The assessment of particulate matter 10 [PM10] functional data at Klang and Shah Alam monitoring stations / Engku Nurul Adlin Engku Zainal Abidin

Engku Zainal Abidin, Engku Nurul Adlin (2021) The assessment of particulate matter 10 [PM10] functional data at Klang and Shah Alam monitoring stations / Engku Nurul Adlin Engku Zainal Abidin. [Student Project] (Unpublished)

Abstract

Air pollution in Malaysia is becoming a major environmental issue due to the rising number of vehicles, open burning, and the release of toxic chemicals. PM10 is a dangerous air pollutant with the capability to negatively affect human health and the surrounding environment. PM10 contamination is intangible and odourless, so its presence in the atmosphere is unnoticeable and often neglected. The occurrence of a high concentration of an abnormal pollutant is more simply known as an anomaly and may describe problems of air quality. Thus, this study was carried out to assess the functional curve of PM10 behaviour in Shah Alam and Klang and also to detect the anomaly in PM10 functional data. The statistical method used in this study is Functional Data Analysis combined with the robust Mahalanobis distance to detect the anomalies using air quality data recorded from 2014 to 2016 in an hourly interval. The Bayesian Information Criteria is used to determine the number of basis functions, K. Based on the anomalies that has been detected, it showed that Klang is more polluted compared to Shah Alam. The maximum level of anomalies was observed during a twenty-four hour period. In conclusion, the detection of anomaly was found useful in investigating air pollution in this study. The findings of this study imply that the location and background of a station play a significant role in influencing the anomalies of PM10.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Engku Zainal Abidin, Engku Nurul Adlin
2017987687
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
T Technology > TD Environmental technology. Sanitary engineering > Air pollution and its control
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons.) Management Mathematics
Keywords: Functional Data Analysis ; PM10 Functional Data ; Basis Function ; Anomaly Detection
Date: 24 March 2021
URI: https://ir.uitm.edu.my/id/eprint/44175
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