Extended statistical entropy analysis for the evaluation of nitrogen budgets in Austria

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.

Statistical entropy analysis as tool for circular economy: Proof of concept by optimizing a lithium-ion battery waste sieving system

“…sieving system, as a proof-of-concept. Even though previous applications of MFA and RSE for resource management have brought positive outcomes (Bai et al, 2015;Laner et al, 2017;Rechberger and Brunner, 2002;Rechberger and Graedel, 2002;Sobantka et al, 2014) the present work reaches the point of process optimization upon which organizational decisions can be based.…”

“…Reportedly, the application of MFA and statistical entropy to different material flow systems has produced positive outcomes in the resource management field. This has been used, for example, to improve the efficiency of a smelting operation by locating losses (Bai et al, 2015), setting the base for an improved resource management by analyzing the Cu flow in Europe and P and N in Austria (Laner et al, 2017;Rechberger and Graedel, 2002;Sobantka et al, 2014), and as a tool to support waste management decisions (Rechberger and Brunner, 2002). Nevertheless, the use of this methodology has been focused on the description of the studied system and not applied as an optimization guideline for recycling systems.…”

Nitrogen Budget and Statistical Entropy Analysis of the Tiber River Catchment, a Highly Anthropized Environment

“…A reduction of 25% or 50% of the N loads increased the N efficiency of the Tiber River catchment system, as demonstrated by the RSE simulations. The first intercomparison exercise was carried out by comparing the values obtained for the Tiber River Catchment with those obtained for the Austrian catchments of Wulka and Ybbs [73]. We observed that the TRC system has a greater nitrogen management efficiency, with a delta surplus = 15.83% (19 kg N/ha yr), NUE = 84% and ∆H = 51%, despite the greater surface area of the catchment and UAA.…”

“…The dilution and/or concentration concerned the natural levels of the environmental concentrations of the element or compounds examined. In general, entropy increased when the nitrogen emitted in a compartment was at a higher concentration than the natural background [71][72][73].…”

Implementation of Extended Statistical Entropy Analysis to the Effluent Quality Index of the Benchmarking Simulation Model No. 2

“…It has been applied to a hypothetical crop farming region showing how the N-performance could be improved in terms of less dilution of N-compounds to the environment [30]. In the following, eSEA has been used to assess the N-performance of Austrian farming regions, suggesting that statistical entropy has the potential to serve as an indicator for the evaluation of nutrient budgets [31]. Furthermore, eSEA has been applied to wastewater treatment plants (WWTPs) estimating the N-removal performance.…”