Spatial and Temporal Variation of Particulate Matter (PM10 and PM2.5) and Its Health Effects during the Haze Event in Malaysia
Source: By:Afiqah Ma’amor, Norazian Mohamed Noor, Izzati Amani Mohd Jafri, Nur Alis Addiena, Ahmad Zia Ul Saufie, Nor Azrita Amin, Madalina Boboc, Gyorgy Deak
DOI: https://doi.org/10.30564/jasr.v6i4.5873
Abstract:This study aims to assess and compare levels of particulate matter (PM10 and PM2.5) in urban and industrial areas in Malaysia during haze episodes, which typically occur in the south west monsoon season. The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries. Daily PM concentrations were analysed for urban and industrial areas including Alor Setar, Tasek, Shah Alam, Klang, Bandaraya Melaka, Larkin, Balok Baru, and Kuala Terengganu in 2018 and 2019. The analysis employed spatiotemporal to examine how PM levels were distributed. The data summary revealed that PM levels in all study areas were right-skewed, indicating the occurrence of high particulate events. Significant peaks in PM concentrations during haze events were consistently observed between June and October, encompassing the south west monsoon and inter-monsoon periods. The study on acute respiratory illnesses primarily focused on Selangor. Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma (AEBA) and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with values of 260.500 and 185.170, respectively. Similarly, for outpatient cases of AEBA and AECOPD, Klang had the highest average values of 41.67 and 14.00, respectively. Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning. The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions, particularly from June to September, as shown in the bar diagram. Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses, seen in higher inpatient and outpatient visits (p < 0.05). However, seasonal variability had minimal impact on healthcare utilization. These findings offer a comprehensive assessment of PM levels during historic haze episodes, providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.
References:[1] Wu, S., Deng, F., Wang, X., et al., 2013. Association of lung function in a panel of young healthy adults with various chemical components of ambient fine particulate air pollution in Beijing, China. Atmospheric Environment. 77, 873-884. DOI: https://doi.org/10.1016/j.atmosenv.2013.06.018 [2] Wang, S., Hao, J., 2012. Air quality management in China: Issues, challenges, and options. Journal of Environmental Sciences. 24(1), 2-13. DOI: https://doi.org/10.1016/S1001-0742(11)60724-9 [3] Li, Y., Zheng, C., Ma, Z., et al., 2019. Acute and cumulative effects of haze fine particles on mortality and the seasonal characteristics in Beijing, China, 2005-2013: A time-stratified case-crossover study. International Journal of Environmental Research and Public Health. 16(13), 2383. DOI: https://doi.org/10.3390/ijerph16132383 [4] Latif, M.T., Othman, M., Idris, N., et al., 2018. Impact of regional haze towards air quality in Malaysia: A review. Atmospheric Environment. 177, 28-44. DOI: https://doi.org/10.1016/j.atmosenv.2018.01.002 [5] Mahmud, M., 2013. Assessment of atmospheric impacts of biomass open burning in Kalimantan, Borneo during 2004. Atmospheric Environment. 78, 242-249. DOI: https://doi.org/10.1016/j.atmosenv.2012.03.019 [6] Dotse, S.Q., Dagar, L., Petra, M.I., et al., 2016. Influence of Southeast Asian Haze episodes on high PM10 concentrations across Brunei Darussalam. Environmental Pollution. 219, 337-352. DOI: https://doi.org/10.1016/j.envpol.2016.10.059 [7] Wen, Y.S., bin Mohd Nor, A.F., 2016. Transboundary air pollution in Malaysia: Impact and perspective on haze. Nova Journal of Engineering and Applied Sciences. 5(1). [8] Indonesia Palm Oil Production by Year (1000 MT) [Internet]. Available from: https://www.indexmundi.com/agriculture/?country=id&commodity=palm-oil&graph=production [9] Zainal, Z., 2016. Root problem of forest fire and solutions in completion (Study in the Riauprovince). Proceedings International Conference on Social Politics. 1. [10]Forsyth, T., 2014. Public concerns about transboundary haze: A comparison of Indonesia, Singapore, and Malaysia. Global Environmental Change. 25, 76-86. DOI: https://doi.org/10.1016/j.gloenvcha.2014.01.013 [11]Jafri, I.A.M., Noor, N.M., Rahim, N.A.A.A., et al., 2023. Spatial and temporal analysis of particulate matter (PM10) in urban-industrial environment during episodic haze events in Malaysia. Environment Asia. 16(1), 111-125. DOI: https://doi.org/10.14456/ea.2023.10 [12]Pavagadhi, S., Betha, R., Venkatesan, S., et al., 2013. Physicochemical and toxicological characteristics of urban aerosols during a recent Indonesian biomass burning episode. Environmental Science and Pollution Research. 20, 2569-2578. DOI: https://doi.org/10.1007/s11356-012-1157-9 [13]Khan, M.F., Latif, M.T., Saw, W.H., et al., 2016. Fine particulate matter in the tropical environment: monsoonal effects, source apportionment, and health risk assessment. Atmospheric Chemistry and Physics. 16(2), 597-617. DOI: https://doi.org/10.5194/acp-16-597-2016 [14]Abba, E.J., Unnikrishnan, S., Kumar, R., et al., 2012. Fine aerosol and PAH carcinogenicity estimation in outdoor environment of Mumbai City, India. International Journal of Environmental Health Research. 22(2), 134-149. DOI: https://doi.org/10.1080/09603123.2011.613112 [15]Department of Environment., 2010. Air quality: Continuous Air Quality Monitoring (CAQM) [Internet]. Available from: https://www.doe.gov.my/wp-content/uploads/2021/10/Air-Qulaity.pdf [16]Mohammed, S.A., Yusof, M.M., 2013. Towards an evaluation framework for information quality management (IQM) practices for health information systems—evaluation criteria for effective IQM practices. Journal of Evaluation in Clinical Practice. 19(2), 379-387. DOI: https://doi.org/10.1111/j.1365-2753.2012.01839.x [17]Latif, M.T., Dominick, D., Ahamad, F., et al., 2014. Long term assessment of air quality from a background station on the Malaysian Peninsula. Science of the Total Environment. 482, 336-348. DOI: https://doi.org/10.1016/j.scitotenv.2014.02.132 [18]Hussain, H., 2019. Jerebu bakal pulih, ribut petir pula menyusul [Haze will recover, thunderstorms will follow] [Internet]. Available from: https://www.sinarharian.com.my/article/48783/BERITA/Nasional/Jerebu-bakal-pulih-ribut-petir-pula-menyusul [19]Official Portal of Department of Environment. Environmental Quality Report 2019 [Internet]; DOE: Putrajaya, Malaysia, 2019. Available from: https://enviro2.doe.gov.my/ekmc/wp-content/uploads/2020/09/EQR-20191.pdf [20]Kumar, A., Gupta, I., Brandt, J., et al., 2016. Air quality mapping using GIS and economic evaluation of health impact for Mumbai City, India. Journal of the Air & Waste Management Association. 66(5), 470-481. [21]Jumaah, H.J., Ameen, M.H., Kalantar, B., et al., 2019. Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, Malaysia. Geomatics, Natural Hazards and Risk. 10(1), 2185-2199. DOI: https://doi.org/10.1080/19475705.2019.1683084 [22]Rahman, S.R.A., Ismail, S.N.S., Raml, M.F., et al., 2015. The assessment of ambient air pollution trend in Klang Valley, Malaysia. World Environment. 5(1), 1-11. DOI: https://doi.org/10.5923/j.env.20150501.01 [23]De Iaco, S., Palma, M., Posa, D., 2005. Modeling and prediction of multivariate space-time random fields. Computational Statistics & Data Analysis. 48(3), 525-547. DOI: https://doi.org/10.1016/j.csda.2004.02.011 [24]Fan, H., Zhao, C., Yang, Y., 2020. A comprehensive analysis of the spatio-temporal variation of urban air pollution in China during 2014-2018. Atmospheric Environment. 220, 117066. DOI: https://doi.org/10.1016/j.atmosenv.2019.117066 [25]Amil, N., Latif, M.T., Khan, M.F., et al., 2016. Seasonal variability of PM 2.5 composition and sources in the Klang Valley urban-industrial environment. Atmospheric Chemistry and Physics. 16(8), 5357-5381. DOI: https://doi.org/10.5194/acp-16-5357-2016 [26]Jaafar, H., Azzeri, A., Isahak, M., et al., 2021. The impact of haze on healthcare utilizations for acute respiratory diseases: Evidence from Malaysia. Frontiers in Ecology and Evolution. 9, 764300. DOI: https://doi.org/10.3389/fevo.2021.764300 [27]Khan, M.F., Hamid, A.H., Ab Rahim, H., et al., 2020. El Niño driven haze over the southern Malaysian peninsula and Borneo. Science of the Total Environment. 730, 139091. DOI: https://doi.org/10.1016/j.scitotenv.2020.139091 [28]Tella, A., Balogun, A.L., 2021. Prediction of ambient PM10 concentration in Malaysian cities using geostatistical analyses. Journal of Advanced Geospatial Science & Technology. 1(1), 115-127. [29]Wang, W., Ying, Y., Wu, Q., et al., 2015. A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China. Respiratory Medicine. 109(3), 372-378. DOI: https://doi.org/10.1016/j.rmed.2015.01.006 [30]Marmaya, E.A., Mahbub, R., 2018. A comparative study on the environmental impact assessment of industrial projects in Malaysia. IOP Conference Series: Earth and Environmental Science. 117(1), 012020. DOI: https://doi.org/10.1088/1755-1315/117/1/012020 [31]Daoud, J.I., 2017. Multicollinearity and regression analysis. Journal of Physics: Conference Series. 949(1), 012009. DOI: https://doi.org/10.1088/1742-6596/949/1/012009 [32]Azmi, S.Z., Latif, M.T., Ismail, A.S., et al., 2010. Trend and status of air quality at three different monitoring stations in the Klang Valley, Malaysia. Air Quality, Atmosphere & Health. 3, 53-64. DOI: https://doi.org/10.1007/s11869-009-0051-1 [33]Wang, Y., Wild, O., Chen, H., et al., 2020. Acute and chronic health impacts of PM2.5 in China and the influence of interannual meteorological variability. Atmospheric Environment. 229, 117397. DOI: https://doi.org/10.1016/j.atmosenv.2020.117397 [34]Sansuddin, N., Ramli, N.A., Yahaya, A.S., et al., 2011. Statistical analysis of PM 10 concentrations at different locations in Malaysia. Environmental Monitoring and Assessment. 180, 573-588. DOI: https://doi.org/10.1007/s10661-010-1806-8 [35]Anderson, G.B., Dominici, F., Wang, Y., et al., 2013. Heat-related emergency hospitalizations for respiratory diseases in the Medicare population. American Journal of Respiratory and Critical Care Medicine. 187(10), 1098-1103. DOI: https://doi.org/10.1164/rccm.201211-1969OC