Geoscience ›› 2019, Vol. 33 ›› Issue (02): 293-304.DOI: 10.19657/j.geoscience.1000-8527.2019.02.05
• Geochemistry • Previous Articles Next Articles
WEI Bin1(), HOU Qingye1(
), TANG Zhimin2, ZONG Qingxia3, YAN Shuai1, HE Haiyun1
Received:
2018-07-10
Revised:
2018-09-19
Online:
2019-05-08
Published:
2019-05-08
Contact:
HOU Qingye
CLC Number:
WEI Bin, HOU Qingye, TANG Zhimin, ZONG Qingxia, YAN Shuai, HE Haiyun. Estimation of Background Values and Contamination Characteristics of Heavy Metals in Sediments of the Pearl River, China[J]. Geoscience, 2019, 33(02): 293-304.
地点 | 含量 | Al2O3 | SiO2 | TFe2O3 | As | Cd | Cr | Cu | Hg | Ni | Pb | Zn |
---|---|---|---|---|---|---|---|---|---|---|---|---|
东江 | 最小值 | 4.5 | 58.1 | 0.72 | 3.4 | 0.04 | 6.7 | 4.6 | 0.008 | 3.6 | 21.2 | 17.5 |
最大值 | 21.6 | 89.2 | 6.42 | 22.5 | 0.27 | 69.4 | 59.3 | 0.086 | 58.0 | 65.2 | 105.9 | |
中位数 | 7.7 | 82.5 | 1.95 | 7.4 | 0.13 | 19.9 | 23.0 | 0.016 | 9.7 | 30.5 | 61.2 | |
平均值 | 9.0 | 80.1 | 2.46 | 9.6 | 0.13 | 29.0 | 25.0 | 0.033 | 17.6 | 34.6 | 62.1 | |
标准差 | 5.2 | 9.8 | 1.82 | 5.9 | 0.08 | 23.6 | 20.4 | 0.031 | 16.9 | 13.1 | 39.9 | |
河网 | 最小值 | 5.4 | 58.1 | 1.92 | 10.2 | 0.26 | 21.7 | 6.7 | 0.022 | 2.9 | 26.6 | 50.3 |
最大值 | 20.2 | 85.8 | 6.86 | 79.0 | 3.90 | 114.5 | 99.5 | 0.200 | 61.7 | 137.8 | 333.5 | |
中位数 | 12.5 | 66.6 | 5.59 | 30.5 | 0.88 | 84.8 | 32.8 | 0.151 | 25.9 | 66.5 | 223.1 | |
平均值 | 13.3 | 70.2 | 5.15 | 34.3 | 1.38 | 73.1 | 45.0 | 0.129 | 26.8 | 67.9 | 201.5 | |
标准差 | 5.5 | 10.7 | 1.81 | 22.5 | 1.25 | 29.9 | 39.2 | 0.064 | 19.4 | 36.1 | 103.0 | |
北江 | 最小值 | 1.1 | 63.9 | 0.35 | 1.4 | 0.05 | 3.6 | 3.0 | 0.002 | 1.4 | 8.3 | 8.7 |
最大值 | 17.4 | 92.2 | 5.43 | 95.8 | 4.36 | 68.7 | 93.3 | 0.617 | 51.5 | 127.5 | 486.3 | |
中位数 | 6.6 | 85.3 | 2.00 | 14.6 | 0.82 | 22.0 | 22.0 | 0.056 | 12.3 | 36.1 | 51.9 | |
平均值 | 8.1 | 81.8 | 2.51 | 26.5 | 1.42 | 28.1 | 31.4 | 0.110 | 17.5 | 51.7 | 109.2 | |
标准差 | 4.2 | 7.8 | 1.50 | 27.8 | 1.33 | 20.4 | 29.0 | 0.153 | 14.1 | 34.6 | 121.5 | |
西江 | 最小值 | 4.7 | 58.2 | 2.42 | 12.9 | 0.17 | 32.5 | 11.6 | 0.031 | 12.9 | 21.2 | 51.4 |
最大值 | 18.9 | 87.6 | 7.79 | 68.1 | 4.51 | 105.9 | 57.1 | 0.262 | 51.8 | 110.2 | 349.2 | |
中位数 | 12.8 | 71.4 | 5.13 | 27.4 | 1.18 | 64.2 | 29.2 | 0.127 | 28.1 | 40.2 | 127.8 | |
平均值 | 11.9 | 72.6 | 5.25 | 28.7 | 1.39 | 67.0 | 30.2 | 0.123 | 29.3 | 44.5 | 144.3 | |
标准差 | 4.7 | 8.9 | 1.37 | 13.3 | 1.03 | 20.1 | 11.8 | 0.065 | 10.5 | 20.6 | 70.5 | |
全国① | 12.8 | 65.2 | 4.5 | 12.0 | 0.18 | 61.0 | 23.0 | 0.046 | 26.0 | 27.0 | 71.0 | |
珠江② | 12.9 | 61.8 | 6.5 | 17.0 | 0.09 | 86.0 | 38.0 | 0.093 | 35.0 | 30.0 | 85.0 | |
全国③ | 12.8 | 65.5 | 4.3 | 8.0 | 0.11 | 54.0 | 20.0 | 0.027 | 22.0 | 22.0 | 65.0 |
Table 1 Summary statistics of element contents in sediments of the Pearl River
地点 | 含量 | Al2O3 | SiO2 | TFe2O3 | As | Cd | Cr | Cu | Hg | Ni | Pb | Zn |
---|---|---|---|---|---|---|---|---|---|---|---|---|
东江 | 最小值 | 4.5 | 58.1 | 0.72 | 3.4 | 0.04 | 6.7 | 4.6 | 0.008 | 3.6 | 21.2 | 17.5 |
最大值 | 21.6 | 89.2 | 6.42 | 22.5 | 0.27 | 69.4 | 59.3 | 0.086 | 58.0 | 65.2 | 105.9 | |
中位数 | 7.7 | 82.5 | 1.95 | 7.4 | 0.13 | 19.9 | 23.0 | 0.016 | 9.7 | 30.5 | 61.2 | |
平均值 | 9.0 | 80.1 | 2.46 | 9.6 | 0.13 | 29.0 | 25.0 | 0.033 | 17.6 | 34.6 | 62.1 | |
标准差 | 5.2 | 9.8 | 1.82 | 5.9 | 0.08 | 23.6 | 20.4 | 0.031 | 16.9 | 13.1 | 39.9 | |
河网 | 最小值 | 5.4 | 58.1 | 1.92 | 10.2 | 0.26 | 21.7 | 6.7 | 0.022 | 2.9 | 26.6 | 50.3 |
最大值 | 20.2 | 85.8 | 6.86 | 79.0 | 3.90 | 114.5 | 99.5 | 0.200 | 61.7 | 137.8 | 333.5 | |
中位数 | 12.5 | 66.6 | 5.59 | 30.5 | 0.88 | 84.8 | 32.8 | 0.151 | 25.9 | 66.5 | 223.1 | |
平均值 | 13.3 | 70.2 | 5.15 | 34.3 | 1.38 | 73.1 | 45.0 | 0.129 | 26.8 | 67.9 | 201.5 | |
标准差 | 5.5 | 10.7 | 1.81 | 22.5 | 1.25 | 29.9 | 39.2 | 0.064 | 19.4 | 36.1 | 103.0 | |
北江 | 最小值 | 1.1 | 63.9 | 0.35 | 1.4 | 0.05 | 3.6 | 3.0 | 0.002 | 1.4 | 8.3 | 8.7 |
最大值 | 17.4 | 92.2 | 5.43 | 95.8 | 4.36 | 68.7 | 93.3 | 0.617 | 51.5 | 127.5 | 486.3 | |
中位数 | 6.6 | 85.3 | 2.00 | 14.6 | 0.82 | 22.0 | 22.0 | 0.056 | 12.3 | 36.1 | 51.9 | |
平均值 | 8.1 | 81.8 | 2.51 | 26.5 | 1.42 | 28.1 | 31.4 | 0.110 | 17.5 | 51.7 | 109.2 | |
标准差 | 4.2 | 7.8 | 1.50 | 27.8 | 1.33 | 20.4 | 29.0 | 0.153 | 14.1 | 34.6 | 121.5 | |
西江 | 最小值 | 4.7 | 58.2 | 2.42 | 12.9 | 0.17 | 32.5 | 11.6 | 0.031 | 12.9 | 21.2 | 51.4 |
最大值 | 18.9 | 87.6 | 7.79 | 68.1 | 4.51 | 105.9 | 57.1 | 0.262 | 51.8 | 110.2 | 349.2 | |
中位数 | 12.8 | 71.4 | 5.13 | 27.4 | 1.18 | 64.2 | 29.2 | 0.127 | 28.1 | 40.2 | 127.8 | |
平均值 | 11.9 | 72.6 | 5.25 | 28.7 | 1.39 | 67.0 | 30.2 | 0.123 | 29.3 | 44.5 | 144.3 | |
标准差 | 4.7 | 8.9 | 1.37 | 13.3 | 1.03 | 20.1 | 11.8 | 0.065 | 10.5 | 20.6 | 70.5 | |
全国① | 12.8 | 65.2 | 4.5 | 12.0 | 0.18 | 61.0 | 23.0 | 0.046 | 26.0 | 27.0 | 71.0 | |
珠江② | 12.9 | 61.8 | 6.5 | 17.0 | 0.09 | 86.0 | 38.0 | 0.093 | 35.0 | 30.0 | 85.0 | |
全国③ | 12.8 | 65.5 | 4.3 | 8.0 | 0.11 | 54.0 | 20.0 | 0.027 | 22.0 | 22.0 | 65.0 |
地球化学背景函数 | R2 | 样品数 |
---|---|---|
As=4.259×Al-1.586 | 0.86 | 58 |
As=7.403×Fe-0.007 | 0.82 | 58 |
As=2.557×Sc-0.306 | 0.84 | 58 |
Cd=0.202×Al-0.207 | 0.36 | 58 |
Cd=0.388×Fe-0.184 | 0.50 | 58 |
Cd=0.117×Sc-0.071 | 0.60 | 58 |
Cu=4.510×Al+0.305 | 0.36 | 58 |
Cu=8.970×Fe-1.245 | 0.89 | 58 |
Cu=2.937×Sc-0.119 | 0.94 | 58 |
Cr=11.801×Al-18.984 | 0.86 | 58 |
Cr=19.644×Fe-6.002 | 0.98 | 57 |
Cr=6.541×Sc-4.804 | 0.95 | 58 |
Hg=0.024×Al-0.042 | 0.81 | 58 |
Hg=0.045×Fe-0.035 | 0.89 | 54 |
Hg=0.014×Sc-0.031 | 0.90 | 58 |
Ni=4.435×Al-2.165 | 0.80 | 58 |
Ni=8.822×Fe-2.354 | 0.91 | 58 |
Ni=3.044×Sc-2.555 | 0.97 | 57 |
Pb=4.889×Al+13.196 | 0.77 | 58 |
Pb=7.690×Fe+19.490 | 0.54 | 58 |
Pb=2.475×Sc+19.252 | 0.60 | 58 |
Zn=23.602×Al-17.931 | 0.79 | 58 |
Zn=38.502×Fe-1.007 | 0.87 | 58 |
Zn=13.109×Sc-2.392 | 0.91 | 58 |
Table 2 Robust regression equations and correlation coe-fficients for heavy metals versus particle-size proxy elements (Al, Fe and Sc) in the sediments of the Pearl River
地球化学背景函数 | R2 | 样品数 |
---|---|---|
As=4.259×Al-1.586 | 0.86 | 58 |
As=7.403×Fe-0.007 | 0.82 | 58 |
As=2.557×Sc-0.306 | 0.84 | 58 |
Cd=0.202×Al-0.207 | 0.36 | 58 |
Cd=0.388×Fe-0.184 | 0.50 | 58 |
Cd=0.117×Sc-0.071 | 0.60 | 58 |
Cu=4.510×Al+0.305 | 0.36 | 58 |
Cu=8.970×Fe-1.245 | 0.89 | 58 |
Cu=2.937×Sc-0.119 | 0.94 | 58 |
Cr=11.801×Al-18.984 | 0.86 | 58 |
Cr=19.644×Fe-6.002 | 0.98 | 57 |
Cr=6.541×Sc-4.804 | 0.95 | 58 |
Hg=0.024×Al-0.042 | 0.81 | 58 |
Hg=0.045×Fe-0.035 | 0.89 | 54 |
Hg=0.014×Sc-0.031 | 0.90 | 58 |
Ni=4.435×Al-2.165 | 0.80 | 58 |
Ni=8.822×Fe-2.354 | 0.91 | 58 |
Ni=3.044×Sc-2.555 | 0.97 | 57 |
Pb=4.889×Al+13.196 | 0.77 | 58 |
Pb=7.690×Fe+19.490 | 0.54 | 58 |
Pb=2.475×Sc+19.252 | 0.60 | 58 |
Zn=23.602×Al-17.931 | 0.79 | 58 |
Zn=38.502×Fe-1.007 | 0.87 | 58 |
Zn=13.109×Sc-2.392 | 0.91 | 58 |
Fig.5 Least trimmed sum of squares (LTS) regression diagnostic plots of heavy metals vs. reference elements in sediments of the Pearl River (Horizontal lines define cut-off values for vertical outliers. The sequence number is ordered for samples)
[1] | FOSTER I D L, CHARLESWORTH S M. Heavy metals in the hydrological cycle: Trends and explanation[J]. Hydrological Processes, 1996,10:227-261. |
[2] | SEGURA R, ARANCIBIA V, ZÙÑIGA M C, et al. Distribution of copper, zinc, lead and cadmium concentrations in stream sediments from the Mapocho River in Santiago, Chile[J]. Journal of Geochemical Exploration, 2006,91(1/3):71-80. |
[3] | HAKANSON L. An ecological risk index for aquatic pollution control.A sedimentological approach[J]. Water Research, 1980,14(8):975-1001. |
[4] | MULLER G. Index of geoaccumulation in sediments of the Rhine River[J]. Geological Journal, 1969,2(3):108-118. |
[5] | SZEFER P, GLASBY G P, KUSAK A, et al. Evaluation of the anthropogenic influx of metallic pollutants into Puck Bay, southern Baltic[J]. Applied Geochemistry, 1998,13(3):293-304. |
[6] | JIANG J, WANG J, LIU S, et al. Background, baseline, normalization, and contamination of heavy metals in the Liao River Watershed sediments of China[J]. Journal of Asian Earth Sciences, 2013,73:87-94. |
[7] | ÇEVIK F, GÖKSU M Z L, DERICI O B, et al. An assessment of metal pollution in surface sediments of Seyhan dam by using enrichment factor, geoaccumulation index and statistical analyses[J]. Environmental Monitoring and Assessment, 2009,152(1/4):309-317. |
[8] | CHEN J B, GAILLARDET J, BOUCHEZ J, et al. Anthropophile elements in river sediments: Overview from the Seine River, France[J]. Geochemistry, Geophysics, Geosystems, 2014,15(11):4526-4546. |
[9] | ZAHRA A, HASHMI M Z, MALIK R N, et al. Enrichment and geo-accumulation of heavy metals and risk assessment of sediments of the Kurang Nallah-feeding tributary of the Rawal Lake Reservoir, Pakistan[J]. Science of the Total Environment, 2014,470/471:925-933. |
[10] | KOITER A J, OWENS P N, PETTICREW E L, et al. The behavioural characteristics of sediment properties and their implications for sediment fingerprinting as an approach for identifying sediment sources in river basins[J]. Earth-Science Reviews, 2013,125:24-42. |
[11] | GRYGAR T M, POPELKA J. Revisiting geochemical methods of distinguishing natural concentrations and pollution by risk elements in fluvial sediments[J]. Journal of Geochemical Exploration, 2016,170:39-57. |
[12] | BLASER P, ZIMMERMANN S, LUSTER J, et al. Critical exa-mination of trace element enrichments and depletions in soils: As, Cr, Cu, Ni, Pb, and Zn in Swiss forest soils[J]. Science of the Total Environment, 2000,249(1/3):257-280. |
[13] | VAROL M, ŞEN B. Assessment of nutrient and heavy metal contamination in surface water and sediments of the upper Tigris River, Turkey[J]. Catena, 2012,92:1-10. |
[14] |
SAKAN S, DEVIĆ G, RELIĆ D, et al. Evaluation of sediment contamination with heavy metals: The importance of determining appropriate background content and suitable element for normalization[J]. Environmental Geochemistry and Health, 2015,37(1):97-113.
URL PMID |
[15] | TAPIA J, AUDRY S, TOWNLEY B, et al. Geochemical background, baseline and origin of contaminants from sediments in the mining-impacted Altiplano and Eastern Cordillera of Oruro, Boli-via[J]. Geochemistry: Exploration, Environment, Analysis, 2012,12(1):3-20. |
[16] | BÁBEK O, GRYGAR T M, FAMĚRA M, et al. Geochemical background in polluted river sediments: How to separate the effects of sediment provenance and grain size with statistical rigour?[J]. Catena, 2015,135:240-253. |
[17] | COVELLI S, FONTOLAN G. Application of a normalization procedure in determining regional geochemical baselines[J]. Environmental Geology, 1997,30(1/2):34-45. |
[18] | GRYGAR T M, NOVÁKOVÁ T, BÁBEK O, et al. Robust assessment of moderate heavy metal contamination levels in floodplain sediments: A case study on the Jizera River, Czech Republic[J]. Science of the Total Environment, 2013,452/453:233-245. |
[19] | MAJEROVÁ L, GRYGAR T M, ELZNICOVÁ J, et al. The differentiation between point and diffuse industrial pollution of the floodplain of the Plouĉnice River, Czech Republic[J]. Water, Air, & Soil Pollution, 2013,224(9):1-20. |
[20] |
VIJVER M G, SPIJKER J, VINK J P M, et al. Determining me-tal origins and availability in fluvial deposits by analysis of geochemical baselines and solid-solution partitioning measurements and modelling[J]. Environmental Pollution, 2008,156(3):832-839.
DOI URL PMID |
[21] | 阂育顺, 祁士华, 张干. 珠江广州河段重金属元素的高分辨沉积记录[J]. 科学通报, 2000,45(S1):2802-2805. |
[22] |
GENG J, WANG Y, LUO H. Distribution, sources, and fluxes of heavy metals in the Pearl River Delta, South China[J]. Marine Pollution Bulletin, 2015,101(2):914-921.
DOI URL PMID |
[23] | 李红玉, 赵彦龙, 梁永津, 等. 北江干流沉积物重金属污染生态风险评价[J]. 广东微量元素科学, 2014,21(7):1-5. |
[24] | 谢文平, 王少冰, 朱新平, 等. 珠江下游河段沉积物中重金属含量及污染评价[J]. 环境科学, 2012,33(6):1808-1815. |
[25] | 许振成, 杨晓云, 温勇, 等. 北江中上游底泥重金属污染及其潜在生态危害评价[J]. 环境科学, 2009,30(11):3262-3268. |
[26] | 吕文英, 周树杰, 雷颖欣. 珠江广州段东朗断面底泥中重金属污染研究[J]. 环境科学与技术, 2009,32(5):183-186. |
[27] | 赖启宏, 杜海燕, 方敬文, 等. 珠江三角洲冲积平原土壤镉高含量区形成原因[J]. 农业环境科学学报, 2005,24(4):746-750. |
[28] | 刘子宁, 窦磊, 张伟. 珠江三角洲第四纪沉积物Cd元素的分布特征及成因[J]. 地质通报, 2012,31(1):172-180. |
[29] | ROUSSEEUW P J. Least median of squares regression[J]. Journal of the American Statistical Association, 1984,79:871-880. |
[30] | R Core Team. R: A language and environment for statistical[CP/OL]. (2018-04-23)[2018-07-03]. https://www.r-project.org/ |
[31] | MAECHLER M, ROUSSEEUW P, CROUX C, et al. robustbase: Basic Robust Statistics R package[CP/OL]. (2018-04-25)[2018-07-03] https://cran.r-project.org/web/packages/robustbase |
[32] | GRYGAR T M, ELZNICOVÁ J, BÁBEK O, et al. Obtaining isochrones from pollution signals in a fluvial sediment record: A case study in a uranium-polluted floodplain of the Plouĉnice River, Czech Republic[J]. Applied Geochemistry, 2014,48:1-15. |
[33] | TUKEY J W. Exploratory Data Analysis[M]. Boston: Addison-Wesley Publishing Company, 1977: 39-56. |
[34] | ROUSSEEUW P J, VAN ZOMEREN B C. Unmasking multivariate outliers and leverage points[J]. Journal of the American Statistical Association, 1990,85:633-639. |
[35] | 迟清华, 鄢明才. 应用地球化学元素丰度数据手册[M]. 北京: 地质出版社, 2007: 92-93. |
[36] | 史长义, 梁萌, 冯斌. 中国水系沉积物39种元素系列背景值[J]. 地球科学, 2008,41(2):234-251. |
[37] | GAŁUSZKA A, MIGASZEWSKI Z M. Geochemical background—an environmental perspective[J]. Mineralogia, 2011,42(1):7-17. |
[38] | BOUCHEZ J, GAILLARDET J, LANORD C F, et al. Grain size control of river suspended sediment geochemistry: Clues from Amazon River depth profiles[J]. Geochemistry, Geophysics, Geosystems, 2013,12(3):1-24. |
[39] | REIMANN C, GARRETT R G. Geochemical background—concept and reality[J]. Science of the Total Environment, 2005,350(1/3):12-27. |
[40] |
GU Y G, LI Q S, FANG J H, et al. Identification of heavy metal sources in the reclaimed farmland soils of the Pearl River estuary in China using a multivariate geostatistical approach[J]. Ecotoxicology and Environmental Safety, 2014,105:7-12.
URL PMID |
[41] | 丁小勇, 陈来国, 张卫东, 等. 北江沉积物汞污染现状与评价初步研究[J]. 农业环境科学学报, 2010,29(2):357-362. |
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