GIS-based mapping of air pollution exposure and health effects in industrial area of Kuantan, Pahang, Malaysia: A pilot study
DOI:
https://doi.org/10.15282/cst.v5i1.13255Keywords:
Air pollution, Industrial, Health, GIS, Urban, Well-beingAbstract
Serious health concerns in developing regions are largely driven by air pollution. The Malaysian Department of Environment has measured that air pollution in industrial areas is much greater than in other areas of the country. This pilot study intends to evaluate outdoor air quality and human health effects in the industrial area of Kuantan. Two Continuous Air Quality Monitoring Stations situated in Balok and Indera Mahkota were chosen to explore how air quality varies across different areas of Kuantan. A structured questionnaire was distributed to residents living nearby, aiming to collect information on any health issues they may be experiencing. The spatial distribution of air pollution was mapped using Geographic Information System (GIS), allowing for a clearer understanding of how these pollutants relate to the health symptoms reported by the local population. The findings revealed that concentrations of PM10, PM2.5, and SO₂ were significantly higher in Balok compared to Indera Mahkota, while NO₂ levels were an exception to this trend. These differences are likely tied to variations in land use between the two areas, which appear to have a strong influence on local air pollution levels. The findings support targeted health actions and better urban planning to protect public well-being.
References
[1] M.A. Adman, J.H. Hashim, M.R. A. Manaf, and D. Norbäck, “Associations between air pollutants and peak expiratory flow and fractional exhaled nitric oxide in students,” The International Journal of Tuberculosis and Lung Disease, vol. 24, no. 2, pp. 189–195, 2020.
[2] N. Aziz, M.A. Adman, N.S. Suhaimi, S. Misbari, A.R. Alias, A.A. Aziz, et al., “Indoor air quality (IAQ) and related risk factors for sick building syndrome (SBS) at the office and home: A systematic review,” IOP Conference Series: Earth and Environmental Science, vol. 1140, no. 1, p. 012007, 2023.
[3] N.A.M. Aziz Nasatioun, M.A. Adman, N. Aziz, and S. Misbari, “Distribution mapping of house type, house age and sick building syndrome among work-from-home workers by using a GIS-based approach,” MAEH Journal of Environmental Health, vol. 5, no. 1, pp. 16–18, 2023.
[4] Q.A. Udin, A. Kasim, H. Rassa, and A.U.H. Abdul Nasir, “Factors that contribute to air pollution in Malaysia,” Malaysian Journal of Business and Economics, vol. 8, no. 2, pp. 43–58, 2021.
[5] N. Aziz, N. K. Paramjothy, M.A. Adman, S. Misbari, and L. F. Lee, “Distribution mapping of building classification and air pollution exposure in the urban city areas by using GIS-based application: A pilot study,” Construction, vol. 4, no. 2, pp. 269–277, 2024.
[6] S. A. Rajper, S. Ullah, and Z. Li, “Exposure to air pollution and self-reported effects on Chinese students: A case study of 13 megacities,” PLoS ONE, vol. 13, no. 3, p. e0194364, 2018.
[7] N. Talib, N.A.M. Sa’aidi, R.H. Narashid, N.A.M. Zaki, N.M. Saad, S. Abdullah, et al., “Relationship between particulate matter (PM₂.₅) concentration and aerosol optical depth (AOD) throughout Peninsular Malaysia,” IOP Conference Series: Earth and Environmental Science, vol. 1019, no. 1, p. 012017, 2022.
[8] A.F. Hayani, M.A. Adman, S. Misbari, and N. Aziz, “Distribution mapping of air pollutant exposure and green spaces in the Kuantan city centre by utilizing the GIS application,” AIP Conference Proceedings, vol. 3266, no. 1, p. 090001, 2025.
[9] H. Mohd Nor, A. Z. Aris, and C. H. Lim, “Particulate matter exposure and health risks in urban Malaysia: Current trends and mitigation strategies,” Environmental Science and Pollution Research, vol. 28, no. 7, pp. 8562–8573, 2021.
[10] N. F. Sulaiman, R. Mohd Zin, and M. Ismail, “Spatial-temporal distribution of PM₁₀ concentration in Klang Valley using GIS interpolation techniques,” Environmental Earth Sciences, vol. 78, no. 15, p. 451, 2019.
[11] L. Gómez-Plata, D. Agudelo-Castañeda, M. Castillo, and E.C. Teixeira, “PM₁₀ source identification: A case of a coastal city in Colombia,” Aerosol and Air Quality Research, vol. 22, no. 10, p. 210293, 2022.
[12] N.M. Hamdan, H. Alawadhi, and M. Shameer, “Physicochemical characterization and seasonal variations of PM₁₀ aerosols in a harsh environment,” Frontiers in Environmental Science, vol. 9, p. 666678, 2021.
[13] J. Linda, J. Pospíšil, K. Köbölová, R. Ličbinský, J. Huzlík, and J. Karel, “Conditions affecting wind-induced PM₁₀ resuspension as a persistent source of pollution for the future city environment,” Sustainability, vol. 14, no. 15, p. 9186, 2022.
[14] Y. Wang, X. Jin, M. Li, J. Gao, X. Zhao, J. Ma, et al., “PM₂.₅ increases systemic inflammatory cells and associated disease risks by inducing NRF2-dependent myeloid-biased hematopoiesis in adult male mice,” Environmental Science & Technology, vol. 57, no. 21, pp. 7924–7937, 2023.
[15] W. Sun, J. Huo, Q. Fu, Y. Zhang, and X. Lin, “Influence of meteorological factors and chemical processes on the explosive growth of PM₂.₅ in Shanghai, China,” Atmosphere, vol. 13, no. 7, p. 1068, 2022.
[16] X. Xu, K. Shi, Z. Huang, and J. Shen, “What factors dominate the change of PM₂.₅ in the world from 2000 to 2019? A study from multi-source data,” International Journal of Environmental Research and Public Health, vol. 20, no. 3, p. 2282, 2023.
[17] Z. Miao, S. Liu, and X. Chen, “Driving factors and spatio-temporal features underlying industrial SO₂ emissions in ‘2+26’ in North China and extended cities,” Chinese Journal of Population, Resources and Environment, vol. 18, no. 4, pp. 296–318, 2020.
[18] P.S. Rickly, H. Guo, P. Campuzano-Jost, J.L. Jimenez, G.M. Wolfe, R. Bennett, et al., “Emission factors and evolution of SO₂ measured from biomass burning in wildfires and agricultural fires,” Atmospheric Chemistry and Physics, vol. 22, no. 23, pp. 15603–15620, 2022.
[19] K.M.A. Islam, M.S.G. Adnan, K.E. Zannat, and A. Dewan, “Spatiotemporal dynamics of NO₂ concentration with linear mixed models: A Bangladesh case study,” Physics and Chemistry of the Earth, Parts A/B/C, vol. 126, p. 103119, 2022.
[20] T. Turek and J.A. Kamińska, “NO₂ concentration modelling using meteorological and traffic features,” in Proceedings of the CSEE 2022 Conference, AVESTIA, 2022.
[21] V. Lambey and A.D. Prasad, “Sensor-based real-time air pollutants monitoring for an urban industrial area,” Journal of Air Pollution and Health, vol. 8, no. 2, 2023.
[22] L. Abecasis, C.A. Gamelas, A.R. Justino, I. Dionísio, N. Canha, Z. Kertesz et al., “Spatial distribution of air pollution, hotspots and sources in an urban-industrial area in the Lisbon Metropolitan Area, Portugal—A biomonitoring approach,” International Journal of Environmental Research and Public Health, vol. 19, no. 3, p. 1364, 2022.
[23] Y. Tian, X. Yao, and L. Chen, “Analysis of spatial and seasonal distributions of air pollutants by incorporating urban morphological characteristics,” Computers, Environment and Urban Systems, vol. 75, pp. 35–48, 2019.
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