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contributor authorDonatella Caniani
contributor authorGiovanni Esposito
contributor authorRiccardo Gori
contributor authorCecilia Caretti
contributor authorGiacomo Bellandi
contributor authorIgnazio M. Mancini
contributor authorMarianna Caivano
contributor authorRaffaella Pascale
contributor authorAlida Cosenza
contributor authorHafed Abouissa
contributor authorGiorgio Mannina
date accessioned2019-09-18T10:40:36Z
date available2019-09-18T10:40:36Z
date issued2019
identifier other%28ASCE%29EE.1943-7870.0001538.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4260142
description abstractMechanisms causing greenhouse gas (GHG) emission in wastewater treatment plants are of great interest among researchers, encouraging the development of new methods for wastewater management. Wastewater treatment plants (WWTPs) emit three major greenhouse gases during the treatment processes: CO2, CH4, and N2O. Additional amounts of CO2 and CH4 are produced during energy consumption, which can be considered an indirect source of GHGs. Recently, several efforts have been undertaken to assess GHGs from WWTPs, with particular attention paid to the N2O assessment due to its high warming potential (300 times stronger than CO2). This study proposes an integrated model platform for WWTP simulation, including the evaluation of both direct and indirect emissions as plant performance parameters. The results of extensive research demonstrate the importance of mathematical modeling for the development of a decision support system (DSS). The project involves four research units (RUs) united in effort to minimize the environmental impact of wastewater treatment plants in terms of both energy consumption and discharged pollutants (solids, liquids, and gases).
publisherAmerican Society of Civil Engineers
titleToward a New Plant-Wide Experimental and Modeling Approach for Reduction of Greenhouse Gas Emission from Wastewater Treatment Plants
typeJournal Paper
journal volume145
journal issue8
journal titleJournal of Environmental Engineering
identifier doi10.1061/(ASCE)EE.1943-7870.0001538
page04019043
treeJournal of Environmental Engineering:;2019:;Volume ( 145 ):;issue: 008
contenttypeFulltext


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