Displaying publications 101 - 120 of 476 in total

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  1. Current status of ceramic-based membranes for oxygen separation from air
    Hashim SM, Mohamed AR, Bhatia S
    Adv Colloid Interface Sci, 2010 Oct 15;160(1-2):88-100.
    PMID: 20813344 DOI: 10.1016/j.cis.2010.07.007
    There has been tremendous progress in membrane technology for gas separation, in particular oxygen separation from air in the last 20 years. It provides an alternative route to the existing conventional separation processes such as cryogenic distillation and pressure swing adsorption as well as cheaper production of oxygen with high purity. This review presents the recent advances of ceramic membranes for the separation of oxygen from air at high temperature. It covers the issues and problems with respect to the selectivity and separation performance. The paper also presents different approaches applied to overcome these challenges. The future directions of ceramic-based membranes for oxygen separation from air are also presented.
    Matched MeSH terms: Air/analysis*
  2. A review on factors related to patient comfort experience in hospitals
    Tian Y
    J Health Popul Nutr, 2023 Nov 08;42(1):125.
    PMID: 37941052 DOI: 10.1186/s41043-023-00465-4
    The creation of a welcoming hospital atmosphere is necessary to improve patient wellbeing and encourage healing. The goal of this study was to examine the variables affecting hospitalised patients' comfort. The study procedure included a thorough search of the Web of Science and Scopus databases, as well as the use of software analytic tools to graphically map enormous literature data, providing a deeper understanding of the linkages within the literature and its changing patterns. Insights from a range of disciplines, including engineering, psychology, immunology, microbiology, and environmental science, were included into our study using content analysis and clustering approaches. The physical environment and the social environment are two crucial factors that are related to patient comfort. The study stress the need of giving patient comfort a top priority as they heal, especially by tackling indoor air pollution. Our research also emphasises how important hospital care and food guidelines are for improving patient comfort. Prioritising patients who need specialised care and attention, especially those who have suffered trauma, should be the focus of future study. Future research in important fields including trauma, communication, hospital architecture, and nursing will be built on the findings of this study. To enhance research in these crucial areas, worldwide collaboration between experts from other nations is also advised. Although many studies stress the significance of patient comfort, few have drawn conclusions from a variety of disciplines, including medicine, engineering, immunology, microbiology, and environmental science, the most crucial issue of thoroughly researching the improvement of patient comfort has not been addressed. Healthcare workers, engineers, and other professions will benefit greatly from this study's investigation of the connection between hospital indoor environments and patient comfort.
    Matched MeSH terms: Air Pollution, Indoor*
  3. Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction
    Hoy ZX, Phuang ZX, Farooque AA, Fan YV, Woon KS
    Environ Pollut, 2024 Mar 01;344:123386.
    PMID: 38242306 DOI: 10.1016/j.envpol.2024.123386
    Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine learning models are applied for MSW-related trend prediction to provide insights on future waste generation or carbon emissions trends and assist the formulation of effective low-carbon policies. Yet, the existing machine learning models are diverse and scattered. This inconsistency poses challenges for researchers in the MSW domain who seek to identify and optimize the machine learning techniques and configurations for their applications. This systematic review focuses on MSW-related trend prediction using the most frequently applied machine learning model, artificial neural network (ANN), while addressing potential methodological improvements for reducing prediction uncertainty. Thirty-two papers published from 2013 to 2023 are included in this review, all applying ANN for MSW-related trend prediction. Observing a decrease in the size of data samples used in studies from daily to annual timescales, the summarized statistics suggest that well-performing ANN models can still be developed with approximately 33 annual data samples. This indicates promising opportunities for modeling macroscale greenhouse gas emissions in future works. Existing literature commonly used the grid search (manual) technique for hyperparameter (e.g., learning rate, number of neurons) optimization and should explore more time-efficient automated optimization techniques. Since there are no one-size-fits-all performance indicators, it is crucial to report the model's predictive performance based on more than one performance indicator and examine its uncertainty. The predictive performance of newly-developed integrated models should also be benchmarked to show performance improvement clearly and promote similar applications in future works. The review analyzed the shortcomings, best practices, and prospects of ANNs for MSW-related trend predictions, supporting the realization of practical applications of ANNs to enhance waste management practices and reduce carbon emissions.
    Matched MeSH terms: Air Pollutants/analysis
  4. 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: Air Pollutants/analysis*
  5. Critical assessment of the effectiveness of different dust control measures in a granite quarry
    Saka MB, Hashim MHBM
    J Public Health Policy, 2024 Jun;45(2):212-233.
    PMID: 38600319 DOI: 10.1057/s41271-024-00481-6
    The exposure to respirable crystalline silica found in granite dust presents significant health hazards to quarry workers and nearby communities, including silicosis and various respiratory ailments. This study evaluates the efficacy of various pollution control measures implemented in granite quarries. It aimed to provide a comprehensive critical assessment of the effectiveness of various dust control measures, considering their mechanisms, impact on air quality, and implications for worker health and community welfare. The strategy involved compiling and systematically analysing existing research articles, literature, and industry reports. The investigation identified three primary categories of measures: engineering controls, water-based suppression methods, and technological solutions. The study highlighted the significance of environmental impact and sustainability factors in selecting measures. These factors include water and energy consumption, production of secondary pollutants, long-term ecological effects, regulatory compliance, and cost-effectiveness. Operators and policymakers should utilize integrated, context-specific, inventive, and interdisciplinary strategies to efficiently control particle emissions from granite quarrying.
    Matched MeSH terms: Air Pollution/prevention & control
  6. Fulltext Recent Techniques in Determining the Effects of Climate Change on Depressive Patients: A Systematic Review
    Ab Kader NI, Yusof UK, Khalid MNA, Nik Husain NR
    J Environ Public Health, 2022;2022:1803401.
    PMID: 35978588 DOI: 10.1155/2022/1803401
    Climate change is amongst the most serious issues nowadays. Climate change has become a concern for the scientific community as it could affect human health. Researchers have found that climate change potentially impacts human mental health, especially among depressive patients. However, the relationship is still unclear and needs further investigation. The purpose of this systematic review is to systematically evaluate the evidence of the association between climate change effects on depressive patients, investigate the effects of environmental exposure related to climate change on mental health outcomes for depressive patients, analyze the current technique used to determine the relationship, and provide the guidance for future research. Articles were identified by searching specified keywords in six electronic databases (Google Scholar, PubMed, Scopus, Springer, ScienceDirect, and IEEE Digital Library) from 2012 until 2021. Initially, 1823 articles were assessed based on inclusion criteria. After being analyzed, only 15 studies fit the eligibility criteria. The result from included studies showed that there appears to be strong evidence of the association of environmental exposure related to climate change in depressive patients. Temperature and air pollution are consistently associated with increased hospital admission of depressive patients; age and gender became the most frequently considered vulnerability factors. However, the current evidence is limited, and the output finding between each study is still varied and does not achieve a reasonable and mature conclusion regarding the relationship between the variables. Therefore, more evidence is needed in this domain study. Some variables might have complex patterns, and hard to identify the relationship. Thus, technique used to analyze the relationship should be strengthened to identify the relevant relationship.
    Matched MeSH terms: Air Pollution*
  7. Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data
    Song J, He X, Zhang F, Wang W, Chan NW, Shi J, et al.
    PLoS One, 2024;19(10):e0312388.
    PMID: 39453961 DOI: 10.1371/journal.pone.0312388
    With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.
    Matched MeSH terms: Air Pollutants/analysis
  8. Fulltext Gamma activity concentration from building materials: Estimation of gamma absorption and indoor radon concentration in Katsina State, Nigeria
    Gambo N, Ramli RM, Noor Azman NZ
    PLoS One, 2025;20(3):e0318497.
    PMID: 40073067 DOI: 10.1371/journal.pone.0318497
    In this research, nineteen (19) samples were collected and analyzed with the following objectives: to evaluate the activity concentration of radionuclides, assess gamma absorption, determine indoor radon concentration, and evaluate the public health impact of building materials used in Katsina State, Nigeria. The study aimed to provide critical data that would inform safe construction practices and regulatory compliance. Samples were sourced locally from various quarry sites, while materials such as cement, paint, tiles, and ceiling materials were purchased from local markets. The methodology involved measuring radionuclide activity concentrations using gamma-ray spectroscopy with a Thallium-doped Sodium Iodide (NaI (Tl)) detector, a highly sensitive method suitable for detecting gamma emissions from radionuclides. Radon gas was identified as the primary radiation source. Results revealed varying activity concentrations of radionuclides across different building materials. Most samples, except for Gravel, Brown Clay (Zone A and C), Kaolin, and Fired Clay Bricks, were below the recommended limits for radionuclide. Similarly, for , except for Cement and Thatch, samples were generally below the average value of 35 Bq/kg. However, several samples including Gravel, Paint, Brown Clay (Zones A, B, C), Thatch, Mud Clay, Laterite, Neem tree, Limestone, Fired Clay Bricks, and Gypsum exceeded the average value of 30 Bq/kg for . The overall average activity concentrations across samples were : 232.421, : 11.791, and : 51.1858 all in Bq/kg. The average Radium equivalent and Gamma index was 113.8 Bq/kg and 0.22, respectively, with an alpha index of 0.11. The external and internal hazard indexes averaged 0.2292 and 0.3102, indicating that these materials pose no significant radiological health risk when used in construction, as all values are below international guidelines of 370 Bq/kg and 1 mSv/y. This study concludes with a recommendation for public awareness on the effects of radiation and the need for continued monitoring and regulation of radiation exposure. The significance of this study lies in its contribution to public health and safety, supporting regulatory compliance and helping to prevent potential health risks associated with construction materials.
    Matched MeSH terms: Air Pollutants, Radioactive/analysis
  9. The effect of the digital economy on carbon emissions: an empirical study in China
    Wang C, Qi F, Liu P, Ibrahim H, Wang X
    Environ Sci Pollut Res Int, 2023 Jun;30(30):75454-75468.
    PMID: 37219774 DOI: 10.1007/s11356-023-27742-3
    Under the new development model, the digital economy has become a new engine to promote the green development of the economy and achieve the goal of "double carbon." Based on panel data from 30 Chinese provinces and cities from 2011 to 2021, the impact of the digital economy on carbon emissions was empirically studied by constructing a panel model and a mediation model. The results show that firstly, the effect of the digital economy on carbon emissions is a non-linear inverted "U" shaped relationship, and this conclusion still holds after a series of robustness tests; secondly, the results of the benchmark regression show that economic agglomeration is an essential mechanism through which the digital economy affects carbon emissions and that the digital economy can indirectly suppress carbon emissions through economic agglomeration. Finally, the results of the heterogeneity analysis show that the impact of the digital economy on carbon emissions varies according to the level of regional development, and its effect on carbon emissions is mainly in the eastern region, while its impact on the central and western regions is weaker, indicating that the impact effect is primarily in developed regions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the development strategy of the digital economy according to local conditions to promote a more significant carbon emission reduction effect of the digital economy.
    Matched MeSH terms: Air Pollution*
  10. Fulltext Dynamics of fungal bioaerosols in Kuwait City: An 8-year survey
    AlSaleh A, Marafie M, Dashti H, Ashkanani L
    PLoS One, 2025;20(8):e0329318.
    PMID: 40802603 DOI: 10.1371/journal.pone.0329318
    Fungi are ubiquitous eukaryotic microorganisms that are often implicated in a wide range of diseases. Exposure to fungal bioaerosols is often associated with conditions such as asthma, allergic rhinitis, keratitis, and pneumonitis, among others. This study aims to shed some light on the configuration of airborne culturable fungal genera in the atmosphere of Kuwait City with analysis of seasonal patterns, intra-diurnal variations and correlations with meteorological factors. Outdoor fungal bioaerosols samples were collected twice a day, two times a week, from January 2016 to December 2023 via volumetric active sampling in Al-Sabah Medical District, Kuwait City, Kuwait. The meteorological data were supplied by Kuwait Meteorological Department, Directorate General of Civil Aviation. The rates of fungal bioaerosols remained relatively high during the months of March, April and May, ranging from 269 to 296 CFU/m3. Cladosporium, Aspergillus and Alternaria were the most common fungal genera in the atmosphere, with a prevalence of 49%, 16% and 14%, respectively. Statistically significant differences (p air quality management decisions and provide baseline information for health-care providers.
    Matched MeSH terms: Air Microbiology*
  11. 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
  12. 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
  13. Tilted membrane panel: A new module concept to maximize the impact of air bubbles for membrane fouling control in microalgae harvesting
    Eliseus A, Bilad MR, Nordin NAHM, Putra ZA, Wirzal MDH
    Bioresour Technol, 2017 Oct;241:661-668.
    PMID: 28609754 DOI: 10.1016/j.biortech.2017.05.175
    Microalgae harvesting using membrane technology is challenging because of its high fouling propensity. As an established fouling mitigation technique, efficacy of air bubbles can be improved by maximizing the impact of shear-rates in scouring foulant. In this study, it is achieved by tilting the membrane panel. We investigate the effect of tilting angle, switching period as well as aeration rate during microalgal broth filtration. Results show that higher tilting angles (up to 20°) improve permeability of up to 2.7 times of the vertical panel. In addition, operating a one-sided panel is better than a two-sided panel, in which the later involved switching mode. One-sided membrane panel only require a half of area, yet its performance is comparable with of a large-scale module. This tilted panel can lead to significant membrane cost reductions and eventually improves the competitiveness of membrane technology for microalgae harvesting application.
    Matched MeSH terms: Air
  14. 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*
  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. 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
  18. 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*
  19. 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*
  20. The exposure of children to PM2.5 and dust in indoor and outdoor school classrooms in Kuala Lumpur City Centre
    Othman M, Latif MT, Matsumi Y
    Ecotoxicol Environ Saf, 2019 Apr 15;170:739-749.
    PMID: 30583285 DOI: 10.1016/j.ecoenv.2018.12.042
    It is important to assess indoor air quality in school classrooms where the air quality may significantly influence school children's health and performance. This study aims to determine the concentrations of PM2.5 and dust chemical compositions in indoor and outdoor school classroom located in Kuala Lumpur City Centre. The PM2.5 concentration was measured from 19th September 2017-16th February 2018 using an optical PM2.5 sensor. Indoor and outdoor dust was also collected from the school classrooms and ion and trace metal concentrations were analysed using ion chromatography (IC) and inductively couple plasma-mass spectrometry (ICP-MS) respectively. This study showed that the average indoor and outdoor 24 h PM2.5 was 11.2 ± 0.45 µg m-3 and 11.4 ± 0.44 µg m-3 respectively. The 8 h PM2.5 concentration ranged between 3.2 and 28 µg m-3 for indoor and 3.2 and 19 µg m-3 for outdoor classrooms. The highest ion concentration in indoor dust was Ca2+ with an average concentration of 38.5 ± 35.0 µg g-1 while for outdoor dust SO42- recorded the highest ion concentration with an average concentration of 30.6 ± 9.37 µg g-1. Dominant trace metals in both indoor and outdoor dust were Al, Fe and Zn. Principle component analysis-multiple linear regression (PCA-MLR) demonstrated that the major source of indoor dust was road dust (69%), while soil dominated the outdoor dust (74%). Health risk assessment showed that the hazard quotient (HQ) value for non-carcinogenic trace metals was
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution, Indoor/analysis*
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