The toxicity of 19 emerging pollutants, including neonicotinoid insecticides, fragrance materials, pharmaceuticals, and other pesticides, was assessed using the larval development test with the mussel Mytilus galloprovincialis. The data evidenced that most of the tested compounds (neonicotinoid pesticides, oranger crystals, erythromycin, amoxicillin, and methiocarb) have low toxicity toward the early-life stages of M. galloprovincialis, with estimated EC50s > 10 mg L-1. The herbicide triallate was the more toxic compound, with an estimated EC50 of 505 μg L-1. The data provided evidence that early-life stages of mussels tend to be more resistant to emerging pollutants than other planktonic bioindicators, such as larval stages of copepods. Further studies are needed to improve the knowledge concerning the effects of these compounds on whole organisms and larval stages.

Effects of emerging pollutants on the larval development of the bivalve Mytilus galloprovincialis

Russo, Martina
;
Picone, Marco
;
Marchetto, Davide;Distefano, Gabriele Giuseppe;Ghirardini, Annamaria Volpi
2022-01-01

Abstract

The toxicity of 19 emerging pollutants, including neonicotinoid insecticides, fragrance materials, pharmaceuticals, and other pesticides, was assessed using the larval development test with the mussel Mytilus galloprovincialis. The data evidenced that most of the tested compounds (neonicotinoid pesticides, oranger crystals, erythromycin, amoxicillin, and methiocarb) have low toxicity toward the early-life stages of M. galloprovincialis, with estimated EC50s > 10 mg L-1. The herbicide triallate was the more toxic compound, with an estimated EC50 of 505 μg L-1. The data provided evidence that early-life stages of mussels tend to be more resistant to emerging pollutants than other planktonic bioindicators, such as larval stages of copepods. Further studies are needed to improve the knowledge concerning the effects of these compounds on whole organisms and larval stages.
2022
2022 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5008702
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