For understanding the environmental behavior and toxicity of Ag nanoparticles (Ag-NPs), a quantitative method for characterizing the AgNPs in soils and sediments is urgently needed. In this study, we validated a previously developed extraction method by optimizing the extraction of silver nanoparticles from soil and sediment samples to which engineered AgNPs had been added. The samples were analyzed by single particle inductively coupled plasma mass spectrometry (SP-ICP-MS). Initially, different extraction conditions were evaluated to validate the optimal extraction procedure. Then the optimal extraction procedure was applied to environmental soil and sediment samples spiked with AgNPs. The extraction data for Ag-NPs with sizes below 30 nm was not shown due to the particle size detection limit of the SP-ICP-MS method (∼20 nm). The number concentrations of Ag particles extracted from different environmental soils and sediments matrices were in the range of (12 ± 1-23 ± 1) × 107 particles/g soil. Similarly, 53.4-100.0% of the particulate Ag mass was recovered. For the relatively low Ag mass recovery of Guiyu agricultural soil, the Ag mass recovery shows great improvement (from 53.4 to 105.8%) by the soil dilution using SiO2. The optimal method was validated to be feasible for extracting Ag-NPs from environmental soils and sediments, except for the soil with high soil organic matter (SOM) content. The SiO2 dilution of soil provides a promising way to promote the extraction of Ag-NPs in soil (or sediment) with high SOM content, which could further promote the study on the environmental behavior and toxicity of Ag-NPs in soil and sediment environment.
Keyphrases
- heavy metals
- organic matter
- silver nanoparticles
- mass spectrometry
- quantum dots
- human health
- risk assessment
- highly efficient
- plant growth
- polycyclic aromatic hydrocarbons
- liquid chromatography
- visible light
- gas chromatography
- oxidative stress
- multiple sclerosis
- high performance liquid chromatography
- machine learning
- big data
- liquid chromatography tandem mass spectrometry
- climate change
- electronic health record
- deep learning
- solid phase extraction
- label free
- magnetic nanoparticles