Continental Aerosols Research Articles

Biological and dust aerosols as sources of ice-nucleating particles in the eastern Mediterranean: source apportionment, atmospheric processing and parameterization

Abstract. Aerosol–cloud interactions in mixed-phase clouds (MPCs) are one of the most uncertain drivers of the hydrological cycle and climate change. A synergy of in situ, remote-sensing and modelling experiments were used to determine the source of ice-nucleating particles (INPs) for MPCs at Mount Helmos in the eastern Mediterranean. The influences of boundary layer turbulence, vertical aerosol distributions and meteorological conditions were also examined. When the observation site is in the free troposphere (FT), approximately 1 in ×106 aerosol particles serve as INPs around −25 °C. The INP abundance spans 3 orders of magnitude and increases in the following order: marine aerosols; continental aerosols; and, finally, dust plumes. Biological particles are important INPs observed in continental and marine aerosols, whereas they play a secondary, although important, role during Saharan dust events. Air masses in the planetary boundary layer (PBL) show both enriched INP concentrations and a higher proportion of INPs to total aerosol particles, compared with cases in the FT. The presence of precipitation/clouds enriches INPs in the FT but decreases INPs in the PBL. Additionally, new INP parameterizations are developed that incorporate the ratio of fluorescent-to-nonfluorescent or coarse-to-fine particles and predict >90 % of the observed INPs within an uncertainty range of a factor of 10; these new parameterizations exhibit better performance than current widely used parameterizations and allow ice formation in models to respond to variations in dust and biological particles. The improved parameterizations can help MPC formation simulations in regions with various INP sources or different regions with prevailing INP sources.

Comparisons of aerosol types and optical characters over Shouxian Area China observed from ground- and space-based systems

This study evaluates the performance of moderate-resolution Imaging spectroradiometer (MODIS) in aerosol optical depth(AOD) and Ångström exponent(AE) retrievals under high aerosol loading conditions across various aerosol types, utilizing ground-based and space-borne aerosol measurements in Shouxian, China. The intercomparison reveals cloud-aerosol LiDAR with orthogonal polarization's (CALIOP) efficacy in detecting significant aerosol layers and the refinement of sunphotometer-based aerosol type classification through CALIPSO, achieving approximately 80% accuracy. Analysis of 2016-2017 data indicates substantial aerosol presence in Shouxian, with monthly mean AODs ranging from 0.35 to 0.72 at 550 nm, significantly above the global average. The predominant aerosol types were mixed-type (54.8%), desert dust (21.2%), urban/industrial(15.5%), biomass-burning aerosol (6.4%), and continental aerosol (12.1%), with frequent observations of elevated long-range transported aerosol layers. MODIS AOD retrievals generally align with sunphotometer measurements but exhibit higher biases, especially with increasing AOD magnitudes. However, there is a notable difference between MODIS and sunphotometer aerosol AE measurements, with MODIS accurately assessing BBA but showing varied performance across other aerosol types. The combination of AOD and AE of the DD aerosol type is the most accurate. Further analysis showed that MODIS AOD biases and AE biases are negatively correlated, these negative bias correlations show strong aerosol type sensitivities. Monthly analysis of MODIS and sunphotometer comparisons highlights varying performance, particularly during normalized difference vegetation index (NDVI) transitions, suggesting that local vegetation cycles and associated surface spectral reflectance changes significantly impact MODIS aerosol retrieval accuracy under high aerosol loading conditions.

Continental aerosol properties and absorption retrieval using random forest machine learning method specific to geostationary remote sensing

The utilization of satellite remote sensing images for retrieving aerosol optical parameters has been extensively discussed over the past few decades. While employing machine learning models is indeed a viable approach, a significant portion of these studies still rely on redundant data. Moreover, the discussion regarding aerosol absorption, a crucial factor for determining aerosol radiative impact and distinguishing aerosol components, is limited in current machine learning studies. In this study, we propose a random forest model to retrieve high-precision aerosol properties and their absorption over land from Himawari-8 geostationary satellite images. Remarkably, this model attains a high degree of accuracy in estimating aerosol optical depth (AOD), absorption aerosol optical depth (AAOD), and single scattering albedo (SSA) of heavy air mass using only seven primary predictors (observational radiances or their mathematical combinations, geometries, and wavelength). For AOD, the new random forest model demonstrates excellent performance on an hourly scale (R2 ≥ 0.89, MAE < 0.07, RMSE <0.13), >80% of the samples fall within the expected error (EE) range. Concerning AAOD, the validation indicates that at least 65% of AAODs have a bias of ≤50%, with an R2 exceeding 0.78, MAE ≤ 0.008 and RMSE ≤0.016. SSA also demonstrates a high accuracy (R2 ≥ 0.57, MAE < 0.03, RMSE <0.05), with >70% of the results have an error ≤ 0.03. Through more comprehensive independent spatiotemporal cross validation, it can be determined that the model also offers reliable spatial and temporal predictions. The proposed RF model is capable of learning aerosol properties under most atmosphere scenarios, providing a reasonable conversion from predictors to AOD and AAOD/SSA under high aerosol loadings. The spatial patterns of these parameters suggest that the retrievals show considerable potential in capturing high aerosol loading in East Asia and biomass burning in Southeast Asia. The method introduced in this study offers a new approach to obtaining aerosol properties from geostationary satellite remote sensing, featuring a flexible process, simple inputs, high accuracy, and enhanced robustness. Additionally, it furnishes supplementary insights into aerosol absorption, presenting new possibilities in determining aerosol radiative impact and distinguishing aerosol components.

Consistency of Aerosol Optical Properties between MODIS Satellite Retrievals and AERONET over a 14-Year Period in Central–East Europe

Aerosols influence Earth’s climate by interacting with radiation and clouds. Remote sensing techniques aim to enhance our understanding of aerosol forcing using ground-based and satellite retrievals. Despite technological advancements, challenges persist in reducing uncertainties in satellite remote sensing. Our study examines retrieval biases in MODIS sensors on Terra and Aqua satellites compared to AERONET ground-based measurements. We assess their performance and the correlation with the AERONET aerosol optical depth (AOD) using 14 years of data (2010–2023) from 29 AERONET stations across 10 Central–East European countries. The results indicate discrepancies between MODIS Terra and Aqua retrievals: Terra overestimates the AOD at 16 AERONET stations, while Aqua underestimates the AOD at 21 stations. The examination of temporal biases in the AOD using the calculated estimated error (ER) between AERONET and MODIS retrievals reveals a notable seasonality in coincident retrievals. Both sensors show higher positive AOD biases against AERONET in spring and summer compared to fall and winter, with few ER values for Aqua indicating poor agreement with AERONET. Seasonal variations in correlation strength were noted, with significant improvements from winter to summer (from R2 of 0.58 in winter to R2 of 0.76 in summer for MODIS Terra and from R2 of 0.53 in winter to R2 of 0.74 in summer for MODIS Aqua). Over the fourteen-year period, monthly mean aerosol AOD trends indicate a decrease of −0.00027 from AERONET retrievals and negative monthly mean trends of the AOD from collocated MODIS Terra and Aqua retrievals of −0.00023 and −0.00025, respectively. An aerosol classification analysis showed that mixed aerosols comprised over 30% of the total aerosol composition, while polluted aerosols accounted for more than 22%, and continental aerosols contributed between 22% and 24%. The remaining 20% consists of biomass-burning, dust, and marine aerosols. Based on the aerosol classification method, we computed the bias between the AERONET AE and MODIS AE, which showed higher AE values for AERONET retrievals for a mixture of aerosols and biomass burning, while for marine aerosols, the MODIS AE was larger and for dust the results were inconclusive.

Annual and Seasonal Variations in Aerosol Optical Characteristics in the Huai River Basin, China from 2007 to 2021

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China’s environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality.

Global horizontal irradiance prediction model for multi-site fusion under different aerosol types

Accurate prediction of global horizontal irradiance (GHI) is crucial for anticipating the volatility of solar power output. Under clear-sky conditions, aerosols play a significant role in influencing GHI, with different types of aerosols exhibiting distinct radiation effects. In this study, we employed the Planck mean aerosol optical depth (AOD) —Informer model to forecast future GHI, utilizing historical data of AOD, meteorological parameters, and GHI as input variables. Two data-fusion schemes were proposed, and the calculation results indicate that Scheme 1, organized in the order of Xianghe—Beijing—Shangdianzi (XBS) based on the day as a unit, demonstrates superior prediction performance. Additionally, the site information was blurred, allowing for the flexible selection of input and output lengths. The calculation results remained stable and reliable, suggesting that the inclusion of fuzzy site information does not degrade the prediction effect. Building upon this, we categorized aerosols into three types based on their time span and data volume. GHI predictions for different aerosol types revealed that the mean square error (0.145) for marine aerosols were significantly lower than those for the other types. The GHI predictions for continental aerosols were closest to the true values.

Characteristics and optical properties of atmospheric aerosols based on long-term AERONET investigations in an urban environment of Pakistan

Radiative balance, local climate, and human health are all significantly influenced by aerosol. Recent severe air pollution over Lahore, a city in Pakistan calls for more thorough research to determine the negative impacts brought on by too many aerosols. To study regional aerosol characteristics and their differences from various aspects, in-depth and long-term (2007–2020) investigations of the columnar aerosol properties over the urban environment of Lahore were carried out by using AERONET data. The Aerosol Optical Depth (AOD400) and Angstrom Exponent (AE400–870) vary from low values of 0.10 to a maximum value of 4.51 and from 0.03 to 1.81, respectively. The huge differences in the amount of AOD440 as well as AE440–870 show the large fluctuation of aerosol classes because of various sources of their emission. During the autumn and winter seasons, the decreasing trend of the optical parameters of aerosols like Single Scattering Albedo (SSA) and Asymmetry Parameter (ASY) with increasing wavelength from 675 to 1020 nm indicates the dominance of light-absorbing aerosols (biomass burning (BB) and industrial/urban (UI). Due to the long-distance dust movement during spring, summer, and autumn, coarse mode particles predominated in Lahore during the study period. Dust type (DD) aerosols are found to be the dominant one during spring (46.92%), summer (54.31%), and autumn (57.46%) while urban industry (BB/UI) was dominant during the winter season (53.21%). During each season, the clean continental (CC) aerosols are found to be in negligible amounts, indicating terrible air quality in Lahore City. The present research work fills up the study gap in the optical properties of aerosols in Lahore and will help us understand more fully how local aerosol fluctuation affects regional climate change over the urban environment of Lahore.

Aerosol-related effects on the occurrence of heterogeneous ice formation over Lauder, New Zealand ∕ Aotearoa

Abstract. The presented study investigates the efficiency of heterogeneous ice formation in natural clouds over Lauder, New Zealand / Aotearoa. Aerosol conditions in the middle troposphere above Lauder are subject to huge contrasts. Clean, pristine air masses from Antarctica and the Southern Ocean arrive under southerly flow conditions, while high aerosol loads can occur when air masses are advected from nearby Australia. This study assesses how these contrasts in aerosol load affect the ice formation efficiency in stratiform midlevel clouds in the heterogeneous freezing range (−40 to 0 ∘C). For this purpose, an 11-year dataset was analyzed from a dual-wavelength polarization lidar system operated by National Institute of Water and Atmospheric Research (NIWA), Taihoro Nukurangi, at Lauder in collaboration with the National Institute for Environmental Studies in Japan and the Meteorological Research Institute of the Japan Meteorological Agency. These data were used to investigate the efficiency of heterogeneous ice formation in clouds over the site as a function of cloud-top temperature as in previous studies at other locations. The Lauder cloud dataset was put into context with lidar studies from contrasting regions such as Germany and southern Chile. The ice formation efficiency found at Lauder is lower than in polluted midlatitudes (i.e., Germany) but higher than, for example, in southern Chile. Both Lauder and southern Chile are subject to generally low free-tropospheric aerosol loads, which suggests that the low ice formation efficiency at these two sites is related to low ice-nucleating-particle (INP) concentrations. However, Lauder sees episodes of continental aerosol, more than southern Chile does, which seems to lead to the moderately increased ice formation efficiency. Trajectory-based tools and aerosol model reanalyses are used to relate this cloud dataset to the aerosol load and the air mass sources. Both analyses point clearly to higher ice formation efficiency for clouds which are more strongly influenced by continental aerosol and to lower ice formation efficiency for clouds which are more influenced by Antarctic/marine aerosol and air masses.

Interfacial carbonyl groups of propylene carbonate facilitate the reversible binding of nitrogen dioxide.

The interaction of NO2 with organic interfaces is critical in the development of NO2 sensing and trapping technologies, and equally so to the atmospheric processing of marine and continental aerosol. Recent studies point to the importance of surface oxygen groups in these systems, however the role of specific functional groups on the microscopic level has yet to be fully established. In the present study, we aim to provide fundamental information on the interaction and potential binding of NO2 at atmospherically relevant organic interfaces that may also help inform innovation in NO2 sensing and trapping development. We then present an investigation into the structural changes induced by NO2 at the surface of propylene carbonate (PC), an environmentally relevant carbonate ester. Surface-sensitive vibrational spectra of the PC liquid surface are acquired before, during, and after exposure to NO2 using infrared reflection-absorption spectroscopy (IRRAS). Analysis of vibrational changes at the liquid surface reveal that NO2 preferentially interacts with the carbonyl of PC at the interface, forming a distribution of binding symmetries. At low ppm levels, NO2 saturates the PC surface within 10 minutes and the perturbations to the surface are constant over time during the flow of NO2. Upon removal of NO2 flow, and under atmospheric pressures, these interactions are reversible, and the liquid surface structure of PC recovers completely within 30 min.

A Regional Aerosol Model for the Middle Urals Based on CALIPSO Measurements

The present work aims to develop a regional Middle Urals Aerosol model (MUrA model) based on the joint analysis of long-term ground-based photometric measurements of the Aerosol Robotic NETwork (AERONET) and the results of lidar measurements of the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite relying on information on the air trajectories at different altitudes calculated using the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory model) software package. The MUrA model contains parameters of normalized volume size distributions (NVSDs) characterizing the tropospheric aerosol subtypes detected by the CALIPSO satellite. When comparing the MUrA model with the global CALIPSO Aerosol Model (CAMel), we found significant differences in NVSDs for elevated smoke and clean continental aerosol types. NVSDs for dust and polluted continental/smoke aerosol types in the global and regional models differ much less. The total volumes of aerosol particles along the atmospheric column reconstructed from satellite measurements of the attenuation coefficient at a wavelength of 532 nm based on the regional MUrA model and global CAMel are compared with the AERONET inversion data. The mean bias error for the regional model is 0.016 μm3/μm2, and 0.043 μm3/μm2 for the global model.

Insights on aerosol properties using two decades-long ground-based remote sensing datasets in Moldova, Eastern Europe

Aerosol optical properties were studied over Chisinau in Moldova, one of the longest running AERONET sites in Eastern Europe. During two decades (September 1999–November 2018), the mean aerosol optical depth (AOD) and Angstrom exponent (AE) were observed as 0.21 ± 0.13 and 1.49 ± 0.29, respectively. The highest AOD (0.24 ± 0.13) and AE (1.60 ± 0.26) were observed during the summer. More than half (∼55%) of the share was occupied by clean continental aerosols with seasonal order of winter (74.8%) > autumn (62%) > spring (48.9%) > summer (44.8%) followed by mixed aerosols with a respective contribution of 30.7% (summer), 28.4% (spring), 22.5 (autumn) and 16.4% (winter). A clear dominance of volume size distribution in the fine mode indicated the stronger influence of anthropogenic activities resulting in fine aerosol load in the atmosphere. The peak in the fine mode was centered at 0.15 μm, whereas that of the coarse mode was centered either at 3.86 μm (summer and autumn) or 5.06 μm (spring and winter). ‘Extreme’ aerosol events were observed during 21 days with a mean AOD (AE) of 0.99 ± 0.32 (1.43 ± 0.43), whereas ‘strong’ events were observed during 123 days with a mean AOD (AE) of 0.57 ± 0.07 (1.44 ± 0.40), mainly influenced by anthropogenic aerosols (during 19 and 101 days of each event type) from urban/industrial and biomass burning indicated by high AE and fine mode fraction. During the whole period (excluding events days), the fine and coarse mode peaks were observed at the radius of 0.15 and 5.06 μm, which in the case of extreme (strong) events were at 0.19 (0.15) and 3.86 (2.24) μm respectively. The fine mode volume concentration was 4.78 and 3.32 times higher, whereas the coarse mode volume concentration was higher by a factor of 1.98 and 2.27 during extreme and strong events compared to the whole period.

Validation and calibration of aerosol optical depth and classification of aerosol types based on multi-source data over China

A refined classification of aerosol types is essential to identify and control air pollution sources. This study focused on improving the resolution and accuracy of aerosol optical depth (AOD) and further refining the classification of aerosol types in China. We validated the accuracy of the AOD acquired using the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) and Copernicus Atmosphere Monitoring Service (CAMS) by comparing it with that acquired using from the Aeronet Robotic Network (AERONET). We simulated the AOD with high spatial resolution and accuracy based on the extremely randomized trees (ERT), adaptive boosting (AdaBoost), and gradient boosting decision trees (GBDT) models and identified aerosol types based on the Angstrom Exponent (AE) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the calibrated AOD. The results showed that CAMS overestimates AOD (21.4 %) and MERRA2 underestimates AOD (−17.3 %). Among the three machine learning models, the ERT model performed best, with a determination coefficient (R2) of 0.825 and the root-mean-square error (RMSE) of 0.174. Biomass burning/urban-industrial aerosols dominated China, with the largest contributions to southern, eastern, and central China in spring and summer. Clean continental aerosols contributed the most to southwestern China in fall and winter, whereas desert dust aerosols contributed the most to northwestern and eastern China in spring.

Mutual changes in temperature and aerosol content in the atmosphere based on Antarctic ice core data for the last 800000 years

A comparative analysis of mutual changes in temperature and aerosol content in the atmosphere was carried out by the data of Antarctic ice cores obtained at the Russian Vostok station and within the framework of the international EPICA project for the past 800,000 years. According to the results of cross-wavelet analysis for the last hundreds of thousands of years, variations in the content of aerosol in the atmosphere, as well as in the content of greenhouse gases CO2 and CH4, are generally lagging relative to temperature changes for the glacial cycles that dominated within the past million years with periods of about 100 thousands years associated with change in the eccentricity of the Earth’s orbit around the Sun. At the same time, for shorter-term glacial cycles, opposite effects appear at certain time intervals with a delay in temperature variations relative to variations in the content of radiatively active components in the atmosphere, including marine and continental (dust) aerosol . In particular, the delay of temperature variations with respect to variations in the content of aerosol in the atmosphere (as well as with respect to variations in the content of methane in the atmosphere) manifests itself for modes associated with the obliquity changes with periods of about 40 thousands years.

Long-term spatiotemporal variation in atmospheric aerosol properties over Türkiye based on MERRA-2 reanalysis data: aerosol classification based on city type.

Due to their complex aerosol characteristics, it is crucial to analyze the trends and properties of atmospheric aerosols over the eastern Mediterranean countries. This study comprehensively evaluates Aerosol Optical Depth (AOD) and Angström Exponent (AE) trends and aerosol classification over Türkiye, using the MERRA-2 reanalysis data from 1980 to 2019. The spatial distributions of AOD and AE were determined across various temporal scales, including multiannual, 5-year intervals, seasonal, and monthly periods. The analysis of the spatial distribution of AOD values revealed that the mean values in the northwestern areas, ranging from 0.20 to 0.25, were comparatively higher than those observed in the eastern regions, which ranged from 0.10 to 0.15. Between 1980 and 1994, the AOD values gradually increased, followed by a subsequent decline from 1995 to 2019. Based on 5-year intervals between 1980 and 2019, the coastal regions exhibited higher AOD values than the inland areas. Specifically, higher AOD values were noted between May and August, whereas lower values were observed during autumn and winter. Additionally, higher AE values were detected over the northwestern region, while the southeastern region had the lowest AE values, particularly during spring, attributed to the frequent occurrence of dust transport events in this area. The AOD and AE values were also examined in different city types, using the population thresholds of the European Commission. The global city category consisting only of Istanbul showed the highest AOD values across all seasons, while the category of very small cities, which includes 12 cities, had the lowest AOD values. Furthermore, this study investigated the contributions of dominant aerosol categories across various city types based on multiannual and seasonal variations of AOD and AE. The results showed that mixed and continental aerosols had higher portions across all city types. However, biomass burning/industrial and mixed aerosol categories were more prominent in global and large cities. Overall, this study provides a comprehensive overview of the atmospheric aerosol properties in Türkiye and can serve as a useful guide for researchers intending to conduct future studies utilizing AOD and AE data obtained through MERRA-2 aerosol diagnosis.

East Asia dust storms in spring 2021: Transport mechanisms and impacts on China

In spring 2021, several strong dust export processes crossed over East Asia, including the combined transport of Mongolia Gobi and Inner Mongolia dust. Based on CAMS forecast systems and satellite sensors, we analyzed the transport mechanisms and impact on China. Our case studies illustrate that in all 4 dust storms, the initial phase of transport was strongly confined by a low-level Mongolian cyclone facilitated by a deep cold-core upper trough. Using a methodology based on MODIS Deep Blue AOD data enables us to estimate the dust optical depth (DOD) and the impact of dust plumes on different areas in China. The result shows that North China was the most affected area in all cases, second only to the source region, with a mean observed DOD >0.8 and depolarization ratio > 0.2. The vertical distribution of the aerosol frequency of occurrence (FoO) was yielded using the CALIOP aerosol classification result. Dust storms were the dominant factor within 6 km (peaked at 2–3 km), while a significant amount of transported smoke aerosols dominated the upper troposphere. Even in dust storms, anthropogenic aerosols still occupied a high proportion of China's atmosphere, especially in South China, indicating the great contribution of human activities. As a subdominant aerosol type, polluted dust showed a profile similar to that of polluted continental aerosols, with peak heights generally lower than that of pure dust, at approximately 1–2 km. The development of cyclone/anticyclone activities was mostly modulated by the atmospheric dynamic background. By discussing the climatic index related to dust storm occurrence in East Asia, we found that the high-frequency years in the 21st century have a satisfactory correspondence with the negative phase of the Pacific Decadal Oscillation (PDO) and the positive phase of the Southern Oscillation Index (SOI). These findings may have positive significance for dust forecasting in East Asia in the future.

Long-range transported continental aerosol in the eastern North Atlantic: three multiday event regimes influence cloud condensation nuclei

Abstract. The eastern North Atlantic (ENA) is a region dominated by pristine marine environment and subtropical marine boundary layer clouds. Under unperturbed atmospheric conditions, the regional aerosol regime in the ENA varies seasonally due to different seasonal surface-ocean biogenic emissions, removal processes, and meteorological regimes. However, during periods when the marine boundary layer aerosol in the ENA is impacted by particles transported from continental sources, aerosol properties within the marine boundary layer change significantly, affecting the concentration of cloud condensation nuclei (CCN). Here, we investigate the impact of long-range transported continental aerosol on the regional aerosol regime in the ENA using data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility on Graciosa Island in 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We develop an algorithm that integrates number concentrations of particles with optical particle dry diameter (Dp) between 100 and 1000 nm, single scattering albedo, and black carbon concentration to identify multiday events (with duration &gt;24 consecutive hours) of long-range continental aerosol transport in the ENA. In 2017, we detected nine multiday events of long-range transported particles that correspond to ∼ 7.5 % of the year. For each event, we perform HYSPLIT 10 d backward trajectories analysis, and we evaluate CALIPSO aerosol products to assess, respectively, the origins and compositions of aerosol particles arriving at the ENA site. Subsequently, we group the events into three categories, (1) mixture of dust and marine aerosols, (2) mixture of marine and polluted continental aerosols from industrialized areas, and (3) biomass burning aerosol from North America and Canada, and we evaluate their influence on aerosol population and cloud condensation nuclei in terms of potential activation fraction and concentrations at supersaturation of 0.1 % and 0.2 %. The arrival of plumes dominated by the mixture of dust and marine aerosol in the ENA in the winter caused significant increases in baseline Ntot. Simultaneously, the baseline particle size modes and CCN potential activation fraction remained almost unvaried, while cloud condensation nuclei concentrations increased proportionally to Ntot. Events dominated by a mixture of marine and polluted continental aerosols in spring, fall, and winter led to a statistically significant increase in baseline Ntot, a shift towards larger particular sizes, a higher CCN potential activation fractions, and cloud condensation nuclei concentrations of &gt;170 % and up to 240 % higher than during baseline regime. Finally, the transported aerosol plumes characterized by elevated concentration of biomass burning aerosol from continental wildfires detected in the summertime did not statistically contribute to increase baseline aerosol particle concentrations in the ENA. However, particle diameters were larger than under baseline conditions, and CCN potential activation fractions were &gt;75 % higher. Consequentially, cloud concentration nuclei concentrations increased by ∼ 115 % during the period affected by the biomass burning events. Our results suggest that, through the year, multiday events of long-range continental aerosol transport periodically affect the ENA and represent a significant source of CCN in the marine boundary layer. Based on our analysis, in 2017, the multiday aerosol plume transport dominated by a mixture of dust and marine aerosol, a mixture of marine and polluted continental aerosols, and biomass burning aerosols caused increases in the NCCN baseline regime of, respectively, 6.6 %, 8 %, and 7.4 % at SS 0.1 % (and, respectively, 6.5 %, 8.2 %, and 7.3 % at SS 0.2 %) in the ENA.

Classifying aerosol type using in situ and satellite observations over a semi-arid station, Anantapur, from southern peninsular India

The chemical composition of aerosols is crucial for understanding aerosol radiative characteristics, classifying aerosol sources, and improving atmospheric aerosol satellite retrieval algorithms. In this study, the absorption angström exponent (AAE) and scattering angström exponent (SAE) values are derived from an aethalometer and three wavelength integrating nephelometer. MERRA-2 (Modern-Era Retrospective Study for Research and Applications) speciated aerosol optical depths and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol subtypes are utilized for the identification of a possible aerosol type over a semi-arid station, Anantapur, in Southern peninsular India from March 2016 to February 2018. Analysis from MERRA-2 for different aerosols illustrates that sulphate aerosol optical depth (SO4 AOD) dominates (>0.16) during winter and post-monsoon, while dust aerosol optical depth (DU AOD), organic carbon optical depth (OCAOD), and sulphate aerosol optical depth (SO4 AOD) mainly contributed (>0.07) to the total AOD during summer. SO4 AOD accounted for over ∼ 50% of total AOD during winter and post-monsoon, whereas DU AOD accounted for<10% of total aerosol optical depth in the respective seasons. The seasonal mean values of SAE (AAE) were found to be 1.95 ± 0.37 (1.03 ± 0.08), 1.65 ± 0.55 (1.03 ± 0.08), 2.53 ± 0.20 (1.03 ± 0.08) and 2.66 ± 0.15 (1.03 ± 0.08) during summer, monsoon, post-monsoon, and winter, respectively. AAE and SAE classification schemes showed that during winter, summer, and post-monsoon, continental polluted aerosols dominated (>56%), while dust and marine pollution aerosols dominated (∼47%) to the total aerosols during the monsoon. Continental aerosols are predominant during all seasons except for monsoon, and result from local anthropogenic activities and the transport of mineral dust particles and smoke aerosols from the north and western India. The observed aerosol types are consistent with the air mass back-trajectory cluster analysis performed with the help of Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT). The various aerosol types (absorbing and non-absorbing) and their change over a region are essential for for reducing the uncertainty in the assessment of aerosol radiative effects.

Bacterial and Chemical Evidence of Coastal Water Pollution from the Tijuana River in Sea Spray Aerosol.

Roughly half of the human population lives near the coast, and coastal water pollution (CWP) is widespread. Coastal waters along Tijuana, Mexico, and Imperial Beach (IB), USA, are frequently polluted by millions of gallons of untreated sewage and stormwater runoff. Entering coastal waters causes over 100 million global annual illnesses, but CWP has the potential to reach many more people on land via transfer in sea spray aerosol (SSA). Using 16S rRNA gene amplicon sequencing, we found sewage-associated bacteria in the polluted Tijuana River flowing into coastal waters and returning to land in marine aerosol. Tentative chemical identification from non-targeted tandem mass spectrometry identified anthropogenic compounds as chemical indicators of aerosolized CWP, but they were ubiquitous and present at highest concentrations in continental aerosol. Bacteria were better tracers of airborne CWP, and 40 tracer bacteria comprised up to 76% of the bacteria community in IB air. These findings confirm that CWP transfers in SSA and exposes many people along the coast. Climate change may exacerbate CWP with more extreme storms, and our findings call for minimizing CWP and investigating the health effects of airborne exposure.

Ice nucleation catalyzed by the photosynthesis enzyme RuBisCO and other abundant biomolecules

Atmospheric aerosol and the cloud droplets and ice crystals that grow on them remain major sources of uncertainty in global climate models. A subset of aerosol, ice nucleating particles, catalyze the freezing of water droplets at temperatures warmer than −38 °C. Here we show that RuBisCO, one of the most abundant proteins in plants and phytoplankton, is one of the most efficient known immersion ice nucleating particles with a mean freezing temperature of −7.9 ± 0.3 °C. Further, we demonstrate RuBisCO is present in ambient continental aerosol where it can serve as an ice nucleating particle. Other biogenic molecules act as immersion ice nucleating particles, in the range of −19 to −26 °C. In addition, our results indicate heat denaturation is not a universal indicator of the proteinaceous origin of ice nucleating particles, suggesting current studies may fail to accurately quantify biological ice nucleating particle concentrations and their global importance.

Contribution of deep-earth fluids to the geothermal system: A case study in the Arxan volcanic region, northeastern China

Investigations of the hot spring water and gas in the volcanic region are involved in assessing geothermal resources and understanding groundwater circulation, volcano, and earthquake activities. The origins of water and gas of the hot springs, lakes, rivers, and rain in the Arxan volcanic region (AVR), northeastern (NE) China, were investigated by conducting a field survey and geochemical analysis. The low electrical conductivity (40–835 μS/cm) and low total dissolved solids (TDS, 23.83–540.00 mg/L) of the water samples indicate that they are fresh water. δ18O and δD values of the water samples range from −4.1% to −16.0% and from −61.3% to −119.9%, respectively. Enrichment of heavy isotopes in the rainwater and the crater lake waters was caused by evaporation. The component H2O of the water samples predominantly originated from the meteoric water, with less than 1 vol% contributed by deep-earth fluids. Ions in the rain sample were predominantly derived from sea salt and continental aerosol. Ions in the surface water samples had multiple origins (mineral dissolution, atmospheric, and anthropogenic sources). While the ions in the hot spring water were predominantly derived from both the dissolution of rocks and deep-earth fluids, the latter contributed 73%–87% of Cl− and 86%–99% of Na+ to the hot spring waters. Gases from the hot springs were composed of more than 95% N2 and less than 5% O2 and Ar, with 3He/4He ratios of 0.14–1.17 RA (RA=1.4×10−6). Excess N2, Ar, He, and CO2 of the hot springs were mainly derived from both the crust and upper mantle. About 3%–23% of the total He in the bubbling gases from the crater lake waters and hot springs is derived from the mantle, implying a supplement of heat energy from the mantle to the geothermal systems. Significantly, about 12% of the He dissolved in the Budonghe water is derived from the mantle, indicating that plenty of mantle-derived heat transported by deep-earth fluids keeps the river water from freezing. Our results indicate that Cl and Na ions and 3He/4He ratio are the feasible geochemical indicators for source partitioning of geothermal fluids.