Displaying publications 121 - 140 of 454 in total

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  1. Source apportionment and health risk assessment among specific age groups during haze and non-haze episodes in Kuala Lumpur, Malaysia
    Sulong NA, Latif MT, Khan MF, Amil N, Ashfold MJ, Wahab MIA, et al.
    Sci Total Environ, 2017 Dec 01;601-602:556-570.
    PMID: 28575833 DOI: 10.1016/j.scitotenv.2017.05.153
    This study aims to determine PM2.5concentrations and their composition during haze and non-haze episodes in Kuala Lumpur. In order to investigate the origin of the measured air masses, the Numerical Atmospheric-dispersion Modelling Environment (NAME) and Global Fire Assimilation System (GFAS) were applied. Source apportionment of PM2.5was determined using Positive Matrix Factorization (PMF). The carcinogenic and non-carcinogenic health risks were estimated using the United State Environmental Protection Agency (USEPA) method. PM2.5samples were collected from the centre of the city using a high-volume air sampler (HVS). The results showed that the mean PM2.5concentrations collected during pre-haze, haze and post-haze periods were 24.5±12.0μgm-3, 72.3±38.0μgm-3and 14.3±3.58μgm-3, respectively. The highest concentration of PM2.5during haze episode was five times higher than World Health Organisation (WHO) guidelines. Inorganic compositions of PM2.5, including trace elements and water soluble ions were determined using inductively coupled plasma-mass spectrometry (ICP-MS) and ion chromatography (IC), respectively. The major trace elements identified were K, Al, Ca, Mg and Fe which accounted for approximately 93%, 91% and 92% of the overall metals' portions recorded during pre-haze, haze and post-haze periods, respectively. For water-soluble ions, secondary inorganic aerosols (SO42-, NO3-and NH4+) contributed around 12%, 43% and 16% of the overall PM2.5mass during pre-haze, haze and post-haze periods, respectively. During haze periods, the predominant source identified using PMF was secondary inorganic aerosol (SIA) and biomass burning where the NAME simulations indicate the importance of fires in Sumatra, Indonesia. The main source during pre-haze and post-haze were mix SIA and road dust as well as mineral dust, respectively. The highest non-carcinogenic health risk during haze episode was estimated among the infant group (HI=1.06) while the highest carcinogenic health risk was estimated among the adult group (2.27×10-5).
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/statistics & numerical data*
  2. Energy consumption and CO2 emissions in Iran, 2025
    Mirzaei M, Bekri M
    Environ Res, 2017 Apr;154:345-351.
    PMID: 28161426 DOI: 10.1016/j.envres.2017.01.023
    Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO2 emissions. A system dynamic model was developed in this study to model the energy consumption and CO2 emission trends for Iran over 2000-2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO2 emissions in 2025 will reach 985million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO2 emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO2 emission outlines.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/statistics & numerical data*
  3. Fulltext Investigating the randomness and duration of PM10 pollution using functional data analysis
    Shaadan, N., Deni, S.M., Jemain, A.A.
    Pertanika Journal of Science & Technology, 2018;26(1):299-308.
    MyJurnal
    Information on situation of air pollution is critically needed as input in four disciplines of research including risk management, risk evaluation, environmental epidemiology, as well as for status and trend analysis. Two normal practices were identified to evaluate daily air pollution situation; first, pollution magnitude has been treated as the common indicator, and second, the analysis was often conducted based on hourly average data. However, the information on the magnitude level alone to represent the pollution condition based on a rigid point data such as the average was seen as insufficient. Thus, to fill the gap, this study was conducted based on continuously measured data in the form of curves, which is also known as functional data, whereby pollution duration is emphasised. A statistical method based on curve ranking was used in the investigation. The application of the method at Klang, Petaling Jaya and Shah Alam air quality monitoring stations located in the Klang Valley, Malaysia, has shown that pollution duration decreases as the magnitude increases. Shah Alam has the longest pollution duration at low and medium magnitude levels. Meanwhile, all the three stations experienced quite a similar length of average pollution duration for the high magnitude level, that is, about 2.5 days. It was also shown that the occurrence of PM10 pollution at the area is significantly not random.
    Matched MeSH terms: Air Pollution
  4. Airborne particles in the city center of Kuala Lumpur: Origin, potential driving factors, and deposition flux in human respiratory airways
    Khan MF, Hamid AH, Bari MA, Tajudin ABA, Latif MT, Nadzir MSM, et al.
    Sci Total Environ, 2019 Feb 10;650(Pt 1):1195-1206.
    PMID: 30308807 DOI: 10.1016/j.scitotenv.2018.09.072
    Equatorial warming conditions in urban areas can influence the particle number concentrations (PNCs), but studies assessing such factors are limited. The aim of this study was to evaluate the level of size-resolved PNCs, their potential deposition rate in the human respiratory system, and probable local and transboundary inputs of PNCs in Kuala Lumpur. Particle size distributions of a 0.34 to 9.02 μm optical-equivalent size range were monitored at a frequency of 60 s between December 2016 and January 2017 using an optical-based compact scanning mobility particle sizer (SMPS). Diurnal and correlation analysis showed that traffic emissions and meteorological confounding factors were potential driving factors for changes in the PNCs (Dp ≤1 μm) at the modeling site. Trajectory modeling showed that a PNC <100/cm3 was influenced mainly by Indo-China region air masses. On the other hand, a PNC >100/cm3 was influenced by air masses originating from the Indian Ocean and Indochina regions. Receptor models extracted five potential sources of PNCs: industrial emissions, transportation, aged traffic emissions, miscellaneous sources, and a source of secondary origin coupled with meteorological factors. A respiratory deposition model for male and female receptors predicted that the deposition flux of PM1 (particle mass ≤1 μm) into the alveolar (AL) region was higher (0.30 and 0.25 μg/h, respectively) than the upper airway (UA) (0.29 and 0.24 μg/h, respectively) and tracheobronchial (TB) regions (0.02 μg/h for each). However, the PM2.5 deposition flux was higher in the UA (2.02 and 1.68 μg/h, respectively) than in the TB (0.18 and 0.15 μg/h, respectively) and the AL regions (1.09 and 0.91 μg/h, respectively); a similar pattern was also observed for PM10.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/statistics & numerical data*
  5. Vertical distribution of smoke aerosols over upper Indo-Gangetic Plain
    Vinjamuri KS, Mhawish A, Banerjee T, Sorek-Hamer M, Broday DM, Mall RK, et al.
    Environ Pollut, 2020 Feb;257:113377.
    PMID: 31672363 DOI: 10.1016/j.envpol.2019.113377
    Attenuated backscatter profiles retrieved by the space borne active lidar CALIOP on-board CALIPSO satellite were used to measure the vertical distribution of smoke aerosols and to compare it against the ECMWF planetary boundary layer height (PBLH) over the smoke dominated region of Indo-Gangetic Plain (IGP), South Asia. Initially, the relative abundance of smoke aerosols was investigated considering multiple satellite retrieved aerosol optical properties. Only the upper IGP was selectively considered for CALIPSO retrieval based on prevalence of smoke aerosols. Smoke extinction was found to contribute 2-50% of the total aerosol extinction, with strong seasonal and altitudinal attributes. During winter (DJF), smoke aerosols contribute almost 50% of total aerosol extinction only near to the surface while in post-monsoon (ON) and monsoon (JJAS), relative contribution of smoke aerosols to total extinction was highest at about 8 km height. There was strong diurnal variation in smoke extinction, evident throughout the year, with frequent abundance of smoke particles at lower height (<4 km) during daytime compared to higher height during night (>4 km). Smoke injection height also varied considerably during rice (ON: 0.71 ± 0.65 km) and wheat (AM: 2.34 ± 1.34 km) residue burning period having a significant positive correlation with prevailing PBLH. Partitioning smoke AOD against PBLH into the free troposphere (FT) and boundary layer (BL) yield interesting results. BL contribute 36% (16%) of smoke AOD during daytime (nighttime) and the BL-FT distinction increased particularly at night. There was evidence that despite travelling efficiently to FT, major proportion of smoke AOD (50-80%) continue to remain close to the surface (<3 km) thereby, may have greater implications on regional climate, air quality, smoke transport and AOD-particulate modelling.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis*
  6. Assessing and comparing PM10 pollutant behaviour using functional data approach
    Norshahida Shaadan, Sayang Mohd Deni, Abd Aziz Jemain
    Sains Malaysiana, 2012;41:1335-1344.
    This study highlights the advantage of functional data approach in assessing and comparing the PM10 pollutant behaviour as an alternative statistical approach during and between the two extreme haze years (1997 and 2005) that have been reported in Selangor, state of Malaysia. The aim of the study was to improvise the current conventional methods used in air quality assessment so that any unforeseen implicit information can be revealed and the previous research findings can be justified. An analysis based on the daily diurnal curves in place of discrete point values was performed. The
    analysis results provided evidences of the influence of the change in the climate (due to the El-Nino event), the different levels of different emission sources and meteorological conditions on the severity of the PM10 problem. By means of the cummulative exceedence index and the functional depth method, most of the monitoring stations for the year 2005 experienced the worst day of critical exceedences on the 10th of August, while for the year 1997 it occurred between 13th and 26th September inclusively at different dates among the stations.
    Matched MeSH terms: Air Pollution
  7. A Comparison of Various Imputation Methods for Missing Values in Air Quality Data
    Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda
    Sains Malaysiana, 2015;44:449-456.
    This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to
    select the best method of imputation and to compare whether there was any difference in the methods used between stations
    in Peninsular Malaysia. Missing data for various cases are randomly simulated with 5, 10, 15, 20, 25 and 30% missing.
    Six methods used in this paper were mean and median substitution, expectation-maximization (EM) method, singular
    value decomposition (SVD), K-nearest neighbour (KNN) method and sequential K-nearest neighbour (SKNN) method. The
    performance of the imputations is compared using the performance indicator: The correlation coefficient (R), the index
    of agreement (d) and the mean absolute error (MAE). Based on the result obtained, it can be concluded that EM, KNN
    and SKNN are the three best methods. The same result are obtained for all the eight monitoring station used in this study.
    Matched MeSH terms: Air Pollution
  8. Application of functional data analysis for the treatment of missing air quality data
    Norshahida Shaadan, Sayang Mohd Deni, Abdul Aziz Jemain
    Sains Malaysiana, 2015;44:1531-1540.
    In most research including environmental research, missing recorded data often exists and has become a common problem for data quality. In this study, several imputation methods that have been designed based on the techniques for functional data analysis are introduced and the capability of the methods for estimating missing values is investigated. Single imputation methods and iterative imputation methods are conducted by means of curve estimation using regression and roughness penalty smoothing approaches. The performance of the methods is compared using a reference data set, the real PM10 data from an air quality monitoring station namely the Petaling Jaya station located at the western part of Peninsular Malaysia. A hundred of the missing data sets that have been generated from a reference data set with six different patterns of missing values are used to investigate the performance of the considered methods. The patterns are simulated according to three percentages (5, 10 and 15) of missing values with respect to two different sizes (3 and 7) of maximum gap lengths (consecutive missing points). By means of the mean absolute error, the index of agreement and the coefficient of determination as the performance indicators, the results have showed that the iterative imputation method using the roughness penalty approach is more flexible and superior to other methods.
    Matched MeSH terms: Air Pollution
  9. Time series analysis of surface ozone monitoring records in Kemaman, Malaysia
    Marzuki Ismail, Mohd Zamri Ibrahim, Tg. Azmina Ibrahim, Ahmad Makmon Abdullah
    Sains Malaysiana, 2011;40:1179-1186.
    Time series analysis and forecasting has become a major tool in many applications in air pollution and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). In this study we used Box-Jenkins methodology to build ARIMA model for monthly ozone data taken from an Automatic Air Quality Monitoring System in Kemaman station for the period from 1996 to 2007 with a total of 144 readings. Parametric seasonally adjusted ARIMA (0,1,1) (1,1,2)12 model was successfully applied to predict the long-term trend of ozone concentration. The detection of a steady statistical significant upward trend for ozone concentration in Kemaman is quite alarming. This is likely due to sources of ozone precursors related to industrial activities from nearby areas and the increase in road traffic volume.
    Matched MeSH terms: Air Pollution
  10. 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: Air Pollutants, Occupational/analysis*; Air Pollution, Indoor/analysis*
  11. Fulltext Patterned Membrane in an Energy-Efficient Tilted Panel Filtration System for Fouling Control in Activated Sludge Filtration
    Osman A, Mat Nawi NI, Samsuri S, Bilad MR, Shamsuddin N, Khan AL, et al.
    Polymers (Basel), 2020 Feb 12;12(2).
    PMID: 32059397 DOI: 10.3390/polym12020432
    A membrane bioreactor enhances the overall biological performance of a conventional activated sludge system for wastewater treatment by producing high-quality effluent suitable for reuse. However, membrane fouling hinders the widespread application of membrane bioreactors by reducing the hydraulic performance, shortening membrane lifespan, and increasing the operational costs for membrane fouling management. This study assesses the combined effect of membrane surface corrugation and a tilted panel in enhancing the impact of air bubbling for membrane fouling control in activated sludge filtration, applicable for membrane bioreactors. The filterability performance of such a system was further tested under variable parameters: Filtration cycle, aeration rate, and intermittent aeration. Results show that a combination of surface corrugation and panel tilting enhances the impact of aeration and leads to 87% permeance increment. The results of the parametric study shows that the highest permeance was achieved under short filtration-relaxation cycle of 5 min, high aeration rate of 1.5 L/min, and short switching period of 2.5 min, to yield the permeances of 465 ± 18, 447 ± 2, and 369 ± 9 L/(m2h bar), respectively. The high permeances lead to higher operational flux that helps to lower the membrane area as well as energy consumption. Initial estimation of the fully aerated system yields the energy input of 0.152 kWh/m3, much lower than data from the full-scale references of <0.4 kWh/m3. Further energy savings and a lower system footprint can still be achieved by applying the two-sided panel with a switching system, which will be addressed in the future.
    Matched MeSH terms: Air
  12. 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: Air Pollutants/analysis*; Air Pollution/analysis
  13. Fulltext Analysis of indoor air pollutants checklist using environmetric technique for health risk assessment of sick building complaint in nonindustrial workplace
    Syazwan A, Rafee BM, Juahir H, Azman A, Nizar A, Izwyn Z, et al.
    Drug Healthc Patient Saf, 2012;4:107-26.
    PMID: 23055779 DOI: 10.2147/DHPS.S33400
    To analyze and characterize a multidisciplinary, integrated indoor air quality checklist for evaluating the health risk of building occupants in a nonindustrial workplace setting.
    Matched MeSH terms: Air Pollution, Indoor
  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: Air Pollutants/analysis; Air Pollution, Indoor/analysis
  15. Fulltext Long-Term Exposure to Ambient Air Pollution and Incidence of Postmenopausal Breast Cancer in 15 European Cohorts within the ESCAPE Project
    Andersen ZJ, Stafoggia M, Weinmayr G, Pedersen M, Galassi C, Jørgensen JT, et al.
    Environ Health Perspect, 2017 10 13;125(10):107005.
    PMID: 29033383 DOI: 10.1289/EHP1742
    BACKGROUND: Epidemiological evidence on the association between ambient air pollution and breast cancer risk is inconsistent.

    OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and incidence of postmenopausal breast cancer in European women.

    METHODS: In 15 cohorts from nine European countries, individual estimates of air pollution levels at the residence were estimated by standardized land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE) and Transport related Air Pollution and Health impacts – Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM) projects: particulate matter (PM) ≤2.5μm, ≤10μm, and 2.5–10μm in diameter (PM2.5, PM10, and PMcoarse, respectively); PM2.5 absorbance; nitrogen oxides (NO2 and NOx); traffic intensity; and elemental composition of PM. We estimated cohort-specific associations between breast cancer and air pollutants using Cox regression models, adjusting for major lifestyle risk factors, and pooled cohort-specific estimates using random-effects meta-analyses.

    RESULTS: Of 74,750 postmenopausal women included in the study, 3,612 developed breast cancer during 991,353 person-years of follow-up. We found positive and statistically insignificant associations between breast cancer and PM2.5 {hazard ratio (HR)=1.08 [95% confidence interval (CI): 0.77, 1.51] per 5 μg/m3}, PM10 [1.07 (95% CI: 0.89, 1.30) per 10 μg/m3], PMcoarse[1.20 (95% CI: 0.96, 1.49 per 5 μg/m3], and NO2 [1.02 (95% CI: 0.98, 1.07 per 10 μg/m3], and a statistically significant association with NOx [1.04 (95% CI: 1.00, 1.08) per 20 μg/m3, p=0.04].

    CONCLUSIONS: We found suggestive evidence of an association between ambient air pollution and incidence of postmenopausal breast cancer in European women. https://doi.org/10.1289/EHP1742.

    Matched MeSH terms: Air Pollutants/analysis; Air Pollution/statistics & numerical data*
  16. Diesel engine emission analysis using fuel from diverse emulsification methods
    Sugeng DA, Yahya WJ, Ithnin AM, Abdul Rashid MA, Mohd Syahril Amri NS, Abd Kadir H, et al.
    Environ Sci Pollut Res Int, 2018 Sep;25(27):27214-27224.
    PMID: 30030755 DOI: 10.1007/s11356-018-2760-1
    The focus of this work is to investigate the emission characteristics of a stationary diesel engine while utilizing an emulsion fuel from a novel preparation process. The emulsion preparation was performed in real time without using any surfactant. Instead of mechanically breaking the water down into droplets, the water is delivered thermally, by changing its phase from gas to liquid. Steam is used in this proposed process, where it will be converted into suspended water droplets once it meets colder diesel. The product is called steam-generated water-in-diesel emulsion fuel (S/D). The method is expected to reduce the moving components of a previous surfactant-less system; therefore, reducing costs and increasing the system reliability. The emission characteristics of S/D were compared with EURO 2 diesel (D2), and a conventional emulsion denoted as E10. E10 was prepared using 10% water (volumetric) and SPAN80 as a surfactant. The emission characterizations were carried out based on the exhaust gas of a single cylinder naturally aspirated CI engine fueled with D2, S/D, and E10. Compared to D2, both emulsions significantly reduced the emissions of nitrogen oxides (NOx) (E10 max ↓58.0%, S/D max ↓40.0%) and particulate matter (PM) (E10 max ↓20.0%, S/D max ↓57.0%).
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/prevention & control
  17. Determinants of pollution and the role of the military sector: evidence from a maximum likelihood approach with two structural breaks in the USA
    Solarin SA, Al-Mulali U, Ozturk I
    Environ Sci Pollut Res Int, 2018 Nov;25(31):30949-30961.
    PMID: 30182312 DOI: 10.1007/s11356-018-3060-5
    We investigate the role of military expenditure on emission in USA during the period 1960-2015. To achieve the objectives of this study, two measures of military expenditure are utilised, while several timeseries models are constructed with the gross domestic product (GDP) per capita, population, energy consumption per capita, non-renewable energy consumption per capita, renewable energy consumption per capita, urbanisation, trade openness and financial development serving as additional determinants of air pollution. We also use ecological indicator as an alternative measure of pollution. Moreover, different timeseries methods are utilised including a likelihood-based approach with two structural breaks. The output of this research concluded that all the variables are cointegrated. It is found that military expenditure has mixed impact on CO2 emissions. Real GDP per capita, energy consumption per capita, non-renewable energy consumption per capita, population and urbanisation increase CO2 emissions per capita in the long-run, while renewable energy consumption, financial development and trade openness reduce it. There is also evidence for the mixed role of military expenditure, when ecological footprint is utilised as the environmental degradation index. From the output of this research, few policy recommendations are offered for the examined country.
    Matched MeSH terms: Air Pollutants/analysis; Air Pollution/analysis*
  18. Spatial-temporal variations in surface ozone over Ushuaia and the Antarctic region: observations from in situ measurements, satellite data, and global models
    Nadzir MSM, Ashfold MJ, Khan MF, Robinson AD, Bolas C, Latif MT, et al.
    Environ Sci Pollut Res Int, 2018 Jan;25(3):2194-2210.
    PMID: 29116536 DOI: 10.1007/s11356-017-0521-1
    The Antarctic continent is known to be an unpopulated region due to its extreme weather and climate conditions. However, the air quality over this continent can be affected by long-lived anthropogenic pollutants from the mainland. The Argentinian region of Ushuaia is often the main source area of accumulated hazardous gases over the Antarctic Peninsula. The main objective of this study is to report the first in situ observations yet known of surface ozone (O3) over Ushuaia, the Drake Passage, and Coastal Antarctic Peninsula (CAP) on board the RV Australis during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC'16). Hourly O3 data was measured continuously for 23 days using an EcoTech O3 analyzer. To understand more about the distribution of surface O3 over the Antarctic, we present the spatial and temporal of surface O3 of long-term data (2009-2015) obtained online from the World Meteorology Organization of World Data Centre for greenhouse gases (WMO WDCGG). Furthermore, surface O3 satellite data from the free online NOAA-Atmospheric Infrared Sounder (AIRS) database and online data assimilation from the European Centre for Medium-Range Weather Forecasts (ECMWF)-Monitoring Atmospheric Composition and Climate (MACC) were used. The data from both online products are compared to document the data sets and to give an indication of its quality towards in situ data. Finally, we used past carbon monoxide (CO) data as a proxy of surface O3 formation over Ushuaia and the Antarctic region. Our key findings were that the surface O3 mixing ratio during MASEC'16 increased from a minimum of 5 ppb to ~ 10-13 ppb approaching the Drake Passage and the Coastal Antarctic Peninsula (CAP) region. The anthropogenic and biogenic O3 precursors from Ushuaia and the marine region influenced the mixing ratio of surface O3 over the Drake Passage and CAP region. The past data from WDCGG showed that the annual O3 cycle has a maximum during the winter of 30 to 35 ppb between June and August and a minimum during the summer (January to February) of 10 to 20 ppb. The surface O3 mixing ratio during the summer was controlled by photochemical processes in the presence of sunlight, leading to the depletion process. During the winter, the photochemical production of surface O3 was more dominant. The NOAA-AIRS and ECMWF-MACC analysis agreed well with the MASEC'16 data but twice were higher during the expedition period. Finally, the CO past data showed the surface O3 mixing ratio was influenced by the CO mixing ratio over both the Ushuaia and Antarctic regions. Peak surface O3 and CO hourly mixing ratios reached up to ~ 38 ppb (O3) and ~ 500 ppb (CO) over Ushuaia. High CO over Ushuaia led to the depletion process of surface O3 over the region. Monthly CO mixing ratio over Antarctic (South Pole) were low, leading to the production of surface O3 over the Antarctic region.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis
  19. Regression and multivariate models for predicting particulate matter concentration level
    Nazif A, Mohammed NI, Malakahmad A, Abualqumboz MS
    Environ Sci Pollut Res Int, 2018 Jan;25(1):283-289.
    PMID: 29032528 DOI: 10.1007/s11356-017-0407-2
    The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R 2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis*
  20. Environmental quality indicators and financial development in Malaysia: unity in diversity
    Alam A, Azam M, Abdullah AB, Malik IA, Khan A, Hamzah TA, et al.
    Environ Sci Pollut Res Int, 2015 Jun;22(11):8392-404.
    PMID: 25537287 DOI: 10.1007/s11356-014-3982-5
    Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
    Matched MeSH terms: Air Pollutants/analysis; Air Pollution/analysis
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