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Assessing the use of sand, peat soil, and pine bark for the attenuation of polar pesticides from agricultural run-off: a bench-scale column experiment

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Abstract

Biofilters have been shown to be efficient for removing pollutants from different water effluents, but little information is available about their capacity to remove highly polar pesticides from agricultural run-off waters. In this study, we assess the capacity of three different biofilter-supporting materials (sand, peat soil, and pine bark) to remove five phenoxyacid herbicides (mecoprop, dicamba, MCPA, dichlorprop and 2,4-D) and five non-ionic pesticides (atrazine, simazine, fenitrotion, diazinon, and alachlor) from real agricultural run-off waters. The experimental design included three columns 120 cm in length and 15 cm in diameter, each filled with 100 cm of one of the selected supporting materials. After 30 days of acclimation, the columns were fed with agricultural run-off water spiked at 10 μg L−1 with each of the studied pesticides for 20 days at a hydraulic loading rate (HLR) of 0.32 m day−1. The results show that the sand filter was the best supporting material for removing phenoxyacid herbicides (77% on average), whereas peat soil and pine bark were best for removing non-ionic pesticides (72% on average). The attenuation of mecoprop and dichlorprop correlated negatively with the enantiomeric fraction. Therefore, this study shows that the use of waste-to-product materials in biofilter systems is a good solution for removing pollutants from agricultural run-off waters.

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Acknowledgments

Dr. V. M. would like to acknowledge a Ramon y Cajal contract from the MEC (RYC-2013-12522).

Funding

The authors gratefully acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness (MEC) through project CTM2012-33547.

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Correspondence to Víctor Matamoros.

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Responsible editor: Philippe Garrigues

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Matamoros, V., Franco, J. Assessing the use of sand, peat soil, and pine bark for the attenuation of polar pesticides from agricultural run-off: a bench-scale column experiment. Environ Sci Pollut Res 25, 20640–20647 (2018). https://doi.org/10.1007/s11356-018-2213-x

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