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Identifying and Evaluating Air Filtration Methods for Personal Protection from Airborne Particulate Matter

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Date
2011-04-29
Author
Ramadan, Ramsey
Advisor
Vandenberg, John
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Abstract
Air pollution is a major environmental health risk in both developing and developed countries. According to the World Health Organization (WHO), air pollution is responsible for more than two million deaths worldwide every year. The WHO recognizes that particulate matter (PM) is the most dangerous among the various air pollutants and affects more people than any other. Exposure to fine particulate matter is dominated by emissions from anthropogenic point sources such as from vehicles, industry and power plants; for larger, coarse particulate matter the major sources are from road dust, construction and wind-blown dust from agricultural areas. Most approaches to reduce exposure involve controls on the emitting sources. Though this approach reduces the health risks, it cannot sufficiently protect our sensitive populations from point source PM, especially fine PM. Air filtration devices such as personal face mask filters are rapidly implementable solutions to reduce fine PM exposure at the point of contact. Most personal face mask filters are designed as single-use devices for the medical and chemical industries; whereas an air filter designed for the general population must allow for multiple uses and protection from PM. Given a set of criteria, the conceptual personal filtration device was evaluated in a case study of China where, if the devices were adopted by the population, health costs associated with fine PM exposure are estimated to be reduced by up to 87% ($ 223 billion).
Type
Master's project
Department
Nicholas School of the Environment and Earth Sciences
Subject
Air
Filtration
Particulate matter (PM)
Efficiency
Permalink
https://hdl.handle.net/10161/3706
Citation
Ramadan, Ramsey (2011). Identifying and Evaluating Air Filtration Methods for Personal Protection from Airborne Particulate Matter. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/3706.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

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