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CO 2 emission performance evaluation is crucial to make abatement policies. Knowledge about the potential and costs of CO 2 reduction could provide information guides for policymakers and help them implement targeted measures. However, relevant studies are rarely subdivided into detailed industrial sectors, and results are lack of inter-industry comparisons. To fill this gap, this study estimates provincial technical inefficiency, abatement potential, and shadow price of CO 2 from fuel combustion in China's 25 industries in 2001-2017. Results show that China's industry could ideally reduce CO 2 emissions by a further 22.01-33.27%, averaging 1645.96 MtCO 2 . Technical efficiency, abatement potential, and cost vary across provinces and industries and should therefore be fully considered when designing emission reduction targets and control policies. Provinces and industries with low technical efficiency, large-scale emissions, great abatement potential and low shadow price are the key to emission reduction. We thus identify key provinces and industries that need to take on more abatement responsibility. Those findings are of great significance to the formulation of carbon reduction targets and the implementation of abatement policies, and prove the feasibility of China's trans-regional carbon trading. It is suggested to prioritize key industries into the trading system and further promote inter-provincial cooperation through carbon trading., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Mollisols rich in natural organic matter are a significant sink of carbon (C) and selenium (Se). Climate warming and agricultural expansion to the cold Mollisol regions may enhance soil respiration and biogeochemical cycles, posing a growing risk of soil C and Se loss. Through field-mimicking incubation experiments with uncultivated and cultivated soils from the Mollisol regions of northeastern China, this research shows that soil respiration remained significant even during cold seasons and caused co-emission of greenhouse gases (CO 2 and CH 4 ) and methylated Se. Such stimulus effects were generally stronger in the cultivated soils, with maximum emission rates of 7.45 g/m 2 /d C and 1.42 μg/m 2 /d Se. For all soil types, the greatest co-emission of CO 2 and dimethyl selenide occurred at 25 % soil moisture, whereas measurable CH 4 emission was observed at 40 % soil moisture with higher percentages of dimethyl diselenide volatilization. Molecular characterization with three-dimensional fluorescence and ultra-high resolution mass spectrometry suggests that CO 2 emission is sensitive to the availability of microbial protein-like substances and free energy from organic carbon biodegradation under variable moisture conditions. Predominant Se binding to biodegradable organic matter resulted in high dependence of Se volatilization on rates of greenhouse gas emissions. These findings together highlight the importance of dynamic organic carbon quality for soil respiration and consequent Mollisol Se loss risk, with implications for science-based management of C and Se resources in agricultural lands to combat with Se deficiency., 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.)

The calculation of marginal abatement costs of CO 2 plays a vital role in meeting China's 2020 emission reduction targets by providing reference for determining carbon tax and carbon trading pricing. However, most existing researches only used one method to discuss regional and industrial marginal abatement costs, and almost no studies predicted future marginal abatement costs from the perspective of CO 2 emission efficiency. To make up for the gaps, this paper first estimates marginal abatement costs of CO 2 in three major industries of 30 provinces in China from 2005 to 2015 based on three assumptions. Second, based on the principle of fairness and efficiency, China's 2020 emission reduction targets are decomposed by province. Based on the ZSG-C-DDF model, the marginal abatement costs of CO 2 in all provinces in China in 2020 are estimated and compared with the marginal abatement costs of 2005 to 2015. The results show that (1) from 2005 to 2015, marginal abatement costs of CO 2 in all provinces show a fluctuating upward trend; (2) compared with the marginal abatement costs of primary industry or tertiary industry, most provinces have lower marginal abatement costs for secondary industry; and (3) the average marginal abatement costs of CO 2 for China in 2020 are 2766.882 Yuan/tonne for the 40% carbon intensity reduction target and 3334.836 Yuan/tonne for the 45% target, showing that the higher the emission reduction target, the higher the marginal abatement costs of CO 2 . (4) Overall, the average marginal abatement costs of CO 2 in China by 2020 are higher than those in 2005-2015. The empirical analysis in this paper can provide multiple references for environmental policy makers.

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.)

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.)

Despite their acute climatic susceptibility, the hot, arid Middle Eastern countries are among the world's largest energy consumers and emitters of greenhouse gases, particularly carbon dioxide (CO 2 ). Nonetheless, no study has been conducted to decompose regionally the influential primary factors of the Middle East's carbon emissions. This study utilized the logarithmic mean Divisia index (LMDI) method to fill this knowledge gap and investigate the driving forces of CO 2 emissions in 12 Middle Eastern countries, namely, Bahrain, Iran, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, the United Arab Emirates, and Yemen (1990-2020). The research confirmed that, with a contribution rate of 53.89 %, population growth is the primary driver of CO 2 emissions in the Middle East, followed by energy intensity (31.97 %) and economic growth (18.42 %); and the most straightforward approach to reduce emissions, are boosting energy efficiency and reforming energy subsidies. It also concluded that the West Asian economy is gradually decoupling from CO 2 due to the effective decarbonization of countries, such as Saudi Arabia and Kuwait, based on the Tapio decoupling model results. Furthermore, each country's future emissions (2020-2026) were projected using a novel group method of data handling (GMDH) approach based on the main identified factors. The countries' decoupling status confirms the accuracy of the projected data on CO 2 emissions growth. The region's CO 2 emissions are expected to rise 13.28 % by 2026, with Syria and Yemen experiencing the most significant increases (129.45 % and 112.14 %, respectively) due to post-civil war economic growth. Other aspects of regional conflicts and migration impacts on the CO 2 emission influencing factors were also explored. Indeed, besides providing a comprehensive analysis of the current and future status of CO 2 emissions in the Middle East, the effects of military conflicts on CO 2 emissions have been investigated using this regional case study for global application., 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 B.V. All rights reserved.)

Carbon dioxide (CO 2 ) emission reduction has become an important concern worldwide. During the past century, human activities have been a significant cause of the increase in the level of greenhouse gases. Past research mainly focuses on evaluating the nexus between unidimensional population factors and CO 2 emissions, while few prior studies in a developing country have reported the impact of multidimensional demographic factors on CO 2 emissions. As an initial attempt, this study investigates the short- and long-run associations between population factors, low-carbon innovation, and carbon dioxide emissions (CO 2 ) for a panel consisting of 285 cities by employing the pooled mean group (PMG) estimator under the framework of the panel autoregressive distributed lag (ARDL) model. Our main findings are as follows: (1) Population size and population density could increase CO 2 emissions, while population quality and low-carbon innovation were essential factors that alleviate carbon emission pressure in the long run. (2) Economic development, foreign direct investment, and industrial development were found to be factors causing the increase in carbon emissions. (3) The split-sample analysis demonstrated that the improvement of population quality still has a positive and significant long-run effect on environmental quality. Simultaneously, low-carbon innovation could realize the enormous dividends of carbon emission reduction in the long run, especially in existing relatively larger CO 2 emission areas. Finally, the paper presents important policy implications., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China has announced to launch a national emission trading system (ETS). The heterogeneity of marginal abatement cost (MAC) is prerequisite for trading, and the knowledge about the evolutionary characteristics of MAC is particularly necessary. However, the β convergence theory has been proved to be suitable yet rarely applied to the study of MAC of CO 2 . To fill this gap, this paper connects them creatively, and the convergence of MAC during 2001-2015 and the influential factors are explored by spatial panel data models. Results show that China's MAC converges during the study period whether the spatial effect is considered or not. When evaluating the convergence of MAC, the spatial effect should not be ignored, because it will improve the explanatory power of models and promote the convergence. The size of labor force, emission level, coal consumption, foreign direct investment, and industrial structure significantly affect the growth rate of MAC. Low-carbon policies could be formulated fully considering the factors and their spillover effects. Those findings are certainly significant in imposing carbon reduction targets and adopting policy instruments. In addition, a national ETS is more applicable to China's reality at this stage and suggested to introduce carbon tax in due course in the future., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With the change of social economic system and the rapid growth of agricultural economy in China, the amount of agricultural energy consumption and carbon dioxide emissions has increased dramatically. Based on the estimation of agricultural carbon dioxide emissions from 1991 to 2018 in China, this paper uses EKC model to analyze economic growth and agricultural carbon dioxide emissions. The Kaya method is used to decompose the factors affecting agricultural carbon dioxide emissions. The experimental results show that there is a co-integration relationship between economic growth and the total intensity of agricultural carbon emissions, and between economic growth and the intensity of carbon emissions caused by five types of carbon sources: fertilizer, pesticide, agricultural film, agricultural diesel oil and tillage. Economic growth is the main driving factor of agricultural carbon dioxide emissions. In addition, technological progress has a strong role in promoting carbon emission reduction, but it has a certain randomness. However, the impact of energy consumption structure and population size on carbon emissions is not obvious., Competing Interests: The authors have declared that no competing interests exist.

To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The adoption and ratification of relevant policies, particularly the household enrolment system metamorphosis in China, led to rising urbanization growth. As the leading developing economy, China has experienced a drastic and rapid increase in the rate of urbanization, energy use, economic growth and greenhouse gas (GHG) pollution for the past 30 years. The knowledge of the dynamic interrelationships among these trends has a plethora of implications ranging from demographic, energy, and environmental and sustainable development policies. This study analyzes the role of urbanization in decoupling GHG emissions, energy, and income in China while considering the critical contribution of energy use. As a contribution to the extant body of literature, the present research introduces a new phenomenon called "the environmental urbanization Kuznets curve" (EUKC), which shows that at the early stage of urbanization, the environment degrades however, after a threshold point the technique effects surface and environmental degradation reduces with rise in urbanization. Applying the autoregressive distributed lag model and the vector error correction model, the paper finds the presence of inverted U-shaped curve between urbanization and GHG emission of CO 2 , while the same hypothesis cannot be found between income and GHG emission of CO 2 . Energy use in all the models contributes to GHG emission of CO 2 . In decoupling greenhouse gas emissions, urbanization, energy, and income, articulated and well-implemented energy and urbanization policies should be considered.

Spatiotemporal variations of industrial carbon emissions (IE) must be scientifically understood, which will be helpful to formulate reasonable emission reduction strategies. Given that spatial distribution of IE is irrelevant to space agents commonly used (such as population and nighttime light), estimation and spatialization methods for total carbon dioxide (CO2) emissions are not entirely suitable for IE. Therefore, this paper used greenhouse gases observing satellite level 4A product to estimate IE at the city level and used industrial land density to obtain the distribution of IE within the administrative districts. Sectoral emission inventories of 182 cities and a mosaic Asian anthropogenic emission inventory named MIX were used to verify the results. Then, spatiotemporal variation characteristics of China's IE were analyzed from multiple levels. Results showed that (1) the mean relative error of estimation results was 56.11%, among which 62 cities had relative error of less than 30%. Gridded IE in this paper had high consistency with MIX. (2) Cities with high IE experienced rapid growth from 2009 to 2012, followed by slower growth from 2012 to 2017. (3) Centroid of significant cold and hot spots moved to the southeast and northwest, respectively. Most cities with high annual IE growth had relatively low emission efficiency, mainly located in Inner Mongolia and Xinjiang. Aggregation of medium and high IE grids may represent high emission efficiency. Significant differences still exist between cities in IE, and sustainable development strategies should be formulated according to local conditions. Regions with high annual growth or low emission efficiency are the key to achieving IE reduction targets in future. [ABSTRACT FROM AUTHOR]

With the popularization of natural gas and the requirements for environmental protection, the development and utilization of natural gas is particularly important. The status of natural gas in China's oil and gas exploration and development is constantly improving, and the country is paying more and more attention to the exploitation and utilization of natural gas. The Upper Paleozoic tight sandstone in the Ordos Basin is characterized by low porosity, low permeability and a large area of concealed gas reservoirs. By injecting carbon dioxide into the formation, the recovery rate of natural gas can be improved, and carbon neutrality can be realized by carbon sequestration. Injecting greenhouse gases into gas reservoirs for storage and improving recovery has also become a hot research issue. In order to improve the recovery efficiency of tight sandstone gas reservoirs, this paper takes the complex tight sandstone of the Upper Paleozoic in the Ordos Basin as the research object; through indoor physical simulation experiments, carried out the influence of displacement rate, fracture dip angle, core permeability, core dryness and wetness on CO2 gas displacement efficiency and storage efficiency; and analyzed the influence of different factors on gas displacement efficiency and storage efficiency to improve the recovery and storage efficiency. The research results show that under different conditions, when the injection pore volume is less than 1 PV, the relationship between the CH4 recovery rate and the CO2 injection pore volume is linear, and the tilt angle is 45°. When the injection pore volume exceeds 1 PV, the CH4 recovery rate increases slightly with the increase in displacement speed, the recovery rate of CO2 displacement CH4 is between 87–97% and the CO2 breakthrough time is 0.7 PV–0.9 PV. In low-permeability and low-speed displacement cores, the diffusion of carbon dioxide molecules is more significant. The lower the displacement speed is, the earlier the breakthrough time is, and the final recovery of CH4 slightly decreases. Gravity has a great impact on carbon sequestration and enhanced recovery. The breakthrough of high injection and low recovery is earlier, and the recovery of CH4 is about 3.3% lower than that of low injection and high recovery. The bound water causes the displacement phase CO2 to be partially dissolved in the formation water, and the breakthrough lags about 0.1 PV. Ultimately, the CH4 recovery factor and CO2 storage rate are higher than those of dry-core displacement. The research results provide theoretical data support for CO2 injection to improve recovery and storage efficiency in complex tight sandstone gas reservoirs. [ABSTRACT FROM AUTHOR]

Following China and the United States, India is the third highest CO2 emitter in the world. With its fast rising population and an industry primarily reliant on coal and oil, the country's emissions will continue to rise unless appropriate measures are taken. In India generally the carbon sequestration is done by storing CO2 in sedimentary basins where it gets capped by the impermeable cap rocks. The study aims to unfold the other techniques of carbon sequestration in subsurface formations, except for narrating the different types of carbon capture and sequestration techniques along with its storage in different types of environments. For instance, abiotic and biotic environments for CO2 sequestration. It further talks about carbon injections of oceanic, geological, and terrestrial types, to name just a few. Types of carbon emission sources are discussed too. In this paper three different approaches are described for carbon mitigation, namely CarbFix, CO2 Plume technology and Carbon Trading. A prefeasibility study was done in order to implement the three techniques in Dholera geothermal region in Gujarat, India. In literature review, it can be seen how the three techniques can help in permanent mitigation of captured carbon through carbonate mineralization, power generation and industrial applications. For any project government and public participation is important. In this regard the study gives a brief understanding about the steps to be taken by government and the public to promote such projects for carbon mitigation. Besides, the steps to be taken in such projects for health and risk assessment were talked about in literature review too. [ABSTRACT FROM AUTHOR]

China's economy has made significant strides in the past three decades. As a direct result of China's "one belt, one road" (OBOR) initiative, the country's rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely dependent on the enormous amounts of energy currently being consumed and forms the foundation of the world's high levels of carbon emissions. It is generally agreed that the production of greenhouse gases, particularly carbon dioxide, is the primary contributor to the current state of climate change. In this paper, a CO2 emission prediction model based on Bi-LSTM is constructed. In order to conduct empirical tests on the model, this study uses data from South Asian countries and China from 2001 to 2020. China's CO2 emissions from 2022 to 2030 were predicted along with those of other countries in order to study the combined effects of the scientific and technological progress, industrial structures, and energy structure factors affecting CO2 emissions. When compared with the LSTM and GRU methods, the Bi-LSTM model's results produced lower MAE, MSE, and MAPE values, indicating that it performs better. According to the findings, carbon emissions represent a significant problem that will become much worse in the future due to China and India's high emissions, particularly in the next 10 years, if the government does not implement policies that help reduce those emissions. [ABSTRACT FROM AUTHOR]

Freshwater resources are scarce globally, and the increase in carbon dioxide (CO 2) concentration leads to both a decrease in soil moisture and arid climate, further limiting agricultural production. Therefore, it is critical to achieve water efficiency in agriculture under elevated CO 2 concentration. A comprehensive analysis was conducted on the research topic of efficient agricultural water under elevated CO 2 concentration using bibliometric methods. The results show that the number of papers on this research has changed from an accumulation phase (1992–2005, 395) to a growth phase (2006–2023, 963). "Carbon dioxide", "water-stress", "growth", "photosynthesis", "yield", and other keywords have been the focus of past research in this area. Kimball BA and Ainsworth EA are the most influential authors in this area. Leakey's (2009) paper in "Experimental Botany" was the most contributing study, summarizing six lessons about the effects of CO 2 enrichment on the relationship among carbon, nitrogen, and water in plants. The United States and China were the most influential countries. Over time, research has shifted from an early focus on atmospheric CO 2 change itself to the response of crops to elevated CO 2 in agricultural production. The efficient crop production strategy under the interaction of environmental factors is becoming a hot spot for future research, and the emission and use of greenhouse gases, the improvement of crop quality, and the efficient guidance of models are also worth exploring. Overall, this study presents a quantitative analysis and comprehensive review of past research conducted on the effect of water and fertilizer on agricultural production under CO 2 enrichment. It also offers suggestions and expectations for future research on the hot spot direction of efficient crop production under climate change. • The continuous research attention is closely related to climate change caused by CO 2 enrichment. • The main research fields included CO 2 enrichment, water stress, crop growth and photosynthesis. • The co-citation analysis reveals broad research clusters in the literature. • The new research focus will be interactive climatic factors, greenhouse gas recycling, and modeling. [ABSTRACT FROM AUTHOR]

An evaluation system has been established for assessing carbon dioxide emissions associated with asphalt pavement construction in China. As described in this paper, the system is based on the European driving force–pressure–state–impact–response model and uses the analytic hierarchy process combined with subjective and objective weighting and the comprehensive index method. It shows that state, response and pressure are the decisive factors. As such, the key factors that promote lower carbon dioxide construction of asphalt pavements are expressway construction investment, asphalt consumption, greenhouse gas effects, environmental quality and energy-saving and emissions-reduction technology. It is suggested that energy-saving and emissions-reduction technologies, such as warm mixing and geothermal regeneration, should be adopted in the construction of asphalt pavements and the concept of low carbon dioxide approaches should be promoted. The findings can provide technical support for decreasing the energy consumption and emissions in asphalt pavement construction. [ABSTRACT FROM AUTHOR]

This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS). [ABSTRACT FROM AUTHOR]

Several countries have weakened the carbon emission objectives to immediately revive the economy in the post-COVID-19 era. Therefore, it is a challenge worth addressing to readjust the economic development and carbon emissions after the COVID-19 pandemic. From the perspective of China's carbon emissions, this study shapes a multi-objective dynamic optimization model based on the material capital input and R&D support aspects. The proposed model imitates China's economic development, energy consumption, and carbon dioxide (CO2) emissions. The model provides theoretical suggestion for the government to revive economic development and reduce carbon emissions. In addition, this research paper compares the evolutionary path of carbon peak under the two scenarios. The first scenario requires maintaining the pre-epidemic development state and pace of carbon emission reduction, referred to as the baseline scenario (BS). The second scenario is termed the optimal scenario (OS) based on the model calculation. The study findings exhibit that China is not able to accomplish the 2030 CO2 emission peak objective, under the BS. However, China under the OS shall expectedly accomplish the 2030 carbon peak objective ahead of schedule, while the peak CO2 emissions shall be around 11.28 billion tons. Reportedly, at least 788 million tons of CO2 reduction contrasted with the BS. Furthermore, there is an 80.35% decline in energy intensity as compared to 2005. Consequently, the study results contribute theoretical guidance for the "green recovery" of China's economy and the adjustment of carbon emission reduction's path after the COVID-19 epidemic. Consistent with this, the research method also contributes to the theoretical research on carbon emissions at the national level while extending a new research perspective for the economic and environmental fields. [ABSTRACT FROM AUTHOR]

It is widely acknowledged that greenhouse gases (GHG) like carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) play a key role in the development of global climate change. 17% of China's GHG came from the agricultural industry. For China's future development, it is essential to investigate low-carbon emission paths in planting fields, as one of the key components of agriculture. In this study, the IPCC method was used to estimate the total carbon emission from cultivation in Eastern China. The Tapio decoupling model was used to study the relationship between economic growth and carbon emission. An extended STIRPAT stimulus model was established to predict the carbon emission of the planting industry in East China with three development paths. The results show that carbon emission in East China has shown a fluctuating downward trend with a peak in 1999, which has strong decoupling characteristics with economic growth. Adjusting agricultural structure and raising the mechanization rate can remarkably reduce agricultural carbon emission. Compared to 2020, carbon emission in 2035 will decrease by 12.50%, 13.68%, and 14.32% with Baseline, Low-carbon, and Enhanced Low-carbon scenarios, respectively. Effective measures such as optimizing planting structure by adjusting rice area, promoting intensive mechanization, and improving fertilizer use efficiency can reduce carbon emission actively. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions from wetlands have exacerbated global warming, attracting worldwide attention. However, the research process and development trends in this field remain unknown. Herein, 1865 papers related to wetlands GHG emissions published from January 2000 to December 2023 were selected, and CiteSpace and VOSviewer were used for bibliometric analysis to visually analyze the publications distribution, research authors, organizations and countries, core journal and keywords, and discussed the research progress, trends and hotspots in the fields. Over the past 24 years, the research has gone through three phases: the "embryonic" stage (2000–2006), the accumulation stage (2007–2014), and the acceleration stage (2015–2023). China has played a pivotal role in this domain, publishing the most papers and working closely with the United States, United Kingdom, Canada, Germany, and Australia. In addition, this study synthesized 311 field observations from 123 publications to analyze the variability in GHG emissions and their driving factors in four different types of natural wetlands. The results suggested that the average carbon dioxide (CO 2), methane (CH 4), and nitrous oxide (N 2 O) fluxes in different wetlands were significantly different. River wetlands exhibited the highest GHG fluxes, while marsh wetlands demonstrated greater global warming potential (GWP). The average CO 2 , CH 4 and N 2 O fluxes were 60.41 mg m−2·h−1, 2.52 mg m−2·h−1 and 0.05 mg m−2·h−1, respectively. The GWP of Chinese natural wetlands was estimated as 648.72 Tg·CO 2 -eq·yr−1, and CH 4 contributed the largest warming effect, accounting for 57.43%. Correlation analysis showed that geographical location, climate factors, and soil conditions collectively regulated GHG emissions from wetlands. The findings provide a new perspective on sustainable wetland management and reducing GHG emissions. [Display omitted] • A 24-year bibliometric analysis of GHG emissions from wetlands was conducted. • The historical evolution and future trends in the field were summarized. • River wetlands exhibited the highest GHG fluxes. • GWP of China's wetlands was estimated to be 648.72 Tg·CO 2 -eq·yr−1. • CH 4 emissions contribute 57.43% to the GWP value in China's wetlands. [ABSTRACT FROM AUTHOR]

Foresight of CO2 emissions from fuel combustion is essential for policy-makers to identify ready targets for effective reduction plans and to further improve energy policies and plans. A new method for forecasting the future development of China's CO2 emissions from fuel combustion is proposed in this paper by using grey forecasting theory. Although the existing fractional nonlinear grey Bernoulli model (denoted as FNGBM(1,1)) has been theoretically proven to enhance the adaptability to diverse sequences, its fixed integer-order differential derivative still impairs the performance to some extent. To this end, a varying-order differential derivative is introduced into the existing differential equation to enable a more flexible structure, thus improving the prediction ability of FNGBM(1,1). Specifically, because of the advantages of conformable fractional accumulation, the traditional differential derivative is first replaced by the conformable fractional differential derivative. As a consequence, the continuous conformable fractional nonlinear grey Bernoulli model (hereinafter referred to as CCFNGBM(1,1)) is proposed. To further increase the validity of the model, a metaheuristic algorithm, namely Grey Wolf Optimizer (GWO), is then applied to search for the optimal emerging coefficients for the proposed model. Two real examples and China's CO2 emissions from fuel combustion are considered to verify the effectiveness of the newly proposed model, the experimental results show that the newly proposed model outperforms other benchmark models in terms of forecasting accuracy. The proposed model is finally employed to forecast the future China's CO2 emissions from fuel combustion by 2023, accounting for 10,039.80 million tons. Based on the forecasts, several policy suggestions are provided to curb CO2 emissions. [ABSTRACT FROM AUTHOR]

Negative emission technologies driven by nature with less energy input, lower costs, and long carbon storage capacities are essential for meeting ambitious global carbon mitigation goals. This paper evaluates the carbon sequestration potential of bivalve shellfish farming because its sequestration process is driven by nature, and it is cost-effective and energy efficient. The carbon in shells and the carbon that enters sediments via bio-deposition are long-lived forms of carbon. Using China as a case study, a preliminary estimation suggests that the carbon sequestration efficiency and intensity of cultivated shellfishes are much higher than those of artificial forests. In China, approximately 6.23 Mt CO 2 -eq a−1 was fixed via net carbon sequestration during shellfish growth from 2015 to 2019. In addition, the farmed shellfishes provided 0.37 Mt of harvested protein, and approximately 37.39 Mt CO2-eq a-1 were reduced compared to the same amount of protein provided by beef, and thus, shellfish farming has the win-win benefits of carbon sequestration and high-quality food provision. More importantly, a total of 5.64 Gt CO 2 -eq, accounting for 17.63% of the total emissions in 2020, can be potentially sequestrated at the global scale under the world's largest farming area scenario. • A Negative Emission Technology via shellfish farming was introduced. • Carbon sequestration function and efficiency of shellfish farming were investigated. • Carbon sequestration potential for bivalve shellfish farming was evaluated globally. • Life cycle GHG emissions of shellfish farming in China was assessed. [ABSTRACT FROM AUTHOR]

A growing interest has recently been placed on the potential of nature-based solutions to help mitigate climate change, reflecting the importance of natural ecosystems as sources and sinks for greenhouse gases. Forests are of the hot debate – that sequester and also emit carbon dioxide (CO2). In this paper, we estimate the forest carbon sequestration potential for China. We show that, as the government plans, by 2020, the size of China's forest carbon stock will reach 12.87 billion tons, among which 5.73 billion tons will be from afforestation and reforestation (A/R). From the up-to-date data on AR activities (by 2018), we find that only 80% of the target sinks have been met. Scenario analysis shows that the carbon sequestered by the forests in 2020 is equivalent to 13%-17% of the industrial CO2 emission that year, with 6%-8% by A/R, 4%-6% by forest-management, 3%-4% by reduced-deforestation-and-forest-degradation, and 1% by wood-product-sink. [ABSTRACT FROM AUTHOR]

Agriculture has become an important source of greenhouse gas emissions. This paper calculates the agricultural GHGs emissions of 30 provinces in China from 1997 to 2016, and analyzes the emission intensity of GDP of carbon dioxide, methane and nitrous oxide by club convergence. After using the DEA CCR model to divide the club, the absolute β-convergence analysis method is used to verify the emission trends of various greenhouse gases. The results showed that the carbon dioxide emission intensity showed obvious absolute β convergence in all three clubs. Methane and nitrous oxide only have absolute β convergence in one of the clubs, respectively, and there is divergence in other clubs. Since the emission trends of the three greenhouse gases in the clubs are different, the formulation of reasonable reduction target allocation plan should be more detailed and targeted, and more stringent emission reduction targets should be set for provinces with high GHGs intensity of GDP in order to reduce it rapidly. [ABSTRACT FROM AUTHOR]

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO 2 e) in 2000 to 77.568 Mt CO 2 e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively. • GHG emissions from livestock in cities of the YRB continued to rise from 2000 to 2021. • GHG emissions per unit of GDP of livestock shown a downward trend. • Analyzing parameter of factors from spatiotemporal aspect by using GTWR model. • Probability of GHG emission transfer in urban livestock was spatially dependent. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

Maintaining crop outputs to feed its large population with limited resources while simultaneously mitigating carbon emissions are great challenges for China. Improving the efficiency of resource use in crop production is important in reducing carbon emissions. This paper constructs a methodological framework combining emergy-based indicator accounting and a nonseparable undesirable output slack-based measurement (SBM) data envelopment analysis (DEA) model. This framework is used to explore the efficiency of inputs and outputs and the greenhouse gas (GHG) emissions reduction potential for crop production systems, using Zhejiang province, China, as a case study. It is found that an emergy synthesis and a nonseparable undesirable output SBM-DEA framework is compatible with the case study. Crop production in Zhejiang province has relied heavily on an increase in agrochemical inputs to maintain agricultural output. Energy and chemical fertilizer use are determined as the province’s major carbon emissions sources. Although carbon emissions per unit of monetary output has decreased sharply, the carbon emissions per unit emergy output has increased, demonstrating a high carbon intensity reality. The DEA highlighted the differences in crop production efficiency, resource factor redundancy and carbon mitigation potential in the different prefectures of the province. To conclude this research, policies to support low carbon agriculture development, including subsidizing low carbon agriculture technology development and expansion and the cancellation of subsidies to high carbon production factors, such as chemical fertilizer production and sales, are discussed to conclude the research. [ABSTRACT FROM AUTHOR]

This paper examines the long-term effects and related short-term movements of energy security (ENS), economic policy uncertainty (EPU), and government ecological expenditure (GEE) on China's carbon dioxide (CO 2) emissions by applying the quantile autoregressive distributed lag approach. The empirical findings demonstrate that ENS and EPU have prominent negative and positive impacts, respectively, on CO 2 emissions in the long term for the majority of quantiles, while their short-term influences are less obvious. In addition, the effect of GEE is short-term and concentrated in high quantiles. The following are the article's main contributions. This study builds special energy security indicators based on the actual situation in China, providing a basis for better understanding the interaction mechanism between ENS and CO 2. Considering that China is the largest oil importer and greenhouse gas emitter, this study explores for the first time the linkages between ENS and CO 2. Both short- and long-term impacts are observed, and long-run effects are dominant in the linkages among variables, suggesting that the level of CO 2 emissions is mainly driven by long-term shocks. In addition, to clarify the nexus between ENS and CO 2 , time- and quantile-varying analyses are used, which take into account not only varied CO 2 emission levels but also distinct time periods for events. The findings emphasize the importance of market participants to form a better understanding of how ENS, EPU, and GEE affect CO 2 under different emission levels. Some detailed policies, including optimizing the energy consumption structure, making prudent economic policy adjustments, and strengthening ecological protection expenditures, are provided to curb pollution. • Energy security and carbon neutralization are main targets for China. • Energy security negatively affects carbon dioxide in the long-term. • Time-varying and quantile-varying features are captured for Energy security. • The quantile autoregressive distributed lag model is utilized in this paper. [ABSTRACT FROM AUTHOR]

Effective management of surface emissions from abandoned gob methane (AGM) is crucial for mitigating greenhouse gas emissions and ensuring public safety. An important geochemical characteristic of near-surface AGM migration is the potential presence of abnormal component concentrations in near-surface soil gas over abandoned coal gobs. To investigate this phenomenon, a surface geochemical survey was conducted based on four survey lines in the Dongyi and Dongsan abandoned gob groups in the Xinghua Coal Mine, Jixi Basin, in China. The gas chromatography technique was used to analyze the concentrations of methane, carbon dioxide, ethane, propane, and butane in the collected 43 soil gas samples. The results revealed a significant anomaly of soil gas concentrations, particularly methane and carbon dioxide anomalies, in the near-surface soil over abandoned gobs. The background concentration for methane was determined to be 7.49 ppm, with an anomalous threshold set at 10 ppm based on a statistical analysis and an iterative method. This threshold could be confirmed by examining the coupling and decoupling relationship between methane, carbon dioxide, and C2–3 as well. A spatial correlation between regions exhibiting anomalous methane and carbon dioxide concentrations and the positions of gob areas, abandoned surface wells, and faults was observed. Abandoned and sealed coalbed methane surface wells and faults near gas-rich gob areas have the potential to act as conduits for AGM leakage to the surface. Furthermore, concentrations of methane, carbon dioxide, and C2–3 in soil gas over abandoned coal gobs were significantly higher compared to areas unaffected by mining activities. This suggests that elevated concentrations of methane, carbon dioxide, and C2–3 in soil gas may originate from underground AGM. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the greenhouse gas (GHG)-related disclosure trends, content and strategies of the eight most high GHG-emitting Chinese power companies, over a period when government pressure to manage GHG emissions increased. Design/methodology/approach: Data were collected from the 2000-2009 annual reports, corporate social and environmental responsibility reports and websites of eight Chinese power companies. Content analysis results were supplemented with excerpts from documents written in English or Chinese. Legitimacy theory informed the interpretation of the findings. Findings: GHG-related disclosures increased from 2002 when the Chinese Government ratified the Kyoto Protocol and promulgated stringent environmental regulations. However, some expected types of GHG-related disclosure were absent or rare. Disclosure practices were found to be underpinned by reputation management objectives and reflected a symbolic rather than substantive legitimation strategy. Research limitations/implications: This study extends the literature on GHG-related disclosures by carbon-intensive firms and points to the need for future research to examine such disclosures in different countries to appreciate the variety in practice. Practical implications: While the Chinese Government appears to have driven the emergence of GHG-related disclosure practices, companies can effect improvement by expanding the scope and content of what they disclose. Also, the growing emphasis on website disclosures may present challenges in ensuring the reliability and assurance of GHG disclosures. Originality/value: This is the first study to examine GHG-related disclosure practices by Chinese power-generating companies, a sector crucial to managing the GHG effects of China's significant economic growth. [ABSTRACT FROM AUTHOR]

The development in uncrewed aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas emission quantification. Here, we report the development of a new air sampler, consisting of a pumped stainless coiled tube of 150 m in length with controlled time stamping, and its deployment from an industrial UAV to quantify CO 2 and CH 4 emissions from the main coking plant stacks of a major steel maker in eastern China. Laboratory tests show that the time series of CO 2 and CH 4 measured using the sampling system is smoothed when compared to online measurement by the cavity ring-down spectrometer (CRDS) analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field testing, the air sampler was mounted on the UAV and flown in virtual boxes around two stacks in the coking plant of the Shagang Group (steel producer). Mixing ratios of CO 2 and CH 4 in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO 2 and CH 4 emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be 0.12±0.014 t h -1 for CH 4 and 110±18 t h -1 for CO 2 , the latter being in excellent agreement with material-balance-based estimates. A Gaussian plume inversion approach was also used to derive the emission rates, and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods. [ABSTRACT FROM AUTHOR]

Coal-fired power plants, as major anthropogenic CO2 emission sources, constitute one of the largest contributors to global greenhouse gas emissions. Accurately calculating the dispersion process of CO2 emissions from these point sources is crucial, as it will aid in quantifying CO2 emissions using remote sensing measurements. Employing the Lagrangian Particle Dispersion Theory Model (LPDTM), our study involves modeling CO2 diffusion from point sources. Firstly, we incorporated high-resolution DEM (Digital Elevation Model) and artificial building elements obtained through the Adaptive Deep Learning Location Matching Method, which is involved in CO2 simulation. The accuracy of the results was verified using meteorological stations and aircraft measurements. Additionally, we quantitatively analyzed the influence of terrain and artificial building characteristics on high spatial resolution atmospheric CO2 diffusion simulations, revealing the significance of surface characteristics in dispersion modeling. To validate the accuracy of the LPDTM in high-resolution CO2 diffusion simulation, a comparative experiment was conducted at a power plant in Yangzhou, Jiangsu Province, China. The simulated result was compared with observation from aerial flights, yielding the R2 (Correlation Coefficient) of 0.76, the RMSE (Root Mean Square Error) of 0.267 ppm, and the MAE (Mean Absolute Error) of 0.2315 ppm for the comparison of 73 pixels where the plume intersected with flight trajectories. The findings demonstrate a high level of consistency between the modeled CO2 point source plume morphology and concentration quantification and the actual observed outcomes. This study carried out a quantitative assessment of the influence of surface features on high-resolution atmospheric CO2 point source diffusion simulations, resulting in an enhanced accuracy of the simulated CO2 concentration field. It offers essential technological and theoretical foundations for the accurate quantification of anthropogenic CO2 emissions using top-down approaches. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems may act as a source or a sink for the atmospheric greenhouse gases, carbon dioxide (CO), methane (CH), and nitrous oxide (NO), depending on land use and management. This paper reviews the literature on carbon, CH, and NO fluxes from terrestrial ecosystems in China, and analyzes its national greenhouse gas budget. Carbon storage in biomass and soils in Chinese terrestrial ecosystems decreased in the past 300 years, due to deforestation and expansion of cultivated land, and reached a minimum in the late 1970s. Since then, carbon storage has increased at an estimated rate of 0.19 to 0.26 Pg C yr, mainly owing to reforestation and afforestation. CH emission from natural wetlands decreased from 6.65 Tg CH yr in 1990 to 5.71 Tg CH yr in 2000 owing to the decrease in wetland area. CH emission from flooded rice fields was 7.41 Tg CH yr. At the same time, aerobic soils took up atmospheric CH at a rate of 2.56 Tg CH yr. Nitrous oxide emission from forestlands, grasslands, and farmlands was positively correlated with precipitation at a national scale, and the emission rate was positively correlated with the CH uptake rate of forestlands and grasslands ( P<0.01). Natural NO sources were estimated to be 419 Gg N yr and anthropogenic sources (from farmlands) to be 292 to 476.3 Gg N yr, with a mean of 372.6 Gg N yr. The integrated budget of greenhouse gasses indicates that Chinese terrestrial ecosystems act as a small net sink for global warming potential (GWP), ranging from 0.04 to 0.32 Pg CO-eq yr, in a striking contrast to terrestrial ecosystems globally, which are a source of 2.75 to 6.78 Pg CO-eq yr. The ratios of anthropogenic to natural sources of CH and NO are much larger in Chinese terrestrial ecosystems than they are in global averages, reflecting greater human disturbance of terrestrial ecosystems in China. [ABSTRACT FROM AUTHOR]

Based on carbon spot prices selected from seven carbon pilots, we assess the financial performances related to carbon volatility in China on the overall perspective. According to the results, the Chinese carbon market fluctuated severely at the beginning of carbon trading, but has stabilised in general, despite several dramatic changes related to ‘yearly compliance events’. Long-term memory exists in the volatility series. Moreover, asymmetry exists in the Chinese carbon market, and volatility reacts more severely to good news than to bad news. Finally, we discuss our empirical results, and make certain suggestions regarding firms’ awareness, international cooperation and individual investors not only for policy makers in China but also for other developing countries who are contemplating either commencing carbon trading or improving the current market. [ABSTRACT FROM AUTHOR]

• The paper analyze the drivers of the per-capita CO 2 emissions inequality in building sector across China. • Economic growth helps to narrow regional disparities for residential buildings. • Energy intensity is the primary contributor to emissions inequality. • This paper highlights the importance of per-capita CO 2 emissions in formulating carbon peak planning. There are significant regional differences in CO 2 emissions in China's building sector. Analyzing and understanding this geographic inequality and its drivers is crucial for balanced regional development and greenhouse gas (GHG) emissions reduction. In this paper, we estimated the CO 2 emissions of China's building sector at the provincial level and then calculated the Theil Index of per-capita CO 2 emissions generated from different building types. Based on these results, a Kaya identity was applied to analyze the drivers of the inequality in CO 2 emissions across China. We found that the inequality index of the different types of buildings makes a significant difference. In general, the Theil Index for public buildings and urban buildings is higher than that for rural buildings. Income, energy intensity and energy mix are the principal drivers of regional disparity of per-capita emissions. Economic growth helps to narrow regional disparities for residential buildings, but its contribution is not significant for public buildings. For all building types, energy intensity is the primary contributor to emissions inequality, and the imbalanced implementation of energy efficiency policies is a leading factor. Energy mix plays an increasing role in the regional disparities of per-capita CO 2 emissions, especially for rural buildings. Reducing these regional disparities is crucial to China's goal of achieving peak GHG emissions and reaching carbon neutrality. This paper highlights the importance of per-capita CO 2 emissions in formulating carbon peak planning, allocating regional emissions reduction targets, formulating building energy policies and allocating low-carbon resources. [ABSTRACT FROM AUTHOR]

As cities become increasingly interconnected in production and lifestyles, metropolitan areas have become the main areas for carbon dioxide (CO2) emissions. This article is the first to investigate the potential for peak CO2 emissions in China's metropolitan areas. Specifically, this study constructs logistic growth models using time series data of CO2 emissions from 1997 to 2017 for 26 metropolitan areas. Secondly, this study combines scenario analysis and the STIRPAT model for projection. Moreover, using the grid search method, this study optimizes ridge regression's penalty term coefficient (alpha). The results show that most metropolitan areas in China entered the saturation stage of carbon emission in 2016, but it is still challenging to achieve the goal of peak carbon dioxide emission by 2030. Per capita GDP, the proportion of the secondary industry, population, and urbanization positively affects CO2 emissions, and green technology innovation negatively affects CO2 emissions. Therefore, to achieve the peak CO2 emissions target, China should develop differentiated carbon reduction strategies for metropolitan areas and focus on the optimization and upgrading of industrial structure, the improvement of green technology level, and the low carbonization of residents' lifestyles in metropolitan areas. The significance of this study is that it helps policymakers to project potential peak CO2 emission trajectories from a bottom-up perspective, and its findings provide insights into China's peak CO2 emissions pathway. [ABSTRACT FROM AUTHOR]

In the modern era, urban freshwater bodies play a significant role in global carbon (C) budgeting, therefore, impacting climate change under rising global mean temperature. However, the trend, magnitude and drivers of greenhouse gas (GHG) emissions in these urban freshwater bodies of China remain uncertain. This study investigated temporal changes in GHG emissions in urban water bodies, including artificial lakes, reservoirs, aquaculture ponds and rivers, within a year in Nanjing city in the areas of the Yangtze River delta of China. In addition, meteorological and hydrochemical parameters were measured to elucidate the key drivers of GHG emissions. The results showed that the average annual flux of carbon dioxide (CO2) and methane (CH4) in aquaculture ponds was estimated to be 1355.6 mg CO2 m−2 day−1 and 116.6 mg CH4 m−2 day−1, followed by that of artificial lakes were 1172.2 mg CO2 m−2 day−1 and 44.1 mg CH4 m−2 day−1, rivers reached 775.9 mg CO2 m−2 day−1 and 23.9 mg CH4 m−2 day−1 and reservoirs were 170.1 mg CO2 m−2 day−1 and 7.2 mg CH4 m−2 day−1, respectively. The results further suggest that although artificial lakes and aquaculture ponds occupied only 23% of the cumulative area under lakes and ponds in the Yangtze River delta, contribute approximately 43%, about 27.5 Gg C, of total fluxes. Furthermore, high concentrations of dissolved organic carbon (DOC) and low dissolved oxygen (DO) coincided with the high GHG emissions. The study suggests that DO, DOC, temperature and wind speed are the key factors impacting the potential of GHG emissions in urban freshwater ecosystems. Strategic mitigation measures in the vicinity of the urban freshwater bodies could efficiently reduce carbon emissions in the future. [ABSTRACT FROM AUTHOR]

As one of the most influential greenhouse gases, carbon dioxide (CO2) has a profound impact on the global climate. The spaceborne integrated path differential absorption (IPDA) lidar will be a great sensor to obtain the columnar concentration of CO2 with high precision. This paper analyzes the performance of a spaceborne IPDA lidar, which is part of the Aerosol and Carbon Detection Lidar (ACDL) developed in China. The line-by-bine radiative transfer model was used to calculate the absorption spectra of CO2 and H2O. The laser transmission process was simulated and analyzed. The sources of random and systematic errors of IPDA lidar were quantitatively analyzed. The total systematic errors are 0.589 ppm. Monthly mean global distribution of relative random errors (RREs) was mapped based on the dataset in September 2016. Afterwards, the seasonal variations of the global distribution of RREs were studied. The global distribution of pseudo satellite measurements for a 16-day orbit repeat cycle showed relatively uniform distribution over the land of the northern hemisphere. The results demonstrated that 61.24% of the global RREs were smaller than 0.25%, or about 1 ppm, while 2.76% of the results were larger than 0.75%. The statistics reveal the future performance of the spaceborne IPDA lidar. [ABSTRACT FROM AUTHOR]

Assessing the mitigation effect on greenhouse gas (GHG) reduction of the National VI Emissions Standard bears great significance in enhanced actions on climate change in China. This research established a reference scenario and National VI scenario to evaluate whether the National VI Emissions Standard could make a contribution to synergistic emission reduction. Here are the main conclusions: carbon dioxide (CO2) was the majority GHG emissions type, accounting for around 99% of GHG emissions between 2019 and 2025 for these two scenarios; implementing the National VI Emissions Standard will not mitigate total GHG emissions from 2019 to 2025, but the National VI Emissions Standard could help mitigate methane (CH4) and nitrous oxide (N2O), not CO2 if considering the mitigation effect from the perspective of GHG type. Based on the results and discussion, this research suggests to consider the economic and technical feasibility of incorporating carbon emissions limits into the National VII Emissions Standard while continuing the evaluation of the National VI Emissions Standard. [ABSTRACT FROM AUTHOR]

This study looks at the global trajectory of the relationship between GDP (gross domestic product) and CO2 (carbon dioxide) emission in the time-series, comparative, and transitional point of view (from Y1992 to Y2014). It sets up a measurement framework and compares thirty-seven countries (thirty-six OECD countries and China) through the fuzzy-set ideal type analysis while focusing on the comparative and relational types. This research found that economic growth (GDP) and environmental problems (CO2 emissions) are tied together in a very solid path-dependent relationship. Particularly, the analysis of comparisons among OECD countries and China shows that the relationship between GDP and CO2 emissions is very firmly coupled, unlike the previous non-combination of one-dimensional statistics that are based on the environmental Kuznets curve (EKC) hypothesis. In short, it draws out and highlights the research implications that the existing conventions regarding the relationship between sustained economic growth and GHG (greenhouse gas) emissions reductions are ill-founded at the international comparative level. This paper reiterates the importance of relevant regulatory policies in order to reduce the harmful external effects of GHG and a need for policy measures to solve the problem in the long term. [ABSTRACT FROM AUTHOR]

Cities consume large amounts of fossil fuels and this results in significant increase of global anthropogenic greenhouse gases. Using city-level carbon dioxide emission data from Shijiazhuang, a traditional heavy manufacturing city and one of the key cities in Jing-Jin-Ji urban agglomeration in Northern China, this paper employs logarithmic mean Divisia index decomposition method (LMDI) to explore the influence of energy intensity, consumption structure, industry structure, per capita Gross Domestic Product (GDP), and population on Shijiazhuang's total carbon dioxide emissions from 2005 to 2016. The LMDI method is further extended to analyze the impacts of above factors at the industry-segment level. This paper finds that the reduction of energy intensity is the major contributor of decreasing carbon dioxide emissions in Shijiazhuang, whereas the growth of per capita GDP is the main driving force for emission accretion. The dominant industrial segments contributing to increasing emissions in Shijiazhuang City from 2005 to 2016, have changed from CMD (coal mining and dressing), EPSH (electric power, steam and hot water production and supply) to SPFM (smelting and pressing of ferrous metals) and PPC (petroleum processing and coking). The CMD industrial segment shows a significant carbon reducing effort and indicates a strong decoupling status. However, the SPFM and PPC respectively show expansive negative decoupling and weak decoupling status, enlightening a change in the policy focus when Shijiazhuang formulates its emission-reduction plans in the future. This study provides important policy insights for the heavy manufacturing cities in other countries with similar industrial structure, as the industry-based carbon mitigation policies should always be adjusted in different stages of the cities' development according to the change of carbon emission driving industries. [ABSTRACT FROM AUTHOR]

Quantitative accounting of greenhouse gas (GHG) emissions has become an important global focus. GHG emissions from the waste sector have high potential in GHG emissions reduction. We analyzed the GHG emissions inventory in the waste sector of the European Union, Germany, the United Kingdom, the United States of America, and Canada from 1990 to 2019. Landfill disposal was the main category of GHGs from the waste sector, with a contribution rate between 69% and 95%. Landfill disposal also played a prominent role in emission reduction, with a contribution rate higher than 86%. GHG emissions from landfill sites in China were calculated using the inventory analysis method recommended by the IPCC and combined with actual situations. The results showed that the highest GHG emissions from landfill disposal in China occurred in 2020, with an estimated 165 million tons of carbon dioxide (CO2) equivalent. In 2019, the per capita GHG emissions from landfill sites in China was 117 kg CO2 equivalent/person, which was higher than Germany (87 kg CO2 equivalent/person) but lower than the European Union (189 kg CO2 equivalent/person). [ABSTRACT FROM AUTHOR]

In view of global warming, caused by the increase in the concentration of greenhouse gases, China has proposed a series of carbon emission reduction policies. It is necessary to obtain the spatiotemporal distribution of carbon emissions accurately. Nighttime light data is recognized as an important basis for carbon emission estimation. A large number of research results show that there is a positive correlation between nighttime light intensity and carbon emission. However, in the current context of China's industrial reforms, this positive relationship may not be entirely correct. First, we correct the nighttime light data from different satellites and established a long-term series data set. Then, we verify the positive correlation between nighttime light and carbon emission. However, the time scale of emission data often lags, and the carbon concentration data are released earlier and are more accurate than emission data. Therefore, we propose to investigate the relationship between nighttime light and carbon concentration. It is found that there may be different correlations between nighttime light and the carbon concentration, due to different urban industrial structure and development planning. Therefore, by exploring the relationship between nighttime light and the carbon concentration, the existing carbon emission estimation model can be modified to improve the accuracy of the emission model. [ABSTRACT FROM AUTHOR]

For the greenhouse gas (GHG) emissions in China, little attention has been given to CH 4 emissions and related emission mitigation. This paper presents a detailed bottom-up estimation and comparison analysis of China's CH 4 and CO 2 emissions for the first time. China's CH 4 emissions are shown with comparable importance to the CO 2 emissions at the national and regional levels. The national total CH 4 emission in 2008 amounts to 39 Tg, equivalent to about 1/8, 1/3 and 3/5 of the total CO 2 emission by the 100-year global warming potential (GWP) factor, the 20-year GWP factor and the global thermodynamic potential factor, respectively. Increasing CH 4 emissions could compromise China's efforts to mitigate its GHG emissions. In contrast to energy-dominated emission pattern for CO 2 , the major sources of China's CH 4 emissions are coal mining, enteric fermentation, rice cultivation and waste management. Meanwhile, there exists a large gap between the eastern coastal regions and the western and central inland regions in the emission magnitude and emission intensity for CH 4 and CO 2 , with different mitigation flexibilities. Reducing CH 4 emissions should be integrated into the national and regional policies for GHG emission mitigation. In some central and western regions such as Shanxi, Henan, Sichuan, Guizhou, Qinghai and Tibet, the inclusion of CH 4 emission intensity reduction can be more cost-effective than only setting a target for CO 2 emission intensity to reduce the regional GHG emission intensity. [ABSTRACT FROM AUTHOR]

Naturally occurring CO 2 often coexists with hydrocarbon accumulations on continental margins around the world, the presence of which may affect hydrocarbon production as a greenhouse gas. In this paper we focus on the natural CO 2 in the Surennuoer Oilfield of the Hailar Basin, and investigate CO 2 origin, distribution, related tectonic controls and accumulation mechanisms using geochemical, petrophysical and seismic data. Results show that the CO 2 is of inorganic origin due to the degassing of magma from the deep crust or mantle, and is mainly stored in structural traps of N1 Member. There are close spatial and temporal relationships among CO 2 distribution, major fault distribution and underneath igneous bodies, indicating a genetic link. The magmatic events and major faults are proposed to be the key controlling factors of CO 2 distribution, which provided CO 2 supply and migration pathways for both magma and degassed CO 2. Additionally these faults also play a role in forming structural traps to store CO 2. The sandstone reservoirs of low porosity and low permeability may play a limited role due to their poor reservoir quality. Two CO 2 accumulation models are outlined in the Surennuoer strike-slip fault zone and the S3 fault zone. The former is characterized by shallower magmatic igneous body and a small amount of CO 2 in the shallower N2 Member in addition to N1 Member. The Surennuoer strike-slip faults may have further channelled magma upwards which initially intruded along the basin-controlling fault, while the magma under the S3 fault zone did not migrate further upward along the S3 faults. Generally this study provides a detailed understanding of CO 2 distribution, accumulation models and geological controls which may guide future hydrocarbon production in the study area. • The CO 2 in the Surennuor Oilfield is proposed to be of inorganic origin from magma degassing. • The CO 2 mainly occurs in structural traps of N1 Member. • Magmatic events and faults may play the major role in controlling the CO 2 accumulation. • Sandstone reservoirs of poor physical properties may play a secondary role in controlling the CO 2 accumulation. • Two accumulation models of the natural CO 2 in the study area are outlined. [ABSTRACT FROM AUTHOR]

Abstract: Northern wetlands are critically important to global change because of their role in modulating atmospheric concentrations of greenhouse gases, especially CO2 and CH4. At present, continuous observations for CO2 and CH4 fluxes from northern wetlands in Asia are still very limited. In this paper, two growing season measurements for CO2 flux by eddy covariance technique and CH4 flux by static chamber technique were conducted in 2004 and 2005, at a permanently inundated marsh in the Sanjiang Plain, northeastern China. The seasonal variations of CO2 exchange and CH4 flux and the environmental controls on them were investigated. During the growing seasons, large variations in net ecosystem CO2 exchange (NEE) and gross ecosystem productivity (GEP) were observed with the range of −4.0 to 2.2 (where negative exchange is a gain of carbon from the atmosphere) and 0–7.6gCm−2 d−1, respectively. Ecosystem respiration (RE) displayed relatively smooth seasonal pattern with the range of 0.8–4.2gCm−2 d−1. More than 70% of the total GEP was consumed by respiration, which resulted in a net CO2 uptake of 143±9.8 and 100±9.2gCm−2 for the marsh over the growing seasons of 2004 and 2005, respectively. A significant portion of the accumulated NEE-C was lost by CH4 emission during the growing seasons, indicating the great potential of CH4 emission from the inundated marsh. Air temperature and leaf area index jointly affected the seasonal variation of GEP and the seasonal dynamic of RE was mainly controlled by soil temperature and leaf area index. Soil temperature also exerted the dominant influence over variation of CH4 flux while no significant relationship was found between CH4 emission and water table level. The close relationships between carbon fluxes and temperature can provide insights into the response of marsh carbon exchange to a changing climate. Future long term flux measurements over the freshwater marsh ecosystems are undoubtedly necessary. [Copyright &y& Elsevier]

Abstract: Greenhouse gas (GHG) emission from geological sources such as volcanic activity, seabed gas hydrate release, hydrocarbon seepage as well as uncontrolled combustion of fossil fuels is erratic and difficult to quantify. In this paper we assess the GHG emission due to spontaneous combustion of in-situ coal deposits (‘coal fires’). This problem is aggravated by human intervention (mining activities) which on the other hand allows better constrained estimations and improved reduction strategies, provided modern mining practices are employed. In this study we present three case studies on coal fire-related GHG emission quantification on provincial scale in China, and we propose an integrated quantification aimed at the joint analyses of local knowledge, geophysical data, and remote sensing data with the objective to retrieve unbiased numbers. As a first estimate, we conclude that the emissions of GHGs from coal fires in China account for well less than 0.22% of all global fossil fuel related CO2 emissions, most likely even less than 0.1%. This is much less than the previously estimated 2–3%. [Copyright &y& Elsevier]

Abstract: The rapid growth in coal and oil consumption has led to increasing emissions of greenhouse gases as well as air pollutants in China. In response to this, the Chinese government has begun to formulate policies to retard the increasing use of energy consumption and to improve air quality. This paper attempts to quantify the co-benefits of reducing carbon dioxide emissions and improving air quality from policies that are originally formulated to improve energy efficiency and to abate emissions of air pollutants from energy use. The present authors have developed an integrated approach, combining an energy projection model, an emission estimation model, an air quality simulation model, and a health benefit evaluation model, to assess the co-benefits of two different sets of energy policies of China. The modeling results show that significant benefits, including 1469 million tonnes of reduced emissions of CO2, 12–32% decline in air pollutant concentrations, and more than 100 billion US$ of health benefit, can be achieved around the year 2030 if aggressive energy policies are implemented. The analyses suggest that such energy policies could do a lot of benefit to the environment. Moreover, better industry structure and energy structure is essential for higher air quality. [Copyright &y& Elsevier]