Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment

WATER RESEARCH

卷:47

Article

Sweetapple, Christine¹  Fu, Guangtao¹  Butler, David¹ 

[1] Univ Exeter, Coll Engn Math & Phys Sci, Ctr Water Syst, Exeter EX4 4QF, Devon, England

关键词: Benchmark model;    Greenhouse gas;    Model identification;    Sensitivity;    Uncertainty;    Wastewater treatment;   

DOI  :  10.1016/j.watres.2013.05.021

来源: Elsevier

【 摘 要 】

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. (C) 2013 Elsevier Ltd. All rights reserved.

【 授权许可】

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