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  1. Tan AZL, Ho WS, Hassim MH, Abdullah F, Lim LY
    Environ Monit Assess, 2025 Mar 12;197(4):385.
    PMID: 40072627 DOI: 10.1007/s10661-025-13797-x
    In industrialized areas, air pollution is a recurring problem, especially in areas with high manufacturing and energy-intensive businesses. The challenge lies in the tension between industrial growth and environmental protection, as these sectors significantly contribute to pollution, resource depletion, and climate change. The objectives of the study were (1) to assess the contribution of each industrial group to the air quality in and around the Pasir Gudang industrial area, Malaysia, and (2) to evaluate the Air Pollution Index (API). Industrial emission sources were grouped into 10 specific groups, namely (1) biomass energy plants, (2) ceramic and mineral, (3) chemical, (4) electrical, (5) food and beverage, (6) metal industries, (7) paint, (8) rubber product, (9) waste recovery, and (10) wood respectively. For this, hourly, daily, and annual modelling of pollutant gases and particulate matter (SO2, NO2, and PM10) for 3 years (2019 to 2021) were conducted using the AERMOD dispersion model. The maximum hourly, daily, and annual average ground level concentrations of SO2 and PM10 were mainly contributed by Wood industry group emissions, while NO2 was dominated by metal industry group emissions. It was observed that the average hourly and daily NO2 levels exceeded Malaysia's standard limits. The API during the study period was 146.97, contributed by NO2, which indicates unhealthy conditions for sensitive groups. Therefore, NO2 pollutant control measures from the Metal industry group should be prioritized in this industrial area.
    Matched MeSH terms: Sulfur Dioxide/analysis
  2. Hanif MA, Ibrahim N, Abdul Jalil A
    Environ Sci Pollut Res Int, 2020 Aug;27(22):27515-27540.
    PMID: 32415453 DOI: 10.1007/s11356-020-09191-4
    Numerous mitigation techniques have been incorporated to capture or remove SO2 with flue gas desulfurization (FGD) being the most common method. Regenerative FGD method is advantageous over other methods due to high desulfurization efficiency, sorbent regenerability, and reduction in waste handling. The capital costs of regenerative methods are higher than those of commonly used once-through methods simply due to the inclusion of sorbent regeneration while operational and management costs depend on the operating hours and fuel composition. Regenerable sorbents like ionic liquids, deep eutectic solvents, ammonium halide solutions, alkyl-aniline solutions, amino acid solutions, activated carbons, mesoporous silica, zeolite, and metal-organic frameworks have been reported to successfully achieve high SO2 removal. The presence of other gases in flue gas, e.g., O2, CO2, NOx, and water vapor, and the reaction temperature critically affect the sorption capacity and sorbent regenerability. To obtain optimal SO2 removal performance, other parameters such as pH, inlet SO2 concentration, and additives need to be adequately governed. Due to its high removal capacity, easy preparation, non-toxicity, and low regeneration temperature, the use of deep eutectic solvents is highly feasible for upscale utilization. Metal-organic frameworks demonstrated highest reported SO2 removal capacity; however, it is not yet applicable at industrial level due to its high price, weak stability, and robust formulation.
    Matched MeSH terms: Sulfur Dioxide/analysis*
  3. Madukpe VN, Zulkepli NFS, Noorani MSM, Gobithaasan RU
    Environ Monit Assess, 2025 Jan 06;197(2):136.
    PMID: 39760901 DOI: 10.1007/s10661-024-13477-2
    This study investigates the effectiveness and efficiency of two topological data analysis (TDA) techniques, the conventional Mapper (CM) and its variant version, the Ball Mapper (BM), in analyzing the behavior of six major air pollutants (NO2, PM10, PM2.5, O3, CO, and SO2) across 60 air quality monitoring stations in Malaysia. Topological graphs produced by CM and BM reveal redundant monitoring stations and geographical relationships corresponding to air pollutant behavior, providing better visualization than traditional hierarchical clustering. Additionally, a comparative analysis of topological graph structures was conducted using node degree distribution, topological graph indices, and Dynamic Time Warping (DTW) to evaluate the sensitivity and performance of these TDA techniques. Both approaches yielded valuable insights in representing the air quality monitoring stations network; however, the complexity of CM, which requires multiple parameters, poses a challenge in graph construction. In contrast, the simplicity of BM, requiring only a single parameter, is preferable for representing air pollutant behavior. The findings suggest an alternative approach for assessing and identifying redundancies in air quality monitoring stations, which could contribute to improved air quality monitoring management and more effective regulatory policies.
    Matched MeSH terms: Sulfur Dioxide/analysis
  4. Mohd Shafi'i MS, Juahir H
    Environ Monit Assess, 2024 Jun 21;196(7):640.
    PMID: 38904667 DOI: 10.1007/s10661-024-12787-9
    The presence of harmful substances in the atmosphere poses significant risks to the environment and public health. These pollutants can come from natural sources like dust and wildfires, or from human activities such as industrial, transportation, and agricultural practices. The objective of this study was to assess air quality on the East Coast of Peninsular Malaysia by analyzing historical data from the Department of Environment, Malaysia. Daily measurements of PM10, O3, SO2, NO2, and CO were collected from eight monitoring stations over 11 years (2011-2021) and analyzed using environmetric techniques. Hierarchical agglomerative cluster analysis (HACA) classified two stations as belonging to the high pollution cluster (HPC), three stations as part of the moderate pollution cluster (MPC), and three stations as the low pollution cluster (LPC). Discriminant analysis revealed a correct assignment rate of 90.50%, indicating that all five parameters were able to differentiate pollution levels with high significance (p 
    Matched MeSH terms: Sulfur Dioxide/analysis
  5. Althuwaynee OF, Pokharel B, Aydda A, Balogun AL, Kim SW, Park HJ
    J Expo Sci Environ Epidemiol, 2021 07;31(4):709-726.
    PMID: 33159165 DOI: 10.1038/s41370-020-00271-8
    Accurate identification of distant, large, and frequent sources of emission in cities is a complex procedure due to the presence of large-sized pollutants and the existence of many land use types. This study aims to simplify and optimize the visualization mechanism of long time-series of air pollution data, particularly for urban areas, which is naturally correlated in time and spatially complicated to analyze. Also, we elaborate different sources of pollution that were hitherto undetectable using ordinary plot models by leveraging recent advances in ensemble statistical approaches. The high performing conditional bivariate probability function (CBPF) and time-series signature were integrated within the R programming environment to facilitate the study's analysis. Hourly air pollution data for the period between 2007 to 2016 is collected using four air quality stations, (ca0016, ca0058, ca0054, and ca0025), situated in highly urbanized locations that are characterized by complex land use and high pollution emitting activities. A conditional bivariate probability function (CBPF) was used to analyze the data, utilizing pollutant concentration values such as Sulfur dioxide (SO2), Nitrogen oxides (NO2), Carbon monoxide (CO) and Particulate Matter (PM10) as a third variable plotted on the radial axis, with wind direction and wind speed variables. Generalized linear model (GLM) and sensitivity analysis are applied to verify and visualize the relationship between Air Pollution Index (API) of PM10 and other significant pollutants of GML outputs based on quantile values. To address potential future challenges, we forecast 3 months PM10 values using a Time Series Signature statistical algorithm with time functions and validated the outcome in the 4 stations. Analysis of results reveals that sources emitting PM10 have similar activities producing other pollutants (SO2, CO, and NO2). Therefore, these pollutants can be detected by cross selection between the pollution sources in the affected city. The directional results of CBPF plot indicate that ca0058 and ca0054 enable easier detection of pollutants' sources in comparison to ca0016 and ca0025 due to being located on the edge of industrial areas. This study's CBPF technique and time series signature analysis' outcomes are promising, successfully elaborating different sources of pollution that were hitherto undetectable using ordinary plot models and thus contribute to existing air quality assessment and enhancement mechanisms.
    Matched MeSH terms: Sulfur Dioxide/analysis
  6. Zhang Q, Zhang Y, Yu H, Qing F, Wang Y
    PLoS One, 2026;21(10):e0360548.
    PMID: 42949875 DOI: 10.1371/journal.pone.0360548
    Existing studies on resource and environmental carrying capacity (RECC) have primarily focused on comprehensive evaluation and linear identification. But the quantification of driving effect on RECC have not been fully explored, especially the interaction and nonlinear effects. Therefore, this paper constructs an explainable machine learning framework, to comprehensively assess the RECC index of 31 provincial regions in China and to reveal nonlinear and interaction mechanisms of influence factors. Firstly, the XGBoost model is utilized to surrogate the evaluation results, which demonstrates outstanding predictive performance (R2 = 0.95, RMSE = 0.08) and stability. The results shows that the average RECC index in China dropping from 1.18 to 0.39, marking a transition from a high-risk state to a safe and sustainable state. Then, the SHAP model quantifies the nonlinear and threshold effects of key influence factors. The results indicate that the total emissions of pollutants in wastewater (X2) and industrial sulfur dioxide emissions (X3) are the two most critical factors, with a cumulative contribution rate of 49%. 50000 tons is a threshold for X2, beyond which the RECC index significantly increases with the increase of X2. 10 billion cubic meters is the marginal contribution of X3, with the greatest impact on RECC index. The interaction effect indicates a significant positive synergistic effect between X2 and X3, with the maximum increase in SHAP value reaching 0.1. There is a significant antagonistic effect between resource availability and environmental pressure. This study offering new directions for understanding the underlying mechanisms of complex environmental systems.
    Matched MeSH terms: Sulfur Dioxide/analysis
  7. Awang MB, Jaafar AB, Abdullah AM, Ismail MB, Hassan MN, Abdullah R, et al.
    Respirology, 2000 Jun;5(2):183-96.
    PMID: 10894109
    OBJECTIVE: Observations have been made on the long-term trends of major air pollutants in Malaysia including nitrogen dioxide, carbon monoxide, the ozone and total suspended particulate matter (particularly PM10), and sulfur dioxide, emitted from industrial and urban areas from early 1970s until late 1998.

    METHODOLOGY: The data show that the status of atmospheric environment in Malaysia, in particular in highly industrialized areas such as Klang Valley, was determined both by local and transboundary emissions and could be described as haze and non-haze periods.

    RESULTS: During the non-haze periods, vehicular emissions accounted for more than 70% of the total emissions in the urban areas and have demonstrated two peaks in the diurnal variations of the aforementioned air pollutants, except ozone. The morning 'rush-hour' peak was mainly due to vehicle emissions, while the late evening peak was mainly attributed to meteorological conditions, particularly atmospheric stability and wind speed. Total suspended particulate matter was the main pollutant with its concentrations at few sites often exceeding the Recommended Malaysia Air Quality Guidelines. The levels of other pollutants were generally within the guidelines. Since 1980, six major haze episodes were officially reported in Malaysia: April 1983, August 1990, June 1991, October 1991, August to October 1994, and July to October 1997. The 1997 haze episode was the worst ever experienced by the country. Short-term observations using continuous monitoring systems during the haze episodes during these periods clearly showed that suspended particulate matter (PM10) was the main cause of haze and was transboundary in nature. Large forest fires in parts of Sumatra and Kalimantan during the haze period, clearly evident in satellite images, were identified as the probable key sources of the widespread heavy haze that extended across Southeast Asia from Indonesia to Singapore, Malaysia and Brunei. The results of several studies have also provided strong evidence that biomass burning is the dominating source of particulate matter. The severity and extent of 1997's haze pollution was unprecedented, affecting some 300 million people across the region. The amount of economic costs suffered by Southeast Asian countries during this environmental disaster was enormous and is yet to be fully determined. Among the important sectors severely affected were air and land transport, shipping, construction, tourism and agro-based industries. The economic cost of the haze-related damage to Malaysia presented in this study include short-term health costs, production losses, tourism-related losses and the cost of avertive action. Although the cost reported here is likely to be underestimated, they are nevertheless significant (roughly RM1 billion).

    CONCLUSIONS: The general air quality of Malaysia since 1970 has deteriorated. Studies have shown that should no effective countermeasures be introduced, the emissions of sulfur dioxide, nitrogen oxides, particulate matter, hydrocarbons and carbon monoxide in the year 2005 would increase by 1.4, 2.12, 1.47 and 2.27 times, respectively, from the 1992 levels.

    Matched MeSH terms: Sulfur Dioxide/analysis
  8. Abdullah L, Khalid ND
    Environ Monit Assess, 2012 Nov;184(11):6957-65.
    PMID: 22160435 DOI: 10.1007/s10661-011-2472-1
    Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.
    Matched MeSH terms: Sulfur Dioxide/analysis
  9. Mohd Jaafar MN, Eldrainy YA, Mat Ali MF, Wan Omar WZ, Mohd Hizam MF
    Environ Sci Technol, 2012 Feb 21;46(4):2445-50.
    PMID: 22296110 DOI: 10.1021/es2025005
    The problems of global warming and the unstable price of petroleum oils have led to a race to develop environmentally friendly biofuels, such as palm oil or ethanol derived from corn and sugar cane. Biofuels are a potential replacement for fossil fuel, since they are renewable and environmentally friendly. This paper evaluates the combustion performance and emission characteristics of Refined, Bleached, and Deodorized Palm Oil (RBDPO)/diesel blends B5, B10, B15, B20, and B25 by volume, using an industrial oil burner with and without secondary air. Wall temperature profiles along the combustion chamber axis were measured using a series of thermocouples fitted axially on the combustion chamber wall, and emissions released were measured using a gas analyzer. The results show that RBDPO blend B25 produced the maximum emission reduction of 56.9% of CO, 74.7% of NOx, 68.5% of SO(2), and 77.5% of UHC compared to petroleum diesel, while air staging (secondary air) in most cases reduces the emissions further. However, increasing concentrations of RBDPO in the blends also reduced the energy released from the combustion. The maximum wall temperature reduction was 62.7% for B25 at the exit of the combustion chamber.
    Matched MeSH terms: Sulfur Dioxide/analysis
  10. Lee KT, Bhatia S, Mohamed AR, Chu KH
    Chemosphere, 2006 Jan;62(1):89-96.
    PMID: 15996711
    High performance sorbents for flue gas desulfurization can be synthesized by hydration of coal fly ash, calcium sulfate, and calcium oxide. In general, higher desulfurization activity correlates with higher sorbent surface area. Consequently, a major aim in sorbent synthesis is to maximize the sorbent surface area by optimizing the hydration conditions. This work presents an integrated modeling and optimization approach to sorbent synthesis based on statistical experimental design and two artificial intelligence techniques: neural network and genetic algorithm. In the first step of the approach, the main and interactive effects of three hydration variables on sorbent surface area were evaluated using a full factorial design. The hydration variables of interest to this study were hydration time, amount of coal fly ash, and amount of calcium sulfate and the levels investigated were 4-32 h, 5-15 g, and 0-12 g, respectively. In the second step, a neural network was used to model the relationship between the three hydration variables and the sorbent surface area. A genetic algorithm was used in the last step to optimize the input space of the resulting neural network model. According to this integrated modeling and optimization approach, an optimum sorbent surface area of 62.2m(2)g(-1) could be obtained by mixing 13.1g of coal fly ash and 5.5 g of calcium sulfate in a hydration process containing 100ml of water and 5 g of calcium oxide for a fixed hydration time of 10 h.
    Matched MeSH terms: Sulfur Dioxide/analysis*
  11. Masseran N, Razali AM, Ibrahim K, Latif MT
    Environ Monit Assess, 2016 Jan;188(1):65.
    PMID: 26718946 DOI: 10.1007/s10661-015-5070-9
    The air pollution index (API) is an important figure used for measuring the quality of air in the environment. The API is determined based on the highest average value of individual indices for all the variables which include sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and suspended particulate matter (PM10) at a particular hour. API values that exceed the limit of 100 units indicate an unhealthy status for the exposed environment. This study investigates the risk of occurrences of API values greater than 100 units for eight urban areas in Peninsular Malaysia for the period of January 2004 to December 2014. An extreme value model, known as the generalized Pareto distribution (GPD), has been fitted to the API values found. Based on the fitted model, return period for describing the occurrences of API exceeding 100 in the different cities has been computed as the indicator of risk. The results obtained indicated that most of the urban areas considered have a very small risk of occurrence of the unhealthy events, except for Kuala Lumpur, Malacca, and Klang. However, among these three cities, it is found that Klang has the highest risk. Based on all the results obtained, the air quality standard in urban areas of Peninsular Malaysia falls within healthy limits to human beings.
    Matched MeSH terms: Sulfur Dioxide/analysis
  12. Hassan NA, Hashim Z, Hashim JH
    Asia Pac J Public Health, 2016 Mar;28(2 Suppl):38S-48S.
    PMID: 26141092 DOI: 10.1177/1010539515592951
    This review discusses how climate undergo changes and the effect of climate change on air quality as well as public health. It also covers the inter relationship between climate and air quality. The air quality discussed here are in relation to the 5 criteria pollutants; ozone (O3), carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM). Urban air pollution is the main concern due to higher anthropogenic activities in urban areas. The implications on health are also discussed. Mitigating measures are presented with the final conclusion.
    Matched MeSH terms: Sulfur Dioxide/analysis
  13. Tajudin MABA, Khan MF, Mahiyuddin WRW, Hod R, Latif MT, Hamid AH, et al.
    Ecotoxicol Environ Saf, 2019 Apr 30;171:290-300.
    PMID: 30612017 DOI: 10.1016/j.ecoenv.2018.12.057
    Rapid urbanisation in Malaysian cities poses risks to the health of residents. This study aims to estimate the relative risk (RR) of major air pollutants on cardiovascular and respiratory hospitalisations in Kuala Lumpur. Daily hospitalisations due to cardiovascular and respiratory diseases from 2010 to 2014 were obtained from the Hospital Canselor Tuanku Muhriz (HCTM). The trace gases, PM10 and weather variables were obtained from the Department of Environment (DOE) Malaysia in consistent with the hospitalisation data. The RR was estimated using a Generalised Additive Model (GAM) based on Poisson regression. A "lag" concept was used where the analysis was segregated into risks of immediate exposure (lag 0) until exposure after 5 days (lag 5). The results showed that the gases could pose significant risks towards cardiovascular and respiratory hospitalisations. However, the RR value of PM10 was not significant in this study. Immediate effects on cardiovascular hospitalisations were observed for NO2 and O3 but no immediate effect was found on respiratory hospitalisations. Delayed effects on cardiovascular and respiratory hospitalisations were found with SO2 and NO2. The highest RR value was observed at lag 4 for respiratory admissions with SO2 (RR = 1.123, 95% CI = 1.045-1.207), followed by NO2 at lag 5 for cardiovascular admissions (RR = 1.025, 95% CI = 1.005-1.046). For the multi-pollutant model, NO2 at lag 5 showed the highest risks towards cardiovascular hospitalisations after controlling for O3 8 h mean lag 1 (RR = 1.026, 95% CI = 1.006-1.047), while SO2 at lag 4 showed highest risks towards respiratory hospitalisations after controlling for NO2 lag 3 (RR = 1.132, 95% CI = 1.053-1.216). This study indicated that exposure to trace gases in Kuala Lumpur could lead to both immediate and delayed effects on cardiovascular and respiratory hospitalisations.
    Matched MeSH terms: Sulfur Dioxide/analysis
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