8.6.2 Levels of Validation

A level of validation, for the purposes of this guidance, is a numeric code indicating the degree of confidence in the data. These levels provide some commonality among data collected and quality controlled by different agencies, and help ensure that all data have received a comparable level of validation. Various data validation "levels" that apply to air quality and meteorological data have been defined by Mueller and Watson [66] and Watson et al. [67]. Basically, four levels of data validation have been defined:

• Level 0 data validation is essentially raw data obtained directly from the data acquisition systems in the field. Level 0 data have been reduced and possibly reformatted, but are unedited and unreviewed. These data have not received any adjustments for known biases or problems that may have been identified during preventive maintenance checks or audits. These data should be used to monitor the instrument operations on a frequent basis (e.g., daily), but should not be used for regulatory purposes until they receive at least Level 1 validation.



• Level 1 data validation involves quantitative and qualitative reviews for accuracy, completeness, and internal consistency. Quantitative checks are performed by software screening programs (see Section 8.7.3.2) and qualitative checks are performed by meteorologists or trained personnel who manually review the data for outliers and problems. Quality control flags, consisting of numbers or letters, are assigned to each datum to indicate its quality. A list of suggested quality control codes is given in Table 8-3. Data are only considered at Level 1 after final audit reports have been issued and any adjustments, changes, or modifications to the data have been made.



• Level 2 data validation involves comparisons with other independent data sets. This includes, for example, intercomparing collocated measurements or making comparisons with other upper-air measurement systems.



• Level 3 validation involves a more detailed analysis when inconsistencies in analysis and modeling results are found to be caused by measurement errors.

8. QUALITY ASSURANCE AND QUALITY CONTROL
8.1 Instrument Procurement 
     8.1.1 Wind Speed 
     8.1.2 Wind Direction  
     8.1.3 Temperature and Temperature Difference 
     8.1.4 Dew Point Temperature 
     8.1.5 Precipitation 
     8.1.6 Pressure 
     8.1.7 Radiation  
 8.2 Installation and Acceptance Testing
     8.2.1 Wind Speed 
     8.2.2 Wind Direction  
     8.2.3 Temperature and Temperature Difference 
     8.2.4 Dew Point Temperature 
     8.2.5 Precipitation 
     8.2.6 Pressure
     8.2.7 Radiation
  8.3 Routine Calibrations  
      8.3.1 Sensor Check  
      8.3.2 Signal Conditioner and Recorder Check  
     8.3.3 Calibration Data Logs 
     8.3.4 Calibration Report  
     8.3.5 Calibration Schedule/Frequency 
     8.3.6 Data Correction Based on Calibration Results  
  8.4 Audits 
     8.4.1 Audit Schedule and Frequency  
     8.4.2 Audit Procedure 
     8.4.3 Corrective Action and Reporting 
  8.5 Routine and Preventive Maintenance 
     8.5.1 Standard Operating Procedures  
     8.5.2 Preventive Maintenance  
 8.6 Data Validation and Reporting  
     8.6.1 Preparatory Steps 
     8.6.2 Levels of Validation  
     8.6.3 Validation Procedures  
     8.6.4 Schedule and Reporting
  8.7 Recommendations