Author
Lidia Morawska
Other affiliations: University of Surrey, Jinan University, Thomas Jefferson University ...read more
Bio: Lidia Morawska is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Particle number & Ultrafine particle. The author has an hindex of 100, co-authored 746 publications receiving 95412 citations. Previous affiliations of Lidia Morawska include University of Surrey & Jinan University.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments, which was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses.
14 citations
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01 Jan 200314 citations
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TL;DR: The presence of particles was found to affect the attached fraction of radon decay products, in such a way that the particles acted as a sink for radionuclides.
Abstract: In order to investigate the interaction between radon progeny and particles, an experimental campaign was carried out in a radon chamber at the Italian National Institute of Ionizing Radiation Metrology, quantifying the amount of attached and unattached radon daughters present in air, as well as the equilibrium factor in the presence of particles generated through indoor sources. A fixed radon concentration was maintained, while particles were generated using incense sticks, mosquito coils and gas combustion. Aerosols were characterized in terms of particle concentrations and size distributions. Simultaneously, radon concentration and attached/unattached potential alpha energy concentration in the air were continuously monitored by two different devices, based on alpha spectroscopy techniques.
The presence of particles was found to affect the attached fraction of radon decay products, in such a way that the particles acted as a sink for radionuclides. In terms of sources which emit large particles (e.g. incense, mosquito coils), which greatly increase particle surface area concentrations, the Equilibrium Factor was found to double with respect to the background level before particle generation sessions. On the contrary, the radon decay product dynamics were not influenced by gas combustion processes, mainly due to the small surface area of the particles emitted.
14 citations
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TL;DR: The study discovered that e-field measurements were not necessarily a true representation of the ground-level ambient ion/particle charge concentrations and that meteorological factors of temperature, humidity, and wind direction showed no influence on the electrical parameters measured.
Abstract: Along with their essential role in electricity transmission and distribution, some powerlines also generate large concentrations of corona ions. This study aimed at the comprehensive investigation of corona ions, vertical direct current electric field (dc e-field), ambient aerosol particle charge, and particle number concentration levels in the proximity of some high/subtransmission voltage powerlines. The influence of meteorology on the instantaneous value of these parameters and the possible existence of links or associations between the parameters measured were also statistically investigated. The presence of positive and negative polarities of corona ions was associated with variation in the mean vertical dc e-field, ambient ion, and particle charge concentration level. Though these variations increased with wind speed, their values also decreased with distance from the powerlines. Predominately positive polarities of ions were recorded up to a distance of 150 m (with the maximum values recorded 50 m downwind of the powerlines). At 200 m from the source, negative ions predominated. Particle number concentration levels, however, remained relatively constant (10(3) particle cm(-3)), irrespective of the sampling site and distance from the powerlines. Meteorological factors of temperature, humidity, and wind direction showed no influence on the electrical parameters measured. The study also discovered that e-field measurements were not necessarily a true representation of the ground-level ambient ion/particle charge concentrations.
13 citations
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TL;DR: In this article, airborne measurements of particle number concentrations from biomass burning were conducted in the Northern Territory, Australia, during June and September campaigns in 2003, which is the early and the late dry season in that region.
13 citations
Cited by
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TL;DR: Authors/Task Force Members: Piotr Ponikowski* (Chairperson) (Poland), Adriaan A. Voors* (Co-Chair person) (The Netherlands), Stefan D. Anker (Germany), Héctor Bueno (Spain), John G. F. Cleland (UK), Andrew J. S. Coats (UK)
13,400 citations
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TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.
11,809 citations
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Theo Vos1, Amanuel Alemu Abajobir, Kalkidan Hassen Abate2, Cristiana Abbafati3 +775 more•Institutions (305)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
10,401 citations
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TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
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University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).
9,180 citations