Scanning Electrical Mobility Methods for Aerosol Characterization

The scanning electrical mobility measurement is the most common tool used to characterize the size distribution of fine particles in the atmosphere. This thesis develops the methods for retrieving the particle size distribution from scanning electrical mobility measurement data for two systems: (1) the scanning electrical mobility spectrometer (SEMS; also known as the scanning mobility particle sizer, SMPS), which measures particle size distribution ranging from 15 - 1000 nm; (2) the scanning radial opposed migration ion and aerosol classifier (ROMIAC) system, which uses a two-stage condensation particle counter as particle detector to complete the 1 - 20 nm particle size distribution measurements. SEMS / SMPS data have traditionally been inverted to determine the particle size distribution by solving a Fredholm integral equation in which the kernel function is based upon constant-voltage operation of the mobility classifier. The viscous boundary layer within the classifier renders that model invalid. This thesis determines, for the first time, the transfer function for a real differential mobility analyzer (DMA) that is operated in the scanning mode. The flow and electric fields within the instrument were obtained by finite element simulations taking into account its detailed geometry. Brownian dynamics simulations were then used to simulate diffusive particle trajectories within the instrument as the voltage was scanned. There results were coupled with empirically-derived response-time functions for the condensation particle counter that serves as a detector in the SEMS / SMPS to obtain integrated system transfer function that substantially improve the fidelity of the SEMS / SMPS data inversion. This approach was also applied to adaptation of the radial opposed migration ion/aerosol classifier (ROMIAC) for scanning-mode operation. The transfer function obtained through simulation of the scanning ROMIAC was used in the experimental validation of this new measurement method. This new instrument was then used to measure wall loss rates for 1.6 nm to 20 nm particles in the Caltech environmental chamber.</p

Multicomponent new particle formation from sulfuric acid, ammonia, and biogenic vapors

A major fraction of atmospheric aerosol particles, which affect both air quality and climate, form from gaseous precursors in the atmosphere. Highly oxygenated organic molecules (HOMs), formed by oxidation of biogenic volatile organic compounds, are known to participate in particle formation and growth. However, it is not well understood how they interact with atmospheric pollutants, such as nitrogen oxides (NO_x) and sulfur oxides (SO_x) from fossil fuel combustion, as well as ammonia (NH_3) from livestock and fertilizers. Here, we show how NO_x suppresses particle formation, while HOMs, sulfuric acid, and NH3 have a synergistic enhancing effect on particle formation. We postulate a novel mechanism, involving HOMs, sulfuric acid, and ammonia, which is able to closely reproduce observations of particle formation and growth in daytime boreal forest and similar environments. The findings elucidate the complex interactions between biogenic and anthropogenic vapors in the atmospheric aerosol system

Scanning DMA Data Analysis I. Classification Transfer Function

The scanning electrical mobility spectrometer (SEMS; also known as the scanning mobility particle sizer, SMPS) enables rapid particle size distribution measurements with a differential mobility analyzer (DMA)/condensation particle counter (CPC) combination by ramping the classifier voltage, and continuously counting particles into time bins throughout the scan. Inversion of scanning measurements poses a challenge due to the finite time response of the CPC; the distorted data can be deconvoluted to improve the fidelity of size distributions obtained with the SEMS/SMPS. Idealized models of the classification region have shown that, for rapid voltage scans that approach the particle residence time in the DMA, the nondiffusive transfer function deviates from the symmetric one seen at constant voltage. Nonetheless, most SEMS/SMPS data analyses employ the constant voltage transfer function, a result that is valid only for plug flow in the classification region. This article develops the scanning-mode transfer function for the actual geometry of the TSI Model 3081 DMA. Finite element calculations are used to determine the flow and electric fields through the entire DMA. The instantaneous scanning-DMA transfer function for diffusive particles is determined using Brownian dynamics simulations. Comparisons of the results from this simulation of a real instrument to those from the idealized models reveal the shortcomings of prior models in describing the instantaneous scanning-DMA transfer function. A companion paper (Part II) combines this scanning-mode transfer function with response functions for the other components of a SEMS/SMPS measurement system in order to derive the response function for the integrated measurement system

Scanning DMA Data Analysis I. Classification Transfer Function

The scanning electrical mobility spectrometer (SEMS; also known as the scanning mobility particle sizer, SMPS) enables rapid particle size distribution measurements with a differential mobility analyzer (DMA)/condensation particle counter (CPC) combination by ramping the classifier voltage, and continuously counting particles into time bins throughout the scan. Inversion of scanning measurements poses a challenge due to the finite time response of the CPC; the distorted data can be deconvoluted to improve the fidelity of size distributions obtained with the SEMS/SMPS. Idealized models of the classification region have shown that, for rapid voltage scans that approach the particle residence time in the DMA, the nondiffusive transfer function deviates from the symmetric one seen at constant voltage. Nonetheless, most SEMS/SMPS data analyses employ the constant voltage transfer function, a result that is valid only for plug flow in the classification region. This article develops the scanning-mode transfer function for the actual geometry of the TSI Model 3081 DMA. Finite element calculations are used to determine the flow and electric fields through the entire DMA. The instantaneous scanning-DMA transfer function for diffusive particles is determined using Brownian dynamics simulations. Comparisons of the results from this simulation of a real instrument to those from the idealized models reveal the shortcomings of prior models in describing the instantaneous scanning-DMA transfer function. A companion paper (Part II) combines this scanning-mode transfer function with response functions for the other components of a SEMS/SMPS measurement system in order to derive the response function for the integrated measurement system

Design, simulation, and characterization of a radial opposed migration ion and aerosol classifier (ROMIAC)

We present the design, simulation, and characterization of the radial opposed migration ion and aerosol classifier (ROMIAC), a compact differential electrical mobility classifier. We evaluate the performance of the ROMIAC using a combination of finite element modeling and experimental validation of two nearly identical instruments using tetra-alkyl ammonium halide mass standards and sodium chloride particles. Mobility and efficiency calibrations were performed over a wide range of particle diameters and flow rates to characterize ROMIAC performance under the range of anticipated operating conditions. The ROMIAC performs as designed, though performance deviates from that predicted using simplistic models of the instrument. The underlying causes of this non-ideal behavior are found through finite element simulations that predict the performance of the ROMIAC with greater accuracy than the simplistic models. It is concluded that analytical performance models based on idealized geometries, flows, and fields should not be relied on to make accurate a priori predictions about instrumental behavior if the actual geometry or fields deviate from the ideal assumptions. However, if such deviations are accurately captured, finite element simulations have the potential to predict instrumental performance. The present prototype of the ROMIAC maintains its resolution over nearly three orders of magnitude in particle mobility, obtaining sub-20 nm particle size distributions in a compact package with relatively low flow rate operation requirements

Rapid growth of organic aerosol nanoparticles over a wide tropospheric temperature range

Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from −25 °C to 25 °C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the single-digit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward

Multicomponent new particle formation from sulfuric acid, ammonia, and biogenic vapors

A major fraction of atmospheric aerosol particles, which affect both air quality and climate, form from gaseous precursors in the atmosphere. Highly oxygenated organic molecules (HOMs), formed by oxidation of biogenic volatile organic compounds, are known to participate in particle formation and growth. However, it is not well understood how they interact with atmospheric pollutants, such as nitrogen oxides (NO_x) and sulfur oxides (SO_x) from fossil fuel combustion, as well as ammonia (NH_3) from livestock and fertilizers. Here, we show how NO_x suppresses particle formation, while HOMs, sulfuric acid, and NH3 have a synergistic enhancing effect on particle formation. We postulate a novel mechanism, involving HOMs, sulfuric acid, and ammonia, which is able to closely reproduce observations of particle formation and growth in daytime boreal forest and similar environments. The findings elucidate the complex interactions between biogenic and anthropogenic vapors in the atmospheric aerosol system

Rapid growth of organic aerosol nanoparticles over a wide tropospheric temperature range

Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from −25 °C to 25 °C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the single-digit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward

Low-volatility compounds contribute significantly to isoprene secondary organic aerosol (SOA) under high-NO_x conditions

Recent advances in our knowledge of the gas-phase oxidation of isoprene, the impact of chamber walls on secondary organic aerosol (SOA) mass yields, and aerosol measurement analysis techniques warrant reevaluating SOA yields from isoprene. In particular, SOA from isoprene oxidation under high-NOx conditions forms via two major pathways: (1) low-volatility nitrates and dinitrates (LV pathway) and (2) hydroxymethyl-methyl-α-lactone (HMML) reaction on a surface or the condensed phase of particles to form 2-methyl glyceric acid and its oligomers (2MGA pathway). These SOA production pathways respond differently to reaction conditions. Past chamber experiments generated SOA with varying contributions from these two unique pathways, leading to results that are difficult to interpret. This study examines the SOA yields from these two pathways independently, which improves the interpretation of previous results and provides further understanding of the relevance of chamber SOA yields to the atmosphere and regional or global modeling. Results suggest that low-volatility nitrates and dinitrates produce significantly more aerosol than previously thought; the experimentally measured SOA mass yield from the LV pathway is ∼0.15. Sufficient seed surface area at the start of the reaction is needed to limit the effects of vapor wall losses of low-volatility compounds and accurately measure the complete SOA mass yield. Under dry conditions, substantial amounts of SOA are formed from HMML ring-opening reactions with inorganic ions and HMML organic oligomerization processes. However, the lactone organic oligomerization reactions are suppressed under more atmospherically relevant humidity levels, where hydration of the lactone is more competitive. This limits the SOA formation potential from the 2MGA pathway to HMML ring-opening reactions with water or inorganic ions under typical atmospheric conditions. The isoprene SOA mass yield from the LV pathway measured in this work is significantly higher than previous studies have reported, suggesting that low-volatility compounds such as organic nitrates and dinitrates may contribute to isoprene SOA under high-NOx conditions significantly more than previously thought and thus deserve continued study