Proportional contributions to organic chemical mixture effects in groundwater and surface water. (15th July 2022) - Spurgeon, David; Wilkinson, Helen; Civil, Wayne; Hutt, Lorraine; Armenise, Elena; Kieboom, Natalie; Sims, Kerry; Besien, Tim
Highlights: GC–MS and LC-MS were used to quantify organic chemical mixtures. Chronic SSD HC50s were used as the hazard metric to predict mixture effect. Increased hazard was found from the presence of a cocktail of substances. The most toxic chemical contributed ≥ 20% of mixture effect in >99% of cases. Mixture complexity was only weakly associated with increased mixture effect. Abstract: Semi-quantitative GC-MS and LC-MS measurements of organic chemicals in groundwater and surface waters were used to assess the overall magnitude and contribution of the most important substances to calculated mixture hazard. Here we use GC-MS and LC-MS measurements taken from two separate national monitoring programs for groundwater and surface water in England, in combination with chronic species sensitivity distribution (SSD) HC50 values published by Posthuma et al . (2019, Environ. Toxicol. Chem, 38, 905–917) to calculate individual substance hazard quotients and mixture effects using a concentration addition approach. The mixture analysis indicated that, as anticipated, there was an increased hazard from the presence of a cocktail of substances at sites compared to the hazard for any single chemical. The magnitude of the difference between the hazard attributed to the most important chemical and the overall mixture effect, however, was not large. Thus, the most toxic chemical contributed ≥ 20% of the calculated mixture effect in >99% of all measured groundwater and surface water samples. On the basis of this analysis, a 5 fold assessment factor placed on the risk identified for any single chemical would offer a high degree of in cases where implementation of a full mixture analysis was not possible. This finding is consistent with previous work that has assessed chemical mixture effects within field monitoring programs and as such provides essential underpinning for future policy and management decisions on how to effectively and proportionately manage mixture risks. Graphical abstract: Image, graphical abstract