Energy storage technologies can reduce grid fluctuations through peak shaving and valley filling and effectively solve the problems of renewable energy storage and consumption. The application of energy storage technologies is aimed at storing energy and supplying energy when needed according to the storage requirements. The existing research focuses on ranking technologies and selecting the best technologies, while ignoring storage requirements. Here, we propose a multi-criteria decision-making (MCDM) framework for selecting a suitable technology based on certain storage requirements. Specifically, we consider nine criteria in four aspects: technological, economic, environmental, and social. The interval number, crisp number, and linguist terms can be transformed into a probabilistic dual hesitant fuzzy set (PDHFS) through the transformation and fusion method we proposed, and a suitable technology can be selected through distance measurements. Subsequently, the proposed method is applied in a representative case study for energy storage technology selection in Shanxi Province, and a sensitivity analysis gives different scenarios for elaboration. The results show that the optimal selection of energy storage technology is different under different storage requirement scenarios. The decision-making model presented herein is considered to be versatile and adjustable, and thus, it can help decision makers to select a suitable energy storage technology based on the requirements of any given use case.

Background: The sustainable development of the building industry has drawn increasing attention around the world. Nanomaterials and nanotechnology play an important role in the processes of energy saving and reducing consumption in the building industry. Nanotechnology patents provide key technological support for the green development of the building industry. Based on patent data in China, this paper quantitatively analyzed the application of nanotechnology patents in the building industry and the time trend, regional differences, and evolution of China's nano-patent applications in the building field. Methods: In this study, the environmental total factor productivity of the building industry considering carbon constraints was determined and then used as the dependent variable to measure the green development of the building industry. On this basis, a panel data regression model was constructed to determine the impact of nano-patents on the green development of the building industry. Results: Nanotechnology patents in the building industry can significantly improve total factor productivity. From the perspective of patent composition, technology-based patents that focus on substantial innovation can significantly promote the green development of the building industry, whereas strategic patents show a significant inhibitory effect. Regionally, the western region of China has the advantage of being less developed and thus more efficient than the central and eastern regions in the application of new nano-products. Finally, the research also showed a significant lag in the application of China's nanotechnology patents and low implementation efficiency. Conclusion: Nano patents can promote green development in the building industry, but there is room for improvement in the speed with which laboratory inventions are transformed into building engineering applications.

Although the issue of embodied pollutants in China’s supply chains has garnered increasing attention, the dynamic changes occurring within them are unclear. Several existing studies analyze one-year or short-term data in supply chain. China’s overall CH₄ emissions have risen from 41.1 Tg in 2000 to 60 Tg in 2020, so conducting long-term analyses can yield a deeper understanding of the dynamic changes across the entire supply chain from production to consumption. This study uses the environmentally extended input–output analysis (EEIOA) and structural path analysis (SPA) methods to investigate the dynamic variation of China’s embodied CH₄ emissions in 20 industry sectors from 2000 to 2020, aiming to determine the key supply chain and key sectors. The results reveal that from the final demand perspective, consumption, investment and export drove 52.1%, 32%, and 15.9% of embodied CH₄ emissions in 2020. The sector with the highest embodied CH₄ emissions has changed from “Agriculture” in 2000 to “Construction” in 2010 to “Other service and activities” in 2020. The top listed supply chain path of embodied CH₄ emissions has also evolved (starting from production to consumption) from “Agriculture → Rural consumption” in 2000 to “Agriculture → Food and tobacco → Urban consumption” in 2010 to “Agriculture → Urban consumption” in 2020. Notably, the high-ranked path, “Agriculture → Food and tobacco → Rural consumption”, shows that the embodied CH₄ emission flowing between agriculture and the food industry cannot be ignored. The supply chain path “Coal Mining → Nonmetal Mineral Products → Construction → Capital Formation” has risen from 17th in 2000 to 3rd in 2020. Thus, it is necessary to control CH₄ emissions from sectors upstream, which are predominantly influenced by the construction industry, and a coordinated effort between sectors is also required to effectively reduce emissions. By 2020, the CH₄ emissions driven by urban consumption were 3.1 times that of rural consumption. This study provides a comprehensive analysis of China's supply chain over the past two decades. In particular, it suggests policy interventions by controlling critical supply chain paths and key sectors associated with embodied CH₄ emission, thereby facilitating the coordinated reduction of anthropogenic CH₄ emissions.

Utilizing China’s air quality monitoring data from 2013 to 2023, this study employs spatial autocorrelation analysis and health impact assessment methodologies to quantify the health economic costs and temporal trends of PM _2.5 and O ₃ pollution across mainland China. Results indicate a substantial decline in PM _2.5 -attributable mortality over the study period. With 0 and 15 μg/m ³ taken as the reference concentrations, all-cause mortality decreased by 47.41% (233,173 cases) and 65.55% (240,448 cases), respectively. Cardiovascular disease mortality declined by 47.71% (56,086 cases) and 65.75% (57,504 cases), while respiratory disease mortality reduced by 46.97% (38,519 cases) and 65.27% (40,055 cases). Conversely, O ₃ -related mortality exhibited a significant upward trend. At reference concentrations of 0 and 60 μg/m ³ , all-cause mortality increased by 24.25% (365,084 cases) and 79.70% (372,724 cases), respectively. Cardiovascular mortality rose by 25.43% (80,056 cases) and 81.52% (77,497 cases), and respiratory mortality increased by 15.46% (98,620 cases) and 64.54% (163,165 cases). Spatially, health economic costs and their GDP proportions for both pollutants followed a high distribution in the east and a low distribution in the west. Shandong, Henan and Jiangsu were the top regions for PM _2.5 -related economic costs, with Henan, Hebei and Tianjin exhibiting the highest GDP ratios. For O ₃ , Guangdong, Jiangsu and Shandong incurred the greatest economic costs, while Henan, Hebei and Gansu showed the highest GDP proportions. These findings underscore the divergent trends in PM _2.5 and O ₃ health impacts and provide critical evidence for targeted air pollution control strategies in China.