Optimization of depth of filler media in horizontal flow constructed wetlands for maximizing removal rate coefficients of targeted pollutant(s)

Saurabh Singh; Abhishek Soti; Niha Mohan Kulshreshtha; Nikhil Kumar; Urmila Brighu; Akhilendra Bhushan Gupta; Achintya N Bezbaruah

doi:10.1016/j.biortech.2023.128898

Optimization of depth of filler media in horizontal flow constructed wetlands for maximizing removal rate coefficients of targeted pollutant(s)

Bioresour Technol. 2023 May:376:128898. doi: 10.1016/j.biortech.2023.128898. Epub 2023 Mar 15.

Authors

Saurabh Singh¹, Abhishek Soti¹, Niha Mohan Kulshreshtha¹, Nikhil Kumar², Urmila Brighu¹, Akhilendra Bhushan Gupta³, Achintya N Bezbaruah⁴

Affiliations

¹ Department of Civil Engineering, Malaviya National Institute of Technology, JLN Marg, Jaipur 302017, India.
² Department of Electrical Engineering, Malaviya National Institute of Technology, JLN Marg, Jaipur 302017, India.
³ Department of Civil Engineering, Malaviya National Institute of Technology, JLN Marg, Jaipur 302017, India. Electronic address: abgupta.ce@mnit.ac.in.
⁴ Nanoenvirology Research Group, Department of Civil and Environmental Engineering, North Dakota State University, Fargo, ND 58105, USA.

PMID: 36931442
DOI: 10.1016/j.biortech.2023.128898

Abstract

Varying the depth of HFCW media causes differences in the redox status within the system, and hence the community structure and diversity of bacteria, affecting removal rates of different pollutants. The key functional microorganisms of CWs that remove contaminants belong to the phyla Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes. Secondary data of 111 HFCWs (1232 datasets) were analyzed to deduce the relationship between volumetric removal rate coefficients (K_BOD, K_TN, K_TKN, and K_TP) and depth. Equations of depth were derived in terms of rate coefficients using machine learning approach (MLR and SVR) (R² = 0.85, 0.87 respectively). These equations were then used to find the optimum depth for pollutant(s) removal using Grey wolf optimization (GWO). The computed optimum depths were 1.48, 1.71, 1.91, 2.09, and 2.14 m for the removal of BOD, TKN, TN, TP, and combined nutrients, respectively, which were validated through primary data. This study would be helpful for optimal design of HFCWs.

Keywords: Grey Wolf Optimization (GWO); Horizontal flow constructed wetlands (HFCWs); Major functional microorganisms; Optimum depth; Volumetric removal rate coefficients.

MeSH terms

Environmental Pollutants*
Nitrogen / analysis
Nutrients
Waste Disposal, Fluid*
Wetlands

Substances

Environmental Pollutants
Nitrogen