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山东省广饶县土壤重金属来源、分布及生态风险

本站小编 Free考研考试/2021-12-29

周旭¹^,, 吕建树¹^,²^,

1. 山东师范大学地理与环境学院,济南 250014

2. 华东师范大学河口海岸学国家重点实验室,上海 200062

Sources, distribution and ecological risk of soil heavy metals in Guangrao county, Shandong province

ZHOUXu¹^,, LVJianshu¹^,²^,

1. College of Geography and Environment, Shandong Normal University, Jinan 250014, China

2. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China

通讯作者:吕建树（1986- ）,男,山东莱芜人,博士,副教授,硕士生导师,研究方向为重金属环境地球化学。E-mail: lvjianshu@126.com
收稿日期:2017-11-27
修回日期:2018-08-11
网络出版日期:2019-02-20
版权声明:2019《地理研究》编辑部《地理研究》编辑部所有
基金资助:

国家自然科学基金项目（41601549,41701604）

山东省自然科学基金项目（ZR2016DQ11,ZR2017BD003）

河口海岸学国家重点实验室开放基金项目（SKLEC-KF201710）

作者简介:
-->作者简介：周旭（1993- ）,男,山东济宁人,硕士,研究方向为土壤重金属污染评价。E-mail: zhouxu3726@126.com

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摘要
选取山东省广饶县作为研究区,采集300个表层土壤样品（0~20 cm）,测定As、Cd、Co、Cr、Cu、Hg、Mn、Ni、Pb和Zn等10种重金属含量;运用多元统计和地统计分析方法揭示广饶县土壤重金属元素的来源与空间分布特征,最后利用H?kanson潜在生态风险指数法评价重金属的潜在生态风险。结果表明：① 研究区土壤中Co和Pb的平均值低于山东省背景值,其他8种元素的平均值均超过山东省背景值;特别是Cd和Hg的平均含量分别达到山东省背景值的1.86倍和2.50倍,说明在土壤中存在明显的富集。② As、Co、Cr、Cu、Mn、Ni和Zn为自然源,受成土母质控制;Hg为人为源,主要来源于煤炭燃烧和工业排放;Cd和Pb受自然和人为因素共同控制。③ 成土母质控制着As、Cd、 Co、Cr、Cu、Mn、Ni、Pb和Zn的基本分布格局,不同土地利用类型的土壤Hg含量差别较明显,其高值区集中在城镇建设用地。④ 总体上,研究区为中等生态风险的偏高水平,其中Cd和Hg分别为中等和较高生态风险,其余8种元素处于低生态风险。

关键词：重金属;来源解析;空间分布;生态风险;广饶县
Abstract
A total of 300 samples in topsoils (0-20 cm) of Guangrao county, Shandong province were collected, and each sample was analyzed for As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, and Zn. The sources and spatial distribution of heavy metals were examined using multivariate analysis and geostatistics, and the ecological risk of heavy metals in soils was evaluated using H?kanson's method. The average contents of Co and Pb were lower than the background values of Shandong, and the average concentrations of the other heavy metals were higher than the background values of the province. In particular, the mean contents of Cd and Hg were 1.86 and 2.50 times their respective background values, indicating that there were obvious accumulations of Cd and Hg in surface soils. As, Co, Cr, Cu, Mn, Ni, and Zn mainly came from natural sources, and were controlled by parent materials. Hg originated from coal combustion and industrial emissions, and was greatly controlled by human activities. Cd and Pb were affected by both natural and human factors. Agricultural practices, especially the application of chemical fertilizers, contributed to the increased Cd contents, while the vehicles emissions were the main human inputs to the Pb contents. The spatial distributions of As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn were controlled by parent materials with the higher contents in the soils from lacustrine deposit and the Yellow River alluvium; there were significant differences among various land use types, and higher contents were observed around the urban area. Totally, the study area suffered the moderate ecological risk with the high value area corresponding to the urban area; the intense human activities have led to high ecological risk in the urban area. The level of ecological risk was the lowest in the northeast part, the high ecological risk was concentrated in the urban area and the surrounding area, and the other regions had middle ecological risk. Hg was at the considerable ecological risk level, and Cd was at the moderate ecological risk level, while other heavy metal elements were at the low ecological risk level.

Keywords：heavy metals;sources;spatial distribution;ecological risk;Guangrao county

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周旭, 吕建树. 山东省广饶县土壤重金属来源、分布及生态风险[J]. 地理研究, 2019, 38(2): 414-426 https://doi.org/10.11821/dlyj020171151
ZHOU Xu, LV Jianshu. Sources, distribution and ecological risk of soil heavy metals in Guangrao county, Shandong province[J]. Geographical Research, 2019, 38(2): 414-426 https://doi.org/10.11821/dlyj020171151

1 引言

随着经济社会发展的进程,土壤重金属污染逐渐成为威胁土壤环境进而限制农业发展的重要因素,成为广泛关注的环境问题^[1,2,3,4]。土壤是重金属的归宿,又可将其输出到大气、水和生物体中,引发二次污染。重金属不仅影响土壤的理化特性,还可以抑制植物、土壤动物及土壤微生物的生命活动^[5,6];其具备在介质中的累积性,并通过食物链逐级传播累积,最终经摄入、呼吸及皮肤接触等方式进入人体,威胁人体健康^{[7,8,9,10,11,12,13]}。土壤中重金属的主要来源为成土母质和人类活动^[13,14]。当前,煤炭燃烧、交通排放和农业生产等人类活动对土壤重金属含量的影响愈演愈烈,许多研究表明人类活动对重金属含量的贡献已经远远超过自然背景^[8,9,15,16]。因此,揭示土壤重金属的来源、分布和生态风险,可以为土壤环境质量评价与管控提供借鉴。
多元统计和地统计分析是研究土壤中重金属来源和空间分异的范式性方法^[17]。多元统计分析可以提炼多个因素相互关联的规律性,实现降维的目的,目前已经普遍应用于土壤重金属来源辨识的研究中^[18,19]。董立宽等运用相关分析等方法研究了江、浙两地茶园土壤中的重金属,对研究区茶园土壤重金属的来源进行了解释^[7];Rodríguez Martín等将多元统计分析应用于西班牙Ebro河流域农业土壤重金属的来源解析,结果表明Ni和Cr的关系更加明显,均为自然来源,而Cu、Zn和Pb所导致的研究区局部重金属浓度的异常与人类活动有关^[18]。地统计方法自20世纪80年代引入土壤学研究以来,广泛运用于研究土壤中物质的空间结构和变异性。普通克里格作为最为简单有效的地统计方法,近年来研究成果丰富。Tripathi等使用普通克里格探究了土壤理化性质的空间变异^[20];Mendlewicz等运用普通克里格和指示克里格对墨西哥城大都会区表层土壤中的有毒元素进行了空间分析^[21];Lin等把因子克里格和指示克里格相结合,研究了土壤重金属空间变异和污染源^[22];Reza等采用普通克里格法研究了矿区重金属污染的空间结构^[23];Mahmoudabadi等探究了土壤重金属分布的影响因素^[24];Zhang等使用普通克里格探究了中国东北黑土区农业土壤的重金属空间分异状况^[25]。多元统计和地统计分析在土壤重金属的研究中的应用逐渐成熟、完善,结合区域土地利用类型和土壤母质分布可以更加准确地辨析土壤重金属的来源,揭示重金属空间分布特征及其影响因素。
广饶县作为山东省北部的典型工业大县,石化、橡胶、纺织等工业集聚,并大力发展生态农业^[26],是黄河三角洲高效生态经济区的代表性县域。伴随着区域的不断发展,特别是黄三角高效生态经济区崛起为国家战略,近年来发展迅速,面貌日新月异。广饶县土壤环境的压力不断增加,因此研究广饶县土壤重金属污染状况是十分必要的,对了解黄三角典型区域的土壤质量与生态状况有较强的现实与示范意义。通过对广饶县研究区300个表层土壤样点的10种重金属元素（As、Cd、Co、Cr、Cu、Hg、Mn、Ni、Pb和Zn）全量的测定,运用多元统计分析方法来辨别土壤重金属的来源,运用地统计方法,在变异函数的基础上使用普通克里格插值^[27],探究重金属空间分布状况;最后运用H?kanson^[28]的方法研究了广饶县土壤重金属的生态风险。

2 研究方法与数据来源

2.1 研究区概况

广饶县处于山东省偏北部,隶属于东营市。地理坐标为118°17′E~118°57′E、36°56′N~37°21′N,南部与淄博临淄相邻,西接滨州博兴,东连潍坊寿光,是黄三角高效生态经济区的中部节点（图1）;全县总面积约为1138 km²。广饶县地跨鲁西台背斜和辽冀台向斜,地势低平,海拔介于2~28 m之间;沉积地层覆盖在变质岩基底之上,地表为第四系沉积物,黄泛淤积分布在研究区北部,土壤多为盐土和潮土,南部主要受山前冲积形成,土壤以褐土和潮土为主。研究区属于大陆性季风气候,年降水量约587.4 mm,年均温12.3 ℃。2016年广饶GDP达到791亿元,在黄河三角洲高效生态经济区19个县（市、区）中位居第三。研究区内有丰富的石油资源,工业类型较为齐全,作为山东省重要的石油化工基地,形成了石化、橡胶、机械、纺织等主导产业。广饶县土壤肥沃,地形平坦,以种植小麦、玉米和棉花等农作物为主,冬枣、大蒜在域内也有较大面积的种植。

显示原图|下载原图ZIP|生成PPT
图1广饶县及采样点分布图
-->Fig. 1Location of soil sampling sites in Guangrao county
-->

2.2 数据来源与处理

运用网格布点法,按照2 km×2 km的规则网格在研究区均匀布设300个采样点^[2]。开展实地采样时,根据实地环境状况进行采样点的适当微调,用GPS记录调整后的采样点坐标,最后生成研究区采样点示意图（图1）。按照多点采样的方式,在布设的采样点周围垂直采集表层0~20 cm的土样,把土样混合均匀后,装入干净的塑料袋,混合后样品的重量在1 kg以上^[2]。把土壤样品在室温下进行自然晾干并去除土壤中的杂质,土壤样品用无污染玛瑙样品制备机研磨至粒径小于100目（0.15 mm）,之后用HNO₃-H₂SO₄-HClO₄-H₂O₂进行消煮,使用原子荧光光谱法测定As和Hg,对Cd、Co、Cr、Cu、Ni、Pb、Mn和Zn用原子吸收分光光度法测定。采用国家一级土壤标准物质（GBW系列）控制测试质量,测试回收率在100±10%,符合监控要求^[1]。通过扫描山东省地质图（1

∶

50万）,并运用ArcGIS 10.1对研究区地质图进行提取,最终获得研究区对应的土壤母质图件;通过人机交互目视解译2016年广饶县Landsat-TM影像获得研究区土地利用类型图。

2.3 研究方法

2.3.1 多元统计与地统计分析运用描述性统计指标剖析数据的结构,采用主成分和相关分析等多元统计方法进行数据的分析^[29],采用单因素方差分析（ANOVA）研究了土地利用和成土母质在空间和浓度上对重金属的影响。利用SPSS 22.0进行多元统计分析,利用GS+9.0进行变异函数的分析,运用ArcGIS 10.1中的地统计模块（Geostatistical analyst）进行普通克里格插值。
2.3.2 生态风险评价潜在生态危害指数法是分析土壤重金属污染行之有效的方法,可以对诸多影响因素综合考虑,是瑞典****H?kanson基于重金属的理化性质和与环境的相互作用提出的^[28]。其中单因子生态危害指数

E_{r}^{i}

为：

E_{r}^{i} = T_{r}^{i} \times \frac{C^{i}}{C_{n}^{i}}

（1）
式中：

C^{i}

代表重金属含量;

C_{n}^{i}

代表每种元素的参考值,参考山东省土壤元素背景值^[30];

T_{r}^{i}

是元素

i

的毒性响应系数,体现了其在环境中的毒害程度。参照相关研究^[1,28],Hg、Cd、As、Co、Cu、Pb、Ni、Cr、Mn和Zn的毒性响应系数分别为40、30、10、5、5、5、5、2、1和1。所有因子的综合生态危害指数

RI

表示为各因子

E_{r}^{i}

之和：

RI = \overset{m}{\sum_{i = 1}} E_{r}^{i}

（2）

3 结果分析

3.1 重金属元素描述性统计

根据广饶县重金属描述性分析结果（表1）,重金属元素As、Cd、Co、Cr、Cu、Hg、Mn、Ni、Pb和Zn的平均值分别为10.8 mg·kg^-1、0.13 mg·kg^-1、11.9 mg·kg^-1、68.1 mg·kg^-1、24.0 mg·kg^-1、0.038 mg·kg^-1、586 mg·kg^-1、28.8 mg·kg^-1、22.6 mg·kg^-1和67.2 mg·kg^-1,对山东省背景值^[30]的超标率分别为70.33%、100%、33.00%、74.33%、66.67%、97.33%、59.67%、80.00%、25.00%和73.00%。各元素均值除Co和Pb外都超过了山东省背景值,其中Cd和Hg的均值分别为各自山东省背景值的1.86倍和2.50倍,两元素的最大值更是分别达到背景值的4.10倍和33.56倍,Cd和Hg相对于山东省背景值的超标率也达到100%和97.33%,可见两元素在研究区某些区域的土壤中有明显的累积。所有元素的平均值均低于国家二级标准^[31],Co和Mn没有可参考值。在所研究的重金属元素中,仅Hg有1个样点超过国家二级标准值。Hg和Cd的偏度分别为9.99和1.10,均高于其他重金属元素,从峰度值可以看出,Hg的峰度达到了128.71,远远超过其他重金属,表明Hg可能受到人类活动影响而产生较多的极端值。变异系数为标准差与平均值之比,可以衡量不同量纲数据的变异程度。根据Wilding对变异系数（Coefficient of Variation, CV）的分级^[32],Co、Cr和Pb的变异系数分别为0.15、0.08和0.13,属于低度变异（CV<0.16）,As、Cd、Cu、Mn、Ni和Zn的变异系数分别为0.24、0.25、0.18、0.17、0.18和0.16,属于中度变异（0.16<CV<0.36）,Hg的变异系数为0.95,属于高度变异（CV>0.36）,可能受到人为因素的影响而产生特征值。
Tab. 1
表1
表1广饶县土壤重金属元素描述性统计（mg·kg^-1）
Tab. 1Descriptive statistics of heavy metals in soils from Guangrao County (mg·kg^-1)

重金属	范围	均值	中值	标准差	偏度	峰度	变异系数	山东省背景值^[30]	国家二级标准^[31]
As	5.2~17.2	10.8	10.3	2.64	0.44	-0.50	0.24	8.9	30
Cd	0.07~0.29	0.13	0.13	0.03	1.10	2.54	0.25	0.07	0.3
Co	6.1~16.9	11.9	11.9	1.83	-0.15	0.22	0.15	12.6	-
Cr	53.5~94.1	68.1	67.5	5.53	0.54	1.08	0.08	64.3	200
Cu	11.8~37.8	24.0	23.7	4.42	0.14	0.69	0.18	22.3	100
Hg	0.011~0.537	0.038	0.032	0.04	9.99	128.71	0.95	0.016	0.5
Mn	411~970	586	576	98.46	0.91	1.11	0.17	552	-
Ni	14.6~43.4	28.8	28.6	5.05	0.09	0.01	0.18	24.4	50
Pb	12.6~30.4	22.6	22.8	2.99	-0.77	1.36	0.13	24.5	300
Zn	34.8~98.6	67.2	66.6	10.63	-0.08	0.29	0.16	60.9	250

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3.2 土壤重金属来源分析

3.2.1 相关分析重金属的相关系数见表2。As、Cr、Co、Cu、Mn、Ni和Zn互相之间的相关系数比较高,均超过了0.5,较高的相关性表明这些元素可能拥有一致的来源。一般来说,Cr和Ni为自然来源的元素,与其相关性较高的元素被认为受到成土母质的控制^[33],因此As、Cr、Co、Cu、Mn、Ni和Zn可以被认为是自然来源。Cd与As、Cu、Mn、Ni和Zn之间的相关系数分别为0.52、0.69、0.85、0.80和0.75,而与Co、Cr、Hg和Pb的相关性较低;Pb与As、Co、Cu、Mn、Ni和Zn相关性较高。Cd和Pb与受成土母质控制的元素存在较高相关性,说明Cd和Pb受到自然来源影响,是否受到人类活动的影响需要进一步的主成分和地统计分析。Hg与其他9种重金属的相关性很弱,均小于0.2,结合Hg高度的变异系数,因此判断Hg为孤立元素,受人类活动影响的可能性大。
Tab. 2
表2
表2广饶县土壤重金属元素的相关系数
Tab. 2Correlation coefficients of heavy metals in soils from Guangrao county

	As	Cd	Co	Cr	Cu	Hg	Mn	Ni	Pb	Zn
As	1
Cd	0.52^**	1
Co	0.66^**	0.40^**	1
Cr	0.57^**	0.46^**	0.54^**	1
Cu	0.69^**	0.54^**	0.82^**	0.63^**	1
Hg	-0.09	0.05	-0.03	-0.11	0.05	1
Mn	0.85^**	0.53^**	0.77^**	0.67^**	0.80^**	-0.10	1
Ni	0.80^**	0.52^**	0.93^**	0.63^**	0.84^**	-0.07	0.88^**	1
Pb	0.51^**	0.48^**	0.63^**	0.41^**	0.78^**	0.19^**	0.50^**	0.62^**	1
Zn	0.75^**	0.54^**	0.89^**	0.59^**	0.92^**	0.02	0.83^**	0.92^**	0.74^**	1
Al₂O₃	0.63^**	0.35^**	0.79^**	0.51^**	0.84^**	-0.03	0.73^**	0.77^**	0.68^**	0.81^**
Fe₂O₃	0.83^**	0.52^**	0.84^**	0.69^**	0.90^**	-0.07	0.91^**	0.91^**	0.68^**	0.91^**
MgO	0.74^**	0.50^**	0.62^**	0.63^**	0.59^**	-0.18^**	0.77^**	0.76^**	0.30^**	0.68^**

注：^**代表在0.01水平显著。

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Al₂O₃、Fe₂O₃以及MgO为母岩风化过程中形成的主量元素,通常较少受到人为影响。除Cd和Hg之外的8种元素与Al₂O₃的相关系数均大于0.5（P<0.01）;除Hg之外的9种元素与Fe₂O₃的相关系数均大于0.5（P<0.01）,除Hg和Pb之外的8种元素与MgO有较高的相关性。As、Cr、Co、Cu、Mn、Ni和Zn同3种主量元素的相关系数均较高,证明了它们的自然来源。Cd和Pb仅与部分的主量元素存在较高的相关性,说明受到成土母质因素的影响,其他来源也需要进一步分析。Hg与Al₂O₃、Fe₂O₃以及MgO的相关系数均较低,仍判断是孤立存在的元素。元素间的相关关系通过其与成土母质主量元素的相关分析结果得到了进一步的验证。
3.2.2 主成分分析通过主成分分析,可以辨别出3个主成分,累计解释了总方差的83.44%,基本可以包括数据所含信息（表3）。主成分1（PC1）的方差贡献率为64.76%,As、Co、Cr、Cu、Mn、Ni、Pb和Zn的因子载荷分别为0.839、0.888、0.714、0.929、0.915、0.948、0.750和0.953（表3）,与Al₂O₃、Fe₂O₃和MgO之间存在较高的相关性,As、Co、Cr、Cu、Mn、Ni、Pb和Zn的平均含量都高于山东省背景值,而且As、Ni和Mn的最大值分别为山东省土壤背景值的1.93倍、1.78倍和1.76倍。这可能是由于研究区石灰岩的地质类型和河流冲积、海积物的特殊背景所致^[34]。因此PC1代表了自然来源。Nanos等对西班牙Duero河流域的研究发现Cr、Cu、Ni、Pb和Zn在第一主成分均为自然来源^[33]。这与本文结论一致。Facchinelli等对意大利Piemonte的研究^[35]、Sajn等对Drava河谷下游冲积平原土壤的研究^[36]和Boruvka等对捷克北部及东北部地区土壤重金属的研究^[37]均发现Co、Cr、Mn、Ni和Zn受地质背景控制。章明奎等也认为Co、Cr和Ni基本上来自于自然源^[38]。郭伟等通过研究呼和浩特市土壤中的重金属,也发现As主要受到自然来源的控制^[39]。
Tab. 3
表3
表3重金属元素因子矩阵
Tab. 3Factors matrix of heavy metals in soils from Guangrao county

重金属	PC1	PC2	PC3
As	0.839	-0.157	0.087
Cd	0.635	0.109	0.684
Co	0.888	-0.010	-0.322
Cr	0.714	-0.217	0.274
Cu	0.929	0.117	-0.091
Hg	-0.018	0.934	0.044
Mn	0.915	-0.155	0.020
Ni	0.948	-0.082	-0.148
Pb	0.750	0.380	-0.087
Zn	0.953	0.072	-0.151
方差贡献率（%）	64.76	11.51	7.17
累计方差贡献率（%）	64.76	76.72	83.44

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主成分2（PC2）的方差贡献率为11.51%,Hg的载荷为0.934（表3）。Hg的平均值为0.038 mg·kg^-1,远高于山东省背景值,最大值为0.537 mg·kg^-1,是山东省背景值的33.56倍。Hg与Al₂O₃、Fe₂O₃和MgO的相关性较低,所以Hg的来源可能为人类活动。Hg是环境中毒性最强的重金属元素之一,主要来自于人为因素,人类活动可以造成Hg在沉积物中的累积^[40]。Hg主要经由大气干湿沉降到土壤中,导致其在土壤中的浓度不断上升^[41,42]。广饶县内有多家燃煤发电厂,造成Hg在土壤中的积累。Pb在PC2上的因子载荷为0.380,与主量元素的相关性很低,表明了Pb的人为来源。Pb主要来源于汽车尾气,同时煤炭燃烧也会造成Pb排放。很多****的研究都认为Hg和Pb有相同的来源^[37,43],与本文的结果一致。所以PC2代表了工业和交通排放等人类活动。
主成分3（PC3）的方差贡献率为7.17%,Cd的载荷为0.684。Cd的平均含量为背景值的1.86倍;其最大含量达到了0.29 mg·kg^-1,远超山东省背景值,是山东省背景值的4.1倍,接近国家二级标准值。相关研究表明土壤Cd污染主要来源于化肥的施用,Cd在磷肥中的平均含量为0.6 mg·kg^{-1 [44]}。研究区作为农业大县,农业精细化程度较高,化肥施用量不断增加,尤其是磷肥的施用量多且广泛,容易造成Cd在土壤中的累积。所以PC3代表了化肥农药施用等人为来源。Zhang等对黑土区农业土壤重金属的研究^[25]以及章明奎等对浙东海积平原土壤重金属的研究^[38]均发现Cd来源于化肥的施用。
Cd在PC1和PC3上的载荷分别为0.635和0.684,均为中等载荷,可看作受到人为源和自然源的共同控制,Zhong等对昆山市土壤重金属的研究也表明Cd受自然和人类活动共同影响^[45]。Pb在PC1和PC2上的载荷分别为0.75和0.38,可认为有人为和自然两个来源,这与吕建树等对日照市土壤重金属的研究^[2]相一致,但Pb主要受到自然来源的控制。
3.2.3 来自不同土地利用类型和成土母质的土壤重金属含量差异通过土地利用类型和成土母质的分布（图2）以及土壤重金属含量单因素方差分析可知（表4）,受土地利用类型影响最为显著的是Hg。Hg在城镇建设用地中的土壤中平均含量为0.098 mg·kg^-1,远高于其他土地利用类型,说明Hg的来源受人类活动的控制。林地土壤中Cd的平均含量为0.15 mg·kg^-1,高于其他地类,主要原因是冬枣种植所需的化肥造成Cd在土壤中的累积。Pb在城镇建设用地的平均值最大,达到24.2 mg·kg^-1。As、Co、Cr、Cu、Mn、Ni和Zn的最大平均值均出现在城镇建设用地以外的土地利用类型,平均含量分别为11.4 mg·kg^-1、12.1 mg·kg^-1、69.1 mg·kg^-1、24.6 mg·kg^-1、601 mg·kg^-1、29.1 mg·kg^-1和69.1 mg·kg^-1,与其他地类之间的差别较小,来源于成土母质的可能性较大,需要结合与成土母质的关系进一步判定这些元素的来源。湖相沉积物和黄河冲积物发育的土壤中As、Cd、Co、Cr、Cu、Mn、Ni、Pb和Zn平均含量高于滨海沉积物和山前冲洪积物母质,说明这些元素受到土壤母质的影响。吕建树等研究表明重金属元素在湖相沉积物和河流冲积物发育土壤中的含量更高^[46];王关玉等研究发现海积物中重金属元素的含量低于其他母质类型^[35]。值得一提的是,Hg在本底值较低的鲁中南山前冲洪积物发育的土壤中的平均含量为0.048 mg·kg^-1,明显高于其他母质类型,主要归因于Hg在城镇建设用地的高含量值改变了土壤重金属在不同母质的分布规律。这也证实了Hg的人为来源。

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图2广饶县成土母质与土地利用分布图
-->Fig. 2Parent materials and land use types in Guangrao county
-->

Tab. 4
表4
表4来自不同土地利用类型和成土母质的土壤重金属含量差异(mg·kg^-1)
Tab. 4The contents of heavy metals in soils from different land use types and parent materials in Guangrao county (mg·kg^-1)

		参数	As	Cd	Co	Cr	Cu	Hg	Mn	Ni	Pb	Zn
土地利用类型	耕地	范围	5.2~17.7	0.07~0.24	6.1~16.9	53.5~94.1	11.8~37.9	0.011~0.261	411~970	14.6~43.4	12.6~29.3	34.8~98.7
		平均值	10.9^b	0.13^a	12.1^a	68.2^a	24.2^a	0.036^b	593^a	29.1^a	22.7^a	67.9^a
		标准差	2.65	0.01	1.78	5.59	4.38	0.02	98.70	4.89	2.81	10.32
	林地	范围	8.6~14.5	0.11~0.17	10.9~13.3	64.1~74.0	22.5~28.6	0.018~0.052	511~698	25.6~32.7	21.4~25.8	63.9~78.3
		平均值	11.4^a	0.15^a	11.9^a	68.4^a	24.6^a	0.033^b	601^a	28.8^a	23.1^a	69.1^a
		标准差	2.28	0.04	0.75	3.53	2.36	0.01	66.99	2.60	1.86	5.92
	草地	范围	9.8~12.7	0.08~0.14	10.7~13.5	66.4~72.7	20.7~23.9	0.019~0.023	568~639	27.2~30.6	22.4~23.3	63.2~65.6
		平均值	11.3^a	0.11^b	11.8^a	69.1^a	22.4^a	0.021^b	597^a	28.9^a	22.8^a	64.3^b
		标准差	1.25	0.02	1.03	2.06	1.24	0.001	26.07	1.29	0.54	1.1
	城镇建设用地	范围	6.5~12.7	0.11~0.16	9.3~13.3	57.4~70.7	19.6~26.9	0.020~0.537	453~609	22.7~29.5	20.0~30.4	54.4~78.9
		平均值	10.1^b	0.14^a	11.3^b	63.8^b	22.9^a	0.098^a	525^b	25.8^b	24.2^a	64.6^b
		标准差	1.45	0.02	1.05	3.34	2.08	0.14	45.94	2.35	2.11	6.59
	农村居民用地	范围	6.5~14.3	0.09~0.21	9.3~15.6	59.4~78.3	17.5~29.7	0.023~0.149	440~726	20.2~37.5	17.1~27.0	49.2~80.6
		平均值	10.5^b	0.13^a	11.9^a	66.7^a	23.1^a	0.041^b	572^a	28.3^a	22.7^a	66.0^a
		标准差	2.20	0.01	1.70	4.09	2.97	0.03	74.69	4.45	2.32	7.34
土壤母质类型	海积物	范围	5.2~16.2	0.07~0.18	6.1~16.2	53.1~94.1	11.9~36.5	0.014~0.031	411~886	14.6~41.4	12.6~28.6	34.8~95.4
		平均值	9.5^b	0.12^a	9.9^b	68.0^a	18.9^b	0.021^c	548^b	24.4^b	18.5^b	56.4^b
		标准差	2.72	0.03	1.9	8.14	5.39	0.004	109.68	5.71	4.00	12.37
	湖相沉积物	范围	7.9~17.7	0.08`0.24	8.8~16.9	57.1~81.9	15.6~36.7	0.017~0.055	464~970	21.6~43.4	17.1~28.4	47.9~98.6
		平均值	12.3^a	0.15^a	12.8^a	70.4^a	25.8^a	0.030^b	649^a	31.9^a	23.6^a	72.4^a
		标准差	2.38	0.03	1.55	5.22	4.15	0.01	102.37	4.47	2.39	9.29
	黄河冲积物	范围	8.4~16.9	0.08~0.21	10.3~15.5	60.9~77.4	20.6~30.7	0.024~0.066	506~743	25.6~36.3	20.9~27.8	58.5~85.6
		平均值	12.9^a	0.14^a	12.6^a	69.6^a	25.4^a	0.036^b	621^a	31.3^a	23.1^a	73.3^a
		标准差	1.82	0.03	1.2	4.31	2.86	0.01	63.62	2.79	1.89	6.73
	鲁中南山前冲洪积物	范围	5.3~15.0	0.08~0.19	9.0~15.5	57.1~75.1	17.5~37.8	0.011~0.537	440~732	20.1~37.8	17.3~30.5	49.3~82.1
		平均值	9.6^b	0.13^a	11.7^a	65.7^b	23.5^a	0.048^a	548^b	27.1^b	23.2^a	65.1^a
		标准差	1.86	0.02	1.49	4.09	3.18	0.05	64.29	3.63	2.21	7.41

注：^a、^b、^c表示变量在0.05水平上存在明显差异

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3.3 土壤重金属空间分布

3.3.1 变异函数理论模型首先采用Kolmogorov-Smirnov（K-S）检验对数据进行正态分布检验,结果表明：Co、Cr、Cu、Ni和Zn均符合正态分布,As、Cd、Hg、Mn和Pb不符合正态分布,经过对数变换后均符合正态分布。变异函数可以分析区域变量的空间结构^[47],对土壤重金属进行变异函数分析,以获得最佳的变异函数模型（表5）,其中As、Co、Cr、Mn、Ni、Pb和Zn属于高斯模型,Cd和Hg属于指数模型,Cu属于球状模型。变程反映变量空间上自相关的范围,用来判断变量的空间自相关性,各变量的有效变程在28020~728846之间,进行空间插值具有有效性。各元素的决定系数均大于0.94,残差均较小,介于0.071×10^-5~0.365×10^-2之间,说明选取的模型基本符合要求。As、Co、Cu、Mn、Ni、Pb、Zn的块金值/基台值均小于0.25,说明这些元素是结构性为主的空间变异,较大程度上受地形、地质背景等要素的影响,Cd、Cr、Hg的块金值/基台值均在0.25~0.75之间,空间相关性为中等强度,受不确定性因素影响的可能性较大^[29]。
Tab. 5
表5
表5土壤重金属元素的变异函数模型
Tab. 5Models for variograms fitting of heavy metals in soils

	模型	块金值 (C₀)	基台值 (C₀+C)	块金值/基台值 (C₀/C₀+C)	变程 (m)	残差	决定系数	K-S检验 (Asymp.sig.)
As	Gaussian	0.006	0.025	0.240	51373	0.201×10^-5	0.993	0.021
Cd	Exponential	0.005	0.012	0.417	28020	0.199×10^-5	0.951	0.016
Co	Gaussian	0.034	0.159	0.215	63272	0.111×10^-3	0.988	0.327
Cr	Gaussian	0.075	0.221	0.340	74253	0.183×10^-3	0.977	0.206
Cu	Spherical	0.110	0.567	0.194	84178	0.230×10^-2	0.957	0.425
Hg	Exponential	0.015	0.049	0.317	61470	0.362×10^-4	0.958	0.017
Mn	Gaussian	0.002	0.014	0.159	728846	0.071×10^-5	0.987	0.023
Ni	Gaussian	0.091	0.637	0.143	70183	0.647×10^-3	0.995	0.331
Pb	Gaussian	0.002	0.015	0.127	114974	0.091×10^-5	0.940	0.014
Zn	Gaussian	0.216	1.457	0.148	92468	0.365×10^-2	0.987	0.362

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3.3.2 重金属元素的空间分布特征根据变异函数分析结果对研究区进行插值（图3）,分析不同元素在空间分布上的特征。As、Cd、Co、Cr、Cu、Mn、Ni、Pb和Zn有相似的空间分布,高值区域主要集中在研究区北部（图3a~图3e、图3g~图3j）,此区域成土母质为湖相沉积物和黄河冲积物（图2b）,并且单因素方差分析表明这两种母质有很高的地质背景,因此成土母质控制着这些元素的空间分布。

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图3广饶县土壤重金属含量空间分布
-->Fig. 3Spatial distribution of the heavy metal contents in Guangrao county
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Hg的高值区域主要分布在大王镇、广饶镇以及稻庄镇（图3f）,与本底地质背景很高的湖相沉积物呈相反分布（图2b）。高值区分布在工业密集的城区,化石燃料的燃烧引起了Hg的累积。Pb的高值区主要集中在研究区中部和北部,中部的高值区与主城区相对应（图3i）,表明了Pb的人为来源,北部的高值区远离城区,并与湖相沉积物的分布一致。说明人类活动和土壤母质共同控制着Pb的分布。
Cd主要分布在北部的花官镇、丁庄镇以及中部的稻庄镇（图3b）,均为以农业种植为主的大镇,其中花官镇和稻庄镇形成规模化的大蒜种植,丁庄镇以冬枣为特色,冬枣对磷肥有较大需求量^[48],是导致区域Cd出现高值区的重要因素。Cd在北部与东南部的高值区与湖相沉积物相对应,根据单因素方差分析,Cd在湖相沉积物中的平均含量高于其他母质类型,说明了化肥施用和成土母质的高本底值是导致Cd高值区的主要因素。

3.4 土壤重金属生态风险评价

根据潜在生态风险的相关研究,单因子生态危害指数

E

与综合生态危害指数

RI

的分级标准需要根据所研究的污染物数量和毒性响应系数进行调整^[1,28,49]。经过调整后的分级标准见表6。
Tab. 6
表6
表6广饶土壤重金属生态风险等级
Tab. 6Ratings of potential ecological risk of heavy metals in soils from Guangrao county

单因子风险		综合风险
等级	得分	等级	得分
低风险	<40	低风险	<118
中等风险	40~80	中等风险	118~236
较高风险	80~160	高风险	236~472
高风险	160~320	极高风险	>472
极高风险	>320

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利用公式（1）计算,As、Cd、Co、Cr、Cu、Hg、Mn、Ni、Pb和Zn的生态风险平均值分别为12.12、57.48、4.73、2.12、5.38、94.88、1.06、5.90、4.62和1.10,重金属元素顺序为Hg>Cd>As>Ni>Cu>Co>Pb>Cr>Zn>Mn。根据调整后的生态风险分级标准,As、Co、Cr、Cu、Mn、Ni、Pb和Zn总体上为低生态风险,Cd和Hg分别为中等和较高生态风险。在研究区中西部的高值区存在Hg含量极高的样点,达到0.537 mg·kg^-1,是山东省背景值的33.56倍,通过之前重金属单因素方差分析和空间分布的研究,说明Hg在城区存在高富集现象,也解释了Hg较高生态风险的原因,需要引起警惕。
研究区的综合生态风险指数为189.39,为中等风险中的偏高水平。其中,17个样点为低风险等级,主要分布在远离城区的东北部（图4）,面积为72 km²,占总面积的6.3%,对应了重金属平均含量较低的海积物;259个样点处于中等生态风险级别,面积最大,为979 km²,占总面积的86%,中等生态风险区域与高重金属含量的湖相沉积物、城镇建设用地以及大量施用化肥的农业用地相对应;处于高生态风险等级的样点有23个,主要分布在主城区及其周围,面积为88 km²,占总面积的7.7%;只有1个样点为极高风险,同样位于主城区,说明剧烈的人类活动导致了该区域的高生态风险。总体来说,研究区具有一定的重金属生态风险,土壤重金属存在较高程度的富集。研究区综合生态风险水平的高值区域已经初步呈现面状分布的趋势。

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图4广饶县土壤重金属综合潜在生态风险分布图
-->Fig. 4Spatial distribution of potential ecologic risk index of heavy metals in Guangrao county
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4 结论

（1）研究区所测定的10种重金属元素,除Co和Mn没有可参考值,其余元素的平均含量均低于国家二级标准值。Co和Pb的平均值低于背景值,其余元素的平均含量均高于山东省背景值,特别是Cd与Hg有较为明显的富集,分别为背景值的1.86倍和2.50倍。
（2）研究区土壤重金属来源：As、Co、Cr、Cu、Mn、Ni和Zn主要来源于土壤母质;Hg在城镇建设用地中的含量最高,主要来源于煤炭燃烧、工业排放等人类工业活动;Cd和Pb同时在两个主成分上具有相当的载荷,受自然和人为源的共同控制。
（3）As、Co、Cr、Cu、Mn、Ni和Zn的高值区主要分布在研究区北部黄河冲积物和湖相沉积物发育的土壤;Hg的高值区对应了城区以及工业集中区;Pb主要分布在湖相沉积物以及城区土壤;Cd的高值区出现在研究区北部、中部和南部,化肥的施用以及高本底值的土壤母质导致了其高值区。
（4）Hg和Cd分别处于较高及中等生态风险等级,其余元素为低风险等级。研究区总体上处于中等生态风险的偏高水平,东北部区域综合生态风险水平最低,高生态风险等级集中在城区及周围,其他区域处于中等生态风险。
The authors have declared that no competing interests exist.

参考文献原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子

[1]	马建华, 王晓云, 侯千, 等. 某城市幼儿园地表灰尘重金属污染及潜在生态风险 . 地理研究, 2011, 30(3): 486-495.https://doi.org/10.11821/yj2011030009 URL [本文引用: 4]摘要选取河南省某市31个幼儿园采集地表灰尘样品,用火焰原子吸收分光光度法测定其Zn、Pb、Cr、Cu和Ni含量,应用地积累指数法和潜在生态风险指数法探讨了灰尘重金属的污染特征和潜在生态风险。结果表明:城区幼儿园灰尘Zn、Pb、Cr、Cu和Ni的平均含量分别是郊区对照幼儿园的1.93、2.13、5.45、1.90和0.98倍;Pb、Zn、Cr和Cu属于人为源重金属,Ni属于混合源重金属。灰尘Pb污染比较严重,Ni和Zn多为轻污染或偏中污染,Cu和Cr污染较轻。所有幼儿园的灰尘重金属潜在生态总风险均在强烈风险以上,Pb对生态总风险的平均贡献率达70.34%,是最主要的风险因子。潜在生态总风险指数(RI)的分级标准必须根据所研究的污染物数目及其毒性响应系数大小进行调整。 [Ma Jianhua, Wang Xiaoyun, Hou Qian, et al.Pollution and potential ecological risk of heavy metals in surface dust on urban kindergartens . Geographical Research, 2011, 30(3): 486-495.]https://doi.org/10.11821/yj2011030009 URL [本文引用: 4]摘要选取河南省某市31个幼儿园采集地表灰尘样品,用火焰原子吸收分光光度法测定其Zn、Pb、Cr、Cu和Ni含量,应用地积累指数法和潜在生态风险指数法探讨了灰尘重金属的污染特征和潜在生态风险。结果表明:城区幼儿园灰尘Zn、Pb、Cr、Cu和Ni的平均含量分别是郊区对照幼儿园的1.93、2.13、5.45、1.90和0.98倍;Pb、Zn、Cr和Cu属于人为源重金属,Ni属于混合源重金属。灰尘Pb污染比较严重,Ni和Zn多为轻污染或偏中污染,Cu和Cr污染较轻。所有幼儿园的灰尘重金属潜在生态总风险均在强烈风险以上,Pb对生态总风险的平均贡献率达70.34%,是最主要的风险因子。潜在生态总风险指数(RI)的分级标准必须根据所研究的污染物数目及其毒性响应系数大小进行调整。
[2]	吕建树, 张祖陆, 刘洋, 等. 日照市土壤重金属来源解析及环境风险评价 . 地理学报, 2012, 67(7): 109-122.https://doi.org/10.11821/xb201207010 URL [本文引用: 4]摘要选择日照市的东港区和岚山区为研究区,采集了445个0~20cm表层土壤样品,并测定了10种重金属元素的含量;采用多元统计和地统计分析,揭示了研究区土壤重金属污染的主要来源以及与土地利用、成土母质之间的关系,绘制了重金属的环境风险概率的空间分布图。结果表明:①As、Co、Cr和Cu的平均值低于山东省东部地区土壤背景值,Cd、Hg、Mn、Ni、Pb和Zn的平均值高于背景值,尤其是Cd、Hg的含量分别为背景值的1.85和1.38倍,土壤中重金属累积较为明显。②10种元素可被辩识出4个主成分(PCs),PC1(Co、Cr、Mn、Ni和Zn)和PC3(As、Cu)为自然源因子,PC2(Cd、Pb)为工农业及交通源因子,PC4(Hg)为工业源因子;其中Pb、Zn在PC1和PC3上均有较大载荷,受地质背景和人类活动的共同控制。③Cd、Hg含量在不同的覆被类型有显著差异,在城镇建设用地的含量最高;Co、Cr、Cu、Mn和Ni在花岗岩和变质岩母质的含量高,与冲积与海积物母质有较大差异。④来自于同一主成分的元素及元素组合的环境风险空间格局与相应主成分插值结果基本一致,所有重金属综合环境风险的高值区在西部和东部呈点状分布,主要是由西部的高地质背景和东部的强烈人为干扰的综合作用造成的。 [Lv Jianshu, Zhang Zulu, Liu Yang, et al.Sources identification and hazardous risk delineation of heavy metals contamination in Rizhao city . Acta Geographica Sinica, 2012, 67(7): 109-122.]https://doi.org/10.11821/xb201207010 URL [本文引用: 4]摘要选择日照市的东港区和岚山区为研究区,采集了445个0~20cm表层土壤样品,并测定了10种重金属元素的含量;采用多元统计和地统计分析,揭示了研究区土壤重金属污染的主要来源以及与土地利用、成土母质之间的关系,绘制了重金属的环境风险概率的空间分布图。结果表明:①As、Co、Cr和Cu的平均值低于山东省东部地区土壤背景值,Cd、Hg、Mn、Ni、Pb和Zn的平均值高于背景值,尤其是Cd、Hg的含量分别为背景值的1.85和1.38倍,土壤中重金属累积较为明显。②10种元素可被辩识出4个主成分(PCs),PC1(Co、Cr、Mn、Ni和Zn)和PC3(As、Cu)为自然源因子,PC2(Cd、Pb)为工农业及交通源因子,PC4(Hg)为工业源因子;其中Pb、Zn在PC1和PC3上均有较大载荷,受地质背景和人类活动的共同控制。③Cd、Hg含量在不同的覆被类型有显著差异,在城镇建设用地的含量最高;Co、Cr、Cu、Mn和Ni在花岗岩和变质岩母质的含量高,与冲积与海积物母质有较大差异。④来自于同一主成分的元素及元素组合的环境风险空间格局与相应主成分插值结果基本一致,所有重金属综合环境风险的高值区在西部和东部呈点状分布,主要是由西部的高地质背景和东部的强烈人为干扰的综合作用造成的。
[3]	戴彬, 吕建树, 战金成, 等. 山东省典型工业城市土壤重金属来源、空间分布及潜在生态风险评价 . 环境科学, 2015, 36(2): 507-515.https://doi.org/10.13227/j.hjkX.2015.02.018 URL [本文引用: 1]摘要选取山东省典型工业城市——莱芜市钢城区为研究区域,系统采集了106个表层土壤样品,测定了As、Cd、Co、Cr、Cu、Hg、Ni、Pb和Zn等9种重金属的含量,分别利用多元统计和地统计方法分析了重金属的来源和空间分布特征,最后对土壤重金属的潜在生态风险进行了评价.结果表明:1研究区9种重金属元素的平均含量均超过了山东省土壤背景值,其中Cd、Hg、Pb和Zn的平均值分别是背景值的2.42、4.69、1.74和1.54倍,在表层土壤中存在明显的富集.2Cd、Pb和Zn主要来源于工业"三废"、交通排放以及农药化肥的施用;Co、Cr和Ni为自然源因子,受到成土母质的控制;As和Hg来源于煤炭燃烧和钢铁冶炼,Cu受自然与人为因素共同影响.3研究区总体上处于中等与高生态风险的临界水平,其中Hg为高生态风险水平,Cd为中等生态风险水平,其他元素则均为低生态风险. [Dai Bin, Lv Jianshu, Zhan Jincheng, et al.Assessment of sources, spatial distribution and ecological risk of heavy metals in soils in a typical industry-based city of Shandong province . Environmental Science, 2015, 36(2): 507-515.]https://doi.org/10.13227/j.hjkX.2015.02.018 URL [本文引用: 1]摘要选取山东省典型工业城市——莱芜市钢城区为研究区域,系统采集了106个表层土壤样品,测定了As、Cd、Co、Cr、Cu、Hg、Ni、Pb和Zn等9种重金属的含量,分别利用多元统计和地统计方法分析了重金属的来源和空间分布特征,最后对土壤重金属的潜在生态风险进行了评价.结果表明:1研究区9种重金属元素的平均含量均超过了山东省土壤背景值,其中Cd、Hg、Pb和Zn的平均值分别是背景值的2.42、4.69、1.74和1.54倍,在表层土壤中存在明显的富集.2Cd、Pb和Zn主要来源于工业"三废"、交通排放以及农药化肥的施用;Co、Cr和Ni为自然源因子,受到成土母质的控制;As和Hg来源于煤炭燃烧和钢铁冶炼,Cu受自然与人为因素共同影响.3研究区总体上处于中等与高生态风险的临界水平,其中Hg为高生态风险水平,Cd为中等生态风险水平,其他元素则均为低生态风险.
[4]	Ghrefat H, Yusuf N. Assessing Mn, Fe, Cu, Zn, and Cd pollution in bottom sediments of Wadi Al-Arab Dam, Jordan . Chemosphere, 2006, 65(11): 2114-2121.https://doi.org/10.1016/j.chemosphere.2006.06.043 URLPMID:16875712 [本文引用: 1]摘要 Thirty five bottom sediment samples were collected in a grid pattern from Wadi Al-Arab Dam. The present study focuses on the levels of Mn, Fe, Cu, Zn, Cd, total organic matter (TOM) and carbonate content ( CO 3 - 2) in order to assess the extent of environmental pollution and to discuss the origin of these contaminants in sediments of the dam. Concentration data were processed using correlation analysis and factor analysis. The results of correlation analysis and factor analysis show low positive and negative correlations among Mn, Fe, Cu, Zn, Cd, TOM, and CO 3 - 2 and indicate that heavy metals in sediments of Wadi Al-Arab have different anthropogenic and natural sources. The results also confirm the complicated behavior of these pollutants, that can be influenced by many factors. Sediments pollution assessment was carried out using enrichment factor and the geoaccumulation index. The calculation of enrichment factors showed that Mn and Cu are depleted by 0.76, and 1.33, respectively, whereas Cu, Zn, and Cd are enriched by 3.6, and 30, respectively. The results of geoaccumulation index reveal that sediments of Wadi Al-Arab are uncontaminated with Mn, Fe, and Cu, moderately contaminated with Zn, and strongly to extremely contaminated with Cd. Some of the elevated concentration of Zn and Cd are probably due to anthropogenic sources nearby the dam site. These sources mainly include fertilizers and pesticides used in agricultural activities, and the effluent of Irbid City treatment plant. Environmental risks of Cd and Zn were evaluated using the risk assessment code (RAC) and sequential extraction method. Zn poses a low environmental risk, whereas Cd poses a medium environmental risk.
[5]	Lv J, Zhang Z, Li S, et al.Assessing spatial distribution, sources, and potential ecological risk of heavy metals in surface sediments of the Nansi Lake, Eastern China . Journal of Radioanalytical and Nuclear Chemistry, 2014, 299(3): 1671-1681.https://doi.org/10.1007/s10967-013-2883-2 URL [本文引用: 1]摘要 The study is conducted to investigate the spatial distribution, sources and ecological risk of seven heavy metals in surface sediments of Nansi Lake, Eastern China. A total of 29 samples were collected in surface sediments of Nansi Lake, and were analyzed for three nutrients (TN, TOC and TP), two major metals (Al and Fe), as well as seven trace metals (As, Cd, Cr, Cu, Hg, Pb and Zn). The mean concentrations of As, Cd, Cr, Cu, Hg, Pb, Zn, Fe and Al were 14.41, 0.22, 71.10, 30.1, 0.048, 29.14, 90.2, 30,816 and 70,653 mg kg 1 , respectively, and the mean contents of these metals were higher than the background values with the exception of Cu and Fe. The spatial distribution indicated that the contents of all seven heavy metals were characterized by relatively higher contents in the upper lake than the lower lake. The hotspots with high values of As, Cd and Hg were associated with the river mouths, and the hotspots of Pb were mainly located around the dam in the central part, while no significant associations were displayed between spatial distribution of Cr, Cu, Zn and the river mouths. The mean enrichment factor (EF) values of As, Cd, Hg and Pb were 2.03, 2.93, 3.21 and 2.18, respectively, showing their moderate enrichment, while Cr, Cu and Zn with mean EF values of 1.19, 0.89 and 1.01 were deficiency to minimal enrichment. Multivariate and geostatistical analyses suggested that PC1 controlled by Cr, Cu and Zn was a lithogenic component, and come from parent rocks leaching. PC2 including Cd and partially Hg represented the factor from industrial wastewater discharge. PC3 showed elevated loadings of As and partially Cd, and could be attributed to the agricultural practices. While PC4 including Pb and partially Hg, was dominated by coal combustion. The results of potential ecological risk suggested that sediment environment of Nansi Lake suffered from high ecological risk.
[6]	Alloway B J.Heavy Metals in Soils . London: Chapman and Hall, 1995. [本文引用: 1]
[7]	董立宽, 方斌. 茶园土壤重金属乡镇尺度下空间异质性分析: 以江浙优质名茶种植园为例 . 地理研究, 2017, 36(2): 391-404.https://doi.org/10.11821/dlyj201702016 URL [本文引用: 2]摘要随着经济社会的快速发展,茶园土壤重金属污染问题日趋严重,不仅影响茶叶的生长和品质,也威胁着人类的健康.以江浙两省优质名茶种植园为例,利用地统计学方法对茶园土壤重金属含量、相关关系及空间异质性等特征进行分析.结果表明:①东山镇土壤Zn超标率最高,达到67.50％;其次是溪龙乡土壤Se,达到50.00％;其他土壤重金属的超标率均比较低.②酸性条件及丰富的有机质有利于土壤Se的贮存,且土壤Se与土壤Cd、As极易共存,但不易与土壤Cu、Zn共存.③土壤重金属含量空间分布受结构性因素和随机性因素共同作用的影响,溪龙乡土壤Cd块金系数为0.890,受随机性因素影响最大;而溪龙乡土壤As块金系数为0.049,受随机性影响因素最小.④各重金属空间分布特征不同,为改善茶园土壤环境,提高茶叶品质,应结合重金属空间分布规律对其进行有效监管并提出有针对性的治理措施. [Dong Likuan, Fang Bin.Analysis of spatial heterogeneity of soil heavy metals in tea plantation: Case study of high quality tea garden in Jiangsu and Zhejiang . Geographical Research, 2017, 36(2): 391-404.]https://doi.org/10.11821/dlyj201702016 URL [本文引用: 2]摘要随着经济社会的快速发展,茶园土壤重金属污染问题日趋严重,不仅影响茶叶的生长和品质,也威胁着人类的健康.以江浙两省优质名茶种植园为例,利用地统计学方法对茶园土壤重金属含量、相关关系及空间异质性等特征进行分析.结果表明:①东山镇土壤Zn超标率最高,达到67.50％;其次是溪龙乡土壤Se,达到50.00％;其他土壤重金属的超标率均比较低.②酸性条件及丰富的有机质有利于土壤Se的贮存,且土壤Se与土壤Cd、As极易共存,但不易与土壤Cu、Zn共存.③土壤重金属含量空间分布受结构性因素和随机性因素共同作用的影响,溪龙乡土壤Cd块金系数为0.890,受随机性因素影响最大;而溪龙乡土壤As块金系数为0.049,受随机性影响因素最小.④各重金属空间分布特征不同,为改善茶园土壤环境,提高茶叶品质,应结合重金属空间分布规律对其进行有效监管并提出有针对性的治理措施.
[8]	Li Y, Gou X, Wang G, et al.Heavy metal contamination and source in arid agricultural soil in central Gansu province, China . Journal of Environmental Sciences, 2008, 20(5): 607-612.https://doi.org/10.1016/S1001-0742(08)62101-4 URLPMID:18575115 [本文引用: 2]摘要铜( Cu )的集中，铅( Pb )，铬( Cr )，水银( Hg )，和砷(作为)在在 Daba 村庄， Shajiawuan 村庄， Gangou 村庄和 Sifangwu 村庄里收集的干旱农业、灌溉的农业土壤被测量，在中央 Gansu 省定位了，除了 Hg 和 Pb 的 China.Concentrations 比在在选择干旱农业 soils.Pb 集中的灰石灰性土壤的背景价值由结果显示出的72.46% .These 在中国超过干旱农业土壤的阀值低有有 Pb 的确实严肃的污染，为在 Daba 村庄里的灌溉农业土壤的另外的选择金属的一个细微污染问题。种量分析(PCA ) 被用来估计土壤数据，使用有凯撒正规化的 varimax 旋转。结果证明灌溉因素，农业因素和人为的因素都贡献了在选择化学特性之间的关系。Cu 的累积的主要因素， Pb， Cr， Hg 并且这是石版印刷在干旱农业区域的逻辑因素。有 Cu 的起源的惹人注目的不同， Pb， Cr， Hg 并且作为在在 irrigate 农业和干旱农业之间的农业土壤。
[9]	Yang P, Mao R, Shao H, et al.The spatial variability of heavy metal distribution in the suburban farmland of Taihang Piedmont Plain, China . Comptes Rendus Biologies, 2009, 332(6): 558-566.https://doi.org/10.1016/j.crvi.2009.01.004 URLPMID:19520319 [本文引用: 2]摘要 The understanding of the spatial variability of soil heavy metals is an important precondition for suitably monitoring and evaluating eco-environment quality in a primary agricultural production zone. 100 topsoils were sampled from the Zhengding County of the urban-rural transition zone in Taihang Piedmont Plain, China. The contents of eight heavy metals Cu, Zn, Cr, Ni, Pb, Cd, Hg and As were tested for each soil sample, and their spatial patterns were analyzed by using the semivariogram approach of geostatistics, with which the kriging method was used to estimate the unobserved points. Then GIS technology was employed to produce spatial distribution maps of the 8 elements. The results showed that the concentration of Cd exceeded its background level. The local pollution from Cd was attributed to the anthropogenic influence. The concentrations of the eight heavy metals are relatively lower than the critical values of the national soil quality standard. The correlation distance of soil heavy metals ranged from 3.28 to 11.63 km, with the eight heavy metals having moderate spatial dependence. Cu, Cr, Ni, Pb and As were associated with and controlled by parent material. The spherical model was fitted to the semivariograms of Cu, Cr, Cd, Hg, Pb and As, and the Zn and Ni were fitted with the Gaussian model and the linear model, respectively. The results are helpful for improving agricultural and forest ecosystem in the region. To cite this article: P.G. Yang et al., C. R. Biologies 332 (2009).
[10]	方小红, 彭渤, 张坤, 等. 沅江下游入湖段河床沉积物重金属污染特征 . 地理研究, 2016, 35(10): 1887-1898.https://doi.org/10.11821/dlyj201610008 URL [本文引用: 1]摘要对沅江入湖沉积物进行钻探取样,利用等离子质谱仪(ICP-MS)对沉积物重金属进行分析.结果表明:重金属Ba、Sc、V、Th、U、Cu、Co、Ni、Cr等在沉积物中含量变化相对稳定,分布相对均匀;而Mn、Zn、Pb、Mo、Cd、T1、Bi等重金属的含量变化大,分布不均匀.重金属含量柱状剖面变化特征及富集系数(EF值)的计算结果显示:沉积物中Cd达显著富集,而Sc、V、Mn、Pb、Bi等为中等富集程度.沉积物中存在3个重金属富集层,即中下部Pb、TI、Bi富集层;中上部Pb、Cr、Ni、Cu富集层;浅表部V、Cr、Mn、Ni、Cu、Zn、Pb、Cd、T1、Bi等多种重金属富集层.地累积指数(Igeo)和综合富集指数(EI)评价结果显示:沅江人湖沉积物重金属污染程度自河床深部向浅部,污染程度趋于增强,污染元素组合趋于由Pb-Bi的单一元素组合向由V-Cr-Mn-Ni-Cu-Zn-Pb-Cd-Bi组成的复合元素组合变化.且自上游向下游,沉积物重金属污染程度趋于降低.这种重金属污染空间变化特征与区域人为活动有关,值得进一步研究. [Fang Xiaohong, Peng Bo, Zhang Kun, et al.Heavy metal contamination of bed sediments in inlet area of the lowermost Yuanjiang river, Hunan province of China . Geographical Research, 2016, 35(10): 1887-1898.]https://doi.org/10.11821/dlyj201610008 URL [本文引用: 1]摘要对沅江入湖沉积物进行钻探取样,利用等离子质谱仪(ICP-MS)对沉积物重金属进行分析.结果表明:重金属Ba、Sc、V、Th、U、Cu、Co、Ni、Cr等在沉积物中含量变化相对稳定,分布相对均匀;而Mn、Zn、Pb、Mo、Cd、T1、Bi等重金属的含量变化大,分布不均匀.重金属含量柱状剖面变化特征及富集系数(EF值)的计算结果显示:沉积物中Cd达显著富集,而Sc、V、Mn、Pb、Bi等为中等富集程度.沉积物中存在3个重金属富集层,即中下部Pb、TI、Bi富集层;中上部Pb、Cr、Ni、Cu富集层;浅表部V、Cr、Mn、Ni、Cu、Zn、Pb、Cd、T1、Bi等多种重金属富集层.地累积指数(Igeo)和综合富集指数(EI)评价结果显示:沅江人湖沉积物重金属污染程度自河床深部向浅部,污染程度趋于增强,污染元素组合趋于由Pb-Bi的单一元素组合向由V-Cr-Mn-Ni-Cu-Zn-Pb-Cd-Bi组成的复合元素组合变化.且自上游向下游,沉积物重金属污染程度趋于降低.这种重金属污染空间变化特征与区域人为活动有关,值得进一步研究.
[11]	王济, 张一修, 高翔. 城市地表灰尘重金属研究进展及展望 . 地理研究, 2012, 31(5): 821-830.https://doi.org/10.11821/yj2012050006 URL [本文引用: 1]摘要 Surface dust in urban areas is one of the important topics in urban environmental science.A review was given in this paper on the conceptual definition of surface dust in urban areas.The new concept and new understandings about surface dust in urban areas were put forward.Surface dust was sources and sinks of many pollutants as heavy metals and PAHs have environmental indicative function in urban areas.A review was given on the advances in the research on heavy metals of surface dust in urban areas in various aspects in this paper,such as content level,space-time distribution,transference and cycle,forms and bioavailability.The concentrations of heavy metals of surface dust in surface dust in urban areas were obviously higher than environmental background values in soil.The research on methods of spatial distribution of heavy metals were line type and face type.The concentrations of pollutants have changed over times.The main transporting medium of surface dust is atmosphere.The heavy metals in surface dust has exchangeable,carbonate combination,iron and manganese oxide combination,organic sulfide combination patterns and residua.The main sources of heavy metals in surface dust were traffic pollution,industrial pollution and urban construction.The sources identification methods included GIS spatial analysis,element tracer technology and multivariate analysis.The future development prospects were also pointed out.It is an urgent task to study the temporal variations such as diurnal changes,seasonal changes or non-seasonal changes by any factors control,the residence time in environment,particle classification as well as to establish standards and study the relationship between transfer characteristics and particle sizes,to optimize the regional human health effects and risk assessment model such as confirming the main routes of exposure,optimizing exposure calculation model and carrying out the human body health risk assessment. [Wang Ji, Zhang Yixiu, Gao Xiang.The advances in research on heavy metals of the surface dust in urban areas . Geographical Research, 2012, 31(5): 821-830.]https://doi.org/10.11821/yj2012050006 URL [本文引用: 1]摘要 Surface dust in urban areas is one of the important topics in urban environmental science.A review was given in this paper on the conceptual definition of surface dust in urban areas.The new concept and new understandings about surface dust in urban areas were put forward.Surface dust was sources and sinks of many pollutants as heavy metals and PAHs have environmental indicative function in urban areas.A review was given on the advances in the research on heavy metals of surface dust in urban areas in various aspects in this paper,such as content level,space-time distribution,transference and cycle,forms and bioavailability.The concentrations of heavy metals of surface dust in surface dust in urban areas were obviously higher than environmental background values in soil.The research on methods of spatial distribution of heavy metals were line type and face type.The concentrations of pollutants have changed over times.The main transporting medium of surface dust is atmosphere.The heavy metals in surface dust has exchangeable,carbonate combination,iron and manganese oxide combination,organic sulfide combination patterns and residua.The main sources of heavy metals in surface dust were traffic pollution,industrial pollution and urban construction.The sources identification methods included GIS spatial analysis,element tracer technology and multivariate analysis.The future development prospects were also pointed out.It is an urgent task to study the temporal variations such as diurnal changes,seasonal changes or non-seasonal changes by any factors control,the residence time in environment,particle classification as well as to establish standards and study the relationship between transfer characteristics and particle sizes,to optimize the regional human health effects and risk assessment model such as confirming the main routes of exposure,optimizing exposure calculation model and carrying out the human body health risk assessment.
[12]	Manta D S, Angelone M, Bellanca A, et al.Heavy metals in urban soils: A case study from the city of Palermo (Sicily), Italy . Science of the Total Environment, 2002, 300(1-3): 229-243.https://doi.org/10.1016/S0048-9697(02)00273-5 URLPMID:12685485 [本文引用: 1]摘要 Concentrations of V, Mn, Cd, Zn, Ni, Cr, Co, Cu, Pb, Hg and Sb were measured on 70 topsoil samples collected from green areas and parks in the city of Palermo (Sicily) in order to: (1) assess the distribution of these heavy metals in the urban environment; (2) discriminate natural and anthropic contributions; and (3) identify possible sources of pollution. Mineralogy, physico-chemical parameters, and major element contents of the topsoils were determined to highlight the influence of ‘natural’ features on the heavy metal concentrations and their distribution. Medians of Pb, Zn, Cu and Hg concentrations of the investigated urban soils are 202, 138, 63 and 0.68 mg kg 611, respectively. These values are higher, in some case by different orders of size, than those of unpolluted soils in Sicily that average 44, 122, 34 and 0.07 mg kg 611. An ensemble of basic and multivariate statistical analyses (cluster analysis and principal component analysis) was performed to reduce the multidimensional space of variables and samples, thus defining two sets of heavy metals as tracers of natural and anthropic influences. Results demonstrate that Pb, Zn, Cu, Sb and Hg can be inferred to be tracers of anthropic pollution, whereas Mn, Ni, Co, Cr, V and Cd were interpreted to be mainly inherited from parent materials. Maps of pollutant distribution were constructed for the whole urban area pointing to vehicle traffic as the main source of diffuse pollution and also showing the contribution of point sources of pollution to urban topsoils.
[13]	李晓燕, 陈同斌, 雷梅, 等. 北京城市广场及校园表土(灰尘)中重金属水平与健康风险 . 地理研究, 2010, 29(6): 989-996.https://doi.org/10.11821/yj2010060004 URL [本文引用: 2]摘要通过对北京市城市广场和学校表层土壤与相应的地表灰尘中重金属含量调查,探讨土壤与灰尘之间元素分布的差异及来源,评估青少年在校期间通过灰尘摄入重金属的健康风险。研究表明:城市广场和校园土壤中Cu、Pb和Zn、灰尘中As、Cu、Pb、Zn和Cd显著高于北京市土壤重金属背景值,土壤(灰尘)中As、Ni、Cu、Pb、Zn和Cd超过背景值的样本比率分别为67%(27%)、13%(63%)、83%(100%)、73%(100%)、83%(100%)和53%(100%)。土壤中Cu、Pb和Zn存在一定积累,灰尘中Cd、Cu、Pb和Zn积累较重。灰尘中Cu、Pb和Zn显著高于土壤。校园土壤中Ni显著高于城市广场土壤,其他元素两者之间差异不大;校园灰尘中Ni、Pb和Zn显著高于城市广场。中学生通过校园灰尘摄入没有导致明显的健康风险。 [Li Xiaoyan, Chen Tongbin, Lei Mei, et al.Concentrations and risk of heavy metals in surface soil and dust in urban squares and school campus in Beijing . Geographical Research, 2010, 29(6): 989-996.]https://doi.org/10.11821/yj2010060004 URL [本文引用: 2]摘要通过对北京市城市广场和学校表层土壤与相应的地表灰尘中重金属含量调查,探讨土壤与灰尘之间元素分布的差异及来源,评估青少年在校期间通过灰尘摄入重金属的健康风险。研究表明:城市广场和校园土壤中Cu、Pb和Zn、灰尘中As、Cu、Pb、Zn和Cd显著高于北京市土壤重金属背景值,土壤(灰尘)中As、Ni、Cu、Pb、Zn和Cd超过背景值的样本比率分别为67%(27%)、13%(63%)、83%(100%)、73%(100%)、83%(100%)和53%(100%)。土壤中Cu、Pb和Zn存在一定积累,灰尘中Cd、Cu、Pb和Zn积累较重。灰尘中Cu、Pb和Zn显著高于土壤。校园土壤中Ni显著高于城市广场土壤,其他元素两者之间差异不大;校园灰尘中Ni、Pb和Zn显著高于城市广场。中学生通过校园灰尘摄入没有导致明显的健康风险。
[14]	Cheng S.Heavy metal pollution in China: Origin, pattern and control . Environmental Science & Pollution Research International, 2003, 10(3): 192-198.https://doi.org/10.1065/espr2002.11.141.1 URLPMID:12846382 [本文引用: 1]摘要 http://link.springer.com/article/10.1065%2Fespr2002.11.141.1
[15]	Kachenko A G, Singh B.Heavy metals contamination in vegetables grown in urban and metal smelter contaminated sites in Australia . Water Air & Soil Pollution, 2006, 169(1-4): 101-123.https://doi.org/10.1007/s11270-006-2027-1 URL [本文引用: 1]摘要 Dietary exposure to heavy metals, namely cadmium (Cd), lead (Pb), zinc (Zn) and copper (Cu), has been identified as a risk to human health through the consumption of vegetable crops. This study investigates the source and magnitude of heavy metal contamination in soil and vegetable samples at 46 sites across four vegetable growing regions in New South Wales, Australia. The four regions Boolaroo, Port Kembla, Cowra and the Sydney Basin were a mix of commercial and residential vegetable growing areas. The extent of metal contamination in soils sampled was greatest in regions located in the vicinity of smelters, such as in Boolaroo and Port Kembla. Soil metal concentrations decreased with depth at these two sites, suggesting contamination due to anthropogenic activities. Cadmium, Pb and Zn contamination was greatest in vegetables from Boolaroo, and Cu concentrations were greatest in vegetables sampled from Port Kembla. At Boolaroo, nearly all the samples exceeded the Australian Food Standards maximum level (ML) (0.01 mg kg 1 fresh weight) of Cd and Pb in vegetables. Over 63% of samples exceeded international food standard guidelines set by the Commission of the European Communities and the Codex Alimentarius Commission. All vegetables sampled from Cowra, which is a relatively pristine site had Cd and Pb levels below the Australian and international food standards guideline values. This study suggests that the Australian guideline values are more conservative in defining the ML for Cd and Pb in vegetable crops. This investigation highlights the increased danger of growing vegetables in the vicinity of smelters.
[16]	楚纯洁, 周金风. 平顶山矿区丘陵坡地土壤重金属分布及污染特征 . 地理研究, 2014, 33(7): 1383-1392.https://doi.org/10.11821/dlyj201407017 URL [本文引用: 1]摘要 An attempt was made to investigate the influence of mining activities upon the hilly upland soil around Pingdingshan coal mining area. Topsoil samples were collected from this area. Subsequently, the contents of five heavy metals, including Cu, Zn, Cr, Ni and Pb, were determined by means of the standard analysis methods of soil chemical composition. We analyzed their distribution characteristics at different altitudes and at different distances off the wind direct from the mining area, and evaluated the conditions of soil heavy metal pollution by adopting geo-accumulation index. The results are shown as follows. 1) The accumulations of heavy metals mentioned above were different from each other at different extents in the hilly upland soil around Pingdingshan coal mining area, in which Ni was the most significant, followed by Cr, Cu and Pb in turn. 2) The higher concentrations of five heavy metals at different altitudes were found in the mining zone, near slope bottom and slope top respectively. On the other hand, the highest concentrations were found within a distance of 50 m off the wind direct from the mining area, and contents of five heavy metals decreased as the distance increase. 3) Contents of Cu, Cr and Pb increase with the slope reduction, while the lowest contents of Zn and Ni were found in soils of slope from 5 to 15 . However, land use patterns showed no effects on the distributions of heavy metals in the upland soil around Pingdingshan coal mining area. Moreover, the contents of five heavy metals between forest land, grassland and arable land were not significantly different. 4) Cu, Zn, Cr, Ni and Pb pollutions were all found in the mining zone, and Cu, Ni and Pb pollutions were also found on the slopes below the mining zone, yet soils in slopes above the mining zone were only lightly polluted by Ni. Cu and Ni were the main pollution elements in downwind direction, with light to intermediate pollutions at different distances. Cr and Pb showed light pollutions within a distance of 50 m off the wind. Otherwise, Zn still kept clean in downwind direction. 5) Ni, Cu and Pb contaminations in the hilly upland soil around Pingdingshan coal mining area were caused mainly by human activities. In contrast, Zn and Cr were chiefly from natural sources. [Chu Chunjie, Zhou Jinfeng.Distribution and pollution of soil heavy metals in hilly upland around Pingdingshan coal mining area . Geographical Research, 2014, 33(7): 1383-1392.]https://doi.org/10.11821/dlyj201407017 URL [本文引用: 1]摘要 An attempt was made to investigate the influence of mining activities upon the hilly upland soil around Pingdingshan coal mining area. Topsoil samples were collected from this area. Subsequently, the contents of five heavy metals, including Cu, Zn, Cr, Ni and Pb, were determined by means of the standard analysis methods of soil chemical composition. We analyzed their distribution characteristics at different altitudes and at different distances off the wind direct from the mining area, and evaluated the conditions of soil heavy metal pollution by adopting geo-accumulation index. The results are shown as follows. 1) The accumulations of heavy metals mentioned above were different from each other at different extents in the hilly upland soil around Pingdingshan coal mining area, in which Ni was the most significant, followed by Cr, Cu and Pb in turn. 2) The higher concentrations of five heavy metals at different altitudes were found in the mining zone, near slope bottom and slope top respectively. On the other hand, the highest concentrations were found within a distance of 50 m off the wind direct from the mining area, and contents of five heavy metals decreased as the distance increase. 3) Contents of Cu, Cr and Pb increase with the slope reduction, while the lowest contents of Zn and Ni were found in soils of slope from 5 to 15 . However, land use patterns showed no effects on the distributions of heavy metals in the upland soil around Pingdingshan coal mining area. Moreover, the contents of five heavy metals between forest land, grassland and arable land were not significantly different. 4) Cu, Zn, Cr, Ni and Pb pollutions were all found in the mining zone, and Cu, Ni and Pb pollutions were also found on the slopes below the mining zone, yet soils in slopes above the mining zone were only lightly polluted by Ni. Cu and Ni were the main pollution elements in downwind direction, with light to intermediate pollutions at different distances. Cr and Pb showed light pollutions within a distance of 50 m off the wind. Otherwise, Zn still kept clean in downwind direction. 5) Ni, Cu and Pb contaminations in the hilly upland soil around Pingdingshan coal mining area were caused mainly by human activities. In contrast, Zn and Cr were chiefly from natural sources.
[17]	Lu A, Wang J, Qin X, et al.Multivariate and geostatistical analyses of the spatial distribution and origin of heavy metals in the agricultural soils in Shunyi, Beijing, China . Science of the Total Environment, 2012, 425(1): 66-74.https://doi.org/10.1016/j.scitotenv.2012.03.003 URLPMID:22459886 [本文引用: 1]摘要 An extensive survey was conducted in this study to determine the spatial distribution and possible sources of heavy metals in the agricultural soils in Shunyi, a representative agricultural suburb in Beijing, China. A total of 412 surface soil samples were collected at a density of one sample per km(2), and concentrations of As, Cd, Cu, Hg, Pb and Zn were analyzed. The mean values of the heavy metals were 7.85 +/- 2.13, 0.136 +/- 0.061, 22.4 +/- 631, 0.073 +/- 0.049, 20.4 +/- 52, and 69.8 +/- 16.5 mg kg(-1) for As, Cd, Cu, Hg, Pb, and Zn, respectively, slightly higher than their background values of Beijing topsoil with the exception of Pb. but lower than the guideline values of Chinese Environmental Quality Standard for Soils. Multivariate and geostatistical analyses suggested that soil contamination of Cd, Cu and Zn was mainly derived from agricultural practices. Whereas, As and Pb were due mainly to soil parent materials, and Hg was caused by the atmospheric deposits from Beijing City. The identification of heavy metal sources in agricultural soils is a basis for undertaking appropriate action to protect soil quality. (C) 2012 Elsevier B.V. All rights reserved.
[18]	Rodríguez Martín J A, Arias M L, Grau Corbí J M. Heavy metals contents in agricultural topsoils in the Ebro basin (Spain). Application of the multivariate geoestatistical methods to study spatial variations . Environmental Pollution, 2006, 144(3): 1001-1012.https://doi.org/10.1016/j.envpol.2006.01.045 URLPMID:16580763 [本文引用: 2]摘要 In this work the content of seven heavy metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) and other parameters (the pH, organic matter, carbonates and granulometric fraction) in agricultural topsoil in the Ebro basin are quantified, based on 624 samples collected according to an 8 by 8 km square mesh. The average concentrations (mg/kg) obtained were: Cd 0.415 ± 0.163, Cr 20.27 ± 13.21, Cu 17.33 ± 14.97, Ni 20.50 ± 22.71, Pb 17.54 ± 10.41, Zn 17.53 ± 24.19 and Hg 35.6 ± 42.05 μg/kg. The concentration levels are relatively low in areas of high pH and low organic matter content concentration. The results of factor analysis group Cd, Cu, Hg, Pb and Zn in F1 and Cr y Ni in F2. The spatial heavy metals component maps based on geostatistical analysis, show definite association of these factors with the soil parent material. The local anomalies (found in Cu, Zn and Pb) are attributed to anthropogenic influence.
[19]	Han Y M, Du P X, Cao J J, et al.Multivariate analysis of heavy metal contamination in urban dusts of Xi'an, Central China . Science of the Total Environment, 2006, 355(1-3): 176-186.https://doi.org/10.1016/j.scitotenv.2005.02.026 URLPMID:15885748 [本文引用: 1]摘要 Though there are many studies of heavy metal contaminations of urban dusts in developed countries, little attention has been paid to this kind of study in developing countries, including China. Therefore, a series of investigations were performed to provide heavy metal signatures of urban dusts and to evaluate potential sources in Xi'an, Shaanxi Province. Sixty-five samples of urban dusts were collected in Xi'an. Then Ag, Cr, Cu, Mn, Pb and Zn concentrations were determined by using atomic absorption spectrophotometry, and As, Hg and Sb concentrations by atomic fluorescence spectroscopy. The results indicate that, in comparison with Chinese soil, urban dusts in Xi'an have elevated metal concentrations as a whole, except those of arsenic and manganese. These concentration levels are comparable to those in other studies. Correlation coefficient analysis, principal component analysis (PCA) and cluster analysis (CA) were performed and three main sources with corresponding cluster elements were identified: (1) Ag and Hg have commercial and domestic sources; (2) Cr, Cu, Pb, Sb and Zn are mainly derived from industrial sources, combined with traffic sources as well for Pb and Zn; (3) As and Mn come mainly from soil sources, and As also has an industrial source. Based on PCA and CA analyses, manganese was selected as the reference element, and heavy metal enrichment factors (Efs) were calculated, which in turn further confirms the source identification. Also, Efs give an insight of human influence degree of urban dusts.
[20]	Tripathi R, Nayak A K, Shahid M, et al.Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging . Arabian Journal of Geosciences, 2015, 8(12): 10693-10703.https://doi.org/10.1007/s12517-015-2003-4 URL [本文引用: 1]摘要 Soil salinization is a major problem affecting 955 Mha globally and 7 Mha in India. Soil properties vary spatially and knowing the extent of spatial variability of soil physicochemical characteristics is highly essential for management of these soils and crop cultivation. This study was conducted in salt-affected coastal parts of eastern India, with the following objectives: (i) to explore the spatial variability of soil properties (soil electrical conductivity (ECe), soil pH, soil organic carbon (SOC), available soil nitrogen, available soil phosphorus, and available soil potassium) and fitting the semivariogram models; (ii) to estimate the values of soil properties at unsampled locations using geostatistical tools; and (iii) to prepare the spatial maps of soil properties using parameters of best fit semivariogram model and interpolation by ordinary kriging technique. A total of 132 soil samples were collected. Gaussian, exponential, circular, spherical, K-Bessel, and spherical semivariogram models were found to be the best fit for assessing the spatial variability in ECe, soil pH, SOC, available soil nitrogen, available soil phosphorus, and available soil potassium, respectively. The best fit model parameters were used to create the spatial maps for these soil properties by ordinary kriging. It was concluded that geostatistical and kriging tools can be used to estimate the value of soil properties at unsampled locations and ultimately to develop spatial maps for site-specific nutrient management.
[21]	Mendlewicz J, Crisafulli C, Calati R, et al.Concentration of toxic elements in topsoils of the metropolitan area of Mexico city: A spatial analysis using ordinary kriging and indicator kriging . Revista Internacional De Contaminacion Ambiental, 2015, 31(1): 47-62.https://doi.org/10.1016/j.neulet.2012.03.063 URLPMID:22487732 [本文引用: 1]摘要 Abstract In order to generate relevant information for decision-makers to protect the inhabitants of the Metropolitan Area of Mexico City, 89 samples of topsoil were collected in urban zones to assess the concentration of toxic elements. For this purpose, the concentration of Cr, Cu, Ni, Pb, V and Zn were quantified with X-ray fluorescence. To evaluate the pollution, we considered the maximum permissible limits, the contamination factor and the pollution load index. The spatial distribution was analyzed by geostatistical methods. Ordinary and indicator Kriging were applied to estimate the values at unmeasured sites and the proportion of the values exceeding the critical concentration for each element within a region. The study revealed that the Metropolitan Area of Mexico City has excessive environmental problems related to pollution. The concentrations of Cr and V are apparently not anthropic, while the high amounts of Cu, Zn and Pb are largely due to human activities. The pollution of Ni exhibits two single spots, while Cu and Zn contents are distributed from the city center towards the northern suburbs. The presence of Pb is spread evenly through the entire urbanized area. The probability maps clearly identify the most contaminated areas, which requires immediate action by local decision-makers
[22]	Lin Y P, Chang T K, Shih C W, et al.Factorial and indicator kriging methods using a geographic information system to delineate spatial variation and pollution sources of soil heavy metals . Environmental Geology, 2002, 42(8): 900-909.https://doi.org/10.1007/s00254-002-0600-5 URL [本文引用: 1]摘要 http://link.springer.com/article/10.1007%2Fs00254-002-0600-5
[23]	Reza S K, Baruah U, Singh S K, et al.Geostatistical and multivariate analysis of soil heavy metal contamination near coal mining area, Northeastern India . Environmental Earth Sciences, 2015, 73(9): 5425-5433.https://doi.org/10.1007/s12665-014-3797-1 URL [本文引用: 1]摘要 The spatial distribution and hazard assessment of heavy metals in the soils of surrounding agricultural fields affected by mine drainage of Ledo coal mining area of Tinsukia district, Assam, India, were investigated using statistics, geostatistics and geographic information system techniques. The amounts of Cr, Cd, Ni and Pb were determined from 83 soil samples collected within the contaminated area. The maps based on ordinary kriging showed that high concentrations of heavy metals were located in the low-lying paddy field and near coal mining site. Indicator kriged probability maps were prepared based on the concentrations to exceed permissible limit (MPL). It was seen that more than 95% of the studied area has a higher than 50% probability to exceed the MPL value of Pb and Ni. Multivariate statistical analyses and principal component analysis suggest that Cd and Pb are derived from anthropogenic sources, particularly coal mining activities, whereas Ni and Cr are derived from lithogenic and/or anthropogenic sources.
[24]	Mahmoudabadi E, Sarmadian F, Moghaddam R N.Spatial distribution of soil heavy metals in different land uses of an industrial area of Tehran (Iran) . International Journal of Environmental Science & Technology, 2015, 12(10): 3283-3298.https://doi.org/10.1007/s13762-015-0808-z URL [本文引用: 1]摘要 Vegetation and different land uses may affect the spatial distribution of heavy metals in soils. The objective of the current article was to study the impact of industrial activities and land use type on the distribution of heavy metals in soils of Chitgar Forrest Park, located in industrial zone in the west of Tehran City. The soil samples were taken from 116 sites in a regular sampling grid (25002×0225002m) at a depth of 0–2002cm, including three different land uses, needle leaf forests, broadleaf forests and rangeland. Nitric acid-extractable form of seven metals, Cu, Cd, Fe, Mn, Ni, Pb and Zn, and DTPA-extractable form of Cu, Fe, Mn and Zn were measured. Soil texture, pH, organic carbon, carbon-to-nitrogen ratio, percentage of calcium carbonate and electrical conductivity (EC) were also determined. According to the maps and background amounts, heavy metals were affected by industrial activities and road traffic. Proximity to heavy traffic highway of Tehran–Karaj and large autoindustry plants can be considered for increasing metal concentrations. Results of statistical methods (coefficient variation and cluster analysis), besides geostatistical analysis (variogram and map), showed that total concentrations of heavy metals are controlled by intrinsic and extrinsic factors in the studied area. Although land use type did not affect the alteration in the distribution of total concentrations of heavy metals, it changed the distribution of DTPA form of heavy metals in the soils through affecting the soil organic matter.
[25]	Zhang J, Wang Y, Liu J, et al.Multivariate and geostatistical analyses of the sources and spatial distribution of heavy metals in agricultural soil in Gongzhuling, Northeast China . Journal of Soils & Sediments, 2016, 16(2): 634-644.https://doi.org/10.1007/s11368-015-1225-0 URL [本文引用: 2]摘要 The content, source, and spatial distribution of heavy metals in soils are necessary to establish quality standard on a regional level, to assess the potential threat of metals to food safety and human health and to target policies of environment friendly and significant economic benefits. The surface horizons of 166 agricultural soils in Gongzhuling, a representative agricultural area in the black soil region, Northeast China, were sampled, and the total contents of Cu, Ni, Zn, Pb, Cr, and Cd were analyzed. Multivariate statistics and geostatistical analysis were combined in characterizing spatial distribution of heavy metals and determining their sources in this study. The mean values of the heavy metal concentrations were 19.6165±656.23, 27.1665±6511.85, 57.8265±6514.28, 28.3465±658.91, 53.0465±6519.27, and 0.10665±650.048 mg kg611 for Cu, Ni, Zn, Pb, Cr, and Cd, respectively, slightly higher than their background values of Siping topsoil, but lower than the guideline values of Chinese Environmental Quality Standard for soils with the exception of individual samples of Ni and Cd. Multivariate and geostatistical analyses suggested that Pb and Cd were related to anthropogenic activities, such as the atmospheric deposition of industrial soot, dust and aerosols and coal burning exhausts, the application of fertilizers, livestock manures and agrochemicals, and the disposal of anthropogenic wastes, whereas Cr and Zn were mainly due to the parent materials, and Cu and Ni displayed a mixed origin of both lithogenic and anthropogenic origin. The analyses of content and sources of heavy metals in agricultural soils are basis for undertaking appropriate action to protect soil quality.
[26]	吕建树, 刘洋, 张祖陆, 等. 鲁北滨海湿地生态旅游资源开发潜力评价及开发策略 . 资源科学, 2011, 33(9): 1788-1798.https://doi.org/10.3724/SP.J.1011.2011.00211 URL Magsci [本文引用: 1]摘要鲁北滨海湿地是山东省生态旅游的热点地区之一，对其开发潜力进行评价可为该区生态旅游资源的科学、合理开发提供依据。针对生态旅游资源开发潜力评价中的各种不确定性因素，从资源禀赋条件、旅游开发条件、生态环境条件、客源市场条件等4个方面建立一套包含42个评价指标的指标体系，利用层次分析法确定各层次评价指标的权重，构建了生态旅游资源开发潜力多层次灰色评价系统，对该区19处代表性生态旅游资源进行评价，评价结果与研究区实际情况基本一致，较为合理，可信度较高；针对研究区生态旅游资源开发潜力均集中在Ⅰ级-Ⅲ级、总体上资源开发空间大的特点及各地市间开发潜力的差异，提出了构建“一体两翼”的大黄河三角洲生态旅游带的总体开发战略和各地市的开发分工体系，并确定了相应的开发时序和空间格局。 [Lv Jianshu, Liu Yang, Zhang Zulu, et al.Evaluation of exploitation potential and formulation of development strategy of eco-tourism resources in coastal wetlands of northern Shandong province . Resources Science, 2011, 33(9): 1788-1798.]https://doi.org/10.3724/SP.J.1011.2011.00211 URL Magsci [本文引用: 1]摘要鲁北滨海湿地是山东省生态旅游的热点地区之一，对其开发潜力进行评价可为该区生态旅游资源的科学、合理开发提供依据。针对生态旅游资源开发潜力评价中的各种不确定性因素，从资源禀赋条件、旅游开发条件、生态环境条件、客源市场条件等4个方面建立一套包含42个评价指标的指标体系，利用层次分析法确定各层次评价指标的权重，构建了生态旅游资源开发潜力多层次灰色评价系统，对该区19处代表性生态旅游资源进行评价，评价结果与研究区实际情况基本一致，较为合理，可信度较高；针对研究区生态旅游资源开发潜力均集中在Ⅰ级-Ⅲ级、总体上资源开发空间大的特点及各地市间开发潜力的差异，提出了构建“一体两翼”的大黄河三角洲生态旅游带的总体开发战略和各地市的开发分工体系，并确定了相应的开发时序和空间格局。
[27]	Lv J, Liu Y, Zhang Z, et al.Factorial kriging and stepwise regression approach to identify environmental factors influencing spatial multi-scale variability of heavy metals in soils . Journal of Hazardous Materials, 2013, 261(13): 387-397.https://doi.org/10.1016/j.jhazmat.2013.07.065 URLPMID:23973471 [本文引用: 1]摘要 The knowledge about spatial variations of heavy metals in soils and their relationships with environmental factors is important for human impact assessment and soil management. Surface soils from Rizhao city, Eastern China with rapid urbanization and industrialization were analyzed for six key heavy metals and characterized by parent material and land use using GIS-based data. Factorial kriging analysis and stepwise multiple regression were applied to examine the scale-dependent relationships among heavy metals and to identify environmental factors affecting spatial variability at each spatial scale. Linear model of coregionalization fitting showed that spatial multi-scale variation of heavy metals in soils consisted of nugget effect, an exponential structure with the range of 12km (short-range scale), as well as a spherical structure with the range of 36km (long-range scale). The short-range variation of Cd, Pb and Zn were controlled by land use, with higher values in urban areas as well as cultivated land in mountain area, and were related to human influence; while parent material dominated the long structure variations of these elements. Spatial variations of Cr and Ni were associated with natural geochemical sources at short- and long-range scales. At both two scales, Hg dominated by land use, corresponded well to spatial distributions of urban areas, and was attributed to anthropic emissions and atmosphere deposition.
[28]	H?kanson L.An ecological risk index for aquatic pollution control: A sedimentological approach . Water Research, 1980, 14(8): 975-1001.https://doi.org/10.1016/0043-1354(80)90143-8 URL [本文引用: 4]摘要 The aim of this work has been to penetrate one of many possible avenues towards a potential ecological risk index to be used as a diagnostic tool for water pollution control purposes, i.e. to sort out which lakes/basins and substances should be given special attention. The work is based on the thesis that a sedimentological risk index for toxic substances in limnic systems should at least,account for the following four requirements.
[29]	Lv J, Liu Y, Zhang Z, et al.Identifying the origins and spatial distributions of heavy metals in soils of Ju county (Eastern China) using multivariate and geostatistical approach . Journal of Soils and Sediments, 2015, 15(1): 163-178.https://doi.org/10.1007/s11368-014-0937-x URL [本文引用: 2]
[30]	魏复盛, 陈静生, 吴燕玉, 等. 中国土壤环境背景值研究 . 环境科学, 1991, 12(4): 12-19.URL [本文引用: 3] [Wei Fusheng, Chen Jingsheng, Wu Yanyu, et al.Study on the background contents on elements of soils in China . Environmental Science, 1991, 12(4): 12-19.]URL [本文引用: 3]
[31]	国家环境保护局. GB15618-1995. 土壤环境质量标准. 北京: 中国标准出版社, 1995. [本文引用: 2] [National Environmental Protection Agency. GB15618-1995. Environmental Quality Standard for Soils. Beijing: China Standards Press, 1995.] [本文引用: 2]
[32]	Wilding L P.Spatial variability: Its documentation, accommodation and implication to soil surveys. In: Nielsen D R, Bouma J. Soil Spatial Variability . Wageningen: Publishing and Documentation Publishers, 1985: 166-194. [本文引用: 1]
[33]	Nanos N, Rodríguez Martín J A. Multiscale analysis of heavy metal contents in soils: Spatial variability in the Duero river basin (Spain) . Geoderma, 2012, 189-190(6): 554-562.https://doi.org/10.1016/j.geoderma.2012.06.006 URL [本文引用: 2]摘要 78 We identify the sources of seven heavy metals in the soils of Duero river basin. 78 We use a multiscale geostatistical method (factorial kriging). 78 Multiscale variation was detected for Hg but not for the rest of heavy metals. 78 Human-originated inputs are only relevant for Hg at the local scale of variation. 78 Large-scale variation in heavy metal concentrations was due to natural factors.
[34]	王关玉, 潘懋, 刘锡大, 等. 山东省土壤中元素含量与母质的关系 . 北京大学学报: 自然科学版, 1992, 28(4): 475-485.URL [本文引用: 1]摘要根据《全国土壤环境背景值研究》课题的总体设计和实施原则,在山东省境内布置了117个剖面,采集不同发生层次的土壤样品341个。样品严格按统一规定和要求进行加工,获得V、Cr、Mn、Co、Ni、Cu、Zn、Pb、Cd、Hg、As和F等12项元素的测定结果。全省四种主要的土壤类型是由12种不同成土母质发育而成的。本文重点讨论了不同母质及其土壤中元素含量的基本特征。研究表明,土壤中元素的自然含量水平主要取决于成土母质,不同母质的土壤中元素含量的差异是显著的。进一步比较表土与底土之间元素含量的差异,并作显著性检验。结果说明,全省土壤中某些元素的含量,明显受到人为因素的影响,特别是水系沉积物母质发育的土壤,极可能受到Pb、Cd和Hg的污染。 [Wang Guanyu, Pan Mao, Liu Xida, et al.On the relationship between the concentrations of elements in soil and the types of soil-forming parent material in Shandong province, China . Acta Scientiarum Naturalium Universitatis Pekinensis, 1992, 28(4): 475-485.]URL [本文引用: 1]摘要根据《全国土壤环境背景值研究》课题的总体设计和实施原则,在山东省境内布置了117个剖面,采集不同发生层次的土壤样品341个。样品严格按统一规定和要求进行加工,获得V、Cr、Mn、Co、Ni、Cu、Zn、Pb、Cd、Hg、As和F等12项元素的测定结果。全省四种主要的土壤类型是由12种不同成土母质发育而成的。本文重点讨论了不同母质及其土壤中元素含量的基本特征。研究表明,土壤中元素的自然含量水平主要取决于成土母质,不同母质的土壤中元素含量的差异是显著的。进一步比较表土与底土之间元素含量的差异,并作显著性检验。结果说明,全省土壤中某些元素的含量,明显受到人为因素的影响,特别是水系沉积物母质发育的土壤,极可能受到Pb、Cd和Hg的污染。
[35]	Facchinelli A, Sacchi E, Mallen L.Multivariate statistical and GIS-based approach to identify heavy metal sources in soils . Environmental Pollution, 2001, 114(3): 313-324.https://doi.org/10.1016/S0269-7491(00)00243-8 URLPMID:11584630 [本文引用: 2]摘要 The knowledge of the regional variability, the background values and the anthropic vs. natural origin for potentially harmful elements in soils is of critical importance to assess human impact and to fix guide values and quality standards. The present study was undertaken as a preliminary survey on soil contamination on a regional scale in Piemonte (NW Italy). The aims of the study were: (1) to determine average regional concentrations of some heavy metals (Cr, Co, Ni, Cu, Zn, Pb); (2) to find out their large-scale variability; (3) to define their natural or artificial origin; and (4) to identify possible non-point sources of contamination. Multivariate statistic approaches (Principal Component Analysis and Cluster Analysis) were adopted for data treatment, allowing the identification of three main factors controlling the heavy metal variability in cultivated soils. Geostatistics were used to construct regional distribution maps, to be compared with the geographical, geologic and land use regional database using GIS software. This approach, evidencing spatial relationships, proved very useful to the confirmation and refinement of geochemical interpretations of the statistical output. Cr, Co and Ni were associated with and controlled by parent rocks, whereas Cu together with Zn, and Pb alone were controlled by anthropic activities. The study indicates that background values and realistic mandatory guidelines are impossible to fix without an extensive data collection and without a correct geochemical interpretation of the data.
[36]	?ajn R, Halami? J, Peh Z, et al.Assessment of the natural and anthropogenic sources of chemical elements in alluvial soils from the Drava River using multivariate statistical methods . Journal of Geochemical Exploration, 2011, 110(3): 278-289.https://doi.org/10.1016/j.gexplo.2011.06.009 URL [本文引用: 1]
[37]	Bor?vka L, Vacek O, Jehli?ka J.Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils . Geoderma, 2005, 128(3-4): 289-300.https://doi.org/10.1016/j.geoderma.2005.04.010 URL [本文引用: 2]摘要 Distinguishing between different sources of potentially toxic elements in soils can be difficult. This paper describes an application of principal component analysis (PCA) to distinguish between geogenic enrichment and anthropogenic pollution with Be, Cd, Co, Cr, Cu, Hg, Ni, Pb, and Zn at 14 localities in Northern and North-eastern Czech Republic. Element speciation, profile distribution, and local geology were used to facilitate interpretation of the PCA results. Of the total element contents in the topsoil and subsoil, a group of non-polluting elements, comprising Co, Cr, Cu, Ni, and Zn, was identified by PCA. There were more non-polluting elements in the subsoil than in the topsoil. The silicate-bound fraction was the most abundant in their speciation. They are likely to be mainly of geogenic origin, therefore. Beryllium also probably originated mainly from parent rocks. However, it had a closer relationship with geogenic Hg and Pb. Cadmium, Pb, and Hg showed strong topsoil enrichment. In speciation, there were larger proportions of their mobile and mobilizable fractions. This implies a significant contribution of anthropogenic pollution to their soil content. In addition, sites with some geochemical anomaly and polluted sites were indicated by the PCA. The analysis provided a concise summary of the complex information on both the generally prevailing origin of potentially toxic elements and the origin of elements at individual sampling localities.
[38]	章明奎, 王浩, 张慧敏. 浙东海积平原农田土壤重金属来源辨识 . 环境科学学报, 2008, 28(10): 1946-1954.https://doi.org/10.3321/j.issn:0253-2468.2008.10.002 URL Magsci [本文引用: 2]摘要为了区别土壤中潜在有毒重金属是来源于成土母质还是人为的污染,在浙东海积平原农田选择了32个采样点,分别采集了耕作层(0～10cm)和心土层(40～50cm)土样,用标准化学分析方法分别测定了Cd、Cu、Cr、Co、Ni、Zn、Hg、Pb、Mo、As和Al含量,用元素剖面分布研究法、元素化学形态分析法和主成分分析法等综合方法探讨了农田土壤中重金属的来源.结果表明,研究区土壤中Cr、Co、Ni为非污染元素,主要来源于成土母质,平均含量在耕作层与心土层中较为接近,残留态是这些重金属绝对优势的化学形态.Cd、Cu、Zn、Hg和Pb为主要污染元素,其耕作层含量明显高于心土层,可提取形态的比例较高;其中,Cd、Cu、Zn和Pb有相似的人为污染来源,而Hg有不同的人为污染来源.土壤中的Mo和As的变化较为复杂,可能受成土母质和外源污染双重影响. [Zhang Mingkui, Wang Hao, Zhang Huimin.Distinguishing different sources of heavy metals in soils on the coastal plain of Eastern Zhejiang province . Acta Scientiae Circumstantiae, 2008, 28(10): 1946-1954.]https://doi.org/10.3321/j.issn:0253-2468.2008.10.002 URL Magsci [本文引用: 2]摘要为了区别土壤中潜在有毒重金属是来源于成土母质还是人为的污染,在浙东海积平原农田选择了32个采样点,分别采集了耕作层(0～10cm)和心土层(40～50cm)土样,用标准化学分析方法分别测定了Cd、Cu、Cr、Co、Ni、Zn、Hg、Pb、Mo、As和Al含量,用元素剖面分布研究法、元素化学形态分析法和主成分分析法等综合方法探讨了农田土壤中重金属的来源.结果表明,研究区土壤中Cr、Co、Ni为非污染元素,主要来源于成土母质,平均含量在耕作层与心土层中较为接近,残留态是这些重金属绝对优势的化学形态.Cd、Cu、Zn、Hg和Pb为主要污染元素,其耕作层含量明显高于心土层,可提取形态的比例较高;其中,Cd、Cu、Zn和Pb有相似的人为污染来源,而Hg有不同的人为污染来源.土壤中的Mo和As的变化较为复杂,可能受成土母质和外源污染双重影响.
[39]	郭伟, 孙文惠, 赵仁鑫, 等. 呼和浩特市不同功能区土壤重金属污染特征及评价 . 环境科学, 2013, 34(4): 1561-1567.URL [本文引用: 1]摘要选择呼和浩特市居民区、科教区、城市公园、商业区、道路、工业区和开发区为研究对象,共采集62个样品.通过分析不同功能区土壤重金属含量,采用单因子污染指数法和内梅罗综合污染指数法评价重金属污染程度,主成分分析重金属污染的成因和来源,旨在为防治城市土壤重金属污染提供理论依据.呼和浩特市不同功能区土壤7种重金属的含量表明,其中5种重金属的平均含量均超过内蒙古自治区土壤背景值,重金属Cu和Zn含量分别达到背景值的2.33倍和1.85倍;单因子污染指数评价表明,不同功能区土壤存在不同程度重金属的污染,重金属Cu在商业区呈重度污染.不同重金属元素平均污染程度为:CuZnCrMnAsNiPb;内梅罗综合污染指数评价表明,商业区污染最严重,呈重污染程度;其次是道路,污染水平为中度污染;科教区和城市公园污染程度最轻.不同功能区土壤重金属的综合污染指数大小为:商业区(3.03)城市道路(2.12)居民区(1.98)科教区(1.81)工业区(1.72)开发区(1.36)城市公园(1.28);主成分分析表明,呼和浩特市土壤不同重金属来源存在差异,其中Cr、Cu、Mn、Pb和Zn主要来自交通污染源和生活废弃物的堆放,Ni和As目前仍然主要受自然因素控制,来源于自然源.呼和浩特市土壤重金属的污染已经对城市生态系统的健康发展构成了一定程度的威胁. [Guo Wei, Sun Wenhui, Zhao Renxin, et al.Characteristic and evaluation of soil pollution by heavy metal in different functional zones of Hohhot . Environmental Science, 2013, 34(4): 1561-1567.]URL [本文引用: 1]摘要选择呼和浩特市居民区、科教区、城市公园、商业区、道路、工业区和开发区为研究对象,共采集62个样品.通过分析不同功能区土壤重金属含量,采用单因子污染指数法和内梅罗综合污染指数法评价重金属污染程度,主成分分析重金属污染的成因和来源,旨在为防治城市土壤重金属污染提供理论依据.呼和浩特市不同功能区土壤7种重金属的含量表明,其中5种重金属的平均含量均超过内蒙古自治区土壤背景值,重金属Cu和Zn含量分别达到背景值的2.33倍和1.85倍;单因子污染指数评价表明,不同功能区土壤存在不同程度重金属的污染,重金属Cu在商业区呈重度污染.不同重金属元素平均污染程度为:CuZnCrMnAsNiPb;内梅罗综合污染指数评价表明,商业区污染最严重,呈重污染程度;其次是道路,污染水平为中度污染;科教区和城市公园污染程度最轻.不同功能区土壤重金属的综合污染指数大小为:商业区(3.03)城市道路(2.12)居民区(1.98)科教区(1.81)工业区(1.72)开发区(1.36)城市公园(1.28);主成分分析表明,呼和浩特市土壤不同重金属来源存在差异,其中Cr、Cu、Mn、Pb和Zn主要来自交通污染源和生活废弃物的堆放,Ni和As目前仍然主要受自然因素控制,来源于自然源.呼和浩特市土壤重金属的污染已经对城市生态系统的健康发展构成了一定程度的威胁.
[40]	冯新斌, 仇广乐, 付学吾, 等. 环境汞污染 . 化学进展, 2009, 21(s1): 436-457. [本文引用: 1] [Feng Xinbin, Qiu Guangle, Fu Xuewu, et al.Mercury pollution in the environment . Progress in Chemistry, 2009, 21(s1): 436-457.] [本文引用: 1]
[41]	方凤满, 王起超. 土壤汞污染研究进展 . 生态环境学报, 2000, 9(4): 326-329.https://doi.org/10.3969/j.issn.1674-5906.2000.04.019 URL [本文引用: 1]摘要对国内外**近些年来对土壤汞污染研究的工作进展作了系统的综述。主要包括土壤汞污染的途径、迁移方式和治理办法。其中重点介绍了大气汞的干湿沉降、土壤汞的释放及生物修复治理土壤污染。最后，还介绍了土壤汞形态的分析方法以及土壤挥发性汞释放通量的测量方法。 [Fang Manfeng, Wang Qichao.A review on the studies on mercury pollution of soil . Ecology and Environmental Sciences, 2000, 9(4): 326-329.]https://doi.org/10.3969/j.issn.1674-5906.2000.04.019 URL [本文引用: 1]摘要对国内外**近些年来对土壤汞污染研究的工作进展作了系统的综述。主要包括土壤汞污染的途径、迁移方式和治理办法。其中重点介绍了大气汞的干湿沉降、土壤汞的释放及生物修复治理土壤污染。最后，还介绍了土壤汞形态的分析方法以及土壤挥发性汞释放通量的测量方法。
[42]	王梅, 黄标, 孙维侠, 等. 强烈人为作用下城镇周围汞的空间变异及其积累迁移规律 . 土壤学报, 2011, 48(3): 506-515.URL [本文引用: 1]摘要研究土壤中汞(Hg)元素积累的空间变异和迁移转化规律对土壤利用、环境评价和污染修复具有重要参考价值。本研究选择经济发展迅速的苏南某地为研究区域,对土壤、水稻和大气降尘中的Hg进行了详细分析。结果表明,该区域土壤全汞平均含量达1 345μg kg-1,有效汞(HC l-Hg)平均含量51μg kg-1,水稻Hg平均含量20μg kg-1,大气Hg沉降量为5.13 g km-230 d-1。土壤和水稻高含量Hg主要积聚于城镇周边,随着与城镇距离的增加其含量逐渐减少。大气Hg沉降量在空间上变化不大。进入土壤中的Hg主要在土壤表层0~20 cm范围内富集,但直至60 cm深处依然存在积累现象,整个剖面土壤活性态汞和半活性态汞含量占全汞的比例变化不大。研究区土壤出现了明显Hg积累,导致水稻Hg吸收明显增加,不少样点超过了国家土壤环境质量二级标准(300μg kg-1)和国家食品污染物限量标准(20μg kg-1),可能对环境和人体健康产生危害。较低的大气Hg沉降量和土壤积累的Hg已与土壤条件达到平衡的事实表明,目前Hg的积累已明显减少。今后应采取措施修复污染土壤或者通过改变作物种类来减少土壤Hg含量或抑制作物对Hg的吸收,达到环境治理的目的。 [Wang Mei, Huang Biao, Sun Weixia, et al.Spatial variability, accumulation and transfer of Hg in soils around towns under intensive human activities in the Yangtze River Delta region, China . Acta Pedologica Sinica, 2011, 48(3): 506-515.]URL [本文引用: 1]摘要研究土壤中汞(Hg)元素积累的空间变异和迁移转化规律对土壤利用、环境评价和污染修复具有重要参考价值。本研究选择经济发展迅速的苏南某地为研究区域,对土壤、水稻和大气降尘中的Hg进行了详细分析。结果表明,该区域土壤全汞平均含量达1 345μg kg-1,有效汞(HC l-Hg)平均含量51μg kg-1,水稻Hg平均含量20μg kg-1,大气Hg沉降量为5.13 g km-230 d-1。土壤和水稻高含量Hg主要积聚于城镇周边,随着与城镇距离的增加其含量逐渐减少。大气Hg沉降量在空间上变化不大。进入土壤中的Hg主要在土壤表层0~20 cm范围内富集,但直至60 cm深处依然存在积累现象,整个剖面土壤活性态汞和半活性态汞含量占全汞的比例变化不大。研究区土壤出现了明显Hg积累,导致水稻Hg吸收明显增加,不少样点超过了国家土壤环境质量二级标准(300μg kg-1)和国家食品污染物限量标准(20μg kg-1),可能对环境和人体健康产生危害。较低的大气Hg沉降量和土壤积累的Hg已与土壤条件达到平衡的事实表明,目前Hg的积累已明显减少。今后应采取措施修复污染土壤或者通过改变作物种类来减少土壤Hg含量或抑制作物对Hg的吸收,达到环境治理的目的。
[43]	方明, 吴友军, 刘红, 等. 长江口沉积物重金属的分布、来源及潜在生态风险评价 . 环境科学学报, 2013, 33(2): 563-569.URL Magsci [本文引用: 1]摘要为了解长江口潮滩沉积物中重金属的污染特征, 采用电感耦合等离子体发射光谱法(ICP-AES)分析了长江口北支、南支和杭州湾27个表层沉积物中Cu、Pb、Ni、Ag、As、Cd、Zn、Sn、Sb和Hg 10种重金属的含量,并对其分布、来源及生态风险进行了评价.结果表明,沉积物中10种重金属的含量和介于102.9~326.4 mg·kg<sup>-1</sup>之间,北支、南支和杭州湾的平均值分别为180.9、244.7 和155.6 mg·kg<sup>-1</sup>.方差分析结果表明,南支与北支、杭州湾平均含量之间均存在显著性差异(<em>p</em>< 0.01),南支因受沿岸工业污水和生活污水的影响污染加重.来源分析表明, 沉积物中大多数重金属的来源具有一定的相似性, 主要来源于各种工农业废水、船舶运输、农药和化肥污染,而Ag和Hg具有不同的来源.地积累指数评价结果表明,10种重金属的平均污染程度由高到低依次为:Cd>Hg>Sb>Ag>As>Cu>Zn>Ni>Sn>Pb, Hg和Cd在多数采样点分别为中度污染和偏重污染,南支Cd和Ag的污染程度高于北支和杭州湾,而在杭州湾Hg的污染程度高于北支和南支.潜在生态风险系数评价结果表明,长江口沉积物7种重金属潜在生态风险系数从高到低依次为: Cd>Hg>As>Cu>Ni>Pb>Zn,长江口沉积物的潜在生态风险主要由Cd和Hg引起, 两者的贡献分别为62.6%和34.0%, 各采样点7种重金属的潜在生态风险指数(RI)介于565.9~1601之间, 均达到极强生态风险. [Fang Ming, Wu Youjun, Liu Hong, et al.Distribution, sources and ecological risk assessment of heavy metals in sediments of the Yangtze River estuary . Acta Scientiae Circumstantiae, 2013, 33(2): 563-569.]URL Magsci [本文引用: 1]摘要为了解长江口潮滩沉积物中重金属的污染特征, 采用电感耦合等离子体发射光谱法(ICP-AES)分析了长江口北支、南支和杭州湾27个表层沉积物中Cu、Pb、Ni、Ag、As、Cd、Zn、Sn、Sb和Hg 10种重金属的含量,并对其分布、来源及生态风险进行了评价.结果表明,沉积物中10种重金属的含量和介于102.9~326.4 mg·kg<sup>-1</sup>之间,北支、南支和杭州湾的平均值分别为180.9、244.7 和155.6 mg·kg<sup>-1</sup>.方差分析结果表明,南支与北支、杭州湾平均含量之间均存在显著性差异(<em>p</em>< 0.01),南支因受沿岸工业污水和生活污水的影响污染加重.来源分析表明, 沉积物中大多数重金属的来源具有一定的相似性, 主要来源于各种工农业废水、船舶运输、农药和化肥污染,而Ag和Hg具有不同的来源.地积累指数评价结果表明,10种重金属的平均污染程度由高到低依次为:Cd>Hg>Sb>Ag>As>Cu>Zn>Ni>Sn>Pb, Hg和Cd在多数采样点分别为中度污染和偏重污染,南支Cd和Ag的污染程度高于北支和杭州湾,而在杭州湾Hg的污染程度高于北支和南支.潜在生态风险系数评价结果表明,长江口沉积物7种重金属潜在生态风险系数从高到低依次为: Cd>Hg>As>Cu>Ni>Pb>Zn,长江口沉积物的潜在生态风险主要由Cd和Hg引起, 两者的贡献分别为62.6%和34.0%, 各采样点7种重金属的潜在生态风险指数(RI)介于565.9~1601之间, 均达到极强生态风险.
[44]	鲁如坤, 时正元. 我国磷矿磷肥中镉的含量及其对生态环境影响的评价 . 土壤学报, 1992, 29(2): 150-157.https://doi.org/10.1007/BF02677083 [本文引用: 1]摘要 Total 67 rock phosphate samples collected from 36 phosphate deposits and 30 phosphate fertilizer samples from main phosphate plants of China were studied.The content of Cd in rock phosphates from different deposits varied from 0.1 to 571 mg/kg, with an average value of 15.3 74 mg/kg. The highist value was found in the rock phosphates from Guangxi Province, varying from 12.2 to 571 mg/kg; while the lowest Cd content of the rock phosphates from Hubei Province varied from less than 1 to 2.10 mg/kg. Fortunarely. all the phosphate deposits of high Cd content are of less importance in the phosphate fertilizer production of China. If not counting these minor important but high Cd content phophase rocks the average Cd content of phosphate rocks of China should be 0.98 mg/kg. [Lu Rukun, Shi Zhengyuan.Cadmium contents of rock phosphates and phosphate fertilizers of China and their effects on ecological environment . Acta Pedologica Sinica, 1992, 29(2): 150-157.]https://doi.org/10.1007/BF02677083 [本文引用: 1]摘要 Total 67 rock phosphate samples collected from 36 phosphate deposits and 30 phosphate fertilizer samples from main phosphate plants of China were studied.The content of Cd in rock phosphates from different deposits varied from 0.1 to 571 mg/kg, with an average value of 15.3 74 mg/kg. The highist value was found in the rock phosphates from Guangxi Province, varying from 12.2 to 571 mg/kg; while the lowest Cd content of the rock phosphates from Hubei Province varied from less than 1 to 2.10 mg/kg. Fortunarely. all the phosphate deposits of high Cd content are of less importance in the phosphate fertilizer production of China. If not counting these minor important but high Cd content phophase rocks the average Cd content of phosphate rocks of China should be 0.98 mg/kg.
[45]	Zhong X, Zhou S, Zhu Q, et al.Fraction distribution and bioavailability of soil heavy metals in the Yangtze River Delta: A case study of Kunshan city in Jiangsu province, China . Journal of Hazardous Materials, 2011, 198(2): 13-21.https://doi.org/10.1016/j.jhazmat.2011.10.003 URLPMID:22018863 [本文引用: 1]摘要 http://linkinghub.elsevier.com/retrieve/pii/S0304389411012313
[46]	吕建树, 何华春. 江苏海岸带土壤重金属来源解析及空间分布 . 环境科学, 2018, 39(6): 2853-2864.URL [本文引用: 1]摘要以江苏省响水如东段海岸带为研究区,系统采集了239个表层土壤样品,分析测试了Cd、Cr、Cu、Hg、Ni、Pb和Zn等7种重金属元素,综合运用多元统计和地统计方法,探讨了研究区土壤重金属的主要来源,绘制了重金属的空间分布图.结果表明:(1)江苏响水如东段海岸带土壤Cd、Cr、Cu、Hg、Ni、Pb和Zn的平均含量分别为0.14、64.23、24.15、0.026、29.16、22.24和77.94 mg·kg~(-1),Cd、Cu、Hg、Pb和Zn存在较为明显的富集,Cr和Ni的平均值低于江苏滨海土壤背景值.(2)Cd、Cr、Cu、Ni、Pb和Zn在海积物母质发育土壤中的含量显著低于河流冲积物、潟湖相沉积物和三角洲沉积物母质;Cd、Cu、Hg、Pb和Zn在城镇建设用地的平均含量显著高于其他地类.(3)Cr和Ni为自然来源元素,受到成土母质的控制;Cd、Cu、Pb和Zn受到成土母质和人类活动的共同影响,人为源主要包括工业、交通排放和农业活动;Hg为人为来源,受到人为排放的大气沉降的影响.(4)Cd、Cu、Pb和Zn的高值区分布在研究区的北部、南部和西部,Hg的高值区分布在研究区的西部和南部的城镇密集区. [Lv Jianshu, He Huachun.Identifying the origins and spatial distributions of heavy metals in soils of Jiangsu coast . Environmental Science, 2018, 39(6): 2853-2864.]URL [本文引用: 1]摘要以江苏省响水如东段海岸带为研究区,系统采集了239个表层土壤样品,分析测试了Cd、Cr、Cu、Hg、Ni、Pb和Zn等7种重金属元素,综合运用多元统计和地统计方法,探讨了研究区土壤重金属的主要来源,绘制了重金属的空间分布图.结果表明:(1)江苏响水如东段海岸带土壤Cd、Cr、Cu、Hg、Ni、Pb和Zn的平均含量分别为0.14、64.23、24.15、0.026、29.16、22.24和77.94 mg·kg~(-1),Cd、Cu、Hg、Pb和Zn存在较为明显的富集,Cr和Ni的平均值低于江苏滨海土壤背景值.(2)Cd、Cr、Cu、Ni、Pb和Zn在海积物母质发育土壤中的含量显著低于河流冲积物、潟湖相沉积物和三角洲沉积物母质;Cd、Cu、Hg、Pb和Zn在城镇建设用地的平均含量显著高于其他地类.(3)Cr和Ni为自然来源元素,受到成土母质的控制;Cd、Cu、Pb和Zn受到成土母质和人类活动的共同影响,人为源主要包括工业、交通排放和农业活动;Hg为人为来源,受到人为排放的大气沉降的影响.(4)Cd、Cu、Pb和Zn的高值区分布在研究区的北部、南部和西部,Hg的高值区分布在研究区的西部和南部的城镇密集区.
[47]	Coburn T.Geostatistics for natural resources evaluation . Journal of Environmental Quality, 1997, 42(4): 437-438.https://doi.org/10.1080/00401706.2000.10485733 URL [本文引用: 1]摘要 Geostatistics for natural resources evaluation / Pierre Goovaerts. The development of geostatisticsin the 1960s resulted from the need for a methodology to evaluate the recoverable This data setshares three features common to most earth science data sets: (1) data are auto
[48]	梁智, 张计峰. 两种枣树矿质营养元素累积特性研究 . 植物营养与肥料学报, 2011, 17(3): 688-692.https://doi.org/10.11674/zwyf.2011.0376 URL Magsci [本文引用: 1]摘要为探明枣树矿质营养元素的累积分配特征，以3年生骏枣树和灰枣树为试材，采用彻底刨根、分解取样的方法，研究了生物量的构成特点、各器官矿质元素含量和累积分配特性。结果表明，骏枣树总干质量为2694.3 g/plant，其中营养器官占68.0%，分别比灰枣高27.6%和21.9%。其N、P、K、Ca、Mg总累积量为33.91、3.43、22.20、31.25和5.53 g/plant，分别比灰枣树高50.1%、22.5%、24.7%、51.0%和88.7%。其中，N主要分配到叶片和果实，P、K主要分配到果实和叶片，Ca、Mg主要分配到叶片和主干；新生营养器官N、P、K的吸收比例为1: 0.063～0.083: 0.41～0.46，果实N、P、K的吸收比例为1: 0.19～0.20: 1.34～1.48。每生产1000 kg干质量骏枣需吸收N 32.83、P 3.41、K 23.14、Ca 29.06、Mg 5.32 kg；灰枣需吸收N 20.53、P 2.66、K 17.71、Ca 18.01、Mg 2.49 kg。骏枣生产单位干质量果实需吸收的养分比灰枣多，养分利用效率比灰枣低。骏枣树养分在叶片中的分配率显著高于灰枣树，在果实中的分配率则显著低于灰枣树。 [Liang Zhi, Zhang Jifeng.Accumulation properties of mineral elements in two types of Chinese jujube . Journal of Plant Nutrition and Fertilizer, 2011, 17(3): 688-692.]https://doi.org/10.11674/zwyf.2011.0376 URL Magsci [本文引用: 1]摘要为探明枣树矿质营养元素的累积分配特征，以3年生骏枣树和灰枣树为试材，采用彻底刨根、分解取样的方法，研究了生物量的构成特点、各器官矿质元素含量和累积分配特性。结果表明，骏枣树总干质量为2694.3 g/plant，其中营养器官占68.0%，分别比灰枣高27.6%和21.9%。其N、P、K、Ca、Mg总累积量为33.91、3.43、22.20、31.25和5.53 g/plant，分别比灰枣树高50.1%、22.5%、24.7%、51.0%和88.7%。其中，N主要分配到叶片和果实，P、K主要分配到果实和叶片，Ca、Mg主要分配到叶片和主干；新生营养器官N、P、K的吸收比例为1: 0.063～0.083: 0.41～0.46，果实N、P、K的吸收比例为1: 0.19～0.20: 1.34～1.48。每生产1000 kg干质量骏枣需吸收N 32.83、P 3.41、K 23.14、Ca 29.06、Mg 5.32 kg；灰枣需吸收N 20.53、P 2.66、K 17.71、Ca 18.01、Mg 2.49 kg。骏枣生产单位干质量果实需吸收的养分比灰枣多，养分利用效率比灰枣低。骏枣树养分在叶片中的分配率显著高于灰枣树，在果实中的分配率则显著低于灰枣树。
[49]	Fernndez J A, Carballeira A.Evaluation of contamination, by different elements, in terrestrial mosses . Archives of Environmental Contamination and Toxicology, 2001, 40(4): 461-468.https://doi.org/10.1007/s002440010198 URLPMID:11525488 [本文引用: 1]摘要 Evaluation was made of the degree to which samples of terrestrial mosses (Scleropodium purum and Hypnum cupressiforme) collected in Galicia (NW Spain) were contaminated by different elements. The concentrations of Al, As, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, Pb, S, Se, and Zn in the mosses were determined, then the contamination factors were calculated by dividing each value by the corresponding background level of that element. To assess contamination using contamination factors (CFs), a scale was established that allowed categorization of sampling sites for each element determined. The proposed scale comprises six categories, ranging from CF values of less than 1 (no contamination) to values of greater than 27 (extreme contamination). Finally, all available information was brought together and summarized in a contamination index. This index has the advantage that it takes into account the toxicity of the elements and that can be used with an already existing scale of classification.

山东省广饶县土壤重金属来源、分布及生态风险

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Sources, distribution and ecological risk of soil heavy metals in Guangrao county, Shandong province

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