A probabilistic water quality index for river water quality assessment: a case study

Available water quality indices have some limitations such as incorporating a limited number of water quality variables and providing deterministic outputs. This paper presents a hybrid probabilistic water quality index by utilizing fuzzy inference systems (FIS), Bayesian networks (BNs), and probabilistic neural networks (PNNs). The outputs of two traditional water quality indices, namely the indices proposed by the National Sanitation Foundation and the Canadian Council of Ministers of the Environment, are selected as inputs of the FIS. The FIS is trained based on the opinions of several water quality experts. Then the trained FIS is used in a Monte Carlo analysis to provide the required input-output data for training both the BN and PNN. The trained BN and PNN can be used for probabilistic water quality assessment using water quality monitoring data. The efficiency and applicability of the proposed methodology is evaluated using water quality data obtained from water quality monitoring system of the Jajrood River in Iran.     

Assessment of dietary intakes of nineteen pesticide residues among five socioeconomic sections of Hyderabad—a total diet study approach

Total diet study approach was used to assess the dietary intakes of pesticide residues among the select population in Hyderabad. When assessed by a food frequency questionnaire, it was found that the food intakes varied among five socioeconomic sections (SES). Therefore, we intended to compare the intakes of pesticide residues through these foods among the five SES. A total of 195 foods from different markets were collected and analyzed for 19 pesticides. The residues were analyzed with a gas chromatograph and were confirmed with mass spectrometry. About 51 % of the samples were detected with one or more residues. Thirteen out of the 19 residues were present in levels above detection limits in various concentrations. The median concentrations of the residues in all the samples tested, ranged from 0.00010 to 0.33 mg/kg. Highest median concentration was for β-HCH in water samples. Exposures to all the residues were below the respective ADIs at both mean and 95th percentile levels of food intakes with highest estimated dietary intakes (EDIs) of β-HCH in both the cases. The EDIs of β-HCH were the highest among all the residues at both the intake levels among all the SES. The EDIs of β-HCH were significantly higher in lower SES than higher SES possibly due to the consumption of rice cooked in water contaminated with β-HCH. EDIs for other residues did not differ significantly among the five SES.