What is the probability of achieving the carbon dioxide emission targets of the Paris Agreement? Evidence from the top ten emitters

Simulation of emission reduction path under the path of differentiated energy transformation in China's industrial cities: a case study of Shanghai

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model.

A Preliminary Assessment of Global CO2: Spatial Patterns, Temporal Trends, and Policy Implications

This study offers a comprehensive analysis of the distribution, evolution, and driving factors of CO2 emissions from 1990 to 2016 at multiple spatial scales. Utilizing 26 indicators encompassing various facets of CO2 emissions, it is employed principal component analysis (PCA) and empirical orthogonal functions (EOFs) to identify the dominant characteristics of global CO2 emissions. This model retained three core components, accounting for 93% of the global CO2 variation, reflecting emission trajectories and associated economic metrics, such as Gross domestic product (GDP). The analysis differentiated the effects of these components based on countries' economic standings. Using a novel aggregated index, significant national contributors to global CO2 emissions are pinpointed. Notably, the leading contributors are found among developed nations (e.g., the United States, Canada, Japan), Gulf states (e.g., Saudi Arabia, Qatar), and emerging economies (e.g., China, Brazil, Mexico). Furthermore, these results highlight that shifts in global CO2 emissions over the past 30 years are predominantly influenced by factors like industrial emissions and GDP. Results also demonstrate a distinct relationship between a country's CO2 emissions and its physical and socioeconomic factors. Specifically, the nation's coastline length, population density in coastal regions, and the diversity of its climatic conditions significantly influence its carbon footprint.

Agricultural carbon emissions in Zhejiang Province, China (2001-2020): changing trends, influencing factors, and has it achieved synergy with food security and economic development?

Given the huge carbon footprint of agricultural activities, reduction in agricultural carbon emission (ACE) is important to achieve China's carbon peaking and carbon neutrality goals, but it may affect agricultural food security and economic development. Therefore, it is important for scientific carbon reduction measures to understand the multi-year trends and the influencing factors of ACE, and clarify whether the process of ACE affects food security and economic development. This study analyzed the trends of total ACE and ACE caused by different agricultural carbon sources (ACS) from 2001 to 2020 in Zhejiang Province, then we revealed the main influencing factors of ACE based on the logarithmic mean Divisia index (LMDI) model and dissected the relationship between ACE and food security and economic development. Results show that the total ACE fluctuated from 6.10 Mt in 2001 to 3.93 Mt in 2020, and the process included a decrease in 2001-2003 and 2005-2020 and an increase in 2003-2005. The decrease in ACE, from 2001 to 2014, was mainly due to the decline in rice acreage, which contributed 90.38%; from 2014 to 2020, it was by the reduction in the use of fertilizer, diesel, and pesticide, which contributed 83.9%. As drivers, agricultural economic development effect and total population size effect drove 4.25 and 1.54 Mt of ACE, respectively. As inhibitors, planting structure effect, technology development effect, and population structure effect inhibited 3.12, 2.11, and 2.74 Mt of ACE, respectively. With the reduction of ACE, the agricultural economy continued to grow, but the food security situation was pessimistic, indicating that ACE reduction has achieved synergy with economic development, but not with food security.

Has the digital economy improved the ecological environment? Empirical evidence from China

The main objectives of this study incorporate the ecological environment index (ENV) and the digital economy index (DIG) into the environmental Kuznets (EKC) model and examine the income effects, scale effects, structural effects, technology effects, and government expenditures on the ecological environment, collating panel data for 31 provincial administrative regions in China over the period 2011-2019. The panel entropy value method was first applied to calculate the ecological environment index (ENV) and the digital economy composite index (DIG). Secondly, a threshold effect test is conducted with the digital economy as the threshold variable, and it is found that there are two threshold values in the model. From the threshold regression results, the impact of the digital economy on the ecological environment shows a positive "U" shape. At this stage, except for individual years in each province, most of the provinces are in the second half of the positive "U" curve. The coefficients of the income effect and scale effect are not significant, while the coefficients of structural effect and technology effect and government expenditure are significantly positive. From the results of the study, it is clear that the digital economy has a significant contribution to the improvement of the ecological environment in China at this stage. Policymakers should go further to promote the development of the digital economy while encouraging regional industrial structure optimization and increasing technological input support to ensure that the environment and economic development are coordinated in the digital economy era.

Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm

China's carbon reduction is of substantial significance in combating global climate change. In the context of the COVID-19 epidemic hit and economic and social development uncertainty, this study intends to discover whether China can attain the strategic destination of carbon peaking by 2030 and carbon neutrality by 2060 on schedule. Toward this aim, the grey relation analysis (GRA) is applied to filter the elements influencing carbon emissions to downgrade the dimensionality of indicators. A hybrid prediction is proposed integrated with Elman neural network (ENN) and sparrow search algorithm (SSA) to explore the potential for China to carbon neutrality from 2020 to 2060. The results reveal eight elements including GDP per capita, population, urbanization, total energy consumption and others are highly correlated with carbon emissions. China has a good chance of carbon peaking from 2028 to 2030, with a value of 11568.6-12330.5 Mt, while only one scenario can achieve carbon neutrality in 2060. In the neutral scenario, China should reach a proportion of renewable energy exceeding 80%, the urbanization rate reaching 85% and energy consumption controlling within 6.5 billion tons. A set of countermeasures for carbon abatement are presented to facilitate the implementation of carbon neutrality strategy.

The role of natural resources, renewable energy, and globalization in testing EKC Theory in BRICS countries: Method of Moments Quantile

This paper aims to validate the EKC hypothesis for BRICS countries, in the presence of natural resources, renewable energy, and globalization factors. FMOLS, DOLS, Method of Moments Quantile Regression (MMQR), and heterogeneous panel causality tests have been applied on the BRICS panel from 1990 to 2014. According to FMOLS and DOLS techniques, the EKC hypothesis does exist in BRICS countries in the presence of alternative energy resources and globalization, whereas quantile level analysis does not support globalization as a significant factor for environmental degradation. Quantile regression validates the EKC hypothesis with a direct association of natural resources and inverse association of renewable energy with environmental degradation. Heterogeneous panel causality also confirms the bidirectional Granger causality between all the variables and CO2, except globalization, which means that panel causality is endorsing the results of MMQR. Thus, it is recommended to encourage the usage of renewable energy resources in BRICS countries.

Carbon mitigation by quota allocation

To avoid the calamitous consequences of an even warmer world, the efforts are focused on overarching and immediate solutions to reduce the greenhouse gases. The emissions trading scheme is deemed worldwide as an ecological and robust management mechanism to curb carbon emissions. The challenge is how to design such a scheme to attain the basic purpose of installing a uniform system and equilibrium efficiency achievement. For the first time, existing idea of group method of data handling (GMDH) type neural network (NN) is developed to predict capital stock, labor force, CO₂ emission, energy consumption, and gross domestic product (GDP) based on past information for the top-26 emitting countries. Then, this study deals with the allocation of emission quotas by proposing a two-step optimization mechanism that takes full advantages of the context-dependent data envelopment analysis (DEA) and equilibrium efficient frontier DEA (EEFDEA) models. In the first step, under the premise of constant total carbon emissions, a pragmatic efficiency-oriented carbon quota trading system is established to attain equilibrium state. In the second step, under the measured total emission mitigation target, the carbon quotas allocation mechanism is formulated to translate the top emitters' mitigation target into national purposes from two features of efficiency and fairness as well as to specify the comprehensive targets for the top emitters to maintain their equilibrium state. Two of the main findings are: 1) The top emitters should decrease the total CO2 emission by at least 37% by 2023. 2) In light of the CO2 emission mitigation allocation, the countries with larger potentials are China, Japan, and the US yet to receive the larger portions of 20%, 9% and 22%, respectively. Finally, the allocation method that takes regional heterogeneity into account is more logical since it alleviates pressure on the emitters to decrease carbon emissions and establishes a baseline for distributing CO₂ emission quotas across the emitters to enhance adaptation to nations' present circumstances.

Strategic Environmental Assessment of Land Transportation: An Application of DEA with Undesirable Output Approach

The efficiency of land transportation contributes significantly to determining a country’s economic and environmental sustainability. The examination of land transportation efficiency encompasses performance and environmental efficiency to improve system performance and citizen satisfaction. Evaluating the efficiency of land transportation is a vital process to improve operation efficiency, decrease investment costs, save energy, reduce greenhouse gas emissions, and enhance environmental protection. There are many methods for measuring transportation efficiency, but few papers have used the input and output data to evaluate the ecological efficiency of land transportation. This research focuses on evaluating the environmental efficiency for land transportation by using the data envelopment analysis (DEA) method with undesirable output to handle unwanted data. By using this, the paper aims to measure the performance of land transportation in 25 Organization for Economic Co-operation and Development (OECD) countries in the period of 2015–2019, considered as 25 decision-making units (DMUs) in the model. For identifying the ranking of DMUs, four inputs (infrastructure investment and maintenance, length of transport routes, labor force, and energy consumption) are considered. At the same time, the outputs consist of freight transport and passenger transport as desirable outputs and carbon dioxide emission (CO2) as an undesirable output. The proposed model effectively determines the environment-efficient DMUs in a very time-efficient manner. Managerial implications of the study provide further insight into the investigated measures and offer recommendations for improving the environmental efficiency of land transportation in OECD countries.

Impact of drivers on real-driving fuel consumption and emissions performance

Eco-driving has attracted great attention as a cost-effective and immediate measure to reduce fuel consumption significantly. Understanding the impact of driver behaviour on real driving emissions (RDE) is of great importance for developing effective eco-driving devices and training programs. Therefore, this study was conducted to investigate the performance of different drivers using a portable emission measurement system. In total, 30 drivers, including 15 novice and 15 experienced drivers, were recruited to drive the same diesel vehicle on the same route, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results show that novice drivers are less skilled or more aggressive than experienced drivers in using the accelerator pedal, leading to higher vehicle and engine speeds. As a result, fuel consumption rates of novice drivers vary in a slightly greater range than those of experienced drivers, with a marginally higher (2%) mean fuel consumption. Regarding pollutant emissions, CO and THC emissions of all drivers are well below the standard limits, while NO_x and PM emissions of some drivers significantly exceed the limits. Compared with experienced drivers, novice drivers produce 17% and 29% higher mean NO_x and PM emissions, respectively. Overall, the experimental results reject the hypothesis that driver experience has significant impacts on fuel consumption performance. The real differences lie in the individual drivers, as the worst performing drivers have significantly higher fuel consumption rates than other drivers, for both novice and experienced drivers. The findings suggest that adopting eco-driving skills could deliver significant reductions in fuel consumption and emissions simultaneously for the worst performing drivers, regardless of driving experience.

Alkalinity Generation Constraints on Basalt Carbonation for Carbon Dioxide Removal at the Gigaton-per-Year Scale

The world adds about 51 Gt of greenhouse gases to the atmosphere each year, which will yield dire global consequences without aggressive action in the form of carbon dioxide removal (CDR) and other technologies. A suggested guideline requires that proposed CDR technologies be capable of removing at least 1% of current annual emissions, about half a gigaton, from the atmosphere each year once fully implemented for them to be worthy of pursuit. Basalt carbonation coupled to direct air capture (DAC) can exceed this baseline, but it is likely that implementation at the gigaton-per-year scale will require increasing per-well CO₂ injection rates to a point where CO₂ forms a persistent, free-phase CO₂ plume in the basaltic subsurface. Here, we use a series of thermodynamic calculations and basalt dissolution simulations to show that the development of a persistent plume will reduce carbonation efficiency (i.e., the amount of CO₂ mineralized per kilogram of basalt dissolved) relative to existing field projects and experimental studies. We show that variations in carbonation efficiency are directly related to carbonate mineral solubility, which is a function of solution alkalinity and pH/CO₂ fugacity. The simulations demonstrate the sensitivity of carbonation efficiency to solution alkalinity and caution against directly extrapolating carbonation efficiencies inferred from laboratory studies and small-injection-rate field studies conducted under elevated alkalinity and/or pH conditions to gigaton-per-year scale basalt carbonation. Nevertheless, all simulations demonstrate significant carbonate mineralization and thus imply that significant mineral carbonation can be expected even at the gigaton-per-year scale if basalts are given time to react.

Evaluation of emission reduction targets contributed by BASIC countries from the perspective of global temperature control targets

In this paper, the BASIC (Brazil, South Africa, India, and China) countries, which play an increasingly significant role in combating climate change, are selected as the research objects. First, we investigate the driving factors of the evolution of carbon emissions in the BASIC group from 2000 to 2016. Second, we use the Monte Carlo simulation to analyze the potential evolution trend of carbon emissions in the benchmark scenario, optimization scenario, and enhanced scenario in the BASIC group from 2017 to 2030 to judge whether the countries can achieve their own autonomous contribution goals. Third, we evaluate whether the BASIC INDC can provide practical support for making the global temperature control goals described in the Paris Agreement. The results show that first, the contribution rate of the energy consumption structure and population size to the carbon emissions of the BASIC are low, and the contributions of R&D efficiency, R&D intensity, and investment intensity to the carbon emission change in the BASIC group are more prominent. Second, under the benchmark scenario, Brazil, South Africa, India, and China from the difference between the complete INDC targets respectively is 265.50 Mt, 207.86 Mt, 1034.70 Mt, and 4660.82 Mt. Under the optimization scenario, China could meet the INDC goals. The gap between Brazil, South Africa, and India is 60.06 Mt, 9.50 Mt, and 413.74 Mt, respectively. Under the enhanced scenario, China and South Africa could meet the INDC target, while Brazil and India are 15.69 Mt and 228.28 Mt away from the INDC target, respectively. Third, although the INDC goals of Brazil and India can achieve the carbon reduction allocated under the 2 °C targets, the INDC targets submitted by the BASIC are not enough to reach the carbon reduction allocated under the global 1.5 °C destination; Brazil, South Africa, India, and China's gap is 64.14 Mt, 246.15 Mt, 236.84 Mt, 3399.64 Mt, respectively. Fourth, Brazil, South Africa, and China should increase its R&D on energy-saving and emission reduction technologies, and India should develop reasonable population policies and green economic development policies.

Country-based rate of emissions reductions should increase by 80% beyond nationally determined contributions to meet the 2 °C target

The 2015 Paris Agreement aims to keep global warming by 2100 to below 2°C, with 1.5°C as a target. To that end, countries agreed to reduce their emissions by nationally determined contributions (NDCs). Using a fully statistically based probabilistic framework, we find that the probabilities of meeting their nationally determined contributions for the largest emitters are low, e.g. 2% for the USA and 16% for China. On current trends, the probability of staying below 2°C of warming is only 5%, but if all countries meet their nationally determined contributions and continue to reduce emissions at the same rate after 2030, it rises to 26%. If the USA alone does not meet its nationally determined contribution, it declines to 18%. To have an even chance of staying below 2°C, the average rate of decline in emissions would need to increase from the 1% per year needed to meet the nationally determined contributions, to 1.8% per year.

The energy-growth nexus revisited: the role of financial development, institutions, government expenditure and trade openness

Although the energy-growth nexus has been widely investigated in the last several decades, there are still vivid debates in the energy economics field. This study evaluates the link between energy consumption and economic growth with the thorough assessment of the roles of institutional quality, government expenditure, financial development and trade openness in 46 Emerging Market and Developing Economies (EMDEs) from 1990 to 2014. By employing appropriate panel econometric techniques, cross-sectional dependence and slope heterogeneity are controlled, which helps explore the unbiased long-run effects of the determinants of economic growth as well as scrutinize the dynamic relationship among variables. The findings demonstrate that energy usage, gross fixed capital formation, government expenditure, financial development and trade openness positively and significantly impact the economic growth in the studied EMDEs. Moreover, Dumitrescu and Hurlin causality tests affirm the occurrence of feedback hypothesis in the connection between energy consumption and other variables including economic growth. Thus, it implies that energy consumption and economic growth are interdependent, which forms a basis for policy-makers to design effective energy and environmental policies. Toward the sustainable development goal, the author recommends the governments of EMDEs to contemplate the importance of finance-governance-trade relationship to economic growth alongside the implementation of energy-efficient policies.

The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental Kuznets curve

The main objective of this study is to examine the impacts of globalization, financial development, government expenditures, and institutional quality on CO₂ emissions, incorporating energy consumption, and GDP per capita in the Environmental Kuznets Curve (EKC) model for 47 Emerging Market and Developing Economies (EMDEs) between 1990 and 2014. Owing to the presence of cross-sectional dependence and slope heterogeneity in the panel data, CADF and CIPS unit root tests are employed to validate the stationarity of the variables. Westerlund (Oxf Bull Econ Stat 69:709-748, 2007) and Banerjee and Carrion-i-Silvestre (J Time Ser Anal 38:610-636, 2017) cointegration tests denote the occurrence of cointegration among the variables. We employed CCEMG, AMG, and DCCE estimators to estimate heterogeneous parameters. The findings demonstrate that globalization, financial development, and energy consumption increase CO₂ emissions. Besides, the EKC hypothesis is affirmed in EMDEs. The accrual of governments' financial and governance activities also boosts carbon dioxide emissions. Moreover, the analysis of Dumitrescu and Hurlin causality provides evidences for the feedbacks among the variables and CO₂ emissions. From the aforementioned results, there exists the trade-off effect between economic growth and environmental quality in EMDE countries. Finally, the empirical findings of this study indicate profound implications for policy makers, which recommend governments to consider the role of finance and governance in order to ensure that energy consumption, financial development, and sustainable economic growth are in harmony with the environment in the globalization era.

Spatial Pattern of a Comprehensive fE Index for Provincial Carbon Emissions in China

China has committed to ambitious targets to reduce its carbon emissions in the next decades, in order to combat climate change and improve the environment. The realization of the targets depends on the fair and effective mitigation plans of all provinces. However, with varying ecological and environmental conditions and social-economic development, it is a critical issue to quantify the provinces’ efforts equally. This paper proposed a comprehensive fE index in coordinating ecology, equity and economy, by accounting for carbon emissions and sinks to characterize provincial carbon emission status in China, from 2000 to 2017, which shows a spatial pattern of “boundary high, central low”. The provinces with higher fE value (>1.5) in boundary areas can be seen as “relative equality” provinces with good ecology circulation, equity and economic efficiency. The provinces with lower fE value (<0.7) in central areas around Bohai Bay are regarded as “severe inequality” provinces, and are identified as the hot-spot provinces, which have emitted more CO2 than their equity share by occupying the carbon emission space of other provinces in recent decades. These results could provide a reference for a provincial guide for carbon reduction and sustainable development of the low-carbon economy.

Incorporating Forests, Agriculture, and Energy Consumption in the Framework of the Environmental Kuznets Curve: A Dynamic Panel Data Approach

Based on country-specific panel data from 1990–2014 for 86 different countries, we quantify the effects of forests and agricultural land in CO2 emissions, using the framework of the Environmental Kuznets Curve (EKC). The results from the dynamic panel data method reveal that forests are an important determinant in reducing CO2 emissions globally, but the effects vary by region. All else constant, we estimate a 0.11% decline in CO2 emissions per 1% increase in the forest area globally. However, the agricultural sector is found to be a true CO2 emitter. Our study provides additional empirical evidence for the roles of forests in regulating atmospheric CO2, further reinforcing the importance of forests in global climate change policies.

China Act on the Energy Efficiency of Civil Buildings (2008): A decade review

China has launched the energy efficiency project (EEP) for its civil building sector beginning in the mid-1980s; however, its implementation has not been effective. To better promote the EEP for the Chinese civil building sector, the Chinese government issued the China Act on the Energy Efficiency of Civil Buildings in 2008. This is the first paper to present a review of this act's implementation over the past decade. Based on China Database of Building Energy Consumption and Carbon Emissions and official documents, the achievements of this act are assessed by examining a variety of indicators. The success of the act can be attributed to the following factors: 1) a strong and sustained government commitment to top policies of building energy efficiency (BEE); 2) extensive efforts to apply the BEE standards to newly built civil buildings; 3) various incentive schemes involving energy efficiency retrofitting for existing civil buildings; 4) the increasing adoption of renewable energy to the civil building sector and of systems and platforms of energy efficiency supervision to commercial buildings; and 5) the rapid development of green buildings. Nevertheless, the revised act must address several challenges in the upcoming phase. These challenges mainly include the following: 1) the "double-control" strategy for the civil building sector; 2) the substantial development of the EEP in rural China; 3) the further development of green buildings for the low-carbon civil buildings; 4) the improvement of official statistical data systems on energy consumption and carbon emissions for civil buildings; and 5) building industrialization and informatization. It's expected that our efforts as constituting significant guidance for evaluating the EEP in the Chinese civil building sector, and the efforts will also be treated as an example for other developing countries to evaluate and revise their BEE acts.

Driving forces and mitigation potential of global CO2 emissions from 1980 through 2030: Evidence from countries with different income levels

To mitigate global carbon dioxide (CO₂) emissions in an effective manner, it is essential to identify the driving forces and estimate the reduction potential of changes to CO₂ emissions. Using an extended logarithmic mean Divisia index (LMDI) method, this study decomposes the changes in global emissions between 1980 and 2015 with consideration of different income levels; it also reports on scenario analysis of the global emissions reduction potential up to the year 2030 to explore feasible mitigation pathways. The results suggest that the key driving force responsible for promoting global emissions from 1980 through 2015 is income, while energy intensity is the most significant factor in inhibiting global emissions. Furthermore, the countries with the largest reductions in global emissions are mainly upper-middle-income (UMI) countries. The key driving forces of emissions changes in countries with different income levels offer mixed results. In addition, the forecast results indicate that the future emissions reduction potential across the globe is significant and that UMI countries offer the greatest emissions mitigation potential. Finally, this study provides several targeted policy suggestions for reducing emissions across the globe.

Meeting National Emissions Reduction Obligations: A Case Study of Australia

Akin to a public good, emissions reduction suffers from the ‘free rider’ syndrome. Although many countries claim that they are meeting their greenhouse gas (GHG) emissions reduction commitments, the average global temperature and GHG emissions continue to rise. This has led to growing speculation that some countries may be taking advantage of the system by effectively exploiting a range of loopholes in global agreements. Using a case study approach, we critically review the evidence from Australia, exploring how Australia has participated in global climate change negotiations and the way in which this emissions intensive country’s national emissions reduction obligations have been met. The findings suggest that: (1) successful negotiation to include Article 3.7 (‘Adjusting the 1990 Baseline’ or ‘the Australia Clause’) in the Kyoto Protocol significantly favored Australia’s ability to meet its First Kyoto Commitment (2008–2012); and (2) successful bargaining for the accounting rule that allowed carbon credits from the first commitment period to be carried over to the second commitment period of the Kyoto Protocol benefitted Australia by 128 MtCO2e. At the national level, a lack of bipartisan political support for an effective mechanism to drive emissions reduction has also been problematic. While the introduction of the Carbon Pricing Mechanism (CPM) in 2012 reduced emissions from electricity production from about 199.1 MtCO2e to 180.8 MtCO2e in 2014, a change of government led to the abolition of the CPM in 2014 and emissions from electricity production subsequently rose to 187 MtCO2e in 2015 and 189 MtCO2e in 2016 with adverse impacts in many sectors as well as Australia’s overall emissions. The current Australian government continues to undermine its commitment to mitigation and the integrity and credibility of its own emissions reductions policy, introducing a softer ‘calculated baseline’ for its own Safeguard Mechanism, which allows companies to upwardly adjust their calculated baselines on the basis of their highest expected emissions, permitting emissions in excess of their historical emissions. While disappointing in the context of the global emissions reduction project, Australia’s actions are sadly not unique and we also provide examples of loopholes exploited by countries participating in a range of other negotiations and emissions reduction projects. Such strategies undoubtedly serve the short-term political and economic interests of these countries; however, it is increasingly apparent that the cumulative impact of such tactics will ultimately impact the entire global community.

CO2 emissions, natural gas and renewables, economic growth: Assessing the evidence from China

This study aims to test the environmental Kuznets curve (EKC) for carbon dioxide (CO₂) emissions in China by developing a new framework based on the suggestion of Narayan and Narayan (2010). The dynamic effect of natural gas and renewable energy consumption on CO₂ emissions is also analyzed. Considering the structural break observed in the sample, a series of econometric techniques allowing for structural breaks is utilized for the period 1965-2016. The empirical results confirm the existence of the EKC for CO₂ emissions in China. Furthermore, in both the long-run and the short-run, the beneficial effects of natural gas and renewables on CO₂ emission reduction are observable. In addition, the mitigation effect of natural gas on CO₂ emissions will be weakened over time, while renewables will become progressively more important. Finally, policy suggestions are highlighted not only for mitigating CO₂ emissions, but also for promoting growth in the natural gas and renewable energy industries.

What drives the carbon mitigation in Chinese commercial building sector? Evidence from decomposing an extended Kaya identity

Energy efficiency in the building sector is expected to contribute >50% to the nationwide carbon mitigation efforts for achieving China's carbon emission peak in 2030, and carbon mitigation in Chinese commercial buildings (CMCCB) is an indicator of this effort. However, the CMCCB assessment has faced the challenge of ineffective and inadequate approaches; therefore, we have followed a different approach. Using the China Database of Building Energy Consumption and Carbon Emissions as our data source, our study is the first to employ the Logarithmic Mean Divisia Index (LMDI) to decompose five driving forces from the Kaya identity of Chinese commercial building carbon emissions (CCBCE) to assess the CMCCB values in 2001-2015. The results of our study indicated that: (1) Only two driving forces (i.e., the reciprocal of GDP per capita of Tertiary Industry in China and the CCBCE intensity) contributed negatively re_mi to CCBCE during 2001-2015, and the quantified negative contributions denoted the CMCCB values. Specifically, the CMCCB values in 2001-2005, 2006-2010, and 2011-2015 were 123.96, 252.83, and 249.07 MtCO₂, respectively. (2) The data quality control involving the CMCCB values proved the reliability of our CMCCB assessment model, and the universal applicability of this model was also confirmed. (3) The substantial achievements of the energy efficiency project in the Chinese commercial building sector were the root cause of the rapidly growing CMCCB. Overall, we believe that our model successfully bridges the research gap of the nationwide CMCCB assessment and that the proposed model is also suitable either at the provincial level or in different building climate zones in China. Meanwhile, a global-level assessment of the carbon mitigation in the commercial building sector is feasible through applying our model. Furthermore, we consider our contribution as constituting significant guidance for developing the building energy efficiency strategy in China in the upcoming phase.