Determination and validation of an aquatic Maximum Acceptable Concentration-Environmental Quality Standard (MAC-EQS) value for the agricultural fungicide azoxystrobin

Abstract

The main goal of the present study was to determine and validate an aquatic Maximum Acceptable Concentration-Environmental Quality Standard (MAC-EQS) value for the agricultural fungicide azoxystrobin (AZX). Assessment factors were applied to short-term toxicity data using the lowest EC50 and after the Species Sensitivity Distribution (SSD) method. Both ways of EQS generation were applied to a freshwater toxicity dataset for AZX based on available data, and to marine toxicity datasets for AZX and Ortiva® (a commercial formulation of AZX) obtained by the present study. A high interspecific variability in AZX sensitivity was observed in all datasets, being the copepoda Eudiaptomus graciloides (LC50,48h = 38 μg L−1) and the gastropod Gibbula umbilicalis (LC50,96h = 13 μg L−1) the most sensitive freshwater and marine species, respectively. MAC-EQS values derived using the lowest EC50 (≤0.38 μg L−1) were more protective than those derived using the SSD method (≤3.2 μg L−1). After comparing the MAC-EQS values estimated in the present study to the smallest AA-EQS available, which protect against the occurrence of prolonged exposure of AZX, the MAC-EQS values derived using the lowest EC50 were considered overprotective and a MAC-EQS of 1.8 μg L−1 was validated and recommended for AZX for the water column. This value was derived from marine toxicity data, which highlights the importance of testing marine organisms. Moreover, Ortiva affects the most sensitive marine species to a greater extent than AZX, and marine species are more sensitive than freshwater species to AZX. A risk characterization ratio higher than one allowed to conclude that AZX might pose a high risk to the aquatic environment. Also, in a wider conclusion, before new pesticides are approved, we suggest to improve the Tier 1 prospective Ecological Risk Assessment by increasing the number of short-term data, and apply the SSD approach, in order to ensure the safety of aquatic organisms.