Displaying publications 21 - 40 of 90 in total

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  1. Access to clean technologies, energy, finance, and food: environmental sustainability agenda and its implications on Sub-Saharan African countries
    Hishan SS, Sasmoko, Khan A, Ahmad J, Hassan ZB, Zaman K, et al.
    Environ Sci Pollut Res Int, 2019 Jun;26(16):16503-16518.
    PMID: 30980369 DOI: 10.1007/s11356-019-05056-7
    The Sub-Saharan Africa (SSA) is far lag behind the sustainable targets that set out in the United Nation's Sustainable Development Goals (SDGs), which is highly needed to embark the priorities by their member countries to devise sustainable policies for accessing clean technologies, energy demand, finance, and food production to mitigate high-mass carbon emissions and conserve environmental agenda in the national policy agenda. The study evaluated United Nation's SDGs for environmental conservation and emission reduction in the panel of 35 selected SSA countries, during a period of 1995-2016. The study further analyzed the variable's relationship in inter-temporal forecasting framework for the next 10 years' time period, i.e., 2017-2026. The parameter estimates for the two models, i.e., CO2 model and PM2.5 models are analyzed by Generalized Method of Moment (GMM) estimator that handle possible endogeneity issue from the given models. The results rejected the inverted U-shaped Environmental Kuznets Curve (EKC) for CO2 emissions, while it supported for PM2.5 emissions with a turning point of US$5540 GDP per capita in constant 2010 US$. The results supported the "pollution haven hypothesis" for CO2 emissions, while this hypothesis is not verified for PM2.5 emissions. The major detrimental factors are technologies, FDI inflows, and food deficit that largely increase carbon emissions in a panel of SSA countries. The IPAT hypothesis is not verified in both the emissions; however, population density will largely influenced CO2 emissions in the next 10 years' time period. The PM2.5 emissions will largely be influenced by high per capita income, followed by trade openness, and technologies, over a time horizon. Thus, the United Nation's sustainable development agenda is highly influenced by socio-economic and environmental factors that need sound action plans by their member countries to coordinate and collaborate with each other and work for Africa's green growth agenda.
    Matched MeSH terms: Particulate Matter/analysis
  2. Fulltext Effect of large-scale social restriction (PSBB) during COVID-19 on outdoor air quality: Evidence from five cities in DKI Jakarta Province, Indonesia
    Anugerah AR, Muttaqin PS, Purnama DA
    Environ Res, 2021 06;197:111164.
    PMID: 33872645 DOI: 10.1016/j.envres.2021.111164
    The variation in the concentration of outdoor air pollutants during the COVID-19 lockdown was studied in Jakarta, Indonesia. The term lockdown was replaced by large-scale social restrictions (PSBB) in Indonesia by more flexible regulations to save the economy. Data on five air pollutants, namely, PM10, SO2, CO, O3, and NO2, from five monitoring stations located in five regions in Jakarta (West, East, Central, North, and South Jakarta) were utilized. We analyzed the changes in the concentrations of outdoor air pollutants before lockdown from January 1 to April 9, 2020, and during lockdown from April 10 to June 4, 2020. Overall, the CO concentration (39.9%) demonstrated the most significant reduction during lockdown, followed by NO2 (7.5%) and then SO2 (5.7%). However, we unexpectedly found that during lockdown, the PM10 concentration in Jakarta increased by 10.9% due to the southwest monsoon during the seasonal change in Jakarta. Among the five cities in Jakarta, East and Central Jakarta experienced the maximum improvement in their air quality, whereas North Jakarta had the least air quality improvement. To the best of our knowledge, this research is the first to study the effect of lockdown on outdoor air quality improvement in Indonesia using ground-level measurement data. The findings of the study provide additional strategies to the regulatory bodies for the reduction of temporal air pollutants in Jakarta, Indonesia, by restricting people mobility as a supplementary initiative.
    Matched MeSH terms: Particulate Matter/analysis
  3. A case study on the source apportionment of indoor air quality at a kindergarten in eastern Peninsular Malaysia using cluster analysis
    Sidek SS, Yatim SRM, Abdullah S, Shafie FA, Ishak AR, Dom NC, et al.
    Med J Malaysia, 2024 Mar;79(Suppl 1):104-109.
    PMID: 38555893
    BACKGROUND: Indoor air quality is an important concern for kindergartener because young children are more vulnerable to the effects of poor air quality. Poor indoor air quality can cause respiratory problems and other health issues, which can negatively affect a child's ability to learn and grow. Aim of this study is to determine the trend and status of indoor air pollutants in study areas by using descriptive statistics and cluster analysis.

    MATERIALS AND METHODS: Air temperature (T), relative humidity (RH), air movement (AM), carbon dioxide (CO2), formaldehyde (HCHO), and particulate matter (PM) are the monitored parameters. Monitoring was carried out in the kindergarten for three consecutive days starting from 8.00am to 12.00pm.

    RESULTS: Indoor carbon dioxide readings were higher at 0800 when parents drove to kindergarten to drop off their children without turning off the engine. In addition to this, the PM10 reading at 1000 was high but still within the standard range according to ICOP-IAQ 2010.

    CONCLUSION: The findings highlight the importance of indoor air quality improvement measures for kindergarten buildings which can be used to improve indoor air quality in kindergarten environments.

    Matched MeSH terms: Particulate Matter/analysis
  4. Recent progress on phytoremediation of urban air pollution
    Duan X, Gu H, Lam SS, Sonne C, Lu W, Li H, et al.
    Chemosphere, 2024 Feb;349:140821.
    PMID: 38042424 DOI: 10.1016/j.chemosphere.2023.140821
    The rapid growth of population and economy has led to an increase in urban air pollutants, greenhouse gases, energy shortages, environmental degradation, and species extinction, all of which affect ecosystems, biodiversity, and human health. Atmospheric pollution sources are divided into direct and indirect pollutants. Through analysis of the sources of pollutants, the self-functioning of different plants can be utilized to purify the air quality more effectively. Here, we explore the absorption of greenhouse gases and particulate matter in cities as well as the reduction of urban temperatures by plants based on international scientific literature on plant air pollution mitigation, according to the adsorption, dust retention, and transpiration functions of plants. At the same time, it can also reduce the occurrence of extreme weather. It is necessary to select suitable tree species for planting according to different plant functions and environmental needs. In the context of tight urban land use, the combination of vertical greening and urban architecture, through the rational use of plants, has comprehensively addressed urban air pollution. In the future, in urban construction, attention should be paid to the use of heavy plants and the protection and development of green spaces. Our review provides necessary references for future urban planning and research.
    Matched MeSH terms: Particulate Matter/analysis
  5. Spatial identification and temporal prediction of air pollution sources using conditional bivariate probability function and time series signature
    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: Particulate Matter/analysis
  6. Recent progress in research on PM2.5 in subways
    Chang L, Chong WT, Wang X, Pei F, Zhang X, Wang T, et al.
    Environ Sci Process Impacts, 2021 May 26;23(5):642-663.
    PMID: 33889885 DOI: 10.1039/d1em00002k
    Nowadays, PM2.5 concentrations greatly influence indoor air quality in subways and threaten passenger and staff health because PM2.5 not only contains heavy metal elements, but can also carry toxic and harmful substances due to its small size and large specific surface area. Exploring the physicochemical and distribution characteristics of PM2.5 in subways is necessary to limit its concentration and remove it. At present, there are numerous studies on PM2.5 in subways around the world, yet, there is no comprehensive and well-organized review available on this topic. This paper reviews the nearly twenty years of research and over 130 published studies on PM2.5 in subway stations, including aspects such as concentration levels and their influencing factors, physicochemical properties, sources, impacts on health, and mitigation measures. Although many determinants of station PM2.5 concentration have been reported in current studies, e.g., the season, outdoor environment, and station depth, their relative influence is uncertain. The sources of subway PM2.5 include those from the exterior (e.g., road traffic and fuel oil) and the interior (e.g., steel wheels and rails and metallic brake pads), but the proportion of these sources is also unknown. Control strategies of PM mainly include adequate ventilation and filtration, but these measures are often inefficient in removing PM2.5. The impacts of PM2.5 from subways on human health are still poorly understood. Further research should focus on long-term data collection, influencing factors, the mechanism of health impacts, and PM2.5 standards or regulations.
    Matched MeSH terms: Particulate Matter/analysis
  7. Fulltext Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia
    Mazeli MI, Pahrol MA, Abdul Shakor AS, Kanniah KD, Omar MA
    Sci Total Environ, 2023 May 20;874:162130.
    PMID: 36804978 DOI: 10.1016/j.scitotenv.2023.162130
    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.
    Matched MeSH terms: Particulate Matter/analysis
  8. Associations between air pollutants and peak expiratory flow and fractional exhaled nitric oxide in students
    Adman MA, Hashim JH, Manaf MRA, Norback D
    Int J Tuberc Lung Dis, 2020 02 01;24(2):189-195.
    PMID: 32127103 DOI: 10.5588/ijtld.19.0096
    BACKGROUND: Studies on the effects of outdoor air pollution on the respiratory health of students in tropical countries such as Malaysia are limited.OBJECTIVE: To assess associations between outdoor air pollutants and peak expiratory flow (PEF) and fractional exhaled nitric oxide (FeNO).METHOD: PEF and FeNO levels of 487 students recruited in Melaka and Putrajaya, Malaysia, were measured in April and June 2014. Multiple linear regression with mutual adjustment was used to analyse the associations between exposure to air pollution and health.RESULTS: PEF was significantly associated with ozone for 1-day exposure (β = -13.3 l/min, 95% CI -22.7 to -3.8), carbon monoxide for 2-day exposure (β = -57.2 l/min, 95% CI -90.7 to -23.7) and particulate matter ≦10 μm in diameter for 3-day exposure (β = -6.0 l/min, 95% CI -9.2 to -2.8) and 7-day exposure (β = -8.6 l/min, 95% CI -13.0 to -4.1). Stratified analysis showed that associations between PEF and outdoor air pollutant exposures were similar in students with and without elevated FeNO levels.CONCLUSION: Outdoor air pollution in Malaysia may cause airway obstruction unrelated to eosinophilic airway inflammation among students as measured using FeNO.
    Matched MeSH terms: Particulate Matter/analysis
  9. Trends in atmospheric particulate matter in Dhaka, Bangladesh, and the vicinity
    Rana MM, Sulaiman N, Sivertsen B, Khan MF, Nasreen S
    Environ Sci Pollut Res Int, 2016 Sep;23(17):17393-403.
    PMID: 27230142 DOI: 10.1007/s11356-016-6950-4
    Dhaka and its neighboring areas suffer from severe air pollution, especially during dry season (November-April). We investigated temporal and directional variations in particulate matter (PM) concentrations in Dhaka, Gazipur, and Narayanganj from October 2012 to March 2015 to understand different aspects of PM concentrations and possible sources of high pollution in this region. Ninety-six-hour backward trajectories for the whole dry season were also computed to investigate incursion of long-range pollution into this area. We found yearly PM10 concentrations in this area about three times and yearly PM2.5 concentrations about six times greater than the national standards of Bangladesh. Dhaka and its vicinity experienced several air pollution episodes in dry season when PM2.5 concentrations were 8-13 times greater than the World Health Organization (WHO) guideline value. Higher pollution and great contribution of PM2.5 most of the time were associated with the north-westerly wind. Winter (November to January) was found as the most polluted season in this area, when average PM10 concentrations in Dhaka, Gazipur, and Narayanganj were 257.1, 240.3, and 327.4 μg m(-3), respectively. Pollution levels during wet season (May-October) were, although found legitimate as per the national standards of Bangladesh, exceeded WHO guideline value in 50 % of the days of that season. Trans-boundary source identifications using concentration-weighted trajectory method revealed that the sources in the eastern Indian region bordering Bangladesh, in the north-eastern Indian region bordering Nepal and in Nepal and its neighboring areas had high probability of contributing to the PM pollutions at Gazipur station.
    Matched MeSH terms: Particulate Matter/analysis*
  10. Fulltext Particulate matter (PM2.5) as a potential SARS-CoV-2 carrier
    Nor NSM, Yip CW, Ibrahim N, Jaafar MH, Rashid ZZ, Mustafa N, et al.
    Sci Rep, 2021 01 28;11(1):2508.
    PMID: 33510270 DOI: 10.1038/s41598-021-81935-9
    The rapid spread of the SARS-CoV-2 in the COVID-19 pandemic had raised questions on the route of transmission of this disease. Initial understanding was that transmission originated from respiratory droplets from an infected host to a susceptible host. However, indirect contact transmission of viable virus by fomites and through aerosols has also been suggested. Herein, we report the involvement of fine indoor air particulates with a diameter of ≤ 2.5 µm (PM2.5) as the virus's transport agent. PM2.5 was collected over four weeks during 48-h measurement intervals in four separate hospital wards containing different infected clusters in a teaching hospital in Kuala Lumpur, Malaysia. Our results indicated the highest SARS-CoV-2 RNA on PM2.5 in the ward with number of occupants. We suggest a link between the virus-laden PM2.5 and the ward's design. Patients' symptoms and numbers influence the number of airborne SARS-CoV-2 RNA with PM2.5 in an enclosed environment.
    Matched MeSH terms: Particulate Matter/analysis
  11. Composition and distribution of surfactants around Lake Chini, Malaysia
    Latif MT, Wanfi L, Hanif NM, Roslan RN, Ali MM, Mushrifah I
    Environ Monit Assess, 2012 Mar;184(3):1325-34.
    PMID: 21472384 DOI: 10.1007/s10661-011-2043-5
    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.
    Matched MeSH terms: Particulate Matter/analysis
  12. Composition of heavy metals and airborne fibers in the indoor environment of a building during renovation
    Latif MT, Baharudin NH, Velayutham P, Awang N, Hamdan H, Mohamad R, et al.
    Environ Monit Assess, 2011 Oct;181(1-4):479-89.
    PMID: 21181256 DOI: 10.1007/s10661-010-1843-3
    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.
    Matched MeSH terms: Particulate Matter/analysis*
  13. Source identification of particulate matter in a semi-urban area of Malaysia using multivariate techniques
    Wahid NB, Latif MT, Suan LS, Dominick D, Sahani M, Jaafar SA, et al.
    Bull Environ Contam Toxicol, 2014 Mar;92(3):317-22.
    PMID: 24435135 DOI: 10.1007/s00128-014-1201-1
    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.
    Matched MeSH terms: Particulate Matter/analysis*
  14. Health impact assessment from building life cycles and trace metals in coarse particulate matter in urban office environments
    Othman M, Latif MT, Mohamed AF
    Ecotoxicol Environ Saf, 2018 Feb;148:293-302.
    PMID: 29080527 DOI: 10.1016/j.ecoenv.2017.10.034
    This study intends to determine the health impacts from two office life cycles (St.1 and St.2) using life cycle assessment (LCA) and health risk assessment of indoor metals in coarse particulates (particulate matter with diameters of less than 10µm). The first building (St.1) is located in the city centre and the second building (St.2) is located within a new development 7km away from the city centre. All life cycle stages are considered and was analysed using SimaPro software. The trace metal concentrations were determined by inductively couple plasma-mass spectrometry (ICP-MS). Particle deposition in the human lung was estimated using the multiple-path particle dosimetry model (MPPD). The results showed that the total human health impact for St.1 (0.027 DALY m-2) was higher than St.2 (0.005 DALY m-2) for a 50-year lifespan, with the highest contribution from the operational phase. The potential health risk to indoor workers was quantified as a hazard quotient (HQ) for non-carcinogenic elements, where the total values for ingestion contact were 4.38E-08 (St.1) and 2.59E-08 (St.2) while for dermal contact the values were 5.12E-09 (St.1) and 2.58E-09 (St.2). For the carcinogenic risk, the values for dermal and ingestion routes for both St.1 and St.2 were lower than the acceptable limit which indicated no carcinogenic risk. Particle deposition for coarse particles in indoor workers was concentrated in the head, followed by the pulmonary region and tracheobronchial tract deposition. The results from this study showed that human health can be significantly affected by all the processes in office building life cycle, thus the minimisation of energy consumption and pollutant exposures are crucially required.
    Matched MeSH terms: Particulate Matter/analysis*
  15. Fulltext Overviewing the air quality models on air pollution in Sichuan Basin, China
    Li X, Hussain SA, Sobri S, Md Said MS
    Chemosphere, 2021 May;271:129502.
    PMID: 33465622 DOI: 10.1016/j.chemosphere.2020.129502
    Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some1inspirations for air pollution forecast in other countries with complex terrain.
    Matched MeSH terms: Particulate Matter/analysis
  16. Air pollution, governance quality, and health outcomes: evidence from developing countries
    Ahmad NA, Ismail NW, Sidique SFA, Mazlan NS
    Environ Sci Pollut Res Int, 2023 Mar;30(14):41060-41072.
    PMID: 36630041 DOI: 10.1007/s11356-023-25183-6
    While studies have demonstrated that air pollution can be catastrophic to the population's health, few empirical studies are found in the economic literature because a considerable proportion of the evidence comes from epidemiological studies. Because of the crucial role of governance in the health community, good governance has been a contentious issue in public sector management in recent years. Therefore, the aim of this study is to examine the effects of air pollution and the role of governance on health outcomes. This study employed the generalized method of moment (GMM) estimation techniques to analyse panel data for 72 developing countries from 2010 to 2017. The empirical results confirm that higher PM2.5 and CO2 levels have a detrimental influence on life expectancy and healthy life expectancy, whereas the role of governance has a positive impact on life expectancy and healthy life expectancy. Furthermore, the findings show governance quality plays a role in moderating the negative effect of PM2.5 on health outcomes. The ongoing rise in air pollution has had a significant impact on the health of developing countries. It appears that governance quality has improved health outcomes. The findings have important policy implications, such that strengthening governance can reduce air pollution emissions in developing countries. However, to reduce the health effects of air pollution, developing countries must implement effective environmental development policies and track the implementation and enforcement of such policies.
    Matched MeSH terms: Particulate Matter/analysis
  17. Fulltext Effects of Population Weighting on PM10 Concentration Estimation
    Abdul Shakor AS, Pahrol MA, Mazeli MI
    J Environ Public Health, 2020;2020:1561823.
    PMID: 32351580 DOI: 10.1155/2020/1561823
    Particulate matter with an aerodynamic diameter of 10 μm or less (PM10) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM10 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM10 concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM10 for each state. The calculated PWEL of PM10 concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM10 concentrations in Malaysia ranged from 31 to 73 µg/m3 but became generally lower, ranging from 20 to 72 µg/m3 after population weighting, suggesting that the PM10 population exposure in Malaysia might have been overestimated. PWEL of PM10 distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM10 pollution.
    Matched MeSH terms: Particulate Matter/analysis*
  18. PM2.5 and ozone in office environments and their potential impact on human health
    Othman M, Latif MT, Yee CZ, Norshariffudin LK, Azhari A, Halim NDA, et al.
    Ecotoxicol Environ Saf, 2020 May;194:110432.
    PMID: 32169727 DOI: 10.1016/j.ecoenv.2020.110432
    It is important to have good indoor air quality, especially in indoor office environments, in order to enhance productivity and maintain good work performance. This study investigated the effects of indoor office activities on particulate matter of less than 2.5 μm (PM2.5) and ozone (O3) concentrations, assessing their potential impact on human health. Measurements of indoor PM2.5 and O3 concentrations were taken every 24 h during the working days in five office environments located in a semi-urban area. As a comparison, the outdoor concentrations were derived from the nearest Continuous Air Quality Monitoring Station. The results showed that the average 24 h of indoor and outdoor PM2.5 concentrations were 3.24 ± 0.82 μg m-3 and 17.4 ± 3.58 μg m-3 respectively, while for O3 they were 4.75 ± 4.52 ppb and 21.5 ± 5.22 ppb respectively. During working hours, the range of PM2.5 concentrations were 1.00 μg m-3 to 6.10 μg m-3 while for O3 they were 0.10 ppb to 38.0 ppb. The indoor to outdoor ratio (I/O) for PM2.5 and O3 was <1, thus indicating a low infiltration of outdoor sources. The value of the hazard quotient (HQ) for all sampling buildings was <1 for both chronic and acute exposures, indicating that the non-carcinogenic risks are negligible. Higher total cancer risk (CR) value for outdoors (2.67E-03) was observed compared to indoors (4.95E-04) under chronic exposure while the CR value for acute exposure exceeded 1.0E-04, thus suggesting a carcinogenic PM2.5 risk for both the indoor and outdoor environments. The results of this study suggest that office activities, such as printing and photocopying, affect indoor O3 concentrations while PM2.5 concentrations are impacted by indoor-related contributions.
    Matched MeSH terms: Particulate Matter/analysis*
  19. Fulltext Modeling the Characteristics of Unhealthy Air Pollution Events: A Copula Approach
    Masseran N
    Int J Environ Res Public Health, 2021 08 19;18(16).
    PMID: 34444503 DOI: 10.3390/ijerph18168751
    This study proposes the concept of duration (D) and severity (S) measures, which were derived from unhealthy air pollution events. In parallel with that, the application of a copula model is proposed to evaluate unhealthy air pollution events with respect to their duration and severity characteristics. The bivariate criteria represented by duration and severity indicate their structural dependency, long-tail, and non-identically marginal distributions. A copula approach can provide a good statistical tool to deal with these issues and enable the extraction of valuable information from air pollution data. Based on the copula model, several statistical measurements are proposed for describing the characteristics of unhealthy air pollution events, including the Kendall's τ correlation of the copula, the conditional probability of air pollution severity based on a given duration, the joint OR/AND return period, and the conditional D|S and conditional S|D return periods. A case study based on air pollution data indices was conducted in Klang, Malaysia. The results indicate that a copula approach is beneficial for deriving valuable information for planning and mitigating the risks of unhealthy air pollution events.
    Matched MeSH terms: Particulate Matter/analysis
  20. Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm
    Ting SC, Ismail AR, Malek MA
    J Environ Manage, 2013 Nov 15;129:260-5.
    PMID: 23968912 DOI: 10.1016/j.jenvman.2013.07.022
    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.
    Matched MeSH terms: Particulate Matter/analysis
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