Non-professional paint stripping, model prediction and experimental validation of indoor dichloromethane levels.

We have experimentally quantified exposure to dichloromethane during non-professional paint stripping and validated the mathematical paint exposure model of van Veen et al. (1999). The model innovates the prediction of the dichloromethane evaporation rate and room concentration by accounting for transport in the paint stripper matrix. The experiments show that peak concentrations range from 600 to 1600 mg/m3, increasing to 2000 mg/m3 when direct sun radiation increases evaporation. A naive model prediction, using a priori parameter values from the experimental set-up and a previous experiment with alkanes, accurately predicts the upper range of the experimental values, but overpredicted four out of six experiments. Statistical fit of the two paint stripper layer parameters to the experimental data resulted in a good coincidence of predicted and experimental data. Model and experiment indicate that 10-30% of dichloromethane is immediately available for evaporation.

Indoor air exposure to volatile compounds emitted by paints: experiment and model.

To describe the evaporation of organic solvents from paints and the resulting indoor concentrations, a mathematical model and an indoor paint experiment are presented. The model describes painting in terms of an increasing area of paint during application and two compartments of paint once applied. Evaporation of organic solvents is driven by the vapor pressure of the organic solvent. The experiment revealed concentrations of n-alkanes in indoor air, during painting, and 3 days thereafter. To compare experimental results to model predictions, model parameters were measured at the start of the experiment. Diffusional exchange between paint compartments and fraction of paint applied to the upper compartment were set by expert judgment. Model predictions and experimental results were in agreement, although the timing of the concentration peak appeared difficult to predict.