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• W4307773198 abstract "Particle filtration can effectively reduce indoor concentrations of particulate matter (PM) but may incur high energy use. This study evaluates fixed and adaptive concentration thresholds to automate the operation of filtration systems. Simulated environments were derived from week-long continuous PM measurements from Dylos DC1700 (N = 104) and Alphasense OPC-N2 (N = 100) particle counters deployed in apartments in Toronto. A fixed threshold of 4.0 μg·m-3 resulted in a mean air cleaner runtime of 6.9%-21.0% depending on clean air delivery rate (CADR) and particle sensor, while providing mean concentration reductions of 67%-71% compared to operating the air cleaner constantly (runtime = 100%). In most environments, runtime could be further reduced by raising the fixed threshold while resulting in only a modest decrease in absolute and normalized mean exposure reduction. Using an adaptive threshold derived from a k-means clustering approach generally provided substantial exposure reduction while preventing high runtimes. These results were generally insensitive to cleaning power and the monitor used to measure particle concentrations. Reducing the energy usage of particle filter systems will make them a more viable and sustainable means of improving occupant health." @default.
• W4307773198 created "2022-11-05" @default.
• W4307773198 creator A5041621089 @default.
• W4307773198 creator A5054829861 @default.
• W4307773198 creator A5082718633 @default.
• W4307773198 date "2022-10-01" @default.
• W4307773198 modified "2023-10-17" @default.
• W4307773198 title "Evaluation of fixed and adaptive concentration thresholds for particle filter systems" @default.
• W4307773198 cites W2014025751 @default.
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• W4307773198 doi "https://doi.org/10.1111/ina.13134" @default.
• W4307773198 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36305063" @default.
• W4307773198 hasPublicationYear "2022" @default.
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