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A probabilistic risk framework for microplastics integrating uncertainty across toxicological and environmental variability: Development and application to marine and freshwater ecosystems

Journal of Hazardous Materials 2026 Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Lidwina Bertrand, Anna Kukkola, Anna Kukkola, Anna Kukkola, Ezra Miller, Ezra Miller, Stephanie B. Kennedy Stephanie B. Kennedy, Andrew Barrick, Scott Coffin, Andrew Barrick, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Anna Kukkola, Scott Coffin, Anna Kukkola, Anna Kukkola, Andrew Barrick, Anna Kukkola, Anna Kukkola, Anna Kukkola, Scott Coffin, Lidwina Bertrand, Scott Coffin, Scott Coffin, Anna Kukkola, Anna Kukkola, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Lidwina Bertrand, Lidwina Bertrand, Lidwina Bertrand, Andrew Barrick, Andrew Barrick, Anna Kukkola, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Anna Kukkola, Kazi Towsif Ahmed, Scott Coffin, Ezra Miller, Ezra Miller, Anna Kukkola, Kazi Towsif Ahmed, Luan de Souza Leite, Ezra Miller, Bethanie Carney Almroth, Anna Kukkola, Anna Kukkola, Anna Kukkola, Anna Kukkola, Scott Coffin, Anna Kukkola, Scott Coffin, Scott Coffin, Scott Coffin, Scott Coffin, Luan de Souza Leite, Luan de Souza Leite, Luan de Souza Leite, Scott Coffin, Luan de Souza Leite, Luan de Souza Leite, Win Cowger, Scott Coffin, Scott Coffin, Lidwina Bertrand, Win Cowger, Win Cowger, Anna Kukkola, Anna Kukkola, Anna Kukkola, Ezra Miller, Win Cowger, Win Cowger, Win Cowger, SinaMariella Siña, Anna Kukkola, SinaMariella Siña, Scott Coffin, Lidwina Bertrand, Anna Kukkola, Anna Kukkola, Anna Kukkola, Anna Kukkola, Andrew Barrick, Anna Kukkola, Scott Coffin, Andrew Barrick, Anna Kukkola, Ezra Miller, Bethanie Carney Almroth, Anna Kukkola, Bethanie Carney Almroth, Ezra Miller, Anna Kukkola, Lidwina Bertrand, Ezra Miller, Ezra Miller, Bethanie Carney Almroth, Bethanie Carney Almroth, Andrew Barrick, Ezra Miller, Bethanie Carney Almroth, Ezra Miller, Ezra Miller, Anna Kukkola, Andrew Yeh, Andrew Yeh, Stephanie B. Kennedy, Stephanie B. Kennedy M. Mair, M. Mair, Anna Kukkola, Lidwina Bertrand, Andrew Barrick, Lidwina Bertrand, Anna Kukkola, Stephanie B. Kennedy, Stephanie B. Kennedy

Summary

Researchers developed a new probabilistic risk assessment framework for microplastics that accounts for uncertainty in how laboratory toxicity data translates to real environmental conditions. Using Monte Carlo simulation and an enhanced species sensitivity distribution model, they found that uncertainty from particle-trait alignments can drive threshold variability by up to two orders of magnitude. The framework highlights that current risk assessments may underestimate hazards and identifies key research needs for improving microplastic environmental safety thresholds.

Study Type Environmental

Quantitative risk assessment for microplastics (MPs) is complicated by misalignments between environmentally relevant particles and those used in toxicity studies. Previous approaches addressed this using ecologically relevant metrics (ERMs) and species sensitivity distributions (SSDs), but did not propagate uncertainty from particle-trait alignments or intraspecies variability. Here, we present a novel probabilistic framework that propagates uncertainty through ERM alignments using Monte Carlo (MC) simulation, paired with a modified probabilistic SSD model (PSSD++). Using high-quality data from the updated Toxicity of Microplastics Explorer (ToMEx 2.0), we compared hazard thresholds derived by three approaches: traditional SSD, MC + SSD, and PSSD++. PSSD++ consistently produced the most health-protective median thresholds and lowest 5th-percentile values, which generally exhibited the widest relative confidence intervals. MC + SSDs produced the narrowest uncertainty ranges. Uncertainty was greater for food dilution than for tissue translocation, and greater for freshwater environments than marine. Sensitivity analysis identified ERM-alignment parameters as the dominant drivers of threshold variability, contributing up to two orders of magnitude difference. This framework emphasizes the importance of propagating alignments uncertainty in MP risk assessments and highlights key research needs, including improved models for tissue translocation and more representative environmental particle characterizations.

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