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Issue 9, 2017
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Some problems and practicalities in design and interpretation of samples of microplastic waste

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Abstract

Plastic as waste-material is increasingly littering the world's environments. Small particles of plastic – microplastics – are an increasing cause of concern because they can potentially cause a range of environmental problems for organisms and for the assemblages in which they live. Particles are a potential source of impacts in their own right, or as carriers of toxins that can then become absorbed into animals or plants. As a result, there has been increasing publication of programmes of sampling to quantify microplastics, to identify what types are where and to consider the extent to which they are causing impacts. Some of the sampling is to consider large-scale patterns. Some is to gather information about temporal trends. Regardless of the objectives, much of the sampling is not adequate to provide robust data to allow comparative assessments, examine trends or, in some cases, even to be sure about the quantities of plastic being encountered. The problems in such sampling programmes have been widely discussed in the ecological literature. Here, we attempt to identify some of the major problems and their causes and to promote thinking about the available solutions, in terms of improved sampling designs. This is done in the hope that more thought about the pitfalls will lead to more seeking of advice from statisticians and those who are expert in sampling, so that better information will become available in the future.

Graphical abstract: Some problems and practicalities in design and interpretation of samples of microplastic waste

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Publication details

The article was received on 22 Sep 2016, accepted on 26 Nov 2016 and first published on 28 Nov 2016


Article type: Critical Review
DOI: 10.1039/C6AY02641A
Citation: Anal. Methods, 2017,9, 1332-1345

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    Some problems and practicalities in design and interpretation of samples of microplastic waste

    A. J. Underwood, M. G. Chapman and M. A. Browne, Anal. Methods, 2017, 9, 1332
    DOI: 10.1039/C6AY02641A

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