Quantitative human health risk assessment along the lifecycle of nano-scale copper-based wood preservatives.
Danail HristozovLisa PizzolGianpietro BaseiAlex ZabeoAiga MackevicaSteffen Foss HansenIlse GosensFlemming R CasseeWim de JongAntti Joonas KoivistoNicole NeubauerAraceli Sanchez JimenezElena SemenzinVrishali SubramanianWouter FransmanKeld Alstrup JensenWendel WohllebenVicki StoneAntonio MarcominiPublished in: Nanotoxicology (2018)
The use of nano-scale copper oxide (CuO) and basic copper carbonate (Cu2(OH)2CO3) in both ionic and micronized wood preservatives has raised concerns about the potential of these substances to cause adverse humans health effects. To address these concerns, we performed quantitative (probabilistic) human health risk assessment (HHRA) along the lifecycles of these formulations used in antibacterial and antifungal wood coatings and impregnations by means of the EU FP7 SUN project's Decision Support System (SUNDS, www.sunds.gd). The results from the risk analysis revealed inhalation risks from CuO in exposure scenarios involving workers handling dry powders and performing sanding operations as well as potential ingestion risks for children exposed to nano Cu2(OH)2CO3 in a scenario involving hand-to-mouth transfer of the substance released from impregnated wood. There are, however, substantial uncertainties in these results, so some of the identified risks may stem from the safety margin of extrapolation to fill data gaps and might be resolved by additional testing. Our stochastic approach successfully communicated the contribution of different sources of uncertainty in the risk assessment. The main source of uncertainty was the extrapolation from short to long-term exposure, which was necessary due to the lack of (sub)chronic in vivo studies with CuO and Cu2(OH)2CO3. Considerable uncertainties also stemmed from the use of default inter- and intra-species extrapolation factors.
Keyphrases
- health risk assessment
- human health
- risk assessment
- drinking water
- heavy metals
- endothelial cells
- climate change
- high resolution
- induced pluripotent stem cells
- cell wall
- pluripotent stem cells
- oxide nanoparticles
- young adults
- metal organic framework
- aqueous solution
- candida albicans
- emergency department
- big data
- single cell
- machine learning
- ionic liquid
- case control
- deep learning
- drug induced
- adverse drug