Aerosol Products Research Articles

On the effects of the gaseous atmosphere in jetting and ultra-fine spraying from bubble bursting

The compressibility effects of the gaseous atmosphere on bubble bursting and collapse on a liquid surface, with emphasis on their implications for sea spray aerosol production and the atmosphere, are analyzed in this work using numerical simulation. The Ohnesorge number (Oh) is maintained around a critical value (Oh ∼ 0.033) corresponding to optimal conditions for the generation of smaller droplets at higher velocities. Numerical simulations show that despite reaching local densities around 40% of the atmospheric baseline during the late stages of bubble collapse, the surrounding gas density has minimal effect on the size and number of ejected droplets as the high-speed jet emerges, and no significant deviations from previous incompressible gas models are observed. However, the number and size of ejected droplets vary with the level of numerical discretization. In this regard, our simulations show that the number of droplets at the smallest length scales reached can be orders of magnitude larger than previously reported. This is observed almost independently of the level of discretization, as long as sufficient accuracy is ensured, and implies that factors, such as the variability of local conditions and the presence of contaminants, or even thermal fluctuations at this smallest scale, could further influence ultrafine aerosol production. These results reemphasize the role of bubble-bursting jets as key players in the critical droplet size spectra from the sea surface that affect primary and secondary aerosol and cloud formation.

Global evaluation of NOAA-20 VIIRS dark target aerosol products over land and ocean

The Dark Target (DT) algorithm has been applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi-NPP (SNPP) and NOAA-20 satellites to extend the aerosol data record from the Moderate Resolution Imaging Spectrometer (MODIS). The newly released VIIRS DT Version 2.0 (V2.0) dataset includes NOAA-20 aerosol products for the first time. This study provides the first evaluation of NOAA-20 VIIRS DT aerosol products, including aerosol optical depth (AOD) and Ångstrom exponent (AE), for the period 2018–2022 using Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) measurements. In addition, the operational DT aerosol products from SNPP VIIRS (V2.0) and MODIS (Collection 6.1) are also used for comparison purposes. Overall, NOAA-20 AODs over land and ocean exhibit good validation metrics globally, showing comparability to MODIS products and superiority over overestimated SNPP products. Nevertheless, it is worth noting that in South Africa specifically, NOAA-20 land AODs tends to display more pronounced negative biases, despite all products being underestimated. Furthermore, all ocean AE products demonstrate high correlation coefficients (>0.83) with the ground-based data, meeting the fraction of expected accuracy (>80%). Encouragingly, NOAA-20 AE product has significantly improved the persistent issue of overestimation at low-value in MODIS product, making it a more preferable choice for usage. Error analysis reveals that the performance of all three land products decreases in sparsely vegetated areas and when the solar zenith angle is small. However, NOAA-20 AOD exhibits relatively stable performance and is less affected by variations in aerosol loading, observation geometry, and surface vegetation cover. In addition, the performance of AOD and AE over ocean is significantly influenced by scattering angle and wind speed. This research is anticipated to serve as a reference for the utilization of operational VIIRS DT aerosol products and possible algorithm optimization.

Spatiotemporal Variation in Aerosol Optical Depth and Its Potential Effects on Snowmelt in High Mountain Asia from 2004 to 2023

Light-absorbing particles, which are vital components of aerosols, can cause significant snow albedo darkening and accelerate melting. However, restricted by the poor quality of remote sensing-based aerosol products in High Mountain Asia (HMA), previous studies have seldom reported the long-term pattern of aerosols. In this study, we analyzed the spatial and temporal distribution characteristics of AOD in HMA and surrounding areas using Moderate Resolution Imaging Spectroradiometer and Ozone Monitoring Instrument data from 2004 to 2023. The Mann‒Kendall test was applied to analyze the temporal trend and abrupt changes in AOD, while Rotated Empirical Orthogonal Function was used to identify subregions and investigate spatiotemporal variations. Moreover, random forest and XGBoost-Shap models were employed to quantify the contributions of the aerosols to changes in snow albedo and melting. The results indicate that the annual (monthly) average highest and lowest AOD occurred in 2021 (April) and 2022 (September) between 2004 and 2023, respectively. The AOD first increased and then decreased during our study period and an abrupt decline was detected in 2013. The REOF model revealed three regions in HMA (northern, southwestern, and southeastern parts) with strong variations in AOD load, which are strongly correlated with atmospheric circulation and monsoon driving. Specifically, REOF1, REOF2, and REOF3 are primarily associated with frequent dust events during springtime atmospheric circulation and anthropogenic emission transport during the monsoon season. Aerosol types were divided into four types, BC aerosol, DUST aerosol, MIX aerosol, and clean conditions, whose proportions were 16.7%, 16.1%, 6.6%, and 60.6%, respectively. The clean conditions constituted the main aerosol type in the region. The AOD notably decreased snow albedo (17.8%) and increased snowmelt (9.0%); we highlight the contribution of AOD to the intensification of snowmelt. These results could provide guidance for further studies on the relationship between snowmelt and AOD.

Bubble fragmentation in turbulent flow and the potential implications of shear structures for bubbles formed by breaking waves

Large bubbles (1–5 mm radius) are important in a wide range of situations, including air-sea gas transfer, aerosol production as they burst at water surfaces, and the aeration of liquids in bioreactors and other industrial processes. When rising through turbulent flow, these bubbles are commonly distorted and may fragment to form daughter bubbles if their radius exceeds the Hinze scale (at which the restoring force due to surface tension is equal to the forces causing bubble distortion). Here, we present the results of laboratory experiments with fragmentation resulting from bubbles rising through a sheared and turbulent flow. The effects of water temperature, surface tension, local shear rate, and viscous dissipation rate of turbulent kinetic energy were assessed. Passive acoustical methods produce robust measurements of bubble fragmentation processes, allowing for rapid data collection to generate large data sets. In our experiments, even for bubbles very close to the Hinze scale, the dominant fragmentation mechanism is the capillary-driven fragmentation of elongated bubble filaments. The probability distribution of daughter bubble sizes from a single fragmentation event was independent of temperature, surface tension, and rate of viscous dissipation of turbulent kinetic energy. The overwhelming majority of fragmentation events resulted in one very large and one very small bubble, even for Hinze-scale parent bubbles and low Weber numbers (We < 5.3). Our results suggest that in a turbulent flow, there may be a link between the shear induced by large scale structures and the size of the smallest bubbles produced underneath a breaking wave.

Accelerated surface brightening in China: The decisive role of reduced anthropogenic aerosol emissions

A profound comprehension of the key determinants behind the fluctuations in surface solar radiation (SSR) over decadal timescales is essential for advancing the fields of energy meteorology, climatology, and solar resources. While there is a general agreement among prior research on the significant impact of aerosols on SSR, a granular understanding of the specific influence that varying aerosol types exert on SSR remains elusive. This investigation delves into the respective impacts of aerosols and cloud radiative effects across China, utilizing data from the Clouds and the Earth's Radiant Energy System (CERES). It further dissects the distinct impacts of different aerosol types on the decadal-scale variations in SSR, employing spectral aerosol optical depths derived from the MODIS aerosol products. The findings reveal a predominantly positive trend in SSR, ranging from 1.5 to 2.5 W/m2/yr between the years 2011 and 2022 for the majority of China's regions. However, certain areas within Northeast and Western China exhibit a decline in SSR exceeding −1 W/m2/yr. Notably, in Eastern China, a downward trend in aerosol radiative effect is observed, with a pronounced reduction of approximately −2 W/m2/yr noted specifically during the summer in Northern China. The study infers that the reduction in urban industrial emissions and biomass burning aerosols is linked to the acceleration of the brightening phenomenon in China. Our results underscore that stringent regulation of anthropogenic emissions could yield dual benefits: environmental amelioration and an upsurge in solar resource. These insights merit serious contemplation in the formulation of future policy and decision-making frameworks.

The emission of pollutants from ornamental shrubs during forest fires

AbstractThis study investigates the combustion behavior, emissions, and aerosol production of four plant species: Laurus nobilis, Cistus monspeliensis, Photinia fraseri, and Cupressus sempervirens. The Heat Release Rate (HRR) and Smoke Production Rate (SPR) were measured, revealing that Cupressus sempervirens had the highest HRR and longest flame duration due to its higher bulk density. Emission Factors (EFs) for key compounds such as CO₂, CO, NO, and aerosols showed significant variation by species. Aerosol analysis indicated that the combustion of all plants primarily emitted fine particles, with the majority being ultrafine particles (PM0.1), particularly in the 25–130‐nm range. Particle size distributions were bimodal in number but monomodal in volume. These findings highlight the impact of plant characteristics on fire behavior and emissions, with significant implications for understanding fire dynamics in wildland–urban interfaces.

Improvement and validation of discrete-sectional method based code for fast reactor aerosol dynamics

The study of the dynamics of aerosols produced during a severe accident is vital to the safety analysis of a Sodium-cooled Fast Reactor (SFR). Sodium leakage into the containment following a severe accident may result in the production of sodium aerosols along with fission product aerosols. The in-containment radioactive source term depends upon the settling behaviour of fission product aerosols, which co-agglomerate with sodium fire aerosols. Hence, an in-depth understanding of the dynamics and deposition of aerosols within the containment is essential for the safety assessment of an SFR. The current work uses an open-source code based on the Discrete-Sectional (DS) method to solve the simplified form of General Dynamics Equation (GDE) for aerosols relevant to fast reactors. Aerosols of SrO2, CeO2 and sodium are considered in the present work. The DS code has been modified and further improved by including gravitational coagulation, turbulent coagulation, Brownian deposition, gravitational deposition and thermophoretic deposition so that the code can handle the different processes leading to the deposition of aerosols following a sodium fire. The code is also enhanced to account for the effect of relative humidity through the modified Cooper's equation. The improved code is then validated with different experiments conducted in the Aerosol Test Facility (ATF), India; Mini Sodium Fire Facility (MINA), India; and AHMED (Aerosol and Heat Transfer Measurement Device), Finland. Validation from different facilities confirms the applicability of the code to various scenarios. It is found that the modified DS code could predict the decay of suspended mass concentration of aerosols in different enclosures with reasonable accuracy.

Secondary Organic Aerosol Formation during the Oxidation of Large Aromatic and Other Cyclic Anthropogenic Volatile Organic Compounds.

The secondary organic aerosol (SOA) production from the reactions of anthropogenic large volatile (VOCs) and intermediate volatility organic compounds (IVOCs) with hydroxyl radicals under high NO x conditions was investigated. The organic compounds studied include cyclic alkanes of increasing size (amylcyclohexane, hexylcyclohexane, nonylcyclohexane, and decylcyclohexane) and aromatic compounds (1,3,5-trimethylbenzene, 1,3,5-triethylbenzene and 1,3,5-tritert-butylbenzene). A considerable amount of SOA was formed from all examined compounds. For the studied cyclohexanes (C11-C16) there appears that the SOA yield depends nonlinearly on the length of their substitute chain. The large cyclohexanes had higher yields than the aromatic compounds, but the aromatic precursors produced a more oxidized SOA. This was due to the production of lower volatility and O:C first generation products by the cyclohexanes. Most oxidation products (with C* < 104 μg m-3) in the case of cyclohexanes are SVOCs (∼50%), while of aromatics are IVOCs (∼60%). Structure, molecular size, and length of the substitute chain of the parent hydrocarbon were found to play key roles in SOA formation, oxidation state, and volatility. The SOA volatility distribution, effective vaporization enthalpy, and effective accommodation coefficient were also quantified by combining SOA yields, thermodenuder (TD) and isothermal dilution measurements. Parameterizations for the Volatility Basis Set (VBS) are proposed for future use in chemical transport models.

Exploring the use of ground-based remote sensing to identify new particle formation events: A case study in the Beijing area

New Particle Formation (NPF) is an important process of secondary aerosol production in the atmosphere, which has significant impacts on the Earth's radiation balance, air quality, and climate change. In this study, we develop a method to identify NPF events based on ground-based remote sensing. We propose a proxy to characterize NPF events utilizing ground-based remote sensing of gaseous precursors and aerosol optical depth (AOD). This proxy is applied to identify the NPF events in Beijing in the winter of 2022 and tested by comparison with in-situ observations of aerosol particle number size distributions (PNSD) from SMPS. The comparison shows that the NPF events for regional nucleation can be identified effectively when the threshold for sulfur dioxide and organic gases (i.e. formaldehyde) are determined as 0.44 × 10−4 and 1.07 × 10−4. Based on these thresholds, the NPF events can be identified at a high percentage (84 %) compared with in-situ observations. The relationship between identification of NPF events and meteorological conditions shows that NPF events in Beijing winter occurred more frequently under weather conditions with north-west wind direction, high wind speed and low relative humidity.

Aerosol optical depth retrieval using scaled digital number (DN) values of multi-spectral satellite and a generating adversarial model based on deep learning application

ABSTRACT The current quantitative retrieval of Aerosol Optical Depth (AOD) typically uses Top-of-atmosphere (TOA) reflectance data obtained by the scale and offset terms of radiometric calibration. Errors can be introduced during the conversion of Digital Number (DN) values to TOA reflectance, restraining the accurate retrieval of AOD. Particularly when surface reflectance is high, conversion errors can significantly distort the retrieval of Aerosol Optical Depth (AOD), given the minimal impact of aerosols on the radiation detected by satellite sensors. To counteract this, we introduce an innovative retrieval algorithm that harnesses a Generative Adversarial Network (GANN), a deep learning (DL) model, to accurately derive AOD from the scaled digital number (DN) values of multi-spectral satellite imagery. The DL technology enables the use of scaled DN values for AOD retrieval, bypassing the conversion errors associated with TOA reflectance since it relies on a sample learning approach instead of radiative transfer calculations. To ensure the number and representativeness of training samples, a total of 37,103 samples from different underlying surfaces from 2014 to 2018 were obtained using a space-time matching strategy. Our K-cross validation demonstrates that employing DN values for AOD retrieval promises to yield higher accuracy compared to using TOA reflectance. Independent 2019 data were used to estimate GANN, MCD19A2 and MOD04_3K aerosol products. Our model showed superior performance compared to the other products in terms of a higher correlation (R = 0.8184) with AERONET AOD and obtaining more reliable retrievals (7601). The sensitivity experiment suggests that GANN exhibits limitations in areas characterized by high aerosol loads and heterogeneity. Our study can give a novel insight into AOD retrieval based on multi-spectral satellite and DL models.

Retrieving hourly aerosol optical depth for geostationary satellite FY-4B/AGRI by surface-related dynamic spectral reflectance ratio method

The Advanced Geostationary Radiation Imager (AGRI) on board Fengyun-4B (FY-4B) has been found to have significant advantages in aerosol dynamic monitoring. This study proposed a surface-related dynamic spectral reflectance ratio (SDSRR) method for FY-4B AGRI to solve the problem of inaccurate surface reflectance estimation in Aerosol Optical Depth (AOD) retrieval. This method introduced Moderate-resolution Imaging Spectroradiometer (MODIS) aerosol product to assist in calculating the surface reflectance of the AGRI blue channel and the spectral reflectance ratio between the shortwave infrared (SWIR) channel and the blue channel, then constructed a surface-related dynamic spectral reflectance ratio series by combining the spectral reflectance ratio, Normalized Difference Vegetation Index (NDVI) and Scattering Angle (SCA) to obtain aerosol retrieval results. To verify the accuracy of the SDSRR method, the AOD dataset of the SDSRR method, the official aerosol products of AGRI (LDA) and Advanced Himawari Imager (AHI) AOD datasets were compared with the ground-based observations of Aerosol Robotic Network (AERONET) and Sun-shy radiometer Observation Network (SONET) in East Asia. The results indicate that the SDSRR method performs more consistently in East Asia compared to the official ARGI aerosol products. The root-mean-square-error (RMSE), mean error (ME), and correlation coefficient (R) between SDSRR AOD and ground-based measurements are 0.286, 0.180 and 0.70, which is better than that of LDA AOD (RMSE = 0.508, ME = 0.292, R = 0.69). Additionally, the RMSE, ME, and R of AHI AOD were 0.253, 0.168, and 0.74, respectively.

Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application

Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.

Dynamics of Bubble Plumes Produced by Breaking Waves

Abstract Bubble plumes play a significant role in the air–sea interface by influencing processes such as air–sea gas exchange, aerosol production, modulation of oceanic carbon and nutrient cycles, and the vertical structure of the upper ocean. Using acoustic Doppler current profiler (ADCP) data collected off the west coast of Ireland, we investigate the dynamics of bubble plumes and their relationship with sea state variables. In particular, we describe the patterns of bubble plume vertical extension, duration, and periodicity. We establish a power-law relationship between the average bubble penetration depth and wind speed, consistent with previous findings. Additionally, the study reveals a significant association between whitecapping coverage and observed acoustic volume backscatter intensity, underscoring the role of wave breaking in bubble plume generation. The shape of the probability distribution of bubble plume depths reveals a transition toward stronger and more organized bubble entrainment events during higher wind speeds. Furthermore, we show that deeper bubble plumes are associated with turbulent Langmuir number Lat ∼ 0.3, highlighting the potential role of Langmuir circulation on the transport and deepening of bubble plumes. These results contribute to a better understanding of the complex interactions between ocean waves, wind, and bubble plumes, providing valuable insights for improving predictive models and enhancing our understanding of air–sea interactions. Significance Statement This research contributes to understanding bubble plume dynamics in the upper ocean and their relationship with sea state variables. The establishment of a power-law relationship between the bubble penetration depth and wind speed, along with the association between whitecapping coverage and acoustic backscatter intensity, contributes to improved predictive capabilities for air–sea interactions and carbon dioxide exchange. The identification of the potential influence of Langmuir circulation on bubble plume dynamics expands our understanding of the role of coherent circulations in transporting bubble plumes. Additionally, this study presents a clear methodology using commercial sensors such as an ADCP, which can be easily replicated by researchers worldwide, leading to potential advancements in our comprehension of bubble plume dynamics.

A comprehensive evaluation of the atmospheric impacts and health risks of cooking fumes from different cuisines

Pollutants emitted by catering enterprises pose a significant threat to the environment and public health. In this study, based on a systematic analysis of volatile organic compound (VOC) emission characteristics of different cuisines, the contribution of cooking emissions from catering enterprises to the PM2.5 and O3 concentrations in the atmosphere was evaluated using generation potential calculations and WRF-CAMx simulations. The health exposure risks of VOCs in kitchen breathing areas and those of PM2.5 and O3 contributed by the catering enterprises were evaluated. The generation potential calculation results showed that the catering enterprises exhibit 2.21–5.00 gO3/gVOCs of ozone formation potential (OFP) and 0.07–0.21 gSOA/gVOCs of secondary organic aerosol production potential (SOAP). The WRF-CAMx simulation results indicated that cooking emissions from catering enterprises contribute 0.36–1.91 μg/m3 and 0.05–0.21 μg/m3 to PM2.5 and maximum daily 8-h average (MDA8) concentrations of O3. The health exposure risks of PM2.5 and O3 were higher in catering enterprises in southern cities than in northern cities and were higher in urban areas than in suburban areas. The average hazardous VOCs (HVOCs) concentrations ranged from 53 ± 16 to 357 ± 31 μg/m3 in kitchen breathing areas. Acrolein was the primary contributor to the hazard index (HI) of all VOC species, accounting for 50.9%–99.5%. The total incremental lifetime carcinogenic risk (ILCR) of all cuisines exceeded the acceptable thresholds of 1.00 × 10−6. These findings provide insights that can aid in the formation and implementation of pollutant mitigation strategies in the catering industry.

Effect of cloud chemistry on seasonal variations of sulfate and its precursors in China

Cloud chemistry is of paramount importance in the secondary production of atmospheric aerosols, influencing the spatial-temporal distribution of gases and aerosols in the atmosphere. Using WRF/CUACE (China Meteorological Administration Unified Atmospheric Chemistry Environment), this study assesses the seasonal impacts of cloud chemistry on the concentrations of SO2, sulfate, as well as two oxidizers, H2O2 and O3, in the most east-central areas of China, including four key pollution zones (the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Sichuan Basin (SCB)). Near the surface, H2O2-oxidation was the dominant pathway for cloud chemistry in four key pollution zones in four seasons. H2O2 consumption is most pronounced in summer, especially in the SCB and NCP, while O3 consumption peaks in autumn, particularly in the PRD and southeastern coastal areas. While at higher altitudes, oxidation by O3 and H2O2 is compatible with the cloud chemistry process. Near the surface, cloud chemistry consumes SO2 ranging from approximately 0.1 ppb–5.0 ppb, resulting in the generation of about 6.0–25.0 μg m−3 of sulfate. Higher SO2 reduction and sulfate increase are in both summer and winter, especially for the SCB and NCP in summer, and the SCB in winter. Vertically, the cloud chemistry process primarily concentrates its influence on SO2 and sulfate concentrations below 5 km, particularly within the turbulent zone of the troposphere below 2 km in all the four pollution zones and four seasons. The most notable seasonal variation occurs in the NCP compared to other zones. This study also shows that cloud chemistry effectively improves the seasonal simulation accuracy of SO2 and sulfate, resulting in improved correlation and a notable reduction in RMSE.

Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites

Abstract. This comprehensive study analyzed aerosol products from six low-Earth orbit (LEO) and geostationary Earth orbit (GEO) sensors. LEO sensors like the MODerate resolution Imaging Spectroradiometer (MODIS) and VIsible InfraRed Suite (VIIRS) provide one to two daily global measurements, while GEO sensors (Advanced Himawari Imager: AHI, Advanced Baseline Imager: ABI) offer high-frequency data (∼ 10 min) over specific regions. The combination of LEO and GEO capabilities offers expanded coverage of the global aerosol system if aerosol retrievals are applied consistently across all sensors and packaged in an easy-to-use product. The Dark Target aerosol retrieval algorithm was applied to the six sensors, and the resulting Level 2 aerosol optical depth (AOD) products were gridded and merged into a Level 3 quarter-degree latitude–longitude grid with a 30 min temporal resolution, providing the necessary consistency and packaging. Validation of this packaged Level 3 AOD product against Aerosol Robotics NETwork (AERONET) measurements across global locations showcased the merged product's robustness with a correlation coefficient of 0.83, revealing a global mean bias of approximately ±0.05, with 65.5 % of retrievals falling within an expected uncertainty range, underlining the reliability of the dataset. The new gridded Level 3 dataset significantly improved daily global coverage to nearly 45 %, overcoming the limitations of individual sensors, which typically range from 12 % to 25 %. Furthermore, this merged dataset approximates the diurnal cycle of AOD observed by AERONET, thus offering insights into diurnal signatures retrieved elsewhere. The resulting dataset's high spatiotemporal resolution and improved global coverage, especially in regions covered by GEO sensors (Americas and Asia), make it a valuable tool for diverse applications. Tracking aerosol transport from phenomena like wildfires and dust storms is gaining precision, enabling enhanced air quality forecasting and hindcasting. Additionally, the study positions the merged dataset as a significant asset for evaluating and intercomparing regional or global model simulations, which was previously unattainable in such a gridded format. The dataset and fusion framework layout in this study have the potential to include data from recently (future) launched other GEO (FCI, AMI) and LEO (PACE, VIIRS-JPSS) sensors.

Development of a New Dry Powder Aerosol Synthetic Lung Surfactant Product for Neonatal Respiratory Distress Syndrome (RDS) – Part II: In vivo Efficacy Testing in a Rabbit Surfactant Washout Model

PurposeSurfactant therapy incorporates liquid bolus instillation via endotracheal tube catheter and a mechanical ventilator in preterm neonates with respiratory distress syndrome (RDS). Aerosolized surfactants have generated interest and conflicting data on the efficacy of phospholipid (PL) dose requirements. We developed and characterized a synthetic lung surfactant excipient enhanced growth (SLS-EEG) dry powder aerosol product. In this study, we compare the in vivo performance of the new aerosol product with standard-of-care liquid instillation.MethodsJuvenile rabbits were sedated, anesthetized, intubated, and ventilated. Endogenous surfactant was depleted via whole lung lavage. Animals received either a standard dose of liquid Curosurf (200 mg PL/kg) instilled via a tracheal catheter, SLS-EEG powder aerosol (60 mg device loaded dose; equivalent to 24 mg PL/kg), or sham control. Gas exchange, lung compliance, and indices of disease severity were recorded every 30 min for 3.5 h and macro- and microscopy images were acquired at necropsy.ResultsWhile aerosol was administered at an approximately tenfold lower PL dose, both liquid-instilled and aerosol groups had similar, nearly complete recoveries of arterial oxygenation (PaO2; 96–100% recovery) and oxygenation index, and the aerosol group had superior recovery of compliance (P < 0.05). The SLS-EEG aerosol group showed less lung tissue injury, greater uniformity in lung aeration, and more homogenous surfactant distribution at the alveolar surfaces compared with liquid Curosurf.ConclusionsThe new dry powder aerosol SLS product (which includes the delivery strategy, formulation, and delivery system) has the potential to be a safe, effective, and economical alternative to the current clinical standard of liquid bolus surfactant instillation.

Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison

This paper is the second part of companion papers describing the development of GRASP approach for aerosol and surface retrieval from Sentinel-5P/TROPOMI. Here we focus on the S5P/TROPOMI GRASP aerosol and surface products global validation and systematic intercomparison with other products from independent instruments and algorithms. Specifically, we have validated the S5P/TROPOMI GRASP, Suomi-NPP/VIIRS DB and MODIS/TERRA DT + DB aerosol products with the ground-based AERONET referenced measurements using the same methodology and intercompare the validation results. In addition, the global pixel-to-pixel intercomparisons of the aerosol products (AOD, fine/coarse mode AOD and SSA) are performed over different surfaces, i.e., ocean and land surface with different NDVIs. Besides, we compared the S5P/TROPOMI GRASP, MODIS MCD43 surface BRDF/albedo as well as OMI, GOME-2 and SCIAMACHY Lambertian-Equivalent Reflectivity (LER) albedo climatology developed by Royal Netherlands Meteorological Institute (KNMI) with the surface reference dataset generated based on the synergetic retrieval of AERONET and S5P/TROPOMI measurements. Finally, the intercomparisons of the surface BRDF and albedo datasets were performed globally at the UV, VIS, NIR and SWIR parts of the spectrum. Overall, generally good agreement was observed between independent aerosol and surface datasets with a high percentage of pixels satisfying the Optimal and Target requirements. We would emphasize two advantages for TROPOMI/GRASP aerosol and surface products: (i) it provides spectral AOD together with detailed aerosol properties, such as fine/coarse mode AOD, spectral AAOD and SSA at UV, VIS, NIR and SWIR wavelengths, which are important for constraining aerosol environmental and climate effects; (ii) the TROPOMI/GRASP aerosol and surface products are globally retrieved simultaneously in a fully consistent manner.

Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States.

Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data. We developed an innovative angle-dependent deep-learning model (ADLM) that accounts for angular diversity in dual-angle observations. The model captures aerosol properties observed from dual angles in the contiguous United States and explores the potential of Greenhouse gases Observing Satellite-2's (GOSAT-2) measurements to retrieve fAOD at a 460 m spatial resolution. The ADLM demonstrates a strong performance through rigorous validation against ground-based data, revealing small biases. By comparison, the official fAOD product from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Multiangle Imaging Spectroradiometer (MISR) during wildfire events is underestimated by more than 40% over western USA. This leads to significant differences in estimates of aerosol radiative forcing (ARF) from wildfires. The ADLM shows more than 20% stronger ARF than the MODIS, VIIRS, and MISR estimates, highlighting a greater impact of wildfire fAOD on Earth's energy balance.

Quality Assessment and Application Scenario Analysis of AGRI Land Aerosol Product from the Geostationary Satellite Fengyun-4B in China.

The Advanced Geostationary Radiation Imager (AGRI) sensor on board the geostationary satellite Fengyun-4B (FY-4B) is capable of capturing particles in different phases in the atmospheric environment and acquiring aerosol observation data with high spatial and temporal resolution. To understand the quality of the Land Aerosol (LDA) product of AGRI and its application prospects, we conducted a comprehensive evaluation of the AGRI LDA AOD. Using the 550 nm AGRI LDA AOD (550 nm) of nearly 1 year (1 October 2022 to 30 September 2023) to compare with the Aerosol Robotic Network (AERONET), MODIS MAIAC, and Himawari-9/AHI AODs. Results show the erratic algorithmic performance of AGRI LDA AOD, the correlation coefficient (R), mean error (Bias), root mean square error (RMSE), and the percentage of data with errors falling within the expected error envelope of ±(0.05+0.15×AODAERONET) (within EE15) of the LDA AOD dataset are 0.55, 0.328, 0.533, and 34%, respectively. The LDA AOD appears to be overestimated easily in the southern and western regions of China and performs poorly in the offshore areas, with an R of 0.43, a Bias of 0.334, a larger RMSE of 0.597, and a global climate observing system fraction (GCOSF) percentage of 15% compared to the inland areas (R = 0.60, Bias = 0.163, RMSE = 0.509, GCOSF = 17%). Future improvements should focus on surface reflectance calculation, water vapor attenuation, and more suitable aerosol model selection to improve the algorithm's accuracy.