Karyab Hamid, Hajimirmohammad-Ali Razieh, Bahojb Akram
1Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Bahonar Blvd, Qazvin, Iran.
2Bio-Medical Technology Center, Qazvin University of Medical Sciences, Bahonar Blvd, Qazvin, Iran.
J Environ Health Sci Eng. 2019 Mar 30;17(1):457-465. doi: 10.1007/s40201-019-00364-z. eCollection 2019 Jun.
This study was conducted to assess the capability of the lumped parameter model (LPM), an efficient model due to its analytical nature and the limited data requirements, to estimate health risks from nitrate in groundwater in arid and semi-arid climates.
To assess the capability of LPM, two scenarios were established: one for estimation of hazard quotient (HQ) via monitoring nitrate concentration in groundwater and the other using the LPM. After nitrate was monitored in 148 randomly-selected wells, a modified LPM was used to estimate water volume and nitrate concentration, which ultimately led to the development of a model for estimating HQ. The performances of LPM were assessed using the coefficient of determination, percentage standard deviation, and root mean square error. To compare health risk maps Kriging, Spline, Inverse distance weighted, and natural neighbor models were run using geographical information system (GIS).
Linear analysis revealed a strong correlation between HQ values estimated in LPM and monitoring scenarios in arid climate compared to semi-arid ( = 0.962, = 22, = 0.00), suggesting that the LPM was more accurate in predicting nitrate concentration in the arid climate. Uncertainty analysis showed that LPM outputs were sensitive to several parameters, especially leakage from cesspits, which are involved in the sources and sinks of nitrate in the groundwater. In addition, it was found that the natural neighbor was the most appropriate model with the lowest errors for preparing health risk maps from nitrate.
The obtained results revealed that LPM can be effectively used to estimate nitrate concentration in groundwater in arid climates and thereby LPM is an appropriate model to estimate health risk from nitrate in this climate.
本研究旨在评估集总参数模型(LPM)估算干旱和半干旱气候地区地下水中硝酸盐健康风险的能力,该模型因其分析性质和有限的数据需求而成为一种高效模型。
为评估LPM的能力,建立了两种情景:一种是通过监测地下水中硝酸盐浓度来估算危害商(HQ),另一种是使用LPM。在对148口随机选取的水井进行硝酸盐监测后,使用改进的LPM估算水量和硝酸盐浓度,最终建立了一个估算HQ的模型。使用决定系数、百分比标准差和均方根误差评估LPM的性能。为比较健康风险地图,使用地理信息系统(GIS)运行克里金法、样条法、反距离加权法和自然邻域模型。
线性分析表明,与半干旱气候相比,干旱气候下LPM估算的HQ值与监测情景之间存在很强的相关性(=0.962,=22,=0.00),这表明LPM在预测干旱气候下的硝酸盐浓度方面更准确。不确定性分析表明,LPM的输出对几个参数敏感,特别是污水坑的渗漏,这涉及地下水中硝酸盐的源和汇。此外,发现自然邻域模型是根据硝酸盐绘制健康风险地图时误差最小的最合适模型。
所得结果表明,LPM可有效用于估算干旱气候地区地下水中的硝酸盐浓度,因此LPM是估算该气候下硝酸盐健康风险的合适模型。