罗布泊“大耳朵”地区L07-10剖面沉积物重金属赋存形态研究

本研究以罗布泊"大耳朵"地区L07-10剖面沉积物中重金属Cu、Ni、Mn为研究对象,研究了重金属Cu、Ni、Mn的赋存形态,结果显示:Cu以残渣态和有机物结合态为主,可交换态和碳酸盐结合态较少;Ni以残渣态存在的比例较高,可交换态和有机物结合态含量较小;Mn以铁锰氧化物结合态和残渣态为主,可交换态和有机物结合态含量较少。重金属Cu、Ni和Mn的赋存形态在该剖面垂直方向上大部分呈波折多峰分布,其赋存形态与有机质也存在一定的相关性,但相关性有所不同。研究结果揭示了这3种重金属在罗布泊"大耳朵"地区L07-10剖面沉积物中赋存形态的分布规律,研究结果可为罗布泊干盐湖区重金属相关研究补充基础数据。     

粤北上坝村稻田土壤及间隙水中重金属污染研究

利用Tessier连续提取法对粤北上坝村稻田土壤中重金属化学形态分布特征进行研究,同时调查稻田间隙水中重金属的污染状况。结果表明,研究区域稻田土壤中Cu超标严重,主要以稳定态的形式存在,环境迁移量相对较少;土壤中Zn的生物有效性最低,Cd污染达到中等水平,其生物有效性最高;可交换态Mn,碳酸盐结合态Cd及铁锰氧化物结合态的Mn、Pb、Zn的占比较高,对农业生产环境具有一定的潜在威胁。稻田间隙水中Cd含量超标1.8倍。     

长江下游沉积物中重金属污染现状与特征

对长江下游沉积物中的重金属Co、Cr、Cu、Ni、Pb、Zn、Mn、Hg和As进行全量和醋酸提取态(包括水溶态、可交换态和碳酸盐结合态)分析.结果表明,大部分重金属主要来源于地壳元素的自然释放,但Cu、Zn、Hg和As在最近十几年因受到人为排放的影响质量比有所增加.长江江苏段的重金属质量比普遍高于入海口上海段;位于悬浮物易沉降地区的靖江重金属质量比明显偏高.Cu和Zn总体质量比较高,且醋酸提取态所占比例较大,对长江下游存在潜在的生态风险.     

钻井废泥浆中重金属化学形态及潜在生态效应评价

利用化学萃取法对江苏9个油田的不同类型钻井废泥浆的重金属化学形态分布特征进行调查分析,同时选用Hakanson的潜在生态危害指数法对钻井废泥浆中的重金属总量进行生态效应评价。结果表明,钻井废泥浆中Cu、Pb、Zn、Cd、Cr主要以残渣态和有机结合态为主,活性形态含量较低;采用Hakanson的潜在生态危害指数进行评价,发现Cu、Pb、Zn、Cd都属于轻微生态危害水平,而Cr多属于中等水平,产生潜在生态危害的重金属主要为Cr。     

微波消解法测定铅锌冶炼厂废旧除尘布袋及其飞灰中重金属的应用研究

以广东某铅锌冶炼厂的废旧除尘布袋及其布袋上的飞灰为实验材料,以HNO3-H2O2-HF对布袋及飞灰进行微波全量消解,采用BCR三步浸提法提取飞灰中Cu、Zn、Pb、Cr、Ni、Cd 6种重金属,并利用火焰原子吸收仪器检测布袋及飞灰中6种重金属的含量及飞灰中各形态含量。结果表明,铅锌冶炼厂废旧布袋和飞灰中重金属含量较高,远大于《国家土壤环境质量标准》(GB 15168—1995)三级标准值。不同重金属在飞灰中的形态分布差异较大,Ni主要以残渣态和酸可交换态为主,Cu和Pb以残渣态为主,Zn的4种形态分布都较均匀,Cd、Zn潜在的迁移性最强。     

湘江(株洲段)沉积物重金属污染现状及生态风险评价

采集湘江(株洲段)9个断面的底泥样品,和1个柱状样品,对重金属(Cu、Pb、Zn、Cd、Ni、Cr、Hg、As)含量进行了检测;并运用地质积累指数法对底泥中重金属进行了生态风险评价.结果表明,该江段底泥已受到较严重的重金属污染,在霞湾断面达峰值.Cu、Pb、Zn、Cd含量为湘江背景值4.6倍~58.8倍,比该江段20世...     

钼矿区周边农田土壤中重金属污染状况的分析与评价

对钼矿区周边农田土壤重金属污染情况进行了详细研究.选择该矿区受污染农田土壤样本80个,采用HNO3-HF-HClO4混酸对土壤样品进行处理,运用欧共体参比司推荐的BCR三步连续提取法进行化学形态分析;使用等离子体发射光谱仪(ICP-AES)测定土壤样品中Mo、Pb、As、Hg、Cr、Cd、Zn、Cu、Ni的全量及各种化学形态的含量并进行评价,同时对矿区地下水进行分析;采用spas软件进行数据分析.结果表明,矿山周边农田土壤重金属主要污染物为Cd、Hg并伴有Cr污染;Nemerow综合指数6.81,综合评价结果为该区土壤已受严重污染;Cd与As污染来源基本相同,Cu、Ni、Zn污染来源基本相同,Hg有独立的污染来源;重金属中化学形态分布为残余态>有机结合态>氧化结合态>酸可提取态;重金属Cr及Hg的有效态比例较大,可能会影响农作物的正常生长;矿山周边农田土壤重金属污染的原因可能是污染地下水的浇灌,矿石的开采、运输和大气降尘等过程;有机农药及塑料农用制品的施用过程,自然成土、矿物的伴生及其转化等过程.     

南京市大气PM2.5中重金属分布特征及化学形态分析

于2017年1、4、7、10月在南京市主城区采集了大气PM2.5样品,用BCR法对PM_(2.5)中重金属进行连续提取,采用电感耦合等离子体-质谱法进行测定,分析重金属在颗粒物中不同形态和分布特征。结果表明,PM_(2.5)中9种重金属质量比排序为:Fe Zn Pb Mn Cu Cr As Ni Cd。Zn、Pb、Cd、Cu、Mn、As主要分布在弱酸提取态; Ni在弱酸提取态、可氧化态和残渣态中分布较均匀,占比26%～37%;而Fe、Cr主要以残渣态存在,分布比例分别为71%和54%。PM_(2.5)中Zn的生物有效性系数 0.8,属生物可利用性元素,表明其在环境中迁移能力最强,其余8种重金属生物有效性系数为0.2～0.8。     

内蒙古畜禽养殖场周边土壤重金属污染特征及评价

于2015年5—8月采集内蒙古自治区东部、中部和西部地区32个畜禽养殖场周边共160个土壤样品,分析8种重金属含量。通过单项污染指数法和内梅罗综合污染指数法评价畜禽养殖场周边土壤重金属的污染程度,主成分分析重金属污染的成因和来源。结果表明,除Hg和As外,Cd、Pb、Cr、Cu、Zn和Ni 6种重金属的平均值均高于内蒙古自治区土壤背景值,其中Cd是背景值的2. 14倍。单项污染指数评价表明,重金属Cd在东部畜禽养殖场周边土壤中呈中度污染,在中部和西部地区畜禽养殖场周边土壤中呈轻度污染。不同重金属元素平均污染程度为:Cd Pb Cr(Ni) Zn Cu As Hg。内梅罗综合污染指数评价表明,东部地区畜禽养殖场周边土壤污染最严重,为中度污染,中部和西部地区畜禽养殖场周边土壤均为轻度污染。不同地区畜禽养殖场周边土壤重金属内梅罗综合污染指数大小顺序为:东部地区(2. 27)西部地区(1. 52)中部地区(1. 35)。主成分分析结果显示,内蒙古不同地区畜禽养殖场周边土壤不同重金属的来源存在差异,其中Pb、Cr、Cu、Zn和Ni主要来源于畜禽粪便和冲洗禽舍等污水的不当排放; Hg主要来源于自然源。     

铅锌尾矿库周边土壤重金属污染特征及环境风险

以尾矿库周边土壤为研究对象,用改进BCR法探讨Zn、Pb、Ni、Cu、Cr形态特征,用污染因子Cf和风险评价代码RAC评估环境风险。结果表明:Pb污染最重,总量是区域背景值的2倍多,污染剖面各重金属总量垂向分布均匀,污染已扩散至1 m深;5种金属均主要以残渣态存在,有效态、可交换态Pb质量占比均高于其他4种金属,与表层土壤相比,中、下层污染剖面各金属以更稳定的形态存在;Zn、Ni、Cu、Cr在表层或污染剖面土壤均存在低风险,部分点位Pb存在中度风险。     

太原市大气颗粒物中重金属的污染特征及来源解析

为了解太原市采暖期大气颗粒物不同粒径中重金属的污染特征及其来源,于2012年10月—2013年2月对环境空气中颗粒物采样,用原子吸收分光光度法测定样品中Fe、Pb、Cu、Ni、Cr、Cd、Mn、Zn等8种元素的含量。结果表明,太原市采暖期重金属浓度从高到低依次为FePbMnZnCrCuNiCd。重金属Pb、Mn、Zn、Ni、Cd主要富集在PM2.5中;Cr主要富集在PM10中;Cu主要富集在PM5中;Fe主要在粒径大于2.5μm的粗粒子中富集。除Zn外,其他7种元素浓度均表现为灰霾期采暖期采暖前。通过主因子分析表明,太原市大气颗粒物中重金属主要来源于冶金、有机合成工业、燃煤、汽车尾气、土壤尘等。     

Speciation and ecological risk of heavy metals in intertidal sediments of Quanzhou Bay, China

The chemical speciation of nine heavy metals in intertidal sediments from Quanzhou Bay was determined using a modified sequential extraction procedure, proposed by the Commission of the European Community Bureau of Reference. The results show that Mn presents the highest percentage in the acid-soluble fraction, and Pb and Cu present the highest percentages in the reducible fraction. The highest percentages of Fe, V, Cr, Ni, Zn, and Co were found in the residual fraction. The mobility order of the heavy metals studied on the basis of the nonresidual content of the elements is Mn > Pb > Cu > Co > Zn > Ni > Cr > V > Fe. The assessment on potential ecological risk indices of some heavy metals indicates that Zn, Ni, and Cr show moderate contamination, while Cu and Pb show slighter contamination. On the whole, the comprehensive potential ecological risk index of Cu, Zn, Ni, Cr, and Pb in the sediments presents moderate degree.     

Spatial distribution and risk assessment of heavy metals in sediments from a hypertrophic plateau lake Dianchi, China

The sediment in Dianchi Lake, a hypereutrophic plateau lake in southwest China, was investigated and the concentration of heavy metals (Cu, Cr, Ni, Zn, Pb, Fe, Mn, and Cd) in the sediment and sediment properties were determined. Their spatial distribution and sources were analyzed using multivariate statistics. The result indicated that the studied metals exhibited three distinct spatial patterns; that is, Cu, Pb, Zn, and Ni had a similar distribution, with a concentration gradient from the north to the south part of the lake; Cd and Cr presented a similar distribution; Fe and Mn presented a quite different distribution than other metals, which indicated their different sources and geochemistry processes. Correlation and cluster analysis (CA) provided origin information on these metals and the CA result was observed corresponding to those three spatial patterns. Principal component analysis further displayed metal source and driving factors; that is, Cu, Pb, Zn, Ni, Cd, and Cr were mainly derived from anthropogenic sources, and Fe and Mn were mainly the result of natural processes. Sediment assessment was conducted using geoaccumulation index (Igeo), potential ecological risk indices, and USEPA guidelines. The result indicated that, generally, Cd was the most serious risk metal; Pb and Cu posed moderate potential ecological risk; Cr, Zn, and Ni had slight ecological risk; Fe and Mn had little risk. Comparison of the assessment tools showed that each of the methods had its limitation and could bias the result, and the combined use of the methodologies and local knowledge on lithology or metal background value of soil in the practice would give a more comprehensive understanding of the metal risk or pollution. Statistical analysis also indicated that nutrients had different impacts on Fe, Mn, and trace elements, which implied that in the assessment of metal risk, nutrients impact should be taken into consideration especially for eutrophic waters.     

Vertical distribution of heavy metals in soil profile in a seasonally waterlogging agriculture field in Eastern Ganges Basin

The accumulation of heavy metals in soil and water is a serious concern due to their persistence and toxicity. This study investigated the vertical distribution of heavy metals, possible sources and their relation with soil texture in a soil profile from seasonally waterlogged agriculture fields of Eastern Ganges basin. Fifteen samples were collected at ～0.90-m interval during drilling of 13.11 mbgl and analysed for physical parameters (moisture content and grain size parameters: sand, silt, clay ratio) and heavy metals (Fe, Mn, Cr, Cu, Pb, Zn, Co, Ni and Cd). The average metal content was in the decreasing order of Fe?>?Mn?>?Cr?>?Zn?>?Ni?>?Cu?>?Co?>?Pb?>?Cd. Vertical distribution of Fe, Mn, Zn and Ni shows more or less similar trends, and clay zone records high concentration of heavy metals. The enrichment of heavy metals in clay zone with alkaline pH strongly implies that the heavy metal distributions in the study site are effectively regulated by soil texture and reductive dissolution of Fe and Mn oxy-hydroxides. Correlation coefficient analysis indicates that most of the metals correlate with Fe, Mn and soil texture (clay and silt). Soil quality assessment was carried out using geoaccumulation index (I _geo), enrichment factor (EF) and contamination factor (CF). The enrichment factor values were ranged between 0.66 (Mn) and 2.34 (Co) for the studied metals, and the contamination factor values varied between 0.79 (Mn) and 2.55 (Co). Results suggest that the elements such as Cu and Co are categorized as moderate to moderately severe contamination, which are further confirmed by I _geo values (0.69 for Cu and 0.78 for Co). The concentration of Ni exceeded the effects-range median values, and the biological adverse effect of this metal is 87 %. The average concentration of heavy metals was compared with published data such as concentration of heavy metals in Ganga River sediments, Ganga Delta sediments and upper continental crust (UCC), which apparently revealed that heavy metals such as Fe, Mn, Cr, Pb, Zn and Cd are influenced by the dynamic nature of flood plain deposits. Agricultural practice and domestic sewage are also influenced on the heavy metal content in the study area.     

Heavy metal concentration and speciation of seven representative municipal sludges from wastewater treatment plants in Northeast China

The analysis of heavy metals is very important for assessing the feasibility of the agricultural utilization for the municipal sludge. In this paper, a four-step sequential extraction method was applied to extract heavy metals (Cu, Zn, Mn, Cr, and Ni) in municipal sludges from seven individual wastewater treatment plants located in Jilin and Heilongjiang Province, China, for estimating the mobility and bioavailability of the metal ions in the agricultural application. The total concentrations of heavy metals and their chemical fractions after the sequential extraction were determined. Principal component analysis (PCA) was applied to analyze the relations of heavy metals fractions in the municipal sludges. Experimental results indicated that the total concentrations of Cu, Zn, Cr, and Ni in all sludge samples were below the threshold values set out by the Chinese legislation (GB18918-2002). Specially, Zn had a high bioavailability and mobility, Cu and Cr had potential bioavailability, while Mn mainly existed in the residual fraction of municipal sludge. On the other hand, Ni had different mobility in different municipal sludge. PCA results were confirmed by the environmental behavior of heavy metals.     

Heavy metal speciation in solid-phase materials from a bacterial sulfate reducing bioreactor using sequential extraction procedure combined with acid volatile sulfide analysis

Heavy metal mobility, bioavailability and toxicity depends largely on the chemical form of metals and ultimately determines potential for environmental pollution. For this reason, determining the chemical form of heavy metals and metalloids, immobilized in sludges by biological mediated sulfate reduction, is important to evaluate their mobility and bioavailability. A modified Tessier sequential extraction procedure (SEP), complemented with acid volatile sulfide (AVS) and simultaneous extracted metals (SEM) measurements, were applied to determine the partitioning of five heavy metals (defined as Fe, Ni, Zn and Cu, and the metalloid As) in anoxic solid-phase material (ASM) from an anaerobic, sulfate reducing bioreactor into six operationally defined fractions. These fractions were water soluble, exchangeable, bound to carbonates (acid soluble), bound to Fe-Mn oxides (reducible), bound to organic matter and sulfides (oxidizable) and residual. It was found that the distribution of Fe, Ni, Zn, Cu and As in ASM was strongly influenced by its association with the above solid fractions. The fraction corresponding to organic matter and sulfides appeared to be the most important scavenging phases of As, Fe, Ni, Zn and Cu in ASM (59.8-86.7%). This result was supported by AVS and SEM (Sigma Zn, Ni and Cu) measurements, which indicated that the heavy metals existed overwhelmingly as sulfides in the organic matter and sulfide fraction. A substantial amount of Fe and Ni at 16.4 and 20.1%, respectively, were also present in the carbonate fraction, while an appreciable portion of As (18.3%) and Zn (19.4%) was bound to Fe-Mn oxides. A significant amount of heavy metals was also associated with the residual fraction, ranging from 2.1% for Zn to 18.8% for As. Based on the average total extractable heavy metal (TEHM) values, the concentration of heavy metals in the ASM was in the order of Cu > Ni > Zn > Fe > As. If the mobility and bioavailability of heavy metals are assumed to be related to their solubility and chemical forms, and that they decrease with each successive extraction step, then the apparent mobility and bioavailability of these five heavy metals in ASM increase in the order of Cu < As < Ni < Fe < Zn. The SEM/AVS ratio was less than one in eight replicate ASM samples, indicating that the ASM was non-toxic with regards to having a low probability of bioavailable metals in the pore water.     

Total concentrations, fractionation and mobility of heavy metals in soils of urban area of Guwahati, India

This work describes the results of assessment of the heavy metals, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn in urban soil of Guwahati City, India from 31 sites of five different land use types covering residential, commercial, industrial, public utilities, and roadside. Sequential extraction procedure was used to evaluate the relative distribution of the eight metals in exchangeable, carbonate, reducible (Fe?CMn oxide), organic and sulfide, and residual fractions. Of the eight metals, Cd and Co occur in lower concentrations (Cd <?< Co) in all types of land, and concentration variation from one type of land use to another is not much significant for both the metals. Ni presence is more than Co, and the concentrations show some variation depending on land use status. Average Cr and Cu concentrations are ??100?mg/kg, but Cr has a significantly higher presence in industrial land use. The results are similar in case of Pb. The two metals, Mn and Zn have domination over the other metals, and the values are ??300?mg/kg. Industrial and roadside soil contains much more Mn, while commercial soil is most enriched with Zn. Of the metals, Ni has the largest proportion (~42%) bound to the exchangeable fraction and Co, Cr, and Pb also have appreciable proportion bound to the same fraction. A significant amount of Co is associated with carbonates. The reducible fraction has bound considerable quantity of Mn and Zn, while most of Cu is associated with the organic and sulfide fraction. Both Cd and Pb are dominantly associated with the residual fraction. Computation of the mobility factor of the metals indicates Mn to be the most mobile metal present in the soil samples.     

Inventory compilation and distribution of heavy metals in wastewater from small-scale industrial areas of Delhi, India

Delhi has the highest cluster of small-scale industries (SSI) in India. There are generally less stringent rules for the treatment of waste in SSI due to less waste generation within each individual industry. This results in SSI disposing of their wastewater untreated into drains and subsequently into the river Yamuna, which is a major source of potable water in Delhi, thus posing a potential health and environmental risk to the people living in Delhi and downstream. To study the quantity, quality and distribution of heavy metals in liquid waste from industrial areas, wastewater, suspended materials and bed sediments were collected from industrial areas and from the river Yamuna in Delhi. This study has also focused on the efficiency of production processes in small-scale industries in India. Heavy metals such as Fe, Mn, Cu, Zn, Ni, Cr, Cd, Co and Pb were detected using a GBC 902 atomic absorption spectrometer. The concentration of heavy metals observed was as follows: Fe 2-212, Mn 0.3-39, Cu 0.2-20, Zn 0.2-5, Ni 0.6-6, Cr 0.2-53, Cd 0.08-0.2, Co 0.013-0.55, Pb 0.3-0.7 mg L(-1) in wastewater; Fe 5842-78 000, Mn 585-10 889, Cu 206-7201, Zn 406-9000, Ni 22-3621, Cr 178-10 533, Co 17-114, Cd 13-141, Pb 67-50 171 mg kg(-1) in suspended material; and Fe 3000-84000, Mn 479-1230, Cu 378-8127, Zn 647-4010, Ni 164-1582, Cr 139-3281, Co 20-54, Cd 37-65, Pb 228-293 mg kg(-1) in bed residues. This indicates that SSI could be one of the point sources of metals pollution in the river system.     

Load of Heavy Metals in the Airborne Dust Particulates of an Urban City of Central India

The geographical and temporal distribution patterns of airborne dust particulates have been studied in different representative areas of Raipur City. Dust fall samples from different sites were collected and some selected toxic metals namely Cr, Mn, Fe, Ni, Cu, Zn, Sb and Pb in them were determined by AAS. Total annual flux of 11.7, 541.4, 2751.0, 14.2, 9.8, 90.9, 17.6, and 17.7 kg km(-2) y(-1) were measured for Cr, Mn, Fe, Ni, Cu, Zn, Sb, and Pb respectively. The occurrence of metal concentration were generally in the order industrial > heavy traffic > commercial > residential area in Raipur city. The results of analysis show the existence of toxic metal concentration in the order Fe > Mn > Zn > Pb approximately Sb > Ni > Cr > Cu in Raipur city. These large levels of metal pollutants have also been correlated with some meteorological parameters like temperature, relative humidity and wind velocity, and strong positive correlations have been observed.     

Assessment of heavy metal contamination in Candarli Gulf sediment, Eastern Aegean Sea

Concentrations of selected heavy metals (Fe, Mn, Ni, Cu, Zn, Pb, Hg, Cr, Al, and As) in surface sediments from 18 stations in the Candarli Gulf were studied in order to understand current metal contamination due to urbanization and economic development in Candarli region, Turkey. The sediment samples were collected by box corer in Candarli Gulf in 2009 to assess heavy metal pollution. Heavy metal concentrations in surface sediment varied from 1.62% to 3.60% for Fe, 0.38?C2.53% for Al, 173?C1,423 for Mn, 8?C100 for Ni, 3?C46 for Cu, 55?C119 for Zn, 16?C138 for Pb, 0.2?C6.3 for Hg, 16?C71 for Cr, and 11?C37 mg kg^???1 for As. This study showed that the concentrations of Mn, Ni, Zn, Pb, Hg, and Cr in the surface sediment layers were elevated when compared with the subsurface layers. Both metal enrichment and contamination factors show that Hg, Zn, and Pb contamination exists in the entire study area and contamination of other metals is also present in some locations depending on the sources.