Evaluation of QSPR Techniques for Wastewater Treatment Processes
Authors: Dickenson, Eric R. V.; Drewes, Jörg E.; Stevens-Garmon, John; Khan, Stuart; McDonald, James
Source: Proceedings of the Water Environment Federation, WEFTEC 2010: Session 51 through Session 60 , pp. 4084-4096(13)
Publisher: Water Environment Federation
Abstract:
Most households regularly use products containing trace organic compounds (TOrCs), which ultimately end up in municipal wastewater treatment systems. In order to assess the exposure of these compounds to the environment there is a need to evaluate their removal within wastewater treatment systems. Quantitative structure property relationships (QSPR) techniques are potential powerful tools to providing water utilities a means to screen rapidly and accurately the fate of TOrCs during wastewater treatment processes and to assess TOrC risk exposures. This study investigated the evaluation of existing QSPRs applicable for the following wastewater treatment fate processes: sorption to sludge solid phases, transformation during biological activated-sludge treatment, and chlorine oxidation processes. A comprehensive literature review of existing biodegradation, sorption and chlorine oxidation QSPRs was performed. The review was used to assess the applicability of existing QSPRs for wastewater treatment systems and identify which QSPRs warrant evaluation. Selected predictive QSPRs were statistically evaluated using experimental biotransformation, sorption and chlorine oxidation fate parameters reported in the literature and measured in this study during laboratory-batch studies. One-parameter log Kowbased models turned out to be the best sorption QSPR models for neutral compounds. Simplified QSPRs are lacking for ionizable organic compounds. The most commonly employed biodegradation SPRs provide the tendency of biotransformation or biodegradation of an organic compound. The reason for this qualitative assessment is that limited consistent and good-quality biodegradation kinetic data are available. This project evaluated U.S. EPA's qualitative BIOWIN SPR models and EPI Suite's semi-quantitative method for estimating biodegradation half-lives. No single BIOWIN model accurately predicted both biodegradable and nonbiodegradable compounds and the half-life technique was conservative in its approach for the removal of TOrCs. What are still lacking are accurate QSPRs that can estimate quantitatively biotransformation and/or biodegradation rates of TOrCs during activated-sludge treatment. Limited QSPRs exist to assess chlorine oxidation of TOrCs. The reason for this is the limited chlorine oxidation kinetic data available. A few models have been developed, but they are only applicable to specific classes of compounds. One QSPR was evaluated, which reasonably predicted the rate constant for a validation set of phenoxide-ion type of compounds and sulfamethoxazole.Keywords: wastewater treatment; trace organic compounds; emerging organic contaminants; quantitative structure property relationships; biotransformation; sorption; chlorination
Document Type: Research article
Publication date: 2010-01-01
- Proceedings of the Water Environment Federation is an archive of papers published in the proceedings of the annual Water Environment Federation® Technical Exhibition and Conference (WEFTEC® ) and specialty conferences held since the year 2000. These proceedings are not peer reviewed. WEF Members: Sign in (right panel) with your IngentaConnect user name and password to receive complimentary access.
- Subscribe to this Title
- Membership Information
- About WEF Proceedings
- WEFTEC Conference Information
- ingentaconnect is not responsible for the content or availability of external websites
- In this: publication
- By this: publisher
- In this Subject: Earth and Environmental Sciences , General & Civil Engineering , Hydraulic & Environmental Engineering
- By this author: Dickenson, Eric R. V. ; Drewes, Jörg E. ; Stevens-Garmon, John ; Khan, Stuart ; McDonald, James

Shopping cart
Receive new issue alert
Get Permissions