Growth Rate Of Carbon Emissions Research Articles

County-Level Spatiotemporal Dynamics and Driving Mechanisms of Carbon Emissions in the Pearl River Delta Urban Agglomeration, China

Encouraging cities to take the lead in achieving carbon peak and carbon neutrality holds significant global implications for addressing climate change. However, existing studies primarily focus on the urban scale, lacking more comprehensive county-level analyses, which hampers the effective implementation of differentiated carbon mitigation policies. Therefore, this study focused on the Pearl River Delta urban agglomeration in China, adopting nighttime light data and socio-economic spatial data to estimate carbon emissions at the county level. Furthermore, trend analysis, spatial autocorrelation analysis, and Geodetector were adopted to elucidate the spatiotemporal patterns and influencing factors of county-level carbon emissions. Carbon emissions were predominantly concentrated in the counties on the eastern bank of the Pearl River Estuary. Since 2010, there has been a deceleration in the growth rate of carbon emissions in the region around the Pearl River Estuary, with some counties exhibiting declining trends. Throughout the study period, construction land expansion consistently emerged as a predominant factor driving carbon emission growth. Additionally, foreign direct investment, urbanization, and fixed asset investment each significantly contributed to the increased carbon emissions during different development periods.

Is digitalization essential for abating carbon emission growth in South Asia?

Output generation processes across South Asia are deemed unclean (highly emission-intensive) due to excessive reliance on fossil fuels. Thus, decarbonizing the growth processes within this region has critical emphasis among policymakers. However, since the South Asian countries are yet to be ready to undergo the renewable energy transition, it is unlikely that “their annual carbon discharge levels will subside” anytime soon. Under such circumstances, these countries need to limit the rate at which their carbon emission levels rise each year. Therefore, the impacts of digitalization on annual carbon emission growth rates in selected South Asian countries are assessed in this study. Overall, considering internet penetration rate as a proxy of digital technology adoption, the results confirm that policies aimed at digitalizing the concerned South Asian economies not only exert emission growth rate-reducing impacts via a direct channel, but also indirectly reduce emission growth rates by making natural resources sectors more productive, expediting the energy sector greening processes, greening the financial sectors, making corruption controlling measures within institutions more effective, and limiting urbanization-induced environmental quality-worsening effects. Therefore, it is relevant for the South Asian government to emphasize on digitalization while simultaneously ensuring that green digital technologies are adopted within the major macroeconomic sectors across this region.

The impact of low-carbon city pilot on carbon emissions of high-polluting enterprises − Based on financing constraint perspective

As the major contributor to climate change, enterprises in high-polluting industries have a large deal of potential to reduce their carbon emissions, and the efficacy of that reduction is correlated with the nation's overall environmental pollution and climate change. As a comprehensive environmental regulation policy, whether the low-carbon city pilot (LCCP) can promote the carbon emission reduction of high-polluting enterprises remains to be verified. Based on the data of all high-polluting listed companies in China during the period of 2010–2020, this study evaluates the implementation effect of the LCCP through the multi-period difference-in-differences model, and conducts a series of robustness tests. In addition, the implementation path, heterogeneity and industry spillover effects of the policy are also studied. The study shows that the LCCP policy significantly reduces the growth rate of carbon emissions of enterprises in high-polluting industries by 1.06 percentage points on average. Financing constraints play a negative moderating role between the LCCP and the growth rate of carbon emissions. The mechanism test demonstrates that the LCCP reduces the carbon emission growth rate of enterprises in high-polluting industries through enterprise technological innovation and increasing environmental protection investment level. Further analysis can also find that the LCCP has a more obvious emission reduction effect on state-owned enterprises and enterprises in areas with lax environmental law enforcement. And there is an economic spillover effect but no industrial spillover effect. In view of this, local governments should play a guiding role in the policy, continue to expand the scale of the LCCP and focus on non-state-owned enterprises to promote the green transformation of high-polluting enterprises. This study offers significant theoretical and practical reference value for the further implementation of environmental regulation in the field of environmental governance and the reduction of enterprise carbon emissions.

Research on the impact of ESG performance on carbon emissions from the perspective of green credit

Utilizing panel data from 30 Chinese provinces, this research examines the non-linear relationship between regional environmental, social, and governance (ESG) performance and carbon emissions (CE) from the viewpoint of green credit. The study reveals a single threshold effect between ESG performance and CE, with green credit acting as the threshold variable. When the amount of green credit in a region exceeds the threshold, the growth rate of CE in that region begins to decline with higher ESG scores. Furthermore, green credit acts as a catalyst, playing a negative moderating role between ESG performance and CE, validated by both threshold regression and fixed effects models on panel data. Green credit indirectly influences carbon emissions by supporting green innovation, thus facilitating the transition to a greener economic development framework. Lastly, regional disparities are found in the moderating influence of green credit between ESG performance and CE. In regions with high ESG performance, the moderating impact of green credit is smaller, while in regions with low ESG performance, the effect is more significant. The research findings offer theoretical backing for policymakers regarding the efficacy of ESG in achieving carbon neutrality objectives, and offer valuable strategic recommendations for the diversified formulation of green credit strategies on both national and provincial scales. Regional heterogeneity test results provide valuable support for formulating policies that encourage green credit in provinces with low ESG performance.

Impact factors and peaking simulation of carbon emissions in the building sector in Shandong Province

The building sector has the fastest growth rate of carbon emissions and the greatest potential for carbon reduction. The building sector in Shandong Province ranks first in China in terms of total carbon emissions and growth rate. The study of carbon emissions in the building sector in Shandong Province is an essential reference for Chinese building sector to achieve the “carbon peaking and carbon neutrality” target. This study uses historical data on carbon emissions in the building sector in Shandong Province, based on which the influencing factors and carbon reduction potential are analyzed. A dynamic and comprehensive carbon emission prediction model for buildings was developed to predict the trajectory of carbon emissions in the building sector in Shandong Province from 2020 to 2050 with the corresponding probability distribution. Results show that the main factors driving the increase in carbon emissions in the building sector in Shandong Province are the level of affluence of the residents and the level of building services. The building area demand index and building energy efficiency are the most important factors inhibiting the increase in carbon emissions in the building sector in Shandong Province during the same period. Under the baseline scenario, carbon emissions in the building sector in Shandong Province will peak at 243.573 (±46.022) million tonnes CO2 in 2035 (±3) years. The floor area demand index and level of affluence of the residents are the most critical factors affecting the uncertainty of future of carbon emissions in the building sector in Shandong Province.

Green technology advancement, energy input share and carbon emission trend studies

In order to study the theoretical mechanism of the impact of green technology progress on carbon emissions, this article constructs a theoretical mechanism of the impact of green technology progress on carbon emission growth. Explore the conditions for achieving carbon peak and carbon reduction. Based on the Cobb Douglas production function, construct a three sector model that includes capital, labor, and energy. Empirical methods were used to analyze the quantitative impact of green technology progress on carbon emission growth and the moderating effect of energy input share. This study mainly used provincial panel data from 1995 to 2020. Calculate carbon dioxide emissions based on energy consumption and carbon dioxide emission coefficients of various energy sources in different regions. Using the perpetual inventory method to calculate capital growth rate, green computing progress rate, etc., to provide data support for the green technology carbon reduction model. Empirical analysis of the impact of green technology progress on carbon emissions using the FGLS panel model. Theoretical and empirical analyses show that green technological progress promotes an increase in the carbon emission growth rate through the scale effect, with an impact coefficient of 0.607; it promotes a decrease in the carbon emission growth rate through the technological effect, with an impact coefficient of − 0.667; the combined effect promotes a decrease in growth rate of carbon emissions, with an impact coefficient of − 0.06. The share of energy inputs has a positive regulating effect on the scale effect.

A new multiregional carbon emissions forecasting model based on a multivariable information fusion mechanism and hybrid spatiotemporal graph convolution network

Developing scientific and effective carbon emissions reduction policies relies heavily on precise carbon emission trend prediction. The existing complex spatiotemporal correlation and diverse range of influencing factors associated with multi-regional carbon emissions pose significant challenges to accurately modeling these trends. Under this constraint, this study is inspired by graph learning to establish a hybrid dynamic and static graph-based regional carbon emission network framework, which introduces a novel research standpoint for investigating short-term carbon emissions prediction (CEP). Specifically, a parallel framework of attribute-augmented dynamic multi-modal graph convolutional neural networks (ADMGCN) and temporal convolutional networks with adaptive fusion multi-scale receptive fields (AFMRFTCN) is proposed. The proposed model is evaluated against nineteen state-of-the-art models using daily carbon emission data from 30 regions in China, demonstrating its effectiveness in accurately predicting the trends of multi-regional carbon emissions. Conclusions are drawn as follows: First, especially in regions with marked periodicity, compared with the best baseline model, the mean absolute percentage error (MAPE) of our model is reduced by 20.19%. Second, incorporating graph convolutional neural networks (GCNs) with dynamic and static graphs is advantageous in extracting the spatial features of China's carbon emission network, which are influenced by geographical, economic, and industrial factors. Third, the parallel ADMGCN-AFMRFTCNs framework effectively captures the influence of external information on carbon emissions while mitigating the issue of low prediction accuracy resulting from univariate information. Fourth, the analysis reveals significant differences in the short-term (30-day) growth rate of carbon emissions among different regions. For example, Henan exhibits the highest growth rate (37.38%), while Guizhou has the lowest growth rate (−7.46%). It is valuable for policymakers and stakeholders seeking to identify regions with distinct emission patterns and prioritize mitigation efforts accordingly.

Can undergoing renewable energy transition assist the BRICS countries in achieving environmental sustainability?

The BRICS countries ratified the 2030 Sustainable Development Goals agenda whereby ensuring environmental sustainability is of paramount importance for these emerging market economies. Although the BRICS nations have recorded noteworthy economic growth trajectories over the last couple of decades, these nations have not fared well in terms of improving their environmental indicators, especially due to gradually becoming more fossil fuel dependent over time. Hence, this study aims to explore whether undergoing the renewable energy transition can directly and indirectly establish environmental sustainability in the BRICS countries by containing their annual growth rates of carbon dioxide emissions. Additionally, the emission growth rate-influencing effects of technological innovation, foreign direct investment receipts, urbanization, and institutional quality are also evaluated. Based on data spanning from 1996 to 2021 and considering the result obtained using advanced panel data estimators, the findings endorse that the yearly carbon emission growth rates are (a) unaffected by undergoing the renewable energy transition on its own; (b) positively impacted by technological innovation, net receipts of foreign direct investment, and urbanization; and (c) negatively impacted by improving institutional quality through effective controlling of the spread of corruption. More importantly, the results verify the joint carbon emission growth rate-mitigating impact of renewable energy transition and institutional quality improvement. Hence, for abating the emission growth rate figures, several policies are prescribed.

Does higher energy efficiency growth homogeneously affect carbon emission growth rate across developing Sub-Saharan African nations? The importance of utilizing clean energy.

Establishing a sustainable environment and acquiring acarbon-neutral status require Sub-Saharan African nations to reduce their year-on-year growth rates of carbon emission levels. Thus, this study considers a sample of 38 countries from this region and selects the time period from 2000 to 2020 for analyzing the annual carbon emission growth rate influencing impacts of energy efficiency, clean energy, institutional quality, international trade, and net receipts of foreign direct investment. Overall, for the full sample of Sub-Saharan African nations, the results verify that the enhancing the growth rate of energy efficiency improvement reducesboth total and per capita annual carbon emission growth rates. Besides, the results endorse thatenhancing renewable energy shares of the final energy consumption profiles and promoting good governance-led betterment of institutional quality alsoplunge emission growth rates in the long run. More importantly, energy efficiency improvement, renewable energy consumption, and better quality institutions are observed to jointly exert carbon emission growth rate-impeding effects, as well. By contrast, more openness to international trade is not seen to influence the carbonemission growth ratesof the Sub-Saharan African nations of concern. Lastly, a greater share of net foreign direct investment receiptsin the national output level is evidenced to boost annual carbon emission growth rates across this region; consequently, the pollution haven hypothesis is verified. Furthermore, these above-mentioned findings are found to beheterogeneous across groups of low-income and middle-income Sub-Saharan African nations. Accordingly, in line with the findings, a couple ofpolicies are recommended to the governments of the Sub-Saharan African countries in order to guide them in designing effective environmental sustainability policies that are relevant for tackling climate change-related atrocitiesin the future.

Has the Development of The Digital Economy Reduced the Growth Rate of Carbon Emissions?

Against the backdrop of the "30 · 60" dual carbon target, low-carbon development and the progress of the digital economy are the focus of attention at home and abroad. The digital economy has become an important driving force for high-quality economic development in China. This article studies panel data at the provincial level in China from 2011 to 2018, empirically testing the negative correlation between the development of the digital economy and the growth rate of carbon emissions, and verifying the mechanism effect of green technology innovation, Finally, the situation in the eastern, central, and western regions was discussed through sample analysis and robustness testing was conducted. Based on the above research conclusions, the following insights can be drawn: firstly, improve the speed and quality of digital economy development; Secondly, focus on the development of green innovative technologies.

Spatio-Temporal Evolution and Action Path of Environmental Governance on Carbon Emissions: A Case Study of Urban Agglomerations in the Yellow River Basin

Since the ecological protection and high-quality development of the Yellow River basin in China have become a major national strategy, reducing carbon emissions has become pivotal. Therefore, based on the relevant data of 53 cities from 2008 to 2021 in seven urban agglomerations in the Yellow River basin, this paper explores the overall situation and spatio-temporal evolution of environmental governance and carbon emissions in the urban agglomerations in the Yellow River basin using the entropy method, ArcGIS, slacks-based measurement models (SBM models), etc. Additionally, this paper quantitatively analyzes the pathways by which environmental governance affects carbon emissions in the urban agglomerations in the Yellow River basin. The results show that carbon emissions increased year on year from 2008 to 2021, the growth rate slowed down gradually and exhibited a downward trend, and the largest amount of carbon was emitted in 2019, at 3495 million tons. Before 2017, the growth rate of carbon emissions showed a trend of increasing year by year, with the largest increase rate being 11.17% in 2010. After that, the growth rate of carbon emissions continued to decrease and entered a stage of fluctuation. The growth rate of carbon emissions in 2020 was the lowest, reaching −5.66%. The environmental governance effect of urban agglomerations in the Yellow River basin exhibits a large gap; the regional difference is obvious, and the overall trend is rising. Environmental governance has a significant negative effect on carbon emissions in urban agglomerations in the Yellow River basin. The cross-terms of environmental governance, the energy consumption structure, industrial structure upgrading, green technological innovation, and foreign direct investment (FDI) have significant negative impacts on carbon emissions, while the indirect impacts on urban agglomerations have shown regional heterogeneity. The goal of reducing carbon emissions in urban agglomerations in the Yellow River basin is being realized gradually. Based on research conclusions, policy suggestions are put forward, hoping to provide ideas for environmental protection and high-quality development of urban agglomerations in the Yellow River basin.

Decoupling CO2 Emissions from Economic Growth in China’s Cities from 2000 to 2020: A Case Study of the Pearl River Delta Agglomeration

As one of the most densely populated, economically developed, and outwardly open urban agglomerations in China, the Pearl River Delta (PRD) urban agglomeration is a key player in achieving China’s carbon peak and carbon neutrality targets. This study analyzes low-emission development by examining the evolutionary patterns of carbon dioxide (CO2) emissions and the decoupling relationship between economic growth and CO2 emissions, using the latest available data from 2000 to 2020. Here are the main findings: (1) We found a significant fluctuation in the decoupling statuses between economic advancements and CO2 emissions within the PRD domain. Predominantly, a weak decoupling scenario was observed, where economic proliferations were paralleled by nearly equivalent increments in CO2 emissions. (2) The growth rate of carbon emissions increased significantly relative to economic expansion during 2015–2020, especially pronounced in cities such as Guangdong, Zhuhai, Foshan, and Dongguan. This delineates the persistent challenges in steering towards a pathway of energy conservation and emission abatement in the region. (3) Furthermore, a differential role of elasticity factors was noted across cities: Guangzhou and Shenzhen witnessed a significant influence of energy-saving elasticity in fostering a decoupling between economic surge and CO2 emissions, whereas in other cities, the emphasis shifted towards emission-reduction elasticity as a more vital determinant. The results of this study are of great significance for guiding policy makers and stakeholders in urban clusters across China and in similar regions globally to achieve low carbon development goals.

Inferring the role of fiscal decentralization and carbon taxes through the ARDL approach

Abstract This paper first introduces the algorithmic steps of the ARDL model, explores the long-run relationship of variables using the cointegration test and estimates the long-run relationship, and then builds an error correction model to explore the short-run relationship in the model to estimate the model coefficients. Finally, we analyze the changes in carbon emissions and the relationship between carbon emissions and economic growth in China in time and space, respectively, and use the ARDL model to empirically test the correlation between fiscal decentralization and carbon tax Between 1978 and 2004, the growth rate of the economy remained above 10%, and the growth rate of carbon emissions also increased rapidly at this time, and carbon emissions were positively correlated with economic growth, and the growth rate of economic growth was positively correlated with the growth rate of carbon emissions. The growth rate of carbon emissions is positively correlated with economic growth, and the trend of the growth rate of economic growth and carbon emissions is roughly the same. The coefficient of fiscal decentralization degree on carbon tax expenditure is inhibited at a 1% significant level. The coefficient of the industrial structure plays a catalytic role in carbon tax expenditure at a 1% significant level, and for every 1% unit decrease in the proportion of secondary industry to GDP, carbon tax expenditure decreases by 2.473%. The implementation of a carbon tax can achieve the goal of energy saving and emission reduction, but we should also pay attention to the possible counter-effects of a carbon tax on economic development and reasonably levy carbon tax to make the economy and environment reach a balanced state.

Factors analysis for the decoupling of grain production and carbon emissions from crop planting in China: A discussion on the regulating effects of planting scale and technological progress

Judging the carbon emissions of various agricultural inputs in crop planting and clarifying the decoupling level between grain production and carbon emissions from crop planting can provide data support and policy references for agricultural carbon emission reduction. Considering six carbon emission sources (plowing, irrigation, fertilizer, pesticide, agricultural film (agrifilm), and diesel fuel (diefuel)). This research accounted the carbon emissions from crop planting in 31 provinces in China from 2000 to 2021. Using the Tapio model to explore the relationship between grain production and carbon emissions from different types of agricultural inputs. The regulating effects of planting scale, technological progress, and their covariates on carbon emission reduction were explored using two-way fixed-effect regression. The results showed that the growth rate of carbon emissions from crop planting in China had a fluctuating declining trend from 2000 to 2021, and it was weakly decoupled from grain production in most years, and that an overall strong decoupling was achieved in 2021. A 1% increase in planting scale leads to 1.0%, 0.68%, and 0.31% increases in carbon emissions from plowing, irrigation, and diefuel, respectively. The synergistic effect of the planting scale and technological progress can significantly reduce the carbon emissions of crop planting, and thus promote the decoupling of grain production and carbon emissions of crop planting. This study provides valuable references for policy formulation in economies to promote synergy between grain production and carbon reduction targets to a greater extent.

Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China.

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

What are the impacts of the carbon peaking and carbon neutrality target constraints on China's economy?

The carbon peaking target (CPT) and carbon neutrality target (CNT) will force the low-carbon transformation of China's economy. However, few studies have evaluated the economic impacts of the CPT and CNT constraints in the context of China's current carbon target policies. Based on the analytical general equilibrium model, this study assesses the impacts of the CPT and CNT constraints on China's economy. The results are shown as follows. First, the CPT and CNT constraints will tighten the high-carbon goods production sector but not hinder the sustained growth of the low-carbon goods production sector, thereby forcing China's industrial structure to transform into a low-carbon direction. In the scenario of achieving the CPT, the output growth rate of the high-carbon goods production sector will drop by 0.03%, while that of the low-carbon goods production sector will rise by 0.14%, relative to the baseline. Second, under the CPT and CNT constraints, some labor and energy inputs in the high-carbon goods production sector will flow into the low-carbon goods production sector, forming the crowding-out effect. Third, carbon target constraints will force the high-carbon goods production sector to transform from energy and labor-intensive to capital and technology-intensive. Fourth, the CPT and CNT constraints will negatively affect households' consumption. Fifth, under the carbon target constraints, the growth rate of carbon emissions price shows a rising trend, while that of labor and energy prices shows a declining trend. These findings suggest that the government should make full use of the forced mechanism of the CPT and CNT constraints to promote the transformation and upgrading of industrial and energy structures. Meanwhile, the government should also be highly vigilant against the risk of an excessive slowdown in the high-carbon goods production sector under carbon target constraints.

Carbon peak forecast and low carbon policy choice of transportation industry in China: scenario prediction based on STIRPAT model.

As the second largest CO2 emission department, transportation industry's carbon peak and carbon reduction are very important for China to smoothly achieve carbon peak by 2030 and carbon neutrality by 2060. This paper analyzes the influencing factors from the perspectives of population, economy, technology and transportation equipment structure, subdivides 20 scenarios to predict the carbon emissions of the transportation industry of the whole China and various regions based on scenario analysis method, explores the carbon peak path, and puts forward corresponding policy recommendations. The study found that (1) from the overall trend of carbon emissions, the total carbon emissions of China's transportation industry showed an overall upward trend from 2010 to 2019 while the growth rate of carbon emissions showed a downward trend. (2) From the perspective of influencing factors, population size, urbanization rate, economic scale, traffic development, traffic carbon intensity, and highway mileage have positive effect on the growth rate of China's transportation CO2 emissions. The increase in the proportion of energy structure and railway cargo turnover has the negative effect on carbon emissions in the transportation industry. (3) From the prediction results at the national level, technological breakthroughs have a limited effect on carbon emission reduction in China's transportation industry, while structural equipment optimization has the most significant effect on its emission reduction. When technological breakthroughs and equipment structure optimization are carried out simultaneously, the carbon emission reduction effect is the best. The carbon peak of China's transportation industry would achieve as early as 2030, with a peak range of 70,355.54-84,136.17 million tons. (4) From the perspective of prediction results at the regional level, the provinces with rapid population growth and per capita GDP growth, the provinces with rapid population growth and per capita GDP growth, and the provinces with low population growth and per capita GDP growth should control their average annual growth rate of carbon emissions of the transportation industry to 1.13%, 0.72% and 0.58% respectively in 2019-2030, in order to ensure the achievements of the carbon peak target.

Changes in Land Use Carbon Emissions and Coordinated Zoning in China

Carbon emissions from land use changes have become one of the main sources of regional carbon emissions. In order to explore its changes, based on the MCD12Q-LUCC data of MODIS from 2001 to 2019 using the carbon emission coefficient method, clustering, and outlier analysis method, the spatial characteristics of land use carbon emissions in various provinces in China in the past 19 years were discussed from the perspectives of carbon emission economy contributive coefficient, carbon ecological support coefficient, and their coupling and coordination relationship. The results showed that:① from 2000 to 2019, the national land use carbon emissions increased significantly; however, after 2011, the growth rate of carbon emissions became flat, whereas the growth of carbon sinks was relatively slow, and the gap between the two was still large. ② Clustering and outlier analysis showed that during the study period, the high-value agglomeration centers of land use carbon emissions in various provinces and cities across the country shifted from Guangdong, Jiangsu, and other provinces to Hebei, Shanxi, Inner Mongolia, and other provinces, and the agglomeration status became increasingly obvious. ③ The economy contributive coefficient of carbon emissions in all provinces and cities across the country had the spatial characteristics of being high in the south and low in the north, and the ecological support coefficient gradually developed from high in the west to low in the east, followed by that in the north, and the coupling coordination between the two showed a downward trend. ④ Based on the economy contributive of carbon emissions and carbon ecological support, this study divided the provinces into four categories:low-carbon maintenance area, economic development area, carbon sink development area, and comprehensive optimization area. We also put forward our own development suggestions, striving to achieve carbon neutrality and low-carbon sustainable development.

Towards a Decoupling between Economic Expansion and Carbon Dioxide Emissions of the Transport Sector in the Yellow River Basin

Realizing the decoupling development between the economic expansion and carbon dioxide emissions of the transport sector is of great importance if the Yellow River basin is to achieve green and low-carbon development. In this paper, we adopt the Tapio decoupling index to examine the decoupling relationship within the transport sector in the Yellow River basin, and then introduce the standard deviational ellipse to dynamically analyze the spatial heterogeneity of carbon emissions and economic growth at the provincial level. Furthermore, based on the decoupling method, we expand the traditional logarithmic mean Divisia index decomposition (LMDI) model to decompose the decoupling index into eight sub-indices, and we identify the impact of each factor on the decoupling relationship. The results indicate that the carbon emissions of the transport sector in the Yellow River basin show the non-equilibrium characteristics of “upstream region < midstream region < downstream region”. The decoupling state of the transport sector shows obvious spatial differences. The less-developed regions are more likely to present non-ideal decoupling states. The growth rate of carbon emissions in Sichuan, Qinghai, and Shandong provinces is relatively fast, and the azimuth of the transport sector’s carbon emissions shows a clockwise trend. Moreover, the inhibitory effects of urbanization on decoupling in the Yellow River basin are much greater than the non-urbanization factors. In addition to the effect of urbanization, the transport structure has a major negative effect on decoupling development in the upstream and midstream regions, while energy intensity and energy structure are key to realizing a decoupled status in the downstream region. Finally, we propose some differentiated policy recommendations.

Research on the impact of COVID-19 on the spatiotemporal distribution of carbon dioxide emissions in China

Since the outbreak of COVID-19 at the end of 2019, the Chinese government has imposed strict control measures on affected cities, which may have impacted the spatial and temporal pattern of carbon dioxide emissions. This paper follows the quantitative analysis method, experimental method, mathematical method, etc., and quantitatively studies the impact of the epidemic on China's carbon emissions. The combination model of ARIMA and BP neural network is used to predict the actual impact of epidemic situation on China's carbon emissions in 2020, and the spatial autocorrelation analysis method is used to analyze the spatial characteristics of China's provincial carbon emissions, which indicate that China's carbon emissions have consistently maintained a growth trend, from 2.05 billion tons in 2005 to 3.89 billion tons in 2019. Furthermore, the growth rate of carbon emissions and the changing trend of the emission intensity are the same, dropping from 12% in 2005 to 3% in 2019. The emission intensity also dropped from 1.1 in 2005 to 0.6 in 2019, indicating that the trend of increasing carbon emissions in northern provinces and Xinjiang changed significantly from 2005 to 2019. The overall carbon emissions of the 30 provinces in 2020 are predicted to be 4.068 billion tons, while the actual energy carbon emissions will be 3.921 billion tons, suggesting that the pandemic significantly reduced carbon emissions. Among affected provinces, carbon emissions from Hubei, Jiangsu, Shandong, Shanghai, and other places changed significantly, from 0.99, 0.25, 0.43, and 76 million tons in 2019 to 0.88, 0.24, 0.42, and 72 million tons in 2020, respectively. The results show a positive spatial correlation between China's provincial carbon emissions; the high-high and bottom-high agglomeration are mainly among the provinces, mainly distributed in North China and East China. Although the pandemic seriously impacts China's carbon emissions, each province's spatial relationship has not changed significantly.