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Under the background of "double carbon", ecological water has become one of the significant resources to ensure the healthy and sustainable development of the regional ecological environment. And the ecological water consumption prediction is a prerequisite for optimizing water supply structures. Considering the impact of CO 2 emissions on ecological water consumption, the FGM(1,1) model was firstly used to predict CO 2 emissions considered as an impact factor in this paper. Then, an adjacent accumulative grey multivariate convolution model (AGMC(1,N)) was combined with the Average Weakening Buffer Operator (AWBO) to predict the annual ecological water consumption of 30 provinces (municipalities and autonomous regions) in China. The results show that the AGMC(1,N) model combined with the AWBO has better prediction effect. In addition, in the next decade, only six provinces in the northern region will have a decreasing trend in ecological water consumption. However, the other provinces are showing an upward trend. The ecological water consumption trends deviate from the CO 2 emission trends in 12 provinces. The research results are beneficial for the formulation of the ecological water consumption policies and the achievement of the dual carbon goals. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [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]

• We explore whether each of the 30 Chinese provinces will peak emissions by 2030. • We combine STIRPAT models and scenario analyses to predict emissions trajectories. • 26 provinces are likely to peak emissions under at least one scenario, but 4 are not. • Peaking time and cumulative emissions are considered in seeking optimal peaking path. • Provincial results in aggregate show China may peak in 2028–2040 and 2030 is optimal. China has pledged in its Nationally Determined Contributions (NDCs) that its carbon emissions will peak no later than 2030. However, the varying carbon emissions trajectories of individual provinces make it difficult to determine whether China can fulfill this ambitious goal on time. To bring transparency and clarity to this core issue, this paper explores for the first time whether and how all the 30 Chinese provinces will peak their energy-related emissions in future by developing a set of extended STIRPAT models that investigate the driving forces behind each province and integrating the estimates into scenario analysis for peaking simulation. We observe that, despite continued economic growth, 26 provinces are highly likely to reach peak emissions under at least one scenario, whereas the remaining are not. We find it interesting that the earliest peaking scenarios may not be the best option for those provinces whose cumulative carbon emissions are estimated to be considerably large. To ensure a viable reaching of China's peak emissions, much more attention should be paid to seeking for the most appropriate emissions trajectory to peak at the subnational level with relatively low cumulative value. Provincial results in aggregate show that China may peak emissions in the period 2028–2040, with cumulative emissions ranging from 403,607 Mt CO 2 (corresponding to peaking in 2030) to 456,191 Mt CO 2 (corresponding to peaking in 2038), while 2030 would be the optimal year for the country to peak because of the lowest cumulative carbon emissions. Our findings only provide a deeper understanding of China's potential peaking paths by province, but also assist policy makers in better prediction and evaluation of possible emissions trajectory for other nations and the whole world from a bottom-up perspective, and therefore could be of global significance. [ABSTRACT FROM AUTHOR]