Combining exposure and effect modeling into an integrated probabilistic environmental risk assessment for...

Area of Science:

• Environmental toxicology
• Nanotechnology risk assessment
• Environmental chemistry

Background:

• Environmental risk assessment (ERA) for engineered nanoparticles (ENPs) is crucial but hindered by data gaps regarding ENP fate and toxicity.
• Existing ERA methods struggle with uncertainty, limiting reliable risk characterization for ENPs.
• Probabilistic methods offer a robust approach to manage and quantify uncertainty in risk assessments.

Purpose of the Study:

• To develop and demonstrate a novel probabilistic method for modeling both variability and uncertainty in ENP environmental risk assessment.
• To enable separate modeling of variability and uncertainty to identify sources of variation in risk assessment outcomes.
• To enhance the transparency and direction of future environmental and toxicological research for ENPs.

Main Methods:

• Developed a probabilistic method based on the concentration ratio and the exposure-to-critical-effect concentration ratio, treating both as random variables.
• Modeled variability and uncertainty separately within the risk assessment framework.
• Applied the method to a simplified aquatic risk assessment scenario involving nano-titanium dioxide (TiO2).

Main Results:

• The developed method successfully models variability and uncertainty independently in ENP risk assessment.
• The approach allows users to distinguish the contributions of variability versus uncertainty to the overall risk assessment outcome.
• Demonstrated application with nano-titanium dioxide provides a transparent risk assessment example.

Conclusions:

• The new method enhances transparency in environmental risk assessment for engineered nanoparticles.
• Separating variability and uncertainty modeling provides clearer insights into risk assessment components.
• This approach can effectively direct future research efforts toward critical data gaps in ENP environmental toxicology and fate.