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To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) will cause large flows of carbon sources and sinks. As the world's largest carbon emitter with a complicated LULC, China's carbon emissions have profound implications for its ecological environment and future development. In this paper, we account for the land-use changes and carbon emissions of 30 Chinese provinces and cities in China from 2000 to 2020. Furthermore, the spatial correlation of carbon emissions among the study areas is explored. Four typical regions with spatial association (Beijing, Hebei, Sichuan, and Anhui) are selected, and their land-use change trends in 2025 and 2030 are simulated to predict the total carbon emissions in the future. The results show that the distribution of land-use in China is mainly cultivated and woodland, but the growth of urban built-up (UBL) land area indirectly leads to the continuous increase of carbon emissions. Total carbon emissions have increased over the past two decades, albeit at a slower growth rate, with some provinces experiencing no further growth. In the typical regional carbon emission simulation, it is found that the carbon emissions of the four provinces would show a downward trend in the future. The main reason is the reduction in indirect carbon emissions from fossil energy in UBL, while the other part is the influx of carbon sinks due to grassland, woodland, etc. We recommended that future carbon reduction measures should focus and prioritize controlling fossil energy and mitigating carbon emissions from UBL. Simultaneously, the significant contribution of forests and other land types as carbon sinks should be acknowledged to better implement China's carbon neutral commitment. [ABSTRACT FROM AUTHOR]

Carbon sink is the process of absorbing CO2 from the atmosphere, through forests, wetlands, grasslands, and oceans. Through this process, greenhouse gases can be absorbed from the atmosphere. In order to analyze the contribution of carbon sinks to carbon neutrality, three parts of works were carried out on carbon sinks in Beijing-Tianjin-Hebei. Firstly, the regional carbon sinks were calculated based on actual data. Secondly, the macro-factors were selected related to carbon sinks, on which the econometric analysis was carried out. Finally, a carbon sink prediction model was constructed based on partial least squares regression. After that, three carbon sink development scenarios with different intensities were set up. Under these three scenarios, the carbon sink potential of the Beijing-Tianjin-Hebei region was forecasted from 2020 to 2030. The results show that under the strong carbon sink scenario, the carbon sink in Beijing-Tianjin-Hebei can neutralize 388.6901 million tons/a of carbon emissions by 2030, whose contribution rate to China's carbon emission reduction can reach 10.48%. Compared with the baseline scenario and weak carbon sink scenario, the strong carbon sink scenario can achieve greater carbon sink potential and contribute more to China's carbon neutrality. As a conclusion, the target of carbon neutrality of China can be easier to achieve under the strong carbon sink scenario. [ABSTRACT FROM AUTHOR]

The Chinese government has officially announced that China's carbon dioxide emissions will reach to peak before 2030 and achieve carbon neutrality before 2060. Based on the carbon neutrality development of 12 provinces and cities in eastern China from 2010 to 2019, this paper constructs an evaluation index system, and it uses the entropy weight method and coefficient of variation method to measure the carbon neutrality development level in the eastern China. The results show that from 2010 to 2019, the changes of carbon source level in 12 provinces and cities in the eastern China are lower than the changes in carbon sink level, and the changes of carbon source and sink level in most provinces and cities show the increasing trend. Spatially, the carbon neutral development level shows the differentiation characteristics of "low in the middle, high in the north and south." The main factors affecting the carbon neutrality level of eastern provinces and cities include policy, economic development and industrial structure, energy intensity and structure, urban development, and population size ecological environment. High-value areas are mainly distributed in Heilongjiang Province, Jilin Province and Fujian Province. Low-value areas are mainly distributed in Jiangsu Province and Shandong Province. Eastern China still needs to strengthen its emphasis on low-carbon policies. For Shandong Province, Jiangsu Province, and Hebei Province, policies should be introduced to reduce carbon sources, accelerate their industrial upgrading, and optimize their energy use structure. For Beijing City, Shanghai City, Heilongjiang Province, and Jilin Province, policies should be introduced to develop carbon sinks while maintaining their low carbon source levels. For Beijing City and Shanghai City, policies related to green and low-carbon technologies should be introduced to promote the development of carbon sink capacity through low-carbon technologies in limited urban areas. [ABSTRACT FROM AUTHOR]

With the statement of Chinese government on energy saving in 2020 at the United Nations General Assembly, carbon neutral was widely spread as a new concept. As a big country, China has the responsibility and obligation to make its own contribution to global climate change. This paper aims to explore and find effective ways for China to achieve carbon neutrality by 2060. We identify the main factors affecting carbon emissions by STIRPAT model; combined with the scenario analysis, we divide the year 2020 to 2060 into three stages: year 2020–2030 is carbon peak stage, year 2030–2050 is rapid emission reduction stage, and year 2050–2060 is complete carbon neutralization stage. At each stage, three development models, high, medium, and low level, were established. There are a total of 27 different scenarios in three stages. A system dynamics model was established to simulate the effects of carbon emission factors and changes in carbon sinks in different scenarios. Finally, 8 paths were found which in line with Chinese current goal of achieving carbon neutrality with treating reach carbon peak in 2030 as an additional filter condition. Comparing per capita GDP levels in different scenarios, we eventually find that keeping economic development at a low level in the first stage, a high level in the second stage, and a medium level in the finally stage, the point where net carbon emissions are less than zero for the first time will appear between year 2056 and 2057. By then, the per capita GDP will reach 144,500 yuan (based on year 2000), nearly four times 2000's. In all, these findings are helpful for policymakers to implement reasonable policies to achieve carbon emission peaking and carbon neutral in China. [ABSTRACT FROM AUTHOR]

In order to achieve the carbon peaking and carbon neutrality goals, energy-intensive industries in China, as the main sectors of energy consumption and carbon emissions, had huge pressure to reduce emissions. In addition, the reduction of vegetation area led to a decline in carbon sink capacity, which further exacerbated the imbalance of mutual penetration between carbon source and carbon sink. Therefore, this article considered the role of carbon source and carbon sink and defined and calculated the "carbon emission penetration" (CEP) of the six energy-intensive industries from 2001 to 2020. The KAYA formula and the LMDI method were used to decompose the driving factors of CEP in the three aspects of scale, intensity, and structure. The combined model of STIRPAT and the environmental Kuznets curve (EKC) was used to simulate and analyze the equilibrium points of energy-intensive industries in China from the perspective of factor driving. The analysis results indicated that there were differences in the fluctuation trend of CEP in the six energy-intensive industries, which can be divided into three types: "two-stage growth," "steady growth," and "single peak." Secondly, the driving factors from the three aspects of scale, intensity, and structure—emission intensity (CE), energy consumption intensity (EI), industrial structure (IS), economic scale (GP), and carbon sequestration scale (PCA)—had differences in industry and time dimensions. And the realization time of the CEP equilibrium points of six industries showed a three-level gradient feature significantly. This can provide some reference for the low-carbon transformation of six energy-intensive industries and optimization of China's environmental management under the carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Global greenhouse gas emission, major factor driving climate change, has been increasing since nineteenth century. STIRPAT and CEVSA models were performed to estimate the carbon emission peaks and terrestrial ecosystem carbon sinks at the provincial level in China, respectively. Utilizing the growth characteristics and the peak time criteria for the period 1997–2019, the patterns of energy consumption and CO2 emissions from 30 Chinese provinces are categorized into four groups: (i) one-stage increase (5 provinces), (ii) two-stage increase (10 provinces), (iii) maximum around 2013 (13 provinces), and (iv) maximum around 2017 (2 provinces). According to the STIRPAT model, the anticipated time of peak CO2 emissions for Beijing from the third group is ~ 2025 in both business-as-usual and high-speed scenarios. For Xinjiang Uygur autonomous region from the first group and Zhejiang province from the second group, the expected peak time is 2025 to 2030. Shaanxi province from the fourth group is likely to reach carbon emission peak before 2030. The inventory-based estimate of China's terrestrial carbon sink is ~ 266.2 Tg C/a during the period 1982–2015, offsetting 18.3% of contemporary CO2 emissions. The province-level CO2 emissions, peak emissions and terrestrial carbon sinks estimates presented here are significant for those concerned with carbon neutrality. [ABSTRACT FROM AUTHOR]

Urbanization is a critical factor affecting regional carbon emissions. Clarifying the linkage between urbanization and carbon emissions can provide a decision-making reference to realize China's goal of carbon neutrality. This article examines the spatiotemporal patterns of urbanization and carbon emissions in the Yangtze River Delta urban agglomeration from 2008 to 2018. A complete set of variables is considered to construct relevant land and ecological urbanization variables, and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and spatial Durbin model (SDM) are adopted to explore the impact of various driving factors on carbon emissions. The results indicate that (1) during the study period, the carbon emissions in the Yangtze River Delta urban agglomeration exhibited a fluctuating increase and that the incremental carbon emissions followed a downward trend. (2) Carbon emissions exhibited a positive spatial correlation. Cold- and hotspot areas indicated a three-gradient pattern from west to east, and a concentric circle radiation pattern occurred with Shanghai as the core. Carbon emissions were spatially imbalanced, but the centre of gravity slightly fluctuated, with a total migration distance of 38.48 km, indicating a migration trend towards the southeast. (3) Regarding the two considered dimensions of urbanization, all driving factors except urbanization played a role in carbon emission enhancement. Consequently, for every 1% increase in economic factors, the carbon emissions correspondingly increased by 0.43–0.57%. Hence, economic factors are the most important factors promoting increased carbon emissions. In the ecological urbanization dimension, urbanization caused a non-significant decrease in carbon emissions, while there was no spillover effect on carbon emissions in neighbouring areas. Accordingly, carbon emission reduction efforts should promote the transformation of urbanization from a land-driven process to an ecologically driven process and realize the synergies among carbon emission reductions, urban development, and land use. [ABSTRACT FROM AUTHOR]

China announced its national goal to reach the peak of carbon emission by 2030 and achieve carbon neutrality by 2060, during the General Assembly of the United Nations in September 2020. In this context, the potential of the carbon sink in China's terrestrial ecosystems to mitigate anthropogenic carbon emissions has attracted unprecedented attention from scientific communities, policy makers and the public. Here, we reviewed the assessments on China's terrestrial ecosystem carbon sink, with focus on the principles, frameworks and methods of terrestrial ecosystem carbon sink estimates, as well as the recent progress and existing problems. Looking forward, we identified critical issues for improving the accuracy and precision of China's terrestrial ecosystem carbon sink, in order to serve the more realistic policy making in pathways to achieve carbon neutrality for China. [ABSTRACT FROM AUTHOR]