Cefic-lri Programme | European Chemical Industry Council

ECO31: Identifying strategies that will provide greater confidence in estimating the degradation rates of organic chemicals in water, soil and sediment

Principal Investigator

Prof. Damian Helbling
School of Civil and Environmental Engineering
220 Hollister Hall
Ithaca, New York 14853
USA
damian.helbling@cornell.edu
Tel: +1 607 255 5146

Collaborators

PD Dr. Kathrin Fenner, Senior Scientist, Eawag, kathrin.fenner@eawag.ch

Description

In the first phase of this project (ECO31.1), the team aimed to identify strategies that will provide greater confidence in estimating the degradation rate constants of organic chemicals in the environment. To meet this objective, the team performed an extensive review of the existing experimental and model-based approaches to estimate the degradation rate constants of chemicals and critically evaluated the key factors that drive degradation rates of specific reactions in different environmental compartments. Through this review and evaluation, the team identified limitations of current regulatory approaches and offer recommendations for considering variable degradation in environmental fate modelling and chemical regulations.

Major conclusions and recommendations resulting from this work include:

  • OECD tests specify environmental factors that should be controlled and recorded during experimentation, but these environmental factors are rarely reported and likely do not adequately cover the space of environmental factors that are important for degradation;
  • The biggest need for QSAR modelling is the generation of well-documented experimental degradation data for both model training and validation;
  • Well-curated metadata related to the environmental conditions under which rate constants are estimated are essential for improving our understanding of variable degradation, and the team strongly recommends improved reporting of metadata. These data should be stored in publically accessible electronic databases for efficient access and analysis;
  • A multivariable analysis of aerobic biodegradation half-lives of pesticides in soil revealed that chemical application history and biomass were important factors for all of the chemical substances for which data was available. Quantitative interdependencies were discovered between: (1) the organic carbon content of soil and the relative solubility of a chemical; and (2) soil sampling depth and the organic carbon-water partitioning coefficient of a chemical.
  • The results of the team’s multivariable analysis can be used to design an experimental framework for considering variable degradation rates in general chemical regulation. For example, experimental guidelines for evaluating aerobic biodegradation in soil should explicitly consider chemical application history on the soils selected for experimentation. Soil texture, organic carbon content, and sampling depth were also found to be important factors for aerobic biodegradation in soil and guidelines on the ranges of those parameters that should be represented in experiments should be refined. Regulatory guidelines should consider the physicochemical properties of the test substance as a trigger for studying certain environmental parameters in more detail.

In a second phase of this project (ECO31.2), the team now aims to identify key factors contributing to the range of degradation rates reported in water, water-sediment, and activated sludge systems, to improve our understanding of chemical persistence in the environment and to create a scientific basis for the comparison of laboratory and field datasets. Two main hypotheses will be investigated:

  • The multivariable framework developed in Phase I of ECO-31 can be applied to uncover key environmental factors that determine the range of degradation rate constants in other environmental compartments
  • Threshold benchmarking can improve our understanding of persistence estimates across variable environmental systems and between laboratory and field studies

To investigate these hypotheses, the following three project objectives were defined:

  1. Collect degradation rate data and associated metadata. There is a need to develop databases containing degradation rate constants, half-lives, and associated metadata for various environmental compartments. Data will be collected for a number of chemicals for each reaction type and for each environmental compartment. The richest datasets (number of chemicals, number of observations, and amount of metadata) are expected to be for activated sludge systems.
  2. Identify key factors contributing to the range of degradation rates. These analyses will provide evidence of relationships between key environmental variables and the magnitude of degradation rate constants in other environmental compartments. Key factors that influence biodegradation of chemicals in water, water sediment, and activated sludge should be identified. The contribution of each factor will be ranked based on how much it contributes to the variability on observed degradation rate constants.
  3. Compare persistence across environments and between laboratory and field. Threshold benchmarking has the potential to improve the scientific quality of persistence assessments. The datasets generated in this work will provide the foundation to identify benchmarking chemicals and explore the potential for threshold benchmarking. The richness of the activated sludge datasets will enable proper evaluation of the threshold benchmarking principle. The results will be generalizable to biodegradation processes occurring in other environmental compartments.

Workflow for clustering chemicals based on predicted biotransformations

The hypothesis whereby the environmental fate of chemicals that undergo similar types of environmental transformation processes might be influenced by similar environmental conditions was tested. The web-based tool known as the Eawag pathway prediction system (Eawag-PPS) was used to predict the initial biotransformations of a group of relevant chemicals.

The Eawag-PPS predicts microbial biotransformations for organic chemicals and is a freely available and user-friendly tool for education and research.

The predictions from the Eawag-PPS were then combined with a statistical technique known as hierarchical clustering. This technique allows to group together chemicals that undergo similar types of microbial biotransformations.

Learn more here.

Related Publications

NEW: Wang Y., Nell M., Fenner K., Helbling D.E. EXECUTIVE SUMMARY – Final report for Cefic-LRI ECO31.2: A multivariate approach to identify key parameters influencing the degradation rates of organic chemicals in water, water‐sediment, and activated sludge systems, August 2020.

Wang Y, Lai A, Latino D, Fenner K, Helbling DE. Evaluating the environmental parameters that determine aerobic biodegradation half-lives of pesticides in soil with a multivariable approach. Chemosphere. 2018 Oct;209:430-438.

Wang Y, Fenner K, Helbling DE. Clustering micropollutants based on initial biotransformations for improved prediction of micropollutant removal during conventional activated sludge treatment. Environmental Science: Water Research & Technology. 2019

Presentations:

Wang, Y., and D.E. Helbling. “Identifying strategies that will provide greater confidence in estimating persistence of organic chemicals in the environment,” 2019 AEESP Research and Education Conference, May 2019, Phoenix, AZ.

Timeline:

  • ECO31.1: June 2016 > May 2017
  • ECO31.2: May 2018 > April 2020

LRI Funding: 

  • ECO31.1: $ 109 000
  • ECO31.2: $ 239 083
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