An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

24 Scopus Citations
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Author(s)

  • Kaili Li
  • Haoran Duan
  • Linfeng Liu
  • Ruihong Qiu
  • Ben van den Akker
  • Bing-Jie Ni
  • Tong Chen
  • Hongzhi Yin
  • Liu Ye

Detail(s)

Original languageEnglish
Pages (from-to)2816-2826
Journal / PublicationEnvironmental Science and Technology
Volume56
Issue number4
Online published2 Feb 2022
Publication statusPublished - 15 Feb 2022
Externally publishedYes

Abstract

Mathematical modeling plays a critical role toward the mitigation of nitrous oxide (N2O) emissions from wastewater treatment plants (WWTPs). In this work, we proposed a novel hybrid modeling approach by integrating the first principal model with deep learning techniques to predict N2O emissions. The hybrid model was successfully implemented and validated with the N2O emission data from a full-scale WWTP. This hybrid model is demonstrated to have higher accuracy for N2O emission modeling in the WWTP than the mechanistic model or pure deep learning model. Equally important, the hybrid model is more applicable than the pure deep learning model due to the lower requirement of data and the pure mechanistic model due to the less calibration requirement. This superior performance was due to the hybrid nature of the proposed model. It integrated the essential wastewater treatment knowledge as the first principal component and the less understood N2O production processes by the data-driven deep learning approach. The developed hybrid model was also successfully implemented under different circumstances for the prediction of N2O flux, which showed the generalizability of the model. The hybrid model also showed great potential to be applied for the N2O mitigation work. Nevertheless, the capability of the hybrid model in evaluating N2O mitigation strategies still requires validation with experiments. Going beyond N2O modeling in WWTP, the novel hybridization modeling concept can potentially be applied to other environmental systems. © 2022 American Chemical Society

Research Area(s)

  • data science, deep learning, domain knowledge, first principal, greenhouse gas, mathematical modeling, nitrous oxide

Citation Format(s)

An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants. / Li, Kaili; Duan, Haoran; Liu, Linfeng et al.
In: Environmental Science and Technology, Vol. 56, No. 4, 15.02.2022, p. 2816-2826.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review