Annual and Diurnal Trend of Surface Ozone (O₃) in Industrial Area

Abstract

Malaysia is a developing country that facing air pollution issues due to industrialization, urbanization activities and population growth. Ozone (O3) is one of the pollutants that can give adverse effects to human health either in long- term or short-term effect. Moreover, it also can interrupt the normal ecosystem and cause extinction in species. This study aims to analyse the annual trends of the concentration of ozone (O3) level for 3-year and the diurnal trends of ozone at Kemaman, Terengganu. One-way Analysis of Variance (ANOVA) revealed that there exists statistically significant different (p<0.05) of O3 concentrations during year 2012-2014. Meanwhile, diurnal trend showed the lowest O3 concentration values in the morning and the highest average concentration values of O3 in the noon, but it starts to decrease gradually in evening and night. The understanding of the ozone trend, yearly and hourly, can helps in tackling the atmospheric pollution problems due to industrialization in Malaysia.

Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms

“…Extreme Gradient Boosting package (XGBoost) is an effective and sophisticated enforcement of the gradient boosting framework (Melville, 2014). XGBoost is a very operative and excessively utilized machine learning approach that analysts massively apply to obtain desirable results on challenges of various machine learning.…”

“…Nowadays, air pollution has been increasing due to anthropogenic activities which are considered among the most world's highlights obstacles. Air pollution typically sources are land transportation, open burning, and industrial emission (Mohd Napi et al, 2020). In Malaysia, air quality, since 1970, was decline, and no countermeasures have been initiated (Afroz et al, 2003).…”

Different Approaches of Multiple Linear Regression (MLR) Model in Predicting Ozone (O3) Concentration in Industrial Area

“…The yearly trend in O3 concentrations during a five-year period of data from an industrial location on Peninsular Malaysia's east coast has changed throughout the years [34]. Fig2 illustrates the fluctuated trends of O3 concentration according to the percentiles 0%, 25%, 50%, 75%, and 100%.…”

Characteristics and source profiles of atmospheric volatile organic compounds (VOCs) in the heavy industrial province of Northeast China with cruise monitoring

“…The formation of ground-level O 3 is inseparable from its precursor, volatile organic compounds (VOCs) and nitrogen oxides (NO x ) (Ma et al, 2016). Due to the complex chemical mechanism of VOCs Yan et al, 2019;Mohd Napi et al, 2020) and the non-linear relationships between O 3 concentrations and precursors (Xing et al, 2011), the control of O 3 pollution poses a significant challenge. Thus, a deep understanding of VOCs is necessary to develop corresponding strategies for O 3 pollution in different regions.…”