Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies

Xavier Flores, L. Corrominas, L. Snip, P.A. Vanrolleghem

Research output: Contribution to journalArticlepeer-review

Abstract

The main objective of this paper is to demonstrate how greenhouse gas (GHG) emissions can be quantified during the evaluation of control strategies in wastewater treatment plants (WWTP). A modified version of the IWA Benchmark Simulation Model No 2 (BSM2G) is hereby used as a simulation case study. Thus, the traditional effluent quality index (EQI), operational cost index (OCI) and time in violation (TIV) used to evaluate control strategies in WWTP are complemented with a new dimension dealing with GHG emissions. The proposed approach is based on a set of comprehensive models that estimate all potential on-site and off-site sources of GHG emissions. The case study investigates the overall performance of several control strategies and demonstrates that substantial reductions in effluent pollution, operating costs and GHG emissions can be achieved when automatic control is implemented. Furthermore, the study is complemented with a scenario analysis that examines the role of i) the dissolved oxygen (DO) set-point, ii) the sludge retention time (SRT) and iii) the organic carbon/nitrogen ratio (COD/N) as promoters of GHG emissions. The results of this study show the potential mechanisms that promote the formation of CO2, CH4 and N2O when different operational strategies are implemented, the existing synergies and trade-offs amongst the EQI, the OCI and TIV criteria and finally the need to reach a compromise solution to achieve an optimal plant performance.
Original languageEnglish
Pages (from-to)4700-4710
JournalWater Research
Volume45
Issue number16
DOIs
Publication statusPublished - 2011

Subject classification (UKÄ)

  • Other Electrical Engineering, Electronic Engineering, Information Engineering

Free keywords

  • Activated sludge modeling
  • Benchmarking
  • Global warming
  • Model-based evaluation
  • Multi-criteria decision making
  • Process control
  • Sustainability

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