微波消解/ICP-MS法测定粮食中的18种痕量元素

对小麦、大米、玉米等粮食中铍、锌、砷等18种痕量元素,建立了微波消解/ICP-MS测试分析方法.讨论了粮食样品制备粒径与微波消解样品称样量、加酸类型和消解过程;同时结合理论、实验及样品特点,各元素质量数、分析模式、内标元素的选择,以降低质谱干扰和非质谱干扰.结果表明,该分析方法具有较好的准确度和精密度,适合粮食样品批量、快速消解和分析.     

佛山农业表层土壤磁化率特征及其与重金属含量的关系

环境磁学方法针对城市、矿区、工业区等特定区域土壤的研究现已比较普遍,但在农业土壤重金属研究中的应用还比较少。本文对采自佛山市的532件农业表层土壤样品进行低频（976 Hz）和高频（15616 Hz）磁化率测试,在分析其空间分布特征的基础上选取175件（其中,旱地土样149件,水田土样26件）代表性样品进行重金属（Cd、Pb、Cr、Cu、Ni、Zn、Hg、As）含量的分析测试。在分析不同土壤样品磁化率与重金属含量之间相关关系的基础上,从旱地和水田土壤中分别挑选出6种与低频磁化率高度相关的重金属元素（旱地Ni、Cu、Cr、Zn、Cd、Pb,相关系数分别为0.599、0.492、0.279、0.510、0.445、0.225;水田Ni、Cu、Cr、Zn、Cd、Hg,相关系数分别为0.728、0.699、0.606、0.602、0.764、0.450）进行回归分析,列出回归方程,并得到一些初步认识。主要有（1）低频磁化率与频率磁化率在空间分布上总体呈现相反趋势;（2）重金属含量与低频磁化率总体呈正相关,但正相关的元素种类在旱地和水田土壤中有所差异;（3）所研究的旱地土壤重金属含量与频率磁化率呈负相关关系,但这种相关关系在水田土壤中没有明显表现;（4）Pb 元素在旱地土壤中与低频磁化率表现出显著正相关（P〈0.01）,在水田土壤中却与低频磁化率和频率磁化率表现出一定的负相关性。（5）通过测定农业土壤的磁化率即可初步推算出相应的重金属含量,为磁学方法在农业表层土壤重金属快速监测领域的进一步应用提供了数据支持和科学依据。     

干法灰化和微波消解-火焰原子吸收法测定铅锌冶炼厂废旧除尘布袋中重金属

采用干法灰化和微波消解两种样品分解方法处理广东省某铅锌冶炼厂布袋试样,用火焰原子吸收光谱法测定样品中Cu、Zn、Pb、Cr、Ni、Cd 6种重金属元素含量.同时用两种前处理方法对国家一级标准物质进行测定,与标准值比对,验证两种方法的准确度和精密度.结果表明,不同的样品分解方法对各重金属元素的测定结果会产生不同程度的影响.微波消解法相对于干法灰化法的准确度高,试剂利用率高,有利于元素的分析.干法灰化和微波消解两种前处理方法的精密度（RSD,n=11）均小于5%.     

环境样品的X射线荧光分析

本文主要介绍大气、水体、土壤和生物样品的X射线荧光分析,并讨论气溶胶样品的采集、薄膜标准的制备、水样的预富集方法,如共沉淀、离子交换、萃取和蒸发,土壤及沉积物的粉末压片、熔融、化学处理等制样方法,以及生物样品中痕量元素的分析。     

新疆东天山某铜矿区土壤重金属污染与生态风险评价

选取戈壁荒漠景观生态环境脆弱区典型铜矿区为研究区,采集308个表层土壤样品,对Cu、Ni、Cd、Cr、Pb、Zn、Hg、As等8种重金属元素进行测试分析,综合运用相关性分析、主成分分析和系统聚类等多元统计和地统计学方法分析了矿区土壤重金属的空间分布特征,运用地累积指数法和潜在生态风险评价法评价了重金属累积程度和潜在生态风险危害程度,并对重金属的可能来源进行了解析.结果表明,研究区表层土壤重金属中Cu、Ni累积程度相对较高,超背景值比例分别为17.53%、14.94%.重金属地质累积程度由强至弱依次为:CuZnCrNiHgPbAsCd;0.65%的土壤样品中Pb属重度污染水平,2.92%土壤样品中Cu属重度污染水平.98.38%的土壤样品重金属污染潜在生态风险危害较轻,重金属迁移影响范围有限.重金属Cu、Ni为主要特征污染物,来源于成土母岩风化和矿业活动共同作用;As、Hg、Cd元素污染程度较低,受人为因素影响较小;Pb元素污染呈点状分布,来源主要为矿区交通运输.     

城市工业用煤X荧光分析及重金属元素污染研究

燃煤是成都市重金属污染的一个重要来源,目前对成都燃煤中重金属元素含量与城市环境污染的相关性研究相对较少。文章以成都市城东工业区为研究对象,利用X荧光分析方法对煤样、煤渣、煤灰、表层土、深层土4种重金属元素进行定量分析,探讨了燃煤中重金属含量与城市土壤重金属污染的相关关系。结果表明,(1)成都市工业用煤原产地煤样重金属元素的含量不尽相同,因此,企业需合理选择煤源。(2)土壤重金属元素污染与工业用煤正相关,工业用煤中有害元素含量较高的对当地土壤的污染也比较严重,相反工业用煤中含量较少的元素在土壤中含量也较小。(3)热电厂燃煤对城市重金属污染的行为属性表现为,Pb属于直接污染大气和土壤,而Cu、Zn、Cr富集在煤渣样、煤灰样中在后期造成对城市土壤的污染。     

发电厂周边土壤重金属空间分布及在土壤-水稻系统中的迁移

赋存于煤炭中的重金属元素,在火电厂经燃烧分解氧化,通过各种途径进入大气环境,并通过大气干沉降和湿沉降进入土壤,从而影响土壤环境质量。以韶关发电厂周边土壤-水稻系统中重金属元素As、Cd、Cr、Cu、Hg、Ni、Pb和Zn的含量为主要研究目标,采集发电厂周边的99对土壤和相应的水稻样品,选择三处典型样点采集垂直剖面土壤样品,并在远离污染源、不受电厂主风向影响和不曾受到其他明显外来污染的地区采集6对土壤-水稻样品,系统地探讨电厂周边农田土壤重金属元素的空间分布特征,采用污染指数评价模型与健康风险评估模型,评价韶关电厂周边耕地土壤和水稻重金属污染状况,分析当地居民摄入本地谷类产品的健康风险。结果表明,(1)各种重金属的含量在电厂附近达到最高值,随着与电厂距离的增加,土壤中重金属含量逐渐下降,表明该电厂燃煤过程产生的污染是当地土壤环境重金属元素的升高的主要原因。(2)8种重金属元素具有相似的空间分异趋势,在表层0-20cm的范围内富集,且含量随深度增加呈下降趋势。(3)水稻田表层土壤中的Cd超过了国家标准限值,Cd污染突出。As、Cr、Cu、Hg、Ni、Pb和Zn的平均含量也分别超过相应的广东省土壤元素的背景值。(4)水稻籽粒中的Cd和Pb均超过了国家标准限值,Cd污染也尤为突出。居民食用本地稻米产品引起重金属的健康暴露风险极大,尤以Cd最为显著。该研究可以为当地环境风险管理和决策提供科学依据。     

南太行山山前平原工业园区土壤重金属污染特征及来源

为了探究工业园区土壤中重金属污染特征和来源,分析了南太行山山前平原某工业园区22个表层土壤样品以及2个区域背景土壤样品.测试土壤微量重金属元素含量以及土壤总碳(TC)、总氮(TN)和总硫(TS)含量,借助主成分分析讨论元素相关关系,利用聚类分析方法讨论受污染土壤的空间分布特征.结果表明:(1)区内22个土壤中Cu、Zn、Pb、Ni、Cr、Co、V和Sr等8种重金属含量平均值分别为85.05、161.32、39.51、42.57、90.80、13.79、117.56、173.23 mg·kg~(-1),是河南省土壤背景值的4.3倍、2.6倍、1.8倍、1.5倍、1.4倍、1.2倍、1倍和0.96倍.(2)区内22个土壤中TC、TN和TS的范围分别为2.19%—6.32%、0.12%—0.21%和0.03%—0.22%,均值分别为3.17%、0.17%和0.10%.区内Co、Ni、V和Cr等重金属元素含量较高的土壤主要分布在区内西南部,来源包括粉煤灰堆放场扬尘、企业燃煤排放废气等.Cu、Pb和Zn等重金属元素含量较高的土壤主要分布在区内中西部,来源包括化工厂、冶炼厂排放废气和粉尘等.土壤重金属Sr来自成土母岩中碳酸盐岩.其余土壤重金属元素受成土母质和工业废气、化学肥料等共同影响.     

X射线荧光光谱测定土壤和水系沉积物中的主元素和痕量元素

采用X射线荧光法分析土壤和沉积物中22种元素含量,以水系沉积物标样(GSD)做为标准样品,回归方法求取各元素的工作曲线常数,元素间效应的影响系数和谱线重叠校正系数,散射内标法和经验系数法共同校正基体效应。用本方法分析了西藏土壤标准参考物(83401)和水系沉积物标准(81101)中的多种元素,结果与标准值或参考值一致。方法简便、快速、有较好的检出下限和准确度。     

衡阳市大羽藓植物及其基质重金属元素含量分析

通过分析衡阳市7个样点的大羽藓植物体及相应土壤样品中的Pb、Zn、Cu、Cd、Hg、As等6种重金属元素含量,大羽藓植物体内6种重金属元素平均含量分别为:40.86 mg/kg、339.27 mg/kg、19.54 mg/kg、0.32 mg/kg、0.27 mg/kg、4.77 mg/kg,基质中重金属元素平均含量分别为:48.32 mg/kg、160.40 mg/kg、22.35 mg/kg、0.21 mg/kg、0.38 mg/kg、11.62 mg/kg,均未超过国家标准2级标准.富集系数分析表明,大羽藓对Zn和Cd具有富集能力,富集系数分别为:2.12和1.52.植物体和土壤基质中重金属含量的相关性分析表明,除Pb外其它5种重金属都达到显著性差异水平(P0.05).     

ASD—ICP—MS联合快速测定土壤中部分金属元素

土壤环境质量例行监测正在全国展开,如何准确快速分析土壤中的金属含量成为当务之急。采用HNO3-HCl-HF—HClO4体系在全自动消解仪（ASD）上对土壤进行前处理,以50．0μg／L的铑作内标,电感耦合等离子体-质谱仪同时测定《土壤环境质量标准》的7种元素：Cd、As、Cu、Ph、Cr、Zn、Ni。各元素的方法检出限为0．003～0．40mg／kg,相对标准偏差小于6．0％,土壤标样的测定值与标准值吻合。该方法简便快捷、灵敏度高、重现性好,为大批量土壤重金属元素含量的快速测定提供了可靠地消解-分析方法。     

大气颗粒物样品中主量和痕量元素的直接测定

采用一种新的标样制备方法,用波长色散X射线荧光光谱直接定量分析由微孔滤膜抽滤所吸附和收集的大气颗粒物中主量和痕量无机元素.具有快速、简便、准确和经济等特点.     

Sequentielle Schwermetallextraktion aus Staubniederschlägen und Straßensedimenten

For the application of sequential extraction of heavy metals from samples that can only be obtained in amounts of a few milligrams (micro samples, e.g. airborne dust fallout), the method afterZeien &Brümmer (1989) was progressed. A down scale to 1∶100 was carried out and the accuracy of this method with variable sample amounts of about 20 mg and an extraction volume of 500 μl was proofed with standard soil samples. The influence of variable extraction ratios (ratio of sample amount and volume of extraction solvent) and the influence of intensive treatment of dust sampled by the Bergerhoff-method (VDI 2119/2, 1972) prior sequential extraction, was within the precision of measurement of our method. Thus, we showed that sequential extraction can be applied for the investigation of heavy metal mobilization in micro samples with variable sample amounts. A first application of our method for microsamples was carried out to investigate airborne dust fallout and street sediments at two urban sites where different heavy metal immission rates due to traffic influence occur. These investigations will be presented in part 2 (“Sequential extraction of heavy metals from urban dust”).     

Improved sample preparation and GC–MS analysis of priority organic pollutants

Mass spectrometry is a major tool for analysing organic pollutants. However, scientists often complain about laborious sample preparation. The development of new commercial high-resolution mass spectrometers gives a chance to improve simultaneously speed, reliability, and sensitivity of the analysis. Here, we used the time-of-flight high-resolution mass spectrometer Pegasus GC-HRT to identify and quantify 55 priority organic pollutants in water samples. This mass spectrometer has a high resolution of 50,000, a high mass accuracy of about 1 ppm and a very high acquisition rate of up to 200 full mass range spectra per second. 1 mL water samples were extracted with 1 mL dichloromethane. Results show that the sample preparation and analysis are achieved 30 times faster, requiring 1,000 times less water and 350 times less solvent than the classic 8270 method of the United States Environmental Protection Agency. The detection limit is 1 μg/L. The quantification limit is 10 μg/L. Our procedure, named accelerated water sample preparation, is simpler, faster, cheaper, safer and more reliable than 8270 Method.     

北京市典型有机设施蔬菜基地重金属污染特征及风险评估

为研究北京市典型有机设施蔬菜基地重金属污染状况,采用野外调查及室内分析法,选取北京市5个有机设施蔬菜基地中125个土壤样品和77个蔬菜样品进行了Pb、Cd、Cr、As和Hg含量的检测、统计分析与评价,对土壤重金属含量与土壤理化指标进行了相关分析,研究了重金属在蔬菜中的迁移规律,并结合美国环保署(US EPA)推荐采用的健康风险评价模型,评价由于蔬菜摄入导致的成人和儿童的健康风险。结果表明,5个设施蔬菜基地中有极少数土壤样本Cd含量超标,有极少数叶菜样本Cr含量超标,其他重金属含量均未超标。污染指数评价表明5个基地土壤重金属污染排序为:基地5基地1基地3基地2基地4,主要由土壤Cd累积所致。土壤重金属与理化性质相关性表明,5种重金属含量都受土壤的理化性质影响较大。总体上,5种重金属在土壤-蔬菜中迁移能力排序为:CdHgAsCrPb,在不同类蔬菜中的富集系数排序为:叶菜类茄果类瓜果类豆菜类。5种重金属造成的目标危害系数大小依次为:CdPbAsHgCr,不同类蔬菜的综合重金属目标危害系数值排序为:叶菜类茄果类瓜果类豆菜类,所有蔬菜单一重金属目标危害系数和复合危害系数都远小于1,说明单一重金属和复合重金属污染对成人和儿童都没有明显的负面健康影响。     

基于高光谱技术的土壤镉污染分级评价研究

提出一种利用高光谱技术进行土壤镉污染分级评价的方法。以FieldSpec 3地物光谱仪采集厂矿区土壤光谱反射率175份,随机分成校正集（135份）和检验集（40份）。光谱经小波去噪和标准归一化（SNV）处理后,以主成分分析法（PCA）降维。将降维所得的前5个主成分数据为输入变量,分别采用Fisher线性判别、Byes逐步判别、模糊模式识别、BP-ANN判别以及SVM 5种方法建立了土壤镉污染分级评价模型,并利用40个未知样对模型进行检验。结果表明：Fisher线性判别准确率为77.5%,Byes逐步判别与模糊模式识别预测为80.0%,BP-ANN模型预测精度为82.5%,SVM模型预测精度最高,达85.0%。说明采用高光谱技术进行土壤镉污染分级评价是可行,其中SVM是建模的优选算法。     

An evaluation of heavy metals contamination in soils from Ganzhou navel orange orchards by geoaccumulation indexes and statistical analysis

Heavy metal pollution in orchard soils is of increasing concern owing to the potential health risk via the food chain. The evaluations of the degree of heavy metal contamination and the potential sources in soils from navel orange orchards in the Ganzhou district were investigated in the present study with the geoaccumulation index and hierarchical cluster analysis. The soil samples were collected from 280 navel orange orchards located in the 18 counties of the Ganzhou district. The concentrations of heavy metals in the samples were determined using atomic fluorescence spectrometry and inductively coupled plasma atomic emission spectrometry with sample preparation by microwave digestion system. The results of the geoaccumulation index showed that the Ganzhou navel orange orchards were practically uncontaminated with Hg, As, Pb, Cd, Cr, Zn, and Cu, while uncontaminated to moderately contaminated with Ni. The results of cluster analysis indicated that four distinct clusters emerged for 18 sampling counties, and the considerable differences between clusters were derived from the different kinds of polluted substances. Results of the assessment of geoaccumulation index of heavy metals in soils will be helpful for the formulation of strategic sustainable agriculture in Ganzhou navel orchards and improvement of the navel orange yield and quality.     

Ecotoxicological testing of soil by four bacterial biotests

The objective of this work was threefold. Firstly, this paper intends to introduce four microbial toxicity screening methods (Bacillus subtilis agar diffusion method, Azotobacter agile and Pseudomonas fluorescens dehydrogenase enzyme inhibition tube test, and Photobacterium phosphoreum contact toxicity test) for the investigation of contaminated solid samples such as soil and sediment. Secondly, this work was carried out to prove that both soil characteristics and chemical form of contaminants influence the bioavailability of contaminants and alter the toxicity of soil sample considerably. Thirdly, the sensitivity of the above mentioned four biotests to different contaminants of the soil (heavy metals, organic compounds) was determined and compared. The data evaluation was processed by computer aided statistical methods such as cluster, correlation and principal components analysis by the use of Statgraphics^R.

According to cluster analysis carried out separately for chemical data and biological data, we observed that those samples that have similar chemical composition do not show similar toxicity, which is probably due to different bioavailability of contaminants, the impacts of soil characteristics as well as interaction of contaminants. According to the investigation of sensitivity of the examined four biotests the following conclusion could be drawn: P. phosphoreum and A. agile tests are similar in the sense that they are sensitive to Cu to a large extent and also to PAHs and hydrocarbons (CH) to a lesser extent. B. subtilis test corresponds well with P. fluorescens test method since both tests give good correlation with heavy metals. Neither B. subtilis nor P.fluorescens biotests are sensitive to organic soil contaminants such as PAH and CH.     

Modified pretreatment method for total microbial DNA extraction from contaminated river sediment

Extraction of high-quality microbial DNA from contaminated environmental samples is an essential step in microbial ecological study. Based on previously published methods for soil and sediment samples, a modified pretreatment method was developed for extracting microbial DNA from heavily contaminated river sediment samples via selection of optimal pretreatment parameters (i.e., reagent solution, reaction duration, and temperature). The pretreatment procedure involves washing the river sediment sample for three times with a solution containing 0.1 mol·L^-1 ethylene diamine tetraacetic acid (EDTA), 0.1 mol·L^-1 Tris (pH 8.0), 1.5 mol·L^-1 NaCl, 0.1 mol·L^-1 NaH₂PO₄, and Na₂HPO₄ at 65°C with 180 r·min^-1 for 15 min to remove humic materials and heavy metals prior to the employment of standard DNA extraction procedures. We compared the results of standard procedure DNA extraction following pretreatment, without pretreatment, and with using a commercial PowerSoil^TM DNA Isolation Kit. The results indicated that the pretreatment significantly improved the DNA quality based on DNA yield, DNA fragment length, and determination of prokaryotic diversity. Prokaryotic diversity exhibited in the DNA with the pretreatment was also considerably higher than that extracted with the PowerSoil^TM DNA Isolation Kit only. The pretreatment method worked well even with a small amount of sediment sample (0.25 g or even lower). The method provides a novel, simple, cost-effective tool for DNA extraction for microbial community analysis in environmental monitoring and remediation processes.     

Evaluation of genotoxic potential of industrial waste contaminated soil extracts of Amritsar, India

The rapid increase in population together with unplanned disposal of effluents from various industries has resulted in accumulation of various heavy metals like As, Cr, Cu, Hg, Ni, Pb and Zn in soil ecosystem which ultimately causes DNA damage in living systems. Considering this, the present study was designed to evaluate the content of various heavy metals (Cu, Cr, Co, Hg, Mn, Ni, Zn) and genotoxicity/mutagenicity of soil samples collected from the outskirts of two industries viz. zinc coating industry (SI) and copper sulphate manufacturing industry (SII) employing Allium root anaphase aberration assay (A/RAAA) and Ames assay. The physicochemical parameters like bulk density, water holding capacity, moisture content, pH, nitrates, phosphates and potassium were also estimated. It was observed that SI sample contained Ni (6.86 mg g-1), Zn (6.53 mg g-1), Co (5.05 mg g-1) and Cr (4.49 mg g-1), while SII contained Cu (32.86 mg g-1), Ni (9.66 mg g-1), Co (6.85 mg g-1) and Zn (5.41 mg g-1). In A/RAA assay, the percentage of cells with anaphase aberrations ranged from 3.63 to 10.67 and 0.38 to 4.83% for samples SI and SII, respectively. In Ames test, sample SII was found to be lethal to Salmonella tester strains at all concentrations used, while sample SI was found to be mutagenic in TA100 strains of Salmonella typhimurium. Sample SII was found to be strongly acidic with pH 3.46. The present study focuses on the increasing heavy metal pollution in Amritsar city due to industrial discharges over lands and also infers that both bioassays Ames and A/RAAA can serve as first alert indication of pollution.