Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/22750
Title: MODELLING OF SICK BUILDING SYNDROME (SBS) SYMPTOMS AND INDOOR AIR QUALITY (IAQ) ACROSS DOMINANT SUB-ECONOMIES IN TERENGGANU: A STUDY OF MONSOONAL VARIATIONS
Authors: AMALINA BINTI ABU MANSOR
Keywords: SICK BUILDING SYNDROME (SBS) SYMPTOMS
INDOOR AIR QUALITY (IAQ)
DOMINANT SUB-ECONOMIE
MONSOONAL VARIATIONS
Issue Date: 2025
Publisher: Universiti Malaysia Terengganu
Abstract: Optimum indoor air quality (IAQ) is crucial for maintaining a healthy work environment. This study examines the effects of IAQ on Sick Building Syndrome (SBS) symptoms across various economic subsectors during the monsoonal seasons in Terengganu, Malaysia. Four locations representing the education (S1), wholesale or retail trade (S2), manufacturing (S3), and services (S4) subsectors were assessed. IAQ was measured using ventilation indicators (carbon dioxide, CO2), chemical parameters (formaldehyde (HCHO), total volatile organic compounds (TVOC), and carbon monoxide (CO)), and physical parameters (temperature, relative humidity, air movement) during the Southwest Monsoon (SWM) and Northeast Monsoon (NEM). The objectives included evaluating IAQ compliance, simulating 3D distributions using Computational Fluid Dynamics (CFD), identifying IAQ factors through Principal Component Analysis (PCA), and developing predictive Generalized Linear Models (GLM). Data included SBS symptom feedback and IAQ metrics, analysed using GLM with SBS syptoms as the dependent variable. Results showed seasonal IAQ variations, with temperatures ranging from 23.50°C to 32.91°C and relative humidity from 57.77% to 90.68%. CO2 levels were higher in enclosed spaces, particularly in manufacturing and retail sectors during the SWM. CFD simulations revealed increased turbulence near ventilation systems, with accuracies of up to 91.90% (SWM, S1) and 91.17% (NEM, S4). PCA identified three main IAQ contributors: physical conditions, chemical exposure, and human activities, accounting for up to 45.58% (NEM, S3), 24.17% (SWM, S3), and 31.42% (SWM, S4) of variance. The GLM demonstrated higher predictive accuracy during the NEM, with an R2 of up to 0.9949. Seasonal variations in IAQ significantly impacted SBS symptoms across different economic sectors in Terengganu, Malaysia. Poor IAQ, driven by physical conditions, chemical exposures, and human activities, was found to be worse during the SWM. The study recommends improving ventilation in enclosed spaces, regularly monitoring IAQ to address seasonal changes, reducing chemical emissions, controlling indoor activities, and enforcing IAQ compliance to create healthier work environments.
URI: http://umt-ir.umt.edu.my:8080/handle/123456789/22750
Appears in Collections:Institut Akuakultur Tropika

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