Forecasting Air Pollution with Sulfur Dioxide Emitted from Burning Desulfurized Diesel Using Artificial Neural Network

Abstract

Concentrations of emitted pollutants in the atmosphere are influenced by the emission sources and metrological data. In Jordan, Diesel fuel is considered to be a main source of SO2, which has negative impact on air quality. In this work, the emitted SO2 during the burning of desulfurized diesel fuel using activated carbon is conducted using three types of Artificial Neural Network (Elman, NARX and Feedforward models). To accomplish this, previously experimental work on desulfurization of diesel fuel using two types of activated carbon was adopted. Metrological data involving the average daily temperature (T), relative humidity (RH), wind speed (WS), pressure (P), concentration of Particulate Matter (PM10) and average daily solar radiation (SR) over the period from 2/1/2020 to 30/12/2020. It was found that NARX model is the most accurate model in the furcating process of SO2, flowed by Elman and feedforward was found to be the least capable model in predicting the SO2 emitted concentration.

Keywords

• air pollution
• activated carbon
• sulfur dioxide
• desulfurized diesel