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The scattering of light by aerosol particles dictates atmospheric visibility, which is a straightforward indicator of air quality. It is affected by numerous factors, such as particle number size distribution, particle mass concentration (PM2.5), ambient relative humidity (RH), and chemical composition. The latter two factors jointly influence the aerosol liquid water content (ALWC). Here, the particle backscattering coefficient (βp) under ambient RH conditions is investigated to differentiate and quantify the contributions of aerosol properties and meteorology using comprehensive observational datasets acquired at three megacities in China, that is, Beijing (BJ), Nanjing (NJ), and Guangzhou (GZ). Overall, the temporal variations in βp under ambient RH conditions are consistent with those in ALWC at the three sites. The PM2.5 in BJ is systematically higher than in NJ and GZ, while ambient RH and aerosol hygroscopicity in NJ are much higher than in BJ and GZ. Notable differences in the variations of βp with related factors at the three sites are demonstrated. βp is more sensitive to particle hygroscopicity and mass in NJ and ambient RH in BJ. The relative contributions of these factors to βp at the three sites under different pollution conditions are differentiated and quantified. The factor with the largest impact on the variability in βp shifts from particle mass to ambient RH as air quality deteriorated to heavy pollution in BJ. The opposite is true in NJ. In GZ, the contributions of these factors to changes in βp under different pollution conditions are similar, both dominated by PM2.5. Plain Language Summary: Scattering of light by aerosol is a straightforward measure of air quality because of its close link to visibility. It is dictated primarily by aerosol mass loading, size distribution, chemical composition, and humidity. We used comprehensive observational datasets acquired at three sites in China to differentiate and quantify the contributions to the scattering of light by aerosol loading measured by aerosol particulate mass and aerosol properties, as well as humidity. The findings differ among the three cities due to differences in aerosol properties and meteorology. Scattering of light by aerosol is more sensitive to particle hygroscopicity and mass concentration in Nanjing and more sensitive to ambient humidity in Beijing. Local emission control measures can effectively reduce aerosol mass concentrations in Nanjing and Guangzhou. Weather conditions are more influential in Beijing due to the dominant influence of humidity. Key Points: This study differentially quantifies the impacts of aerosol loading and properties and meteorology on scattering at three sites in ChinaScattering of light by aerosol is most sensitive to particle hygroscopicity and mass in Nanjing and humidity in BeijingHumidity substantially affects scattering during heavy haze in Beijing, whereas particle mass is more impactful in Nanjing and Guangzhou [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) absorption correction of the sulfur dioxide (SO2) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO2 camera for the real-time NO2 absorption correction and aerosol scattering correction. This method performs NO2 absorption correction by the correlation between the NO2 column density measurement of the DOAS and the NO2 optical depth of the corresponding channel from the SO2 camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO2 camera to correct for aerosol scattering and it can be reduced by 11.3% after NO2 absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO2 camera system with NO2 absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO2 emissions. [ABSTRACT FROM AUTHOR]

Summary: Free‐space radio‐frequency (RF) communication links for intersatellite or satellite‐to‐ground communications are getting increasingly constraint by the insufficient spectrum availability and limited data rate of RF technology. With the advent of large satellite mega‐constellation networks for global communications coverage, this limitation of classical RF communication becomes even more critical. Therefore, the establishment of point‐to‐point free‐space optical link technology (FSO) in space will become of paramount importance in future systems, where the application will be for data‐relays links, or for mega‐constellations inter‐satellite links, as well as for direct data downlinks, or from deep‐space probes to ground. Further advantages of optical FSO—besides spectrum availability—is its increased power efficiency, higher data rates, avoidance of interference, and inherent protection against interception. When, however, these optical communication links have to pass through Earth's atmosphere, attenuation and scattering effects do influence the signal transmission. In this publication, we investigate the effects of atmospheric attenuation, including the effects of molecular absorption as well as aerosol scattering and absorption, for typical wavelength regions used for FSO, dependent on the link geometries. Based on transmission‐simulation databases, we show useful spectral ranges and their specific attenuation strength. Free spectral transmission windows dependent on atmospheric quality and elevation angle are identified for reliable and efficient use of the optical transmission technology in space applications. [ABSTRACT FROM AUTHOR]

A practical Atmospheric Correction algorithm for inLand and Nearshore Coastal waters (ACLANC) is proposed in this study. The ACLANC algorithm uses interpolated aerosol optical depth (AOD) products (AOD $_{\mathrm {interp}}$) from nearby land surfaces and simulates the corresponding aerosol reflectance spectrum using a combination of the continental model in the satellite signal in the solar spectrum-vector (6SV) radiative transfer code and an approximate aerosol model (r85f20) in the Sea-viewing Wide Field-of view Sensor (SeaWiFS) Data Analysis System (SeaDAS). Validations with worldwide in situ measurements show that the ACLANC-derived remote-sensing reflectance ($R_{\mathrm {rs}}$) for nine Moderate Resolution Imaging Spectroradiometer (MODIS) bands agreed well with the in situ datasets, where the mean $R^{2}$ was 0.77 ± 0.09 and the mean unbiased percent difference was 28.7% ± 9.8%. ACLANC outperformed the existing atmospheric correction algorithms in not only the accuracy of the $R_{\mathrm {rs}}$ retrievals but also data coverage. Vicarious calibration over the ACLANC algorithm showed minor improvement in the derived $R_{\mathrm {rs}}$ products. Error budget analysis revealed that the uncertainties in AODinterp represent >50% of the errors for ACLANC and that this proportion increases with decreasing AOD. Further efforts can also be applied to improve the aerosol models, especially for turbid aerosol environments, where the fixed aerosol model in SeaDAS contributes up to 30% of the error budget. The ACLANC algorithm can potentially be implemented in ocean color missions other than MODIS to obtain $R_{\mathrm {rs}}$ with high accuracy and wide coverage for global inland and nearshore coastal waters. [ABSTRACT FROM AUTHOR]

From August to October 2019, the aerosol backscattering and deformation of the Earth's crust were monitored in the tunnels of the Baksan Neutrino Observatory above the Elbrus volcano chamber. An omnidirectional modulation of the seasonal crust compression with a multiple excess of the average rate (~4 μm/day) and with a change in the sign of decrease in the lidar-signal scattering on aerosols to anomalous growth in the "hot" tunnel is found. It is established that the modulation is induced by the rapid cooling of the external atmosphere. The delays of the accelerated compression of the strainmeter arm (up to 14 μm/day) and the beginning of growth of the backscattering lidar signal relative to the beginning of the temperature decrease (~2 and ~7 days, respectively) are measured. The mechanism of the phenomena discovered is discussed. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) absorption correction of the sulfur dioxide (SO2) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO2 camera for the real-time NO2 absorption correction and aerosol scattering correction. This method performs NO2 absorption correction by the correlation between the NO2 column density measurement of the DOAS and the NO2 optical depth of the corresponding channel from the SO2 camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO2 camera to correct for aerosol scattering and it can be reduced by 11.3% after NO2 absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO2 camera system with NO2 absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO2 emissions.

Due to the polarization effects of the Earth's surface reflection and atmospheric particles' scattering, high-precision retrieval of atmospheric parameters from near-infrared satellite data requires accurate vector atmospheric radiative transfer simulations. This paper presents a near-infrared vector radiative transfer model based on the doubling and adding method. This new model utilizes approximate calculations of the atmospheric transmittance, reflection, and solar scattering radiance for a finitely thin atmospheric layer. To verify its accuracy, the results for four typical scenarios (single molecular layer with Rayleigh scattering, single aerosol layer scattering, multi-layer Rayleigh scattering, and true atmospheric with multi-layer molecular absorption, Rayleigh and aerosol scattering) were compared with benchmarks from a well-known model. The comparison revealed an excellent agreement between the results and the reference data, with accuracy within a few thousandths. Besides, to fulfill the retrieval algorithm, a numerical differentiation-based Jacobian calculation method is developed for the atmospheric and surface parameters. This is coupled with the adding and doubling process for the radiative transfer calculation. The Jacobian matrix produced by the new algorithm is evaluated by comparison with that from the perturbation method. The relative Jacobian matrix deviations between the two methods are within a few thousandths for carbon dioxide and less than 1.0×10−3% for aerosol optical depth. The two methods are consistent for surface albedo, with a deviation below 2.03×10−4%. All validation results suggest that the accuracy of the proposed radiative transfer model is suitable for inversion applications. This model exhibits the potential for simulating near-infrared measurements of greenhouse gas monitoring instruments. [ABSTRACT FROM AUTHOR]

In this paper, we present the revision of the cross-section database used for the retrieval of aerosol and gas species from remote sensing measurements by the GOMOS instrument onboard ENVISAT. The absorption cross-section spectra concern ozone, nitrogen dioxide and nitrogen trioxide, for which improved datasets have been published since the implementation of the original GOMOS cross-section database in preparation of the ENVISAT mission. We evaluate the molecular absorption cross-section spectra currently available for O3, NO2 and NO3, and we present and discuss our selection of datasets and the set-up of the revised absorption cross-section database, with the focus on these three gases. The objective is to provide an optimal characterization of their absorption spectrum over the UV-visible-near IR range used by AerGOM, a retrieval algorithm that was designed to optimize the retrieval of aerosol species from GOMOS measurements. Despite its application to the specific case of GOMOS, it is the aim of this work to cover a more general scope than this particular mission, and to provide an evaluation applicable to any other case of remote sensing experiment covering the UV to near IR range, possibly with a high spectral resolution.

COVID-19 is evolving into one of the worst pandemics in recent history, claiming a death toll of over 1.5 million as of December 2020. In an attempt to limit the expansion of the pandemic in its initial phase, nearly all countries imposed restriction measures, which resulted in an unprecedented reduction of air pollution. This study aims to assess the impact of the lockdown effects due to COVID-19 on in situ measured aerosol properties, namely spectral-scattering (bsca) and absorption (babs) coefficients, black carbon (BC) concentrations, single-scattering albedo (SSA), scattering and absorption Ångström exponents (SAE, AAE) in Athens, Greece. Moreover, a comparison is performed with the regional background site of Finokalia, Crete, for a better assessment of the urban impact on observed differences. The study examines pre-lockdown (1–22 March 2020), lockdown (23 March–3 May 2020) and post-lockdown (4–31 May 2020) periods, while the aerosol properties are also compared with a 3–4 year preceding period (2016/2017–2019). Comparison of meteorological parameters in Athens, between the lockdown period and respective days in previous years, showed only marginal variation, which is not deemed sufficient in order to justify the notable changes in aerosol concentrations and optical properties. The largest reduction during the lockdown period was observed for babs compared to the pre-lockdown (−39%) and to the same period in previous years (−36%). This was intensified during the morning traffic hours (−60%), reflecting the large decrease in vehicular emissions. Furthermore, AAE increased during the lockdown period due to reduced emissions from fossil-fuel combustion, while a smaller (−21%) decrease was observed for bsca along with slight increases (6%) in SAE and SSA values, indicating that scattering aerosol properties were less affected by the decrease in vehicular emissions, as they are more dependent on regional sources and atmospheric processing. Nighttime BC emissions related to residential wood-burning were slightly increased during the lockdown period, with respect to previous-year means. On the contrary, aerosol and pollution changes during the lockdown period at Finokalia were low and highly sensitive to natural sources and processes.

Smoke from fires significantly influences climate, weather, and human health. Fire smoke is traditionally detected using an aerosol index calculated from spectral contrast changes. However, such methods usually miss thin smoke plumes. It also remains challenging to accurately separate smoke plumes from dust, clouds, and bright surfaces. To improve smoke plume detections, this paper presents a new scattering-based smoke detection algorithm (SSDA) depending mainly on visible and infrared imaging radiometer suite (VIIRS) blue and green bands. The SSDA is established based on the theory of Mie scattering that occurs when the diameter of an atmospheric particulate is similar to the wavelength of the scattered light. Thus, smoke commonly causes Mie scattering in VIIRS blue and green bands because of the close correspondence between smoke particulate diameters and the blue/green band wavelengths. For developing the SSDA, training samples were selected from global fire-prone regions in North America, South America, Africa, Indonesia, Siberia, and Australia. The SSDA performance was evaluated against the VIIRS aerosol detection product and smoke detections from the ultraviolet aerosol index using manually labeled fire smoke plumes as a benchmark. Results show that the SSDA smoke detections are superior to existing products due chiefly to the improved ability of the algorithm to detect thin smoke and separate fire smoke from other surface types. Moreover, the SSDA smoke distribution pattern exhibits a high spatial correlation with the global fire density map, suggesting that SSDA is capable of detecting smoke plumes of fires in near real-time across the globe.

An efficient spectrally resolved radiative model is used to calculate surface downwelling longwave (DLW) radiation (0  ∼  2500 cm − 1 ) under clear sky (cloud free) conditions at the ground level. The wavenumber spectral resolution of the model is 0.01 cm − 1 and the atmosphere is represented by 18 non-uniform plane-parallel layers with pressure in each layer determined on a pressure-based coordinate system. The model utilizes the most up-to-date (2016) HITRAN molecular spectral data for 7 atmospheric gases: H 2 O, CO 2 , O 3 , CH 4 , N 2 O, O 2 and N 2 . The MT_CKD model is used to calculate water vapor and CO 2 continuum absorption coefficients. Longwave absorption and scattering coefficients for aerosols are modeled using Mie theory. For the non-scattering atmosphere (aerosol free), the surface DLW agrees within 2.91% with mean values from the InterComparison of Radiation Codes in Climate Models (ICRCCM) program, with spectral deviations below 0.035 W cm m − 2 . For a scattering atmosphere with typical aerosol loading, the DLW calculated by the proposed model agrees within 3.08% relative error when compared to measured values at 7 climatologically diverse SURFRAD stations. This relative error is smaller than a calibrated parametric model regressed from data for those same 7 stations, and within the uncertainty (+/− 5 W m − 2 ) of pyrgeometers commonly used for meteorological and climatological applications. The DLW increases by 1.86  ∼  6.57 W m − 2 when compared with aerosol-free conditions, and this increment decreases with increased water vapor content due to overlap with water vapor bands. As expected, the water vapor content at the layers closest to the surface contributes the most to the surface DLW, especially in the spectral region 0  ∼  700 cm − 1 . Additional water vapor content (mostly from the lowest 1 km of the atmosphere) contributes to the spectral range of 400  ∼  650 cm − 1 . Low altitude aerosols ( ∼  3.46 km or less) contribute to the surface value of DLW mostly in the spectral range 750  ∼  1400 cm − 1 . [ABSTRACT FROM AUTHOR]

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 PM 1 and PM 10 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 PM 1 and PM 10 , 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. [Display omitted] • Investigation of aerosol optical, chemical properties in the marine environments around the EMME region. • Aerosol scattering/absorption maximized in the Persian Gulf due to anthropogenic/industrial aerosol. • Contrasting aerosol-type dominance between the marine subregions. • Spectral SSA enables to detect the dust imprint in the marine boundary layer. • Significant influence of the particle size on aerosol properties and dominant types. [ABSTRACT FROM AUTHOR]

Abstract: Large retrieval errors in column‐weighted CO2 mixing ratio (XCO2) over deserts are evident in the Orbiting Carbon Observatory 2 version 7 L2 products. We argue that these errors are caused by the surface albedo being close to a critical surface albedo (αc). Over a surface with albedo close to αc, increasing the aerosol optical depth (AOD) does not change the continuum radiance. The spectral signature caused by changing the AOD is identical to that caused by changing the absorbing gas column. The degeneracy in the retrievals of AOD and XCO2 results in a loss of degrees of freedom and information content. We employ a two‐stream‐exact single scattering radiative transfer model to study the physical mechanism of XCO2 retrieval error over a surface with albedo close to αc. Based on retrieval tests over surfaces with different albedos, we conclude that over a surface with albedo close to αc, the XCO2 retrieval suffers from a significant loss of accuracy. We recommend a bias correction approach that has significantly improved the XCO2 retrieval from the California Laboratory for Atmospheric Remote Sensing data in the presence of aerosol loading. [ABSTRACT FROM AUTHOR]