Estimation of riverine loads of nitrogen and phosphorus to the Baltic Sea, 1970–1993 View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-09

AUTHORS

Per StÅlnacke, Anders Grimvall, Karin Sundblad, Andrzej Tonderski

ABSTRACT

This article presents the results of the first critical examination of time series of riverine nutrient-load data for the entire Baltic Sea drainage area. Water quality data collected by or for the different national environmental agencies were compiled and analysed statistically to identify and remove inconsistent or obviously incorrect observations. Moreover, sampling tours were undertaken to acquire additional information about the present nutrient concentrations in the largest rivers in the study area. Gaps in the time series of approved data were then filled in by employing statistical interpolation and extrapolation methods. Thereafter, the concentration and runoff data were combined to obtain estimates of monthly nutrient loads for the time period 1970–93. The results of the calculations showed that although there had been substantial changes in land use, atmospheric deposition and wastewater treatment in many parts of the study area, the total riverine loads of nitrogen (N) and phosphorus (P) to the Baltic Sea have been fairly constant since 1980, and most likely also since 1970. Moreover, the interannual variation was clearly correlated to the runoff. The mean annual loads for the time period 1980–93 were found to be about 825 000 tonnes N and 41 000 tonnes P, respectively. This implies that (i) several other investigators have strongly underestimated the riverine loads of nutrients, especially the nitrogen, and that (ii) the riverine loads by far exceed the input to the Baltic Sea from other sources, {i.e.} atmospheric deposition, direct emissions from cities and industries along the Baltic Sea coast and nitrogen fixation by marine algae. More... »

PAGES

173-200

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1006073015871

DOI

http://dx.doi.org/10.1023/a:1006073015871

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019242248


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