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In this paper, a novel framework and methodology based on hidden semi-Markov models (HSMMs) for high PM 2.5 concentration value prediction is presented. Due to lack of explicit time structure and its short-term memory of past history, a standard hidden Markov model (HMM) has limited power in mod-eling the temporal structures of the prediction problems. To(More)
Ambient PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) samples collected at a rural monitoring site in Bondville, IL on every third day using Interagency Monitoring of Protected Visual Environments (IMPROVE) sampler were analyzed through the application of the positive matrix factorization (PMF). The particulate carbon fractions were(More)
Large-scale studies like the Southeast Michigan Ozone Study (SEMOS) have focused attention on quantifying and spedating inventories for volatile organic compounds (VOCs). One approach for evaluating the accuracy of a VOC emission inventory is the development of a chemical mass balance (CMB) receptor model for ambient non-methane organic compound (NMOC)(More)
The trends in secondary organic aerosol at a remote location are studied using atmospheric fine particulate matter samples collected at Seney National Wildlife Refuge (NWR) in northern Michigan. Detailed analysis of particle-phase organic compounds revealed very low concentrations of primary anthropogenic emissions and relatively high levels of organic di-,(More)
Reformulated gasoline (RFG) contains oxygen additives such as methyl tertiary butyl ether or ethanol. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of carbon monoxide (CO) and volatile organic compounds (VOCs). Because VOCs react with sunlight to form ozone (O3), the Clean Air Act requires severe O3(More)
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