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Can Benchmarking Increase the Accuracy of Predicting Biodegradation Rates across Aquatic Ecosystems?

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Group-specific chemical benchmarking effectively reduces variability in biodegradation rates. Optimizing chemical groups is key, but predicting these groups a priori remains challenging due to limited understanding of biodegradability factors.

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Area of Science:

  • Environmental Chemistry
  • Ecotoxicology
  • Biodegradation Science

Background:

  • Temporal and spatial variability in biodegradation rate constants complicates persistence and exposure assessments.
  • Chemical benchmarking, using a reference chemical like an internal standard, can capture environmental-specific data to predict other chemical rates.
  • A dataset of 1656 biodegradation rate constants for 97 chemicals in European and Australian aquatic ecosystems, measured via a modified OECD 309 protocol, was compiled.

Purpose of the Study:

  • To assess the effectiveness of two chemical benchmarking approaches in reducing spatiotemporal variability of biodegradation rate constants.
  • To evaluate universal benchmarking (normalizing all chemicals to one benchmark) versus group-specific benchmarking (normalizing within chemical groups).

Main Methods:

  • Compiled biodegradation rate constants from a standardized modified OECD 309 test protocol.
  • Applied universal benchmarking, normalizing all 97 chemicals to a single benchmark.
  • Applied group-specific benchmarking, optimizing chemical groupings and normalizing within groups.
  • Assessed variability reduction using predicted chemical groupings based on Molecular ACCess System (MACCS) fingerprints or biotransformation rules.

Main Results:

  • Universal benchmarking failed to reduce the measured spatiotemporal variability in biodegradation rate constants.
  • Optimized group-specific benchmarking successfully reduced data variability.
  • Predicting chemical groups using MACCS fingerprints or biotransformation rules did not consistently reduce variability for most chemicals.

Conclusions:

  • Group-specific benchmarking shows potential for predicting spatiotemporal variability in biodegradation rate constants.
  • Effective implementation requires appropriate chemical grouping, which is currently limited by insufficient understanding of key biodegradability features.
  • Reliable a priori chemical grouping for benchmarking purposes needs further research into structure-biodegradability relationships.