9 Search Results

New particle formation and growth (NPF&G) is the process by which ultrafine particles are formed from gas-phase precursors. NPF&G is the dominant source of global aerosol number with important influences on climate. Most observations of NPF&G events are conducted at stationary sites; however, NPF&G observed from stationary sites is influenced by gradual or rapid changes in the air masses passing over the site, complicating NPF&G analysis. In this work, we use observations and a 3D aerosol model to compare aerosol size distributions at a stationary site (Southern Great Plains [SGP] observatory, Oklahoma, USA) and along Lagrangian trajectories crossing the site.more » The model simulates the NPF&G events reasonably well at SGP. Using the model to compare the Lagrangian and stationary perspectives, we can explain previously unanalyzable days with some evidence of NPF&G as either non-event or analyzable NPF&G days. We find most of the unanalyzable NPF&G days are due to isolated and inhomogeneous NPF&G occurring upwind of the stationary site, often in the outflow of urban regions. Finally, we compare formation rates of 3 nm particles, growth rates, and the survival probability of 3 nm particles growing to 25 nm between the stationary and Lagrangian perspectives. Because of the much larger number of analyzable days along the Lagrangian trajectories, this perspective potentially provides more robust statistics and better characterization of NPF&G event extremes. Our method for extracting chemical/physical properties along Lagrangian trajectories from 3D models can be applied to a wide range of science questions.« less

A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitationmore » micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.« less

This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH₄) and carbon dioxide (CO₂), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH₄ emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH₄ hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS andmore » an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s^-1 when the wind magnitude is less than 3.5 m s^-1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH₄ and CO₂ occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH₄ emissions in near real time.« less

Abstract. When aerosol particles seed the formation of liquid water droplets in the atmosphere, they are called cloud condensation nuclei (CCN). Different aerosols will act as CCN under different degrees of water supersaturation (relative humidity above 100 %), depending on their size and composition. In this work, we build and analyze a best-estimate CCN spectrum product, tabulated at ∼ 45 min resolution, generated using high quality data from seven independent instruments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The data product spans a large supersaturation range, from 0.0001 % to ∼ 30 %, and time period of 5 years,more » from 2009–2013, and is available on the ARM data archive. We leverage this added statistical power to examine relationships that are unclear in smaller datasets. Our analysis is performed in three main areas. First, probability distributions of many aerosol and CCN metrics are found to exhibit skewed log-normal distribution shapes. Second, clustering analyses of CCN spectra reveal that the primary drivers of CCN differences are aerosol number size distributions, rather than hygroscopicity or composition, especially at supersaturations above 0.2 %, while also allowing for a simplified understanding of seasonal and diurnal variations in CCN behavior. The predictive ability of using limited hygroscopicity data with accurate number size distributions to estimate CCN spectra is investigated, and the uncertainties of this approach are estimated. Third, the dynamics of CCN spectral clusters and concentrations are examined with cross-correlation and autocorrelation analyses. We find that CCN concentrations change rapidly on the timescale of 1–3 h, with some conservation beyond that which is greatest for the lower supersaturation region of the spectrum.« less

A quality-controlled, 5-year dataset of aerosol number size distributions (particles with diameters (Dp) from 7 nm through 14 µm) was developed using observations from a scanning mobility particle sizer, aerodynamic particle sizer, and a condensation particle counter at the Department of Energy's Southern Great Plains (SGP) site. This data set was used for two purposes. First, typical characteristics of the aerosol size distribution (number, surface area, and volume) were calculated for the SGP site, both for the entire dataset and on a seasonal basis, and size distribution lognormal fit parameters are provided. While the median size distributions generally had similarmore » shapes (four lognormal modes) in all the seasons, there were some significant differences between seasons. These differences were most significant in the smallest particles(Dp<30 nm) and largest particles (Dp>800 nm).Second, power spectral analysis was conducted on this long-term dataset to determine key temporal cycles of total aerosol concentrations, as well as aerosol concentrations in specified size ranges. The strongest cyclic signal was associated with a diurnal cycle in total aerosol number concentrations that was driven by the number concentrations of the smallest particles(Dp<30 nm). This diurnal cycle in the smallest particles occurred in all seasons in ~50% of the observations,suggesting a persistent influence of new particle formation events on the number concentrations observed at the SGP site. This finding is in contrast with earlier studies that suggest new particle formation is observed primarily in the springtime at this site. The timing of peak concentrations associated with this diurnal cycle was shifted by several hours depending on the season,which was consistent with seasonal differences in insolation and boundary layer processes. Significant diurnal cycles in number concentrations were also found for particles with Dp between 140 and 800 nm, with peak concentrations occurring in the overnight hours, which were primarily associated with both nitrate and organic aerosol cycles. Weaker cyclic signals were observed for longer timescales (days to weeks) and are hypothesized to be related to the timescales of synoptic weather variability. The strongest periodic signals (3.5–5 and 7 d cycles) for these longer timescales varied depending on the season, with no cyclic signals and the lowest variability in the summer.« less

A 4-year record of aerosol size and hygroscopic growth factor distributions measured at the Department of Energy’s Southern Great Plains (SGP) site in Oklahoma, U.S. were used to estimate supersaturation (S)-dependent cloud condensation nuclei concentrations (N_CCN). Baseline or reference N_CCN(S) spectra were estimated using κ-Köhler Theory without any averaging of the measured distributions by creating matrices of size- and hygroscopicity-dependent number concentration (N) and then integrating for S > critical supersaturation (S_c) calculated for the same size and hygroscopicity pairs. Moreover, those estimates were first compared with directly measured N_CCN at the same site. Subsequently, N_CCN was calculated using themore » same dataset but with an array of simplified treatments in which the aerosol was assumed to be either an internal or an external mixture and the hygroscopicity either assumed or based on averages derived from the growth factor distributions. The CCN spectra calculated using the simplified treatments were compared with those calculated using the baseline approach to evaluate the error introduced with commonly used approximations.« less

During the summer 2013 Southern Aerosol and Oxidant Study (SOAS) field campaign in a rural site in the southeastern United States, the effect of hygroscopicity and composition on the phase state of atmospheric aerosol particles dominated by the organic fraction was studied. The analysis is based on hygroscopicity measurements by a Hygroscopic Tandem Differential Mobility Analyzer (HTDMA), physical phase state investigations by an Aerosol Bounce Instrument (ABI) and composition measurements using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). To study the effect of atmospheric aging on these properties, an OH-radical oxidation flow reactor (OFR) was used to simulate longer atmosphericmore » aging times of up to 3 weeks. Hygroscopicity and bounce behavior of the particles had a clear relationship showing higher bounce at elevated relative humidity (RH) values for less hygroscopic particles, which agrees well with earlier laboratory studies. Additional OH oxidation of the aerosol particles in the OFR increased the O:C and the hygroscopicity resulting in liquefying of the particles at lower RH values. At the highest OH exposures, the inorganic fraction starts to dominate the bounce process due to production of inorganics and concurrent loss of organics in the OFR. Our results indicate that at typical ambient RH and temperature, organic-dominated particles stay mostly liquid in the atmospheric conditions in the southeastern US, but they often turn semisolid when dried below ~50 % RH in the sampling inlets. Furthermore, while the liquid phase state suggests solution behavior and equilibrium partitioning for the SOA particles in ambient air, the possible phase change in the drying process highlights the importance of thoroughly considered sampling techniques of SOA particles.« less