Evolution of the sewage treatment plant model SimpleTreat: Applicability domain and data requirements

Abstract

SimpleTreat 3.1 is the sewage treatment plant (STP) model implemented in the European Union (EU) framework for the environmental risk assessment of chemicals. The model was originally designed for neutral hydrophobic chemicals, whereas many substances currently under regulatory scrutiny, are ionizable at environmental pH. Although the model has been adapted to describe ionization (SimpleTreat 3.1), the fate of organic ions is limited to the unbound aqueous phase, which seriously restricts the applicability domain. New regressions were implemented to estimate the sludge-water partition coefficient normalized to organic carbon (KOC ) of monovalent acids and bases from the octanol-water partition coefficient (KOW ), the dissociation constant (pKa) and the pH. We evaluated the updated model (SimpleTreat 3.2) with 10 test chemicals by comparing predictions with monitoring data collected from the literature. Test chemicals were specifically selected to challenge the applicability domain and to cover a wide range of functionality and physical-chemical properties. Although predicted effluent concentrations are generally conservative, SimpleTreat 3.2 provides reasonable estimates for use in lower-tier risk assessment for neutral and monovalent ionizable chemicals. The accuracy of the new KOC regressions is acceptable for monovalent acid but is lower for bases, for which measured sludge KOC is highly recommended. Measured KOC are also recommended for ionic surfactants and necessary for organic ligands, which may limit the applicability of SimpleTreat using a basic input data set. The conservative nature of model estimates reflects the default worst case, non-numerical parameterization of biodegradation rates and the assumption that biodegradation is limited to the unbound aqueous phase. The potential of refining the description of biodegradation using higher tier simulation tests is explored in a parallel article (Franco et al. this issue).

Evolution of the sewage treatment plant model SimpleTreat: Use of realistic biodegradability tests in probabilistic model simulations

“…SimpleTreat 3.1 is recommended in regulatory environmental risk assessments of chemicals in home and personal care products, industrial chemicals (REACH) (EC ), biocides (Biocidal Products Regulation) (EC ) and pharmaceuticals (European Medicines Agency ). The model has been updated to incorporate new algorithms to improve the estimation of the partitioning behavior of ionizable chemicals, making it applicable to a wider range of substances (Franco et al this issue). SimpleTreat 3.1 is usually run with a basic input data set and due to its worst‐case parameterization, predictions tend to be conservative.…”

“…SimpleTreat 3.1 is usually run with a basic input data set and due to its worst‐case parameterization, predictions tend to be conservative. Results of the evaluation study with 9 test chemicals, including neutral and ionizable substances, have shown that SimpleTreat underestimates the removal efficiency, in particular for readily and inherently biodegradable substances (Franco et al this issue), in agreement with previous observations (HERA ; Geerts et al ). The underestimation of removal efficiency is in most cases due to the default first‐order biotransformation rate constants, assigned based on the non‐numerical results of screening biodegradability tests (i.e., OECD 301 or OECD 302) and applied only to the fraction of chemical dissolved in water.…”

Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes

“…Consequently, models have also been developed for APIs in different ion classes (Dobbs et al, 1989, Franco et al, 2009, Franco et al, 2013, Franco and Trapp, 2008, Guo et al, 2004, Sabljic et al, 1995). Recent work by Sathyamoorthy and Ramsburg (2013) derived separate multivariate models to predict K d values (at the experimental pH used for the measurements) for uncharged, and positively and negatively charged APIs, and combined models for their whole dataset.…”

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

“…For TCS and CIP, this resulted from an underestimation of removal via sorption to sewage sludge. Accordingly, Franco et al (2013a) suggested using measured K d values as input to SimpleTreat, though neglecting the impact of different sorption potentials of neutral and ionized species.…”