Data Quality Control and Quality Assurance

Before data analysis begins, STI scientists devote considerable attention to data quality. Data validation is necessary because serious errors in data analysis and modeling results can be caused by erroneous individual data values. Data validation consists of procedures developed to identify deviations from measurement assumptions. STI staff have developed tools and procedures to validate air quality and meteorological data including a widely used air toxics and hydrocarbon data validation tool (VOCDat from http://vocdat.sonomatech.com/).