钢丝绳产业区重金属对土壤－农产品的复合污染及生态风险评价?

选取钢丝绳行业比较发达的某乡镇为研究区域,对其地区周边土壤及农产品的污染状况进行了野外调查和实验分析研究。结果表明：（1）土壤中铅、锌的含量均有不同程度的污染。（2）土壤中重金属含量与废水灌溉方式有关。（3）废水灌溉的农产品均有不同程度的污染。（4）重金属主要富集在农产品的根部,果实中富集的量很少。     

白银市土壤重金属污染源分析及防治措施

通过对白银市土壤调查结果进行评价分析,发现东大沟土壤重金属污染较为严重。同时对土壤重金属污染来源进行讨论,认为大面积土壤重金属来源主要是农民节流灌溉所引起的,小范围的土壤污染可能由于固体废弃物(如铬渣等)的堆存造成。其他污染源对土壤造成的污染较轻,但长期的污染物积累也会造成很大的污染。在此基础上提出防治重金属污染的措施。     

上海绿色食品产地土壤环境质量评价

在对上海市嘉定区绿色食品产地华亭人家和马陆葡萄基地的土壤进行全面调查的基础上,对土壤肥力和重金属污染现状进行了监测和初步评价。结果表明,两样区土壤环境质量总体上达到清洁水平,为安全等级,尚未受重金属污染。土壤均为弱碱性土壤;有机质含量处于较差水平;马陆葡萄基地土壤保肥能力较强,华亭人家土壤保肥能力为中等水平;土壤全氮含量均属于肥力Ⅱ级标准。8项重金属指标和2项有机物指标均达到国家土壤环境二级标准,但部分指标超过上海市安全卫生优质农产品产地环境标准。     

我国高速公路周边土壤重金属污染现状及研究进展

以我国高速公路周边土壤重金属为研究对象，综述了我国高速公路周边土壤重金属污染特征、影响因素、来源、环境风险及其研究进展。高速公路周边土壤主要受Pb、Cd、Cr、Cu、Zn等重金属污染，主要呈现指数分布、偏态分布和两者混合分布等特点，并且受到土地利用、风向、地形、车流量等多种因素的综合影响。土壤重金属的来源除了受成土母质等自然因素影响以外，公路交通和周边工农业活动也会对其来源产生较大影响。传统的土壤重金属评价方法主要采用单因子指数法、地累积指数法、生态风险评价法等对重金属的污染等级和环境风险进行评价。未来的研究应将重金属形态分析、空间和地统计分析、重金属稳定同位素示踪和源解析模型以及预测模型等多种手段相结合，开展高速公路周边土壤重金属的污染特征、时空分布、来源及预测预警研究等，为我国高速公路沿线工农业生产布局及其土壤重金属污染防控提供科学依据和决策支撑。     

乌鲁木齐市米东污灌区农田土壤重金属污染评价

对米东污灌区农田土壤重金属含量进行监测分析,利用不同的评价方法和标准对土壤重金属的环境质量进行评价。结果表明:米东污灌区农田土壤重金属含量分别为Cd(0.12±0.06)mg/kg,Cu(40.43±5.30)mg/kg,Zn(78.38±11.04)mg/kg,Pb(11.66±11.79)mg/kg,Ni(20.24±8.05)mg/kg,Cr(75.81±8.05)mg/kg。以国家土壤环境质量标准(二级)为标准评价,各元素的污染指数排序为Cu>Ni>Cr>Zn>Cd>Pb,综合污染指数为0.337,污染程度为安全。以食用农产品产地土壤环境质量要求为标准评价,各元素的污染指数排序为Cu>Ni>Cr>Zn>Cd>Pb,综合污染指数为0.343,污染程度为安全。表明米东污灌区农田土壤重金属含量尚能达到食用农产品产地土壤环境质量要求。Pb、Cu、Zn的平均含量超过乌鲁木齐市土壤背景值,这说明污灌区土壤重金属Pb、Cu、Zn近年来已有所累积,存在一定的污染风险。     

城市土壤重金属污染研究现状与趋势

阐述了城市土壤重金属的主要来源、空间分布特征、化学形态与影响因素,以及对人体的健康风险与生物效应,指出今后的研究重点与趋势是建立城市土壤重金属污染概念和标准体系,研究其在环境中的迁移转化机制与规律及城市土壤重金属复合污染,发展判源分析新技术.     

贵州农业非点源污染土壤重金属含量特征及区域差异性研究

贵州农用地土壤在长期的耕作过程中,承载大量的重金属污染物,影响土壤质量。采集了贵州东部、南部、中部、北部主要农业非点源重金属污染区土壤样品进行检测。结果表明,贵州农业非点源重金属污染物主要是Hg、Pb,贵州省农业非点源污染土壤中重金属累积污染程度Hg＞Pb＞Cd＞As＞Cr。各地区污染物种类和程度不同,重金属As污染为中部地区较高,农业土壤Hg、Pb污染主要集中在中部和东部地区,Cd污染主要发生在南部区域。     

基于PMF模型的矿区土壤重金属来源解析

通过在某矿区采集农田土壤和菠菜样品,分析其中重金属含量,基于相关性分析和PMF模型对该矿区农田土壤重金属来源进行解析。结果表明,研究区土壤中Cd、As、Zn、Cr和Cu 元素明显富集,分别是当地土壤背景值的5.7倍、4.4倍、2.4倍、1.5倍和1.3倍;相关性分析结果显示,研究区内Cu、Zn、As、Cd元素存在一定的相关性,可能具有同一污染源;PMF模型结果说明,研究区土壤中重金属主要来源分别为工业污染源、自然母质源、交通污染源和农业污染源,其对当地土壤重金属污染贡献率分别为39.8%、22.8%、21.6%和15.8%。     

基于重金属有效态的农田土壤重金属污染评价研究

目前农田土壤重金属污染评价以重金属全量为依据,而评价农田土壤重金属污染影响时主要考虑农产品安全从而保障人体健康,农作物对重金属的吸收积累量则取决于土壤中有效态重金属含量。在阐述土壤重金属有效态定义的基础上,综合分析了土壤重金属有效态的影响因素及其与土壤中重金属全量和农作物中重金属含量的相关性,概括了土壤重金属有效态在土壤重金属污染评价中的应用,以期提出建立以土壤重金属有效态含量为基础、结合土壤重金属全量及作物中吸收的重金属含量的土壤重金属污染评价体系。     

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。     

Heavy metals assessment and identification of their sources in agricultural soils of Southern Tehran, Iran

A detailed investigation was conducted to evaluate heavy metal sources and their spatial distribution in agricultural fields in the south of Tehran using statistics, geostatistics, and a geographic information system. The content of Cd, Cu, Co, Pb, Zn, Cr, and Ni were determined in 106 samples. The results showed that the primary inputs of Cr, Co, and Ni were due to pedogenic factors, while the inputs of Zn, Pb, and Cu were due to anthropogenic sources. Cd was associated with distinct sources, such as agricultural and industrial pollution. Ordinary kriging was carried out to map the spatial patters of heavy metals, and disjunctive kriging was used to quantify the probability of heavy metal concentrations higher than their recommended threshold values. The results show that Cd, Cu, Ni, and Zn exhibit pollution risk in the study area. The sources of the high pollution levels evaluated were related to the use of urban and industrial wastewater and agricultural practices. These results are useful for the development of proper management strategies for remediation practices in the polluted area.     

Source identification study of heavy metal contamination in the industrial hub of Unnao,India

India's Unnao region is home to many leather-treatment facilities and related industries. Industrial and agricultural waste leads to heavy metal contamination that infiltrates groundwater and leads to human health hazards. This work measured the amount of heavy metal in groundwater at specific sites near the industrial facilities in Unnao and identified potential sources of contamination as anthropogenic or lithogenic. Groundwater samples were taken from 10 bore well sites chosen for depth and proximity to industry. Data obtained from sample sites was interpreted using a multivariate statistical analytical approach, i.e., principal component analysis, clustering analysis, and correlation analysis. The results of the multivariate analysis showed that cadmium, copper, manganese, nickel, lead, and zinc were correlated with anthropogenic sources, while iron and chromium were associated with lithogenic sources. These findings provide information on the possible sources of heavy metal contamination and could be a model for assessing and monitoring heavy metal pollution in groundwater in other locales. This study analyzed a selection of heavy metals chosen on the basis of industries located in the study area, which might not provide a complete range of information about the sources and availability of all heavy metals. Therefore, an extended investigation on heavy metal fractions will be developed in further studies.     

Seasonal variation of some heavy metal pollution with environmental and microbiological parameters in sub-basin of Kocabas Stream (Biga, Canakkale, Turkey) by ICP-AES

Waste water pollution in industrial areas is one of the most important environmental problems. Heavy metal pollution, especially chromium species in waste water sources from tannery affects our lives. Kocabas Stream is located in south-west Marmara region and Biga town is positioned in the sub basin on the stream. This water source functions as the water for irrigation in agriculture, drinking water for animals and for human use. Thus, this study is of great importance. Waste water pollution can affect all ecosystems and human health by directly or indirectly as in food chain. The concentration of heavy metals (Pb, Cd, Cu, Zn and Cr) were pre-analysed by ICP-AES method in water samples taken from sub-basin of Kocabas stream. In the results of these analyses, concentrations of the metals except chromium were founded at the limit value. But the total concentration of the Cr was found at high levels of between 0.0082 +/- 0.0001 and 5.7231 +/- 0.0921 mg l(-1) over the limit value (0.05 mg l(-1); WHO, EPA, TSE 266 and inland water quality classification) at sampling points very close to tannery factories. Also physicochemical and microbiological parameters of Kocabas Stream were determined. The effects of the experimental results on environment were investigated.     

Impact of industrial waste effluents on river Damodar adjacent to Durgapur industrial complex, West Bengal, India

The present study deals with the characterization of industrial effluents released from various industries and distribution of heavy metals in effluent discharge channel and its impact on the river Damodar. The effluent of tamlanala, a natural storm water channel, is extensively used for irrigation for growing vegetables in and around the study area. The heavy metals in water of the study area are in the order of Fe > Mn > Pb >?Cd and sediments follow similar trends too. The enrichment of heavy metals in the sediments are in the order of Cd (39.904) > Pb (33.156) > Mn (0.164) > Fe (0.013). The geoaccumulation index values reveal effluent channel is subjected to moderate to high pollution with respect to Cd (4.733) and Pb (4.466). The analyzed data for enrichment factors and the pollution load index (1.305) show that effluent channels have suffered from significant heavy metal contamination following industrialization and urbanization. Compared to baseline values, the surface sediment layers show high enrichment across the channel and at its discharge point. The factor analysis reveals three factors—industrial sources, surface runoff inputs, and background lithogenic factors which clarify the observed variance of the environmental variables. Metal pollution assessment of sediments suggests that pollution from the heavy metals observed is high in the tamlanala which in turn affects the downstream of the river system.     

湖北省重点区域及周边表层土壤重金属污染现状及评价

对湖北省内9类不同重点区域及周边表层土壤环境质量进行检测,测定重金属镉、汞、砷、铅、铬、铜、镍、锌含量水平,采用内梅罗污染指数法和Hakanson潜在生态风险指数法对检测结果进行评价。结果表明:9类不同重点区域及周边土壤环境质量整体良好,未受重金属污染的土壤监测点位比例为68.2%~92.6%,轻度污染的点位比例为5.8%~20.4%,中度污染为0.0%~8.6%,重度污染为0.0%~9.1%;污染企业周边、油田采矿区周边、固废处置场地周边、工业遗留遗弃场地及周边4类重点区域受重金属污染相对较严重,影响其土壤环境质量的重金属主要是镉、砷、铜、铅;9类不同重点区域周边土壤环境质量的潜在生态风险等级以轻微、中度为主,对应的监测点位比例分别为36.4%~80.5%、18.1%~47.7%,潜在生态风险等级为强度、很强、极强的监测点位比例总和为1.4%~15.9%,主要分布在受重金属污染严重的监测区域。