白银市区土壤作物系统重金属污染分析与防治对策研究

通过对白银市区土壤作物系统重金属含量与分布变化特征的调查分析，结果表明，只有东大沟污灌区土壤作物污染严重，Cd,Pb超标明显；西大沟清污混灌区土壤环境为轻度污染，但作物质量符合标准要求；其余灌区土壤物质符合标准要求。最后，根据土壤作物重金属含量分布变化特征，提出了相应的防治对策。     

土壤-植物系统中磷对重金属生物有效性的影响机制

磷对植物吸收重金属元素的影响作用属于植物营养和重金属污染生态研究的前沿。污染土壤中施入磷是否能够降低重金属离子的生物有效性，除了与重金属离子本身特性有关外，还与含磷化合物的性质及土壤环境条件有关。在分析中，就土壤中磷与重金属离子间交互作用机制、土壤中影响磷降低重金属离子生物有效性的环境因子及磷与重金属交互作用的国内外研究进展作了简要综述，并对今后的研究提出了展望。     

土壤中重金属污染的研究进展

介绍了土壤重金属的污染及其特点，重金属对环境危害和在土壤中的化学行为，最后论述了土壤重金属元素的背景值。     

某矿区土壤和地下水重金属污染调查与评价

为了解湘南某矿区土壤和地下水重金属污染状况，对该矿区东河流域附近重金属污染源进行了调查，同时，对地下水和土壤样品进行了采样分析，结果表明：（1）该矿区东河流域附近的主要污染源有18个，其中有色金属选厂、尾矿库、采矿场和冶炼厂是排放重金属较多的污染源；（2）20个采样点中土壤重金属Pb、Cd、Zn、As和Hg大部分超过国家土壤环境质量标准（GB15618-1995），综合污染指数P综〉1，该矿区主要的重金属污染元素为Cd、As和Hg，且土壤中Cd、Zn和As的含量两两之间存在着极显著的正线性相关关系；（3）重金属元素在土壤中的纵向迁移不明显，该矿区附近20个采样点的地下水并未受到污染，综合污染指数P综〈1。20个采样点地下水Pb、Cd、Zn、As、Hg浓度均能达到地下水质量标准（GB／T14848．9）中的Ⅲ类标准。     

城市污水处理厂的污泥农用对土壤的重金属影响

污泥农用是城市污水处理厂污泥资源化利用的有效途径，但污泥中的重金属元素含量高，可能成为环境中的一种安全隐患。重金属对环境的危害不仅与其总量有关，更大程度上由其形态分布所决定。实验研究了污泥农用所引入的重金属对土壤重金属总量及其形态的影响，研究结果表明，污泥农用虽然明显增加了土壤中的重金属总量，但重金属在土壤中的活性却受到了抑制，从而降低了重金属通过食物链危害人类健康的风险。     

桉树人工林地土壤养分和重金属现状分析与评价

为了评价大面积人工种植桉树对当地土壤养分变化和重金属富集效应的影响，本研究以普洱市3.75万hm²桉树人工林为研究对象，通过定位观测并将其与当地次生林、撂荒地进行比较，分析土壤养分变化情况、重金属污染等级以及两者之间的相关性。结果表明，桉树林表层土壤养分的含量均高于背景值，其中有效磷、水解性氮、全磷、全钾、有机质和速效钾极显著高于撂荒地（P<0.01），全氮略高但差异不显著；与次生林相比，桉树林土壤养分全氮和水解性氮显著低（P<0.05），全钾和全磷的含量显著高（P<0.05），有效磷的含量极显著高（P<0.01），有机质和速效钾略高但差异不显著。桉树林表层土壤样品重金属综合污染指数为1.08，低于撂荒地的1.14而高于次生林的0.67，说明桉树林土壤已处于轻微度污染等级，有可能会引起农作物污染，其中铅、锌、铜、镍、砷和铬等6种重金属含量处于安全水平，而镉的单因子污染指数值介于1~2之间，表明桉树林土壤属于轻度镉污染，但相关性分析结果表明，桉树林表层土壤养分的含量与重金属的含量无显著相关。     

层次分析法与地理信息系统在农田土壤重金属污染评价中的应用

以《土壤环境质量标准》(GB 15618—1995)二级标准作为评价标准,采用以改进层次分析法确定权重的加权平均法对南京市郊典型蔬菜地的土壤重金属污染状况进行了评价。结果表明,研究区土壤中Cu、Pb、Cr的单因子污染指数平均值均小于1,含量超标率均不超过10.32%,而Cd的单因子污染指数平均值达2.15,含量超标率为84.13%,急需对该区土壤和受体做进一步的Cd污染深入调查或风险评估;研究区土壤重金属综合污染指数平均值为1.28,属玷污水平;利用ArcGIS 8.3软件进行土壤重金属污染的空间分布特征分析结果表明,研究区各元素的污染程度为Cd>Pb>Cu>Cr,各元素的污染格局较为相似,城市化活动对土壤污染贡献较大;研究区有81.16%的土壤重金属污染级别为玷污,3.78%处于本底级,15.06%处于安全级。     

燃煤电厂重金属排放与周边土壤重金属污染评价

为研究燃煤电厂重金属排放对周边土壤重金属污染的影响,测定了某燃煤电厂烟囱入口烟气中Cd、Cr、Hg、Ni、Pb、As含量,同时根据当地气象及地形条件,在燃煤电厂周边采集19个土壤样品,分析了土壤中重金属含量及分布情况,并对其污染程度进行评价.结果表明,燃煤电厂烟气中6种重金属元素的质量浓度为0.02～2.00μg/m3...     

钢丝绳产业区废水重金属对土壤与蔬菜的影响及生态风险评价

选取钢丝绳产业区某较发达的一乡镇为研究区域，对其周边土壤及蔬菜的污染状况进行调查和实验研究，结果表明：（1）钢丝绳产业区废水重金属对附近土壤并未产生较大污染，蔬菜重金属元素锌的安全率为100％，铅仅为55％。（2）钢丝绳产业区叶类蔬菜中铅的含量最高，豆类蔬菜中却是锌的含量最高，根茎类蔬菜中铅和锌的含量均较低。     

陕北原油污染土壤不同层次重金属含量及分布特性分析

以延长油田西区采油厂原油污染土壤为研究对象,选取有代表性的6个丛式井场,采集深度为0~10、10~20、20~30cm 3个土层的土壤样品,同时设非污染对照点。重点分析了原油污染土壤中Hg、As、Cd、Pb、Zn、Cu、Cr共7种重金属的含量及其在不同土层的分布状况,重金属含量与相应土壤理化性质的关系。结果表明,油区土壤石油污染为点污染,采样点1、3、4、6土样的石油烃质量浓度在1 111.67~2 799.00mg/kg,达重度污染。虽然各土样中7种重金属均未超过《土壤环境质量标准》(GB 15618—1995)的二级标准限值,然而单因子富集指数表明,Hg、Cd、Pb、Zn、Cu均有不同程度的富集。原油污染显著改变土壤性质,土壤石油烃含量与总有机碳、速效氮极显著相关,与土壤电导率、Zn含量、Cu含量显著相关。本研究完善了陕北原油污染土壤中重金属含量及分布状况资料,为污染环境的生物修复提供了基础信息。     

Evaluation of plant availability of soil trace metals by chemical fractionation and multiple regression analysis

Soil samples with a range of chemical and physical properties were collected from 10 different rural regions of China. Trace metals (Ni, Co, Cu, and Pb) in the soils were partitioned by a sequential extraction procedure into Mg(NO(3))(2) extractable (F1), CH(3)COONa extractable (F2), NH(2)OH.HCl extractable (F3), HNO(3)?H(2)O(2) extractable (F4), and residual (F5) fractions. Chemical fractionation showed that F1 fraction of the metals was less than 1% and residue was the dominant form for Cu and Ni in all samples, and for Co in most of the samples. Significant interrelationships of the fractions varied considerably with the different metals. Winter wheat (Triticum aestivum L.) and alfalfa (Medicago sativa L.) had been grown on the soils in a pot-culture experiment under greenhouse conditions for 40 days. Metal availability to the plants was evaluated by simple and multiple regression analysis. The Mg(NO(3))(2) extractable Co (F1) was significantly correlated with Co concentrations in different parts of wheat and in the whole of alfalfa. For the other metals, the independent variables of the multiple regression models, chosen by stepwise selection, were given as: F1 and F2 + F3 + F4 for Ni; F1, F2 + F3 and F4 for Cu; and F3 + F4 for Pb. The results of this study demonstrate that the sequential extraction procedure, in conjunction with multiple regression models using a combination of correlated fractions as an independent variable, may be useful for the prediction of plant absorption of trace metals in soils.     

Comparison of a rhizosphere-based method with other one-step extraction methods for assessing the bioavailability of soil metals to wheat

There is no method recognized as a universal approach for evaluation of bioavailability of heavy metals in soil. Based on the simulation of the rhizosphere soil conditions and integration of the combined effects of root-soil interactions as a whole, a rhizosphere-based method has been proposed. Wet fresh rhizosphere soil was extracted by low-molecular-weight organic acids (LMWOAs) to fractionate metal fractions of soil pools, which were then correlated with the metal contents of wheat roots and shoots. The rhizosphere-based method was compared with other one-step extraction methods using DTPA, EDTA, CaCl2, and NaNO3 as extractants and the first step of the Community Bureau of Reference (BCR) method. Simple correlation and stepwise multiple regression analysis were used for the comparison. Simple correlation indicated that the extractable Cu, Zn, Cr, and Cd of soils by the rhizosphere-based method were significantly correlated with the metal contents of wheat roots. For DTPA, BCR1 and EDTA methods there was a relatively poor correlation between the extractable Cu, Zn and Cd of soil and metal contents of wheat roots. Stepwise multiple regression analysis revealed that the equation of the rhizosphere-based method was the simplest one, and no soil properties variables needed to be added. In contrast, the equations of other one-step extraction methods were more complicated, and soil properties variables needed to be entered. The most distinct feature of the rhizosphere-based method was that the recommended method was suitable for acidic, neutral and near alkaline soils. However, the DTPA and EDTA extraction methods were suitable for calcareous soils only-or-only for acidic soils. The CaCl2, and NaNO3 extraction methods were only suitable for exchangeable metals. In short, the rhizosphere-based method was the most robust approach for evaluation of bioavailability of heavy metals in soils to wheat.     

Uptake of PAHs by cabbage root and leaf in vegetable plots near a large coking manufacturer and associations with PAHs in cabbage core

Samples of ambient air (including gaseous and particulate phases), dust fall, surface soil, rhizosphere soil, core (edible part), outer leaf, and root of cabbage from eight vegetable plots near a large coking manufacturer were collected during the harvest period. Concentrations, compositions, and distributions of parent PAHs in different samples were determined. Our results indicated that most of the parent PAHs in air occurred in the gaseous phase, dominated by low molecular weight (LMW) species with two to three rings. Specific isomeric ratios and principal component analysis were employed to preliminarily identify the local sources of parent PAHs emitted. The main emission sources of parent PAHs could be apportioned as a mixture of coal combustion, coking production, and traffic tailing gas. PAH components with two to four rings were prevailing in dust fall, surface soil, and rhizosphere soil. Concentrations of PAHs in surface soil exhibited a significant positive correlation with topsoil TOC fractions. Compositional profiles in outer leaf and core of cabbage, dominated by LMW species, were similar to those in the local air. Overall, the order of parent PAH concentration in cabbage was outer leaf > root > core. Partial correlation analysis and multivariate linear stepwise regression revealed that PAH concentrations in cabbage core were closely associated with PAHs present both in root and in outer leaf, namely, affected by adsorption, then absorption, and translocation of PAHs from rhizosphere soil and ambient air, respectively.     

Regression models to predict water-soil heavy metals partition coefficients in risk assessment studies

Risk assessment studies apply fate and transport models to predict the behaviour of chemicals in the environment. The definition of physico-chemical properties is crucial to predict the mobility of pollutants and heavy metals in particular within the environmental compartments. The conservative approach normally adopted at a screening level in attributing a value to the K(d) value, results in an extremely variable mobility in soil. In this paper a regression model to estimate rapidly the K(d) for heavy metals is proposed and applied to Pb, allowing a considerable reduction (3-4 orders of magnitude) of the estimation uncertainty. The application of a stepwise forward multiple regression to literature data provided a pH-dependent regression equation of the soil-water distribution coefficient (K(d)) for Pb: log K(d)=1.99+0.42 pH.     

An Empirical Model for Forecasting Maximum Daily Ozone Levels in the Northeastern U.S.

A stepwise multiple regression procedure was employed to develop the best .fit equation relating maximum afternoon ozone concentrations to meteorological and emission factors along a 24h upwind air parcel trajectory. The equation was developed using ozone data from receptor sites in Northern New Jersey and the resulting correlation coefficient was 0.96. The four most significant variables were the upwind ozone maximum on the previous day, today’s maximum temperature, the previous day’s upwind maximum temperature and the mean wind speed from the surface to 1000 m. The model was also successfully tested at 5 other sites in the Northeastern Quadrant of the United States. The results indicate that the model could be a potentially useful tool for air pollution forecasters in predicting maximum ozone concentrations in this quadrant of the country.     

人工湿地构筑根孔作用下土壤物质分布状况

嘉兴市石臼漾湿地应用人工构筑根孔技术,以玉米秸秆和油菜秸秆按比例混合埋植于土壤亚表层,作为湿地的基质/填料。在湿地运行一年半后,按照正交设计表,以埋植秸秆的种类(S)、填埋的土壤层次(L)、距离秸秆外环的远近(D)和秸秆周围土壤的表观颜色(C)作为实验因素,对秸秆周围养分物质浓度、土壤酶活性以及铁含量进行采样分析。实验结果显示:玉米秸秆和油菜秸秆腐烂较充分,分别形成较发达的粗根孔和细根孔;根孔周围土壤呈中度还原状态;粗根孔具有较强的优先流效应,其周围土壤具有较高的养分物质含量和较低的Fe2+/Fe3+比。粗根孔周围土壤具有较高的磷酸酶活性,而细根孔周围具有较高的β-葡糖苷酶活性和脲酶活性。综合比较,人工湿地构建初期,径级较大秸秆腐烂后形成的粗根孔发挥着更高的水分传导效率和更强的物质截留效应。     

A comparison of the rhizosphere-based method with DTPA, EDTA, CaCl2, and NaNO3 extraction methods for prediction of bioavailability of metals in soil to barley

A rhizosphere-based method was compared with DTPA, EDTA, CaCl2, and NaNO3 extraction methods for the evaluation of bioavailability of heavy metals in soil to barley. The extractable amounts of Cr, Cu, Zn and Cd analyzed by the rhizosphere-based method correlated significantly with the metal content of barley roots. The extractable metals identified by DTPA, EDTA, CaCl2 and NaNO3 methods exhibited relatively poor or no correlation with the metal content of barley roots. The stepwise multiple regression equation of the rhizosphere-based method was the simplest one, as no soil properties needed to be entered, whereas the equations for the DTPA, EDTA, CaCl2 and NaNO3 extraction methods always require those variables. The most distinct feature of the rhizosphere-based method was that the proposed method was suitable for acidic, neutral and near alkaline soils. In contrast, the other extraction methods were restricted to soil types. In summary, the rhizosphere-based method is the most robust approach for evaluation of bioavailability of metals in soil to barley.     

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: influence of matrix porosity, matrix permeability, and fracture coating minerals

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ((3)HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient (D(m)/D*). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of (D(m)/D*) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log(D(m)/D*) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log(D(m)/D*) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.     

Copper uptake by Elsholtzia splendens and Silene vulgaris and assessment of copper phytoavailability in contaminated soils

Tolerance and metal uptake are two essential characteristics required for phytoextraction of metals from contaminated soils. We compared tolerance and Cu uptake of Elsholtzia splendens (reported previously to be a Cu hyperaccumulator) with Silene vulgaris (the Imsbach population, a well-known Cu-tolerant excluder species), using 30 soils varying widely in total Cu concentration (19-8645 mg kg(-1)). We further investigated the effectiveness of different soil testing methods for predicting plant metal uptake. The results showed that both Elsholtzia splendens and Silene vulgaris were tolerant to Cu, especially Silene vulgaris. However, Elsholtzia splendens did not hyperaccumulate Cu, but behaved as a typical Cu excluder like Silene vulgaris. The concentrations of Cu in both plants correlated more closely with 1 M NH4NO3 extractable Cu, soil solution Cu, or effective Cu concentration determined using DGT, than with soil total Cu, EDTA extractable Cu or free Cu2+ activity. The relationships between soil solution properties and root Cu concentrations were further investigated using multiple regression. The results showed that increasing soil solution pH increased root Cu concentration when free Cu2+ activity was held constant, suggesting a higher phytoavailability of free Cu2+ at a higher pH. Soil solution DOC appeared to play two contrasting roles on the phytoavailability of Cu: (1) reducing Cu availability by complexing Cu; and (2) increasing Cu availability at the same level of free Cu2+ activity by providing a strong buffer for free Cu2+. The results are consistent with the intensity/capacity concept for phytoavailability of metals in soils.     

Cadmium availability to wheat grain in soils treated with sewage sludge or metal salts

Grain Cd concentrations were determined in wheat (Triticum aestivum L.) grown in 1999, 2001 and 2003, at six sludge cake field experiments. Three of these sites also had comparisons with Cd availability from metal amended liquid sludge and metal salts. Grain Cd concentrations in all years and at all sites were significantly linearly correlated with NH4NO3 extractable Cd and soil total Cd (P<0.001). Soil extractability was greater in the liquid sludge and metal salt experiments than in the cake experiments, as were grain Cd concentrations. Across all the sites, NH4NO3 extractable soil Cd was no better at predicting grain Cd than soil total Cd. Stepwise multiple linear regression analysis showed that soil total Cd, pH and organic carbon were the only significant (P<0.001) variables influencing wheat grain Cd concentrations, explaining 78% of the variance across all field experiments (1408 plots). This regression predicted that the current UK soil total Cd limit of 3 mg kg(-1) was not sufficiently protective against producing grain above the European Union (EU) grain Cd Maximum Permissible Concentration (MPC) of 0.235 mg Cd kg(-1) dry weight, unless the soil pH was > 6.8. Our predictions show that grain would be below the MPC with > 95% confidence with the proposed new EU draft regulations permitting maximum total Cd concentrations in soils receiving sludge of 0.5 mg kg(-1) for soils of pH 5-6, 1 mg kg(-1) for soils of pH 6-7, and 1.5 mg kg(-1) for soils of pH > or = 7.