Podrobnosti záznamu

    An elevation-based regional model for interpolating sulphur and nitrogen deposition
    Hejzlar, Josef
    Kopáček, Jiří
    Oulehle, Filip
    Posch, Maximilian
    Volková, Alena
Typ dokumentu
    článek v periodiku
Zdrojový dokument - seriál
    Atmospheric Environment
    Roč. 50, č. April
Výraz tezauru
    Atmospheric deposition, Sulphur, Nitrogen, Vltava river
Klíčové slovo
Abstrakt (anglicky)
   We developed and tested a regression model, interpolating long-term sequences of observed atmospheric deposition of SO4, NO3, and NH4 in the upper Vltava river catchment (Czech Republic) to its three sub-regions, differing in elevation and forest cover. The model provides more realistic estimates of wet and total S and N depositions and their inter-annual variability in the study catchment than the available European deposition sequences, especially in the case of wet S deposition prior to 1997. In the model, ion fluxes are calculated as the product of the precipitation volume and ion concentrations, which both are derived as empirical functions of elevation and time. The long-term sequences of ion concentrations are based on measured deposition data at 19 stations and their relationships with central European emission trends of SO2, NOx, and NH3 for years with no measurements. Exponential relationships between elevation and precipitation volume (positive) and elevation and ion concent
   rations(negative) are used to convert the long-term sequences of precipitation and concentrations into values for individual elevations. Throughfall fluxes (TF) of S and N in the forest areas are calculated from their fluxes in precipitation (PF), using long-term sequences of TF:PF ratios, based on measured fluxes and the S and N emission trends. The calculated fluxes of S and reactive nitrogen (NO3 and NH40 explain 80% and 56% of the variability in their measured fluxes, respectively, along an elevation gradient from 275 to 1334 m.
    Česká geologická služba
Kód přispěvatele
    ČGS (RIV)
Zdrojový formát
Datum importu
    15. 10. 2014