Identification and Quantification of Nanoplastics in Surface Water and Groundwater by Pyrolysis Gas Chromatography-Mass Spectrometry.
Yanghui XuQin OuMeng JiaoGang LiuJan Peter van der HoekPublished in: Environmental science & technology (2022)
Nanoplastics (NPs) are currently considered an environmental pollutant of concern, but the actual extent of NP pollution in environmental water bodies remains unclear and there is not enough quantitative data to conduct proper risk assessments. In this study, a pretreatment method combining ultrafiltration (UF, 100 kDa) with hydrogen peroxide digestion and subsequent detection with pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) was developed and used to identify and quantify six selected NPs in surface water (SW) and groundwater (GW), including poly(vinylchloride) (PVC), poly(methyl methacrylate) (PMMA), polypropylene (PP), polystyrene (PS), polyethylene (PE), and poly(ethylene terephthalate) (PET). The results show that the proposed method could detect NPs in environmental water samples. Nearly all selected NPs could be detected in the surface water at all locations, while PVC, PMMA, PS, and PET NPs were frequently below the detection limit in the groundwater. PP (32.9-69.9%) and PE (21.3-44.3%) NPs were the dominant components in both surface water and groundwater, although there were significant differences in the pollution levels attributed to the filtration efficiency of riverbank, with total mass concentrations of 0.283-0.793 μg/L (SW) and 0.021-0.203 μg/L (GW). Overall, this study quantified the NPs in complex aquatic environments for the first time, filling in gaps in our knowledge about NP pollution levels and providing a useful methodology and important reference data for future research.
Keyphrases
- human health
- risk assessment
- heavy metals
- gas chromatography mass spectrometry
- health risk assessment
- hydrogen peroxide
- oxide nanoparticles
- water quality
- climate change
- drinking water
- health risk
- sewage sludge
- healthcare
- nitric oxide
- particulate matter
- big data
- electronic health record
- machine learning
- pet ct
- heat shock protein
- high resolution
- gas chromatography
- current status
- air pollution
- life cycle
- municipal solid waste