Advertisement

Assessment of potential health risk of major contaminants of groundwater in a densely populated agricultural area

  • Zijun Li
  • Kun Yang
  • Chuan Xie
  • Qingchun YangEmail author
  • Xiaohui Lei
  • Hao Wang
Original Paper
  • 46 Downloads

Abstract

As a key part of Bohai New Area development, Haixing County has been undergoing rapid development. In order to estimate potential risks of chemical parameters to human health of local residents, carcinogenic and non-carcinogenic risks via direct ingestion of drinking water were calculated using human health risk assessment (HHRS) based on triangular fuzzy number. The levels of pH, total dissolved solids, total harness, SO42−, Na+, Cl, SO42−, F, Fe (total iron), NO3, and NO2 were more or less higher than the permissible limits except parameters As and Mn. The analysis results show that risk level for different crowds in the study area demonstrated an obvious variation, generally in the order of infants > children > adult males > adult females for non-carcinogenic risk values (Rn), while the sequence of the carcinogenic risk values (Rc) are adult males > adult females > children > infants. When the confidence level was 0.8, the non-carcinogenic risk values (Rn) through drinking water intake were higher than 1, and this implied that potential health impacts on human health for local residents. However, the risks of carcinogenic risk values (Rc) were lower than 1.0E−4, demonstrating minimal and acceptable health risk. Furthermore, according to the middle values (α = 1) of Rn, the total non-carcinogenic risks for local residents were obtained in the following order: GW (Gaowan Town) > XJ (Xinji-Xiangfang County) > ZM (Zhaomaotao County) > HX (Haixing-Suji Town) > ZH (Zhanghuiting County) > XS (Xiaoshan County), and ZM > XJ > GW > HX > XS > ZH for Rc. It was also found that the spatial distribution of fluoride level in drinking water is urgently needed to be identified. In conclusion, the potential health risks to residents should cause enough attention both from society and the academic community.

Keywords

Groundwater Human health risk assessment Triangular fuzzy number Fluoride Haixing County 

Notes

Acknowledgements

This research was financially supported by Comprehensive Geological Survey of ecological economic zone along Huang River in Ningxia Province (Grant No. DD90296).

Supplementary material

10653_2019_470_MOESM1_ESM.docx (429 kb)
Supplementary material 1 (DOCX 428 kb)

References

  1. Ahada, C. P. S., & Suthar, S. (2017). Assessment of human health risk associated with high groundwater fluoride intake in southern districts of Punjab, India. Exposure and Health.Google Scholar
  2. Ahmad, S. A., Sayed, M. H. S., Khan, M. H., Karim, M. N., Haque, M. A., Bhuiyan, M. S. A., et al. (2007). Sociocultural aspects of arsenicosis in Bangladesh: Community perspective. Journal of Environmental Science and Health, Part A,42(12), 1945–1958.CrossRefGoogle Scholar
  3. Ali, N., Khan, S., Rahman, I. U., & Muhammad, S. (2018). Human health risk assessment through consumption of organophosphate pesticide-contaminated water of Peshawar basin, Pakistan. Exposure and Health,10(4), 259–272.CrossRefGoogle Scholar
  4. Anonymous. (2008). Assessment of surface water for drinking quality. Mughalpura, Lahore: Directorate of Land Reclamation Punjab, Irrigation and Power Department, Canal Bank.Google Scholar
  5. Arunraj, N. S., Mandal, S., & Maiti, J. (2013). Modeling uncertainty in risk assessment: an integrated approach with fuzzy set theory and monte carlo simulation. Accident Analysis & Prevention, 55, 242–255.CrossRefGoogle Scholar
  6. Ayotte, J. D., Belaval, M., Olson, S. A., Burow, K. R., Flanagan, S. M., Hinkle, S. R., et al. (2015). Factors affecting temporal variability of arsenic in groundwater used for drinking water supply in the United States. Science of the Total Environment,505, 1370–1379.CrossRefGoogle Scholar
  7. Azizullah, A., Muhammad, N. K. K., Peter, R., & Donat, P. H. (2011). Water pollution in Pakistan and its impact on public health—A review. Environment International,37, 479–497.CrossRefGoogle Scholar
  8. Bao, Z., Hu, Q., Qi, W., Tang, Y., Wang, W., Wan, P., et al. (2017). Nitrate reduction in water by aluminum alloys particles. Journal of Environmental Management,196, 666–673.CrossRefGoogle Scholar
  9. Barbeau, A. (1984). Manganese and extrapyramidal disorders (A critical review and tribute to Dr. George C. Cotzias). NeuroToxicol,5, 13–35.Google Scholar
  10. Barzegar, R., Asghari Moghaddam, A., Adamowski, J., & Nazemi, A. H. (2018). Assessing the potential origins and human health risks of trace elements in groundwater: A case study in the Khoy Plain, Iran. Environmental Geochemistry and Health,77, 551.Google Scholar
  11. Beckman, L. E. (1999). Interaction between haemochromatosis and transferrin receptor genes in different neoplastic disorders. Carcinogenesis,20(7), 1231–1233.CrossRefGoogle Scholar
  12. Berg, D., Gerlach, M., Youdim, M. B. H., Double, K. L., Zecca, L., Riederer, P., et al. (2002). Brain iron pathways and their relevance to Parkinson’s disease. Journal of Neurochemistry,80(4), 1.CrossRefGoogle Scholar
  13. Chen, J., Qian, H., Gao, Y., & Li, X. (2018). Human health risk assessment of contaminants in drinking water based on triangular fuzzy numbers approach in Yinchuan City, Northwest China. Exposure & Health,10, 155–166.CrossRefGoogle Scholar
  14. Chen, J., Qian, H., & Wu, H. (2017). Nitrogen contamination in groundwater in an agricultural region along the New Silk Road, northwest China: Distribution and factors controlling its fate. Environmental Science Pollution Resesrch,24(15), 13154–13167.CrossRefGoogle Scholar
  15. Chen, J., Wu, H., & Qian, H. (2016). Groundwater nitrate contamination and associated health risk for the rural communities in an agricultural area of Ningxia, Northwest China. Exposure & Health,3, 1–11.Google Scholar
  16. Chotpantarat, S., Wongsasuluk, P., Siriwong, W., Borjan, M., & Robson, M. (2014). Non-carcinogenic hazard maps of heavy metal contamination in shallow groundwater for adult and aging populations at an agricultural area in Northeastern Thailand. Human and Ecological Risk Assessment: An International Journal,20(3), 689–703.CrossRefGoogle Scholar
  17. Chowdhury, M. A. I., Uddin, M. T., Ahmed, M. F., Ali, M. A., Rasul, S. M. A., Hoque, M. A., et al. (2006). Collapse of socio-economic base of Bangladesh by arsenic contamination in groundwater. Pakistan Journal of Biological Sciences,9(9), 1617–1627.CrossRefGoogle Scholar
  18. Crossgrove, J., & Zheng, W. (2004). Manganese toxicity upon overexposure. NMR in Biomedicine,17(8), 544–553.CrossRefGoogle Scholar
  19. Dippong, T., Mihali, C., Hoaghia, M. A., Cical, E., & Cosma, A. (2019). Chemical modeling of groundwater quality in the aquifer of Seini Town—Someş Plain, Northwestern Romania. Ecotoxicology and Environmental Safety,168, 88–101.CrossRefGoogle Scholar
  20. Dissanayake, C. B. (1991). The fluoride problem in the ground water of Sri Lanka—environmental management and health. International Journal of Environmental Studies,38(38), 137–155.CrossRefGoogle Scholar
  21. Dragon, K. (2012). Groundwater nitrate pollution in the recharge zone of a regional Quaternary flow system (Wielkopolska region, Poland). Environmental Earth Science,68(7), 2099–2109.CrossRefGoogle Scholar
  22. Edmunds, W. M., Ahmed, K. M., & Whitehead, P. G. (2015). A review of arsenic and its impacts in groundwater of the Ganges–Brahmaputra–Meghna Delta, Bangladesh. Environmental Science: Processes Impacts,17(6), 1032–1046.Google Scholar
  23. Ellervik, C., Mandrup-Poulsen, T., Nordestgaard, B. G., Larsen, L. E., Appleyard, M., Frandsen, M., et al. (2001). Prevalence of hereditary haemochromatosis in late-onset type 1 diabetes mellitus: A retrospective study. Lancet,358(9291), 1405–1409.CrossRefGoogle Scholar
  24. Farooqi, A., Masuda, H., & Firdous, N. (2007). Toxic fluoride and arsenic contaminated groundwater in the Lahore and Kasur districts, Punjab, Pakistan and possible contaminant sources. Environmental Pollution,145(3), 839–849.CrossRefGoogle Scholar
  25. Gardner, M. J., & Altman, D. G. (1986). Confidence intervals rather than p values: Estimation rather than hypothesis testing. BMJ,292(6522), 746–750.CrossRefGoogle Scholar
  26. Garg, V. K., Suthar, S., Singh, S., Sheoran, A., Garima, Meenakshi, et al. (2009). Drinking water quality in villages of southwestern Haryana, India: Assessing human health risks associated with hydrochemistry. Environmental Geology (Berlin),58(6), 1329–1340.CrossRefGoogle Scholar
  27. Gupta, S. K., Gupta, R. C., Gupta, A. B., Seth, A. K., Bassin, J. K., & Gupta, A. (2000). Recurrent acute respiratory tract infections in areas with high nitrate concentrations in drinking water. Environmental Health Perspectives,108(4), 363–366.CrossRefGoogle Scholar
  28. Han, G. R. (2014). Health Risk Assessment on groundwater environment of an area in Chengdu. Chengdu City, Sichuan Province: Chengdu University of Technology.Google Scholar
  29. Hem, J. D. (1991). Study and interpretation of chemical characteristics of natural waters (3rd ed., p. 2254). Jodhpur: Scientific Publishers, Jodhpur Book.Google Scholar
  30. Holden, W. S. (1970). Water treatment and examination (p. 513). London: J & Churchill Publishers.Google Scholar
  31. Inoue, N. (1996). Neurological aspects in human exposure to manganese. In Toxicology of metals (pp. 415–421).Google Scholar
  32. Jabed, Md. A., Alak, P., & Kumar, N. T. (2018). Peoples’ perception of the water salinity impacts on human health: A case study in South-Eastern Coastal Region of Bangladesh. Exposure and Health.Google Scholar
  33. Joseph, T., Dubey, B., & Mcbean, E. A. (2015). Human health risk assessment from arsenic exposures in Bangladesh. Science of the Total Environment,527–528, 552–560.CrossRefGoogle Scholar
  34. Kawasaki, T., Delea, C. S., Bartter, F. C., & Smith, H. (1978). The effect of high-sodium and low-sodium intakes on blood pressure and other related variables in human subjects with idiopathic hypertension. The American Journal of Medicine,64(2), 193–198.CrossRefGoogle Scholar
  35. Khan, U. T., & Valeo, C. (2015). A new fuzzy linear regression approach for dissolved oxygen prediction. International Association of Scientific Hydrology Bulletin,60(6), 1096–1119.CrossRefGoogle Scholar
  36. Kleinjans, J. C., Albering, H. J., Marx, A., Van Maanen, J. M., Van Agen, B., Ten Hoor, F., et al. (1991). Nitrate contamination of drinking water: Evaluation of genotoxic risk in human populations. Environmental Health Perspectives,94, 189–193.Google Scholar
  37. Liu, F., Song, X. F., Han, D. M., Zhang, Y. H., Ma, Y., et al. (2015). The role of anthropogenic and natural factors in shaping the geochemical evolution of groundwater in the Subei Lake basin, ordos energy base, Northwestern China. Science of the Total Environment,538(538), 327–340.CrossRefGoogle Scholar
  38. McCarthy, M. F. (2004). Should we restrict chloride rather than sodium? Medical Hypothesis,63, 138–148.CrossRefGoogle Scholar
  39. Mehdi, Q., Mojtaba, A., Mansoureh, F., Abolfazl, B., Mohadeseh, A., & Ahmad, Z. (2018). Health risk assessment of nitrate exposure in groundwater of rural areas of Gonabad and Bajestan, Iran. Environmental Earth Sciences,77(15), 551.CrossRefGoogle Scholar
  40. Milman, N., Pedersen, P., Steig, T. Á., Byg, K. E., Graudal, N., & Fenger, K. (2001). Clinically overt hereditary hemochromatosis in Denmark 1948–1985: Epidemiology, factors of significance for long-term survival, and causes of death in 179 patients. Annals of Hematology,80(12), 737–744.CrossRefGoogle Scholar
  41. Ministry of Environmental Protection. (2013). Manual of exposure parameters for Chinese population—Adult volume. Beijing: China Environmental Press.Google Scholar
  42. Mondal, D., & Polya, D. A. (2008). Rice is a major exposure route for arsenic in Chakdaha block, Nadia District, West Bengal, India: A probabilistic risk assessment. Applied Geochemistry,23(11), 2987–2998.CrossRefGoogle Scholar
  43. Muhammad, S., Khan, N. N., Camille, D., Ravi, N., Sana, K., Mahmudur, R. M., et al. (2018). A meta-analysis of the distribution, sources and health risks of arsenic-contaminated groundwater in Pakistan. Environmental Pollution,242, 307–319.CrossRefGoogle Scholar
  44. Nazir, M., & Khan, F. I. (2006). Human health risk modeling for various exposure routes of trihalomethanes (THMS) in potable water supply. Environmental Modelling and Software,21(10), 1416–1429.CrossRefGoogle Scholar
  45. Office of the Women and Children’s Working Committee of the Hebei Provincial Government. (2018). http://www.nwccw.gov.cn/2018-07/03/content_212951.htm.
  46. Ozsvath, D. L. (2009). Fluoride and environmental health: A review. Reviews in Environmental Science and Bio/Technology,8(1), 59–79.CrossRefGoogle Scholar
  47. Parkkila, S., Niemelä, Onni, Savolainen, Eeva-Riitta, & Koistinen, P. (2001). HFE mutations do not account for transfusional iron overload in patients with acute myeloid leukemia. Transfusion,41, 828–831.CrossRefGoogle Scholar
  48. PCRWR. (2005). Annual report 2005–2006, part 2. Islamabad: Pakistan Council for Research in Water Resources.Google Scholar
  49. Radloff, K. A., Zheng, Y., Michael, H. A., Stute, M., Bostick, B. C., Mihajlov, I., et al. (2011). Arsenic migration to deep groundwater in Bangladesh influenced by adsorption and water demand. Nature Geoscience,4(11), 793–798.CrossRefGoogle Scholar
  50. Rahman, M. A., Rahman, A., Khan, M., & Renzaho, A. (2018). Human health risks and socio-economic perspectives of arsenic exposure in Bangladesh: A scoping review. Ecotoxicology and Environmental Safety,150, 335–343.CrossRefGoogle Scholar
  51. Rao, N. S., Rao, P. S., Reddy, G. V., Nagamani, M., Vidyasagar, G., & Satyanarayana, N. L. V. V. (2012). Chemical characteristics of groundwater and assessment of groundwater quality in Varaha river basin, Visakhapatnam district, Andhra Pradesh, India. Environmental Monitoring and Assessment,184(8), 5189–5214.CrossRefGoogle Scholar
  52. Rasmussen, M. L., Folsom, A. R., Catellier, D. J., Tsai, M. Y., Garg, U., & Eckfeldt, J. H. (2001). A prospective study of coronary heart disease and the hemochromatosis gene (HFE) c282y mutation: The atherosclerosis risk in communities (ARIC) study. Atherosclerosis,154(3), 739–746.CrossRefGoogle Scholar
  53. Raza, N., Niazi, S. B., Sajid, M., & Iqbal, F. (2007). Studies on relationship between season and inorganic elements of Kallar Kahar Lake (Chakwal), Pakistan. Journal of Research (Science), Bahauddin Zakariya University, Multan, Pakistan,18, 61–68.Google Scholar
  54. Saba, G., Parizanganeh, A. H., Zamani, A., & Saba, J. (2015). Phytoremediation of heavy metals contaminated environments: Screening for native accumulator plants in Zanjan-Iran. International Journal of Environmental Research,9(1), 309–316.Google Scholar
  55. Sarabjot, K., & Rohit, M. (2019). Toxicological risk assessment of protracted ingestion of uranium in groundwater. Environmental Geochemistry and Health,41, 681–698.CrossRefGoogle Scholar
  56. Sayre, L. M., Perry, G., Atwood, C. S., & Smith, M. A. (2000). The role of metals in neurodegenerative diseases. Cellular and Molecular Biology (Noisy-le-Grand, France),46(4), 731–741.Google Scholar
  57. Shakoor, M. B., Nawaz, R., Hussain, F., Raza, M., Ali, S., Rizwan, M., et al. (2017). Human health implications, risk assessment and remediation of as-contaminated water: A critical review. Science of the Total Environment,601–602, 756–769.CrossRefGoogle Scholar
  58. Siddique, A., Saied, S., Mumtaz, M., Hussain, M. M., & Khwaja, H. A. (2015). Multipathways human health risk assessment of trihalomethane exposure through drinking water. Ecotoxicology and Environmental Safety,116, 129–136.CrossRefGoogle Scholar
  59. Smith, A. H., Lingas, E. O., & Rahman, M. (2000). Contamination of drinking water by arsenic in Bangladesh: A public health emergency. Bulletin of the World Health Organisation,78(9), 1093–1103.Google Scholar
  60. Solgi, E., Esmaili-Sari, A., Riyahi-Bakhtiari, A., & Hadipour, M. (2012). Soil contamination of metals in the three industrial estates, Arak, Iran. Bulletin of Environmental Contamination and Toxicology,88(4), 634–638.CrossRefGoogle Scholar
  61. Su, H., Kang, W., Xu, Y., & Wang, J. (2018). Assessing groundwater quality and health risks of nitrogen pollution in the Shenfu mining area of Shaanxi province, Northwest China. Exposure and Health,10, 77–97.CrossRefGoogle Scholar
  62. Su, X., Wang, H., & Zhang, Y. (2013). Health risk assessment of nitrate contamination in groundwater: A case study of an agricultural area in northeast china. Water Resources Management,27(8), 3025–3034.CrossRefGoogle Scholar
  63. Tang, L. L. (2014). Research on the financing efficiency evaluation of the small and mid-sized scientific enterprises with triangular fuzzy method. Sichuan Province, Mianyang City: Southwest university of science and technology.Google Scholar
  64. Tauhid, U. R. M., Rasheduzzaman, M., Habib, M. A., Ahmed, A., Tareq, S. M., & Muniruzzaman, S. M. (2017). Assessment of fresh water security in coastal Bangladesh: An insight from salinity, community perception and adaptation. Ocean and Coastal Management,137(Complete), 68–81.CrossRefGoogle Scholar
  65. Todd, D. K. (1980). Groundwater hydrology, Wiley International Edition. New York: Wiley.Google Scholar
  66. Ugran, V., Desai, N. N., Chakraborti, D., Masali, K. A., & Das, K. K. (2016). Groundwater fluoride contamination and its possible health implications in Indi taluk of Vijayapura district (Karnataka state), India. Environmental Geochemistry and Health,39(5), 1–13.Google Scholar
  67. Ul-Haque, I., Nabi, D., Baig, M. A., & Hayat, W. (2007). Groundwater arsenic contamination—A multi-directional emerging threat to water scarce areas of Pakistan. In GQ07: Securing groundwater quality in urban and industrial environments (Proceedings 6th international groundwater quality conference held in Fremantle, Western Australia, 27 Dec 2007). Google Scholar
  68. USEPA. (1989). Risk assessment guidance for superfund, vol I., Human health evaluation manual (Part A). Washington, DC: Office of Emergency and Remedial Response.Google Scholar
  69. USEPA (U.S. Environmental Protection Agency). (2009). Risk Assessment Guidance for superfund (Vol. I): human health evaluation manual (Part F, Supplemental Guidance for Inhalation Risk Assessment). Washington DC: Office of Superfund Remediation and Technology Innovation.Google Scholar
  70. USEPA. (1989). Risk assessment guidance for superfund (Vol. I), Human health evaluation manual (Part A). Washington, DC: Office of Emergencyand Remedial Response.Google Scholar
  71. USEPA. Drinkingwater Health Advisory For Manganese. (2004). United States Environmental Protection Agency (p. 20460). Washington, DC: Health and Ecological Criteria Division.Google Scholar
  72. Wang, H. (2017). Fault tree analysis based on TOPSIS and triangular fuzzy number. International Journal of System Assurance Engineering & Management,8(4), 2064–2070.CrossRefGoogle Scholar
  73. Wang, X. F., Deng, C. B., Sunahara, G., Yin, J., Xu, G. P., & Zhu, K. X. (2018a). Risk assessments of heavy metals to children following non-dietary exposures and sugarcane consumption in a rural area in Southern China. Exposure and Health.  https://doi.org/10.1007/s12403-018-0275-0.CrossRefGoogle Scholar
  74. Wang, S., & Huang, G. H. (2012). Identifying optimal water resources allocation strategies through an interactive multi-stage stochastic fuzzy programming approach. Water Resources Management,26(7), 2015–2038.CrossRefGoogle Scholar
  75. Wang, S., Huang, G. H., Lu, H. W., & Li, Y. P. (2011). An interval-valued fuzzy linear programming with infinite α-cuts method for environmental management under uncertainty. Stochastic Environmental Research and Risk Assessment,25(2), 211–222.CrossRefGoogle Scholar
  76. Wang, H. F., Wu, Q. M., Hu, W. Y., Dong, L., & Liu, G. (2018b). Using multi-medium factors analysis to assess heavy metal health risks along the Yangtze River in Nanjing, Southeast China. Environmental Pollution,243, 1047–1056.CrossRefGoogle Scholar
  77. Wang, W. L., Yang, G. Y., & Wang, G. L. (2010). Groundwater numerical model of Haolebaoji well field and evaluation of the environmental problems caused by exploitation. South-to-North Water Transfers and Water Science & Technology,21(2), 255–261.Google Scholar
  78. Wei, C., Guo, H., Zhang, D., Wu, Y., Han, S., An, Y., et al. (2016). Occurrence and hydrogeochemical characteristics of high-fluoride groundwater in Xiji county, southern part of Ningxia province, China. Environmental Geochemistry and Health,38(1), 275–290.CrossRefGoogle Scholar
  79. Weyer, P. J., Cerhan, J. R., Kross, B. C., Hallberg, G. R., Kantamneni, J., Breuer, G., et al. (2001). Municipal drinking water nitrate level and cancer risk in older women: The Iowa women’s health study. Epidemiology,12(3), 327–338.CrossRefGoogle Scholar
  80. World Health Organization (WHO). (2011). Guidelines for drinking water quality (Vol. 4). Geneva: WHO.Google Scholar
  81. Yang, X., Ding, J., & Hou, H. (2013). Application of a triangular fuzzy AHP approach for flood risk evaluation and response measures analysis. Natural Hazards,68(2), 657–674.CrossRefGoogle Scholar
  82. Yang, Q., Li, Z., Ma, H., Wang, L., & Martín, J. (2016). Identification of the hydrogeochemical processes and assessment of groundwater quality using classic integrated geochemical methods in the southeastern part of Ordos basin, China. Environmental Pollution,218, 879–888.CrossRefGoogle Scholar
  83. Yang, S., Yang, Q., Ma, H., Liang, J., Niu, C., & Martin, J. (2018). Health risk assessment of phreatic water based on triangular fuzzy theory in Yinchuan plain. Ecotoxicology and Environmental Safety,164, 732–738.CrossRefGoogle Scholar
  84. Yousefi, M., Ghoochani, M., & Mahvi, A.H. (2018). Health risk assessment to fluoride in drinking water of rural residents living in the poldasht city, northwest of Iran. Ecotoxicology and Environmental Safety, 148, 426–430.CrossRefGoogle Scholar
  85. Zadeh, L. A. (1965). Fuzzy set. Information and Control,8(3), 338–353.CrossRefGoogle Scholar
  86. Zang, F., Wang, S., Nan, Z., Ma, J., Zhang, Q., Chen, Y., et al. (2017). Accumulation, spatio-temporal distribution, and risk assessment of heavy metals in the soil-corn system around a polymetallic mining area from the Loess Plateau, Northwest China. Geoderma,305(5), 188–196.CrossRefGoogle Scholar
  87. Zhai, Y., Zhao, X., Teng, Y., Li, X., Zhang, J., Wu, J., et al. (2017). Groundwater nitrate pollution and human health risk assessment by using HHRA model in an agricultural area, NE China. Ecotoxicology and Environmental Safety,137, 130–142.CrossRefGoogle Scholar
  88. Zhang, H. T. (2015). Risk assessment on non-point nitrogen pollution in groundwater. China: Jilin University.Google Scholar
  89. Zhang, K. (2009). Modeling uncertainty and variability in health risk assessment of contaminated sites. Thesis (Ph.D.), Department of Civil Engineering, University of Calgary, Calgary, AB, Canada.Google Scholar
  90. Zhang, K., & Achari, G. (2010). Uncertainty propagation in environmental decision making using random sets. Procedia Environmental Sciences,2(none), 576–584.CrossRefGoogle Scholar
  91. Zhang, Li′e, Huang, D., Yang, J., Wei, X., Qin, J., Ou, S., et al. (2017). Probabilistic risk assessment of chinese residents\” exposure to fluoride in improved drinking water in endemic fluorosis areas. Environmental Pollution,222, 118–125.CrossRefGoogle Scholar
  92. Zhang, Y., Wu, J., & Xu, B. (2018). Human health risk assessment of groundwater nitrogen pollution in Jinghui canal irrigation area of the Loess Region, Northwest China. Environmental Earth Sciences,77(7), 273.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Zijun Li
    • 1
  • Kun Yang
    • 2
  • Chuan Xie
    • 2
  • Qingchun Yang
    • 1
    Email author
  • Xiaohui Lei
    • 3
  • Hao Wang
    • 3
  1. 1.Key Laboratory of Groundwater Resources and Environment Ministry of EducationJilin UniversityChangchunPeople’s Republic of China
  2. 2.Geothermal Institute of Hydrological Engineering Geological SurveyShijiazhuangPeople’s Republic of China
  3. 3.China Institute of Water Resources and Hydropower ResearchBeijingPeople’s Republic of China

Personalised recommendations