| In this thesis, the topsoils in vicinities of the thermal power plant, the cement plant and Meigang Road were selected as the subject of this study. Distribution characteristics and influence factors of heavy metal pollution were investigated systemically. The relationship between heavy metals and magnetic parameters was discussed and magnetic diagnosis models were established correspondingly. The main results were summarized as follows:(1) The average contents of 10 heavy metals were basically higher than the corresponding background values of the nature cinnamon soils. Among them Cdwas the severest with the background of 6~8 times, secondly, Cu, Zn and Pb were more than 2 times, while the concentrations of V, Co, Mn and Fe were slightly higher than the background, respectively.(2)The semivariogram analysis showed that nugget/sill ratios of Cr, Cu, Zn, Cd and Pb were between 25%~75%. In addition, the ratios of Mn, Fe and N i around the thermal power plant, Fe and N i around the cement plant, Mn and N i on both sides of Meigang Road were more than or close to 25%, which considers that variables are amount to or close to a medium spatial correlation, indicating that the anthropogenic factors changed its spatial correlation through farming, industrial production, traffic pollution and other human activities. However, V and Co around the thermal power plant, V, Mn and Co near the cement plant, V, Fe and Co along Meigang Road were strongly spatially dependent with ratios of less than 20%, predicating that they can be attributed to the effects of natural factors, such as the parent material,soil type, climate and soil- forming factors.(3) Spatial distribution maps of the soil heavy metals by means of Ordinary Kriging interpolation showed that distribution patterns of Cu, Zn, Cd and Pb had certain similarities. The high concentrations around the thermal power plant distributed in the north and the southwest areas, and that close to the plant. Similar results were observed near the cement plant, high value locations were in the north and the southwest, and relatively higher in the southwest. Features of N i, Cu and Zn distributions presented ribbon and plaque shapes on both sides of Meigang Road. The high concentration locations were close to the road and the concentrations dropped gradually along with the distance increasing. According to Nemerow pollution index of heavy metal, the soils almost reached the severe risk level in the study area. The distribution maps of the indices had a similar variation trend. These distribution characteristics are not caused by farming, management practices, etc., but caused by industrial production, traffic pollution, and so on. The heavy metal contents were relatively higher, presumably influenced by climatic conditions.(4) Soil p H values were almost negative correlations with heavy metal contents except zwitterionic elements, such as Zn, Pb. TOC showed a positive correlation with most metals owing to adsorption. The heavy metal concentrations were negative correlations with sand contents in soils, but positive with silt and clay one. Ten metals can be divided into three categories according to the results of correlation analysis, principal component analysis and hierarchical cluster analysis: Cu, Zn, Cd and Pb near the thermal power plant and the cement plant, as well as N i, Cu and Zn along Meigang Road were mainly derived from the corresponding pollution sources; whereas V, Co and Mn throughout the regions, and Fe near the thermal power plant and Meigang Road are interpreted to be mainly inherited from parent materials; in addition, the sources of Cr and N i around the thermal power plant, Cr, Fe and N i around the cement plant, and Cr, Cd and Pb on both sides of the road can be from parent material, industrial and traffic pollution, as well as agricultural pollution.(5) The topsoils have the high χlf values up to 497.6×10-8m3/kg, as much 7 times as that of the range of normal values, the topsoil χlf generally tended to decrease with increasing distance from the pollution sources. A detailed result on both sides of Meigang Road showed thatthe spatial distribution of χlf in the vertical directions has some obvious features.The χlf of the samples changed evidently and were affected by climates within 15 m away from the road, but in the space ranging 15~40 m, the values, varied slightly, were low and close to that of topsoils with 500 m away from the pollution source, which conformed to the characteristics of traffic activities. The χlf was a negative correlation with χfd, which indicated that the strong signals of magnetic phases in vicinities of typical pollution sources mainly originated from the release of the sources. Magnetic mineralogy parameters of F300 and S-100 suggested that samples are dominated by ferrimagnetic minerals, but contain a small amount of anti- ferromagnetic material. The contents of anti- ferromagnetic materials around the thermal power plant and the cement plant were relatively higher than that of on both sides of Meigang Road. The measurement values of SIRM and SOFT were larger and had a good linear relation with χlf, which showed that the magnetic properties of topsoils were dominated by coarser MD magnetite grain. The phenomenon often comes from the industrial and mining enterprises emissions dust, vehicle exhaust and other human activities. In addition, spatial distribution maps of magnetic parameters, such as χlf and SIRM, were similar to that of Nemerow pollution indices of heavy metals, it was concluded that there was a close relationship between magnetic properties and heavy metal pollution.(6) The magnetic hysteresis loopsof representative topsoil samples were narrow and closed in 250~300 m T of external magnetic field, IRM reaches 83%~95% of saturation value at 300 m T, which indicated that low coercivity ferrimagnetic minerals were dominant in the samples. All representative samples located within the MD range of a hysteresis parameter Day-plot. Magnetic minerals can be identified by TDS curves and χlf decreases sharply at about 580°C, revealing magnetite as the major contributor to χlf and MD magnetite grains are often caused by anthropogenic activities. The results of correlation analysis, principal component analysis and hierarchical cluster analysis showed that χfd is significant correlation with elements mainly originated from natural factors, such asthe parent material, soil type and formation. Whereas there was a relatively strong correlation between χlf, SOFT, SIRM, χARM and the heavy metals dominated by human factors, such as industrial production, traffic or agricultural pollution. By multivariate step linear regression technology, different equations of heavy metals were established with soil magnetic parameters, they are magnetic diagnosis model of heavy metal pollutions.(7) Results of SEM showed that magnetic spherules and irregular-shaped particles are observed. The EDX of spherules surfaces show dominant peaks of Fe, along with smaller peaks of Pb, Zn, Cu, Cd, and so on. A preliminary explanation on the magnetic indicative function for heavy metal pollution can be given because magnetic particles and heavy metals are likely coexisting with each other.(8) The relationship between heavy metal concentrations and magnetism parameters in vicinities of typical pollution sources indicated that the parameters can be applied as proxy indicators of heavy metal pollution. Magnetic measurements can be used to monitor and evaluate heavy metal contamination of soil caused by industrial production, traffic pollution and other human activities because they are simple, rapid, and have low-cost and non-destructive characteristics. |
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