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Artificial intelligence control of a sequencing batch reactor for nitrogen removal via nitrite from landfill leachate

TitoloArtificial intelligence control of a sequencing batch reactor for nitrogen removal via nitrite from landfill leachate
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2010
AutoriSpagni, A., and Marsili-Libelli S.
RivistaJournal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering
Volume45
Paginazione1085-1091
ISSN10934529
Parole chiaveActivated sludge process, aeration, Aeration energy, article, Artificial intelligence, Automation, Batch reactors, Biochemical oxygen demand, Chemical oxygen demand, Computer control systems, Control and automation, control system, Dissolution, dissolved oxygen, energy conservation, Fluid, Fuzzy control, Fuzzy logic, Fuzzy systems, heavy metal removal, High strength wastewater, Hydraulic retention time, Kjeldahl, landfill, landfill leachate, Landfill leachates, Leachate treatment, Leachates, leaching, Loading rate, Main process, nitrite, Nitrites, Nitrogen, Nitrogen removal, Operating condition, oxidation reduction potential, Oxidation-reduction potentials, pH, phase transition, Phase transitions, Process measurements, Refuse Disposal, Sanitary landfill, Sequencing batch reactor, Sequencing batch reactor (SBR), Sequencing batch reactors, Smart control systems, System-based, Time-varying process, Waste disposal, waste water, Wastewater, Wastewater treatment
Abstract

Leachate generated in old landfills is a high-strength wastewater, which is particularly difficult to treat owing to its low biochemical oxygen demand/total Kjeldahl nitrogen ratio. This paper seeks to demonstrate that reliable leachate treatment by means of sequencing batch reactors (SBRs) is indeed possible by means of the application of a smart control system. This study assesses the results of a computer-controlled bench-scale SBR treating raw sanitary landfill leachate to achieve nitrogen removal through the nitrite shortcut. Significant improvements have been obtained by introducing a fuzzy inferential system based on simple process measurements (i.e. dissolved oxygen, oxidation-reduction potential and pH). The paper analyzes the results of a test period of over 280 consecutive days of operation, during which the fuzzy control system correctly recognized over 97% of the SBR phase transitions and provided smart adjustments of the process operating conditions in terms of phase length and external COD addition. In spite of time-varying process conditions, the application of fuzzy logic provided stable nitrogen removal via nitrite through continuous adjustments of the main process parameters and resulted in a decreased hydraulic retention time, an increased loading rate, a saving in the external COD addition and considerable aeration energy conservation. Copyright © Taylor & Francis Group, LLC.

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cited By 4

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77953264210&doi=10.1080%2f10934529.2010.486339&partnerID=40&md5=bc51f63a674a57d61e3847c1cbd63326
DOI10.1080/10934529.2010.486339
Citation KeySpagni20101085