Determination of particle number concentration for biological particles using AF4-MALS: Dependencies on light scattering model and refractive index
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In support of the Holistic Interactions of Shallow Clouds, Aerosols, and Ecosystems (HI-SCALE) project to study new particle formation in the atmosphere, a pair of custom water condensation particle counters were provided to the second intensive field campaign, from mid-August through mid-September 2017, at the U.S. Department of Energy Southern Great Plains Atmospheric Radiation Measurement (ARM) Climate Research Facility observatory. These custom instruments were developed by Aerosol Dynamics, Inc. (Hering et al. 2017) to detect particles into the nanometer size range. Referred to as “versatile water condensation particle counter (vWCPC)”, they are water-based, laminar-flow condensational growth instruments whose lower particle size threshold can be set based on user-selected operating temperatures. For HI-SCALE, the vWCPCs were configured to measure airborne particle number concentrations in the size range from approximately 2nm to 2μm. Both were installed in the particle sizing system operated by Chongai Kuang of Brookhaven National Laboratory (BNL). One of these was operated in parallel to a TSI Model 3776, upstream of the mobility particle sizing system, to measure total ambient particle concentrations. The airborne particle concentration data from this “total particle number vWCPC” (Ntot-vWCPC) system has been reported to the ARM database. The data are reported with one-second resolution. The second vWCPC was operated in parallel with the BNL diethylene glycol instrument to count particles downstream of a separate differential mobility size analyzer. Data from this “DMA-vWCPC” system was logged by BNL, and will eventually be provided by that laboratory.
In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved Na product to in situ Na data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11 separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter Na agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged Na. We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged Na and the lidar + polarimeter vertically resolved Na are of similar magnitude and represent a significant improvement upon current remote sensing estimates of Na.
In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved N(a) product to in situ N(a) data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter N(a) agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged N(a). We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged N(a) and the lidar + polarimeter vertically resolved N(a) are of similar magnitude and represent a significant improvement upon current remote sensing estimates of N(a).
A major challenge in assessing the impact of aerosols on climate change is to understand how human activities change aerosol loading and properties relative to the pristine-preindustrial baseline. Here we combine chemical transport simulation and field measurements to investigate the effect of anthropogenic pollution from an isolated metropolis on particle number concentration over the preindustrial-like Amazon rainforest through various new-particle formation (NPF) mechanisms and primary particle emissions. To represent organic-mediated NPF, we employ a state-of-the-art model that systematically simulates the formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes, and further update the model to improve organic NPF simulations under human-influenced conditions. Results show that urban pollution from the metropolis increases particle number concentration by a factor of 5–25 over the downwind region (within 200 km from city center) compared to background conditions. Overall, our model indicates that NPF contributes over 70% of the total particle number in the downwind region except immediately adjacent to the sources. Among different NPF mechanisms, the ternary NPF involving organics and sulfuric acid overwhelmingly dominates. The improved understanding of particle formation mechanisms will help better quantify anthropogenic aerosol forcing from pristine-preindustrial times to present day.
The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.
Highlights: • Differential susceptibility to air pollution effects has been reported, but evidence is limited. • The Puerto Rican population may be susceptible based on high prevalence of chronic conditions. • Particle number is associated with C-reactive protein, but only among women. • The results show impacts of similar magnitude to other studies. Air pollution has been linked to adverse cardiovascular outcomes; however, susceptibility may vary by population. Puerto Rican adults living in the US may be a susceptible group due to a high rate of adverse cardiovascular events. We evaluated the effect of changes in ambient particle number concentration (PNC, a measure of ultrafine particles) and effects on biomarkers of cardiovascular risk in the Boston Puerto Rican Health Study (BPRHS), a longitudinal cohort (n = 1499). Ambient PNC was measured at a fixed site between 2004 and 2013 and daily mean concentrations were used to construct PNC metrics, including lags of 0, 1 and 2 days and moving averages (MAs) of 3, 7 and 28 days. We examined the association of each metric with C-reactive protein (CRP) and blood pressure. Each model included subject-specific random intercepts to account for multiple measurements. An interquartile range (IQR) increase in PNC was associated with CRP for all metrics, notably a 3-day increase in PNC was associated with a 7.1% (95% CI: 2.0%, 12.2%) increase in CRP. Significant associations with CRP were seen in women, but not men; with current and former (but not non-) smokers; participants younger (but not older) than 65 y; those without diabetes (but not with), and those with (but not without), hypertension. Our study extends knowledge about the health effects of air pollution to a vulnerable population that has been understudied.
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Abstract Eleven years (by publication) years after the development and application of the control banding (CB) Nanotool for the qualitative assessment and control of engineered nanoparticles (ENP), there remains no quantitative gold standard to serve as an alternative to the qualitative assessment. Many CB models have been developed during the years subsequent to the initial development of the CB Nanotool and the literature continues to blossom with comparisons and applications of these various tools; however, these developments have hitherto been made in the absence of validating and verifying their effectiveness using existing, albeit limited, quantitative methods. This paper reviews the existing literature on the CB Nanotool to evaluate its effectiveness in a variety of settings and presents a summary of qualitative and quantitative information from its application in a broad range of ENP handling activities performed in two different research institutions. A total of 28 ENP activities were assessed using the CB Nanotool (Version 2.0). Due to the lack of guidance on a single exposure assessment methodology, a combination of real-time monitoring, filter analysis, and microscopic analysis was used to assess various quantitative metrics, including mass concentration, particle number concentration, and particle speciation. All the results indicated that the control outcomes from the CB Nanotool qualitative assessment were sufficient to prevent workers from being exposed to ENP at levels beyond established exposure limits or background levels. These data represent an independent quantitative validation of CB Nanotool risk level outcomes and give further credence to the use of the CB Nanotool to effectively control worker exposures in the absence of quantitative air monitoring results.
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Explore the source record for details and available documents.
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Aerosol particles play an important role for the regional and global climate. Therefore, a network of measurement sites has been established worldwide, but only a small fraction of them is capturing the marine boundary layer (MBL) while approximately 70% of the Earth’s surface is covered with water. The main focus of this project is to improve the knowledge of sources and exchange processes of aerosol particles in general (German Research Foundation [DFG] project WE 2757/2-1) and of cloud condensation nuclei in particular (DFG project HE 6770/2-1) in the MBL in the northeastern Atlantic Ocean where the influence of local anthropogenic sources is negligible. The main hypothesis of the project is that long-range transport of aerosols from North America as well as new particle formation in the free troposphere (FT) and at cloud edges followed by vertical transport contribute significantly to the aerosol budget in the MBL. The knowledge of sources and sinks of aerosol particles in combination with vertical exchange between FT and MBL is a prerequisite to predict aerosol particle number concentrations in the lowest regions of the MBL and its influence on the formation of clouds. These processes are not sufficiently quantified over the ocean up to now. To verify the hypothesis stated above, vertical exchange processes and particle sources over the Azores will be quantified using data of 17 measurement flights with high spatial resolution using a helicopter-borne platform developed at the Leibniz Institute for Tropospheric Research (TROPOS). Here, aerosol particle number concentration and vertical wind speed have been measured with a temporal resolution allowing the direct estimate of the vertical turbulent flux of aerosol particles in different heights for the first time. In addition, aerosol particle number size distributions, number concentrations of cloud condensation nuclei (CCN), cloud droplet number concentration (CDNC), and particle absorption at three different wavelengths have been determined. The data analysis is ongoing and final results are not available yet. The detailed analysis of these data will be used to conclude sources and origin of the investigated aerosol particles.
Supercooled fogs can have an important radiative impact at the surface of the Greenland Ice Sheet, but they are difficult to detect and our understanding of the factors that control their lifetime and radiative properties is limited by a lack of observations. This study demonstrates that spectrally resolved measurements of downwelling longwave radiation can be used to generate retrievals of fog microphysical properties (phase and particle effective radius) when the fog visible optical depth is greater than ~0.25. For 12 cases of fog under otherwise clear skies between June and September 2019 at Summit Station in central Greenland, nine cases were mixed-phase. The mean ice particle (optically-equivalent sphere) effective radius was 24.0 ± 7.8 µm, and the mean liquid droplet effective radius was 14.0 ± 2.7 µm. These results, combined with measurements of aerosol particle number concentrations, provide evidence supporting the hypotheses that (a) low surface aerosol particle number concentrations can limit fog liquid water path, (b) fog can act to increase near-surface aerosol particle number concentrations through enhanced mixing, and (c) multiple fog events in quiescent periods gradually deplete near-surface aerosol particle number concentrations.
A wealth of observational data exists on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) Central Facility site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of the total aerosol and the cloud condensation nuclei (CCN) subset, and their variability, through merged data products. This study was aimed at exploiting the multiple measurement types at SGP to develop the first such multi-year estimates. Further, the resulting data were analyzed to understand temporal patterns ranging from hourly to seasonal, thereby gaining insights into the particle sources affecting the atmosphere in this region. DOE-funded datasets that were analyzed in this study include total particle number concentrations, submicron aerosol scattering coefficients, dry aerosol size distributions, and more recently, time-resolved submicron aerosol chemical composition. Data are also available for the number concentrations of particles that are activated in a cloud condensation nucleus instrument at a series of setpoint supersaturations, providing direct observations of the number concentrations of “CCN”. This variable is the quantity that is generally desired for inclusion in numerical models that seek to represent and predict the impacts of varying aerosol characteristics on the formation and microphysical properties of clouds. One limitation of the use of direct CCN observations is that they are not available for supersaturations larger than about 1%, which is insufficient for deep convection and may be insufficient even for shallow convection, depending on the nature of the available CCN and the dynamics of the cloud. We developed a data-based approach to representing the full aerosol size spectrum with size-dependent hygroscopicity, and used this to extrapolate CCN spectra beyond the limited measurements. Five years of SGP aerosol data (2009 -2013) were analyzed. As a side product of our work, we identified and communicated several previously-unflagged data quality issues. The resulting merged aerosol distributions, along with fits for seasonal averages, were published and submitted to the ARM archive as a special value-added product (VAP; submitted as a PI product). CCN spectra were computed for the same data period and will similarly be published and submitted to the archive for use by the community. We also note that our methodologies and findings have been discussed at several Joint ARM User Facility/Atmospheric System Research (ASR) Principal Investigators Meetings and that recent ARM/ASR aerosol data reporting strategies have included similar ideas for data merging, indicating that this work has had a lasting impact on ARM aerosol data acquisition and reporting. The proposed work advances the science of the interactions of aerosols, clouds and precipitation, with direct application to improve representation of such interactions for clouds in regional and global climate models. The archived data will continue to serve research studies in the future.
A detailed ice-phase bulk microphysical scheme has been developed for simulating the hydrometeor distributions of convective and stratiform precipitation in different large-scale environmental conditions. The proposed scheme involves 90 distinct microphysical processes, which predict the mixing ratios and the number concentrations of small ice crystals, snow, graupel, and frozen drops/hail, as well as the mixing ratios of liquid water on wet precipitation ice (snow, graupel, frozen drops). The number of adjustable coefficients has been significantly reduced in comparison with other bulk schemes. Additional improvements have been made to the parameterization in the following areas: (1) representing small ice crystals with nonzero terminal fall velocities and dispersive size distributions, (2) accurate and computationally efficient calculations of precipitation collection processes, (3) reformulating the collection equation to prevent unrealistically large accretion rates, (4) more realistic conversion by riming between different classes of precipitation ice, (5) preventing unrealistically large rates of raindrop freezing and freezing of liquid water on ice, (6) detailed treatment of various rime-splintering ice multiplication mechanisms, (7) a simple representation of the Hobbs-Rangno ice enhancement process, (8) aggregation of small ice crystals and snow, and (9) allowing explicit competition between cloud water condensation and ice deposition rates rather than using saturation adjustment techniques. For the purposes of conserving the higher moments of the particle distributions, preserving the spectral widths (or slopes) of the particle spectra is shown to be more important than strict conservation of particle number concentration when parameterizing changes in ice-particle number concentrations due to melting, vapor transfer processes (sublimation of dry ice, evaporation from wet ice), and conversion between different hydrometeor species. The microphysical scheme is incorporated into a nonhydrostatic cloud model in Part 2 of this study. The model performed well in simulating the radar and microphysical structures of a midlatitude-continental squall lines and a tropical-maritime squall system with minimal tuning of the parameterization, even though the vertical profiles of radar reflectivity differed substantially between these storms.
Electric wind -- the movement of gas, induced by ions moving in an electric field -- can be a distorting factor in size distribution measurements using Differential Mobility Analyzers (DMAs). The aim of this study was to determine the conditions under which electric wind occurs in the locally-built VLDMA (Very Long Differential Mobility Analyzer) and TSI Long-DMA (3081) and to describe the associated distortion of the measured spectra. Electric wind proved to be promoted by the increase of electric field strength, aerosol layer thickness, particle number concentration and particle size. The measured size spectra revealed three types of distortion: widening of the size distribution, shift of the mode of the distribution to smaller diameters and smoothing out the peaks of the multiply charged particles. Electric wind may therefore be a source of severe distortion of the spectrum when measuring large particles at high concentrations.