Modelling The Multi Year Air Quality Time Series
In Edinburgh: An Application Of The
Hierarchical Profiling Approach
Author(s)
H. Al-Madfai, D. G. Snelson & A. J. Geens
Abstract
Modelling and forecasting of time series of concentrations of air pollutants is
essential in monitoring air quality and assessing whether set targets will be
achieved. While many established time series modelling approaches transform
the data to stationarity a priori, the explicit modelling and presentation of the
non-stationary components of the series in this application is essential to allow
for further understanding of variability and hence more informed policies. The
Hierarchical Profiling Approach (HPA) was used to model the multi-year daily
air quality data gathered at St. Leonards in Edinburgh, UK spanning from 1st of
March 2004 to 15th July 2007. The HPA is an avant-garde approach that
explicitly models the non stationary component of time series data at different
levels depending on the span of the component, so that within-year disturbances
are at Level 1 and year-long variability such as seasonality is at Level 2, and so
on. HPA decomposes the variability into deterministic, stochastic and noise and
uses continuous models to describe the non-stationary components using the
deterministic part of the model. The stationary stochastic component is then
modelled using established approaches. The dataset modelled was the total daily
concentrations of carbon monoxide. After modelling within-year events at Level
1, a harmonic regression with trend model was used to describe the weekly
aggregates of the data at Level 2. This model was then sampled back in the daily
domain and no evidence of a larger cyclical component was found. Wind-speed
and a dummy intervention-variable indicating the implementation of the smoking
ban were considered in a transfer function model. The concluding model
included the present and one lagged observations of wind speed. The smoking
ban variable was not significant.
Keywords: monitoring air quality, Hierarchical Profiling Approach, smoking.
Keywords
monitoring air quality, Hierarchical Profiling Approach, smoking.
Related Book
Other papers in this volume
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