• Energy Research
• 2021-2025close
• US close
• Chinese Academy of Sciences close

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).

AbstractMicrobial carbon (C) use efficiency (CUE) delineates the proportion of organic C used by microorganisms for anabolism and ultimately influences the amount of C sequestered in soils. However, the key factors controlling CUE remain enigmatic, leading to considerable uncertainty in understanding soil C retention and predicting its responses to global change factors. Here, we investigate the global patterns of CUE estimate by stoichiometric modeling in surface soils of natural ecosystems, and examine its associations with temperature, precipitation, plant‐derived C and soil nutrient availability. We found that CUE is determined by the most limiting resource among these four basic environmental resources within specific climate zones (i.e., tropical, temperate, arid, and cold zones). Higher CUE is common in arid and cold zones and corresponds to limitations in temperature, water, and plant‐derived C input, while lower CUE is observed in tropical and temperate zones with widespread limitation of nutrients (e.g., nitrogen or phosphorus) in soil. The contrasting resource limitations among climate zones led to an apparent increase in CUE with increasing latitude. The resource‐specific dependence of CUE implies that soils in high latitudes with arid and cold environments may retain less organic C in the future, as warming and increased precipitation can reduce CUE. In contrast, oligotrophic soils in low latitudes may increase organic C retention, as CUE could be increased with concurrent anthropogenic nutrient inputs. The findings underscore the importance of resource limitations for CUE and suggest asymmetric responses of organic C retention in soils across latitudes to global change factors.

Embodied emissions from the production of building materials account for 17% of China's carbon dioxide (CO2) emissions and are important to focus on as China aims to achieve its carbon neutrality goals. However, there is a lack of systematic assessments on embodied emissions reduction potential of building materials that consider both the heterogeneous industrial characteristics as well as the Chinese buildings sector context. Here, we developed an integrated model that combines future demand of building materials in China with the strategies to reduce CO2 emissions associated with their production, using, and recycling. We found that measures to improve material efficiency in the value-chain has the largest CO2 mitigation potential before 2030 in both Low Carbon and Carbon Neutrality Scenarios, and continues to be significant through 2060. Policies to accelerate material efficiency practices, such as incorporating embodied emissions in building codes and conducting robust research, development, and demonstration (RD&D) in carbon removal are critical.

AbstractAcross the world, social‐ecological rangeland systems have been transformed from a preindustrial extensive status to intensive exploitation, often leading to long‐term livestock population booms, overgrazing, and rangeland degradation. To understand the regulatory mechanisms involved in such historical social‐ecological transformations, we collected population data on the native sheep of the last nomadic county in the Inner Mongolia Autonomous Region (1961–2005). We detected changes in internal feedbacks (e.g., density‐dependent effects) and external disturbance (e.g., winter harshness, rainfall, harvest) between the extensive and intensive management periods using regression models of sheep population growth rate and counterfactual analyses. We found that, in the extensive period, sheep populations were regulated during harsh winters by climate, while they were regulated during mild winters by negative density dependence. In the intensive period, the negative feedback of density dependence was removed through the provision of additional forage and shelter, and only winter climate and growing season rainfall regulated sheep populations. Counterfactual analyses also confirmed the irreplaceable role of density‐dependence in maintaining a sustainable rangeland ecosystem. Although herders attempted to adapt to the removal of negative feedbacks by improving livestock harvest, overgrazing and grassland degradation remain a challenge in this system. We conclude that internal feedbacks within social‐ecological systems should be carefully anticipated and accounted for when managing rangelands for sustainability.

Abstract To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 μg·m-3; the largest contribution was from the NO3- ion, at 14.6 ± 14.2 μg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. Although the emission rate of SO2 was low in summer, its conversion rate was high. In winter and autumn, NORs were significantly higher than in spring and summer, and a higher NOR in autumn contributed to significant elevation of the NO3- concentration in autumn relative to spring and summer. The average concentration of secondary organic carbon in 2019 was 2.8±1.9 μg·m-3, and it comprised approximately 30% of total OC. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively.

As an energy harvester that converts mechanical power into electrical energy, a triboelectric nanogenerator (TENG) with a pair of metallic and insulating electrodes can generate only the displacement current (Idis) in the electrodes, whereas a chemical potential difference generator (CPG) with a pair of semiconducting or/and metallic electrodes can generate both Idis and conduction current (Icon). Considering the effects of motion parameters on Idis and Icon is important for harvesting different mechanical energies in practical scenarios; the output characteristics of CPGs and traditional TENGs under different external resistance (R), contact-separation frequency (f), and maximum separation distance (xm) were systematically studied for the first time in this work. More interestingly, a direct current (DC) output can be generated directly by CPGs under R > 10 Mω or f > 100 Hz. This work not only provides a guideline for collecting different mechanical energies but also promotes the development of CPGs as an energy harvester and self-powered vibration sensor in the semiconductor industry. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) This project is financially supported by National Key Research and Development Program of China for Young Scientists (2021YFF0603500), National Natural Science Foundation of China (11974266 and U21A20147), Fundamental Research Funds for the Central Universities (WUT:2022IVA061, E1E46802), A*STAR AME IRG Grant SERC A1983c0027, and MOE AcRF Tier2 (2018-T2-2-005), Singapore.