Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

A quantitative assessment of a terrestrial biosphere model's data needs across North American biomes

Abstract: Terrestrial biosphere models are designed to synthesize our current understanding of how ecosystems function, test competing hypotheses of ecosystem function against observations, and predict responses to novel conditions such as those expected under climate change. Reducing uncertainties in such models can improve both basic scientific understanding and our predictive capacity, but rarely are ecosystem models employed in the design of field campaigns. We provide a synthesis of carbon cycle uncertainty analyses conducted using the Predictive Ecosystem Analyzer ecoinformatics workflow with the Ecosystem Demography model v2. This work is a synthesis of multiple projects, using Bayesian data assimilation techniques to incorporate field data and trait databases across temperate forests, grasslands, agriculture, short rotation forestry, boreal forests, and tundra. We report on a number of data needs that span a wide array of diverse biomes, such as the need for better constraint on growth respiration, mortality, stomatal conductance, and water uptake. We also identify data needs that are biome specific, such as photosynthetic quantum efficiency at high latitudes. We recommend that future data collection efforts balance the bias of past measurements toward aboveground processes in temperate biomes with the sensitivities of different processes as represented by ecosystem models. ©2014. American Geophysical Union. All Rights Reserved.

Nitrogen-doped ordered mesoporous carbon single crystals: aqueous organic–organic self-assembly and superior supercapacitor performance

Abstract: Nitrogen-doped ordered mesoporous carbon (NOMC) with a cubic Imm symmetry and rhombic dodecahedral single-crystal morphology has been successfully synthesized for the first time via organic–organic self-assembly of triblock copolymer, 3-aminophenol, and hexamethylenetetramine (HMTA) in basic aqueous solution. A steam treatment at elevated temperature has been developed to remove the surfactant from the as-synthesized sample, open the mesoporous cages, and create abundant micropores in the final product. Benefiting from the unique features of high surface area, uniform and uninterrupted mesopores, rich microporosity, and moderate nitrogen-doping (3.42%), the resultant NOMC single crystals show a high capacitance (281 F g−1 at 0.5 A g−1), excellent rate capability (195.5 F g−1 at 20 A g−1), and outstanding cycling stability (97% capacity retention after 5000 cycles at 5 A g−1) in electrochemical double-layer capacitors (EDLCs).

Risk assessment to China’s agricultural drought disaster in county unit

Abstract: China faces drought disaster risk under the changing climate. Risk analysis is a suitable approach in order to design ex-ante measure able to anticipate effects of drought on agricultural production. In this article, with the support of historic drought disaster data from 583 agro-meteorological observations (1991–2009), a risk analysis method based on information diffusion theory was applied to create a new drought risk analysis model, and the risk of China’s agriculture drought disaster was evaluated on higher spatial resolution of county unit. The results show that in more than three hundred counties of China, risk probability was biyearly or annually when Drought Affected Index (DAI) was over 5%. When DAI was up to 40%, more than one hundred counties were prone to drought disaster annually or once every 5 years. This showed that the impact of drought disaster on China’s agriculture, whether in frequency or intensity, was large. With the different level of DAI, China’s agricultural drought risk pattern showed variable pattern characteristics. When DAI was low, the distribution of county agricultural drought risk in China presented the East–West pattern of differentiation, and high risk mainly lied in the eastern, low risk mainly in the western. On the other hand, when DAI was high, the distribution of county risk appeared a pattern of high in center, and the north areas higher than the south, increased gradually from southwest to northeast. Drought risk presents a clear zonal differentiation that may be result from stepped topography, different precipitation and hazard-affected bodies. Spread of high value area of drought risk in northern may be related to the southeast monsoon and ecological degradation in northern Ecotone.

Carbon price forecasting with variational mode decomposition and optimal combined model

Abstract: In order to deal with non-stationary and nonlinear carbon price series, a hybrid forecasting approach is proposed in this study, which is incorporated variational mode decomposition (VMD), mode reconstruction (MR) and optimal combined forecasting model (CFM). The proposed approach introduces a new modes reconstruction method by using evolutionary clustering algorithm, and utilizes optimal combined model to forecast the reconstructed modes. The major steps of developed method can be summarized as: Firstly, carbon price is decomposed into several modes via VMD model, and the modes are obtained adaptively. Secondly, the comprehensive contribution index (CCI) of each mode is calculated and modes are further reconstructed by evolutionary clustering algorithm according to CCI. Then, a new sub-series called virtual modes (V-Modes) is defined and obtained. Thirdly, the optimal combined forecasting model is developed to forecast the V-Modes. In the end, the final forecasting results are obtained by summing the forecasts of V-Modes. For illustration and comparison, the carbon price data from Shenzhen and Hubei Province in China are shown as numerical examples. The empirical results confirm that the proposed approach outperforms benchmark models in terms of some statistical measures and robustness. Therefore, the proposed hybrid approach can be utilized as an effective model for the forecasting of carbon price.