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Time series analysis of long-term data sets of atmospheric mercury concentrations
Authors:Christian Temme  Ralf Ebinghaus  Jürgen W. Einax  Alexandra Steffen  William H. Schroeder
Affiliation:(1) GKSS Research Centre Geesthacht, Institute for Coastal Research, Max-Planck-Str. 1, 21502 Geesthacht, Germany;(2) Institute for Inorganic und Analytical Chemistry, Department of Environmental Analysis, Friedrich Schiller University of Jena, Lessingstr. 8, 07743 Jena, Germany;(3) Meteorological Service of Canada, Downsview/Toronto, ON, Canada, M3H 5T4
Abstract:Different aspects and techniques of time series analysis were used to investigate long-term data sets of atmospheric mercury in the Northern Hemisphere. Two perennial time series from different latitudes with different seasonal behaviour were chosen: first, Mace Head on the west coast of Ireland (53°20primeN, 9°54primeW), representing Northern Hemispherical background conditions in Europe with no indications for so-called atmospheric mercury depletion events (AMDEs); and second, Alert, Canada (82°28primeN, 62°30primeW), showing strong AMDEs during Arctic springtime. Possible trends were extracted and forecasts were performed by using seasonal decomposition procedures, autoregressive integrated moving average (ARIMA) methods and exponential smoothing (ES) techniques. The application of time series analysis to environmental data is shown in respect of atmospheric long-term data sets, and selected advantages are discussed. Both time series have not shown any statistically significant temporal trend in the gaseous elemental mercury (GEM) concentrations since 1995, representing low Northern Hemispherical background concentrations of 1.72±0.09 ng m–3 (Mace Head) and 1.55±0.18 ng m–3 (Alert), respectively. The annual forecasts for the GEM concentrations in 2001 at Alert by two different techniques were in good agreement with the measured concentrations for this year.
Keywords:Time series analysis  Atmosphere  Mercury  Long-term trend  Forecast  Atmospheric mercury depletion events
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