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The Influence of Spatial Variability of Critical Conversion Point (CCP) in Production of Ground Level Ozone in the Context of Tropical Climate

Category: Urban Air Quality

Volume: 16 | Issue: 1 | Pages: 153-165
DOI: 10.4209/aaqr.2015.04.0225
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Norrimi Rosaida Awang, Maher Elbayoumi , Nor Azam Ramli, Ahmad Shukri Yahaya

  • Clean Air Research Group, School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia


High variability in critical conversion point (CCP) was observed.
Critical conversion time (CCT) for O3 formation occurred from 8:00 a.m. to 11:00 a.m.
Spatial variation in O3 level during CCT due to meteorological variables.
Decreasing NO titration rate accelerate the formation of CCP.


Critical conversion point (CCP) is a very crucial step in production of the ground level O3 chemistry. Thus, a multivariate analysis was applied on the dataset of nine selected locations in Malaysia from 1999 to 2010. It incorporated hierarchical agglomerative cluster analysis (HACA) to explore the spatial variability of CCP and principal component analysis (PCA) to determine the major sources of the air pollutants that influence ozone CCP. High variability in CCP was observed between the monitoring stations that occurred during critical conversion time (CCT) from 8:00 a.m. to 11:00 a.m. The HACA results grouped the nine monitoring stations into three different clusters, based on the characteristics of ozone concentrations during CCT period. Results of PCA for the three clusters showed that the contributions to O3 level variation during CCT by meteorological variables (UVB, temperature, relative humidity, and wind speed) are higher at 51.6%, 48.5%, and 33.3% than that of primary air pollutants (NO2, SO2, PM10) at 19.2%, 21.4%, and 15.2% for cluster 1, cluster 2, and cluster 3, respectively. Therefore, applying a targeted spatial control strategy for ground level O3 precursors during the CCT period is a crucial step.


NO2 photolysis NO titration Critical conversion point Multivariate analysis

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