K. W. Dawson

Results are shown for methane emissions associated with oil loading operations to a shuttle tanker, using measurements obtained from a research aircraft and an unmanned aerial vehicle (UAV), together with multiple modeling approaches.

Site-level measurements of methane emissions are used by operators for reconciliation with bottom-up emission inventories with the aim to improve accuracy, thoroughness, and confidence in reported emissions. In that context it is of critical importance to avoid measurement errors and to understand the measurement uncertainty. Remotely piloted aircraft systems (commonly referred to as “drones”) can play a pivotal role in the quantification of site-level methane emissions. Typical implementations use the “mass balance method” to quantify emissions, with a high-precision methane sensor mounted on a quadcopter drone flying in a vertical curtain pattern; the total mass emission rate can then be computed post hoc from the measured methane concentration data and simultaneous wind data. Controlled-release tests have shown that errors with the mass balance method can be considerable. For example, Liu et al. (2024) report absolute errors for more than 100 % for the two drone solutions tested; on the other hand, errors can be much smaller, of the order of 16 % root-mean-square errors in Corbett and Smith (2022), if additional constraints are placed on the data, restricting the analysis to cases where the wind field was steady. In this paper we present a systematic error analysis of physical phenomena affecting the error in the mass balance method for parameters related to the acquisition of methane concentration data and to postprocessing. The sources of error are analyzed individually, and it must be realized that individual errors can accumulate in practice, and they can also be augmented by other sources that are not included in the present work. Examples of these sources include the uncertainty in methane concentration measurements by a sensor with finite precision or the method used to measure the unperturbed wind velocity at the position of the drone. We find that the most important source of error considered is the horizontal and vertical spacings in the data acquisition, as a coarse spacing can result in missing a methane plume. The potential error can be as high as 100 % in situations where the wind speed is steady and the methane plume has a coherent shape, contradicting the intuition of some operators in the industry. The likelihood of the extent of this error can be expressed in terms of a dimensionless number defined by the spatial resolution of the methane concentration measurements and the downwind distance from the main emission sources. What is learned from our theoretical error analysis is then applied to a number of historical measurements in a controlled-release setting. We show how what is learned about the main sources of error can be used to eliminate potential errors during the postprocessing of flight data. Second, we evaluate an aggregated data set of 1001 historical drone flights; our analysis shows that the potential errors in the mass balance method can be of the order of 100 % on occasion, even though the individual errors can be much smaller in the vast majority of the flights. The Discussion section provides some guidelines for industry on how to avoid or minimize potential errors in drone measurements for methane emission quantification.

Lidar retrievals of aerosol extinction and collocated relative humidity (RH) were acquired during the Department of Energy Combined High Spectral Resolution Lidar (HSRL) and Raman Measurement Study campaign in the summer of 2015 at the Southern Great Plains site in northern Oklahoma. Measurements of the hygroscopic properties of aerosols are crucial for accurately representing their relationship with clouds, which can be a significant source of uncertainty in assessing direct and indirect radiative effects. The ability for lidar to retrieve measurements of the vertically resolved f (RH), that is, the aerosol extinction at some wet RH normalized by the aerosol extinction at a dry reference RH, is investigated here and compared with nephelometer‐measured f (RH) at the surface. We introduce a modified approach to fitting the lidar measurements of aerosol extinction and our comparisons reveal that lidar and nephelometer measurements of f (RH) are consistent, both with each other and with reported values in the literature. The implications for this work present a path forward for global‐scale retrievals of remotely sensed aerosol hygroscopic properties. Most importantly, the efforts in this study could lead to closing the gap on uncertainties associated with the aerosol indirect radiative effect when combined with inversion retrievals of aerosol microphysical properties.

Atmospheric measurements of aerosol size‐resolved hygroscopicity at submicron sizes are carried out at the United States Army Corps of Engineers Field Research Facility in Duck, North Carolina. The scientific aim of the field deployment is to gain improved understanding of the springtime advection of aerosols from the East Coast of the United States over the Atlantic and help to constrain assessments of anthropogenic particle contributions to the marine boundary layer aerosol budget. Air mass back trajectories show that the aerosol sampled at the coast is largely of continental origin that either gets transported directly from the land or spends some time over the Atlantic Ocean. Aerosol size‐resolved hygroscopicity measurements are consistent with air masses of both continental and marine background that are heavily influenced by the continental outflow. Aitken and accumulation mode mean diameters range from 49.1 ± 1.7 nm to 66.9 ± 0.8 nm and 142.8 ± 1.1 nm to 155.0 ± 2.8 nm, respectively. Hygroscopicity distributions for 96 nm, 188 nm, and 284 nm dry‐sized particles show the mode hygroscopicity parameter range from 0.20 ± 0.01 to 0.54 ± 0.03, suggesting the presence of anthropogenic aerosols. We have used the method described by Royalty et al. (2017) to decompose the hygroscopicity distributions into three distinct classes based on the ambient aerosol hygroscopic properties relative to the hygroscopic properties of a reference compound. The method shows that continental outflow heavily influences aerosol chemical and physical properties at the East Coast, with hygroscopicities of submicron aerosols consistent with sulfate‐containing species (62% to 83%), with small contributions from sodium‐ and carbon‐containing particles (up to 9% and 37%, respectively).

The accurate representation of aerosols in climate models requires direct ambient measurement of the size- and composition-dependent particle production fluxes. Here, we present the design, testing, and analysis of data collected through the first instrument capable of measuring hygroscopicity-based, size-resolved particle fluxes using a continuous-flow Hygroscopicity-Resolved Relaxed Eddy Accumulation (Hy-Res REA) technique. The Hy-Res REA system used in this study includes a 3D sonic anemometer, two fast-response solenoid valves, two condensation particle counters, a scanning mobility particle sizer, and a hygroscopicity tandem differential mobility analyzer. The different components of the instrument were tested inside the US Environmental Protection Agency's Aerosol Test Facility for sodium chloride and ammonium sulfate particle fluxes. The new REA system design does not require particle accumulation, and therefore avoids the diffusional wall losses associated with long residence times of particles inside the air collectors of traditional REA devices. A linear relationship was found between the sodium chloride particle fluxes measured by eddy covariance and REA techniques. The particle detection limit of the Hy-Res REA flux system is estimated to be ∼3 × 10⁵ m⁻² s⁻¹. The estimated sodium chloride particle classification limit, for the mixture of sodium chloride and ammonium sulfate particles of comparable concentrations, is ∼6 × 10⁶ m⁻² s⁻¹. Copyright © 2018 American Association for Aerosol Research

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH‐derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first‐generation airborne High Spectral Resolution Lidar (HSRL‐1) retrievals during the Ship‐Aircraft Bio‐Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH‐derived aerosol types are determined by multivariate clustering of model‐calculated variables that have been trained using retrievals of aerosol types from HSRL‐1. CATCH‐derived aerosol types (with the exception of smoke) compare well with HSRL‐1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System‐ with Chemistry (GEOS‐Chem) model. Spatial distributions of CATCH‐derived aerosol types for the North American model domain during July/August 2014 show that aerosol type‐specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model‐generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL‐1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

The impact of anthropogenic aerosol on climate forcing remains uncertain largely due to inadequate representation of natural aerosols in climate models. The marine boundary layer (MBL) might serve as a model location to study natural aerosol processes. Yet source and sink mechanisms controlling the MBL aerosol number, size distribution, chemical composition, and hygroscopic properties remain poorly constrained. Here aerosol size distribution and water uptake measurements were made aboard the R/V Hi'ialakai from 27 June to 3 July 2016 in the subtropical North Pacific Ocean. Size distributions were predominantly bimodal with an average integrated number concentration of 197 ± 98 cm⁻³. Hygroscopic growth factors were measured using the tandem differential mobility analyzer technique for dry 48, 96, and 144 nm particles. Mode kappa values for these were 0.57 ± 0.12, 0.51 ± 0.09, and 0.52 ± 0.08, respectively. To better understand remote MBL aerosol sources, a new algorithm was developed which decomposes hygroscopicity distributions into three classes: carbon‐containing particles, sulfate‐like particles, and sodium‐containing particles. Results from this algorithm showed low and steady sodium‐containing particle concentrations while the sulfate‐like and carbon‐containing particle concentrations varied during the cruise. According to the classification scheme, carbon‐containing particles contributed at least 3–7%, sulfate‐like particles contributed at most 77–88% and sodium‐containing particles at least contributed 9–16% to the total aerosol number concentration. Size distribution and hygroscopicity data, in conjunction with air mass back trajectory analysis, suggested that the aerosol budget in the subtropical North Pacific MBL may be controlled by aerosol entrainment from the free troposphere.

Knowledge of the physical characteristics and chemical composition of marine organic aerosols is needed for the quantification of their effects on cloud microphysical processes and solar radiative transfer. Here we use xanthan gum (XG)—a bacterial biopolymer—as a proxy for marine hydrogels. Measurements were performed for pure XG particles and mixtures of XG with sodium chloride, calcium nitrate, and calcium carbonate. The aerosol hygroscopicity parameter (κ) is derived from hygroscopic growth factor measurements (κ_gf) at variable water activity (a_w) and from cloud condensation nuclei activation efficiency (κ_ccn). The Zdanovskii, Stokes, and Robinson (ZSR) hygroscopicity parameter derived for multicomponent systems (κ_{mix, sol}) is used to compare measurements of κ_gf and κ_ccn. Pure XG shows close agreement of κ_gf (at a_w = 0.9) and κ_ccn of 0.09 and 0.10, respectively. Adding salts to the system results in deviations of κ_gf (at a_w = 0.9) from κ_ccn. The measured κ_gf and ZSR‐derived hygroscopicity parameter (κ_{mix, sol}) values for different solutions show close agreement at a_w > 0.9, while κ_gf is lower in comparison to κ_{mix, sol} at a_w < 0.9. The differences between predicted κ_{mix, sol} and measured κ_gf and κ_ccn values are explained by the effects of hydration and presence of salt ions on the structure of the polymer networks. Results from this study imply that at supersaturations of 0.1 and 0.5%, the presence of 30% sea salt by mass can reduce the activation diameter of pure primary marine organic aerosols from 257 to 156 nm and from 87 to 53 nm, respectively.

The atmospheric supply of dust iron (Fe) plays a crucial role in the Earth's biogeochemical cycle and is of specific importance as a micronutrient in the marine environment. Observations show several orders of magnitude variability in the fractional solubility of Fe in dust aerosols, making it hard to assess the role of mineral dust for global ocean biogeochemical Fe cycle. In this study we compare the operational solubility of dust aerosol Fe associated with one of the flow-through leaching protocols to the results of the global 3-D chemical transport model GEOS-Chem. In the protocol aerosol Fe is defined soluble by first deionized water leaching of mineral dust through a 0.45 μm pore size membrane followed by acidification and storage of the leachate over a long period of time prior to the analysis. To assess the concentrations of soluble Fe inferred by this flow-through leaching protocol we are using in situ measurements of dust size distribution with the prescribed of 50 % fractional solubility of Fe in less than 0.45 μm sized dust particles collected in the leachate. In the model, the fractional solubility of Fe is either explicitly calculated using complex dust Fe dissolution module, or prescribed to be 1 and 4 %. Calculations show that the fractional solubility of Fe derived through the flow-through leaching is typically higher compared to the model results. The largest differences (>30 %) are predicted to occur farther away from the dust source regions, over the areas where sub-0.45 μm sized mineral dust particles contribute a larger fraction of the total dust mass. This study suggests that inconsistences in the operational definition of soluble Fe could contribute to the wide range of the fractional solubility of dust aerosol Fe reported in the literature.