Advanced characterisation of aerosol size properties from measurements of spectral optical depth using the GRASP algorithm

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018)

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

Pre-filter analysis for retrieval of microphysical particle parameters: a quality-assurance method applied to 3 backscatter (β) +2 extinction (α) optical data taken with HSRL/Raman lidar

We analyze the solution space of 3β+2α optical data inferred from lidar measurements, i.e., backscatter coefficients at three wavelengths and extinction coefficients at two wavelengths. These optical data are governed by microphysical parameters that can be expressed in terms of particle size distribution, effective radius, and complex refractive index (CRI). In our analysis, we consider two scenarios of the solution space. First, it can be expressed in terms of monomodal particle size distributions represented either by fine modes or by coarse modes. Secondly, the particle size distributions contain a fine mode as well as a coarse mode. Consideration of both scenarios and different values of the effective radius and CRI allows us to find synthetic 3β+2α optical data and corresponding intensive parameters (IPs) such as lidar ratios, backscatter- and extinction-related Ångström exponents at the available measurement wavelengths. Based on interdependencies between synthetic IPs and various microphysical properties, the qualitative and quantitative criteria for the optical data quality-assurance tool are developed. We derive the conditions of smoothness, closeness, convergence, and stability of the solution space for the quantitative criteria to test the quality of the 3β+2α optical data. Our novel methodology, to the best of our knowledge, can be used not only for particles of spherical shape, but also for cases in which particles are irregularly shaped. Another strength of our methodology is that it also works for the case of a size-dependent and wavelength-dependent CRI. We show the potential of this methodology for a measurement case from the ORACLES campaign. Data were taken with NASA Langley's airborne HSRL-2 instrument on September 24, 2016.

Extensive characterization of aerosol optical properties and chemical component concentrations: Application of the GRASP/Component approach to long-term AERONET measurements

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93-1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Mobile Observations by Lidar, Sun Photometer and in Situ in North China Plain

A mobile laboratory integrating lidar, sun photometer and in situ instruments has been deployed to observe the aerosol spatial variability in North China Plain in May 2017. Results from the campaign are presented.

Optimal Estimation Retrieval of Aerosol Fine-Mode Fraction from Ground-Based Sky Light Measurements

In this paper, the feasibility of retrieving the aerosol fine-mode fraction (FMF) from ground-based sky light measurements is investigated. An inversion algorithm, based on the optimal estimation (OE) theory, is presented to retrieve FMF from single-viewing multi-spectral radiance measurements and to evaluate the impact of utilization of near-infrared (NIR) measurements at a wavelength of 1610 nm in aerosol remote sensing. Self-consistency tests based on synthetic data produced a mean relative retrieval error of 4.5%, which represented the good performance of the OE inversion algorithm. The proposed algorithm was also performed on real data taken from field experiments in Beijing during a haze pollution event. The correlation coefficients (R) for the retrieved aerosol volume fine-mode fraction (FMFv) and optical fine-mode fraction (FMFo) against AErosol RObotic NETwork (AERONET) products were 0.94 and 0.95 respectively, and the mean residual error was 4.95%. Consequently, the inversion of FMFv and FMFo could be well constrained by single-viewing multi-spectral radiance measurement. In addition, by introducing measurements of 1610 nm wavelength into the retrieval, the validation results showed a significant improvement in the R value for FMFo (from 0.89–0.94). These results confirm the high value of NIR measurements for the retrieval of coarse mode aerosols.

Inferring Fine-Mode and Coarse-Mode Aerosol Complex Refractive Indices from AERONET Inversion Products over China

Detailed knowledge of the complex refractive indices (m) of fine- and coarse-mode aerosols is important for enhancing understanding of the effect of atmospheric aerosol on climate. However, studies on obtaining aerosol modal m values are particularly scarce. This study proposes a method for inferring m values of fine- and coarse-mode aerosol using the inversion products from the AERONET ground-based aerosol robotic network. By identifying the aerosol type, modal m values are constrained and then inferred based on a maximum likelihood method. Numerical tests showed that compared with the reference values, our method slightly overestimates the real parts of the refractive indices (n), but underestimates the imaginary parts (k) by 2.11% ± 11.59% and 8.4% ± 26.42% for fine and coarse modes, respectively. We applied this method to 21 AERONET sites around China, which yielded annual mean m values of (1.45 ± 0.04) + (0.0109 ± 0.0046)i and (1.53 ± 0.01) + (0.0039 ± 0.0011)i for fine- and coarse-mode aerosols, respectively. It is observed that the fine mode n decreased from 1.53 to 1.39 with increasing latitude, while fine mode k values were generally larger than 0.008 over most of China. The coarse-mode n and k ranged from 1.52 to 1.56 and from 0.002 to 0.006, respectively.

A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms

We have developed a method for evaluating the fidelity of the Aerosol Robotic Network (AERONET) retrieval algorithms by mimicking atmospheric extinction and radiance measurements in a laboratory experiment. This enables radiometric retrievals that use the same sampling volumes, relative humidities, and particle size ranges as observed by other in situ instrumentation in the experiment. We use three Cavity Attenuated Phase Shift (CAPS) monitors for extinction and University of Maryland Baltimore County’s (UMBC) three-wavelength Polarized Imaging Nephelometer (PI-Neph) for angular scattering measurements. We subsample the PI-Neph radiance measurements to angles that correspond to AERONET almucantar scans, with simulated solar zenith angles ranging from 50 ∘ to 77 ∘ . These measurements are then used as input to the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, which retrieves size distributions, complex refractive indices, single-scatter albedos, and bistatic LiDAR ratios for the in situ samples. We obtained retrievals with residuals less than 8% for about 90 samples. Samples were alternately dried or humidified, and size distributions were limited to diameters of less than 1.0 or 2.5 μ m by using a cyclone. The single-scatter albedo at 532 nm for these samples ranged from 0.59 to 1.00 when computed with CAPS extinction and Particle Soot Absorption Photometer (PSAP) absorption measurements. The GRASP retrieval provided single-scatter albedos that are highly correlated with the in situ single-scatter albedos, and the correlation coefficients ranged from 0.916 to 0.976, depending upon the simulated solar zenith angle. The GRASP single-scatter albedos exhibited an average absolute bias of +0.023–0.026 with respect to the extinction and absorption measurements for the entire dataset. We also compared the GRASP size distributions to aerodynamic particle size measurements, using densities and aerodynamic shape factors that produce extinctions consistent with our CAPS measurements. The GRASP effective radii are highly correlated (R = 0.80) and biased under the corrected aerodynamic effective radii by 1.3% (for a simulated solar zenith angle of θ ∘ = 50 ∘ ); the effective variance indicated a correlation of R = 0.51 and a relative bias of 280%. Finally, our apparatus was not capable of measuring backscatter LiDAR ratios, so we measured bistatic LiDAR ratios at a scattering angle of 173 degrees. The GRASP bistatic LiDAR ratios had correlations of 0.71 to 0.86 (depending upon simulated θ ∘ ) with respect to in situ measurements, positive relative biases of 2–10%, and average absolute biases of 1.8–7.9 sr.

Comparing Aerosol Refractive Indices Retrieved from Full Distribution and Size- and Mass-Selected Measurements

Refractive index retrievals (also termed inverse Mie methods or optical closure) have seen considerable use as a method to extract the refractive index of aerosol particles from measured optical properties. Retrievals of an aerosol refractive index use one of two primary methods: 1) measurements of the extinction, absorption and/or scattering cross-sections or efficiencies of size- (and mass-) selected particles for mass-mobility refractive index retrievals (MM-RIR) or 2) measurements of aerosol size distributions and a combination of the extinction, absorption and/or scattering coefficients for full distribution refractive index retrievals (FD-RIR). These two methods were compared in this study using pure and mixtures of ammonium sulfate (AS) and nigrosin aerosol, which constitute a non-absorbing and absorbing material, respectively. The results indicate that the retrieved complex refractive index values are correlated to the amount of nigrosin in the aerosol but can be highly variable with differences in the real and imaginary components that range between -0.002 and 0.216 and -0.013 and 0.086; the average and standard deviation of the differences are 0.046 ± 0.046 and 0.023 ± 0.033, respectively. Forward calculation of the optical properties yielded average absolute values of the relative deviation of ≈ 15 % and ≈ 26 % for FD-RIR data using the MM-RIR values and contrariwise. The range of retrieved refractive indices were used to calculate the normalized global average aerosol radiative forcing of a model accumulation mode remote continental aerosol. Deviations using the refractive indices of the pure materials range from 9 % to 32 % for AS and 27 % to 45 % for nigrosin. For mixtures of nigrosin and AS, deviations were all > 100 % and not always able to capture the correct direction of the forcing; i.e., positive versus negative.