WARREN FINLAY Pengarang

Accuracy of recovered moments for narrow mobility distributions obtained with commonly used inversion algorithms for mobility size spectrometers Mark R. Stolzenburg and Peter H. McMurry Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota, USA A B S T R A C T A e r o s o l m o b i l i t y s i z e s p e c t r o m e t e r s a r e c o m m only used to measure size distributions of submicrometer aerosol particles. Commonly used data inversion algorithms for these instruments assume that the measured mobility distribution is broad relative to the DMA transfer function. This article theoretically examines errors that are incurred for input distributions of any width with an emphasis on those with mobility widths comparable to that of the DMA’s transfer function. Our analysis is valid in the limit of slow scan rates, and is applicable to the interpretation of measurements such as those obtained with tandem differential mobility analyzers as well as broader distributions. The analysis leads to expressions that show the relationship between the inverted number concentration, mean size, and standard deviation and true values of those parameters. For narrow distributions (e.g., for a mobility distribution produced by a DMA with a 1:10 aerosol:sheath air flow ratio) under typical operating conditions, number concentrations and mean mobility obtained with inversion algorithms are accurate to within 0.5% and 1.0%, respectively. This corresponds to mean diameter retrieval errors of 1.0% for large particles and 0.5% for small (kinetic regime) particles. The widths (i.e., relative mobility variance) of the inverted distributions, however, significantly exceed the true values. Ambient aerosol composition by infrared spectroscopy and partial least squares in the chemical speciation network: Multilevel modeling for elemental carbon Andrew T. Weakleya, Satoshi Takahamab, Anthony S. Wexlera, and Ann M. Dillnera aAir Quality Research Center, University of California Davis, Davis, California, USA; bENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland A B S T R A C T Fourier transform infrared spectroscopy (FT-IR) has been used to predict elemental carbon (EC) on polytetrafluoroethylene (PTFE) filter samples from the United States Environmental Protection Agency’s Chemical Speciation Network (CSN). This study provides a proof-of-principle demonstration of using multilevel modeling to determine thermal/optical reflectance (TOR) equivalent EC (a.k.a., FT-IR EC) on PTFE samples collected in the CSN. Initially, spectra from nine geographically disperse sites were pooled and calibrated directly to collocated TOR EC measurements. The FT-IR EC quantified in test samples was deemed substandard when judged against an earlier study, e.g., R2 D 0.760 and median absolute deviation (MAD) D 26.7%. Upon scrutinizing each sample’s absolute prediction error and squared Mahalanobis distance, Elizabeth, NJ predictions were found to exhibit atypical systematic errors, motivating the development of a multilevel classification and calibration procedure. Atypical Elizabeth spectra were distinguished from the (typical) CSN spectra by training a partial least-square discriminant analysis. Predicting EC using calibrations dedicated to either atypical or typical samples produced a satisfactory improvement in overall performance (R2 D 0.886, MAD D 19.8%). Analysis of the atypical FT-IR spectra and select TOR thermal fractions suggested that Elizabeth samples contained elevated levels of diesel particulate matter as evidenced by the use of organic nitrogen functional groups for prediction, very low average OC/EC, and minimal charring during TOR speciation. FT-IR EC from the other eight sites was predominately determined by aliphatic C-H, C D C aromatic, and functional groups associated with oxidation. This study provides preliminary confirmation that FT-IR EC may be accurately determined from source-oriented calibrations under a combined classification and calibration methodology. Direct radiative impacts of desert dust on atmospheric water content Christos Spyrou Department of Physics, National and Kapodistrian University of Athens, Athens, Greece A B S T R A C T The direct and indirect radiative impact of naturally produced dust particles infl uences climate from regional to global scale, introducing one of the largest uncertainties in future climate projections. By absorbing and scattering solar radiation, aerosols reduce the amount of energy reaching the earth’ s surface, while at the same time they enhance the greenhouse effect by absorbing and emitting longwave radiation (direct dust effect). In this study an attempt is made to quantify the feedback of this energy redistribution in the atmospheric water content in the Arabian Peninsula (one of the main sources of atmospheric mineral dust globally). To this end the SKIRON/dust modeling system was used for 2 years (2014– 2015) and two sets of simulations were performed: in the fi rst one the dust particles exert no feedback on the radiative transfer due to dust particles (control run), while in the second set dust interacts with radiation (direct radiative effect). Both simulations have been evaluated in their ability to describe the impacts on surface humidity, with the simulations including the dust feedback showing improved results. These direct feedbacks lead to an increase in the mass of water in the atmospheric column that can reach a maximum daily average of 0.5 g per kg of dry air. Water vapor is the most important greenhouse gas and through this process dust enhances its own greenhouse effect, further increasing the surface temperature and humidity, making life difficult for people living in an already harsh desert climate. Experimental investigations of particle formation from propellant and solvent droplets using a monodisperse spray dryer James W. Iveya, Pallavi Bhambria, Tanya K. Church b, David A. Lewis b, and Reinhard Vehringa aDepartment of Mechanical Engineering, University of Alberta, Edmonton, Alberta, Canada; bChiesi Limited, Chippenham, Wiltshire, United Kingdom A B S T R A C T Experimental studies of particle formation from solution droplets were conducted using a newly developed monodisperse spray drying process. Solutes beclomethasone dipropionate and caffeine were dissolved in ethanol, pressurized hydrofluoroalkane propellant 134a, and mixtures thereof. Solutions were atomized into monodisperse microdroplets using a custom droplet generator installed in a laboratory scale spray dryer, enabling drying and collection of the resulting monodisperse microparticles. The effects of droplet diameter, solution concentration, solvent composition, and drying rate on the physical properties of the dried particles were evaluated. Particle morphology and size were assessed using ultramicroscopy and image analysis of micrographs. Extent of crystallinity and polymorphism were investigated using Raman spectroscopy. The drying temperature was found to have a large effect on the morphology of amorphous beclomethasone dipropionate particles. Particles dried near room temperature were spheroidal to ellipsoidal with prevalent surface concavities and evidence of shell buckling; increasing the drying temperature for fixed droplet size and composition resulted in a transition to more spherical, smooth-surfaced particle morphologies. Crystalline caffeine microparticles were made up of assemblies of multiple crystallites. The measured length and breadth of these crystallites was found to be correlated with the time available for crystal nucleation and growth as calculated using a particle formation model. The results highlight the abilities and limitations of currently available particle formation models in elucidating the relationships between the size, composition, and evaporation rate of drying solution droplets and the physical properties of the resulting particles. The work demonstrates the suitability of monodisperse spray drying as an experimental technique for investigating the fundamentals of particle formation from solution droplets. Laboratory evaluation of species-dependent relative ionization effi ciencies in the Aerodyne Aerosol Mass Spectrometer Wen Xu a, Andrew Lambea, Philip Silvaa,b,*, Weiwei Hu c,d, Timothy Onasch a, Leah Williamsa, Philip Croteaua, Xuan Zhanga,**, Lindsay Renbaum-Wolffa,b, Edward Fortnera, Jose L. Jimenez c,d, John Jaynea, Douglas Worsnop a, and Manjula Canagaratnaa aCenter for Aerosol & Cloud Chemistry, Aerodyne Research, Inc., Billerica, Massachusetts, USA; bDepartment of Chemistry, Boston College, Chestnut Hill, Massachusetts, USA; cDepartment of Chemistry, University of Colorado, Boulder, Colorado, USA; dCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA A B S T R A C T Mass concentrations calculated from Aerodyne’s aerosol mass spectrometers depend on particle collection efficiency (CE) and relative ionization efficiency (RIE, relative to the primary calibrant ammonium nitrate). We present new laboratory RIE measurements for a wide range of organic aerosol species (RIEOA). An improved laboratory RIE calibration protocol with size and mass selection of calibrant particles and a light scattering-based detection of CE is used. Simpler calibrations of alcohol RIEs using binary mixtures with NH4NO3 are demonstrated. Models that account for only thermal velocity and electron ionization of vaporized molecules do not reproduce RIEOA measurements, confirming that other processes are significant. The relationship between RIEOA and average carbon oxidation state (OSC), a metric used to describe atmospheric OA, is investigated. An average RIEOA of 1.6 § 0.5 (2s) is found for ¡1.0 < OSC < 0.5, a range consistent with most ambient OA except hydrocarbon-like organic aerosol (HOA) and cooking organic aerosol (COA). RIEOA from 2 to 7 are found for OSC below and above this range. The RIEOA typically used for ambient OA (1.4 § 0.3) is within the laboratory RIEOA measurement uncertainty of oxidized organic species, but is a factor of 2 to 5 lower than that of reduced species. Such biases in OA mass concentrations have not been observed in published field analyses. Chemically reduced ambient OA may have composition, phase states, or compensating CE effects that are not mimicked well in the laboratory. This work highlights the need for further ambient OA studies to better constrain the composition dependence of ambient RIEOA, and the need to always calibrate with the OA under study for laboratory experiments. Measuring aerosol size distributions with the aerodynamic aerosol classifi er Tyler J. Johnsona, Martin Irwinb, Jonathan P. R. Symondsb, Jason S. Olfertc, and Adam M. Boiesa aUniversity of Cambridge, Cambridge, United Kingdom; bCambustion Ltd., Cambridge, United Kingdom; cDepartment of Mechanical Engineering, University of Alberta, Edmonton, Alberta, Canada A B S T R A C T The Aerodynamic Aerosol Classifier (AAC) is a novel instrument that selects aerosol particles based on their relaxation time or aerodynamic diameter. Additional theory and characterization is required to allow the AAC to accurately measure an aerosol’s aerodynamic size distribution by stepping while connected to a particle counter (such as a Condensation Particle Counter, CPC). To achieve this goal, this study characterized the AAC transfer function (from 32 nm to 3 mm) using tandem AACs and comparing the experimental results to the theoretical tandem deconvolution. These results show that the AAC transmission efficiency is 2.6–5.1 times higher than a combined Krypton-85 radioactive neutralizer and Differential Mobility Analyzer (DMA), as the AAC classifies particles independent of their charge state. However, the AAC transfer function is 1.3–1.9 times broader than predicted by theory. Using this characterized transfer function, the theory to measure an aerosol’s aerodynamic size distribution using an AAC and particle counter was developed. The transfer function characterization and stepping deconvolution were validated by comparing the size distribution measured with an AAC-CPC system against parallel measurements taken with a Scanning Mobility Particle Sizer (SMPS), CPC, and Electrical Low Pressure Impactor (ELPI). The effects of changing AAC classifier conditions on the particle selected were also investigated and found to be small (<1.5%) within its operating range. Simulated sensitivity of secondary organic aerosol in the South Coast Air Basin of California to nitrogen oxides and other chemical parameters Robert J. Griffi na, Matthew L. Dawsonb, and Donald Dabdubb aDepartment of Civil and Environmental Engineering, Rice University, Houston, Texas, USA; bDepartment of Mechanical and Aerospace Engineering, University of California—Irvine, Irvine, California, USA A B S T R A C T Sensitivity of secondary organic aerosol (SOA) concentrations in the South Coast Air Basin (SoCAB) of California to nitrogen oxide (NOx) emission is simulated using gas-phase chemistry and gas-particle partitioning modules. These modules are implemented into a three-dimensional air quality model applied for high-pollution summer meteorology and 2008 emissions. To test sensitivity, Nox emissions in all locations and at all times are scaled by factors ranging from 0.1 to 10.0 in separate model runs. The basin-wide average SOA concentration exhibits a ‘turnover’ NOx emission multiplicative factor, above and below which the average SOA concentration decreases. For the entire SoCAB, this critical NOx emission factor is »0.3; while the magnitude of SOA concentrations changes with time, this peak value ( »0.2–0.3) appears to be relatively independent of the hour of the simulated day. When considering individual locations within the SoCAB, this peak factor shows a slightly broader range. Projected emissions for 2023 indicate a decrease in basin-average SOA concentration; the response at individual locations, however, can be either positive or negative, indicating the need for location-specific considerations. Ensembles of module simulations based on parameter values selected using efficient sampling techniques (Latin Hypercube method) are used to identify parameters to which SOA predictions are significantly sensitive. Total SOA predictions are most sensitive (in no particular order) to concentrations of O3, unsaturated species formed from the gas-phase oxidation of monoaromatic compounds, and substituted products from long-chain alkane oxidation. Secondary inorganic aerosol species, likely through influencing aerosol liquid water, control at least partially the formation of SOA upwind. In addition, the rate at which unsaturated bicyclic oxidation products of monoaromatic compounds are oxidized by hydroxyl radical impacts significantly SOA prediction. These findings emphasize the need for consideration of long-chain alkanes and monoaromatic species when designing emission control strategies.