H. Hauck et al., Requirements for the completeness of ambient air quality data sets with respect to derived parameters, ATMOS ENVIR, 33(13), 1999, pp. 2059-2066
Monitoring and sampling of air quality data is costly and labor intensive.
The necessary efforts increase progressively with increasing accuracy requi
rements. Also loss of data because of instrument break down, data transmiss
ion failure, or service and calibrating procedures is more or less unavoida
ble. Calculation of characteristic parameters like means or percentiles as
necessary for information compression and also for comparison with air qual
ity standards do not require complete data sets, since successive primary d
ata like half-hour means are not independent from each other. Emission patt
erns and periodically reappearing or comparably slowly changing transmissio
n conditions are responsible for autocorrelation of these data. Using air q
uality data from the Austrian public monitoring networks for various air po
llutants (NO2, SO2, CO, O-3) over the last decade various patterns of data
loss are simulated and used to compute air quality parameters (fractiles, s
emi-annual means, daily means). The variation interval of these parameters
is compared to equivalent parameters resulting from the complete data sets.
Furthermore, autocorrelation functions of these data are calculated and di
scussed briefly. Finally, the applicability of the parameters obtained from
truncated data sets for air quality management decisions is discussed and
compared to the Austrian standard. The results indicate an error of a few p
ercent - depending on the type of data loss - if these parameters are compu
ted from incomplete data sets up to 50% data loss. Thus reduction of monito
ring efforts without substantial loss of information is possible. (C) 1999
Elsevier Science Ltd. All rights reserved.