Human Health Risk Assessment of Contaminants in Drinking Water Based on Triangular Fuzzy Numbers Approach in Yinchuan City, Northwest China

Access to safe drinking water is one of the fundamental human rights and an important component of healthy life. In this paper, the triangular fuzzy numbers approach has been used for recognizing uncertainties in the estimation of health risks proposed by the United States Environmental Protection Agency in Yinchuan city, northwest China. The levels of As, Cd, Cr, Mn, Cu, Zn, Hg, Pb, F, NO3-N, and NH4-N in drinking water were within the permissible limits except for Fe. The results showed that the health risks were primarily attributed by Cr, As, and F in drinking water. When the confidence level was 0.8, the total carcinogenic and noncarcinogenic risks values were less than the acceptable risk levels (10−4 and 1.0) set by the USEPA, respectively. The health risk of drinking water in Yinchuan city is as follows: Nanjiao water source > Beijiao water source > Dongjiao water source. Furthermore, the total noncarcinogenic risks were more sensitive with respect to different confidence levels. The spatial distribution of As and F levels in drinking water sources is urgently needed to be ascertained in drinking water, especially for Nanjiao water source. The health risk assessment model based on the triangular fuzzy numbers approach is effective to quantify uncertainty in risks with less complexity. The findings in this paper will help managers minimize the potential health risks and provide a new insight for solving uncertainties in water management.

[1]  O. Akoto,et al.  Health risk assessment of heavy metals and metalloid in drinking water from communities near gold mines in Tarkwa, Ghana , 2015, Environmental Monitoring and Assessment.

[2]  L. Wan,et al.  Hydrochemical and isotopic study of groundwater in the Yinchuan plain, China , 2013, Environmental Earth Sciences.

[3]  Vilém Novák,et al.  Fuzzy Set , 2009, Encyclopedia of Database Systems.

[4]  H. Qian,et al.  Nitrogen contamination in groundwater in an agricultural region along the New Silk Road, northwest China: distribution and factors controlling its fate , 2017, Environmental Science and Pollution Research.

[5]  Juliang Jin,et al.  Risk evaluation of China’s natural disaster systems: an approach based on triangular fuzzy numbers and stochastic simulation , 2012, Natural Hazards.

[6]  Peiyue Li,et al.  Progress, opportunities, and key fields for groundwater quality research under the impacts of human activities in China with a special focus on western China , 2017, Environmental Science and Pollution Research.

[7]  Yahong Zhou,et al.  Groundwater Quality Evaluation and Health Risk Assessment in the Yinchuan Region, Northwest China , 2016, Exposure and Health.

[8]  Peiyue Li,et al.  Assessment of groundwater vulnerability in the Yinchuan Plain, Northwest China using OREADIC , 2012, Environmental Monitoring and Assessment.

[9]  Inmaculada Ortiz,et al.  Arsenic and fluoride contaminated groundwaters: A review of current technologies for contaminants removal. , 2015, Journal of environmental management.

[10]  D. Kostić,et al.  Statistical characteristics of selected elements in vegetables from Kosovo , 2015, Environmental Monitoring and Assessment.

[11]  Peiyue Li,et al.  Origin and assessment of groundwater pollution and associated health risk: a case study in an industrial park, northwest China , 2014, Environmental Geochemistry and Health.

[12]  Peiyue Li,et al.  Appraising Groundwater Quality and Health Risks from Contamination in a Semiarid Region of Northwest China , 2016, Exposure and Health.

[13]  Bo Gao,et al.  Occurrence and health risk assessment of selected metals in drinking water from two typical remote areas in China , 2016, Environmental Science and Pollution Research.

[14]  Jie Chen,et al.  Assessing Nitrate and Fluoride Contaminants in Drinking Water and Their Health Risk of Rural Residents Living in a Semiarid Region of Northwest China , 2017, Exposure and Health.

[15]  Noor Jehan,et al.  Drinking water quality and human health risk in Charsadda district, Pakistan , 2013 .

[16]  J. Ahn Geochemical occurrences of arsenic and fluoride in bedrock groundwater: a case study in Geumsan County, Korea , 2011, Environmental Geochemistry and Health.

[17]  M. Stute,et al.  Arsenic migration to deep groundwater in Bangladesh influenced by adsorption and water demand , 2011, Nature geoscience.

[18]  K. Dragon Groundwater nitrate pollution in the recharge zone of a regional Quaternary flow system (Wielkopolska region, Poland) , 2013, Environmental Earth Sciences.

[19]  P. Tchounwou,et al.  Heavy metal toxicity and the environment. , 2012, Experientia supplementum.

[20]  Lazhar Belkhiri,et al.  Using Multivariate Statistical Analysis, Geostatistical Techniques and Structural Equation Modeling to Identify Spatial Variability of Groundwater Quality , 2015, Water Resources Management.

[21]  Honghan Chen,et al.  Investigation of quality and pollution characteristics of groundwater in the Hutuo River Alluvial Plain, North China Plain , 2016, Environmental Earth Sciences.

[22]  Xi Wu,et al.  Spatial and temporal patterns of groundwater arsenic in shallow and deep groundwater of Yinchuan Plain, China , 2013 .

[23]  Yan Zheng,et al.  At the crossroads: Hazard assessment and reduction of health risks from arsenic in private well waters of the northeastern United States and Atlantic Canada. , 2015, The Science of the total environment.

[24]  Yong Deng,et al.  Fault tree analysis based on TOPSIS and triangular fuzzy number , 2017, Int. J. Syst. Assur. Eng. Manag..

[25]  D. Dubois,et al.  Operations on fuzzy numbers , 1978 .

[26]  Wanfang Zhou,et al.  Finding harmony between the environment and humanity: an introduction to the thematic issue of the Silk Road , 2017, Environmental Earth Sciences.

[27]  Hui Hou,et al.  Application of a triangular fuzzy AHP approach for flood risk evaluation and response measures analysis , 2013, Natural Hazards.

[28]  S. Suthar,et al.  Nitrate contamination in groundwater of some rural areas of Rajasthan, India. , 2009, Journal of hazardous materials.

[29]  Hui Qian,et al.  Building a new and sustainable “Silk Road economic belt” , 2015, Environmental Earth Sciences.

[30]  M. Gardner,et al.  Confidence intervals rather than P values: estimation rather than hypothesis testing. , 1986, British medical journal.

[31]  A. Smith,et al.  Contamination of drinking-water by arsenic in Bangladesh: a public health emergency. , 2000, Bulletin of the World Health Organization.

[32]  H. Qian,et al.  Challenges and prospects of sustainable groundwater management in an agricultural plain along the Silk Road Economic Belt, north-west China , 2018 .

[33]  D. Deere,et al.  Water Quality : Guidelines , Standards and Health , 2003 .

[34]  Gordon H. Huang,et al.  An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination. , 2007, Journal of environmental management.

[35]  Peiyue Li,et al.  Hydrochemical appraisal of groundwater quality for drinking and irrigation purposes and the major influencing factors: a case study in and around Hua County, China , 2015, Arabian Journal of Geosciences.

[36]  M. Neuberger [Heavy metals--toxicity at low doses in the environment and in the work place]. , 1984, Acta medica Austriaca.

[37]  Oliver Schmoll ... et al. Protecting groundwater for health , 2013 .

[38]  Hector Malano,et al.  Assessment of Sustainability of Urban Water Supply and Demand Management Options: A Comprehensive Approach , 2016 .

[39]  A. Vengosh,et al.  Groundwater quality and its health impact: An assessment of dental fluorosis in rural inhabitants of the Main Ethiopian Rift. , 2012, Environment international.

[40]  H. Qian,et al.  Groundwater Nitrate Contamination and Associated Health Risk for the Rural Communities in an Agricultural Area of Ningxia, Northwest China , 2016, Exposure and Health.

[41]  Cungen Cao,et al.  Multiplication Operation on Fuzzy Numbers , 2009, J. Softw..

[42]  J Maiti,et al.  Modeling uncertainty in risk assessment: an integrated approach with fuzzy set theory and Monte Carlo simulation. , 2013, Accident; analysis and prevention.

[43]  H. Qian,et al.  Assessment of arsenic and fluoride pollution in groundwater in Dawukou area, Northwest China, and the associated health risk for inhabitants , 2017, Environmental Earth Sciences.

[44]  Jianfeng Tang,et al.  Health risk assessment of heavy metals and bacterial contamination in drinking water sources: a case study of Malakand Agency, Pakistan , 2016, Environmental Monitoring and Assessment.

[45]  K. Lee,et al.  Groundwater pumping effects on contaminant loading management in agricultural regions. , 2014, Journal of environmental management.

[46]  Dongguang Wen,et al.  Arsenic, fluoride and iodine in groundwater of China , 2013 .