Modelling Temporal Changes Of Nitrogen
Dioxide Concentrations In An Urban Area
Author(s)
C. Capilla
Abstract
Meteorological variability must be taken into account in the modelling of
temporal changes in air pollutants to evaluate emissions reduction strategies. In
this paper nitrogen dioxide (NO2) hourly data are analyzed at two monitoring
stations in Valencia (Spain). Meteorologically-adjusted nitric oxide (NO) is used
as an indicator of traffic density. The low-pass filter developed by Kolmogorov
and Zurbenko is used to split the logarithm of NO2 and NO hourly
concentrations into long-term, seasonal and short-term components.
Meteorological effects are analyzed and removed from filtered pollutants time
series. Forward stepwise regression is employed to select the filtered
meteorological variables that explain more variability. A natural logarithmic
transformation is applied to the series of hourly data and the model for the hourly
pollutants concentrations is multiplicative. The dependencies of urban NO2 on
the corresponding vehicular emissions and relevant meteorological parameters
are non-linear. Long-term components represent a small amount in the overall
variability of air pollution data. Seasonal and short-term components mask the
underlying relationship between NO2 and emissions if studied as a whole. The
pollutant temporal components have to be studied separately due to their
different physical and explanatory mechanisms.
Keywords: air pollution, Kolmogorov-Zurbenko filter, nitrogen dioxide,
temporal changes, urban air quality.
1 Introduction
Air pollution in urban areas is regarded as a growing problem for communities.
Some compounds like ozone, nitrogen oxides, sulphur dioxide and atmospheric
Keywords
air pollution, Kolmogorov-Zurbenko filter, nitrogen dioxide,temporal changes, urban air quality.
Related Book
Other papers in this volume
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