4.5 Article

Comparison of different monitoring methods for the measurement of metaldehyde in surface waters

Journal

ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 191, Issue 2, Pages -

Publisher

SPRINGER
DOI: 10.1007/s10661-019-7221-x

Keywords

Metaldehyde; Water monitoring; Drinking water; Spot sampling; Passive sampling; On-line gas chromatography; mass spectrometry

Funding

  1. Natural Environment Research Council (NERC) [NE/L009145/1]

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Metaldehyde is recognised as an emerging contaminant. It is a powerful molluscicide and is the active compound in many types of slug pellets used for the protection of crops. The application of pellets to land generally takes place between August and December when slugs thrive. Due to its high use and physico-chemical properties, metaldehyde can be present in the aquatic environment at concentrations above the EU Drinking Water Directive limit of 100ngL(-1) for a single pesticide. Such high concentrations are problematic when these waters are used in the production of drinking water. Being able to effectively monitor this pollutant of concern is important. We compared four different monitoring techniques (spot and automated bottle sampling, on-line gas chromatography/mass spectrometry (GC/MS) and passive sampling) to estimate the concentration of metaldehyde. Trials were undertaken in the Mimmshall Brook catchment (Hertfordshire, UK) and in a feed in a drinking water treatment plant for differing periods between 17th October and 31st December 2017. This period coincided with the agricultural application of metaldehyde. Overall, there was a good agreement between the concentrations measured by the four techniques, each providing complementary information. The highest resolution data was obtained using the on-line GC/MS. During the study, there was a large exceedance (500ngL(-1)) of metaldehyde that entered the treatment plant; but this was not related to rainfall in the area. Each monitoring method had its own advantages and disadvantages for monitoring investigations, particularly in terms of cost and turn-a-round time of data.

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