Direct and indirect photodegradation in aquatic systems mitigates photosensitized toxicity in screening-level substance risk assessments of selected petrochemical structures.

Photochemical processes are typically not incorporated in screening-level substance risk assessments due to the complexity of modeling sunlight co-exposures and resulting interactions on environmental fate and effects. However, for many substances, sunlight exerts a profound influence on environmental degradation rates and ecotoxicities. Recent modeling advances provide an improved technical basis for estimating the effect of sunlight in modulating both substance exposure and toxicity in the aquatic environment. Screening model simulations were performed for 25 petrochemical structures with varied uses and environmental fate properties. Model predictions were evaluated by comparing the ratios of predicted exposure concentrations with and without light to the corresponding ratios of toxicity thresholds under the same conditions. The relative ratios of exposure and hazard in light vs. dark were then used to evaluate how inclusion of light modulates substance risk analysis. Results indicated that inclusion of light reduced PECs by factors ranging from 1.1- to 63-fold as a result of photodegradation, while reducing PNECs by factors ranging from 1- to 49-fold due to photoenhanced toxicity caused by photosensitization. Consequently, the presence of light altered risk quotients by factors that ranged from 0.1- to 17-fold, since the predicted increase in substance hazard was mitigated by the reduction in exposure. For many structures, indirect photodegradation decreases environmental exposures independently of the direct photolysis pathway which is associated with enhanced phototoxicity. For most of the scenarios and chemicals in the present work, photosensitization appears to be mitigated by direct and indirect degradation from sunlight exposure.

Parsing the toxicity paradox: Composition and duration of exposure alter predicted oil spill effects by orders of magnitude.

Oil spilled into an aquatic environment produces oil droplet and dissolved component concentrations and compositions that are highly variable in space and time. Toxic effects on aquatic biota vary with sensitivity of the organism, concentration, composition, environmental conditions, and frequency and duration of exposure to the mixture of oil-derived dissolved compounds. For a range of spill (surface, subsea, blowout) and oil types under different environmental conditions, modeling of oil transport, fate, and organism behavior was used to quantify expected exposures over time for planktonic, motile, and stationary organisms. Different toxicity models were applied to these exposure time histories to characterize the influential roles of composition, concentration, and duration of exposure on aquatic toxicity. Misrepresenting these roles and exposures can affect results by orders of magnitude. Well-characterized laboratory studies for <24-hour exposures are needed to improve toxicity predictions of the typically short-term exposures that characterize spills.

In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.

Hydraulic fracturing (HF) is commonly used to enhance onshore recovery of oil and gas during production. This process involves the use of a variety of chemicals to support the physical extraction of oil and gas, maintain appropriate conditions downhole (e.g., redox conditions, pH), and limit microbial growth. The diversity of chemicals used in HF presents a significant challenge for risk assessment. The objective of the present study is to establish a transparent, reproducible procedure for estimating 5th percentile acute aquatic hazard concentrations (e.g., acute hazard concentration 5th percentiles [HC5s]) for these substances and validating against existing toxicity data. A simplified, grouped target site model (gTSM) was developed using a database (n = 1696) of diverse compounds with known mode of action (MoA) information. Statistical significance testing was employed to reduce model complexity by combining 11 discrete MoAs into three general hazard groups. The new model was trained and validated using an 80:20 allocation of the experimental database. The gTSM predicts toxicity using a combination of target site water partition coefficients and hazard group-based critical target site concentrations. Model performance was comparable to the original TSM using 40% fewer parameters. Model predictions were judged to be sufficiently reliable and the gTSM was further used to prioritize a subset of reported Permian Basin HF substances for risk evaluation. The gTSM was applied to predict hazard groups, species acute toxicity, and acute HC5s for 186 organic compounds (neutral and ionic). Toxicity predictions and acute HC5 estimates were validated against measured acute toxicity data compiled for HF substances. This case study supports the gTSM as an efficient, cost-effective computational tool for rapid aquatic hazard assessment of diverse organic chemicals. Environ Toxicol Chem 2024;43:1161-1172. © 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.