Influence of natural organic matter on the aquatic ecotoxicity of engineered nanoparticles: Recommendations for environmental risk assessment

Artikel i vetenskaplig tidskrift, 2020

In this study, we investigate whether the influence of natural organic matter (NOM) on the aquatic ecotoxicity of

engineered nanoparticles (ENPs) can be described quantitatively for the purpose of risk assessments based on

existing ecotoxicity studies. A review of the literature studying the aquatic ecotoxicity of ENPs in the presence of

NOM identified 66 studies in total, covering the metal and metal oxide ENPs most commonly used in consumer

products. It was found that 80% of the studies show a reduction in ENP ecotoxicity in the presence of NOM.

Analyses of ecotoxicity data based on 50% effect/inhibition/lethal concentrations (collectively referred to as

XC50) were conducted. Correlations of XC50 values with the concentrations of NOM were investigated through

Spearman's rank correlation coefficient as well as linear, power law, polynomial, exponential and logarithmic

correlations. Furthermore, multiple linear regression (MLR) analyses, including also the pH in the reviewed

ecotoxicity test systems (mainly in the range pH 7.0–8.5), were conducted. While none of these statistical approaches

provided strong empirical correlations between XC50 values, NOM concentration and pH, an empirical

rule of thumb was discovered for the ratio between XC50 values with and without NOM over an environmentally

realistic concentration range for NOM (0.1–10 mg/L): XC50 values obtained in experiments with NOM present

tended to be a factor of 1–10 higher than those without NOM. Until more accurate correlations are provided, a

pragmatic approach for environmental risk assessments of ENPs might therefore be to use observed XC50 values

from experiments without NOM present as reasonably conservative proxies for XC50 values with NOM present.

Further studies are needed to confirm or falsify this rule of thumb for different ENPs, environmental conditions

and metrics.