Knowledge Gaps, Future Directions, and the Emergence of Nanoplastics as an Environmental Threat Pollutant

The terrestrial, aquatic, and human health sections to this book highlight an emerging concern regarding the largely uncertain toxicological and environmental impacts of nanomaterials. In particular, the human health impact of environmentally persistent nanoparticles and chemically complex ultrafine particulates represents a significant knowledge gap. A major challenge in the field of environmental nanotoxicology is the paucity of a historically rich data set on the effects of engineered nanoparticles, engineered nanomaterials, and ultrafine particulate matter. Nanoparticles and nanomaterials are now used extensively across industrial, scientific, biomedical, and technological platforms, a circumstance that has served to heighten critical concerns and highlight unanswered questions regarding their environmental fate, transport, and safety. This chapter will survey the knowledge gaps identified in the context of aquatic and terrestrial systems and suspected and demonstrated adverse human health effects. Moreover, the emergence of an expanding array of novel nanoparticles and composites (or nanoforms) in diverse industrial and consumer settings, as well as in diagnostic and therapeutic settings, presents a level of complexity that requires novel approaches that can provide meaningful data in risk assessment settings. There are clear data gaps not only in deepening our understanding of the chemical and physical characteristics of nanoparticles but also in strengthening our understanding of the mechanisms and modes of action of both ambient ultrafine particles and engineered nanomaterials. Significant data gaps are evident in regards to the emerging environmental health impacts of micro- and nanoplastic pollutants and their potential threat to public health. Finally, the advent of new approaches or alternative testing strategies to include in vitro models of biological and toxicological analysis; and in silico approaches like computational and mathematical modeling will not only strengthen existing or more traditional frameworks in the risk assessment enterprise but will also advance scientific knowledge and quality, and of course defensible regulation.