Long-term assessment of the wet precipitation chemistry in Austria (1984-1999).
The aim of the present study was to determine the long-time trends in concentrations and depositions of major ions in wet precipitation samples collected at 11 sampling sites from the Austrian precipitation chemistry network in the period 1984-1999. The analytical results were treated by the use of least square linear regression method. It is shown that a serious decrease of sulfate (between 30% and 60% for the period) and hydrogen ion (between 60% and 102% for the period) concentrations and depositions is achieved at almost all sampling sites and in most of these cases the linear trend proves to be statistically significant. Nitrogen containing ions and base cations do not reveal a distinct trend of changing and in the majority of the sites the linear models are not adequate. In principle, an overall slight concentration and deposition decrease for these major ions is observed (up to 30% for the period of observation) but some substantial exceptions are also found (site Haunsberg or site Lobau). The changes in chloride concentration and deposition, too, do not indicate significant linear trend and, in general, are decreasing for the period of monitoring. In order to give some explanation of the exceptional behaviour of some of the major ions in several sites, an additional comparison with Austrian emission data (sulfur dioxide, nitrogen oxides, ammonium) and with data from five EMEP sites from neighbouring countries is performed. A significant West-East trend of acidity increase is found as well as a good correlation with the emission trends. Therefore, both transboundary and specific local factors could be substantial factors in the wet precipitation chemistry in the region.
Institute for Analytical Chemistry, Vienna University of Technology, Getreidemarkt 9/151, A-1060 Vienna, Austria.
H
H
Puxbaum
V
V
Simeonov
M
M
Kalina
S
S
Tsakovski
H
H
Löffler
G
G
Heimburger
P
P
Biebl
A
A
Weber
A
A
Damm
D001317:Austria; D011232:Chemical Precipitation; D016014:Linear Models