What is data validation in ambient monitoring?

• A. Installing new sensors.
• B. Disregarding QA criteria.
• C. Compressing data files.
• D. The process of reviewing data against QA/QC criteria, flagging anomalies, and approving data for reporting.

Answer: (D)

Data validation in ambient monitoring is the process of reviewing data against QA/QC criteria, flagging anomalies, and approving data for reporting. It starts with checking measurements against predefined quality checks—see if readings are within plausible ranges, instruments are properly calibrated, and there are no unexpected gaps. If something looks off, the data are flagged for review so analysts can decide whether to correct, exclude, or annotate the issue. Only data that pass these checks are used in official reports, ensuring the information used for air quality decisions is accurate and defensible. Installing new sensors relates to data collection, not validation; disregarding QA criteria undermines data quality; and compressing files is about data management, not validation.