Author(s): G. Latini, G. Passerini & S. Tascini
In this work we present a set of procedures to achieve an extended air quality Data
Base starting from sets of raw data which can be affected by wide gaps due to
malfunction of sensors and/or weaknesses in collection software.
The focus is on
the statistic filling of incomplete time series, after evaluating a short range of
In the first step we analyse statistics and substituted undoubtedly abnormal
isolated values by means of specific algorithms such as Wilcoxon rank sum test,
Box-Jenkins model, trend analysis, regression etc.
Then we proceed with
missing data filling along time series choosing among linear interpolation, nearest
neighbor and spatial averaging algorithms.
Standard filling protocols such as those
proposed by EPA (Environmental Protection Agency) and by NWS (National
Size: 1,236 kb
Paper DOI: 10.2495/AIR010581
the Full Article
This article is part of the WIT OpenView scheme and you can download the full text Adobe PDF article for FREE by clicking the 'Openview' icon below.
this page to a colleague.