Variation of Surface Ozone Recorded at the Eastern Coastal Region of the Malaysian Peninsula

Abstract

Problem statement:Variations of ozone (O 3 ) concentrations in the Eastern Coastal Region of the Malaysia peninsula were investigated using data obtained from the Malaysian Department of the Environment. The aim of this study was to determine the monthly and seasonal variations of ozone concentrations at all monitoring sites. This study deals with the air quality data recorded at four air quality monitoring stations in the East Coast of the Malaysian peninsula over a ten year period (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006). Approach: We focused on the usage of S-Plus and SPSS to analyze this data. The S-Plus programming was used to impute missing data and SPSS was used to obtain the variations of ozone and also to clarify the relationship between stations. Results: Over the entire 10 year period (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006), the trend in annual baseline ozone generally increased each year for all the four monitoring sites. There was also a seasonal variability in the measured ozone levels with high concentrations during the southwest monsoon and the northeast monsoon season, producing a significant increase in the amplitude of the seasonal cycle. The results also shown that the highest ozone concentrations were recorded at the Bukit Kuang air monitoring station (S1), with a daily mean value of 19 ppb followed by the Indera Mahkota air monitoring station (S2). The concentration of ozone recorded at Kota Bharu (S3) and Kuala Terengganu (S4), two stations located in the city centre, was found to be lower than the values recorded at Bukit Kuang and Indera Mahkota. The correlation between O 3 and NO is high at Kuala Terengganu (S4) (ρ = -0.579), whilst the relationship between O 3 and NO 2 are high (ρ = -0.397) at Indera Mahkota (S2). Conclusion: The concentration of ozone in the East Coast of Malaysian peninsula depends on the concentration of NOx and seasonal meteorological factors.

Seasonal Variation of Criteria Pollutant in an Urban Coastal Environment: Kuala Terengganu

“…For NEM, PC1 (52.6% of the total variance) was loaded with windspeed, relative and humidity and O 3 which grouped all the meteorological factors in one. O 3 has shown a strong correlation with the meteorological factors [28][29][30][31][32][33][34][35] and thus, falls into the same group. The relative humidity shows a negative score which indicates increasing relative humidity brings negative contributions towards PM 10 concentration as high water vapor content in the air provides washing effects which reduce the amount of particles in the atmosphere [36][37].…”

Performance of Bayesian Model Averaging (BMA) for Short-Term Prediction of PM10 Concentration in the Peninsular Malaysia

“…In Kota Bharu, the agricultural and industrial park Pengkalan Chepa is the main use of land. Vehicle emissions from nearby major roads have the biggest effects on the Kota Bharu monitoring station during morning and late afternoon rush hours [61,62]. Jerantut, the background station, is located in the center of Peninsular Malaysia.…”

Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System

“…Several pollutants affecting air quality are of major concern in developed countries, especially in urban region, including carbon monoxide (CO), nitrogen dioxide (NO 2 ) and secondary pollutants such as ozone (O 3 ) [3]. In Malaysia these gas pollutants are usually found at significantly high concentrations over urban areas such as the Klang Valley, as reported by Latif et al, Banan et al, Ahamad et al and Ismail et al [4,5,6,7]. In line with these findings, it is important for local authorities to continuously monitor these pollutants.…”