The natural isotopic compositions and C/N elemental ratios of sedimentary organic matter were determined in the intertidal flat of the Yangtze Estuary. The results showed that the ratios of carbon and nitrogen stable isotopes were respectively −29.8‰ to − 26.0‰ and 1.6‰–5.5‰ in the flood season (July), while they were −27.3‰ to − 25.6‰ and 1.7‰–7.8‰ in the dry season (February), respectively. The δ13C signatures were remarkably higher in July than in February, and gradually increased from the freshwater areas to the brackish areas. In contrast, there were relatively complex seasonal and spatial changes in stable nitrogen isotopes. It was also reflected that δ15N and C/N compositions had been obviously modified by organic matter diagenesis and biological processing, and could not be used to trace the sources of organic matter at the study area. In addition, it was considered that the mixing inputs of terrigenous and marine materials generally dominated sedimentary organic matter in the intertidal flat. The contribution of terrigenous inputs to sedimentary organic matter was roughly estimated according to the mixing balance model of stable carbon isotopes. 相似文献
The differential code bias (DCB) in satellites of the Global Navigation Satellite Systems (GNSS) should be precisely corrected when designing certain applications, such as ionospheric remote sensing, precise point positioning, and time transfer. In the case of COMPASS system, the data used for estimating DCB are currently only available from a very limited number of global monitoring stations. However, the current GPS/GLONASS satellite DCB estimation methods generally require a large amount of geographically well-distributed data for modeling the global ionospheric vertical total electron content (TEC) and are not particularly suitable for current COMPASS use. Moreover, some satellites with unstable DCB (i.e., relatively large scatter) may affect other satellite DCB estimates through the zero-mean reference that is currently imposed on all satellites. In order to overcome the inadequacy of data sources and to reduce the impact of unstable DCB, a new approach, designated IGGDCB, is developed for COMPASS satellite DCB determination. IGG stands for the Institute of Geodesy and Geophysics, which is located in Wuhan, China. In IGGDCB, the ionospheric vertical TEC of each individual station is independently modeled by a generalized triangular series function, and the satellite DCB reference is selected using an iterative DCB elimination process. By comparing GPS satellite DCB estimates calculated by the IGGDCB approach based on only a handful (e.g., seven) of tracking stations against that calculated by the currently existing methods based on hundreds of tracking stations, we are able to demonstrate that the accuracies of the IGGDCB-based DCB estimates perform at the level of about 0.13 and 0.10?ns during periods of high (2001) and low (2009) solar activity, respectively. The iterative method for DCB reference selection is verified by statistical tests that take into account the day-to-day scatter and the duration that the satellites have spent in orbit. The results show that the impact of satellites with unstable DCB can be considerably reduced using the IGGDCB method. It is also confirmed that IGGDCB is not only specifically valid for COMPASS but also for all other GNSS. 相似文献
A numerical and experimental modeling is presented for studying the transport of waste heat from a nuclear power plant into coastal water by using a full-field physical model with scale distortion, a local physical model with normal scale and a depth-averaged k− turbulence model with a modified second-order upwind scheme. Field investigations are also used to provide the calibration and validation of the modeling. A case study simulating the turbulent tidal flow and waste heat transport in the coastal water near Daya Bay Nuclear Power Plant in Southern China was conducted. The experimental result of the case study shows that the water temperature in coastal water was a little oversimulated near the surface and was a little undersimulated near the bottom of heated-water layer by the full-field physical model. The numerical study shows that the depth-averaged k− turbulence model presented a satisfied prediction of turbulent tidal flow and far-field temperature distribution in coastal water, although the near-field stratification due to the heated water effluent was not accounted for. The result of the effect of scale distortion on physical model shows that a full-field physical model with a scale distortion of 10 produced a satisfied result of temperature distribution in the present case study. 相似文献
Maximum and minimum void ratios (emax and emin) of granular soils are commonly used as indicators of many engineering properties. However, few methods, apart from laboratory tests, are available to provide a rapid estimation of both emax and emin. In this study, we present a theoretical model to map the densest and the loosest packing configurations of granular soils onto the void space. A corresponding numerical procedure that can predict both emax and emin of granular soils with arbitrary grain size distributions is proposed. The capacity of the proposed method is evaluated by predicting the maximum and minimum void ratios of medium to fine mixed graded sands with different contents of fines. The influence of the grain size distribution, characterized quantitatively by uniformity parameter and the fractal dimension, on emax and emin is discussed using the proposed method. Moreover, application of this method in understanding the controlling mechanism for the void ratio change during grain crushing is presented.
To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking. 相似文献