Fate and Characterization Factors of Nanoparticles in Seventeen Subcontinental Freshwaters: A Case Study on Copper Nanoparticles

Abstract

The lack of characterization factors (CFs) for engineered nanoparticles (ENPs) hampers the application of life cycle assessment (LCA) methodology in evaluating the potential environmental impacts of nanomaterials. Here, the framework of the USEtox model has been selected to solve this problem. On the basis of colloid science, a fate model for ENPs has been developed to calculate the freshwater fate factor (FF) of ENPs. We also give the recommendations for using the hydrological data from the USEtox model. The functionality of our fate model is proved by comparing our computed results with the reported scenarios in North America, Switzerland, and Europe. As a case study, a literature survey of the nano-Cu toxicology values has been performed to calculate the effect factor (EF). Seventeen freshwater CFs of nano-Cu are proposed as recommended values for subcontinental regions. Depending on the regions and the properties of the ENPs, the region most likely to be affected by nano-Cu is Africa (CF of 11.11 × 10(3) CTUe, comparative toxic units) and the least likely is north Australia (CF of 3.87 × 10(3) CTUe). Furthermore, from the sensitivity analysis of the fate model, 13 input parameters (such as depth of freshwater, radius of ENPs) show vastly different degrees of influence on the outcomes. The characterization of suspended particles in freshwater and the dissolution rate of ENPs are two significant factors.

Influence of Dissolution on Fate of Nanoparticles in Freshwater

“…[12] By doing this, it was possible to determine which input parameter should receive more attention in the future. One of the methods used in the study was labeled as "Single Parameter SA".…”

“…One of the methods used in the study was labeled as "Single Parameter SA". [12] It was performed by varying each selected parameter within its range while holding the others constant. There were 13 parameters involved in total.…”

“…The first five parameters with high relative importance follow the order shown in (1), while the relative importance of the other studied parameters was at least 3 orders of magnitude lower compared to the first fives. [12] k diss > r LSP > ρ SNP > α 2 ≈ Depth water (1) where k diss is the dissolution rate of ENPs in freshwater; r LSP is the radius of larger suspended particles (LSP, > 450 nm) in freshwater; ρ SNP is the density of the suspended particles in freshwater; α 2 is the attachment efficiency between ENPs and LSP; Depth water is the depth of freshwater. [12], [18] C…”

“…Ref. [8], [12] a recently published research has demonstrated that there are many factors affecting the output of fate model, such as dissolution rate of ENPs, diameter of suspended particles in freshwater, depth of freshwater. Among them, dissolution rate is one of the most significant factor for many subcontinental regions [12].…”

“…Ref. [11], [12] therefore, in practice, as an acceptable simplification, the dissolution rate constant of ENPs in freshwater is assumed to be 0-10 -5 s -1 for different ENPs. [14] In this study, four important input parameters of a fate model were selected.…”