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China has always tried to maintain multilateralism and advocated working together to deal with global climate change through multilateral mechanisms. Although China’s announcement to peak its carbon emissions by 2030 comes as no surprise, its commitment to carbon neutrality does. As the period between its carbon peaking and carbon neutrality is far shorter than that in the developed countries, China’s economic and energy structures need to be adjusted toward the low-carbon and carbon-free end with unprecedented efforts. To that end, China should define the responsibilities of local authorities and industrial entities to promote the orderly accomplishment of carbon peaking in all regions and industries. To supply the huge investments needed to achieve the goals of carbon peaking and carbon neutrality, China has an urgent need to accelerate the development of green finance and a national carbon emissions trading market, guide the rational allocation of resources, and channel resources to eco-friendly projects for green and low-carbon development. At the same time, China and the international community should strengthen dialogue and coordination, promote international cooperation on the way to carbon neutrality, formulate widely acceptable policy guidelines as soon as possible, and avoid unilateral measures that may cause conflicts. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Introduction: Carbon neutrality has become a key strategy to combat global climate change. However, current methods for predicting carbon emissions are limited and require the development of more effective strategies to meet this challenge. This is especially true in the field of sports and competitions, where the energy intensity of major events and activities means that time series data is crucial for predicting related carbon emissions, as it can detail the emission patterns over a period of time. Method: In this study, we introduce an artificial intelligence-based method aimed at improving the accuracy and reliability of carbon emission predictions. Specifically, our model integrates an Improved Mahjong Search Algorithm (ISSA) and GRU-Transformer technology, designed to efficiently process and analyze the complex time series data generated by sporting events. These technological components help to capture and parse carbon emission data more accurately. Results: Experimental results have demonstrated the efficiency of our model, which underwent a comprehensive evaluation involving multiple datasets and was benchmarked against competing models. Our model outperformed others across various performance metrics, including lower RMSE and MAE values and higher R2 scores. This underscores the significant potential of our model in enhancing the accuracy of carbon emission predictions. Discussion: By introducing this new AI-based method for predicting carbon emissions, this study not only provides more accurate data support for optimizing and implementing carbon neutrality measures in the sports fi eld but also improves the accuracy of time series data predictions. This enables a deeper understanding of carbon emission trends associated with sports activities. It contributes to the development of more effective mitigation strategies, making a significant contribution to global efforts to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]