Aerosol Observations Research Articles

Aircraft observation of aerosol and mixed-phase cloud microphysical over the North China Plain, China: Vertical distribution, size distribution, and effects of cloud seeding in two-layered clouds

Aerosol and clouds are essential to climate effects. Based on an aircraft observation in a mixed-phase cloud in Shijiazhuang, China, on November 21, 2020, analyzing the vertical and size distributions of cloud droplets, and ice crystal particles, and the effects of the similar to a “seeder-feeder” process after cloud seeding on cloud microphysics. The first seeding cloud (CS1) and second seeding cloud (CS2) were at 2600–2800 m and 1500–2300 m, respectively. Before seeding, the average number concentration of cloud droplets (Nc) was 236.91 cm−3 and 152.13 cm−3 in CS1 and CS2 from vertical observation. In CS1, the average number concentration of ice crystals (Ni) was 0.26 L−1 with dendritic ice crystals and graupel, while in CS2, the average Ni was 0.19 L−1, including rimed plate ice crystals, graupel, and needle ice crystals. After seeding, the average Nc decreased from 322.90 to 260.69 cm−3 and the spectrum of Nc broadened from 2.5 to 24 to 45 μm in CS1. The ice microphysics also had different responses in the layered cloud. Ni increased by 421 times in regions with high Nc and low LWC (Nc > 322.90 cm−3, LWC < 0.14 g∙m−3), including spoked and heavily rimed ice crystals and graupel (200–500 μm) in CS1. In CS2, the maximum Ni was 252.03 L−1 and the average Ni increased by 2 magnitudes (from 0.39 to 11.44 L−1). There were rimed needles and columnar ice crystals (200–300 μm) in regions with high Nc and high LWC (Nc > 92.78 cm−3, LWC > 0.13 g∙m−3), and high Nc and low LWC (Nc > 92.78 cm−3, LWC < 0.13 g∙m−3). Seeding in CS1 and CS2 formed a structure similar to the “seeder-feeder” process. Controlled by the downdraft (>1 m/s), these particles descended into the “feeder” region of CS2. Appropriate temperature and rimed crystals contributed to secondary ice crystal production (SIP), resulting in main columns (200–300 μm) observed in CS2. The “feeder” region generated more ice crystals than the “seeder” region.

On the рossibility of multichannel optical backscattering sondes for joint balloon and lidar studies of the aerosol composition of the middle atmosphere

Aerosol backscattering sondes in the practice of aerological sounding, along with lidar observations, are used at night to study and monitor polar stratospheric clouds, tropospheric and stratospheric aerosol, cirrus clouds, pyroconvection, volcanic aerosol, as well as to verify remote methods and means of ground-based and satellite-based aerosol observations. For aerosol sondes, a simple two-wave measurement technique is used, which makes it possible to diagnose changes in aerosol composition by color index. The possibilities of the two-wave technique have limitations, which are discussed in this article. Aerological sounding combined with lidar observations expands the wavelength range for multi-wavelength studies, and direct measurements of atmospheric temperature increase the accuracy of aerosol sensing. The paper considers the application of 3 or more wavelenght techniques. Data from probe measurements using wavelengths of 470, 528, 850 and 940 nm and lidar sensing at wavelengths of 355 and 532 nm are presented.

From Polar Day to Polar Night: A Comprehensive Sun and Star Photometer Study of Trends in Arctic Aerosol Properties in Ny-Ålesund, Svalbard

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources.

Mobile laboratory measurements of air pollutants in Baltimore, MD elucidate issues of environmental justice

ABSTRACT The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations – near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0–10.9] μg m−3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 – 1.8] μg m−3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles. Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source – diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems. Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

A machine learning paradigm for necessary observations to reduce uncertainties in aerosol climate forcing.

Uncertainties in estimates of climate cooling by anthropogenic aerosols have not decreased significantly in the last two decades, partly because observational constraints on crucial aerosol properties simulated in Earth System Models are insufficient. To help address this insufficiency in aerosol observations, we describe a paradigm for deriving higher-level aerosol properties with machine learning algorithms that use only lidar observations and reanalysis data as predictors. Our paradigm employs high-accuracy suborbital lidar and collocated in situ measurements to train and test two fully-connected neural network algorithms. We use two lidar data sets as input to our machine learning algorithms. The first data set consists of suborbital lidar observations not previously used in the training of the machine learning algorithms. The second data set consists of simulated UV-only observations to preview the algorithms' predictive capabilities in anticipation of data from the ATmospheric LIDar system on the EarthCARE satellite, which was launched in May 2024. Here we show that our algorithms predict two crucial aerosol properties, aerosol light absorption and cloud condensation nuclei concentrations with unprecedented accuracy, yielding mean relative errors of 21% and 13%, respectively, when suborbital lidar data are used as predictors. These errors represent significant improvements over conventional aerosol retrievals. Applied to future satellite missions, the paradigm presented here has great potential for constraining Earth System Models and reducing uncertainties in their estimates of aerosol climate forcing and future global warming.

Development and observation of a three-dimensional scanning coaxial Mie lidar for dynamic monitoring of near-surface aerosol plumes

Accurate three-dimensional spatiotemporal distribution information on near-surface aerosols is of great significance for environmental research. In this study, a 3D scanning coaxial Mie lidar (3D-STML) was developed to achieve a fast three-dimensional scanning observation of aerosol diffusion processes in near-surface areas. 3D-STML generates high-spatiotemporal resolution images of aerosol extinction coefficient in real-time and captures the dynamic changes of aerosols in near real-time. By optimizing the design of the light guide mirror and the telescope sub-mirror, the system has a small overlap. Based on this, a highly stable and high-speed mechanical rotation mechanism was developed to enable three-dimensional observations. The integration of a solid-state high-repetition-rate pulsed laser and a coaxial, optical system for the transmitter and receiver ensures rapid tracking of aerosol plumes. To meet the observation requirements of near-surface aerosols, an aerosol inversion algorithm combining the Fernald and Klett methods was designed and developed. For aerosol plume monitoring needs, an aerosol plume-tracking algorithm based on Kalman filtering was developed to track the spatiotemporal evolution of aerosols automatically. Experimental results demonstrated that 3D-STML is capable of detecting aerosols in a range from 15 m to 4 km, with a distance resolution of 1.5 m and a time resolution of 0.083 s. It can effectively track and capture aerosol plumes. It can be used for large-scale, long-term observation of near-surface aerosols and for monitoring the spatiotemporal evolution of aerosol plumes.

Extreme wildfires over northern Greece during summer 2023 – Part A: Effects on aerosol optical properties and solar UV radiation

In Mediterranean countries, such as Greece, the frequency of forest fires has increased in recent years, primarily due to the widespread impacts of climate change. At the end of August 2023, Greece experienced a record-breaking heatwave that triggered severe wildfire incidents, significantly impacting the atmospheric conditions of several cities, among them Thessaloniki. A significant number of wildfires occurred in northern Greece (Evros), burning thousands of hectares of the protected Dadia forest (Natura 2000) and releasing a significant load of smoke into the atmosphere. According to the European Strategy Forum on Research Infrastructures (ESFRI) a total area of 90,000ha was burnt collectively by the Evros extreme wildfires during August 2023. The emissions led to severely adverse air pollution conditions, causing reduced visibility across an extended eastern Mediterranean region for several days. In this work, we analyze the influence of the transported biomass burning particles on the aerosol properties in the free troposphere, as well as on the surface UV radiation levels over Thessaloniki during the last week of August 2023. The transported smoke plume was detected over the Laboratory of Atmospheric Physics (LAP) in Thessaloniki, approximately 240 km away from the burning area, from August 22nd to the 25th. During this period, the presence of smoke led to exceptionally increased levels of aerosol optical depth (AOD), reaching up to 3.4 at 340nm (the highest ever recorded in Thessaloniki), as well as high Ångström exponent (AE) values, peaking at 2.4 for the 440–870nm range, followed by high Fine Mode Fractions (FMFs), indicating the prevalence of fine-mode smoke aerosol particle. Moreover, during the event, the presence of the biomass burning aerosols led to a strong attenuation of the solar UV irradiance by up to 90 %, reaching unprecedented levels, similar of a solar eclipse. The primary goal of this study is to highlight the extensive impacts that wildfires have, which are anticipated to increase in frequency in the near future, due to the predicted rise in the rate of occurrence of summer heatwaves especially for Mediterranean areas and specifically for Greece. Furthermore, the great value of the synergistic monitoring of the event with ground-based remote sensing instrumentation, along with satellite aerosol observations and modeling tools, is made prominent.

Observation and Classification of Low-Altitude Haze Aerosols Using Fluorescence–Raman–Mie Polarization Lidar in Beijing during Spring 2024

Haze aerosols have a profound impact on air quality and pose serious health risks to the public. Due to its geographical location, Beijing experienced haze events in the spring of 2024. Lidar is an active remote sensing technology with a high spatiotemporal resolution and the ability to classify aerosols, and it is essential for effective haze monitoring. This study utilizes fluorescence–Raman–Mie polarization lidar with an emission wavelength of 355 nm, employing the δp-Gf method based on the particle depolarization ratio at 355 nm (δp355) and the fluorescence capacity (Gf), and combines meteorological data and backward-trajectory analysis to observe and classify low-altitude haze aerosols in Beijing during the spring of 2024. Notably, a mining dust event with strong fluorescence backscatter was detected. The haze aerosols were categorized into three types: pollution aerosols, desert dust, and mining dust. Their optical properties were summarized and compared. Desert dust showed a particle depolarization ratio range of 0.23–0.39 and a fluorescence capacity range from 0.18 × 10−4 to 0.63 × 10−4. Pollution aerosols had a larger fluorescence capacity but a lower depolarization ratio compared to desert dust, with a fluorescence capacity ranging from 0.55 × 10−4 to 1.10 × 10−4 and a depolarization ratio ranging from 0.10 to 0.17. Mining dust shared similar depolarization characteristics with desert dust but had a larger fluorescence capacity, ranging from 0.71 × 10−4 to 1.23 × 10−4, with a depolarization ratio range of 0.30–0.39. This study validates the effectiveness of the δp355-Gf method in classifying low-altitude haze aerosols in Beijing. Additionally, it offers a new perspective for more detailed dust classification using lidar. Furthermore, utilizing the δp355-Gf classification method and the δp355-Gf distributions of three typical aerosol samples, we developed a set of equations for the analysis of mixed aerosols. This method facilitates the separation and fraction analysis of aerosol components under various mixing scenarios. It enables the characterization of variations in the three types of haze aerosols at different altitudes and times, offering valuable insights into the interactions between desert dust, mining dust, and pollution aerosols in Beijing.

Constraining Present‐Day Anthropogenic Total Iron Emissions Using Model and Observations

AbstractIron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long‐term, near‐source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub‐sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under‐ or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting‐related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long‐term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.

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.

In-situ aircraft observations of aerosol and cloud microphysical characteristics of mixed-phase clouds over the North China Plain

Aerosol-cloud interactions play a vital role in climate change. This study leverages observations from the King-350 aircraft over the North China Plain on November 29, 2019, to examine aerosol and cloud microphysical characteristics of mixed-phase clouds. Through detailed vertical and spectral distributions, we investigate aerosol, cloud droplet, and ice crystal distributions in seeded clouds (SC) and natural precipitating clouds (NPC) within the same cloud system. From the vertical profile, SC and NPC have similar vertical distributions of aerosol and cloud droplets, with over 95 % of aerosols concentrated below 1600 m near the ground. Cloud droplets are more evenly distributed within the two clouds, cloud droplet number concentrations (Nc) in SC were three orders of magnitude higher than in NPC. Ice water content (IWC) and ice crystal number concentration (Ni) show distinct layer preferences—accumulating predominantly in SC's top layer and NPC's middle layer. From spectral distribution, a smaller proportion of cloud droplets (40–50 μm in diameter, the same hereafter) in SC compared to NPC. Rimed ice crystals and globular graupel (1325–1550 μm in diameter) were in SC, while plate and irregular ice crystals (300–450 μm) were in NPC with an order of magnitude higher than in SC. These microphysical differences highlight the complexity of cloud seeding efficacy, which varies based on cloud conditions and microphysical properties. In the first seeding, Ni increased by 1–2 orders of magnitude (125–300 μm) in the high Nc (Nc > 1.11 × 105 L−1) region. Seeding in low Nc (Nc < 1.11 × 105 L−1) regions was hard to be effective, especially in low Nc and low liquid water content (LWC) (LWC < 0.122 g/m3) regions. In the second seeding, ice crystals (125–250 μm) produced by the first seeding enhance the seeding efficiency. The responded regions were more sensitive to subsequent seeding, resulting in stronger reactions or longer duration.

Ground-Based Remote Sensing of Aerosol, Clouds, Dynamics, and Precipitation in Antarctica: First Results from the 1-Year COALA Campaign at Neumayer Station III in 2023

Abstract Novel observations of aerosol and clouds by means of ground-based remote sensing have been performed in Antarctica over the Ekström Ice Shelf on the coast of Dronning Maud Land at Neumayer Station III (70.67°S, 8.27°W) from January to December 2023. The deployment of the OCEANET-Atmosphere remote sensing observatory in the framework of the Continuous Observations of Aerosol-Cloud Interaction (COALA) campaign has brought Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) aerosol and cloud profiling capabilities next to meteorological and air chemistry in situ observations at the Antarctic station. We present an overview of the site, the instrumental setup, and data analysis strategy and introduce 3 scientific highlights from austral fall and winter, namely, 1) observations of a persistent mixed-phase cloud embedded in a plume of marine aerosol. Remote sensing–based retrievals of cloud-relevant aerosol properties and cloud microphysical parameters confirm that the free-tropospheric mixed-phase cloud layer formed in an aerosol-limited environment. 2) Two extraordinary warm air intrusions: one with intense snowfall produced the equivalent of 10% of the yearly snow accumulation and a second one with record-breaking maximum temperatures and heavy icing due to supercooled drizzle. 3) Omnipresent aerosol layers in the stratosphere. Our profiling capabilities could show that 50% of the 500-nm aerosol optical depth of 0.06 was caused by stratospheric aerosol, while the troposphere was usually pristine. As demonstrated by these highlights, the 1-yr COALA observations will serve as a reference dataset for the vertical structure of aerosol and clouds above the region, enabling future observational and modeling studies to advance understanding of atmospheric processes in Antarctica.

Impact of sea ice on the physicochemical characteristics of marine aerosols in the Arctic Ocean

Marine aerosols (MA) can be influenced by sea ice concentration, potentially playing a pivotal role in the formation of cloud condensation nuclei and exerting an impact on regional climate. In this study, a high-resolution aerosol observation system was employed to measure the concentration and size of aerosols in the floating ice region and seawater region of the Arctic Ocean during the 8th and 9th Chinese Arctic Expedition Research Cruise. The identification of aerosol sources was conducted using a modified positive definite matrix factorization method and a backward air mass trajectory model. Two types of MA including the sea-salt aerosol (SSA) and the marine biogenic aerosol (BA) were identified and their concentrations were calculated. Then the physical-chemical characteristics of MA in the floating ice region and seawater region were compared under normalized conditions (−2.5 °C < T < −0.1 °C; 5.80 m/s < WS < 10.95 m/s) to discern the impact of sea ice. A unimodal distribution was observed for MA number concentration with a dominant peak ranging from 0.5 μm to 1.0 μm in size range. The findings revealed that the presence of sea ice cover led to a significant reduction of 52.2 % in the number concentration of SSA, while exerting minimal influence on its composition. BA number concentration in the floating ice region was 33.3 % higher than that in the seawater region. Strong winds (wind speed >6.5 m/s) transported organic matter and nutrients entrapped in sea ice into the atmosphere, leading to an increase in BA concentration. However, the presence of sea ice cover hampered the exchange of biogenic gases between the ocean and air, resulting in a reduction of secondary BA formation. Our study elucidates the correlation between MA release and sea ice coverage in the Arctic Ocean, thereby establishing a theoretical foundation for climate prediction models.

Evolution of the Climate Forcing During the Two Years After the Hunga Tonga‐Hunga Ha'apai Eruption

AbstractWe calculate the climate forcing for the 2 ys after the 15 January 2022, Hunga Tonga‐Hunga Ha'apai (Hunga) eruption. We use satellite observations of stratospheric aerosols, trace gases and temperatures to compute the tropopause radiative flux changes relative to climatology. Overall, the net downward radiative flux decreased compared to climatology. The Hunga stratospheric water vapor anomaly initially increases the downward infrared radiative flux, but this forcing diminishes as the anomaly disperses. The Hunga aerosols cause a solar flux reduction that dominates the net flux change over most of the 2 yrs period. Hunga induced temperature changes produce a decrease in downward long‐wave flux. Hunga induced ozone reduction increases the short‐wave downward flux creating small sub‐tropical increase in total flux from mid‐2022 to 2023. By the end of 2023, most of the Hunga induced radiative forcing changes have disappeared. There is some disagreement in the satellite measured stratospheric aerosol optical depth (SAOD) observations which we view as a measure of the uncertainty; however, the SAOD uncertainty does not alter our conclusion that, overall, aerosols dominate the radiative flux changes.

Pan-Arctic methanesulfonic acid aerosol: source regions, atmospheric drivers, and future projections

Natural aerosols are an important, yet understudied, part of the Arctic climate system. Natural marine biogenic aerosol components (e.g., methanesulfonic acid, MSA) are becoming increasingly important due to changing environmental conditions. In this study, we combine in situ aerosol observations with atmospheric transport modeling and meteorological reanalysis data in a data-driven framework with the aim to (1) identify the seasonal cycles and source regions of MSA, (2) elucidate the relationships between MSA and atmospheric variables, and (3) project the response of MSA based on trends extrapolated from reanalysis variables and determine which variables are contributing to these projected changes. We have identified the main source areas of MSA to be the Atlantic and Pacific sectors of the Arctic. Using gradient-boosted trees, we were able to explain 84% of the variance and find that the most important variables for MSA are indirectly related to either the gas- or aqueous-phase oxidation of dimethyl sulfide (DMS): shortwave and longwave downwelling radiation, temperature, and low cloud cover. We project MSA to undergo a seasonal shift, with non-monotonic decreases in April/May and increases in June-September, over the next 50 years. Different variables in different months are driving these changes, highlighting the complexity of influences on this natural aerosol component. Although the response of MSA due to changing oceanic variables (sea surface temperature, DMS emissions, and sea ice) and precipitation remains to be seen, here we are able to show that MSA will likely undergo a seasonal shift solely due to changes in atmospheric variables.

Sensitivity of cloud microphysics to aerosol is highly associated with cloud water content: Implications for indirect radiative forcing

The sensitivity of cloud microphysics to aerosol loading, quantified by the aerosol-cloud interactions (ACI) index, plays a crucial role in calculating the radiative forcing due to ACI (RFaci). However, the dependence of the ACI index on liquid water content (LWC) and its impact on RFaci are often overlooked. This study aims to investigate this dependence and evaluate its implications for RFaci, based on ground in-situ aerosol-cloud observations on Mt. Lu in eastern China. The results demonstrate that the ACI index exhibits an initial increase, followed by a decline with increasing LWC. In the unconstrained LWC scenario, the ACI index, calculated based on cloud droplet number concentration (ACIn of 0.13), is found to be lower than the lower bound of ACIn (0.17 to 0.35) obtained from the constrained LWC scenario. Neglecting this LWC-dependence leads to a significant underestimation of the mean RFaci by 53%. Furthermore, when calculating RFaci using the ACI index from droplet effective diameter (ACId), implying the neglect of the dispersion effect by assuming a fixed droplet spectrum width, it results in an overestimation of RFaci by 22% compared to using ACIn. These findings shed new light on the assessment of RFaci and help reconcile differences between observed and simulated RFaci. Plain language summaryAerosol-cloud interactions are the major source of uncertainty in understanding human-induced climate change. This study focused on the relationship between aerosol and clouds, specifically investigating how the sensitivity of cloud properties to aerosol loading associates with the amount of liquid water present in the clouds. Using ground in-situ observations of clouds and aerosols on Mt. Lu in eastern China, this study showed that the sensitivity of cloud properties to aerosol loading initially increases and then decreases as the cloud water content increases. Neglecting this dependence can lead to a significant underestimation of the impact of aerosol-cloud interactions on climate. These findings provide valuable insights for improving our understanding of how aerosols and clouds interact and contribute to climate change.

Addressing observational gaps in aerosol parameters using machine learning: Implications to aerosol radiative forcing

The role of atmospheric aerosols has remained hugely uncertain due to lack of long-term systematic observations. This is particularly the case in the global emission hotspot the Indo-Gangetic Plain. In this paper, we apply a machine learning (ML) approach to fill gaps in aerosol observations by combining meteorological reanalysis, and satellite-observations. Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Asymmetry Parameter (AP) are critical parameters for understanding the atmospheric aerosol properties, radiative forcing and climate patterns. We considered AOD, SSA, and AP over an urban site, Kanpur, in the Indo-Gangetic Plain, which is a global hot-spot of high aerosol loading. We used ML technique to fill the observational gaps in AOD, SSA, and AP at 440 nm. Accurate ground-based daily observations of AOD, SSA, and AP from AERONET (Aerosol Robotic Network) over a period of ∼2 decades (2001–2022) are used in the analysis, which have ∼ 37%, ∼62%, and ∼58% data gap, respectively. To reduce observational gaps, an ML model was trained with reanalysis (meteorological parameters) and satellite (angstrom exponent and absorbing aerosol index) datasets by optimally tuning the hyperparameters. The model tested on unseen data showed that it could simulate the AOD (coefficient of determination, R2 = 0.51 and refined index of agreement, RIA = 0.66), SSA (R2 = 0.60 and RIA = 0.70), and AP (R2 = 0.64 and RIA = 0.71), successfully with moderate accuracies: root mean square error of 0.25, 0.018, and 0.018, respectively. This magnitude of error in AOD is comparable to the errors, 0.26 and 0.25, in satellite (MODIS-Moderate Resolution Imaging Spectroradiometer) derived and reanalysis (MERRA-2- Modern-Era Retrospective analysis for Research and Applications, Version 2) AODs, respectively for the study region. When MODIS AOD was included as a predictor in the ML model, it could reproduce AOD with much smaller errors of 0.14, reproducing 84% of total variability. Thus, based on available input data, we reduced observational gaps of daily AOD, SSA, and AP by ∼10% (∼2 years), ∼23% (∼5 years), and ∼21% (∼4 years), respectively, at the study region. Aerosol Radiative Forcing (ARF) at the top-of-atmosphere was estimated using AOD, SSA, and AP both with and without gap-filling. We found that data gaps can significantly impact the estimations of aerosol climate forcing. A considerable change in ARF, ∼ ± 3 Wm−2 indicating that the observational gaps can mislead our understanding of aerosols' impact on climate. This points toward the need for more comprehensive measurements with minimal observational gaps. Our study highlights the possibility of compensating observational gaps by an optimised ML model and that such innovative approach can potentially lead to better understanding of impact of aerosols on climate. Further, the present study could be of immense interest for the community as our validated approach can be applied for other pollutants and for other data-scarce regions in the South and Southeast Asia.

Shipborne observations of black carbon aerosols in the western Arctic Ocean during summer and autumn 2016–2020: impact of boreal fires

Abstract. Black carbon (BC) aerosol is considered one of the most important contributors to rapid climate warming as well as snow and sea ice melting in the Arctic, yet the observations of BC aerosols in the Arctic Ocean have been limited due to infrastructural and logistical difficulties. We observed BC mass concentrations (mBC) using light absorption methods on board the icebreaker R/V Araon in the Arctic Ocean (&lt; 80° N and 166° E to 156° W) as well as the North Pacific Ocean in summer and early autumn of 2016–2020. The levels, interannual variations, and pollution episodes of mBC in the Arctic were examined, and the emission sources responsible for the high-BC episodes were analyzed with global chemistry-transport-model simulations. The average mBC in the surface air over the Arctic Ocean (72–80° N) observed by the 2019 cruise exceeded 70 ng m−3, which was substantially higher than that observed by cruises in other years (approximately 10 ng m−3). The much higher mBC observed in 2019 was perhaps due to more frequent wildfires occurring in the Arctic region than in other years. The model suggested that biomass burning contributed most to the observed BC by mass in the western Arctic Ocean and the marginal seas. For these 5 years, we identified 10 high-BC episodes north of 65° N, including one in 2018 that was associated with co-enhancements of CO and CH4 but not CO2 and O3. The model analysis indicated that certain episodes were attributed to BC-containing air masses transported from boreal fire regions to the Arctic Ocean, with some transport occurring near the surface and others in the mid-troposphere. This study provides crucial datasets on BC mass concentrations and the mixing ratios of O3, CH4, CO, and CO2 in the western Arctic Ocean regions, and it highlights the significant impact of boreal fires on the observed Arctic BC during the summer and early autumn months.

Assessment of light-absorbing carbonaceous aerosol origins and properties at the ATOLL site in northern France

Abstract. Understanding the lifecycle of light-absorbing carbonaceous aerosols, from emission to deposition, is critical for assessing their climate impact. This study integrated multi-year aerosol observations from the ATOLL (ATmospheric Observations in liLLe, northern France) platform, with air mass back trajectories and emission inventory as a newly developed “INTERPLAY” (IN-siTu obsERvations, hysPLit, And emission inventorY) approach. Applied to black carbon (BC), the method apportioned source contributions (shipping, vehicular, residential heating, industrial) and studied aerosol aging effects, notably on the brown carbon (BrC) component. Results estimate that, throughout the year, vehicular traffic dominated BC (31 %), followed by shipping (25 %, of which one-third was from canals/rivers) and residential heating (21 %). Comparing INTERPLAY results with the aethalometer model highlights that the “residential sector” BC can be entirely apportioned to BC from wood burning (BCwb), notably in winter, while vehicular traffic corresponds to only about 41 % of BC fossil fuel (BCff) at the ATOLL site, the rest being apportioned to shipping (33 %) and industrial (23 %) emissions. Thus, vehicular traffic and BCff should not be used interchangeably, particularly in regions near intense maritime traffic. Concerning BrC, our analysis confirms a dominant role of residential heating. Focusing on winter, results suggest a considerable decrease in the BrC component only 24 h after emission, with fresh residential emissions being responsible for 72 % of BrC absorption at ATOLL. The results from this study allow for an improved understanding of sources and atmospheric dynamics of light-absorbing carbonaceous aerosols in northern France, being crucial for both source abatement strategies as well as a better assessment of their climate impact.

Use of an uncrewed aerial system to investigate aerosol direct and indirect radiative forcing effects in the marine atmosphere

Abstract. An uncrewed aerial system (UAS) has been developed for observations of aerosol and cloud properties relevant to aerosol direct and indirect forcing in the marine atmosphere. The UAS is a Hybrid Quadrotor–fixed-wing aircraft designed for launch and recovery from a confined space such as a ship deck. Two payloads, clear sky and cloudy sky, house instrumentation required to characterize aerosol radiative forcing effects. The observing platform (UAS plus payloads) has been deployed from a ship and from a coastal site for observations in the marine atmosphere. We describe here details of the UAS, the payloads, and first observations from the TowBoatU.S. Richard L. Becker (March 2022) and from the Tillamook UAS Test Range (August 2022). The development of this UAS technology for flights from ships and coastal locations is expected to greatly increase observations of aerosol radiative effects in the marine boundary layer over both temporal and spatial scales.