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Submit DataData ReportingCommentsModulesQA    October 17, 2019

Description

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 ebas@nilu.no. 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.

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:                 "http://fp7.actris.eu/Portals/97/deliverables/PU/WP4_D4.6_M24_final_v2.pdf"
QA2 measure ID:                       ACTRIS NO round robin 2012
QA2 date:                                  20121231000000
QA2 document URL:                 "http://fp7.actris.eu/Portals/97/deliverables/PU/WP4_D4.4_M24.pdf" 

Metadata

Description

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.

MPSS-2016-5

EMEP33

QA date:

(End)date for exercise (format YYYYMMDD)

20160901

20150801

QA document URL:

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

http://actris-ecac.eu/files/ECAC-report-MPSS-2016-5-1.pdf

http://www.nilu.no/projects/ccc/intercomparison/qameasure/emep33_G.pdf

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

QA outcome:

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

 

pass

QA bias

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

 

5.1%

QA variability

 

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

 

2.3%

 

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
 Particulate matter and aerosol particle variables:
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Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability  Examples
Levoglucosan 2009 An intercomparison study of analytical methods used for quantification of levoglucosan in ambient aerosol filter samples Levoglucosan

QA measure ID: Levoglucosan 2009
QA date:         20080713
QA document URL: "https://doi.org/10.5194/amt-8-125-2015"
EMEP-ACTRIS-Levoglucosan-2013  EMEP QA based on raw data from ACTRIS inter-comparison) Levoglucosan

 
EMEP-ACTRIS-ECOC-<year>  EMEP QA based on raw data from ACTRIS inter-comparison) EC/OC


QA1 measure ID:                          EMEP-ACTRIS-ECOC-2013
QA1 date:                                     20140716
QA1 document URL:                    "http://www.nilu.no/projects/ccc/reports/cccr1-2013.pdf"
QA1 bias:                                      10% 
QA1 variability:                              15%
ECAC-OCEC-<year>-<number> ECAC Inter-laboratory comparison exercise for TC and EC measurements EC/OC


QA1 measure ID:                          ECAC-OCEC-2018-1
QA1 date:                                     20180316
QA1 document URL:                    "https://www.actris-ecac.eu/files/ECAC-report-OCEC-2018-1.pdf"
QA1 bias:                                      3.5%
QA1 variability:                              5.3%
WCCAP-CPC-<year>-<number> Calibration workshops and laboratory intercomparisons of Condensation Particle Counter Particle Number Concentration  
QA measure ID:   WCCAP-CPC-2016-5
QA date:         20160927
QA document URL: "http://www.actris-ecac.eu/files/ECAC-report-CPC-2016-5-1.pdf"



WCCAP-MPSS-<year>-<number> Calibration workshops and laboratory intercomparisons of Mobility Particle Size Spectrometers Particle Number Size Distribution  
QA measure ID:   WCCAP-MPSS-2016-5
QA date:         20160912
QA document URL: "http://www.actris-ecac.eu/files/ECAC-report-MPSS-2016-5-7.pdf"



WCCAP-OSIA-<year>-<number> On-site Intercomparison & Audit Particle Number Size Distribution (Particle Number Concentration)  
QA measure ID:   WCCAP-OSIA-2016-1
QA date:         20160526
QA document URL: "https://www.actris-ecac.eu/files/ECAC-report-OSIA-2016-1-1_UHEL_DMPS.pdf"



WCCAP-AP-<year>-<number> Calibration workshops and laboratory intercomparisons of Absorption Photometers  Particle light absorption coefficient  
QA measure ID:   WCCAP-AP-2015-1
QA date:         20150925
QA document URL: "http://www.actris-ecac.eu/files/ECAC-report-AP-2015-1-1_ISSeP_AE22-1083.pdf"



WCCAP-IN-<year>-<number> Calibration workshops and laboratory intercomparisons of Integrating Nephelometers
Particle light scattering coefficient  
WCCAP-CCNC-<year>-<number>  Calibration workshops and laboratory intercomparisons of Cloud Condensation Nuclei Counter Cloud condensation nuclei number concentration    No online reports available.
WCCAP-ACSM-<year>-<number>
Calibration workshops and laboratory intercomparisons of Aerosol Chemical Speciation Monitors
Particulate chemical composition  
QA measure ID:   WCCAP-ACSM-2016-1
QA date:         20160314
QA document URL: "http://www.actris-ecac.eu/files/ECAC-report-ACSM-2016-1-4.pdf"


 Photochemical oxidants, greenhouse gases and other trace gases:
Minimize
 
Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability Examples
ACTRIS-VOC-1 ACTRIS VOC round-robin (Hörger et al., AMT, 2015) NMHC/VOC/OVOC


QA measure ID:   ACTRIS-VOC-1
QA date:         20120422
QA document URL: "https://doi.org/10.5194/amt-8-2715-2015"
AMOHA 3 Accurate Measurements of Hydrocarbons in the Atmosphere(AMOHA): Three European intercomparisons
J. Geophys. Res.,107(D19), 4409, doi:10.1029/2001JD001357, 2002.
 NMHC  
QA measure ID:   AMOHA 3
QA date:         19990222
QA document URL: "https://doi.org/10.1029/2001JD001357"
WCC Empa Site Audit  World Calibration Centre (WCC-Empa) for Surface Ozone, Carbon Monoxide, Methane and Carbon Dioxide Site Audits ozone, carbon_monoxide, carbon_dioxide, methane
bias = slope of the residual regression line (in %)
variability = arithmetic mean of the distance of all values from the residual regression line
 
ACTRIS NO round robin 2012 ACTRIS WP4- NA4: Trace gases networking: Volatile organic carbon and nitrogen oxides
Deliverable D4.4: Results of Round Robin exercise of NO
 NOx  
QA measure ID:   ACTRIS NO round robin 2012
QA date:         20121231
QA document URL: "http://fp7.actris.eu/Portals/97/deliverables/PU/WP4_D4.4_M24.pdf"
ACTRIS NOx s-b-s 2012 ACTRIS WP4- NA4: Trace gases networking: Volatile organic carbon and nitrogen oxides
Deliverable D4.6: Results of NOx side-by-side inter-comparison exercise of ambient air and test gases
 NOx  
QA measure ID:   ACTRIS NOx s-b-s 2012
QA date:         20121116
QA document URL: "http://fp7.actris.eu/Portals/97/deliverables/PU/WP4_D4.6_M24_final_v2.pdf"
 Persistent organic pollutants:
Minimize
 
Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability  Examples
EMEP_AMAP_POP_2010


POP Not yet applicable
EMEP_POP_2002 POP   Not yet applicable
 Inorganic compounds in air and precipitation:
Minimize
 
Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability  Examples
EMEP1
...
EMEP33
EMEP laboratory intercomparison Inorganic ions in air and precipitation Calculating QA bias and variability from laboratory comparisons.pdf
QA1 measure ID:         EMEP31
QA1 date:                     20131016
QA1 document URL:             "http://www.nilu.no/projects/ccc/intercomparison/qameasure/emep31_ABCJ.pdf"                           
 Heavy metals:
Minimize
 
Currently known QA measures

QA measure ID  QA measure description Applicable to Calculation of QA bias and QA variability  Examples
EMEP1
...
EMEP33
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:             "http://www.nilu.no/projects/ccc/intercomparison/qameasure/emep31_ABCJ.pdf"                                  

Generic QA measure ID's for ozone measurements

QA procedures for ozone can either refer to a regular and predefined QA measure (e.g. WCC Empa audit), or calibrations are performed using a laboratory standard traceable to a national standard (or both). This section describes the laboratory standard QA procedure.

The procedure is typically performed in this way: The laboratory standard instrument is calibrated against a national standard every few years. All field instruments used by a laboratory are calibrated against the laboratory standard instrument more regularly.

When the QA using a laboratory standard should be described in the EBAS metadata, a QA measure ID can be generically generated when reporting the data, using the following convention:

  • Each calibration of the laboratory standard creates a new QA measure. Each calibration of a field instrument can then refer to the laboratory standard and it's last calibration.
  • There is no explicit registration of the QA measures in the EBAS database in this case. Each laboratory can report this information implicitly by referring to a new QA measure. However, to automate this, some additional requirements are necessary:
    • The QA measure ID must be generated according to this syntax <LAB_CODE>_reference_calibration_<DateYYYYMMDD>.
    • This strict syntax requirement makes sure, we can create the QA measure automatically the first time it is reported.
    • By including the laboratory code, the measure ID will be automatically in the domain of each laboratory and ID conflicts will be avoided.
    • Additional metadata elements for describing the QA measure must be included: QA measure ID, QA date and QA document URL
 
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Other relevant literature

Description
 Category
 

Plass Dülmer et al., JGR, 2006:European hydrocarbon intercomparison experiment AMOHA part 4: Canister sampling of ambient air

This publication contains the main findings of the AMOHA intercomparison in 2000. Although its contents are somehow outdated, it still contains a lot of useful information.

 NMHC

Rappenglück et al., Atmos. Environ., 2006:The first VOC intercomparison exercise within the Global Atmosphere Watch (GAW).

This first GAW-VOC intercomparison experiment highlights the need of a network-wide calibration standard (establishing of a scale) for improving data comparability.


NMHC


Apel et al., JGR, 2003: Nonmethane Hydrocarbon Intercomparison Experiment (NOMHICE): Task 4, ambient air

The NOMHICE program has been designed to evaluate current methods being used to determine the ambient levels of various atmospheric non-methane hydrocarbons, to identify existing problems in these analyses, to correct these problems and to help ensure quality control of hydrocarbon analyses made by atmospheric scientists throughout the world.


NMHC


Steinbrecher et al., J. Environ. Anal. Chem.,1994:Monoterpenes in Air Samples: European Intercomparison Experiments.


Terpenes


Larsen et al., Atmos. Environ., 1997: Sampling and analysis of terpenes in air: an interlaboratory comparison.


Terpenes


Apel et al., JGR, 2008:Intercomparison of oxygenated volatile organic compound measurements at the SAPHIR atmosphere simulation chamber.

The first large-scale in situ intercomparison of oxygenated volatile organic compound (OVOC) measurements. The intercomparison was conducted blind at the large (270 m3) simulation chamber, Simulation of Atmospheric Photochemistry in a Large Reaction Chamber (SAPHIR), in Juelich, Germany.



OVOC


Wisthaler et al., ACP, 2008:Intercomparison of formaldehyde measurements at the atmosphere simulation chamber SAPHIR.


OVOC
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