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Summary: Chinese cities need independent but synergetic dual-carbon abatement roadmaps to mitigate climate change and achieve carbon neutrality. Using source-level data, we develop a time-series, full-scale emission inventory for all Chinese cities from 2005 to 2020, exploring associated heterogeneous and homogeneous patterns. We find that 31% of cities have had a significant carbon emission peak, with the main driver being carbon intensity reductions through efficiency gains and structural improvements. Despite discrepant emission levels and socioeconomic determinants, a uniform trajectory in emission changes exists across cities via four emission phases: growth of 8%–9% annually (95% confidence interval) before peaking; plateau and decline by 9%–13% for 5–7 years; and plain with slower declines. We project that if cities follow their early-peaked counterparts’ mitigation pathways, China will reach a carbon peak in 2026 at 13 Gt and carbon neutrality during 2051–2058, revealing the feasibility of Chinese climate goals and the importance of long-reaching, city-targeted planning. Science for society: China established its dual-carbon goals to achieve a carbon peak before 2030 and carbon neutrality by 2060. It is important for cities to identify their distinctive patterns and define individual dual-carbon roadmaps to achieve carbon neutrality in China. In this study, we conduct a carbon inventory for all Chinese cities from 2005 to 2020 to quantitatively define the emission phases in the process of carbon peak. We find that 31% of cities have had a significant carbon emission peak, with the main driver being carbon intensity reductions. A uniform trajectory in emission changes exists across cities, despite significant differences in emission levels and socioeconomic determinants. We project that if cities follow their early-peaked counterparts’ mitigation pathways, China could achieve its climate change goals ahead of the policy deadlines.

Neurobasis chinensis is widely distributed in eastern tropical Asia. Its only congener in China, the N. anderssoni, has not been observed for decades. To protect N. chinensis, it is necessary to understand the ecological properties of its habitats and specie’s range shift under climate change. In the present study, we modeled its potential distribution under one historical, current, and four future scenarios. We evaluated the importance of the factors that shape its distribution and habitats and predicted the historical and current core spatial distributions and their shifting in the future. Two historical core distribution areas were identified: the inland region of the Bay of Bengal and south-central Vietnam. The current potential distribution includes south China, Vietnam, Laos, Thailand, Myanmar, Luzon of Philippines, Malaysia, southwest and northeast India, Sri Lanka, Indonesia (Java, Sumatera), Bangladesh, Nepal, Bhutan, and foothills of the Himalayas, in total, ca. 3.59 × 106 km2. Only one core distribution remained, concentrated in south-central Vietnam. In a warming future, the core distribution, high suitable habitats, and even the whole range of N. chinensis will expand and shift northwards. Currently, N. chinensis mainly resides in forest ecosystems below 1200 m above sea level (preferred 500 m to 1200 m a.s.l.). Annual precipitation, mean temperature of driest quarter, and seasonality of precipitation are important factors shaping the species distribution. Our study provides systematic information on habitats and geographical distribution, which is useful for the conservation of N. chinensis.

Accurately calculating the losses of ferromagnetic materials is crucial for optimizing the design and ensuring the safe operation of electrical equipment such as motors and power transformers. Commonly used loss calculation models include the Bertotti empirical formula and hysteresis models. In this paper, a new hybrid hysteresis model method is proposed to calculate losses—namely, the combination of the Jiles–Atherton hysteresis model (J–A) and the Fourier hysteresis model. The traditional Jiles–Atherton hysteresis model is mainly suitable for fitting the saturation hysteresis loop, but the fitting error is relatively large for internal minor hysteresis loops. In contrast, the Fourier hysteresis model is suitable for fitting the minor hysteresis loops because the corresponding magnetic induction strength or magnetic field is lower and the waveform distortion is small. Moreover, Fourier series expansion can be expressed with fewer terms, which is convenient for parameter fitting. Through examples, the results show that the hybrid hysteresis model can take advantage of the strengths of each model, not only reducing computational complexity, but also ensuring high fitting accuracy and loss calculation accuracy.

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

In this paper, the notion of a cohesive and self-sufficient grid is proposed. Based on a cohesive and self-sufficient virtual microgrid, an active distribution network is optimally planned, and an optimal configuration of demand-side resources, distributed generations, and energy storage systems are generated. To cope with stochastic uncertainty from forecast error in wind speed and load, flexibility reserves are needed. In this paper, the supply relation between flexibility and uncertainty is quantified and integrated in an innovative index which is defined as cohesion. The optimization objectives are a minimized operational cost and system net-ability cohesion as well as self-sufficiency, which is defined as the abilities both to supply local load and to deal with potential uncertainty. After testing the optimal configuration in the PG&E 69 bus system, it is found that with a more cohesive VM partition, the self-sufficiency of VMs is also increased. Also, a case study on uncertainty-caused system imbalance is carried out to show how flexibility resources are utilized in real-time operational balance.