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

Abstract

Abstract:Extended statistical entropy analysis (eSEA) is used to assess the nitrogen (N) removal performance of the wastewater treatment (WWT) simulation software, the Benchmarking Simulation Model No. 2 (BSM No. 2 ). Six simulations with three different types of wastewater are carried out, which vary in the dissolved oxygen concentration (O 2,diss. ) during the aerobic treatment. N 2 O emissions generated during denitrification are included in the model. The N-removal performance is expressed as reduction in statistical entropy, ΔH, compared to the hypothetical reference situation of direct discharge of the wastewater into the river. The parameters chemical and biological oxygen demand (COD, BOD) and suspended solids (SS) are analogously expressed in terms of reduction of COD, BOD, and SS, compared to a direct discharge of the wastewater to the river (ΔEQ rest ). The cleaning performance is expressed as ΔEQ new , the weighted average of ΔH and ΔEQ rest . The results show that ΔEQ new is a more comprehensive indicator of the cleaning performance because, in contrast to the traditional effluent quality index (EQ), it considers the characteristics of the wastewater, includes all N-compounds and their distribution in the

Mapping Recyclability of Industrial Waste for Anthropogenic Circularity: A Circular Economy Approach

“…The distribution of substances in a given waste can be estimated relying on a mathematical function called “statistical entropy” from the Information Theory . Integrating the statistical entropy with material flow analysis on waste management, certain specific management goals can be achieved, such as evaluating the waste treatment system, ,, assessing the chemical compound concentration and dilution, ,− mapping substance flows, and harnessing waste and resource . The statistical entropy of a finite probability distribution is expressed by eqs and . where P i is the probability of event i , which is replaced by the concentration of i material; n is the total number of materials in an industrial waste sample; and H denotes entropy (unit of entropy is bit).…”

Emerging outcomes from a cross-disciplinary doctoral programme on water resource systems

“…They were typically categorised as contextual multidisciplinary and borrowed methods or models from one setting and applied them in a new setting without modifying them, e.g. a method for evaluating resource management of metals was applied to the new setting of nitrogen in wastewater treatment (see Sobantka et al, 2014). The low number of multidisciplinary publications could suggest that Programme researchers mainly work on interdisciplinary endeavours, or alternatively perhaps suggests that multidisciplinary work is more difficult to publish in leading ISI indexed journals.…”