Effects of Temperature and Relative Humidity on Filter Loading by Simulated Atmospheric Aerosols & COVID-19 Related Mask and Respirator Filtration Study
2020-08
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Effects of Temperature and Relative Humidity on Filter Loading by Simulated Atmospheric Aerosols & COVID-19 Related Mask and Respirator Filtration Study
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2020-08
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This dissertation focuses on the effects of temperature and relative humidity on filter loading by simulated atmospheric aerosols and COVID-19 related mask and respirator filtration study. There are two objectives of this dissertation: the first one is to fill the gap between lab filter testing and actual filter operation, and the second one is to help curb the COVID-19 spreading from filtration perspective. Filter life is an important criterion to evaluate air filters, and longer life is preferred before reaching the replacing pressure. Filter life could be evaluated in the laboratory by loading lab-generated contaminants on the test filter sample, typically at high concentrations to accelerate the testing process. However, the current filter loading testing protocols and standards use the non-hygroscopic micron dust or less-hygroscopic lab salt particles (NaCl, KCl) as challenging particles. Meanwhile, the testing environment, especially relative humidity, have not been strictly controlled. With increasingly more stringent pollution control requirement in place in past decades, sub-micron particles are becoming more important, such as inorganic salts ((NH4)2SO4, NH4NO3), soot, organic compounds, which are more hygroscopic than lab salts. Therefore, there have been discrepancies between lab filter testing and actual filter operation, including challenging particle species, testing relative humidity and temperature. It is vital to understand how air filters perform in the actual environment so that both filter recommendations and optimization could be done confidently and wisely. This dissertation thrives on the effects of temperature and relative humidity on filter loading by simulated atmospheric aerosols. A Lab-simulated Ambient Environment Air Filter Test Rig was firstly built with controlled temperature and relative humidity testing environment, simulated atmospheric aerosols generation, and advanced filter testing capability. The testing temperature and relative humidity are well controlled to simulate different filter operating conditions. The techniques to generate atmospheric aerosols were developed, including inorganic salt generation and dry/wet state control at various testing relative humidities, fresh soot and aged soot by organic compounds coating. The versatile atmospheric aerosols generation techniques enable filter loading tests with “real” atmospheric aerosols rather than lab salts. The temperature effect on filter loading was studied, and it is found that temperature is a minor factor affecting filter life, compared to relative humidity. The relative humidity effect on filter loading was then investigated with conventional cellulose filter and nanofiber coated cellulose filter. The testing relative humidity covered from below salts’ efflorescence relative humidity to above their deliquescence relative humidity, and both dry and wet particles at different relative humidities were loaded on test filters. It is found that, in general, the higher the loading relative humidity, the longer the filter life. But the filter life also depends on the filter structure and challenging particle state. Filtration efficiency evolution was also studied. To better simulate atmospheric aerosols, test filters were loaded with (NH4)2SO4 and NH4NO3 mixture particles and soot aged by organic compounds coating separately at various relative humidities. It is found that relative humidity is a very strong factor affecting filter life, particularly for salt mixtures. There is a discrepancy between fresh soot and aged soot, and aged soot should be used in filter loading since it can represent atmospheric soot more realistically. These studies reveal that actual filter operation with atmospheric aerosols is complex, and the filter recommendation should be carefully made, and the actual operating conditions should be considered as much as possible. The above research was conducted at constant loading relative humidity, which is not possible in actual filter operation. Hence the effect of relative humidity change on hygroscopic salt loaded filters was studied. This study broadens the understanding of the loaded filter behavior in varying relative humidity which could benefit potential techniques to prolong filter life or to clean filters by reverse pulsing. The ultimate goal of the first objective is to recommend filters based on operating locations. Whereas it is still challenging to achieve filter selection and optimization based on all research mentioned above. We developed and established a Global Air Pollutant/Meteorological Condition Database and a Smart Sensor for Filter Performance Monitoring System. For a city of interest, this Database can report historical pollutants speciation and concentration, historical monthly average temperature and RH, and pollutant concentration trend in past years. The Smart Sensor could monitor filtration efficiency, the differential pressure across the filter, and operating temperature, RH in real-time. With millions of the Smart sensor installations, massive filter operation data could be received for machine learning and big data analysis. With the aid of the Database and Smart Sensor, the above experiment conclusions could be utilized to better test and recommend filters based on operating locations. COVID-19 becomes a global challenge in 2020. Two mask and respirator studies were carried out to help curb the spread of COVID-19 and relieve the severe shortage of masks and respirators. The first one compared common materials that have the potential to be used as alternative masks for the public in daily protection. The second one aimed to evaluate the effect of decontamination of the commercial and alternative mask and respirator materials from the filtration perspective.
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University of Minnesota Ph.D. dissertation.September 2020. Major: Mechanical Engineering. Advisor: David Pui. 1 computer file (PDF); xvi, 238 pages.
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