Sofia University "St. Kliment Ohridski", Faculty of Chemistry and Pharmacy, Chair of Analytical Chemistry, 1164 Sofia, Bulgaria.
University of Architecture, Civil Engineering and Geodesy, Faculty of Hydraulic Engineering, Chair of Water Supply, Water and Wastewater Treatment, 1046 Sofia, Bulgaria.
Molecules. 2019 Jun 18;24(12):2274. doi: 10.3390/molecules24122274.
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, Daphtoxkit F), 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.
根据许多国际非政府组织（NGO）的说法，水质恶化是一个全球性的主要问题。保加利亚作为欧盟（EU）成员国之一，也有义务按照欧盟立法，保持对地表水水质和废水处理过程效率进行最佳评估的做法。出于这些原因，进行了研究，以利用生态毒理学（Microtox、Phytotoxkit F、Daphtoxkit F）、仪器（用于测定 pH 值、电导率（EC）、化学需氧量、总悬浮固体（TSS）、总氮（N）和磷（P）、氯化物、硫酸盐、Cr、Co、Cu、Cd、Ba、V、Mn、Fe、Ni、Zn、Se、Pb）以及先进的化学计量学方法（偏最小二乘判别分析（PLS-DA））对数据进行评估，以全面评估 21 个主要保加利亚城市周围的废水处理厂（WWTP）的废水和地表水水质。理化参数的 PLS-DA 分类模型在 WWTP 废水和地表水之间进行了出色的区分，正确预测率为 93.65％（EC、TSS、P、N、Cl、Fe、Zn 和 Se 有显著贡献）。基于生态毒理学数据的分类模型表明，与所研究的细菌或甲壳类动物终点相比，植物测试终点对分类模型效率的影响更大。
