Tool for selecting indicator substances to evaluate the impact of wastewater treatment plants on receiving water bodies
Autor: | Joachim Reichert, Kassandra Klaer, Monika Hammers-Wirtz, Silke Classen, Johannes Pinnekamp, Ira Brückner |
---|---|
Rok vydání: | 2020 |
Předmět: |
Pollution
Environmental Engineering 010504 meteorology & atmospheric sciences media_common.quotation_subject Transferability Detailed data 010501 environmental sciences Pulp and paper industry 01 natural sciences Water body Wastewater Environmental Chemistry Environmental science Sewage treatment Water quality Water pollution Waste Management and Disposal 0105 earth and related environmental sciences media_common |
Zdroj: | Science of The Total Environment. 745:140746 |
ISSN: | 0048-9697 |
Popis: | The elimination of organic micropollutants (OMPs) from wastewater could in future become mandatory for operators of wastewater treatment plants (WWTPs). Indicator substances are a great help and a cost-efficient way in monitoring the pollution of water bodies with OMPs caused by the discharge of WWTPs. However, with the still increasing number of OMPs in our environment, the selection of suitable indicator substances presents a challenge. A concept was developed to help identify representative indicator substances. The derived indicator substances are not only used to assess water pollution, but can also be used to calculate elimination efficiencies of WWTPs. In the present investigations, the indicator substances were used to evaluate the reduction of OMPs in the water body on the basis of the expansion of a WWTP with an ozonation plant. The transferability of the tool was verified with a second WWTP. Furthermore, the impact of the number of measurements was analysed via statistical combinatorics. With the tool, 36 substances were classified, leading to the identification of 9 suggested indicator substances. Among them ibuprofen and diclofenac attracted attention due to their ecotoxicological relevance. Detailed data analyses were carried out using principal component analysis (PCA) and loads. |
Databáze: | OpenAIRE |
Externí odkaz: |