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Predictive models of copper runoff from external structures
Inger Odnevall Wallinder1, Sofia Bertling, Xueyuan Zhang
1Div. Corrosion Science, Royal Institute of Technology, SE-100 44 Stockholm, Sweden. ingero@kth.se
Journal of Environmental Monitoring : JEM
|August 5, 2004
Summary
A new model predicts annual copper runoff from buildings using rain acidity and quantity. This model accurately estimates copper loss, with pH being the most significant factor influencing patina dissolution.
Area of Science:
- Environmental Science
- Materials Science
- Chemistry
Background:
- Copper patina formation on buildings is influenced by environmental factors.
- Understanding copper runoff is crucial for assessing material degradation and environmental impact.
Purpose of the Study:
- To develop a general model for predicting annual total copper runoff rates from naturally patinated copper on buildings.
- To investigate the effects of rain composition (pH, sulfate, chloride, nitrate) on copper patina dissolution.
Main Methods:
- Deduction of a predictive model from laboratory and field data.
- Analysis of parameters including average annual rain acidity (pH), rain quantity, and building geometry (surface inclination).
- Immersion experiments using artificial rainwater simulating urban and rural European conditions to study rain composition effects.
Main Results:
- The developed model predicts annual runoff rates within 30% of observed values for 70% of cases.
- Rain acidity (pH) has a dominant effect on patina dissolution.
- Nitrate shows a small inhibiting effect, while chloride and sulfate have no significant impact.
Conclusions:
- A physically meaningful model for copper runoff prediction has been established, prioritizing rain acidity.
- The model demonstrates good predictability, with pH being the key environmental factor.
- An alternative model using SO2 is less predictable and lacks physical explanation compared to the pH-based model.