Real-time automated quality control of atmospheric aerosol time series

Abstract. Automated, reproducible quality control (QC) of aerosol optical time series is essential for comparable, reusable data in observation networks and research infrastructures. We present a real-time-capable QC workflow for AE33 Aethalometer equivalent black carbon (eBC) and Aurora 4000 nephelometer scattering measurements (σ_sca). The workflow is implemented in the open-source SaQC framework and wrapped by the actris_qc package, which encodes community QA/QC recommendations into a three-stage, machine-readable rule set for device-control, channel-specific and derived-variable checks. The pipeline is parameterised using a catalogue of instrument anomalies from the urban TROPOS site and validated at the rural Melpitz station, demonstrating robust transfer across contrasting environments. It reliably flags outliers, noise, plateaus and device malfunctions while preserving genuine atmospheric variability and achieves real-time performance on standard hardware. The modular, configuration-driven design enables straightforward adaptation to additional instruments and networks, providing harmonised QC flags and provenance and enabling FAIR-compliant and AI-ready downstream use in monitoring systems.