• Energy Research
• 7. Clean energy close
• 15. Life on land close
• 11. Sustainability close
• Chinese Academy of Sciences close

The issue of achieving sustainable livelihoods (SL) is a persistent problem that has gained significant interest for all countries. Even though contexts of vulnerability have been highlighted to be critical to SL, the difference of SL under vulnerability contexts, particularly disaster, has been ignored. As one disaster-prone area, there is an urgent need to conduct studies on SL in Shenzha, within the context of the construction of a national park. This paper proposes to address this research gap by evaluating SL under various disaster contexts in Shenzha, China. According to the frequency of natural disasters, towns in Shenzha can be divided into three groups: Snowstorm and windstorm-dominated towns (SWT), mixed towns (MT) and drought-dominated towns (DT). The results showed that (1) a great disparity of SL can be observed among the three vulnerability groups. The scores of these SL were sorted into descending order as: DT > SWT > MT. (2) In detail, herdsmen in DT have a high value of SL because they have high livelihood assets, livelihood strategies and disaster management capabilities. (3) Herdsmen in SWT have high livelihood assets, particularly human and financial assets, and livelihood strategies. (4) The low livelihood assets and livelihood strategies have restricted the SL of herdsmen in MT. An analysis of SL under various disaster contexts helped to depict the characteristics of SL. Accordingly, targeted policies were developed for the development of SL under various disaster contexts.

A hybrid structure constructed by uniformly anchoring crystalline Ni2P cocatalyst on 1D CdS nanorods exhibits extraordinarily efficient photocatalytic activity for H2 evolution in water (rate of 1,200 μmol h−1 mg−1 and TOF of 36,400 h−1 per mol Ni2P) under visible light irradiation.

This paper proposes a series of parallel optimizations on a high-resolution ocean model, the LASG/IAP Climate System Ocean Model (LICOM), which was independently developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. The version of LICOM that we used was LICOM 2.1. In order to improve the parallel performance of LICOM, a series of parallel optimization methods were applied. We optimized the parallelization scheme to tackle the problem of load imbalance. Some communication optimizations were implemented, including data packing, the application of the least communication algorithm, and the replacement of communications with calculations. Furthermore, for the calculation procedures, we implemented some mature optimizations and expanded functions in a loop. Additionally, a hybrid of MPI and OpenMP, as well as an asynchronous parallel IO, was used. In this work, the optimized version of LICOM 2.1 was able to achieve a speedup of more than two times compared with the original code. The parallelization scheme optimization and the communication optimization produced considerable improvement in performance in the large-scale parallelization. Meanwhile, the newly optimized LICOM could scale up to 245,760 processor cores. However, for the original version, there was no speedup when scaled up to over 10,000 processor cores. Additionally, the problem of jumpy wall time during the time integration process was also tackled with this optimization. Finally, we conducted a practical simulation from 1993 to 2007 by using the optimized version of LICOM 2.1. The results showed that the mesoscale vortex was well simulated by the model.

Climate change and human activities are two major drivers of grasslands degradation. Understanding the vulnerability of grasslands to both drives is of great importance for grassland conservation. This research established a vulnerability assessment model with historical and future the Normalized Difference Vegetation Index (NDVI), which was predicted by an optimized spatiotemporal NDVI prediction model, and then examined the vulnerability of grasslands under climate change and human activities in Gannan Prefecture on the north-eastern Qinghai-Tibet Plateau. Our results show that Gannan grasslands would show a vulnerability pattern of higher in the west and lower in the east under climate change and human activities. More than 46 % and 17 % of the region will become highly and medium vulnerable areas in the future, mainly concentrated in Maqu, Luqu and Xiahe counties in the west, southwest and northwest of Gannan. Specifically, the vulnerability is the lowest under the future climate scenario of moderate carbon emissions (i.e. RCP 4.5). Land use types such as forest land, unutilized land and cultivated land conversion to grassland could partially offset the vulnerability mainly caused climate change, while the conversion of grassland to unutilized land, forest land and cultivated land would increase the vulnerability of grassland. Our results would help to deepen the understanding of the patterns and main drivers of Gannan grasslands vulnerability under the impacts of climate change and human activities, and provide theoretical basis for the development of corresponding grassland management policies.

Abstract Cu2BaSn(S,Se)4 (CBTSSe) solar cells are emerging photovoltaic devices due to their high theoretical efficiencies of ~31%, environment-friendly and earth-abundant composition, low density of non-recombination defects, and so on. However, the record efficiency of CBTSSe solar cell is only 5.2%, showing the importance of studying their performance via numerical analysis to further enhance their practical efficiencies. In this paper, the effect of absorber and buffer layers on performances of Cu2BaSnS4 (CBTS) solar cells are firstly systematically studied via the SCAPS-1D software to provide a platform for the study of the effect of MoS2 interlayer on the performances of CBTS solar cells. The highest PCE of CBTS solar cell with a 30 nm CdS buffer layer is 11.87%. The PCE of CBTS solar cell with a 0.8 μm CBTS absorb layer is 12.51%, indicating that the CBTS solar cell is a potential low-cost solar cell due to its large optical absorption coefficient (α > 104 cm−1). The efficiency of CBTS solar cell is improved to 16.47% when the carrier concentration of CBTS is 1016 cm−3. The relationship between the performance of solar cell and the band gap, thickness, donor concentration, acceptor concentration of MoS2 interlayer is systematically investigated on the basis of the optimized efficiency. It is found that MoS2 interlayer plays an important role in the performance of CBTS solar cell. The p-type MoS2 has a beneficial effect on the efficiency improvement while the n-type MoS2 has a negative effect on the efficiency enhancement. The highest PCE of CBTS solar cell is as high as 18.28% when the thickness and the acceptor concentration of MoS2 are 4 nm and 1019 cm−3, respectively. Our simulation result provides a promising research direction to further improve the actual efficiency of the CBTS solar cell.

Ferrocene was introduced as a solid additive in organic solar cells (OSCs). The use of ferrocene provides PM6:Y6 based device with improved performance and stability, demonstrating its great potential in the fabrication of efficient and stable OSCs.

A new small molecule acceptor, Y18, was designed and synthesized. Over 17% efficiency was obtained with single junction solar cells based on Y18.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Farmland is the most basic material condition for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both stable rural livelihoods and sustainable farmland use into account has vital significance in theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems, and natural and social factors that are related to its changing process need to be considered when modeling farmland changing processes. This paper uses Qianjingou Town in the Inner Mongolian farming–pastoral zone as a study area. From the perspective of the relationship between household livelihood and farmland use, this study establishes the process mechanism of farmland use change based on questionnaire data, and constructs a multi-agent simulation model of farmland use change using the Eclipse and Repast toolbox. Through simulating the relationship between natural factors (including geographical location) and household behavior, this paper systematically simulates household farmland abandonment and rent behaviors, and accurately describes the dynamic interactions between household livelihoods and the factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (household family structures, economic development and government policies). Ultimately, this study scientifically predicts the future farmland use change trend in the next 30 years. The simulation results show that the number of abandoned and sublet farmland plots has a gradually increasing trend, and the number of non-farming households and pure-outworking households has a remarkable increasing trend, whereas the number of part-farming households and pure-farming households has a decreasing trend. Household livelihood sustainability in the study area is confronted with increasing pressure, and household non-farm employment has an increasing trend, while regional appropriate-scale agricultural management is maintained. The research results establish the theoretical foundation and a basic method for developing sustainable farmland use management that can meet the willingness of households and guarantee grain and ecological security.