中国地质调查局南京地质调查中心主办
高级检索

淮河流域平原区高铁锰地下水环境健康风险评估

,  ,  , 

文章导航 > 华东地质 > 2023 > 44(2): 119-127

上一篇

下一篇

许乃政, 陶小虎, 龚建师, 檀梦皎. 2023. 淮河流域平原区高铁锰地下水环境健康风险评估. 华东地质, 44(2): 119-127. doi: 10.16788/j.hddz.32-1865/P.2023.02.001
引用本文: 许乃政, 陶小虎, 龚建师, 檀梦皎. 2023. 淮河流域平原区高铁锰地下水环境健康风险评估. 华东地质, 44(2): 119-127. doi: 10.16788/j.hddz.32-1865/P.2023.02.001
shu
XU Naizheng, TAO Xiaohu, GONG Jianshi, TAN Mengjiao. 2023. Exposure risk of high Fe and Mn groundwater from Huaihe River Plain. East China Geology, 44(2): 119-127. doi: 10.16788/j.hddz.32-1865/P.2023.02.001
Citation: XU Naizheng, TAO Xiaohu, GONG Jianshi, TAN Mengjiao. 2023. Exposure risk of high Fe and Mn groundwater from Huaihe River Plain. East China Geology, 44(2): 119-127. doi: 10.16788/j.hddz.32-1865/P.2023.02.001
shu

淮河流域平原区高铁锰地下水环境健康风险评估

  • 1. 中国地质调查局南京地质调查中心, 江苏 南京 210016;

  • 2. 自然资源部流域生态地质过程重点实验室, 江苏 南京 210016

  • 基金项目:

    中国地质调查局"长江下游及淮河流域水文地质与水资源调查监测(编号:DD20230428)"项目资助。

详细信息
    作者简介: 许乃政,1971年生,男,研究员,博士,主要从事环境科学研究。Email:xzzz100@sina.com。
    通讯作者: 龚建师,1979年生,男,高级工程师,学士,主要从事水文地质学研究。Email:593591934@qq.com。

  • 中图分类号: X53

Exposure risk of high Fe and Mn groundwater from Huaihe River Plain

  • 1. Nanjing Center, China Geological Survey, Nanjing 210016, Jiangsu, China;

  • 2. Key Laboratory of Watershed Eco-Geological Processes, Ministry of Natural Resources, Nanjing 210016, Jiangsu, China

More Information

    摘要
  • 基于近期获得的水文地球化学分析数据,应用指示克立格法开展了淮河流域平原区高铁、锰地下水环境健康风险评估,并分析了高铁、锰地下水的形成原因。结果表明:铁、锰是影响研究区地下水质量的主要化学组分,铁、锰在地下水中的空间分布上表现出明显的变异性。铁、锰超标概率峰值具有相似的空间分布格局,铁、锰高风险地区呈岛状分布,深层地下水的环境健康风险明显降低。含铁浅层地下水高风险地区面积为1 257.15 km2,面积占比0.07％;含铁深层地下水高风险地区面积为476.93 km2,面积占比0.03％。含锰浅层地下水高风险地区面积为35 883.16 km2,面积占比19.19％;含锰深层地下水高风险地区面积为1 269.30 km2,面积占比0.07％。淮河流域高铁锰地下水是原生成因,铁、锰离子主要来源于含水层中含铁、锰矿物的还原性溶解。高铁锰地下水的风险评价结果,可为区域供水区划提供指导。
    Based on the analysis of hydro-geochemical data obtained recently, this study assessed exposure risk of high Fe and Mn groundwater from Huaihe River Plain in eastern China using Indicator Kriging method, as well as discussed its origin. The results showed that Fe and Mn were the main chemical substances affecting groundwater quality, indicating obvious spatial variability. The peak value of Fe and Mn risk probability were distributed similarly in spatial pattern. The high-risk areas of Fe and Mn presented an island distribution, and the hazard risk of deep groundwater were significantly reduced against the shallow counterpart. The high risk zone of Fe in shallow groundwater covers 1 257.15 km2, accounting for 0.07％ of the study area, and the counterpart in deep groundwater was 476.93 km2, accounting for 0.03％, respectively. The high risk zone of Mn in shallow groundwater covers 35 883.16 km2, accounting for 19.19％, while its counterpart in deep groundwater was 1 269.30 km2, accounting for 0.07％, respectively. The high Fe and Mn groundwater was of in-situ origin, and Fe and Mn were derived from geogenic iron and manganese minerals in aquifers by reductive dissolution. This paper carried out research on exposure risk of high Fe and Mn groundwater from Huaihe River Plain, which may provide guidance for the regionalization of drinking groundwater safety.
    • HTML全文
  • 加载中
    • 参考文献(25)
  • [1]

    CAO H L, XIE X J, WANG Y X, et al. Predicting the risk of groundwater arsenic contamination in drinking water wells[J]. Journal of Hydrology, 2018, 560:318-325.

    [2]

    LI Y F, WAN D, LIU Y Y, et al. A predictive risk model of groundwater arsenic contamination in China applied to the Huai River Basin, with a focus on the region’s cluster of elevated cancer mortalities[J]. Applied Geochemistry, 2017, 77: 178-183.

    [3]

    SHAHID N M, NIAZI K, DUMAT C, et al. A meta-analysis of the distribution, sources and health risks of arsenic-contaminated groundwater in Pakistan[J]. Environmental Pollution, 2018, 242(A):307-319.

    [4]

    李璐,殷乐宜,牛浩博,等. 基于贝叶斯模型的地下水风险源污染概率估计方法研究[J].环境科学研究,2020,33(6):1322-1327.

    LI L, YIN L Y, NIU H B, et al. Contamination probability of groundwater risk sources by Bayesian [J]. Research of Environmental Sciences, 2020, 33(6):1322-1327.

    [5]

    滕彦国,左锐,苏小四,等.区域地下水环境风险评价技术方法[J].环境科学研究, 2014,27(12):1532-1539.

    TENG Y G, ZUO R, SU X S, et al. Technique for assessing environmental risk of regional groundwater[J]. Research of Environmental Sciences, 2014, 27(12):1532-1539.

    [6]

    左锐,石榕涛,王膑,等.地下水型水源地水质安全预警技术体系研究[J].环境科学研究, 2018,31(3):409-418.

    ZUO R,SHI R T,WANG B,et al.Technological system of early warning for groundwater quality in a groundwater source area [J]. Research of Environmental Sciences, 2018, 31(3): 409-418.

    [7]

    张博,李国秀,程品,等. 基于随机理论的地下水环境风险评价[J]. 水科学进展, 2016,27(1):100-106.

    ZHANG B, LI G X, CHENG P, et al. Groundwater environment risk assessment based on stochastic theory[J]. Advances in Water Science, 2016, 27(1):100-106.

    [8]

    姚丽利,高童,胡立堂.地下水水源地污染预警应用研究——以浑河冲洪积扇为例[J].南水北调水利科技, 2016,14(1):37-41,66. YAO L L, GAO T, HU L T. Applications study of groundwater pollution early warning in source field: A case study in alluvial-pluvial fan of Hun River [J]. South-North Water Transfer and Water Science ＆ Technology, 2016,14(1):37-41, 66.

    [9]

    PARRONE D, GHERGO S, FROLLIINI E, et al. Arsenic-fluoride contamination in groundwater: Background and anomalies in a volcanic-sedimentary aquifer in central Italy [J]. Journal of Geochemical Exploration, 2020, 217:106590.

    [10]

    谢云峰,杜平, 曹云者,等. 基于地统计条件模拟的土壤重金属污染范围预测方法研究[J].环境污染与防治,2015,37(1): 1-6.

    XIE Y F, DU P, CAO Y Z, et al. Estimating the area of heavy metal contaminated soil using geostatistical conditional stimulation [J]. Environmental Pollution ＆ Control, 2015, 37(1): 1-6.

    [11]

    谢云峰,曹云者,杜晓明,等. 土壤污染调查加密布点优化方法构建及验证[J]. 环境科学学报, 2016,36(3): 981-989

    . XIE Y F, CAO Y Z, DU X M, et al. Development and validation of a sampling design optimization procedure for detailed soil pollution investigation [J]. Acta Scientiae Circumstantiae, 2016, 36(3): 981-989

    [12]

    徐英,陈亚新,王俊生,等. 农田土壤水分和盐分空间分布的指示克立格分析评价[J]. 水科学进展,2006,17(4): 477-482.

    XU Y, CHEN Y X, WANG J S, et al. Using indicator Kriging to analyze and evaluate spatial distributions of soil water and salt in field[J]. Advances in Water Science, 2006, 17(4):477-482.

    [13]

    李保国,胡克林,黄元仿,等.区域浅层地下水硝酸盐含量评价的指示克立格法[J].水利学报,2001(3): 1-5.

    LI B G, HU K L, HUANG Y F, et al. Application of indicator Kriging method for assessing nitrate content of regional shallow groundwater[J].Journal of Hydraulic Engineering, 2001(3): 1-5.

    [14]

    刘瑞民,王学军,张巍. 天津表土PAHs区域环境风险评价研究[J]. 环境科学, 2008, 29(6):1719-1723.

    LIU R M, WANG X J, ZHANG W. Regional environment risk assessment and probability distribution of topsoil PAHs in Tianjin area [J]. Environmental Science, 2008, 29(6): 1719-1723.

    [15]

    姜菲菲,孙丹峰,李红,等.北京市农业土壤重金属污染环境风险等级评价[J].农业工程学报,2011,27(8): 330-337.

    JIANG F F, SUN D F, LI H, et al. Risk grade assessment for farmland pollution of heavy metals in Beijing [J]. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(8): 330-337.

    [16]

    张小文,何江涛,黄冠星. 石家庄地区浅层地下水铁锰分布特征及影响因素分析[J].地学前缘, 2021, 28(4):206-218.

    ZHANG X W, HE J T, HUANG G X. Iron and manganese in shallow groundwater in Shijiazhuang: Distribution characteristics and a cause analysis [J]. Earth Science Frontiers, 2021, 28(4):206-218.

    [17]

    蔡玲,胡成,陈植华,等.江汉平原东北部地区高铁锰地下水成因与分布规律[J]. 水文地质工程地质, 2019, 46(4):18-25.

    CAI L, HU C, CHEN Z H, et al. Distribution and genesis of high Fe and Mn groundwater in the northeast of the Jianghan Plain[J]. Hydrogeology ＆ Engineering Geology, 2019, 46(4):18-25.

    [18]

    周锴锷,王赫生,龚建师,等. 淮河流域平原区浅层地下水铁锰分布特征及成因浅析[J]. 资源调查与环境, 2014,35(2):147-151.

    ZHOU K E, WANG H S, GONG J S, et al. Elementary analysis of distribution features and formation of Fe2+ and Mn2+ in the shallow groundwater of the Huaihe River alley plain [J]. Resource Survey and Environment, 2014,35(2):147-151.

    [19]

    张克信,潘桂棠,何卫红,等. 中国构造-地层大区划分新方案[J].中国地质大学学报:地球科学, 2015, 40(2): 206-233.

    ZHANG K X, PAN G T, HE W H, et al. New division of tectonic-strata super region in China [J]. Earth Science, 2015, 40: 206-233.

    [20]

    许乃政,龚建师,檀梦皎,等.淮河流域高砷地下水的形成演化过程及其环境健康风险[J]. 中国地质,2021,48(5): 1418-1428.

    XU N Z, GONG J S, TAN M J, et al. Hydrogeochemical processes and potential exposure risk of high-arsenic groundwater in Huaihe River Basin, China [J]. Geology in China, 2021, 48(5):1418-1428.

    [21]

    World Health Organization. Guidelines for drinking-water quality (Fourth edition) [M]. Geneva: The World Health Organization, 2011: 1-564.

    [22]

    中国卫生部. GB5749—2006生活饮用水卫生标准[S]. 北京:中国标准出版社,2006:1-10.

    Ministry of Health, PRC. GB5749—2006 Quality standard for drinking water [S].Beijing: China Standard Publishing House, 2006:1-10.

    [23]

    中国国土资源部和水利部. GB/T 14848—2017 地下水质量标准[S]. 北京:中国标准出版社,2017:1-14.

    Ministry of Land and Resources, Ministry of Water Resources, PRC. GB/T 14848—2017 Quality standard for ground water[S]. Beijing: China Standard Publishing House, 2017:1-14.

    [24]

    SARKAR M, CHANDRA PAL S. Human health hazard assessment for high groundwater arsenic and fluoride intact in Malda district, Eastern India [J]. Groundwater for Sustainable Development, 2021, 13:100565.

    [25]

    韩吟文,马振东, 张宏飞,等. 地球化学[M].北京:地质出版社, 2003:1-370.

    HAN Y W, MA Z D, ZHANG H F, et al. Geochemistry [M]. Beijing: Geological Publishing House, 2003:1-370.

    • 相关文章
  • 施引文献
  • 资源附件(0)
  • 加载中
计量
  • 文章访问数:  796
  • PDF下载数:  58
  • 施引文献:  0
出版历程
收稿日期:  2022-01-26
修回日期:  2022-05-25

目录

    版权所有：中国地质调查局发展研究中心 copyright @2020
    返回