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The structure of renewable energy (RE) development varies substantially across China's provinces, and the spatio-temporal pattern evolution is too pronounced to allow direct comparisons. Therefore, a reasonable method for RE efficiency estimation is important. Markov and spatial Markov chains can be used to analyze the evolution of the temporal and spatial patterns of provincial RE. Simultaneously, data envelopment analysis game cross-efficiency evaluation can quantify the RE generation efficiency of each province from the perspective of competition. Nine factors were selected to identify the key influencing factors the RE generation efficiency. From the perspective of spatio-temporal heterogeneity, a geographically and temporally weighted regression model was combined for spatial modeling. Results show a significant change in the categories of wind and solar power installations, a medium change in biomass installations, and a small change in hydropower installations. Two-thirds of the provincial RE generation efficiency increased from 2015 to 2020. There is spatio-temporal heterogeneity regarding the impact of various factors on the RE generation efficiency: The impact of technology market transactions exhibits the greatest inter-provincial variation and the impact of electricity industry investment exhibits the smallest inter-provincial variation. [ABSTRACT FROM AUTHOR]

• Establishing HWPS investment limitation and suitability assessment indicator systems. • Determination of expert weights using dynamic social networks. • TIFN was used to quantify the qualitative indicators. • Combining BWM and CRITIC combination weighting and TODIM to rank the alternatives. • Investment suitability assessment of 62 completed hydropower plants in China. The hydropower-wind-photovoltaic-storage (HWPS) complementary system is one of the essential ways for China to build a new type of power system and to realize the dual-carbon goal. However, China's HWPS complementary system is still in the exploratory stage, and it is important to propose a rational multi-attribute decision-making (MADM) framework for investment suitability assessment based on completed hydropower plants. Therefore, this study first established a limitation indicator system for preliminary screening hydropower plants and an HWPS investment suitability assessment indicator system containing six dimensions: nature, market, infrastructure, land, society, and environment. Second, the weights among experts were determined based on the dynamic social network, and a mechanism for updating expert weights was proposed. Again, triangular intuitionistic fuzzy number (TIFN) was used to quantify the qualitative indicators and combined the weights according to the best-worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) methods. Finally, the TODIM (an acronym in Portuguese for interactive and MADM) method was used for scheme suitability assessment with sensitivity analysis and method comparison. The results show that 62 eligible hydropower plants were preliminarily screened out of 647 completed medium- and large-scale hydropower plants in China by combining GIS technology. Natural factors are the most important of the six dimensions, followed by social factors. According to the suitability assessment results of TODIM, #23 hydropower station has the highest suitability for HWPSCS investment, which provides a reference for the layout of China's HWPS complementary system. With different decision makers' risk preferences and different MADM methods, #23 hydropower plant is still the best investment option, which proves the effectiveness of the MADM framework proposed in this study. [ABSTRACT FROM AUTHOR]

Same as other bay areas, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is also suffering atmospheric composite pollution. Even a series of atmospheric environment management policies have been conducted to win the "blue sky defense battle", the atmospheric secondary pollutants (e.g., O 3 ) originated from oxygenated volatile organic compounds (OVOCs) still threaten the air quality in GBA. However, there lacks a systematic summary on the emission, formation, pollution and environmental effects of OVOCs in this region for further air quality management. This review focused on the researches related to OVOCs in GBA, including their pollution characteristics, detection methods, source distributions, secondary formations, and impacts on the atmosphere. Pollution profile of OVOCs in GBA revealed that the concentration percentage among total VOCs from Guangzhou and Dongguan cities exceeded 50 %, while methanol, formaldehyde, acetone, and acetaldehyde were the top four highest concentrated OVOCs. The detection technique on regional atmospheric OVOCs (e.g., oxygenated organic molecules (OOMs)) underwent an evolution of off-line derivatization method, on-line spectroscopic method and on-line mass spectrometry method. The OVOCs in GBA were mainly from primary emissions (up to 80 %), including vehicle emissions and biomass combustion. The anthropogenic alkenes and aromatics in urban area, and natural isoprene in rural area also made a significant contribution to the secondary emission (e.g., photochemical formation) of OVOCs. About 20 % in average of ROx radicals was produced from photolysis of formaldehyde in comparison with O 3 , nitrous acid and rest OVOCs, while the reaction between OVOCs and free radical accelerated the NOx-O 3 cycle, contributing to 15 %-60 % cumulative formation of O 3 in GBA. Besides, the heterogeneous reactions of dicarbonyls generated 21 %-53 % of SOA. This review also provided suggestions for future research on OVOCs in terms of regional observation, analytical method and mechanistic study to support the development of a control and management strategy on OVOCs in GBA and China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Carbon emission reduction is an essential means to achieve the "double carbon goal," and the scientific and reasonable allocation of carbon emission quotas (CEQ) is the basis for promoting carbon emission reduction. In this study, the first level was based on the entropy TOPSIS scores of provinces under the principles of fairness, efficiency, sustainability, and feasibility and used the K-mean clustering method to cluster the 30 provinces and allocate the CEQ to each zone group; the second level consolidated the impacts of the four principles and the marginal abatement costs of CO 2 to allocate CEQ to the provinces within the zone group. Finally, each province's initial spatial balance of CEQ (ISBQ) is classified and evaluated. The study shows that the most quotas are for Guangdong, Zhejiang, and Inner Mongolia, and the least for Ningxia, Shanxi, and Guizhou. This study compares the results of CEQ allocation with the current carbon emission scale and finds that 11 provinces, such as Shandong and Hebei, show a deficit in future carbon emission space, and 19 provinces, such as Hainan and Beijing, show a surplus in carbon emission space. Given each province's different emission reduction tasks and pressures, differentiated emission control policies are the key to achieving China's "2030 target"., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)