Temporal Characterisation of Ground-level Ozone Concentration in Klang Valley

Hashim, Nur Izzah Mohamad; Noor, Norazian Mohamed; Yusof, Sara Yasina

doi:10.1051/e3sconf/20183402047

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…x~GEV μ(t),σ,ξ where μ(t) = β + β t (3) This model is considered as linear trend in the location parameter, μ . The parameter 0  corresponds to mean value while 1  is the weekly rate of change in weekly maxima of GLO data.…”

Section: Extreme Value Theory (Evt)mentioning

confidence: 99%

“…Extreme ground-level ozone (GLO) in this study refers to the maximum value of GLO concentration in a specific period of time such as yearly, monthly, biweekly or weekly. Higher concentrations will adversely affect human health, indirectly affect the efficiency of photosynthesis in plants as well as other activities in the ecosystem as mentioned in several literatures [1]- [3]. Therefore, continuous monitoring for GLO trends is important to ensure that the level of ozone concentration does not exceed the standard recommendation stated by the National Ambient Air Quality Standard (NAAQS) and Malaysia Ambient Air Quality Standard (MAAQS).…”

Section: Introductionmentioning

confidence: 99%

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Stationary and Non-Stationary Models of Extreme Ground-Level Ozone in Peninsular Malaysia

Zakaria¹,

Amin²,

Radi³

et al. 2021

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High ground-level ozone (GLO) concentrations will adversely affect human health, vegetations as well as the ecosystem. Therefore, continuous monitoring for GLO trends is a good practice to address issues related to air quality based on high concentrations of GLO. The purpose of this study is to introduce stationary and non-stationary model of extreme GLO. The method is applied to 25 selected stations in Peninsular Malaysia. The maximum daily GLO concentration data over 8 hours from year 2000 to 2016 are used. The factors of this distribution are anticipated using maximum likelihood estimation. A comparison between stationary (constant model) and non-stationary (linear and cyclic model) is performed using the likelihood ratio test (LRT). The LRT is based on the larger value of deviance statistics compared to a chi-square distribution providing the significance evidence to non-stationary model either there is linear trend or cyclic trend. The best fit model between selected models is tested by Akaike's Information Criterion. The results show that 25 stations conform to the non-stationary model either linear or cyclic model, with 14 stations showing significant improvement over the linear model in location parameter while 11 stations follow the cyclic model. This study is important to identify the trends of ozone phenomenon for better quality risk management.

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Section: Extreme Value Theory (Evt)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stationary and Non-Stationary Models of Extreme Ground-Level Ozone in Peninsular Malaysia

Zakaria¹,

Amin²,

Radi³

et al. 2021

View full text Add to dashboard Cite

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Transformational characteristics of ground-level ozone during high particulate events in urban area of Malaysia

Awang

Ramli

Shith

et al. 2018

Air Qual Atmos Health

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Observations of ground-level ozone (O 3), nitric oxide (NO), nitrogen dioxide (NO 2), particulate matter (PM 10) and meteorological parameter (temperature, relative humidity and wind speed) fluctuations during high particulate event (HPE) and non-HPE in Malaysia have been conducted for 2 years (2013 and 2014). The study focuses on urban areas, namely, Shah Alam, Petaling Jaya and Bandaraya Melaka. The diurnal variations of ground-level O 3 concentration were higher during HPE than those during non-HPE in all urban areas. The concentration of O 3 fluctuated more in 2014 than 2013 due to the higher incidences of HPE. Temperature and wind speed fluctuated with higher PM 10 , NO 2 and NO concentrations during HPE than those during non-HPE in all urban sites. Relative humidity was lower during HPE than that during non-HPE. Positive correlations were found between PM 10 and ozone during HPE for Shah Alam and Petaling Jaya with 0.81 and 0.79, respectively. Meanwhile, negative correlation (− 0.76) was recorded for Bandaraya Melaka. The non-HPE correlation of PM 10 and O 3 showed negative values for all locations except Petaling Jaya (0.02). Temperature and wind speed shows a strong positive correlation with ozone for all locations during HPE and non-HPE with the highest at Shah Alam (0.97). Inverse relationships were found between relative humidity and O 3 , in which the highest was for Shah Alam (− 0.96) in 2013 and Shah Alam (− 0.97) and Bandaraya Melaka (− 0.97) in 2014. The result of the ozone best-fit equation obtained an R 2 of 0.6730. The study parameters had a significant positive relationship with the ozone predictions during HPE.

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Surface Ozone and its Precursor Gases Concentrations during COVID-19 Lockdown and Pre-Lockdown Periods in Hyderabad City, India

et al. 2021

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Graphical abstract Drastic measures such as lockdown imposed in the countries worldwide to control the extent of COVID-19 have influenced environmental parameters substantially. The aim of the present study was to investigate the impact of lockdown on the air quality in Hyderabad city by comparing the pollutants concentration during lockdown and pre-lockdown periods. A comparative study was also made on the pollutant concentrations observed during the pre-lockdown (1st February – 23rd March 2020) and lockdown period (24th March - 30th April 2020) to those of the pollutants in the previous years (2018 and 2019). The Pearson correlation coefficient was employed to correlate the ozone (O 3 ) concentration with other pollutants. Carbon monoxide (CO), nitrogen oxides (NO X ) and O 3 were monitored along with meteorological parameters like temperature, relative humidity and solar radiation. It was observed that the O 3 concentration increased from 26 ppb (by volume) to 56.4 ppb during pre-lockdown and lockdown period, respectively, due to the decrease in CO and NO X concentration. The concentration of NO 2, NO and CO were also reduced during the lockdown period by 33.7%, 53.8% and 27.25%, respectively. To identify the statistical significance of the parameters, analysis of variance (ANOVA) was used. The present study provides new insights on the ambient air pollution in terms of the aforesaid parameters and could pave the way for regulatory authorities to implement control measures to curb the air pollution. Highlights • COVID-19 lockdown improved the air quality by the reduction in air pollutants leading to increased ozone concentration. • Pearson model was used to correlate the ozone (O 3 ) with oxides of nitrogen (NO X ), CO and other meteorological parameters. • NO X and carbon monoxide (CO) concentrations were reduced by 33.7 % and 27.25 %, respectively, due to COVID lockdown.

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Temporal Characterisation of Ground-level Ozone Concentration in Klang Valley

Cited by 4 publications

References 8 publications

Stationary and Non-Stationary Models of Extreme Ground-Level Ozone in Peninsular Malaysia

Stationary and Non-Stationary Models of Extreme Ground-Level Ozone in Peninsular Malaysia

Transformational characteristics of ground-level ozone during high particulate events in urban area of Malaysia

Surface Ozone and its Precursor Gases Concentrations during COVID-19 Lockdown and Pre-Lockdown Periods in Hyderabad City, India

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