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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472
EISSN: 1735-2630
Vol. 11, No. 7, 2014, pp. 1947-1958
Bioline Code: st14191
Full paper language: English
Document type: Research Article
Document available free of charge

International Journal of Environment Science and Technology, Vol. 11, No. 7, 2014, pp. 1947-1958

 en Extended statistical entropy analysis for the evaluation of nitrogen budgets in Austria
Sobańtka, A.P.; Thaler, S.; Zessner, M. & Rechberger, H.

Abstract

Extended statistical entropy analysis (eSEA) is used to evaluate the nitrogen (N) budgets of two Austrian catchments, the Wulka and the Ybbs, and of entire Austria. The eSEA quantifies the extent of N dispersion in the environment. The results from the eSEA are compared to the corresponding N use efficiencies (NUEs). Application of the eSEA reveals that the Ybbs catchment, compared to the Wulka catchment leads to a greater extent of N dispersion, primarily as a result of increased losses of N compounds to the atmosphere and in leachates to the groundwater. The NUE in the Wulka catchment, at 63 %, is substantially higher than that in the Ybbs catchment, at 43 %, and confirms a more efficient N use in Wulka. Furthermore, it is shown that the adoption of a healthy, balanced diet, as defined by the German Nutrition Society, changes the N budget of Austria in a way that significantly reduces the dispersion of N. Decreased N losses to the atmosphere and to the groundwater are primarily responsible for this result. The national NUE of Austria responds only moderately to the adoption of such a diet increasing from 48 to 53 % and leads to statistically insignificant results if the uncertainty of the input data is taken into account. This study demonstrates the effectiveness of eSEA for the evaluation of N budgets in agricultural regions and suggests that statistical entropy can serve as a reliable agri-environmental indicator to support decisions regarding nutrient management.

Keywords
Agri-environmental indicators; Emissions from agriculture; Evaluation methods; Nitrogen budgets; Optimized nutrition; Statistical entropy

 
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