2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques
| Format: | General Document |
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| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 |
| copyright | Copyright©PWB2025 |
| country | Malaysia |
| date | 2019-01-20 |
| format | General Document |
| id | 15333 |
| institution | UniSZA |
| internalnotes | Sila masukkan subject wajib Dissertations, Academic. Terima kasih... |
| originalfilename | 15333_9be872bbda3915f.pdf |
| person | Ku Mohd Kalkausar Bin Ku Yusof |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15333 |
| sourcemedia | Server storage Scanned document |
| spelling | 15333 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15333 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 General Document Malaysia Library Staff (Top Management) Library Staff (Management) Library Staff (Support) Terengganu Faculty of Bio-resources & Food Industry English application/pdf 1.5 Server storage Scanned document Universiti Sultan Zainal Abidin UniSZA Private Access Universiti Sultan Zainal Abidin SAMBox 2.3.4; modified using iTextSharp™ 5.5.10 ©2000-2016 iText Group NV (AGPL-version) 284 2019-01-20 15333_9be872bbda3915f.pdf 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques Ku Mohd Kalkausar Bin Ku Yusof Air Quality Haze Episodes Air Quality Assessment Multivariate Techniques Copyright©PWB2025 The frequent haze occurrences in Malaysia have caused various problems including health, economy, transportation and etc. Haze issues were actively debated when it was happening, however it was deserted once the haze has diminished. In order to have a better understanding on these issues, three main objectives were stated in this study. Firstly was to identify the affected study area during haze occurrences, secondly was to determine the relationship between PM10 and other pollutants (including meteorological factors) and lastly to relate the pollutant apportionment influences towards PM10 variations during haze episodes. Any pollutant (including meteorological parameters) associated with PM10 (> 150 µg/m3) also selected as well in this study in order to identify the relationship during haze. This research involved the analyses of haze occurrences with PM10 more than 150 µg/m3 was selected as main criterion. All data was based on secondary air quality collected at 51 monitoring stations in Malaysia started from January 2006 until December 2015 with a total of 11 258 set of data. Descriptive statistical analysis was engaged to compare the haze occurrence status on five different zones namely Borneo, Central, Eastern, Northern and Southern. Aside descriptive study, Mann-Kendall and multivariate techniques also been incorporated in this study. As Mann-Kendall provided the trend pattern on each pollutant involved, multivariate techniques provided a better interpretation on air quality status in this study. Three multivariate techniques were chosen; Hierarchical Agglomerative Cluster Analysis (HACA), Artificial Neural Network (ANN) and Sensitivity Analysis (SA) with additional two multivariate techniques (Principal Component Regression (PCR) and Generalized Linear Model (GLM)) added to validate the ANN-SA. To achieve the first objective, HACA technique was used. The application of HACA was to cluster the monitoring station based on two situations; (1) haze frequency occurrences and (2) the concentration of PM10. HACA formed three different classes of cluster; High Risk Area (HRA), Moderate Risk Area (MRA) and Low Risk Area (LRA). On frequency description, CA0020 (Taiping), CA0027 (Bintulu), CA0011 (Klang) and CA0006 (Bukit Rambai) were inclusively considered as High Risk Area. On the other hand, on concentration perceptiveness, CA0039, CA0050, CA0004, CA0026, CA0026, CA0027, CA0028, CA0029, CA0035 and CA0016 were definitely classified as HRA. Amidst of frequency and concentration conceptual, it was only monitoring station appeared as the most affected by haze and it is located at CA0027 in Bintulu. Spearman Rank correlation test was applied in determining the relationship between PM10 and pollutant during monsoonal season. Literally, Northeast Monsoon (NEM) and Southwest Monsoon (SWM) have strongly influenced to PM10 – air pollutant relationship at eastern and Peninsula’s west coast region (northern, central and southern) respectively. The development of ANN-SA was the best approach to relate the air pollutants apportionment influences towards PM10 variability in five zones. Relatively, UVb and SO2 were the most affected by haze circumstances with UVb was the only variable that perfectly predicted by ANN SA in all five zones study area. From this research, it can be seen that multivariate techniques are practically proven as the ultimate approaches in order to solve the air quality issues especially in haze episodes in Malaysia during 2006 – 2015 periods. Dissertations, Academic Sila masukkan subject wajib Dissertations, Academic. Terima kasih... Thesis |
| spellingShingle | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| state | Terengganu |
| subject | Air Quality Dissertations, Academic |
| summary | The frequent haze occurrences in Malaysia have caused various problems including health, economy, transportation and etc. Haze issues were actively debated when it was happening, however it was deserted once the haze has diminished. In order to have a better understanding on these issues, three main objectives were stated in this study. Firstly was to identify the affected study area during haze occurrences, secondly was to determine the relationship between PM10 and other pollutants (including meteorological factors) and lastly to relate the pollutant apportionment influences towards PM10 variations during haze episodes. Any pollutant (including meteorological parameters) associated with PM10 (> 150 µg/m3) also selected as well in this study in order to identify the relationship during haze. This research involved the analyses of haze occurrences with PM10 more than 150 µg/m3 was selected as main criterion. All data was based on secondary air quality collected at 51 monitoring stations in Malaysia started from January 2006 until December 2015 with a total of 11 258 set of data. Descriptive statistical analysis was engaged to compare the haze occurrence status on five different zones namely Borneo, Central, Eastern, Northern and Southern. Aside descriptive study, Mann-Kendall and multivariate techniques also been incorporated in this study. As Mann-Kendall provided the trend pattern on each pollutant involved, multivariate techniques provided a better interpretation on air quality status in this study. Three multivariate techniques were chosen; Hierarchical Agglomerative Cluster Analysis (HACA), Artificial Neural Network (ANN) and Sensitivity Analysis (SA) with additional two multivariate techniques (Principal Component Regression (PCR) and Generalized Linear Model (GLM)) added to validate the ANN-SA. To achieve the first objective, HACA technique was used. The application of HACA was to cluster the monitoring station based on two situations; (1) haze frequency occurrences and (2) the concentration of PM10. HACA formed three different classes of cluster; High Risk Area (HRA), Moderate Risk Area (MRA) and Low Risk Area (LRA). On frequency description, CA0020 (Taiping), CA0027 (Bintulu), CA0011 (Klang) and CA0006 (Bukit Rambai) were inclusively considered as High Risk Area. On the other hand, on concentration perceptiveness, CA0039, CA0050, CA0004, CA0026, CA0026, CA0027, CA0028, CA0029, CA0035 and CA0016 were definitely classified as HRA. Amidst of frequency and concentration conceptual, it was only monitoring station appeared as the most affected by haze and it is located at CA0027 in Bintulu. Spearman Rank correlation test was applied in determining the relationship between PM10 and pollutant during monsoonal season. Literally, Northeast Monsoon (NEM) and Southwest Monsoon (SWM) have strongly influenced to PM10 – air pollutant relationship at eastern and Peninsula’s west coast region (northern, central and southern) respectively. The development of ANN-SA was the best approach to relate the air pollutants apportionment influences towards PM10 variability in five zones. Relatively, UVb and SO2 were the most affected by haze circumstances with UVb was the only variable that perfectly predicted by ANN SA in all five zones study area. From this research, it can be seen that multivariate techniques are practically proven as the ultimate approaches in order to solve the air quality issues especially in haze episodes in Malaysia during 2006 – 2015 periods. |
| title | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| title_full | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| title_fullStr | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| title_full_unstemmed | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| title_short | 2018_A Decade of Intercomparative Studies on Haze Episodes in Malaysia_ Air Quality Assessment and Prognosis Using Multivariate Techniques |
| title_sort | 2018_a decade of intercomparative studies on haze episodes in malaysia_ air quality assessment and prognosis using multivariate techniques |