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Semi-automated analysis of microplastics in complex wastewater samples

Research output: Contribution to journalJournal articlepeer-review

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  • A.A. Horton
  • R.K. Cross
  • D.S. Read
  • M.D. Jürgens
  • H.L. Ball
  • C. Svendsen
  • J. Vollertsen
  • A.C. Johnson
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Article number115841
<mark>Journal publication date</mark>1/01/2021
<mark>Journal</mark>Environmental Pollution
Volume268
Number of pages10
Publication StatusPublished
Early online date13/10/20
<mark>Original language</mark>English

Abstract

In order to assess risks to the natural environment from microplastics, it is necessary to have reliable information on all potential inputs and discharges. This relies on stringent quality control measures to ensure accurate reporting. Here we focus on wastewater treatment works (WwTWs) and the complex sample matrices these provide. Composite samples of both influent and effluent were collected over a 24 h period on two separate occasions from eight different WwTWs across the UK. Sludge samples were taken on five occasions from five WwTWs. The WwTW treatments included activated sludge, trickling filter and biological aerated flooded filter with or without tertiary treatment. Using micro-FTIR analysis, microplastics ≥25 μm were identified and quantified. Procedural blanks were used to derive limits of detection (LOD) and limits of quantification (LOQ). Where values were above the LOQ, microplastics in the influent ranged from 955 to 17,214 microplastic particles/L and in the effluent from 2 to 54 microplastic particles/L, giving an average removal rate of 99.8%. Microplastics could be quantified in sludge at concentrations of 301–10,380 microplastics/g dry weight, this analytical method therefore revealing higher concentrations than reported in previous studies. The most common polymers present overall were polyethylene (PE), polypropylene (PP) and polyethylene terephthalate (PET). We also report on critical considerations for blank corrections and quality control measures to ensure reliable microplastic analysis across different sample types.