The water quality assessment of the surface water bodies (SWBs) is one of the major tasks of environmental authorities dealing with water management. The present study proposes a water quality assessment scheme for the investigation of the surface waters’ physicochemical status changes and the identification of significant anthropogenic pressures. It is designed to extract valuable knowledge from the Water Frame Directive (WFD) mandatory monitoring datasets. The water quality assessment scheme is based on the Canadian Council of Ministers of the Environment water quality index (CCME-WQI), trend analysis of estimated WQI values, and Principal Component Analysis (PCA) using calculated excursions during the determination of WQI values. The combination of the abovementioned techniques preserves their benefits and additionally provides important information for water management by revealing the latent factors controlling water quality, taking into account the type of the SWB. The results enable the identification of the anthropogenic impact on SWBs and the type of the corresponding anthropogenic pressure, prioritization and monitoring restoration measures, and optimization of conducted monitoring programs to reflect significant anthropogenic pressures. The proposed simple and reliable assessment scheme is flexible to introducing additional water quality indicators (hydrological, biological, specific pollutants, etc.), which could lead to a more comprehensive surface water quality assessment.

Background: An improved understanding of copper metabolism is needed to derive more precise estimates of dietary requirements. Objectives: The objectives were to validate a method for estimating endogenous losses of copper, test whether a simple model can predict true absorption from the plasma appearance of labeled copper, and develop a compartmental model for copper metabolism by using stable isotopes. Design: A stable isotope of copper was intravenously administered to 6 men, and fecal samples were collected for 14 d. Four weeks later the study was repeated, but with an oral dose, and blood samples were collected for 7 d and fecal samples for 14 d. Results: There was no significant difference (P = 0.48) in the estimated endogenous loss of copper calculated by using either the excreted intravenous dose (x̄ ± SD: 32 ± 5%) or the absorbed and excreted oral dose (35 ± 2%). A simple mathematical model fitted to plasma isotope appearance data estimated true absorption to be 8 ± 2% compared with 48–49% measured by fecal monitoring. A more complicated compartmental model predicted that, when newly absorbed copper first enters the blood, 74% is removed by the liver and 99% is bound to ceruloplasmin in the plasma. The exchangeable pool of copper was estimated to be 43 ± 30 mg. Daily endogenous losses were predicted to be 2.4 mg. Conclusions: The results showed that fecal monitoring is the only method that can reliably measure labeled copper absorption, and it is not necessary to administer an intravenous dose of copper to estimate endogenous losses. The compartmental model provides new insights into human copper metabolism.

Deterioration of water quality is a major problem world widely according to many international non-governmental organizations (NGO). As one of the European Union (EU) countries, Bulgaria is also obliged by EU legislation to maintain best practices in assessing surface water quality and the efficiency of wastewater treatment processes. For these reasons studies were undertaken to utilize ecotoxicological (Microtox^®, Phytotoxkit F^TM, Daphtoxkit F^TM), instrumental (to determine pH, electrical conductivity (EC), chemical oxygen demand, total suspended solids (TSS), total nitrogen (N) and phosphorus (P), chlorides, sulphates, Cr, Co, Cu, Cd, Ba, V, Mn, Fe, Ni, Zn, Se, Pb), as well as advanced chemometric methods (partial least squares–discriminant analysis (PLS-DA)) in data evaluation to comprehensively assess wastewater treatment plants’ (WWTPs) effluents and surface waters quality around 21 major Bulgarian cities. The PLS-DA classification model for the physicochemical parameters gave excellent discrimination between WWTP effluents and surface waters with 93.65% correct predictions (with significant contribution of EC, TSS, P, N, Cl, Fe, Zn, and Se). The classification model based on ecotoxicological data identifies the plant test endpoints as having a greater impact on the classification model efficiency than bacterial, or crustaceans’ endpoints studied.