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Monitoring of environmental contaminants is a critical part of exposure sciences research and public health practice. Missing data are often encountered when performing short-term monitoring ( less then 24 h) of air pollutants with real-time monitors, especially in resource-limited areas. Approaches for handling consecutive periods of missing and incomplete data in this context remain unclear. Our aim is to evaluate existing imputation methods for handling missing data for real-time monitors operating for short durations. In a current fie