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Full mobilization and effective use of climate aid is of great importance for the low carbon transition of Belt and Road Initiative (BRI) countries. This study utilizes the two-step system generalized method of moments model to evaluate the effects of climate aid on carbon emissions reduction and the impact mechanism through energy structure optimization. The panel data of 93 Belt and Road countries from 2000 to 2018 were used for empirical analysis. Results show that climate aid has a significant reduction effect on the carbon emissions intensity of BRI countries, and the dominant component of climate aid, i.e., mitigation aid, corresponds to better carbon emissions reduction benefits than adaptation aid. The impact mechanism demonstrates that the climate aid has dual carbon emissions reduction effects in BRI countries which have an intermediate energy structure. It indicates that climate aid not only directly reduces carbon emissions by increasing carbon reduction resources, but also indirectly reduces carbon emissions by promoting renewable energy and optimizing the energy structure. The results evidence the theory of environmental Kuznets curve hypothesis and channels of climate aid effects. Practical implications from the current study include that more climate finance support should be provided to BRI countries by developed countries, the effectiveness of climate aid should be improved by investing in projects with significant carbon reduction like renewable energy, data monitoring and performance evaluation of climate aid should be strengthened, and China should take its role and make more contributions to the low carbon transition especially energy transition of BRI countries. [ABSTRACT FROM AUTHOR]

International cooperation for renewable energy under the Belt and Road Initiative (BRI) plays a pivotal role in the transition to low-carbon energy in BRI developing countries. However, the rise in energy, debt, food, and geopolitical crises, along with the unique internal challenges found in different BRI developing countries, introduce multiple uncertainties to international renewable energy cooperation (IREC). Therefore, it is crucial to analyze the risks associated with IREC across different BRI countries by incorporating international cooperation theory. This study proposes an analytical framework comprising cooperation consensus–state capacity–institutional environment, which encompasses the willingness to cooperate, national capabilities, and international institutional considerations. An evaluation indicator system is constructed based on this framework. The study optimizes the indicator weights obtained from expert surveys using the analytic hierarchy process and the criteria importance through intercriteria correlation method. A quantitative assessment of IREC risks was conducted for 114 BRI countries from 2010 to 2020. The results indicate a gradual reduction in IREC risks between China and BRI countries. Regional risk assessments reveal that Southeast Asia exhibits the lowest average risk, while Africa not only records the highest average risk but also indicates substantial cooperation potential. Therefore, we recommend a comprehensive approach to risk mitigation. Such an approach would include gradually improving cooperation mechanisms, promoting both top-down and bottom-up cooperation, encouraging the involvement of multiple stakeholders, and prioritizing early-stage risk assessments and research. • A new analytical framework based on international cooperation theories. • A dynamic risk map for Belt and Road renewable energy cooperation. • The combination of AHP and CRITIC. • Tailored risk mitigation strategies for different regions. [ABSTRACT FROM AUTHOR]

To balance China's socio-economic development and emission reduction goals, a fair and effective provincial carbon emission allowance (CEA) allocation is necessary. By considering the implied emissions of inter-provincial power transfer, this study designed a dynamic multi-criteria CEA allocation model based on four criteria-egalitarianism, historical responsibility, emission reduction capability, and emission efficiency-to calculate the provincial CEA year by year before 2030. The efficiency and fairness of the CEA scheme were evaluated through the Data envelopment analysis (DEA) model, the environmental Gini coefficient, and its grouped decomposition method. The national overall CEA, the results revealed, will peak during the 15th Five-Year Plan (FYP) period. Specifically, the CEA for eastern and central China is expected to peak first during the 14th FYP period, while the northeast region's CEA remains stable and that of the western region continues to grow. Provinces with high carbon emissions, high carbon emission intensity and high per capita carbon emissions and provinces with particularly high carbon emissions will face great pressure regarding emission reduction, and their CEA peaks are expected to arrive before 2025 and 2030 respectively. The CEA of the less-developed provinces will have a surplus. In terms of time, the high-emission provinces face greater emission reduction pressure during the 15th FYP period than during the 14th FYP period. In terms of scheme evaluation, the scheme achieved a double improvement in fairness and efficiency compared with the current actual emissions of various provinces. Reducing the differences in per capita CEA between the different regions and provinces in the western and eastern regions will help improve the scheme's fairness. This study overcomes the existing researches' shortcomings on the large differences in the distribution of emission reduction pressures in key provinces and is more feasible in practice., Competing Interests: Declaration of competing interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled., (Copyright © 2022. Published by Elsevier B.V.)