The Nature of Plastics

In recent decades, pollution of the environment with plastic debris has received increasing attention in society due to the visibility of plastic debris, because of ethical and aesthetical considerations and because of concerns with respect to both ecological harm and more recently to human health (GESAMP, 2015). This chapter aims to provide an overview of the existing evidence and the properties of plastic and plastic debris, its occurrence and concentration in the environment, exposure, its hazards and effects on organisms, communities and food webs, and finally the probability of risks for the environment and human health. We also review models that have been used for scenario studies with respect to the problem of plastics debris. Risk in the context of chemical assessment can be defined from the perspective of natural sciences as “the probability of an adverse effect on man [sic] or the environment occurring as a result of a given exposure to a chemical or mixture” (Vermeire & van Leeuwen, 2007). Risk assessments often use simple risk characterisation ratios (RCRs), whereby a risk is characterised as the ratio of actual or predicted exposures to the maximum acceptable concentration of a given chemical or particle in a given environment. An RCR exceeding 1 is usually interpreted by policymakers as an unacceptable situation that warrants further study and/or risk mitigation measures. For the risk assessment of microplastics, risk metrics have also been suggested that consider the likelihood of risk exceedance, as well as impact severity (Mahon et al.,2017; United Nations, 2016). A risk is the chance (high or low) that any hazard will actually cause harm. Risk exceedance simply means the likelihood of being exposed to the hazard at some given level or higher.

Expected and actual exposure levels differ vastly between environmental compartments and sites. Furthermore, maximum acceptable concentrations (e.g. Predicted No Effect Concentrations (PNECs), Derived No Effect Levels (DNELs), Acceptable Daily Intakes (ADIs) and similar estimates) have to be determined in relation to the most sensitive (eco)toxicologically relevant endpoint (i.e. reproduction, growth or mortality) and the species/ecological communities present in a given compartment, which can be detailed for each and every microplastic particle type of interest. This renders any chemical risk assessment highly complex and data-demanding. This issue is even more challenging for microplastics than for ’ordinary’ chemicals, because their overall risk might be driven by a combination of at least four interlinked processes: physical effects of the particles; food limitation caused by particle exposure; chemical toxicity from associated chemicals and the unintentional distribution of associated (micro) biota; and the interactions between these factors (Engler, 2012; Reisser et al., 2014; Syberg et al., 2015). Real-world exposure is not to one well-defined particle type, but to a complex mixture of particles of different polymers, sizes, shapes, surface characteristics and chemical composition (Lambert, Scherer, & Wagner, 2017). In principle, this demands an individual risk assessment for each class of NMP, for instance for each individual polymer and size class (Koelmans et al., 2017). In practice, this is not feasible now because exposure and hazard data would be needed for each particle class. Whether and how this complexity can be simplified into a single RCR (or at least to a small set of distinct RCRs) is currently unclear. Koelmans et al. (2017a) provided a first template, employing adverse outcome pathways and tiered hazard assessment strategies to systematize the issues at hand, but practical experiences are still missing.

This chapter is structured following the main components of this classical risk assessment framework. After providing basic definitions and an introduction to polymer science in the context of plastic debris, we discuss exposure, hazard assessment, and finally risk characterization. As requested by the GCSA, for each section, the information is separated into what is known, what is unknown, and a category in between representing what is not well known, to roughly indicate the level of certainty associated with current knowledge. The bars along the side of the page indicate these categories: dark blue for known, blue for partially known and grey for unknown. We emphasise that this information represents a continuous scale and that allocation into these three categories is subjective to some extent, despite the fact that this has been performed by subject experts following a thorough literature review. We report the conclusions of the working group based on the current evidence as a whole and their interpretations of the robustness of the evidence (even where research is at an early stage), so that diverging and consensus opinions are reported.