According to results of the estimation of drinking water on the index of the chemical harmlessness of five water intake structures of the city of Ufa, the drinking water of a superficial water intake on total and population cancerogenic risks was shown to be more harmful in comparison with water from infiltration water intakes. At the same time, drinking water from an infiltration water intake with ultra-violet disinfecting has smallest values of cancerogenic and non-cancerogenic risks. Trigalogenmetans and dichloroacetic acid (water disinfection chlorine by-products)| make the main contribution to the value of the total cancerogenic risk of the studied drinking waters, trigalogenmetans and di(2-ethylhexyl)phthalate make the contribution to the value of noncancerogenic risk. Polycyclic Aromatic Hydrocarbons fail to have a significant impact on the value of total cancerogenic risk of drinking water of the city in view of their presence at low concentration. Work is carried out according to R 2.1.10.1920-04 and MR 2.1.4.0032-11.
Introduction. To conduct a total assessment of carcinogenic, non-carcinogenic, and organoleptic risks to public health and cover both normalized and non-normalized pollutants of potable water, based on the results of long-term monitoring studies, it is possible using an integral indicator of chemical harmlessness of water. Material and methods. Authors studied potable water of water intakes of surface and infiltration types from potable water reservoirs and remote zones of Ufa water distribution networks. Impurities were determined by chromatography, inductively coupled plasma mass spectrometry, photometric, nephelometric, and titrimetric methods. Results. The main effect on the amount of carcinogenic risk in potable water of the surface water intake are chloroform, bromodichlethane, dichloroacetic acid, in the infiltration water intake - in addition to these compounds zinc, lead and chromium are in addition influenced. Organic compounds (phthalates, benz(a)pyrene, volatile aromatic compounds, etc.) have no effect on this type of risk due to the presence in water in low background concentrations. The identified number of individual carcinogenic risks for bromodichloroacetic acid and dichloroacetic acid according to the WHO classification corresponds to the second range. As the surface type water intake is removed from the potable water reservoir, the total carcinogenic risk of water decreases by 13-30%, and the infiltration type increases by 41-84%. Values of noncancerogenic and organoleptic risks are constant for potable water of different water intakes and correspond to recommended limit values. The excess of the maximum permissible concentrations (SanPin 1.2.3685-21) of individual substances in the potable water of the city has not been detected for the whole period of observation. In terms of the integral indicator of chemical harmlessness, the most favorable is the po-table water of the infiltration water intake, in the technology of which is mainly used the UV for decontamination of water. Conclusion. Using a risk assessment methodology complements the traditional approach to assessing water quality under modern hygiene standards. It becomes possible to evaluate the effect of pollutants of various classes on water quality when they are present together.
Regression and neural network model for predicting the required dose of coagulant, depending on the quality of river water supplied for water treatment, are considered, their comparative analysis is carried out. For modelling and forecasting, statistical data collected for the period from 2005 to nowadays. Regression models were built on the true values of the factors (water quality indicators) and on their first differences to eliminate the trend in the series. For the models built on the true values, the statistical significance, was confirmed, high values of the coefficient of the determination were obtained, the values of the approximation errors were 22–25 %. In neural network modelling, networks of the multilayer perception were used. Generalization error on the test set when using other type of networks (RBF-networks, Elman networks), was significant above. Computational experiments have shown that, in general, the accuracy of neural network models is higher than regression ones. The average learning error was 7–9 %, the error on the test set increases to 12–16 %. The reliability of the forecast is increased by training the network on more recent data and using a larger set of facts. An increase in the influence of indicators of permanganate oxidability and colour of the initial river water on the dose of reagents with a simultaneous decrease in the degree of influence of alkalinity over the last five-year period was revealed. This confirms the need to periodically update data for building models. Selected models recommended for implementation in industrial monitoring of water treatment technology at the enterprise.
An approach based on the quantitative determination of squalene biomarker by the chromato mass spectrometry method has been proposed for assessment of the intensity of biotransformation of organic compounds in water. The method sensitivity amounted to 5 × 10 -5 mg/dm 3 . It is recommended to use squalene for the detection of stagnant zones in the city water distribution system and the biological activity in filtering layers of wells of infiltration water intakes and in filters for industrial and domestic water treatment. An enhanced intensity of biotransformation processes is related to the rise of squalene concen tration in the tested water.
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