Regularized Inversion of Aerosol Hygroscopic Growth Factor Probability Density Function: Application to Humidity-Controlled Fast Integrated Mobility Spectrometer Measurements

Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-squares methods are the most widely used algorithms for inverting the GF-PDF from measurements of the humidified tandem differential mobility analyzer (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least-squares methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert the aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey\u27s iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-squares methods, are quantitatively compared. The result shows that Twomey\u27s method generally outperforms other inversion methods. The capabilities of Twomey\u27s method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated

Measurement Report: Long-Range Transport Patterns into the Tropical Northwest Pacific during the CAMP2Ex Aircraft Campaign: Chemical Composition, Size Distributions, and the Impact of Convection

The tropical Northwest Pacific (TNWP) is a receptor for pollution sources throughout Asia and is highly susceptible to climate change, making it imperative to understand long-range transport in this complex aerosol-meteorological environment. Measurements from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex; 24 August to 5 October 2019) and back trajectories from the National Oceanic and Atmospheric Administration Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) were used to examine transport into the TNWP from the Maritime Continent (MC), peninsular Southeast Asia (PSEA), East Asia (EA), and the West Pacific (WP). A mid-campaign monsoon shift on 20 September 2019 led to distinct transport patterns between the southwest monsoon (SWM; before 20 September) and monsoon transition (MT; after 20 September). During the SWM, long-range transport was a function of southwesterly winds and cyclones over the South China Sea. Low- (high-) altitude air generally came from MC (PSEA), implying distinct aerosol processing related to convection and perhaps wind shear. The MT saw transport from EA and WP, driven by Pacific northeasterly winds, continental anticyclones, and cyclones over the East China Sea. Composition of transported air differed by emission source and accumulated precipitation along trajectories (APT). MC air was characterized by biomass burning tracers while major components of EA air pointed to Asian outflow and secondary formation. Convective scavenging of PSEA air was evidenced by considerable vertical differences between aerosol species but not trace gases, as well as notably higher APT and smaller particles than other regions. Finally, we observed a possible wet scavenging mechanism acting on MC air aloft that was not strictly linked to precipitation. These results are important for understanding the transport and processing of air masses with further implications for modeling aerosol lifecycles and guiding international policymaking to public health and climate, particularly during the SWM and MT

Arctic warming by abundant fine sea salt aerosols from blowing snow

The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m−2 under cloudy sky conditions

Optimizing the Activation Efficiency of Sub-3 Nm Particles in a Laminar Flow Condensation Particle Counter: Model Simulation

The measurement of airborne particles with sizes below 3 nm is critical, as it helps the understanding of atmospheric nucleation and elucidates important particle synthesis mechanisms in the gas phase. Condensation particle counters (CPCs) have been widely used to measure the concentration of aerosols. However, it is challenging for the CPCs to measure particles below 3 nm due to the insufficient activation of these particles via vapor condensation. Methods have been proposed to increase the saturation ratio of the condensing vapor to promote the detection efficiency of sub-3 nm particles in the CPCs. Different working fluids also make a considerable impact on particle detection. Given the various types of parameters and the wide range of values these parameters can take, modeling studies are needed in searching for the optimal operating conditions of a CPC. In this work, we simulated the sub-3 nm particle activation and growth in a laminar flow CPC using COMSOL Multiphysics®, which has the advantages of simulating complex flow conditions and interfacing with post-processing software such as MATLAB. Our simulation incorporates the influence of temperature-dependent air and working fluid properties on particle activation and the impact of latent heat and non-continuum effects on droplet growth. Following the method introduced by Iida, Stolzenburg and McMurry (2009), particle activation is optimized for a given working fluid and condenser temperature by adjusting the saturator temperature to achieve a homogeneous nucleation rate of 1 s-1. The results, characterized by Dkel,0 (largest particle size that cannot be activated) and Dkel,50 (particle size activated with 50% efficiency), were compared against the analytical Graetz model used in Stolzenburg (1988). Our COMSOL simulations show that glycerine, diethylene glycol, ethylene glycol, 2-aminoethanol, and dimethyl phthalate are the best five working fluids achieving the smallest Dkel,50 among 45 commonly used solvents. The Dkel,50 values simulated by COMSOL under a condenser temperature of 10 °C for the five working fluids are 1.56, 1.88, 1.92, 1.98, and 2.10 nm, respectively, while the values simulated by the analytical Graetz solution differ slightly from 0.4% to 0.7%. The results demonstrate excellent agreement between these two simulation methods. For the five best working fluids activating the same 2.1 nm particles, the droplets can grow to sizes detectable by a second-stage CPC. The sensitivity of the COMSOL solution to the inlet condition and the form of convective diffusion equations is investigated. We also discussed the effect of CPC operating conditions, such as the condenser geometry and flow conditions, on particle activation for optimizing the performance of the CPC in detecting sub-3 nm particles

Regularized Inversion of Aerosol Hygroscopic Growth Factor Probability Density Function: Application to Humidity-Controlled Fast Integrated Mobility Spectrometer Measurements

Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-squares methods are the most widely used algorithms for inverting the GF-PDF from measurements of the humidified tandem differential mobility analyzer (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least-squares methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert the aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey\u27s iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-squares methods, are quantitatively compared. The result shows that Twomey\u27s method generally outperforms other inversion methods. The capabilities of Twomey\u27s method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated

On the Performance of an Aerosol Electrometer with Enhanced Detection Limit

An aerosol electrometer with enhanced detection limit was developed for measuring the collected particles electrical current ranging from −50 pA to 50 pA with no range switching necessary. The detection limit was enhanced by suppressing the electric current measurement noise and improving the detection efficiency. A theoretical model for the aerosol electrometer has been established to investigate the noise effect factors and verified experimentally. The model showed that the noise was a function of ambient temperature, and it was affected by the characteristics of feedback resistor and operational amplifier simultaneously. The Faraday cup structure of the aerosol electrometer was optimized by adopting a newly designed cup-shaped metal filter which increased the surface area of the cup; thus the particle interception efficiency was improved. The aerosol electrometer performance-linearity, noise and the particle detection efficiency, were evaluated experimentally. When compared with TSI-3068B, a 99.4% ( R 2 ) statistical correlation was achieved. The results also showed that the root mean square noise and the peak-to-peak noise were 0.31 fA and 1.55 fA, respectively. The particle detection efficiency was greater than 99.3% when measuring particle diameter larger than 7.0 nm

Rapid measurement of RH-dependent aerosol hygroscopic growth using a humidity-controlled fast integrated mobility spectrometer (HFIMS)

The ability of aerosol particles to uptake water (hygroscopic growth) is an important determinant of aerosol optical properties and radiative effects. Aerosol hygroscopic growth is traditionally measured by humidified tandem differential mobility analyzers (HTDMA), in which size-selected dry particles are exposed to elevated relative humidity (RH), and the size distribution of humidified particles are subsequently measured using a scanning mobility particle sizer. As a scanning mobility particle sizer can measure only one particle size at a time, HTDMA measurements are time-consuming, and ambient measurements are often limited to a single RH level. Pinterich et al. (2017b) showed that fast measurements of aerosol hygroscopic growth are possible using a humidity-controlled fast integrated mobility spectrometer (HFIMS). In HFIMS, the size distribution of humidified particles is rapidly captured by a water-based fast integrated mobility spectrometer (WFIMS), leading to a factor of ~10 increase in measurement time resolution. In this study we present a prototype HFIMS that extends fast hygroscopic growth measurements to a wide range of atmospherically relevant RH values, allowing for more comprehensive characterizations of aerosol hygroscopic growth. A dual-channel humidifier consisting of two humidity conditioners in parallel is employed such that aerosol RH can be quickly stepped among different RH levels by sampling from alternating conditioners. The measurement sequence is also optimized to minimize the transition time between different particle sizes. The HFIMS is capable of measuring aerosol hygroscopic growth of six particle diameters under five RH levels ranging from 20 % to 85 % (30 separate measurements) every 25 min. The performance of this HFIMS is characterized and validated using laboratory-generated ammonium sulfate aerosol standards. Measurements of ambient aerosols are shown to demonstrate the capability of HFIMS to capture the rapid evolution of aerosol hygroscopic growth, and its dependence on both size and RH