扬中县土壤背景值及其与恶性肿瘤死亡率关系

本文对我国癌症高发区扬中县土壤环境背景值作了论述,并与同期调查的全国和江苏省土壤背景值进行对比,采用多元素综合效应比值、相关、多元回归分析法,探讨了癌症发病率与土壤微量元素间的关系。     

广西桂东北地区农业土壤环境若干重金属元素背景值的调查

应用分层抽样统计方法,调查研究广西桂东北地区农业土壤环境Cu、Zn、Pb、Cd、Ni、As、Cr、Hg等8种重金属元素背景值,并分别求算出各元素背景值95％的置信区间。经方差分析,各成土母质间几种元素背景值都有不同程度差异。探讨了该区域农业土壤元素背景值与世界土壤、地壳丰度和国内土壤元素背景值的差异,为开展农业环境科学研究提供依据。     

天津市土壤元素背景值的地域差异及成因分析

论述了天津土壤中Cu,Pb等13种微量元素背景值在行政区，土壤类型中的差异规律，并分析了引起元素背景值地域差异的原因。     

探讨富集因子背景值的选择

为探讨富集因子(EF)背景值的选择,利用黑龙江省甘南县大气降尘重金属元素数据,分别选用黑龙江省A层土壤环境、平均大陆地壳、大陆上地壳为背景,计算Cr、Mn、Ni、Pb、As、Cu、Zn的EF值.研究表明,采用平均大陆地壳和大陆上地壳元素丰度作为背景值时,Pb、Zn、As等元素的EF均值大于2,元素富集一定程度上与人为输入作用有关;采用黑龙江省A层土壤作为背景,As元素EF均值小于2,元素在大气中的富集主要为自然输入;通过相关性分析,As与Cr、Mn、Ni、Cu同为自然源,结果与选用黑龙江省A层土壤为背景时判别结果较一致.本文认为,导致不同背景值取得的EF值差异较大的原因为自然条件下元素的富集和亏损,采用区域土壤元素背景值能够较为准确地判断大气降尘中元素的主要来源.     

天津南港工业区土壤环境背景值调查

通过对天津南港工业区土壤环境背景值的调查研究,对其土壤进行了环境质量评价,并得出了该区域土壤元素的分布规律。在与其他地区的土壤背景值进行比较后,指出了其异同点。天津南港工业区土壤元素在垂直方向上以不规则分布型为主,但As和Cd在土壤表层和深层的含量变化差异较小,Pb表现为表层富集。水平方向上,园区西北部的土壤元素含量比...     

山西省五台山区土壤氟元素的环境背景值及分布规律

对山西省五台山区垂直土壤主要土类的氟元素背景值进行了调查与分析，揭示了五台山区土壤氟元素区域背景的分布特征和变化趋势。结果表明：五台山区土壤氟背景值略高于我国平均水平，多数土壤Ｂ层含氟量最高。     

贵州遵义松林Ni-Mo多金属矿区土壤Mo污染及农作物健康风险初步评价

为了研究贵州遵义松林Ni-Mo多金属矿区土壤和农作物Mo污染情况,测定矿区不同类型土壤(旱地土、水稻土和森林土)和农作物样品Mo含量,采用地质累积指数法评价了土壤Mo污染状况,并采用危险商法评价农作物Mo健康风险.分析结果显示,矿区旱地土、水稻土和森林土Mo平均含量分别为64.66 mg·kg~(-1)、11.83 mg·kg~(-1)和40.24 mg·kg~(-1),相比于本研究的对照样品Mo含量(0.54 mg·kg~(-1))及贵州土壤Mo背景值(2.40 mg·kg~(-1)),3种类型土壤均具有高Mo含量特征.地质累积指数评价结果显示,3种类型土壤均出现不同程度的Mo污染.其中,旱地土Mo污染最为严重,污染级别在中度污染至极重污染之间;其次为森林土,处于中度污染至重度污染-极重污染之间;水稻土Mo污染相对较轻,污染级别在轻度污染至中度污染-重度污染之间.6种农作物样品Mo含量范围为0.36—59.97 mg·kg~(-1).危险商法评价结果表明,水稻和白菜的健康风险指数(HQ)大于1,长期食用可能对人体产生一定的健康风险;玉米、甘薯、辣椒和萝卜的健康风险指数小于1,对人体造成健康风险的可能性较小.若同时食用这6种农作物,Mo造成的总风险值高达3.62,存在较高的健康风险.季节性食用农作物(玉米、甘薯、白菜和萝卜)在食用季节(秋季)将具有更高的健康风险.本研究的结果表明,矿区Mo元素存在Ni-Mo多金属矿石及其围岩(黑色页岩)-土壤-农作物的迁移过程,并在土壤和农作物中富集,造成了一定程度的土壤Mo污染和农作物Mo健康风险.     

浙江省土壤地球化学基准值与环境背景值

以浙江省农业地质环境调查取得的区域地球化学资料为依据,遵循地球化学背景值的基本概念,根据成土母质类型将土壤地球化学基准值划分成13个统计单元,土壤环境背景值以浙北杭嘉湖与宁绍平原、浙东沿海温黄与温瑞平原、浙中金衢盆地为统计单元,在反复剔除异常值后,获得52种元素(氧化物)的平均值、标准差和变异系数,为区域土壤环境质量标准的制订、土壤污染评价与修复提供了重要的地球化学依据.     

三峡库区地质高背景区土壤-油菜重金属迁移特征

三峡库区广泛分布的黑色岩系富含镉（Cd）、铬（Cr）、镍（Ni）、锌（Zn）等重金属元素,导致土壤重金属元素含量显著高于我国土壤背景值,成为典型的地质高背景区。本文选择三峡库区地质高背景区油菜种植地为研究对象,分析了土壤-油菜系统中砷（As）、Cd、Zn、铜（Cu)、铅（Pb）、Cr、Ni、汞（Hg）等重金属元素含量分布特征、富集迁移规律以及影响因素。研究结果表明,研究区油菜种植地土壤中Cd、Cr、Cu、Hg、Ni等重金属含量显著高于我国土壤背景值,单因子污染指数评价显示土壤As、Zn、Hg、Pb等重金属均属于无污染等级,Cu、Ni污染程度受到pH影响,Cd为重度污染和极高生态风险。不同重金属元素在油菜各部位含量差异明显,Pb、Cd、As等生物非必需元素更倾向进入茎、果荚,营养元素Cu和Zn则在油菜籽中含量较高,而Cr易在果荚中富集。研究区土壤中重金属元素含量、土壤p H、重金属元素间的拮抗作用以及油菜解毒机制可能是影响重金属元素在土壤-油菜各部位富集迁移的重要因素。     

土壤元素背景值影响因素的剖析

土壤元素背景值影响因素的研究是环境背景值研究的一项重要课题,在野外工作基础上应用主组元分析及聚类分析两者结合的方法,研究影响土壤元素的各种因素,是一种行之有效的方法。本文使用这种方法研究了影响江苏省一些土壤元素背景值的因素,并根据各自所受的主要影响进行了分类。可分为综合作用影响型、火成岩母质影响型、海成沉积岩母质影响型、现代表生作用影响型,并得到一组计算未知类型的主组元方程,用以估测影响这些未知类型土壤元素背景值的主要因素。     

Molybdenum background and pollution levels in the Taipu River,China

Environmental Chemistry Letters - Pollution of river sediments by industrial molybdenum (Mo) is a potential threat to human and ecosystem health, yet the lack of a geochemical background level for...     

Geochemical disturbance of soil cover in the nonferrous mining centers of the Selenga River basin

The anthropogenic geochemical transformation of soil cover in large nonferrous mining centers of the Selenga River basin was assessed. The results of the geochemical survey of 2010–2012 revealed the spatial distribution patterns and abundances of 18 hazardous heavy metals and metalloids in the soils of Erdenet (Mongolia) and Zakamensk (Buryat republic, Russian Federation). In both cities, mining activities disturbed soil cover which accumulates Mo, Cu, As, Sb, W in Erdenet and Bi, W, Cd, Be, Pb, Mo, Sb in Zakamensk. Maximum accumulation of elements in Erdenet is restricted to the industrial zone. In Zakamensk, it has spread on ½ of the territory with the degree of multielemental pollution exceeding the extremely dangerous level by 16 times. The effect of mining centers on the state of the river system is local and does not spread to the Selenga River. Downstream from Erdenet, an artificial pool intercepts heavy metal and metalloid flows of the Erdenetii-Gol River. By contrast, downstream from the tailing dumps of the Dzhida tungsten–molybdenum plant the concentrations of ore elements W and Mo and their accessories Bi and Cd in the Modonkul River exceed background values by 146, 20, 57, and 21 times, respectively, decreasing by an order of magnitude 30 km downstream.     

洋涌河、茅洲河和东宝河沉积物中重金属的污染及评价

根据重金属环境化学行为的特点,应用沉积学原理,对深圳三条河流沉积物中的重金属进行了研究,采用Lars Hakanson指数法对重金属的潜在生态危害进行了评价,研究结果表明,即使按当地最高背景值为参比值计算,三条河流都受到重金属的严重污染,多数河段属于强的生态危害,少数河段属于中等生态危害。     

江河中有机污染物挥发速率的模拟和预测

以第二松花江重点有机污染物－硝基芳烃为对象，模拟研究了它们在江河中的挥发过程，同时采用４种理论模式，预测了１６种硝基芳烃的挥发速率常数，并将其结果与模拟实测值进行比较评价，讨论了各种模式的优缺点。     

Urban Geochemistry: Investigations in the Berlin Metropolitan Area

The distribution of 41 trace and 11 major elements in 4000 samples of topsoils (0–20cm) from the Berlin Megacity is interpreted. The detailed comparative analysis of the element distributions and the results of factor analysis showed that the distributions of the elements Al, K, Na, Rb, Zr, Nb and Ti are mainly natural origin, i.e. related to the composition of the parent material. Industrial and commercial areas often display considerably elevated values for Mo, Ni, As, Ag, Cr, Sb, Fe, Mn, Mg, P, TOC and especially Pb, Hg and electrical conductivity relative to the geogenic background of the area surrounding Berlin. Industrial areas tend to be characterised by contamination of the subsoil with Cu, Cd, Zn, Hg, Pb and Sn. In the area around Berlin, extensive, strong anamalies of Cd, Zn, Pb, Cu and Hg occur near iron and steel industries and construction materials industries, as well as in the vicinity of sewage farms.     

Heavy metals in coastal sediments in Guipuzcoa (Spain)∗

Surficial sediment samples were wet digested (HNO₃‐HCI‐HF) and analysed by atomic absorption spectroscopy. The background values in the area, and the Pollution Index Load in the sampling points were calculated. Metal inputs of continental origin are specially important in Deva, Oria and Urola river mouths.     

Importance of background values in assessing the impact of heavy metals in river ecosystems: case study of Tisza River,Serbia

The main objective of this paper is to evaluate how a choice of different background values may affect assessing the anthropogenic heavy metal pollution in sediments from Tisza River (Serbia). The second objective of this paper is to underline significance of using geochemical background values when establishing quality criteria for sediment. Enrichment factor (EF), geoaccumulation index (I _geo), pollution load index (PLI), and potential ecological risk index (PERI) were calculated using different background values. Three geochemical (average metal concentrations in continental crust, average metal concentrations in shale, and average metal concentrations in non-contaminated core sediment samples) and two statistical methods (delineation method and principal component analyses) were used for calculating background values. It can be concluded that obtained information of pollution status can be more dependent on the use of background values than the index/factor chosen. The best option to assess the potential river sediment contamination is to compare obtained concentrations of analyzed elements with concentrations of mineralogically and texturally comparable, uncontaminated core sediment samples. Geochemical background values should be taken into account when establishing quality criteria for soils, sediments, and waters. Due to complexity of the local lithology, it is recommended that environmental monitoring and assessment include selection of an appropriate background values to gain understanding of the geochemistry and potential source of pollution in a given environment.