QA measure is a general term for different procedures involved in the quality assurance (QA) of the measurements. QA measures can be an on-site or off-site intercomparison, round-robin or an on-site audit. 

All the QA measures need to be identified with a unique ID (QA measure ID). Usually the ID itself provides a reference to the organization defining the QA measure and a reference to the QA procedure. The QA measure ID's are either administered centrally at NILU or at a calibration Centre. It is only possible to use the predefined QA measure IDs. If additional IDs need to be generated, please contact The QA measure also needs a date (use the enddate if it lasts for a longer period) and a URL where the results can be retrieved. The results can either be site/laboratory specific or it might be a report with the results of the complete QA measure. Which one to use is defined in the different templates.

For some QA measures, it is recommended to also report the statistical results, given as relative bias and variability. Currently this is implemented for inorganic ions and heavy metals in air and precipitation, and EC/OC where annual laboratory intercomparisons are conducted. The results of bias and variability to be included in the data files are calculated centrally; follow the links for the specific templates to download your results.

Note that QA measures can be set in the file global metadata (as the example below). This way it applies to all variables in the file. It could also be overridden for each variable by specifying the metadata in the VNAME lines of the nasa ames file, see this example. In addition, empty metadata values ("tag=") are interpreted as "metadata element not reported". This is used e.g. when resetting the metadata elements for one variable (when it was set to any value in the file global metadata).

More than one QA instance can be relevant for the data contained in a single NASA Ames file. This may happen if the measurements are covered by QA procedures of different networks, or QA measures before and after the data submission interval are relevant. One can state this just by setting numbers 1..n after the QA prefix of the metadata tag (ie QA1 measure ID:), for example:

QA1 measure ID:                       ACTRIS NOx s-b-s 2012
QA1 date:                                   20121116000000
QA1 document URL:                 ""
QA2 measure ID:                       ACTRIS NO round robin 2012
QA2 date:                                  20121231000000
QA2 document URL:                 "" 



Ex. Mobility Particle Size Spectrometer 2016 data from Auchencorth Moss:


Ex: Inorganic ions in precipitation. (Birkenes NO0001-2015)

QA measure ID:

Unique ID for a workshop, intercomparison exercise, or similar.



QA date:

(End)date for exercise (format YYYYMMDD)



QA document URL:

A pdf describing the results either for the specific instrument or lab, or a summary for the whole measure

Implemented for selected components (inorganic ions, heavy metals, EC/OC):

QA outcome:

pass/no pass related to the data quality objectives (DQO)



QA bias

Relative bias from reference value. Marked if systematic. Calculated by the calibration centre (or EMEP/CCC)



QA variability


Relative standard deviation from reference value. Calculated by the calibration Centre (or EMEP/CCC)



Additional metadata generated mainly for export (might be revised):

  • QA measure description
  • QA document name
  • QA measure title
  • QA measure type
  • QA measure responsible instance
  • QA measure URL
 Heavy metals:
Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability  Examples
EMEP laboratory intercomparison Heavy metals in air and precipitation Calculating QA bias and variability from laboratory comparisons.pdf
QA1 measure ID:               EMEP31
QA1 date:                          20131016
QA1 document URL:             ""                                  

This service has been funded or supported by the Norwegian Institute for Air Research (NILU), the EU research infrastructure ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure), the European Monitoring and Evaluation Programme (EMEP).