Aerosol Types Research Articles

Application of DIAL/HSRL and CATCH algorithm-based methodologies for surface PM2.5 concentrations during the KORUS-AQ campaign

Particulate matter with an aerodynamic diameter of equal to or less than 2.5 μm (PM2.5) has been found to have a serious adverse effect on human health and the environment. While the importance of measuring PM2.5 has been demonstrated, doing so remotely remains challenging. In this study, methodologies for the assessment of aerosol PM2.5 and chemical composition based on a combination of regional and global models and active remote sensing were evaluated against surface observations from the KORUS-AQ campaign. The model outputs from the Community Multiscale Air Quality (CMAQ) and GEOS-Chem were used and were available at the KORUS-AQ campaign data archive. For remote sensing, aerosol extinction and derived aerosol types available from NASA Langley Airborne Differential Absorption Lidar (DIAL)/High Spectral Resolution Lidar (HSRL) flying onboard DC-8 aircraft were used. A revised version of the algorithm, which incorporates size-specific aerosol dry mass extinction efficiencies for sulfate, nitrate, and ammonia as well as organic matter, is also presented. The PM2.5 concentration estimates were compared with measurements taken at the ground stations. The estimated mean absolute error between the ground station measurements and the remote-sensing-based methodologies was significantly lower compared to the models. The data analysis has shown that uncertainties in relative humidity values, the presence of particles larger than 2.5 μm in diameter, and the abundance of black carbon and organic matter in Asian aerosol were unlikely to explain the differences between measured and predicted surface PM2.5. Local meteorology was found to play a key role influencing the spatiotemporal variability of aerosols and the most important factor determining the agreement between the estimated and ground site-measured PM2.5. The lowest mean absolute error was found for the May 1–16 period, when aerosols were well mixed within the mixing layer and homogeneous across the temporal (1 h) and spatial (8 km) scales used in this study. Under these conditions, the methodologies presented here could give reasonable estimates of PM2.5 concentration and derived chemical composition over South Korea when HSRL data are available.

Simulated depolarization ratios for dust and smoke at laser wavelengths: implications for lidar application.

Polarization measurements have been widely used to detect aerosol properties by remote sensing in recent decades. To better understand the polarization characteristics of aerosols by lidar, the numerically exact T-matrix method was used to simulate the depolarization ratio (DR) of dust and smoke aerosols at typical laser wavelengths in this study. The results show that the DRs of dust and smoke aerosols have obviously different spectral dependences. Moreover, the ratio of DRs at two wavelengths has an obvious linear relationship with the microphysical properties of aerosols, including aspect ratio, effective radius and complex refractive index. At short wavelengths, we can use it to invert the absorption characteristics of particles, further improving the detection ability of lidar. Comparing the simulation results of different channels, DR, (color ratio) CR and (lidar ratio) LR have a good logarithmic fitting relationship at 532 nm and 1064 nm, which helps to classify the aerosol types. On this basis, a new inversion algorithm, "1β+1α+2δ", was presented. By this algorithm, the backscattering coefficient (β), extinction coefficient (α), DR (δ) at 532 nm and 1064 nm can be used to expand the range of inversion and compare lidar data with different configurations to obtain more extensive optical characteristics of aerosols. Our study enhances the application of laser remote sensing in aerosol observations more accurately.

Water-soluble brown carbon in atmospheric aerosols from the resource-dependent cities: Optical properties, chemical compositions and sources

As a vital type of light-absorbing aerosol, brown carbon (BrC) presents inherent associations with atmospheric photochemistry and climate change. However, the understanding of the chemical and optical properties of BrC is limited, especially in some resource-dependent cities with long heating periods in northwest China. This study showed that the annual average abundances of Water-soluble BrC (WS-BrC) were 9.33±7.42 and 8.69±6.29 µg/m3 in Baotou and Wuhai and the concentrations, absorption coefficient (Abs365), and mass absorption efficiency (MAE365) of WS-BrC presented significant seasonal patterns, with high values in the heating season and low values in the non-heating season; while showing opposite seasonal trends for the Absorption Ångström exponent (AAE300-400). Comparatively, the levels of WS-BrC in developing regions (such as cities in Asia) were higher than those in developed regions (such as cities in Europe and Australia), indicating the significant differences in energy consumption in these regions. By combining fluorescence excitation-emission matrix (EEM) spectra with the parallel factor (PARAFAC) model, humic-like (C1 and C2) and protein-like (C3) substances were identified, and accounted for 61.40%±4.66% and 38.6%±3.78% at Baotou, and 60.33%±6.29% and 39.67%±4.17% at Wuhai, respectively. The results of source apportionment suggested that the potential source regions of WS-BrC varied in heating vs. non-heating seasons and that the properties of WS-BrC significantly depended on primary emissions (e.g., combustion emissions) and secondary formation.

Self-lofting of wildfire smoke in the troposphere and stratosphere: simulations and space lidar observations

Abstract. Wildfire smoke is known as a highly absorptive aerosol type in the shortwave wavelength range. The absorption of sunlight by optically thick smoke layers results in heating of the ambient air. This heating is translated into self-lofting of the smoke up to more than 1 km in altitude per day. This study aims for a detailed analysis of tropospheric and stratospheric smoke lofting rates based on simulations and observations. The main goal is to demonstrate that radiative heating of intense smoke plumes is capable of lofting them from the lower and middle free troposphere (injection heights) up to the tropopause without the need of pyrocumulonimbus (pyroCb) convection. The further subsequent ascent within the lower stratosphere (caused by self-lofting) is already well documented in the literature. Simulations of absorbed solar radiation by smoke particles and resulting heating rates, which are then converted into lofting rates, are conducted by using the ECRAD (European Centre for Medium-Range Weather Forecasts Radiation) scheme. As input parameters thermodynamic profiles from CAMS (Copernicus Atmosphere Monitoring Service) reanalysis data, aerosol profiles from ground-based lidar observations, radiosonde potential temperature profiles, CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) aerosol measurements, and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth retrievals were used. The sensitivity analysis revealed that the lofting rate strongly depends on aerosol optical thickness (AOT), layer depth, layer height, and black carbon (BC) fraction. We also looked at the influence of different meteorological parameters such as cloudiness, relative humidity, and potential temperature gradient. To demonstrate the applicability of our self-lofting model, we compared our simulations with the lofting processes in the stratosphere observed with CALIOP after major pyroCb events (Canadian fires in 2017, Australian fires in 2019–2020). We analyzed long-term CALIOP observations of smoke layers and plumes evolving in the UTLS (upper troposphere and lower stratosphere) height region over Siberia and the adjacent Arctic Ocean during the summer season of 2019. Our results indicate that self-lofting contributed to the vertical transport of smoke. We hypothesize that the formation of a near-tropopause aerosol layer, observed with CALIOP, was the result of self-lofting processes because this is in line with the simulations. Furthermore, Raman-lidar-based aerosol typing (in Leipzig and the High Arctic) clearly indicated the dominance of smoke in the UTLS aerosol layer since August 2019, most probably also the result of smoke self-lofting.

Relationship between the sub-micron fraction (SMF) and fine-mode fraction (FMF) in the context of AERONET retrievals

Abstract. The sub-micron (SM) aerosol optical depth (AOD) is an optical separation based on the fraction of particles below a specified cutoff radius of the particle size distribution (PSD) at a given particle radius. It is fundamentally different from spectrally separated FM (fine-mode) AOD. We present a simple (AOD-normalized) SM fraction versus FM fraction (SMF vs. FMF) linear equation that explains the well-recognized empirical result of SMF generally being greater than the FMF. The AERONET inversion (AERinv) products (combined inputs of spectral AOD and sky radiance) and the spectral deconvolution algorithm (SDA) products (input of AOD spectra) enable, respectively, an empirical SMF vs. FMF comparison at similar (columnar) remote sensing scales across a variety of aerosol types. SMF (AERinv-derived) vs. FMF (SDA-derived) behavior is primarily dependent on the relative truncated portion (εc) of the coarse-mode (CM) AOD associated with the cutoff portion of the CM PSD and, to a second order, the cutoff FM PSD and FM AOD (εf). The SMF vs. FMF equation largely explains the SMF vs. FMF behavior of the AERinv vs. SDA products as a function of PSD cutoff radius (“inflection point”) across an ensemble of AERONET sites and aerosol types (urban-industrial, biomass burning, dust, maritime and a mixed class of Arctic aerosols). The overarching dynamic was that the linear SMF vs. FMF relation pivots clockwise about the approximate (SMF, FMF) singularity of (1, 1) in a “linearly inverse” fashion (slope and intercept of approximately 1−εc and εc) with increasing cutoff radius. SMF vs. FMF slopes and intercepts derived from AERinv and SDA retrievals confirmed the general domination of εc over εf in controlling that dynamic. A more general conclusion is the apparent confirmation that the optical impact of truncating modal (whole) PSD features can be detected by an SMF vs. FMF analysis.

Bivariate and Partial Wavelet Coherence analysis of aerosols impact on Global Horizontal Irradiation in Far-North and Littoral regions of Cameroon

This study investigated the time-frequency variability of Global Horizontal Irradiation (GHI) under clear sky conditions in Cameroon in relation to aerosol types using the wavelet transform method. For this purpose, we focused on two climatically different zones (Far North and Littoral) in Cameroon chosen because of the large difference in term of proportion in type of aerosols. From the Bivariate Wavelet Coherence (BWC) analysis, it was found in the Littoral zone (Dust DU, Organic Matter OM, Black Carbon BC, Sulfates SU) aerosols are negatively correlated with GHI at all frequencies, whereas Sea Salt (SS) aerosols are positively correlated with GHI. In the Far North zone, all aerosols are negatively correlated with GHI in the 0-8 month band but the dynamic has changed in the 8-16 month band. However, with the Partial Wavelet Coherence (PWC) analysis, we found that the correlations between GHI and each analyzed variable decreased after removing the effects of the remaining variables. Only the correlations between GHI and DU are still significant, with an average wavelet coherence (AWC) and percentage of significant coherence (PASC) values of 0.60 and 24.36% respectively. It is noteworthy with PWC analysis that the area with significant correlation between GHI and the other aerosol types except DU is very limited. This shows that their influences on GHI have already been covered by DU. The study also showed the combined effect of the analyzing variables (SS, BC, SU and OM) on GHI, since, independently as shown by the PWC, each of them is weakly correlated to GHI. However, with the BWC, the combined effect of other aerosols on BC and SU makes their influences on GHI important. The PWC and BWC implementations have been compiled by Matlab and can be accessed freely following this link (https://figshare.com/s/bc97956f43fe5734c784).

Difference between global and regional aerosol model classifications and associated implications for spaceborne aerosol optical depth retrieval

AbstractAerosol model are generally adopted to describe the physical and optical characteristics of aerosols in different regions, and this is important for climate and environmental studies as well as satellite aerosol retrieval. However, current mainstream aerosol retrieval algorithms still lack differentiated and dynamic descriptions of aerosol models, and the aerosol optical depth (AOD) retrieval accuracy is hence largely compromised. Therefore, in this study, we aimed to investigate the difference between global and regional aerosol model classifications and the impact of these differences on satellite AOD retrieval. We developed global and regional (for China) aerosol models through the K-means cluster analysis method, and used the 6SV radiative transfer model based on these global and regional aerosol models to simulate air pollution events. The cluster analysis revealed that both global and regional aerosols can be clustered into five main aerosol types with different optical and physical parameters. The aerosol types include strongly absorbing, moderately absorbing, weakly absorbing, dust and coarse-fine mixed aerosols. These two aerosol models exhibited distinct seasonal variations. Comparing the clustering results obtained with the two models at five Aerosol Robotic Network (AERONET) sites, we found that the proportion of strongly absorbing aerosols in the global results is low. According to the China clustering results, a higher proportion of strongly absorbing aerosols occurred in autumn, winter, and early spring, and dust aerosols attained an increasing proportion in spring. Comparing the aerosol parameters with observational data, the regional aerosol model performed better than the global aerosol model. Simulations of AOD during a pollution episode and in different seasons at the Beijing-CAMS site with the 6SV radiative transfer model further confirmed that the regional aerosol model achieved a better simulation accuracy than the global model. The findings suggest that regional aerosol models can provide a useful reference for satellite remote sensing algorithm, climate change and air pollution assessment, and that the dynamic description of the aerosol model is a key parameter in satellite AOD retrieval algorithms.

A high-precision aerosol retrieval algorithm for FY-3D MERSI-II images

The Medium Resolution Spectral Imager-II (MERSI-II) onboard the recently launched Chinese Fengyun-3D (FY-3D) satellite has great capability in detecting global aerosols as it includes aerosol bands similar to Moderate Resolution Imaging Spectroradiometer (MODIS). However, to date, aerosol retrieval based on MERSI-II is still limited to dark target regions and there is no official aerosol products for the MERSI-II. This study focuses on developing a high-precision algorithm to retrieve aerosol optical depth (AOD) suitable for entire land areas (except snow/ice and inland waters) based on MERSI-II measurements. Considering both the accuracy and retrieval efficiency, a new cost function is constructed based on (1) the fact that the AOD (550 nm) retrieved independently from different bands should be the same with the correct aerosol model, and (2) the assumption that the aerosol types are the same in the 5 × 5 km spatial range. The retrieval method based on the new cost function is nearly 50 times faster than most current methods using iterative calculations. To extend the application adaption of the FY-3D MERSI-II AOD retrieval and avoid the errors caused by the surface Lambertian hypothesis, a bidirectional reflectance distribution function (BRDF) database is built using MODIS products. Eight candidate aerosol models in different natural zones of China are constructed based on AERONET aerosol products from 2010 − 2021. The new method is applied to MERSI-II images over China and validated against ground-based measurements at 14 stations from 2020 to 2021. MODIS aerosol products from three operational algorithms are also used for comparison purposes. The results show that MERSI-II AOD retrievals agree well with the ground-based measurements with correlation coefficient (R), root mean square error (RMSE), and relative mean bias (RMB) of 0.913, 0.123, and 0.955, respectively. In addition, 72.19 % of AOD matchups fall within the expected error (EE) envelopes. The MERSI-II retrievals show higher accuracy than that of MODIS dark target (DT) and deep blue (DB) products and comparable accuracy of the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) product. MERSI-II AOD also shows higher stability in terms of spatial and temporal and better performance under heavy aerosol loading conditions than MODIS products. A good AOD agreement with R from 0.777 to 0.863 between MERSI-II and MODIS products is found over the land of China. The new method showing high retrieval efficiency and accuracy has great potential to be operationally applied on AOD retrieval for MERSI-II.

Diurnal and Seasonal Variability of the Atmospheric Boundary-Layer Height in Marseille (France) for Mistral and Sea/Land Breeze Conditions

Marseille (France) is a city on the Mediterranean coast characterized by two specific wind patterns: mistral (northwesterly wind blowing above 10 m/s) and sea/land breezes (southwesterly wind during daytime/northeasterly wind during the nighttime, blowing below 6 m/s). For the first time, this study investigates the diurnal and seasonal variability in the atmospheric boundary-layer height (ABLH) in Marseille for both wind patterns. A 532 nm aerosol lidar was installed in the urban center in the summer of 2021. The lidar installed in the winter of 2021–2022 had an additional near-infrared channel at 808 nm. The ABLH was extracted from the lidar datasets using a Haar wavelet method. For well-established mistral conditions, the ABLH reached to about 1000 m and showed a diurnal amplitude of ~650 m in winter and 740 m in summer, with a morning growth rate limited by turbulence. During sea breeze situations, the ABLH maxima were lower in both seasons (300–600 m) due to the sea’s thermal inertia. During land breeze situations, ABLH minima were estimated to be lower than 150 m. In summer, the Haar method was unable to calculate them because of unpronounced aerosol layers. While the near-infrared channel gives better results, the polarization of the green channel allows us to understand the type of aerosols and thus the origin of the air mass; a combination of the two gives complementary information.

Aerosol Effects on Clear‐Sky Shortwave Heating in the Asian Monsoon Tropopause Layer

AbstractThe Asian tropopause aerosol layer (ATAL) has emerged in recent decades with aerosol accumulation near tropopause above Asian Summer Monsoon region. Although ATAL effects on surface and top‐of‐atmosphere (TOA) radiation budgets are well established, the magnitude and variability of ATAL effects on radiative transfer within the tropopause layer remain poorly constrained. Here, we investigate the impacts of various aerosol types and layer structures on clear‐sky shortwave radiative heating in the Asian monsoon tropopause layer using reanalysis products and offline radiative transfer simulations. ATAL effects on shortwave radiative heating based on the Modern‐Era Retrospective Analysis for Research and Applications, version 2 aerosol reanalysis are on the order of 15% of mean clear‐sky radiative heating within the tropopause layer, although discrepancies among recent reanalysis and forecast products suggest that this ratio could be as small as ∼10% or as large as ∼70%. Uncertainties in surface and TOA flux effects are also large, with values spanning one order of magnitude at the TOA. ATAL effects on radiative heating peak between 150 and 80 hPa (360–400 K potential temperature) along the southern flank of the anticyclone. Clear‐sky and all‐sky shortwave heating are at local minima in this vertical range, which is situated between the positive influences of monsoon‐enhanced water vapor and the negative influence of the “ozone valley” in the monsoon lower stratosphere. ATAL effects also extend further toward the west, where diabatic vertical velocities remain upward despite descent in pressure coordinates.

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses

Ambient fine particulate matter (PM2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Impact of changes in refractive indices of secondary organic aerosols on precipitation over China during 1980–2019

Secondary organic aerosols (SOAs), which include both colorless and colored carbonaceous aerosols, represent a major type of aerosol globally. Previous studies have reported that colored aerosols drive the well-known precipitation changes over southern China called the south-flood north-drought (SFND). Considering the highest concentration of SOA in China, SOAs can cause fluctuations in the precipitation system over China. However, studies on the climatic effects of SOAs over East Asia are scarce owing to the chemical complexity of SOAs and high computational cost. Therefore, to investigate the effect of SOAs on the precipitation change over China, we implemented an SOA scheme using empirical parameters in the chemistry-climate model. We performed a control and two sensitivity simulations depending on the difference in refractive indices of SOAs to elucidate the effects of light absorption by SOAs on precipitation. Our results suggest that strong light absorption by SOAs strengthens the convective precipitation over southern China following the enhancement of atmospheric stability with a secondary circulation effect. However, the surface temperature changes caused by SOAs shift the jet core if weak light absorption by SOAs is assumed, causing a strong downdraft in the mid-troposphere and decreasing humidity over south-eastern China. Therefore, precipitation was significantly reduced over southern China. Our results show that light-absorbing SOAs have had a significant impact on precipitation in southern China for the past few decades. Furthermore, the apparent difference in mechanisms of precipitation change between strong and weak light absorption by SOAs suggests the importance of choosing suitable refractive indices for SOAs in the climate–atmospheric chemistry model.

Atmospheric correction algorithm based on the interpolation of ultraviolet and shortwave infrared bands.

Traditional atmospheric correction algorithms of ocean color remote sensing are mostly based on the extrapolation of aerosol scattering radiance from a reference band (near infrared, shortwave infrared, or ultraviolet bands), which inevitably leads to the problem of extrapolation error amplification with the increase of extrapolation spectral distance. In this study, we propose a practical interpolation-based algorithm (named the UV-SWIR-AC algorithm) using three reference bands (one ultraviolet and two shortwave infrared bands) for turbid waters. According to 6SV radiative transfer simulations with 15 customized aerosol types, we establish a fitting function framework for the aerosol scattering radiance in the wavelength range of 322-1643 nm. We apply the UV-SWIR-AC algorithm to the real satellite ocean color data observed by the Second-Generation Global Imager aboard the Global Change Observation Mission-Climate (SGLI/GCOM-C) and compare the retrieved remote sensing reflectance with the in-situ data from the observation platform of Hangzhou Bay in the East China Sea and typical bays. The results show that the UV-SWIR-AC algorithm can achieve a better performance than the traditional, extrapolation-based algorithm in turbid waters. Moreover, in the typical regional analysis, this new algorithm also demonstrates a high applicability. The UV-SWIR-AC algorithm should be helpful to improve the atmospheric correction accuracy for next-generation ocean color missions (e.g., NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission and China's Haiyang-1E/F (HY-1E/F) mission) with wider spectral ranges from the ultraviolet to shortwave infrared wavelengths.

The CALIPSO version 4.5 stratospheric aerosol subtyping algorithm

Abstract. The accurate classification of aerosol types injected into the stratosphere is important to properly characterize their chemical and radiative impacts within the Earth climate system. The updated stratospheric aerosol subtyping algorithm used in the version 4.5 (V4.5) release of the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) level 2 data products now delivers more comprehensive and accurate classifications than its predecessor. The original algorithm identified four aerosol subtypes for layers detected above the tropopause: volcanic ash, smoke, sulfate/other, and polar stratospheric aerosol (PSA). In the revised algorithm, sulfates are separately identified as a distinct, homogeneous subtype, and the diffuse, weakly scattering layers previously assigned to the sulfate/other class are recategorized as a fifth “unclassified” subtype. By making two structural changes to the algorithm and revising two thresholds, the V4.5 algorithm improves the ability to discriminate between volcanic ash and smoke from pyrocumulonimbus injections, improves the fidelity of the sulfate subtype, and more accurately reflects the uncertainties inherent in the classification process. The 532 nm lidar ratio for volcanic ash was also revised to a value more consistent with the current state of knowledge. This paper briefly reviews the previous version of the algorithm (V4.1 and V4.2) then fully details the rationale and impact of the V4.5 changes on subtype classification frequency for specific events where the dominant aerosol type is known based on the literature. Classification accuracy is best for volcanic ash due to its characteristically high depolarization ratio. Smoke layers in the stratosphere are also classified with reasonable accuracy, though during the daytime a substantial fraction are misclassified as ash. It is also possible for mixtures of ash and sulfate to be misclassified as smoke. The V4.5 sulfate subtype accuracy is less than that for ash or smoke, with sulfates being misclassified as smoke about one-third of the time. However, because exceptionally tenuous layers are now assigned to the unclassified subtype and the revised algorithm levies more stringent criteria for identifying an aerosol as sulfate, it is more likely that layers labeled as this subtype are in fact sulfate compared to those assigned the sulfate/other classification in the previous data release.

Aerosol characteristics and types in the marine environments surrounding the East Mediterranean - Middle East (EMME) region during the AQABA campaign

This study analyzes the aerosol optical properties (scattering, absorption coefficients, single scattering albedo), supported by chemical composition measurements, in the marine boundary layer of the East Mediterranean – Middle East (EMME) region, aiming to explore the spatio-temporal variability, aerosol mixing state, sources and dominant types. The measurements were taken during the AQABA (Air Quality and climate change in the Arabian Basin) cruise campaign (1st July – September 1, 2017) from the south of France to Kuwait and back. Both scattering and absorption coefficients for PM1 and PM10 particles maximized in the southern Red Sea, due to continental outflow from East Africa, and in the Arabian/Persian Gulf due to enhanced anthropogenic/industrial emissions, leading to 3-fold sulfate concentrations compared to the other regions. The East Mediterranean exhibited moderate aerosol loading, with high scattering Ångström Exponent (SAE) values (1.98, 1.30 for PM1 and PM10, respectively), which increased in the Suez Canal and the Arabian Gulf due to impact from combustion sources. The aerosol over the Gulf of Aden and the West Arabian Sea was dominated by coarse particles (SAE<1), with higher Ca2+ concentrations (dust influence). The absorption Ångström Exponent (AAE) remained close to 1, indicative of black carbon (BC) from fossil fuel combustion, while it increased in regions dominated by dust (Gulf of Aden, Arabian Sea). Contrasting aerosol types were identified between the sub-regions using the SAE vs. AAE classification scheme. The “BC-dominated” type prevailed over the East Mediterranean and Suez Canal, while dust mixtures dominated in the Gulf of Aden and the Arabian Sea. Over the Arabian Gulf, mixing of anthropogenic pollution with marine aerosols formed a type with fine particles and low spectral dependence of absorption (AAE<1). Spectral SSA significantly varied along the ship cruise, while it was used for determination of dust influence in the marine environment.

Correlation between Graphitic Carbon and Elemental Carbon in Diesel Particulate Matter in Workplace Atmospheres.

We investigated the suitability of the graphitic carbon (GC) content of diesel particulate matter (DPM), measured using Raman spectroscopy, as a surrogate measure of elemental carbon (EC) determined by thermal optical analysis. The Raman spectra in the range of 800-1800 cm-1 (including the D mode at ∼1322 cm-1 and the G mode at ∼1595 cm-1) were used for GC identification and quantification. Comparison of the Raman spectra for two certified DPM standards (NIST SRM 1650 and SRM 2975), two types of diesel engine exhaust soot, and three types of DPM-enriched workplace aerosols show that the uncertainty of GC quantification based on the D peak height, G peak height, and the total peak area below D and G peaks was about 6.0, 6.7, and 6.9%, respectively. The low uncertainty for different aerosol types suggested possible use of GC as a surrogate measure of EC in workplace atmospheres. A calibration curve was constructed using two laboratory-aerosolized DPM standards to describe the relationship between GC measured by a portable Raman spectrometer and the EC concentration determined by NIOSH Method 5040. The calibration curve was then applied to determine GC-based estimates of the EC contents of diesel engine exhaust samples from two vehicles and seven air samples collected at a hydraulic fracturing worksite. The GC-EC estimates obtained through Raman measurements agreed well with those found by NIOSH Method 5040 for the same samples at EC filter loadings below 2.86 μg/cm2. The study shows that using an appropriate sample collection method that avoids high filter mass loadings, onsite measurement of GC by a portable or hand-held Raman spectrometer can provide a useful indicator of EC in workplace aerosol.

Simultaneous Use of Ground-Based and Satellite Observation to Evaluate Atmospheric Air Pollution over Amman, Jordan

In this study, a combination of ground-based particulate matter measurements in synergy with space-borne CALIOP lidar recordings, meteorological observations, and reanalysis models have been used to study atmospheric air pollution over Amman, Jordan. The measurement was conducted over a 24-month period spanning from January 2018 to the end of December 2019. The CALIOP aerosol profiles and aerosol layer products version 4.21, level 2, with 5 km horizontal resolution were used to evaluate the vertical structure of the atmospheric constituent over the Amman region. The particle depolarization ratio (PDR) was extracted from CALIOP recordings and has been utilized to classify the type of atmospheric aerosols. This method reveals that the atmosphere above Amman mostly contains three different aerosol types including coarse-mode dust, fine-mode dust (polluted dust), and non-dust aerosols (pollution). Aerosols with 0 &lt; δp≤ 0.075 are categorized as pollution, aerosols with 0.075 &lt; δp≤ 0.20 as polluted dust, and aerosols with 0.20 &lt; δp≤ 0.40 are classified as dust. Both the one- and two-step POlarization-LIdar PHOtometer Networking (POLIPHON) approaches have been applied to the CALIOP aerosol profile product to retrieve the vertical profile of the optical and micro-physical properties of each aerosol type. Lofted-layer top heights and layer thickness in the atmosphere above Amman during the study period were also extracted from the CALIOP aerosol layer products. The highest frequency of occurrence was observed for layers with a top height of 0.5 to 2.5 km with a second smaller peak at 3.5 km. The maximum frequency of the lofted layers (40% of cases) were observed with layer thickness below 0.5 km. For layers with a top height lower than 500 m above ground level, the atmosphere was mostly impacted by polluted dust and pollution aerosols. On the other hand, for layers with a top height above 2500 m agl, the atmosphere was contaminated by depolarizing dust particles.

Seasonal variability in size-resolved hygroscopicity of sub-micron aerosols over the Western Ghats, India: Closure and parameterization

Hygroscopicity of atmospheric aerosol primarily depends on the size and chemical composition of the particle and is important for estimating anthropogenic aerosol radiative forcing. There is limited information exists over the Indian region on size segregated aerosol hygroscopicity (κ) in different seasons. This study presents ‘κ’ as derived from a Humidified Tandem Differential Mobility Analyzer (HTDMA) over a High Altitude Cloud Physics Laboratory (HACPL) in the Western Ghats, India for more than a year (from May 2019 to May 2020). The average hygroscopicity values of aerosol particles of diameters 32, 50, 75, 110, 150, 210 and 260 nm at 90 % RH condition are 0.19, 0.18, 0.16, 0.17, 0.18, 0.20, 0.21 respectively during the entire observation period. κ was observed to decrease with an increase in size in the Aitken mode regime (32–75 nm) and an increase in the accumulation mode (110–260 nm). Seasonal variation of hygroscopicity for a wide range of particle diameters is reported which is highly demanding as there is a change in the air mass flow pattern in each of the seasons. The diurnal cycle of hygroscopicity showed a prominent peak during the midnight to early morning hours followed by a decrease in the forenoon hours and a secondary peak in the afternoon hours. κ is found to be higher in pre-monsoon compared to winter season as Chl is approximately 3 % higher in pre-monsoon and NH4Cl is highly hygroscopic among the assumed chemical composition. Hygroscopicity derived through chemical speciation observations assuming internal and external mixing of aerosols i.e. κinter and κexter are overestimating as compared to κHTDMA. However, the bias between kexter and kHTDMA is relatively lower as external mixing type of aerosol is evident through the growth factor data sets measured by HTDMA. Utilizing the hygroscopicity measurements available for discrete diameters by HTDMA, a parameterization of hygroscopicity with the dry diameter of sub-micron particles is developed.

Accounting for the aerosol type and additional satellite-borne aerosol products improves the prediction of PM2.5 concentrations

Fine airborne particles (diameter <2.5 μm; PM2.5) are recognized as a major threat to human health due to their physicochemical properties: composition, size, shape, etc. However, normally only size-fraction-specific particle concentrations are monitored. Interestingly, although the aerosol type is reported as part of the aerosol optical depth retrieval from satellite observations, it has not been utilized, to date, as an auxiliary information/co-variate for PM2.5 prediction. We developed Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models that account for this information when predicting surface PM2.5. The models take as input only widely available data: satellite aerosol products with full cover and surface meteorological data. Distinct models were developed for AOD of specific aerosol types. Both the RF and XGBoost models performed well, showing moderate-to-high cross-validated adjusted R2 (RF: 0.753–0.909; XGBoost: 0.741–0.903), depending on the aerosol type and other covariates. The weighted performance of the specific aerosol-type models was higher than of the RF and XGBoost baseline models, where all the AOD retrievals were used together (the common practice). Our approach can provide improved risk estimates due to exposure to PM2.5, better resolved radiative forcing calculations, and tailored abatement surveillance of specific pollutants/sources.

Evaluation and comparison of VIIRS dark target and deep blue aerosol products over land

The dark target (DT) and deep blue (DB) algorithms have been applied to the VIIRS to construct a long-term climate data recording of atmospheric aerosols. This study provides the first evaluation and comparison of two updated VIIRS aerosol products over global land based on Version 3 Level 1.5 AERONET measurements. Overall, both AOD products agree well with AERONET measurements with correlation coefficients >0.85 and over 75 % of AOD matchups falling within the expected error (EE). The DB product is superior to the DT product with more AOD matchups meeting the EE. Meanwhile, the DB AOD performs better in spatiotemporal accuracy, adaption to different aerosol types, and addresses the effects of large view geometry. DT AOD shows higher accuracy in the summer months in the northern hemisphere and evergreen broadleaf forest areas than DB AOD. The two products exhibit similar spatial distribution patterns of AOD, but higher values are seen in the DT product, especially in Asia and Western North America. The spatial completeness of the DB AOD is higher than DT, especially in brighter surface regions. In contrast, higher temporal completeness of the DT AOD is found in vegetated areas. A case study of the Western United States wildfires in 2020 indicates both products can capture extreme smoke aerosols. In addition, the DB AOD shows a distinct advantage in spatial and temporal continuity and in displaying the regional transport of smoke aerosols. However, the accuracy of the AOD retrieval for both products still needs to be improved in sparse vegetation regions, northern hemisphere summers, fine particle aerosols, and during extreme aerosol events. The overall evaluation of DB SSA and AE products shows that they are unsuitable for quantitative scientific research. This study can provide users a guide on how to select VIIRS aerosol products for different research purposes.