Graduation Year

2021

Document Type

Thesis

Degree

M.S.E.V.

Degree Name

MS in Environmental Engr. (M.S.E.V.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Mauricio E. Arias, Ph.D.

Committee Member

Sarina J. Ergas, Ph.D.

Committee Member

Mahmood Nachabe, Ph.D.

Keywords

biochar, ammonia, landfill leachate, nitrification, Python, zeolite

Abstract

There is a need for alternative methods for municipal landfill leachate treatment as the high concentrations of pollutants in leachate interfere with processes at publicly owned treatment works (POTWs). Constructed wetlands (CWs) have been shown to be a sustainable alternative with good removal efficiencies for chemical oxygen demand (COD) and ammonia nitrogen (NH4+). The addition of an adsorbent media, such as zeolite and biochar, to CWs to further enhance removal efficiencies has been investigated in recent years. However, the long-term effects of zeolite and biochar addition to CWs is not well known. A model could be a useful tool to aid in the design of CWs with zeolite and biochar. A preliminary version of a numerical process model was developed to account for the major processes that occur in CWs and incorporates the effects of zeolite added to a vertical subsurface flow (VSSF) CW and biochar added to a horizontal subsurface flow (HSSF) CW. The model was developed in Python 3.7 to facilitate use and allows for varying leachate characteristics. The model is dynamic and can be used to predict daily effluent concentrations of COD, organic N, NH4+, and NO3-. Experimental data from a pilot-scale CW was used to calibrate the model. High simulated rates of nitrification were observed in the VSSF amended with zeolite and high simulated rates of denitrification were observed in the HSSF with biochar addition. Overall, the model is able to predict the general trends in effluent concentrations of COD, NH4+, and NO3-; however, high root mean square errors (RMSE) were observed. The model could potentially be improved by taking spatial gradients into consideration. Additionally, the bioregeneration of biochar could also be modeled to increase model fitness over a longer period of time.

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