Effects of time-averaging climate parameters on predicted multicompartmental fate of pesticides and POPs.
With the aim to investigate the justification of time-averaging of climate parameters in multicompartment modelling the effects of various climate parameters and different modes of entry on the predicted substances' total environmental burdens and the compartmental fractions were studied. A simple, non-steady state zero-dimensional (box) mass-balance model of intercompartmental mass exchange which comprises four compartments was used for this purpose. Each two runs were performed, one temporally unresolved (time-averaged conditions) and a time-resolved (hourly or higher) control run. In many cases significant discrepancies are predicted, depending on the substance and on the parameter. We find discrepancies exceeding 10% relative to the control run and up to an order of magnitude for prediction of the total environmental burden from neglecting seasonalities of the soil and ocean temperatures and the hydroxyl radical concentration in the atmosphere and diurnalities of atmospheric mixing depth and the hydroxyl radical concentration in the atmosphere. Under some conditions it was indicated that substance sensitivity could be explained by the magnitude of the sink terms in the compartment(s) with parameters varying. In general, however, any key for understanding substance sensitivity seems not be linked in an easy manner to the properties of the substance, to the fractions of its burden or to the sink terms in either of the compartments with parameters varying. Averaging of diurnal variability was found to cause errors of total environmental residence time of different sign for different substances. The effects of time-averaging of several parameters are in general not additive but synergistic as well as compensatory effects occur. An implication of these findings is that the ranking of substances according to persistence is sensitive to time resolution on the scale of hours to months. As a conclusion it is recommended to use high temporal resolution in multi-media modelling.
Lammel
Gerhard
G
Max Planck Institute for Meteorology, Bundesstr. 55, 20146, Hamburg, Germany. lammel@dkrz.de
D002980:Climate; D004785:Environmental Pollutants; D004787:Environmental Pollution / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D009930:Organic Chemicals; D010575:Pesticides; D013997:Time Factors
D004785:Environmental Pollutants; D009930:Organic Chemicals; D010575:Pesticides