Predictive models of copper runoff from external structures.

Abstract

A general model for annual runoff rate predictions of total copper from naturally patinated copper on buildings at specific urban or rural sites of low chloride influence has been deduced from laboratory and field data. All parameters within the model have a physical meaning and include the average annual rain acidity (pH), the annual rain quantity and the geometry of a building in terms of surface inclination. In 70% of all reported annual runoff rates, the predicted values are within 30% from the observed values. The individual and interactive effect of rain composition in terms of pH, sulfate, chloride and nitrate concentration was investigated in immersion experiments in artificial rain water representative of urban and rural sites of Europe. The results show pH to have a dominating effect on patina dissolution, nitrate to have a small inhibiting effect, whereas no significant effect was seen for chloride and sulfate. In case pH data are not available, a model has been statistically deduced from field data by considering SO2 as influencing parameter, rather than pH. The predictability with the SO2 model is not as good as with the pH model i.e. the pH model should preferentially be used since it is a better predictor and all parameters within the model can be physically explained.