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Full-Text Articles in Engineering
Multiple New-Particle Growth Pathways Observed At The Us Doe Southern Great Plains Field Site, Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. Mcmurry, James N. Smith, Jeffery R. Pierce
Multiple New-Particle Growth Pathways Observed At The Us Doe Southern Great Plains Field Site, Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. Mcmurry, James N. Smith, Jeffery R. Pierce
Civil and Environmental Engineering Faculty Publications and Presentations
New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low volatility species, from diameters ∼ 1 to 30–100 nm in order to potentially impact climate. There are currently uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in aerosol-climate modeling. Four main pathways for new-particle growth have been identified: condensation of sulfuric-acid vapor (and associated bases when available), condensation of organic vapors, uptake of organic acids …
Application Of Tree-Structured Regression For Regional Precipitation Prediction Using General Circulation Model Output, Xiangshang Li, David J. Sailor
Application Of Tree-Structured Regression For Regional Precipitation Prediction Using General Circulation Model Output, Xiangshang Li, David J. Sailor
Mechanical and Materials Engineering Faculty Publications and Presentations
This study presents a tree-structured regression (TSR) method to relate daily precipitation with a variety of free-atmosphere variables. Historical data were used to identify distinct weather patterns associated with differing types of precipitation events. Models were developed using 67% of the data for training and the remaining data for model validation. Seasonal models were built for each of 2 US sites: San Francisco, California, and San Antonio, Texas. The average correlation between observed and simulated daily precipitation data series is 0.75 for the training set and 0.68 for the validation set. Relative humidity was found to be the dominant variable …