Smoking is the most well-established cause of chronic airflow obstruction (CAO) but particulate air pollution and poverty have also been implicated. We regressed sex-specific prevalence of CAO from 41 Burden of Obstructive Lung Disease study sites against smoking prevalence from the same study, the gross national income per capita and the local annual mean level of ambient particulate matter (PM2.5) using negative binomial regression. The prevalence of CAO was not independently associated with PM2.5 but was strongly associated with smoking and was also associated with poverty. Strengthening tobacco control and improved understanding of the link between CAO and poverty should be prioritised.
Numerous epidemiological studies have evaluated the association of fractional exhaled nitric oxide (FeNO) and indoor air pollutants, but limited information available of the risks between schools located in suburban and urban areas. We therefore investigated the association of FeNO levels with indoor particulate matter (PM10 and PM2.5), and nitrogen dioxide (NO2) exposure in suburban and urban school areas. A comparative cross-sectional study was undertaken among secondary school students in eight schools located in the suburban and urban areas in the district of Hulu Langat, Selangor, Malaysia. A total of 470 school children (aged 14 years old) were randomly selected, their FeNO levels were measured, and allergic skin prick tests were conducted. The PM2.5, PM10, NO2, and carbon dioxide (CO2), temperature, and relative humidity were measured inside the classrooms. We found that the median of FeNO in the school children from urban areas (22.0 ppb, IQR = 32.0) were slightly higher as compared to the suburban group (19.5 ppb, IQR = 24.0). After adjustment of potential confounders, the two-level hierarchical multiple logistic regression models showed that the concentrations of PM2.5 were significantly associated with elevated of FeNO (>20 ppb) in school children from suburban (OR = 1.42, 95% CI = 1.17−1.72) and urban (OR = 1.30, 95% CI = 1.10−1.91) areas. Despite the concentrations of NO2 being below the local and international recommendation guidelines, NO2 was found to be significantly associated with the elevated FeNO levels among school children from suburban areas (OR = 1.11, 95% CI = 1.06−1.17). The findings of this study support the evidence of indoor pollutants in the school micro-environment associated with FeNO levels among school children from suburban and urban areas.
Principal component analysis (PCA) and correlation have been used to study the variability of particle mass and particle number concentrations (PNC) in a tropical semi-urban environment. PNC and mass concentration (diameter in the range of 0.25->32.0 μm) have been measured from 1 February to 26 February 2013 using an in situ Grimm aerosol sampler. We found that the 24-h average total suspended particulates (TSP), particulate matter ≤10 μm (PM10), particulate matter ≤2.5 μm (PM2.5) and particulate matter ≤1 μm (PM1) were 14.37 ± 4.43, 14.11 ± 4.39, 12.53 ± 4.13 and 10.53 ± 3.98 μg m(-3), respectively. PNC in the accumulation mode (<500 nm) was the most abundant (at about 99 %). Five principal components (PCs) resulted from the PCA analysis where PC1 (43.8 % variance) predominates with PNC in the fine and sub-microme tre range. PC2, PC3, PC4 and PC5 explain 16.5, 12.4, 6.0 and 5.6 % of the variance to address the coarse, coarser, accumulation and giant fraction of PNC, respectively. Our particle distribution results show good agreement with the moderate resolution imaging spectroradiometer (MODIS) distribution.
In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM2.5). This study assessed the environmental burden of disease attributable to PM2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347-12,791), COPD was between 164 and 957 (95 % CI: 95-1411), lung cancer was between 109 and 307 (95 % CI: 63-437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2-394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3-261). An increase in estimated health endpoints was associated with increased estimated PWEL PM2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.
This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.
The molecular composition and distribution of sterols were investigated in the East China Sea to identify the origins of suspended particulate matter (SPM) in offshore waters influenced by Changjiang River Diluted Water (CRDW). Total sterol concentrations ranged from 3200 to 31,900pgL(-1) and 663 to 5690pgL(-1) in the particulate and dissolved phases, respectively. Marine sterols dominated representing 71% and 66% in the particulate and dissolved phases, respectively. Typical sewage markers, such as coprostanol, were usually absent at ~250km offshore. However, sterols from allochthonous terrestrial plants were still detected at these sites. A negative relationship was observed between salinity and concentrations of terrestrial sterols in SPM, suggesting that significant amounts of terrestrial particulate matter traveled long distance offshore in the East China Sea, and the Changjiang River Diluted Water (CRDW) was an effective carrier of land-derived particulate organic matter to the offshore East China Sea.
This study aimed to investigate the chemical composition and potential sources of PM10 as well as assess the potential health hazards it posed to school children. PM10 samples were taken from classrooms at a school in Kuala Lumpur's city centre (S1) and one in the suburban city of Putrajaya (S2) over a period of eight hours using a low volume sampler (LVS). The composition of the major ions and trace metals in PM10 were then analysed using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. The results showed that the average PM10 concentration inside the classroom at the city centre school (82µg/m(3)) was higher than that from the suburban school (77µg/m(3)). Principal component analysis-absolute principal component scores (PCA-APCS) revealed that road dust was the major source of indoor PM10 at both school in the city centre (36%) and the suburban location (55%). The total hazard quotient (HQ) calculated, based on the formula suggested by the United States Environmental Protection Agency (USEPA), was found to be slightly higher than the acceptable level of 1, indicating that inhalation exposure to particle-bound non-carcinogenic metals of PM10, particularly Cr exposure by children and adults occupying the school environment, was far from negligible.
Current study presents RSM based optimized production of biodiesel from palm oil using chemical and enzymatic transesterification. The emission behavior of biodiesel and its blends, namely, POB-5, POB-20, POB-40, POB-50, POB-80, and POB-100 was examined using diesel engine (equipped with tube well). Optimized palm oil fatty acid methyl esters (POFAMEs) yields were depicted to be 47.6 ± 1.5, 92.7 ± 2.5, and 95.4 ± 2.0% for chemical transesterification catalyzed by NaOH, KOH, and NaOCH3, respectively, whereas for enzymatic transesterification reactions catalyzed by NOVOZYME-435 and A. n. lipase optimized biodiesel yields were 94.2 ± 3.1 and 62.8 ± 2.4%, respectively. Distinct decrease in particulate matter (PM) and carbon monoxide (CO) levels was experienced in exhaust emissions from engine operating on biodiesel blends POB-5, POB-20, POB-40, POB-50, POB-80, and POB-100 comparative to conventional petroleum diesel. Percentage change in CO and PM emissions for different biodiesel blends ranged from -2.1 to -68.7% and -6.2 to -58.4%, respectively, relative to conventional diesel, whereas an irregular trend was observed for NOx emissions. Only POB-5 and POB-20 showed notable reductions, whereas all other blends (POB-40 to POB-100) showed slight increase in NOx emission levels from 2.6 to 5.5% comparative to petroleum diesel.
This study was carried out to determine the concentration of lead (Pb), anions, and cations at six primary schools located around Kuala Lumpur. Low volume sampler (MiniVol PM10) was used to collect the suspended particulates in indoor and outdoor air. Results showed that the concentration of Pb in indoor air was in the range of 5.18 ± 1.08 μg/g-7.01 ± 0.08 μg/g. All the concentrations of Pb in indoor air were higher than in outdoor air at all sampling stations. The concentrations of cations and anions were higher in outdoor air than in indoor air. The concentration of Ca(2+) (39.51 ± 5.01 mg/g-65.13 ± 9.42 mg/g) was the highest because the cation existed naturally in soil dusts, while the concentrations of NO3 (-) and SO4 (2-) were higher in outdoor air because there were more sources of exposure for anions in outdoor air, such as highly congested traffic and motor vehicles emissions. In comparison, the concentration of NO3 (-) (29.72 ± 0.31 μg/g-32.00 ± 0.75 μg/g) was slightly higher than SO4 (2-). The concentrations of most of the parameters in this study, such as Mg(2+), Ca(2+), NO3 (-), SO4 (2-), and Pb(2+), were higher in outdoor air than in indoor air at all sampling stations.
This study aims to determine the composition and sources of particulate matter with an aerodynamic diameter of 10 μm or less (PM10) in a semi-urban area. PM10 samples were collected using a high volume sampler. Heavy metals (Fe, Zn, Pb, Mn, Cu, Cd and Ni) and cations (Na(+), K(+), Ca(2+) and Mg(2+)) were detected using inductively coupled plasma mass spectrometry, while anions (SO4 (2-), NO3 (-), Cl(-) and F(-)) were analysed using Ion Chromatography. Principle component analysis and multiple linear regressions were used to identify the source apportionment of PM10. Results showed the average concentration of PM10 was 29.5 ± 5.1 μg/m(3). The heavy metals found were dominated by Fe, followed by Zn, Pb, Cu, Mn, Cd and Ni. Na(+) was the dominant cation, followed by Ca(2+), K(+) and Mg(2+), whereas SO4 (2-) was the dominant anion, followed by NO3 (-), Cl(-) and F(-). The main sources of PM10 were the Earth's crust/road dust, followed by vehicle emissions, industrial emissions/road activity, and construction/biomass burning.
The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.
This study aims at developing a novel effluent removal management tool for septic sludge treatment plants (SSTP) using a clonal selection algorithm (CSA). The proposed CSA articulates the idea of utilizing an artificial immune system (AIS) to identify the behaviour of the SSTP, that is, using a sequence batch reactor (SBR) technology for treatment processes. The novelty of this study is the development of a predictive SSTP model for effluent discharge adopting the human immune system. Septic sludge from the individual septic tanks and package plants will be desuldged and treated in SSTP before discharging the wastewater into a waterway. The Borneo Island of Sarawak is selected as the case study. Currently, there are only two SSTPs in Sarawak, namely the Matang SSTP and the Sibu SSTP, and they are both using SBR technology. Monthly effluent discharges from 2007 to 2011 in the Matang SSTP are used in this study. Cross-validation is performed using data from the Sibu SSTP from April 2011 to July 2012. Both chemical oxygen demand (COD) and total suspended solids (TSS) in the effluent were analysed in this study. The model was validated and tested before forecasting the future effluent performance. The CSA-based SSTP model was simulated using MATLAB 7.10. The root mean square error (RMSE), mean absolute percentage error (MAPE), and correction coefficient (R) were used as performance indexes. In this study, it was found that the proposed prediction model was successful up to 84 months for the COD and 109 months for the TSS. In conclusion, the proposed CSA-based SSTP prediction model is indeed beneficial as an engineering tool to forecast the long-run performance of the SSTP and in turn, prevents infringement of future environmental balance in other towns in Sarawak.
The main objective of this cross-sectional comparative study is to observe the relationship between traffic-related air pollutants, particularly particulate matter (PM) of total suspended particulate (TSP) and PM of size 10 µm (PM10), and vehicle traffic in Amman, Jordan. Two study areas were chosen randomly as a high-polluted area (HPA) and low-polluted area (LPA). The findings indicate that TSP and PM10 were still significantly correlated with traffic count even after controlling for confounding factors (temperature, relative humidity, and wind speed): TSP, r = 0.726, P < .001; PM10, r = 0.719, P < .001). There was a significant positive relationship between traffic count and PM level: TSP, P < .001; PM10, P < .001. Moreover, there was a significant negative relationship between temperature and PM10 level (P = .018). Traffic volume contributed greatly to high concentrations of TSP and PM10 in areas with high traffic count, in addition to the effect of temperature.
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.
This study aims to determine the composition of surfactants in the lake surface microlayer, rainwater, and atmospheric aerosols in the area surrounding Lake Chini, Pahang. Surfactants in the lake surface microlayer were taken from seven different stations around the lake, while samples of rainwater were taken from five different sampling stations. The samples of atmospheric aerosols were collected from the Lake Chini Research Centre which is in close proximity to the lake. The colorimetric analysis method was used to determine the composition and concentration of anionic surfactants as methylene blue active substances (MBAS) and cationic surfactants as disulphine blue active substances (DBAS). The concentration of anionic surfactants, as MBAS, in the surface microlayer ranged between 0.08 to 0.23 μmol L(-1), while the range of concentration of cationic surfactants as DBAS ranged from 0.09 to 0.11 μmol L(-1). The concentration of MBAS was higher in rainwater when compared to surfactants in the lake surface microlayer. The high concentration of surfactants in the fine mode of atmospheric aerosols suggests that natural and anthropogenic sources of surfactants contribute to the atmospheric surfactants.
The renovation of a building will certainly affect the quality of air in the vicinity of where associated activities were undertaken, this includes the quality of air inside the building. Indoor air pollutants such as particulate matter, heavy metals, and fine fibers are likely to be emitted during renovation work. This study was conducted to determine the concentration of heavy metals, asbestos and suspended particulates in the Biology Building, at the Universiti Kebangsaan, Malaysia (UKM). Renovation activities were carried out widely in the laboratories which were located in this building. A low-volume sampler was used to collect suspended particulate matter of a diameter size less than 10 μm (PM₁₀) and an air sampling pump, fitted with a cellulose ester membrane filter, were used for asbestos sampling. Dust was collected using a small brush and scope. The concentration of heavy metals was determined through the use of inductively coupled plasma-mass spectroscopy and the fibers were counted through a phase contrast microscope. The concentrations of PM₁₀ recorded in the building during renovation action (ranging from 166 to 542 μg m⁻³) were higher than the value set by the Department of Safety and Health for respirable dust (150 μg m⁻³). Additionally, they were higher than the value of PM₁₀ recorded in indoor environments from other studies. The composition of heavy metals in PM₁₀ and indoor dust were found to be dominated by Zn and results also showed that the concentration of heavy metals in indoor dust and PM₁₀ in this study was higher than levels recorded in other similar studies. The asbestos concentration was 0.0038 ± 0.0011 fibers/cc. This was lower than the value set by the Malaysian Department of Occupational, Safety and Health (DOSH) regulations of 0.1 fibers/cc, but higher than the background value usually recorded in indoor environments. This study strongly suggests that renovation issues need to be considered seriously by relevant stakeholders within the university in order to ensure that the associated risks toward humans and indoor environment are eliminated, or where this is not feasible, minimized as far as possible.
Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.
Water quality degradation in the Citarum river will increase from the year to year due to increasing pollutant loads when released particularly from Bandung region of the upstream areas into the river without treatment. This will be facing the problems on water quality status to use for multi-purposes in the downstream areas. The water quality evaluation system is used to evaluate the available water condition that distinguishes into two categories, i.e., the water quality index (WQI) and water quality aptitude (WQA). The assessment of water quality for the Citarum river from 10 selected stations was found that the WQI situates in the bad category generally and the WQA ranges from the suitable quality for agriculture and livestock watering uses to the unsuitable for biological potential function, drinking water production, and leisure activities and sports in the upstream areas of Saguling dam generally.
Results from the present study in Kuala Terengganu, Malaysia indicated a significant spatial variation but generally the total suspended particulate concentrations (mean = 17.2-148 microg/m(3)) recorded were below the recommended Malaysia guideline for total suspended particulate (mean of 24-h measurement = 260 microg/m(3)). Some of the elemental composition of particulate aerosol is clearly affected by non crustal sources, e.g. vehicular emission sources. Based on correlation and enrichment analyses, the elements could be grouped into two i.e. Pb, Cd and Zn group with sources from vehicular emission (r > 0.6; enrichment factor > 10) and Al, Fe, Mn and Cr group that appears to be of crustal origin (r > 0.6; enrichment factor < 10). It can also be concluded that the mean levels of Pb (1 ng/m(3)), Cd (0.02 ng/m(3)) and Zn (2 ng/m(3)) in the study area are generally lower than other urban areas in Malaysia (Pb < 181 ng/m(3); Cd < 6 ng/m(3); Zn < 192 ng/m(3)).
The purpose of this study was to determine the indoor air quality (IAQ) status of an automotive assembly plant in Rawang, Selangor, Malaysia using selected IAQ parameters, such as carbon dioxide (CO2), carbon monoxide (CO), temperature, relative humidity (RH) and respirable particulate matter (PM10). A cross-sectional study was conducted in the paint shop and body shop sections of the plant in March 2005. The Q-TRAK Plus IAQ Monitor was used to record the patterns of CO, CO2, RH and temperature; whilst PM10 was measured using DUSTTRAK Aerosol Monitor over an 8-hour time weight average (8-TWA). It was found that the average temperatures, RH and PM10 in the paint shop section and body shop sections exceeded the Department of Safety and Health (DOSH) standards. The average concentrations of RH and CO were slightly higher in the body shop section than in the paint shop section, while the average concentrations of temperature and CO2 were slightly higher in the paint shop section than in the body shop section. There was no difference in the average concentrations of PM10 between the two sections.