PLoS ONE, 2015, Vol.10(5)
During their aquatic life cycle, nanoparticles are subject to environmentally driven surface modifications (e.g. agglomeration or coating) associated with aging. Although the ecotoxicological potential of nanoparticles might be affected by these processes, only limited information about the potential impact of aging is available. In this context, the present study investigated acute (96 h) and chronic (21 d) implications of systematically aged titanium dioxide nanoparticles (nTiO 2 ; ~90 nm) on the standard test species Daphnia magna by following the respective test guidelines. The nTiO 2 were aged for 0, 1, 3 and 6 d in media with varying ionic strengths (Milli-Q water: approx. 0.00 mmol/L and ASTM: 9.25 mmol/L) in the presence or absence of natural organic matter (NOM). Irrespective of the other parameters, aging in Milli-Q did not change the acute toxicity relative to an unaged control. In contrast, 6 d aged nTiO 2 in ASTM without NOM caused a fourfold decreased acute toxicity. Relative to the 0 d aged particles, nTiO 2 aged for 1 and 3 d in ASTM with NOM, which is the most environmentally-relevant setup used here, significantly increased acute toxicity (by approximately 30%), while a toxicity reduction (60%) was observed for 6 d aged nTiO 2 . Comparable patterns were observed during the chronic experiments. A likely explanation for this phenomenon is that the aging of nTiO 2 increases the particle size at the start of the experiment or the time of the water exchange from 〈100 nm to approximately 500 nm, which is the optimal size range to be taken up by filter feeding D . magna . If subjected to further agglomeration, larger nTiO 2 particles, however, cannot be retained by the daphnids’ filter apparatus ultimately reducing their ecotoxicological potential. This non-linear pattern of increasing and decreasing nTiO 2 related toxicity over the aging duration, highlights the knowledge gap regarding the underlying mechanisms and processes. This understanding seems, however, fundamental to predict the risks of nanoparticles in the field.