Development of Ozone prediction model in urban area
One of the main challenges for countries in tropical area such as Malaysia is the high concentration of ozone (O3) caused by elevated levels of anthropogenic and natural ozone precursors. In this study, variation of O3 concentrations in urban area (Klang) was investigated using data covering three-y...
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2023
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my.uniten.dspace-245372023-05-29T15:24:20Z Development of Ozone prediction model in urban area Abdullah S. Nasir N.H.A. Ismail M. Ahmed A.N. Jarkoni M.N.K. 56509029800 57210571494 57210403363 57214837520 57202203768 One of the main challenges for countries in tropical area such as Malaysia is the high concentration of ozone (O3) caused by elevated levels of anthropogenic and natural ozone precursors. In this study, variation of O3 concentrations in urban area (Klang) was investigated using data covering three-year period (2012�2015) on hourly basis. Result shows that the diurnal cycle of ozone concentration has a mid-day peak (1400hrs) while lower concentration occurs at night time (2100hrs) as it titrates nitrogen dioxide (NO2). There exists statistically significant difference (p<0.05) of O3 concentration at study areas. Moderate Spearman correlation coefficient was evaluated between O3 and NO2 (r=0.45, p<0.05). Multiple linear regression (MLR) model was developed and signifies that nitrogen oxides (NO), relative humidity (RH), NO2, carbon monoxide (CO), wind speed (WS), temperature (T) and sulphur dioxide (SO2) are the significant predictors for O3 concentration. This study suggests that the emission of O3 precursors, particularly NOx from motor vehicles, needs to be controlled to reduce the incidence of high O3 levels in Malaysia. � BEIESP. Final 2023-05-29T07:24:20Z 2023-05-29T07:24:20Z 2019 Article 10.35940/ijitee.J1127.0881019 2-s2.0-85070968600 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070968600&doi=10.35940%2fijitee.J1127.0881019&partnerID=40&md5=bde65022101e7a2d45a054ae1f5d8e73 https://irepository.uniten.edu.my/handle/123456789/24537 8 10 2263 2267 All Open Access, Bronze Blue Eyes Intelligence Engineering and Sciences Publication Scopus |
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One of the main challenges for countries in tropical area such as Malaysia is the high concentration of ozone (O3) caused by elevated levels of anthropogenic and natural ozone precursors. In this study, variation of O3 concentrations in urban area (Klang) was investigated using data covering three-year period (2012�2015) on hourly basis. Result shows that the diurnal cycle of ozone concentration has a mid-day peak (1400hrs) while lower concentration occurs at night time (2100hrs) as it titrates nitrogen dioxide (NO2). There exists statistically significant difference (p<0.05) of O3 concentration at study areas. Moderate Spearman correlation coefficient was evaluated between O3 and NO2 (r=0.45, p<0.05). Multiple linear regression (MLR) model was developed and signifies that nitrogen oxides (NO), relative humidity (RH), NO2, carbon monoxide (CO), wind speed (WS), temperature (T) and sulphur dioxide (SO2) are the significant predictors for O3 concentration. This study suggests that the emission of O3 precursors, particularly NOx from motor vehicles, needs to be controlled to reduce the incidence of high O3 levels in Malaysia. � BEIESP. |
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56509029800 |
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56509029800 Abdullah S. Nasir N.H.A. Ismail M. Ahmed A.N. Jarkoni M.N.K. |
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Article |
| author |
Abdullah S. Nasir N.H.A. Ismail M. Ahmed A.N. Jarkoni M.N.K. |
| spellingShingle |
Abdullah S. Nasir N.H.A. Ismail M. Ahmed A.N. Jarkoni M.N.K. Development of Ozone prediction model in urban area |
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Abdullah S. |
| title |
Development of Ozone prediction model in urban area |
| title_short |
Development of Ozone prediction model in urban area |
| title_full |
Development of Ozone prediction model in urban area |
| title_fullStr |
Development of Ozone prediction model in urban area |
| title_full_unstemmed |
Development of Ozone prediction model in urban area |
| title_sort |
development of ozone prediction model in urban area |
| publisher |
Blue Eyes Intelligence Engineering and Sciences Publication |
| publishDate |
2023 |
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1806426486110945280 |
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