Prediction Of Environmental Fate Research Articles

Prioritization of pharmaceuticals in drinking water exposure based on toxicity and environmental fate assessment by in silico tools: An integrated and transparent ranking

The concentration of pharmaceuticals in water and health risk to the human population is a topic of concern among the scientific community, regulators, and the general population. Many recent studies have suggested different, even conflicting, criteria for the definition of priority pharmaceuticals for drinking-water exposure. In this work, we assessed 10 endpoints of environmental fate and human toxicity for 39 active pharmaceutical ingredients (APIs) by in silico models and data review. A visual and transparent Toxicological Prioritization Index (ToxPi) was proposed based on in silico, in chemico, in vitro, and in vivo results. Predictions of environmental fate and toxicity were made through in silico models of EPISuiteTM, PBT Profiler v.2, TEST v4.2 and QSAR Toolbox v.3.2. The software ToxPi GUI was used to create a multicriteria-based ranking with environmental fate and human toxicity endpoints to identify priority compounds. Our multicriteria ranking (fate and hazard-based) suggested that the some of the most concerning APIs were metronidazole (ToxPi: 5.67; CI95%: 5.51–5.83), nitrofurantoin (ToxPi: 5.22 CI95%: 5.21–5.22) and ethinylestradiol (ToxPi: 5.20; CI95%: 4.70–5.79). Different APIs may represent high level of concern by different characteristics of environmental exposure and/or toxicity, and our visual muticriteria ranking can support targeted decision-making. Computational tools may be important for predicting environmental fate and toxicity as well as visually identifying priority compounds by multicriteria-based rankings and predicting compounds with high priority to support more targeted multicriteria decision-making, risk assessment, and monitoring steps.

Estimation of U.S. sewer residence time distributions for national-scale risk assessment of down-the-drain chemicals

Sewer residence time (the amount of time a given volume of wastewater resides in a sewer system prior to treatment) can have a significant influence on predictions of environmental fate and transport of wastewater constituents and corresponding risk assessment. In this study, a geographic information systems-based approach for estimating the distribution of sewer residence times for the U.S. was developed using road networks as a spatial proxy for sewer networks. The suitability of the approach was evaluated using case study municipalities, and the approach was subsequently extrapolated to 3422 wastewater treatment facilities of varying size across the U.S. to estimate a national distribution of sewer residence times. The estimated national median residence time for the U.S. was 3.3h. Facilities serving smaller municipalities (<1 million gallons per day) had comparatively shorter sewer residence times to facilities serving larger municipalities, though the latter comprise a greater proportion of overall national wastewater volume. The results of this study provide an important data resource in combination with chemical in-sewer biodegradation data to enable probabilistic risk assessment of consumer product chemicals disposed of down the drain.

The partition behavior of tributyltin and prediction of environmental fate, persistence and toxicity in aquatic environments

Tributyltin (TBT) is one of the most toxic anthropogenic compounds introduced into the aquatic environment. It has a relatively high affinity for particulate matter, providing a direct and potentially persistence route of entry into benthic sediments. To understand TBT behavior, computational programs are an exceptionally helpful tool for modeling and prediction. EPISuite program was used for evaluation of the prediction data including fate, persistence and toxicity from the partition coefficient values. Without experimental data, the model is useful for prediction but is essentially a default model. A site specific assessment is possible by measuring the partition coefficients and entering the experimental values obtained into the model. This paper describes the results of a study undertaken to determine the partition coefficients and the effect of various parameters on such partition coefficients. The octanol–water partition coefficient ( K ow) was determined by the OECD shake-flask method, with the logarithm values obtained ranging from 3.9 to 4.9 depending on salinity. The sediment–water partition coefficient ( K d) was determined by ASTM method of generating Freundlich adsorption isotherms, the obtained values ranged from 88 to 4909 L kg −1 depending on sediment properties, salinity, pH, and temperature. The experimental partition coefficient K ow and K oc (calculated from K d) were used as input data into the prediction program to provide accurate values for the natural samples in situ. The experimental prediction showed lower toxicity than the default model, but represent actual toxicity and accumulation at the natural site. Moreover, the environmental fate was significantly different when the experimental values and the default values were compared.

特集 「地球環境および地域環境と化学」 有機塩素系農薬の特定地域での環境中運命予測

特集 「地球環境および地域環境と化学」 有機塩素系農薬の特定地域での環境中運命予測