Absorption Optical Depth Research Articles

An inter-satellite laser occultation method profiling atmospheric temperature and pressure from troposphere to lower mesosphere

We propose a laser occultation method for simultaneous profiling atmospheric temperature and pressure. Measurements can be performed on the optical link between two low-orbit satellites, where frequency-stepwise laser pulses are transmitted from one to the other. These pulses, covering several oxygen absorption lines in the wavelength domain, measure the broadened atmospheric absorption optical depth along the transmission path with a spectral resolution of tens of megahertz. In this way, atmospheric temperature and pressure are obtained by analysing the retrieved shape and intensity of the spectral lines. With the motion of the two satellites, the inter-satellite optical link penetrates different atmospheric layers at various altitudes, enabling the measurement of the vertical structure of atmospheric thermodynamic parameters from the troposphere to the lower thermosphere. This paper presents an end-to-end simulation of the proposed method, including models for laser occultation beam tracing, radiative transfer, and data inversion. The simulation results reveal that with minimal satellite payload resources, this method can accurately measure temperature and pressure at a vertical resolution of 100 m from 5 km to 90 km altitude with accuracies of ±1.5 K and 5 %, respectively. As the proposed differential absorption laser occultation method is independent of the hydrostatic equilibrium hypothesis for data inversion, it can eliminate errors associated with prior data at reference altitudes. It is believed that our method has provided a promising approach to laser satellite constellation for atmospheric observation.

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.

Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Martian column CO2 and pressure measurement with spaceborne differential absorption lidar at 1.96 µm

Abstract. By utilizing progress in millijoule-level pulsed fiber lasers operating in the 1.96 µm spectral range, we introduce a concept utilizing a spaceborne differential absorption barometric lidar designed to operate within the 1.96 µm CO2 absorption band for remote sensing of Martian atmospheric properties. Our focus is on the online wavelength situated in the trough region of two absorption lines, selected due to its insensitivity to laser frequency variations, thus mitigating the necessity for stringent laser frequency stability. Our investigation revolves around a compact lidar configuration, featuring reduced telescope dimensions and lower laser pulse energies. These adjustments are geared towards minimizing costs for potential forthcoming Mars missions. The core measurement objectives encompass the determination of column CO2 absorption optical depth, columnar CO2 abundance, surface atmospheric pressure, and vertical distributions of dust and cloud layers. Through the amalgamation of surface pressure data with atmospheric temperature insights garnered from sounders and utilizing the barometric formula, the prospect of deducing atmospheric pressure profiles becomes feasible. Simulation studies validate the viability of our approach. Notably, the precision of Martian surface pressure measurements is projected to surpass 1 Pa when the aerial dust optical depth is projected to be under 0.7, a typical airborne dust scenario on Mars, considering a horizontal averaging span of 10 km.

Laser-induced transverse voltage effect in c-axis inclined La x Sr1−x TiO3 thin films prepared by MOCVD

Light and thermal detectors based on the laser-induced transverse voltage (LITV) effect have garnered significant interest for their rapid and broad spectral response. In this study, we prepared the La-doped SrTiO3 (STO) epitaxial thin films on the 12° inclined single crystal LaAlO3 (LAO) (100) substrates using our home-designed metal–organic chemical vapor deposition system. Under the illumination of a 248 nm laser, the LITV signals of La x Sr1−x TiO3 films were observed and showed dependence on the La doping level, which can be explained by the changes in the light absorption coefficient, thermal conductivity, and optical penetration depth. The optimized LITV signal was observed with a peak voltage of 23.25 V and a decay time of 106 ns under the laser power density of 1.0 mJ mm−2. The high peak voltage and fast response time of La x Sr1−x TiO3 show great potential in the field of light and thermal detection.

Probing Lorentz Invariance Violation with Absorption of Astrophysical γ-Rays by Solar Photons

We compute in detail the absorption optical depth for astrophysical γ-ray photons interacting with solar photons to produce electron–positron pairs. This effect is greatest for γ-ray sources at small angular distances from the Sun, reaching optical depths as high as τ γ γ ∼ 10−2. We also calculate this effect including modifications to the absorption cross-section threshold from subluminal Lorentz invariance violation (LIV). We show for the first time that subluminal LIV can lead to increases or decreases in τ γ γ compared to the non-LIV case. We show that, at least in principle, LIV can be probed with this effect with observations of γ-ray sources near the Sun at ≳20 TeV by HAWC or LHAASO, although a measurement will be extremely difficult due to the small size of the effect.

Silicate Extinction Profile Based on the Stellar Spectrum by Spitzer/IRS

The 9.7 and 18 μm interstellar spectral features, arising from the Si–O stretching and O–Si–O bending modes of amorphous silicate dust, are the strongest extinction features in the infrared. Here we use the “pair method” to determine the silicate extinction profile by comparing the Spitzer/IRS spectra of 49 target stars with obvious extinction with those of unreddened stars of the same spectral type. The 9.7 μm extinction profile is determined from all the 49 stars and the 18 μm profile is determined from six stars. It is found that the profile has a peak wavelength at ∼9.2–9.8 and ∼18–22 μm, respectively. The peak wavelength of the 9.7 μm feature seems to become shorter for stars of late spectral types; meanwhile the FWHM seems irrelevant to the spectral type, which may be related to circumstellar silicate emission. The silicate optical depth at 9.7 μm, Δτ 9.7, mostly increases with the color excess in J − K S ( EJKS ). The mean ratio of the visual extinction to the 9.7 μm silicate absorption optical depth is A V /Δτ 9.7 ≈ 17.8, in close agreement with that of the solar-neighborhood diffuse interstellar medium. When EJKS>4 , this proportionality changes. The correlation coefficient between the peak wavelength and the FWHM of the 9.7 μm feature is 0.4, which indicates a positive correlation considering the uncertainties of the parameters. The method is compared with replacing the reference star by an atmospheric model spectral energy distribution and no significant difference is observed.

Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths

Abstract. Methods based on the absorption Ångström exponent (AAE) are widely used to estimate the absorption by brown carbon (BrC), and the estimated absorption by BrC can be significantly different from 0, even for pure black carbon (BC). However, few studies have systematically quantified the effects of BC microphysical properties. Moreover, the conditions under which AAE-based methods are applicable are still unclear. In this work, we used BC models partially coated with non-absorbing materials to calculate the total absorption. Since the total absorption is entirely due to BC, the estimated BrC absorption should be 0 if the retrieval methods are accurate. Thus, the ratio of the estimated BrC absorption to BC absorption (ABSBrC) should be the proportion of the BC absorption that is incorrectly attributed to BrC. The results show that a BC AAE of 1 can generally provide reasonable estimates for freshly emitted BC, since ABSBrC is generally in the range of −4.8 % to 2.7 % during that period. However, when BC aerosols are aged, ABSBrC can sometimes reach about 38.7 %. The wavelength dependence of the AAE (WDA) method does not necessarily improve the estimates; sometimes a negative ABSBrC of about −40.8 % is found for partially coated BC. By combining simulations of a global chemical transport model, this work also quantified the effects of BC microphysical properties on BrC global aerosol absorption optical depth (AAOD) estimates. The AAE = 1 method sometimes leads to a misassigned global mean AAOD of about −0.43–0.46×10-3 if the BC aerosols have a complex morphology. The WDA method does not necessarily improve the estimates. In our cases, the WDA methods based on spherical models could lead to a global-mean misassigned AAOD range of about −0.87–0.04×10-3. At the regional scale, the AAE = 1 method sometimes leads to a distributed AAOD of about −7.3 to 5.7×10-3 in some specific regions. Mie-theory-based WDA methods lead to an estimated AAOD error of about -22×10-3 in some regions (e.g., East Asia). This work also showed that the misattributed BrC absorption would lead to substantial uncertainties in the estimation of the global direct radiative forcing (DRF) of absorbing aerosols from different sources.

Threefold reduction of modeled uncertainty in direct radiative effects over biomass burning regions by constraining absorbing aerosols.

Absorbing aerosols emitted from biomass burning (BB) greatly affect the radiation balance, cloudiness, and circulation over tropical regions. Assessments of these impacts rely heavily on the modeled aerosol absorption from poorly constrained global models and thus exhibit large uncertainties. By combining the AeroCom model ensemble with satellite and in situ observations, we provide constraints on the aerosol absorption optical depth (AAOD) over the Amazon and Africa. Our approach enables identification of error contributions from emission, lifetime, and MAC (mass absorption coefficient) per model, with MAC and emission dominating the AAOD errors over Amazon and Africa, respectively. In addition to primary emissions, our analysis suggests substantial formation of secondary organic aerosols over the Amazon but not over Africa. Furthermore, we find that differences in direct aerosol radiative effects between models decrease by threefold over the BB source and outflow regions after correcting the identified errors. This highlights the potential to greatly reduce the uncertainty in the most uncertain radiative forcing agent.

Using transducerless time-domain thermoreflectance technique to measure in- and cross-plane thermal conductivity of nanofilms

Time-domain thermoreflectance (TDTR) and frequency-domain thermoreflectance techniques have been widely used to measure thermal properties. However, the existence of the metal sensor brings some limitations to the experimental measurement, such as temperature limits, disability to measure low in-plane thermal conductivity, in situ measurement cannot be achieved, etc. This paper proposes a transducerless time-domain thermoreflectance method to measure in- and cross-plane thermal conductivity of nanofilms, in which the optical absorption depth and thermal conductivity tensor are considered to establish a new differential equation that can describe the heat conduction process in multilayer structures. This thermal model can also calculate the effects of spot ellipticity and spot offset distance. Then, the analytical solution and relative deviation of this new model and the surface heat flow boundary model used in conventional TDTR are compared by calculating the phase signals. In terms of experimental measurement, this model is successfully used to derive cross- and in-plane thermal conductivity of PdSi and IrNiTa amorphous alloy nanofilms without a metal sensor.

Anomalous Selective Absorption of Smoke Aerosol during Forest Fires in Alaska in July–August 2019

According to the monitoring data of the optical and microphysical characteristics of smoke aerosol at AERONET stations during forest fires in the summer of 2019 in Alaska, anomalous selective absorption of smoke aerosol was detected in the visible and near infrared spectral range from 440 to 1020 nm. With anomalous selective absorption, the imaginary part of the refractive index of smoke aerosol reached 0.315 at a wavelength of 1020 nm. A power-law approximation of the spectral dependence of the imaginary part of the refractive index with an exponent from 0.26 to 2.35 is proposed. It is shown that for anomalous selective absorption, power-law approximations of the spectral dependences of the aerosol optical extinction and absorption depths are applicable with an Angstrom exponent from 0.96 to 1.65 for the aerosol optical extinction depth and from 0.97 to –0.89 for the aerosol optical absorption depth, which reached 0.72. Single scattering albedo varied from 0.62 to 0.96. In the size distribution of smoke aerosol particles with anomalous selective absorption, the fine fraction of particles of condensation origin dominated. The similarity of the fraction of particles distinguished by anomalous selective absorption with the fraction of tar balls detected by electron microscopy in smoke aerosol, which, apparently, arise during the condensation of terpenes and their oxygen-containing derivatives, is noted.

A Plant Species Dependent Wildfire Black Carbon Emission Inventory in Northern Eurasia

AbstractWildfire emission inventories are usually applied with biome‐scale emission factors for atmospheric modeling. However, emission factors measured for different plant species vary substantially within the same biome. We apply the species‐specific emission factors and refine the Fire Emission Inventory‐northern Eurasia (FEI‐NE), and derive the wildfire black carbon emission inventory in northern Eurasia from 2002 to 2015. Our new inventory produces 61% more black carbon emissions than current estimates based on Global Fire Emission Database (GFED) and 33% less than FEI‐NE. Model simulations with different inventories are compared with ground‐based and satellite retrievals of aerosol absorption optical depth (AAOD). Compared with the Ozone Monitoring Instrument, the normalized root mean square deviation of AAOD over northern Eurasia is reduced from 1.0 under FEI‐NE to 0.95 through application of the new inventory. This study reveals the importance of applying sub‐biome‐scale emission factors for wildfire inventories development and revisiting emissions uncertainty in atmospheric modeling.

A comparison of atmospheric aerosol absorption properties from the MERRA-2 reanalysis with AERONET

Our focus is the comparison of atmospheric aerosol absorption properties between the MERRA-2 reanalysis and the inversion product of the surface station network AERONET. We use the available Aerosol Absorption Optical Depth (AAOD) and Single Scattering Albedo (SSA) data from both sources during the period 1993–2022, for the globe. The comparison is performed for the whole dataset, but also repeated for different classifications, namely by aerosol types, Köppen climate, and continent. Moreover, we investigate the relationships between these classifications. For these medium and high optical depth cases, the MERRA-2 relative bias for AAOD and SSA is globally −3.7% and −1.4%, but there is a wide differentiation in performance for the different types, climates, and continents. The MERRA-2 SSA frequency distribution is too narrow compared to the AERONET. MERRA-2 strongly overestimates the absorption over N. America and less so over S. America and Europe, while it underestimates it greatly over Oceania. AAOD is underestimated over biomass-burning regions and overestimated over most areas rich in dust. There is evidence that the lack of brown carbon in the aerosol type classification scheme in MERRA-2 hampers its performance. The comparison over Asia dry areas (classified as Köppen climate type B) shows a large underestimation in AAOD, non-existent in other dry (B) climate types. For the relatively few observations over polar (Köppen type E) climates, MERRA-2 gives too absorptive aerosols. With respect to absorption properties, it appears that MERRA-2 would improve its agreement with AERONET by addressing some erroneous aerosol classifications, employing the brown carbon type, and introducing more detail in dry region aerosol sources.

Prediction of gamma-ray emission from Cygnus X-1, SS 433, and GRS 1915+105 after absorption

Context. Stellar black hole X-ray binary stars (BHXRBs) are among the most luminous and powerful systems located in our Milky Way and in other galaxies of the Universe. Their jets are prominent sources of particles (e.g., neutrinos) and radiation emissions in energy ranges detectable by terrestrial and space telescopes, even from galaxies deep in the space. A significant factor, however, would be the photon absorption effect that occur due to scattering on the lower end of the energy radiation of the system’s surroundings. Aims. We aim to study in detail and extract predictions for the emitted gamma-ray intensities and integral fluxes of the jets emanating from BHXRB systems Cygnus X-1, GRS 1915+105, and SS 433. Toward this end, we also investigate the severe effects of gamma-ray absorption that eradicate part of the produced intensity spectra. Furthermore, we explore the jet regions that are most likely to emit unabsorbed gamma-rays capable of reaching detectors on Earth. Our goal is to calculate the integral fluxes before and after absorption for the abovementioned systems and compare the results with the very-high-energy gamma-ray observations of sensitive telescopes such as the MAGIC, H.E.S.S., Fermi-LAT, and so on. Methods. The implemented gamma-ray emission mechanisms initiate from the p − p scattering process inside the hadron-dominated jets following the well-known shock-wave particle acceleration. In addition, we estimate the optical depths of three absorption processes between gamma-ray photons and (i) accretion disk X-ray emission, (ii) black hole corona photons, and (iii) donor star thermal emission. We also examine the dependence of the absorption optical depths on various parameters, such as the disk’s temperature, coronal radius and, donor star luminosity. Results. We find that disk absorption is dominant for distances of z &lt; 1010 cm from the black hole, while the donor star absorption dominates for 1010 &lt; z &lt; 1012 cm. Beyond that jet point, the absorption effects become significantly weaker. Cygnus X-1 presents the highest gamma-ray integral flux across the jet length, while GRS 1915+105 emits the least due to its weakly collimated jets. The jets of SS 433 emit gamma-rays only for z &gt; 1010 cm due to severe disk absorption fueled by the system’s super-Eddington accretion limit.

Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing

Quantitative estimations of atmospheric aerosol absorption are rather uncertain due to the lack of reliable information about the global distribution. Because the information about aerosol properties is commonly provided by single-viewing photometric satellite sensors that are not sensitive to aerosol absorption. Consequently, the uncertainty in aerosol radiative forcing remains one of the largest in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC AR5 and AR6). Here, we use multi-angular polarimeters (MAP) to provide constraints on emission of absorbing aerosol species and estimate global aerosol absorption optical depth (AAOD) and its climate effect. Our estimate of modern-era mid-visible AAOD is 0.0070 that is higher than IPCC by a factor of 1.3-1.8. The black carbon instantaneous direct radiative forcing (BC DRF) is +0.33 W/m2 [+0.17, +0.54]. The MAP constraint narrows the 95% confidence interval of BC DRF by a factor of 2 and boosts confidence in its spatial distribution.

Modeling the Extragalactic Background Light and the Cosmic Star Formation History

We present an updated model for the extragalactic background light (EBL) from stars and dust, over wavelengths ≈0.1–1000 μm. This model uses accurate theoretical stellar spectra, and tracks the evolution of star formation, stellar mass density, metallicity, and interstellar dust extinction and emission in the universe with redshift. Dust emission components are treated self-consistently, with stellar light absorbed by dust reradiated in the infrared as three blackbody components. We fit our model, with free parameters associated with star formation rate and dust extinction and emission, to a wide variety of data: luminosity density, stellar mass density, and dust extinction data from galaxy surveys; and γ-ray absorption optical depth data from γ-ray telescopes. Our results strongly constraint the star formation rate density and dust photon escape fraction of the universe out to redshift z = 10, about 90% of the history of the universe. We find our model result is, in some cases, below lower limits on the z = 0 EBL intensity, and below some low-z γ-ray absorption measurements.

Echo-Signal De-Noising of CO2-DIAL Based on the Ensemble Empirical Mode Decomposition

The carbon dioxide (CO2) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected to improve the inversion result. In this paper, we simultaneously decompose three signal pairs into different intrinsic mode functions (IMFs) using the method of ensemble empirical mode decomposition (EEMD). Further, the correlation coefficients of the IMFs with the same temporal scale are regarded as the criterion to determine the components that need removal. This method not only retains the useful information effectively but also removes the noise component. A significant improvement in the R2 of the differential absorption optical depth (DAOD) of the de-noised signals is obtained. The results of the simulated and observed analysis signal demonstrated improvement both in the SNR and in the retrieval precision.

Aerosol Characteristics during the COVID-19 Lockdown in China: Optical Properties, Vertical Distribution, and Potential Source

The concentration changes of aerosols have attracted wide-ranging attention during the COVID-19 lockdown (CLD) period, but the studies involving aerosol optical properties (AOPs) are relatively insufficient, mainly AOD (fine-mode AOD (AODf) and coarse-mode AOD (AODc)), aerosol absorption optical depth (AAOD), and aerosol extinction coefficient (AEC). Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, &lt;2 km) decreased in most areas of China. Compared with previous years (average 2017–2019), the AOD (AEC) of NCP, CC, YRD, PRD, and SB reduced by 3.33% (10.76%), 14.36% (32.48%), 10.80% (29.64%), 31.44% (22.68%), and 15.50% (8.44%), respectively. In addition, MODIS (AODc) and MERRA-2 (AODc) decreased in the five study areas compared with previous years, so the reduction in dust activities also contributed to improving regional air quality during the epidemic. Despite the reduction of anthropogenic emissions (AODf) in most areas of China during the CLD periods, severe haze events (AODf &gt; 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans.

Using Multi-Platform Satellite Observations to Study the Atmospheric Evolution of Brown Carbon in Siberian Biomass Burning Plumes

A bulk of evidence from in situ observations and lab experiments suggests that brown carbon (light-absorbing organic compounds in particles) can provide a significant yet highly variable contribution to the overall light absorption by aerosol particles from biomass burning (BB). Partly stemming from the complexity of the atmospheric evolution of organic aerosol (OA), the variability in brown carbon (BrC) absorption makes it difficult to partition the radiative effects of BrC and black carbon (BC) in atmospheric and climate models; as such, there are calls for satellite-based methods that could provide a statistical characterization of BrC absorption and its evolution in different regions of the world, especially in remote BB regions, such as Siberia. This study examined the feasibility of the statistical characterization of the evolution of BrC absorption and related parameters of BB aerosol in smoke plumes from intense wildfires in Siberia through the analysis of a combination of data from three satellite instruments: OMI (Ozone Monitoring Instrument), MISR (Multi-Angle Imaging SpectroRadiometer), and MODIS (Moderate Resolution Imaging Spectroradiometer). Using a Monte Carlo method, which related the satellite retrievals of the absorption and extinction aerosol optical depths to Mie theory calculations of the optical properties of BB aerosol, we found that the BrC absorption, as well as the imaginary refractive index for the OA, decreased significantly in Siberian BB smoke plumes during about 30 h of the daylight evolution, nevertheless remaining considerable until at least 70 h of the daylight evolution. Overall, the study indicated that the analysis of multi-platform satellite observations of BB plumes can provide useful insights into the atmospheric evolution of BrC absorption and the partitioning of BrC and BC contributions to the total light absorption by BB aerosol.

Aerosol climatology characterization over Bangladesh using ground-based and remotely sensed satellite measurements

Atmospheric aerosols affect human health, alter cloud optical properties, influence the climate and radiative balance, and contribute to the cooling of the atmosphere. Aerosol climatology based on aerosol robotic network (AERONET) and ozone monitoring instrument (OMI) data from two locations (Urban Dhaka and coastal Bhola Island) over Bangladesh was conducted for 8 years (2012–2019), focusing on two characterization schemes. Four aerosol parameters, such as extinction angstrom exponent (EAE), absorption AE (AAE), single scattering albedo (SSA), and real refractive index (RRI), were exclusively discussed to determine the types of aerosol. In addition, the light absorption properties of aerosol were inspected tagging the association between size parameters similar to fine mode fraction (FMF), AE, and absorption parameters (SSA and AAE). Results of aerosol absorption optical depth (AAOD) were validated with the satellite-borne cloud–aerosol lidar and infrared pathfinder satellite observation (CALIPSO) aerosol subtype profiles. The overall average values of AAOD for Dhaka and Bhola were (0.110 ± 0.002) [0.106, 0.114] and (0.075 ± 0.001) [0.073, 0.078], respectively. The values derived by OMI were the similar (0.024 ± 0.001 [0.023, 0.025] for Dhaka, and 0.023 ± 0.001 [0.023, 0.024] for Bhola). Two types of aerosols were potentially identified, for example, biomass burning and urban/industrial types over Bangladesh with insignificant contribution from the dust aerosol. Black carbon (BC) was the prominent absorbing aerosol (45.9%–89.1%) in all seasons with negligible contributions from mixed BC and/or dust and dust alone. Correlations between FMF and SSA confirmed that BC was the dominant aerosol type over Dhaka and Bhola. CALIPSO’s vertical information was consistent with the AERONET column information. The results of aerosol parameters will have a substantial impact on the aerosol radiative forcing, and climate modeling as well as air quality management in Southeast Asia’s heavily polluted territories.