[Research on the Matrix Interference on Major and Minor Elements in Soil Samples with ICP-AES].

According to the commonly used method of analysis with ICP-AES in geochemistry, to study the influence factors of interference from the analysis results, standard soil substances were selected to be the calibration curve of work, and the same method of digestion with soil samples was used to balance and eliminate the matrix interference. The concentrations of major and minor elements in soil samples were measured; the relative deviation of the results was compared under conditions of soil matrix and non-soil matrix interference; the relations and laws were being analyzed. The relative deviation (RE%) of testing results under non-soil-matrix interference were found floating around zero, the ratios of positive deviation and negative deviation were almost the same. Excluding the factors of spectral interference, the method of matrix matching can effectively eliminate the effects of matrix interference on soil. It was found that the analysis results of major elements, such as Al, Ca, Fe, Mg, P, Ti and Ba, were influenced negatively greatly under the condition of soil matrix interference, The maximum deviation of Mg 279.5 nm was up to -14.49%. The degree of influence ranking showed as Ti, Mg>P, Fe>Ca, Ba>Al. However, there is no obvious effect on other elements, including Na, Cr, Cu, V, Li, Mn, Ni and Sr. Contrary to the original ideas, the matrix interference effected greatly on the results of elements of high content, nevertheless, the effects on minor elements were not significant. As to the comprehensive matrix interference , the large proportion of interference from component self-content appeared of elements of Ca and Mg, because obvious linear correlation was found between component self-content and the relative deviation of the testing results of Ca and Mg. But no linear trend appeared between the self-contents of other elements and the results of matrix interference, indicating that the influence weight from self-content of other elements was very small. It was very important to select the right spectral lines, and remove the factors of interference to determinate the results of measurement. Factors and rules of interference effect has always been the research topic by all of scholars in the research field of ICP spectrum. On the guidance of above research results, the spectral lines will be selected and the accuracy judged reasonably, when soil samples being analyzed by ICP-AES.

Association of soil arsenic and nickel exposure with cancer mortality rates, a town-scale ecological study in Suzhou, China.

Heavy metals and arsenic are well-known carcinogens. However, few studies have examined whether soil heavy metals and arsenic concentrations associate with cancer in the general population. In this ecological study, we aimed to evaluate the association of heavy metals and arsenic in soil with cancer mortality rates during 2005-2010 in Suzhou, China, after controlling for education and smoking prevalence. In 2005, a total of 1683 soil samples with a sampling density of one sample every 4 km(2) were analyzed. Generalized linear model with a quasi-Poisson regression was applied to evaluate the association between town-scale cancer mortality rates and soil heavy metal concentrations. Results showed that soil arsenic exposure had a significant relationship with colon, gastric, kidney, lung, and nasopharyngeal cancer mortality rates and soil nickel exposure was significantly associated with liver and lung cancer. The associations of soil arsenic and nickel exposure with colon, gastric, kidney, and liver cancer in male were higher than those in female. The observed associations of soil arsenic and nickel with cancer mortality rates were less sensitive to alternative exposure metrics. Our findings would contribute to the understanding of the carcinogenic effect of soil arsenic and nickel exposure in general population.

[Quantifying the influence of different matrices on Pb accumulation in the soil from Nanjing and suspended matter from the lower of the Yangtze River with Pb isotopic technique].

Lead pollution and its geochemical behavior have an influence on ecological environment and human health. It is of significance to study the characteristics and mechanism of Pb accumulation and to quantify the contributions of different environmental matrices to Pb accumulation in soils and river suspended matter in the representative fluvial delta area, such as the lower of the Yangtze River. The results showed that lead was enriched in the urban topsoil in Nanjing and the suspended matter in the lower of the Yangtze River. The urban topsoil and the river suspended matter showed higher 206Pb/207Pb and lower 208Pb/206Pb relative to the natural matrices, and this was resulted from the influence of the anthropogenic lead. The relative contribution of separate Pb sources was assessed with the Pb geochemical model, 18%-56% (average 35%) Pb in Nanjing urban soil was derived from the anthropogenic matrices, and anthropogenic Pb contributed 22%-46% (average 32%) of total Pb in the Yangtze River suspended matter.

Reflectance spectroscopy study of Cd contamination in the sediments of the Changjiang River, China.

Sediments of the Changjiang River have been found in recent studies to be enriched in cadmium (Cd). The possibility and mechanisms for evaluating total Cd concentration and its binding form using reflectance spectroscopy within the visible-near-infrared (VNIR) region (400-2500 nm) have been investigated. Bottom sediments (69 samples) in the lower reaches of the river were collected for chemical analyses and spectral measurements. Total Cd concentration in the sediments was found to be exponentially related to the spectral proxies for organic matter(spectral reflectance at 400-530 nm), clay minerals (first derivative (FD) values at the shoulders related to absorption bands near 1400, 1900, and 2200 nm), and Fe oxides (FD values at 560-760 nm). The results indicated that the spectrally featureless Cd was mostly bound to these spectrally active materials, which made it possible for Cd concentration to be determined from reflectance spectra. This conclusion was also confirmed bythe results of chemically sequential extraction of Cd. This study has demonstrated the usage and theoretical basis of reflectance spectroscopy, which is a rapid and inexpensive analytical method, for evaluating contamination by heavy metals and their binding forms in sediments.

[Coregionalization, spatial-correlation and spatial-factor analysis of soil available heavy metals in a typical region of the Yangtze River Delta].

The method of factorial kriging based on the theory of coregionalization is developed by the combination of multi-statistics, geostatistics and GIS. Soil available heavy metals of 126 topsoil samples in Kunshan city, a typical region of Yangtze River Delta, were analyzed, and the spatial distribution pattern was investigated by the method of factorial kriging. Based on the analysis of multi-scale spatial structure characteristics of available heavy metals, we discussed the pollution source and cause of this spatial distribution by means of spatial scale-correlation analysis and spatial principal component analysis. Our results show that all the available heavy metals distribute normally or lognormally with great variability, and the contamination of available Cd is the biggest. The available heavy metals are categorized into three spatial scales, i.e. nugget, short-range (15 km) and long-range (40 km), respectively, and a linear model of coregionalization comprising these three spatial scales is fitted to the experimental auto-and cross-variograms of the soil available heavy metals. Significant relationship is found between Cd and Zn in the three scales. The spatial correlation of available heavy metals in short-range and long-rang are stronger than it in nugget, while the long-rang has more obvious negative correlation than the other two spatial scales. The results of spatial principal component analysis show the pollution sources are different in the three spatial scales. The kriging interpolation method was applied to work out the distribution maps of first and second principal component of available heavy metal, which indicate that available heavy metal concentrations in the soils are closely related to their industry activity, sewage irrigation and soil characteristics.