Dissolved organic matter (DOM) is an important chemical component in natural water. Chromophoric dissolved organic matter (CDOM), a fraction of optical properties, plays art important role in the biogeochemical cycle of nutrients in aquatic environment. People realized that DOM cycle is crucial in the global carbon and nitrogen flux, and also is inherently related to nutrients and trace metal elements. Therefore, CDOM was concerned by scientists in global oceanography and limnology fields. Water samples were collected from three sections (North Channel, South Channel and Zhuyuan) of the Yangtze (Changjiang River) estuary in March 2006 Three-dimensional excitation emission matrix (3-DEEM) fluorescence spectra were analyzed for those filtrates through Whatman GF/F filters. Dissolved organic carbon (DOC) was also measured by TOC analyzer. The tidal variety was also taken into account. The 3-D EEM fluorescence scans suggested the fluorescence characteristics of humic acid (Ex=332-344 nm, Em=439-451 nm) and fulvic acid (Ex=250-254 nm, Em=472-478 nm) were obvious, and the fluorescence group of protein-like and tyrosine (Ex=230 nm, Em=283 nm) was also found. They are mainly composed of CDOM in the Yangtze estuary. Further data analysis, especially the fluorescence index (f 450/500), showed that terrestrial signal was rather strong (1.41-1.65) in the surface water, however, some terrestrial CDOM signals of bottom water showed excursions (1.28-1.39). On the other hand, anthropogenic sign was impressed in the waters of Zhuyuan, which is one of the main drain outlets of Shanghai Metropolis. DOC concentrations ranged from 2.2 mg/L to 3.4 mg/L in Zhuyuan and South Channel, and from 2.0 mg/L to 2.4 mg/L in North Channel. The tide effect played a role in the composition of the CDOM measured by 3-D fluorescence scan technology. 相似文献
Heavy metal distribution patterns in river sediments aid in understanding the exogenic cycling of elements as well as in assessing the effect of anthropogenic influences. In India, the Subernarekha river flows over the Precambrian terrain of the Singhbhum craton in eastern India. The rocks are of an iron ore series and the primary rock types are schist and quartzite. One main tributary, the Kharkhai, flows through granite rocks and subsequently flows through the schist and quartzite layers. The Subernarekha flows through the East Singhbhum district, which is one of India’s industrialised areas known for ore mining, steel production, power generation, cement production and other related activities. Freshly deposited river sediments were collected upstream and downstream the industrial zone. Samples were collected from four locations and analysed in <63-μm sediment fraction for heavy metals including Zn, Pb, Cd and Cu by anodic stripping voltammetry. Enrichment of these elements over and above the local natural concentration level has been calculated and reported. Sediments of the present study are classified by Muller’s geo-accumulation index (Igeo) and vary from element to element and with climatic seasons. During pre-monsoon period the maximum Igeo value for Zn is moderately to highly polluted and for Cu and Pb is moderately polluted, respectively, based on the Muller’s standard. Anthropogenic, lithogenic or cumulative effects of both components are the main reasons for such variations in Igeo values. The basic igneous rock layer through which the river flows or a seasonal rivulet that joins with the main river may be the primary source for lithogenic components. 相似文献
Chemical weathering indices are useful tools in characterizing weathering profiles and determining the extent of weathering. However, the predictive performance of the conventional indices is critically dependent on the composition of the unweathered parent rock. To overcome this limitation, the present paper introduces an alternative statistical empirical index of chemical weathering that is extracted by the principal component analysis (PCA) of a large dataset derived from unweathered igneous rocks and their weathering profiles. The PCA analysis yields two principal components (PC1 and PC2), which capture 39.23% and 35.17% of total variability, respectively. The extent of weathering is reflected by variation along PC1, primarily due to the loss of Na2O and CaO during weathering. In contrast, PC2 is the direction along which the projections of unweathered felsic, intermediate and mafic igneous rocks appear to be best discriminated; therefore, PC1 and PC2 represent independent latent variables that correspond to the extent of weathering and the chemistry of the unweathered parent rock. Subsequently, PC1 and PC2 were then mapped onto a ternary diagram (MFW diagram). The M and F vertices characterize mafic and felsic rock source, respectively, while the W vertex identifies the degree of weathering of these sources, independent of the chemistry of the unweathered parent rock.
The W index has a number of significant properties that are not found in conventional weathering indices. First, the W index is sensitive to chemical changes that occur during weathering because it is based on eight major oxides, whereas most conventional indices are defined by between two and four oxides. Second, the W index provides robust results even for highly weathered sesquioxide-rich samples. Third, the W index is applicable to a wide range of felsic, intermediate and mafic igneous rock types. Finally, the MFW diagram is expected to facilitate provenance analysis of sedimentary rocks by identifying their weathering trends and thereby enabling a backward estimate of the composition of the unweathered source rock. 相似文献
In this paper , by using the seismic data of strong earthquake (M≥7) which have occurred since 1900,correlative features of strong earthquake activity in Tianshan region which crosses China and USSR have been studied . Meanwhile , we selected 15 seismic windows (11 in China , 4 in USSR) by censusing , systematically researching and statistically examing seismic data of regional seismic network which are in Chian and USSR.The anomalous features of seismic window and seismic window network , prediction index and prediction plan have been studied . In the same time ,its prediction efficency have been evaluated . Several examples of successful earthquake prediction are given out in this paper .Finally ,the possible physical mechanism of the results are discussed. 相似文献