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• Accurate data enhances chemical risk assessment and informs policy decisions. • The PRM improves pesticide risk estimates, reducing uncertainty in assessments. • The PRM was applied to 706 sites and highlights widespread ecological risks. • 50.8% of sites failed AA-EQS for mixtures and Italy had the most exceedances. • Insecticides drove 61.4% of toxicity and 14 PAIs accounted for 99% of the impact. Significant advancements have been made in the development of methods to assess mixture risk, with the hazard unit and concentration addition methods being commonly used for tier one screening risk assessments. However, a reduction in risk estimate uncertainty is required for higher tier assessments and targeted management action, particularly in the context of policy frameworks, such as the European Green Deal which aims to reduce the use and risk of pesticides that may pollute air, water and soil. This study proposes the Pesticide Risk Metric (PRM), an approach grounded in existing ecotoxicological methods for this purpose. By combining the species sensitivity distribution approach with the independent action model of joint toxicity, the PRM reduces uncertainty and provides more reliable risk estimates for individual toxicants and mixtures. The PRM method was applied to aqueous pesticide monitoring data from eight countries to demonstrate the utility of the method. Of the 706 sites, 61 (8.6%) did not meet the annual average environmental quality standard (AA-EQS) for individual pesticide active ingredients, with Italy showing the highest number of exceedances. When assessed as a mixture, 359 sites (51%) failed to meet the AA-EQS, with Italy and the Netherlands showing the highest annual mixture toxicity. The primary contributors to mixture toxicity were insecticides (61%), followed by other herbicides (32%) and photosystem II inhibiting herbicides (6.1%), with significant variation at the country and site levels. Fourteen pesticides contributed 99% of the annual average mixture toxicity at the country level. The adaptability and reliable risk estimates of the PRM make it a valuable tool for second-tier risk assessment, further enhancing targeted policy and management decisions.
Neelamraju et al. (Thu,) studied this question.