Most of the clusters except those in HBOY shrunk from 2000 to 2010 and remained relatively stable from 2010 to 2019. These urban agglomerations should promote synergistic emission reduction. High-low (HL) clusters mostly appeared in central cities with a high socioeconomic level and surrounding cities with low CO 2 emissions s, i.e., in urban agglomerations of Chengdu-Chongqing region (CC), the Beibu Gulf (BG), and Lanzhou-Xining (LX). These urban agglomerations with prominent polarization phenomena should adhere to regional overall coordination and thus minimize total regional costs of CO 2 emission reduction. The results could provide references for the synergistic reduction of CO 2 emissions and the coordinated development in urban agglomerations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

The relationship between the two sustainable development goals (SDGs)-inequality reduction and carbon emission reduction is critical for governments formulating and implementing environmental and redistribution policies. This study uses micro survey data from the China Family Panel Studies (CFPS) to conduct a counterfactual analysis that decomposes and quantifies the net effects of consumption growth, redistribution, and changing patterns of consumption on household carbon emissions. The counterfactual approach helps to overcome the endogeneity concerns. The findings of our study convey a profoundly important and alarming message: the redistribution measures for inequality reduction may increase household carbon emissions. The findings attest to the need for Chinese policymakers to seriously consider the trade-off between inequality reduction and emission reduction, particularly in certain regions in China. To address the trade-off, one key measure is to encourage low-carbon lifestyles and consumption patterns to ensure that the benefits gained by poorer households from redistribution measures will not translate into higher emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)