Spatio-temporal assessment of nocturnal surface ozone in Malaysia

Yusoff, Mohd.; Latif, Mohd Talib; Juneng, Liew; Khan, Firoz; Ahamad, Fatimah; Chung, Jing Xiang; Mohtar, Anis Asma Ahmad

doi:10.1016/j.atmosenv.2019.03.023

Cited by 28 publications

(14 citation statements)

References 33 publications

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“…After sunset, the intensity of solar radiation decreases, resulting in weak photochemical intensity and ultimately a reduction in O 3 concentration. (Faridi et al, 2018;Yusoff et al, 2019). After nightfall, O 3 concentration continues to decrease due to the NO titration effect (Xu et al, 2019) and reaches a minimum before sunrise (7:00) the next day.…”

Section: Analysis Of Ozone Variabilitymentioning

confidence: 99%

Diurnal and inter-annual variability of surface ozone in Baicheng region, China

Ting-ting

et al. 2021

Tellus B: Chemical and Physical Meteorology

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With the rapid development of industry and economy, the problem of ozone (O 3) pollution in China is of increasing concern in recent years. The problem of ozone pollution has become worse in Baicheng City which belongs to the province of Jilin. We analyze the spatial and temporal distribution of surface ozone and its correlation with precursors and meteorological factors during 2015 and 2019 using data from the automatic Atmospheric Environmental Quality Monitoring Station located in Baicheng. Results showed that the daily and monthly mean values of O 3 concentration were both single-peak patterns, and interannual variation presented a inverted 'V' pattern in Baicheng. The high concentration of O 3 in a year generally occurs from May to July, with the highest daily concentration occurring in the afternoon. The total number of days with O 3 concentration exceeding the limits was 35 days from 2015 to 2019, among which the number of days exceeding the maximal daily average eight-hour (MDA8) O 3 of 100 lg/m 3 was the highest in 2018, and the 90th percentile MDA8 showed an overall growth pattern. Seasonal variations in O 3 concentration in 2018 and 2019 were not consistent with the three previous years.

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Section: Analysis Of Ozone Variabilitymentioning

confidence: 99%

Diurnal and inter-annual variability of surface ozone in Baicheng region, China

Ting-ting

et al. 2021

Tellus B: Chemical and Physical Meteorology

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“…The minima occurred at 8.00 a.m at all stations. Several recent studies exhibit that O 3 exhibits strong diurnal variations [8], [15]- [17] at different locations. Day time surface ozone [18] and nocturnal surface ozone [17] variations depending on its precursors and meteorological conditions.…”

Section: B Diurnal Variationsmentioning

confidence: 98%

“…The monthly diurnal variation analysis revealed the second peaks of surface ozone during night time happened at more than 50% of all CAQMS occurring around 3.00 a.m. to 5.00 a.m and the ratio mean of nighttime to daytime ozone concentration was the highest in the east coast region and lowest in the central region while the other regions were in average. This could explain the highest is due to horizontal transport while the lowest is due to titration [17].…”

Section: Fig 3: Composite Diurnal Plot Of O 3 No and No 2 Concentrmentioning

confidence: 99%

Trends of Transformation Characteristics of Ground-Level Ozone in Urban Peninsular Malaysia

2019

IJRTE

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Ozone (O3 ) is the second prominent air pollution in Malaysia. The annual variation of ozone concentration depends upon several conditions such as the sources of its precursor, the land use type and meteorological parameter. This study aims to understand the trends and issues of transformation characteristics of O3 in 4 urban area (Shah Alam, Kajang, Johor Bahru and Kota Bharu) during specific critical conversion time (CCT) as well as to introduce the critical transformation time (CTT) of O3 in 4 selected continuous air quality monitoring stations (CAQMS) from the year 2000 to 2011. The identification of CTT for O3 formation was identified occurring between 8.00 a.m and 11.00 a.m., and the O3 uni-modal peaks usually after CTT at approximately between 12.00 p.m and 4.00 p.m. The results indicated that the CTT of O3 in the Kota Bharu is slightly earlier occurring between 8.00 a.m to 10.00 a.m whereas Shah Alam, Kajang and Johor Bahru the CTT later occurring between 10.00 a.m to 11.00 a.m. Only Kota Bharu recorded data was below 100 part per billion volume (ppbv), while Shah Alam, Kajang and Johor have recorded exceedances above 100 ppbv. This research elucidates that CTT is adequate to control ozone concentration. Ozone might exceed Recommended Ambient Air Quality Guideline (RMAAQC) unless nitrogen emissions are adequately managed, due to the detrimental effects for those who are at risk of respiratory health problems resulting from air pollution.

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“…Finally, in the nighttime and early morning, human activities are reduced. Consequently, the emission of NOx drops, stabilizing the chemistry of the atmosphere generating no net production or destruction of O3 (Yusoff et al, 2019).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Hourly Ozone and PM2.5 Prediction Using Meteorological Data – Alternatives for Cities with Limited Pollutant Information

Cifuentes

Galvez

González

et al. 2021

Aerosol Air Qual. Res.

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Using statistical models, the average hourly ozone (O3) concentration was predicted from seven meteorological variables (Pearson correlation coefficient, R = 0.87 -0.90), with solar radiation and temperature being the most important predictors. This can serve to predict O3 for cities with real time meteorological data but no pollutant sensing capability. Incorporating other pollutants (PM2.5, SO2, and CO) into the models did not significantly improve O3 prediction (R = 0.91 -0.94). Predictions were also made for PM2.5, but results could not reflect its peaks and outliers resulting from local sources. Here we make a comparative analysis of three different statistical predictor models: (1) Multiple Linear Regression (MLR), (2) Support Vector Regression (SVR), and (3) Artificial Neuronal Networks (ANNs) to forecast hourly O3 and PM2.5 concentrations in a mid-sized Andean city (Manizales, Colombia). The study also analyzes the effect of using different sets of predictor variables: (1) Spearman coefficients higher than ± 0.3, (2) variables with loadings higher than ± 0.3 from a principal component analysis (PCA), (3) only meteorological variables, and (4) all available variables. In terms of the O3 forecast, the best model was obtained using ANNs with all the available variables as predictors. The methodology could serve other researchers for implementing statistical forecasting models in their regions with limited pollutant information.

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Spatio-temporal assessment of nocturnal surface ozone in Malaysia

Cited by 28 publications

References 33 publications

Diurnal and inter-annual variability of surface ozone in Baicheng region, China

Diurnal and inter-annual variability of surface ozone in Baicheng region, China

Trends of Transformation Characteristics of Ground-Level Ozone in Urban Peninsular Malaysia

Hourly Ozone and PM2.5 Prediction Using Meteorological Data – Alternatives for Cities with Limited Pollutant Information

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