Predicting sulphur and nitrogen deposition using a simple statistical method. (September 2016)

• Record Type: Journal Article
• Authors: Oulehle, Filip; Kopáček, Jiří; Chuman, Tomáš; Černohous, Vladimír; Hůnová, Iva; Hruška, Jakub; Krám, Pavel; Lachmanová, Zora; Navrátil, Tomáš; Štěpánek, Petr; Tesař, Miroslav; Evans, Christopher D.
• Is Part Of: Atmospheric environment. Volume 140(2016)
• Page Start: 456
• Page End: 468
• Publication Date: 2016-09
• Subjects: Precipitation -- Sulphur -- Nitrogen -- Deposition -- Monitoring -- Upscaling; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2016.06.028
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Data from 32 long-term (1994–2012) monitoring sites were used to assess temporal development and spatial variability of sulphur (S) and inorganic nitrogen (N) concentrations in bulk precipitation, and S in throughfall, for the Czech Republic. Despite large variance in absolute S and N concentration/deposition among sites, temporal coherence using standardised data (Z score) was demonstrated. Overall significant declines of SO4 concentration in bulk and throughfall precipitation, as well as NO3 and NH4 concentration in bulk precipitation, were observed. Median Z score values of bulk SO4, NO3 and NH4 and throughfall SO4 derived from observations and the respective emission rates of SO2, NOx and NH3 in the Czech Republic and Slovakia showed highly significant (p < 0.001) relationships. Using linear regression models, Z score values were calculated for the whole period 1900–2012 and then back-transformed to give estimates of concentration for the individual sites. Uncertainty associated with the concentration calculations was estimated as 20% for SO4 bulk precipitation, 22% for throughfall SO4, 18% for bulk NO3 and 28% for bulk NH4 . The application of the method suggested that it is effective in the long-term reconstruction and prediction of S and N deposition at a variety of sites. Multiple regression modelling was used to extrapolate site characteristics (mean precipitation chemistry and its standard deviation) from monitored to unmonitored sites. Spatially distributed temporal development of S and N depositions were calculated since 1900. The method allows spatio-temporal estimation of the acid deposition in regions with extensive monitoring of precipitation chemistry. Graphical abstract: Highlights: Temporal coherence of precipitation SO4, NO3 and NH4 was demonstrated. Regional S and N emissions enabled to reconstruct long-term changes in deposition. Empirically-based interpolation allowed spatial deposition variations to be mapped.