Prediction of Odor Concentration Emitted from Wastewater Treatment Plant Using an Artificial Neural Network (ANN)

Jeong-Hee Kang,Bong-Jae Lee,Hyon Wook Ji,Sung Soo Yoo,Jihyeon Song

doi:10.3390/atmos11080784

Jeong-Hee Kang, Bong-Jae Lee + Show 3 more

Open Access

https://doi.org/10.3390/atmos11080784

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Abstract

The odor emitted from a wastewater treatment plant (WWTP) is an important environmental problem. An estimation of odor emission rate is difficult to detect and quantify. To address this, various approaches including the development of emission factors and measurement using a closed chamber have been employed. However, the evaluation of odor emission involves huge manpower, time, and cost. An artificial neural network (ANN) is recognized as an efficient method to find correlations between nonlinear data and prediction of future data based on these correlations. Due to its usefulness, ANN is used to solve complicated problems in various disciplines of sciences and engineering. In this study, a method to predict the odor concentration in a WWTP using ANN was developed. The odor concentration emitted from a WWTP was predicted by the ANN based on water quality data such as biological oxygen demand, dissolved oxygen, and pH. The water quality and odor concentration data from the WWTP were measured seasonally in spring, summer, and autumn and these were used as input variations to the ANN model. The odor predicted by the ANN model was compared with the measured data and the prediction accuracy was estimated. Suggestions for improving prediction accuracy are presented.

Highlights

Odor is an environmental pollutant that causes displeasure and health risk to human beings.Residents are weary of the installation of foundational environmental facilities such as wastewater treatment plants (WWTPs) near their neighborhoods owing to the bad odor emitted from their operations
We propose an odor concentration prediction method based on water quality data that is automatically measured daily using a tele-measuring system
Prior to the prediction of the odor concentrations, the odor characteristic in the WWTP were monitored at the six identified locations on a monthly basis from May to September of 2018

Summary

Introduction

Odor is an environmental pollutant that causes displeasure and health risk to human beings. In addition to the above studies, the estimation of water treatment process or patterns and the prediction of biological oxygen demand concentration based on odor concentration has been reported [11] These predictions were conducted using principal component analysis, which involves a significant amount of data and long evaluation period to identify and quantify each component using instrumental analysis. Many restraints are faced while deploying these instruments in the field [8] To overcome these limitations, we propose an odor concentration prediction method based on water quality data that is automatically measured daily using a tele-measuring system. Odor emanating from the WWTP was measured using the olfactometric method and water quality data were obtained from the facility’s officer From these data, odor concentration was predicted using the ANN model

Data Acquisition

Odor Characteristics

Odor Prediction