Synchronous detection of multiple optical characteristics of atmospheric aerosol by coupled photoacoustic cavity

Due to the influence of sampling loss, cavity difference and detecting source, the multi-optical parameter measurement of atmospheric aerosol cannot be detected simultaneously under the same reference. In order to solve this problem, a new method for simultaneous detection of aerosol optical parameters by coupling cavity ring-down spectroscopy with photoacoustic spectroscopy was proposed. Firstly, the coupled photoacoustic cavity is formed by the organic fusion of the photoacoustic cavity and the ring-down cavity. Secondly, the integrated design of the coupling spectroscopy system is carried out. Finally, the extinction coefficient and absorption coefficient of aerosol are measured simultaneously by the system, and then the aerosol scattering coefficient and single albedo are calculated indirectly. The accuracy of the system is verified by comparing with the data from the environmental quality monitoring station, which provides a new idea for the detection of multi-optical characteristics of atmospheric aerosol.

Atmospheric Correction of Airborne Hyperspectral CASI Data Using Polymer, 6S and FLAASH

Airborne hyperspectral data play an important role in remote sensing of coastal waters. However, before their application, atmospheric correction is required to remove or reduce the atmospheric effects caused by molecular and aerosol scattering and absorption. In this study, we first processed airborne hyperspectral CASI-1500 data acquired on 4 May 2019 over the Uljin coast of Korea with Polymer and then compared the performance with the other two widely used atmospheric correction approaches, i.e., 6S and FLAASH, to determine the most appropriate correction technique for CASI-1500 data in coastal waters. Our results show the superiority of Polymer over 6S and FLAASH in deriving the Rrs spectral shape and magnitude. The performance of Polymer was further evaluated by comparing CASI-1500 Rrs data with those obtained from the MODIS-Aqua sensor on 3 May 2019 and processed using Polymer. The spectral shapes of the derived Rrs from CASI-1500 and MODIS-Aqua matched well, but the magnitude of CASI-1500 Rrs was approximately 0.8 times lower than MODIS Rrs. The possible reasons for this difference were time difference (1 day) between CASI-1500 and MODIS data, higher land adjacency effect for MODIS-Aqua than for CASI-1500, and possible errors in MODIS Rrs from Polymer.

Why was the sky red in Jambi during the forest fire?

Extreme biomass burning occurred in Jambi, Indonesia, in 2019 and coincided exacerbated with El Nino. Peak burning season was in September, with a total hotspot of 7034. Red sky has been reported on September 21 during the day. Sun photometer measurements in Jambi as one of the Aerosol Robotic Network (AERONET) stations in Indonesia from 1 to September 26, 2019, were used to investigate the red sky phenomenon. Assessment of aerosol optical properties and spectral variation analysis is conducted. The study reveals that the red sky occurred due to, firstly, very high aerosol loading with fine size particles were present. The aerosol optical depth (AOD) was 0.34 at 500 nm on a non-hazy day (early September) and increased sharply to 5.74 during a hazy day. A high level of fine-mode particle was indicated with Angstrom Exponent>1. Secondly, during September 23, only longer wavelengths of AOD were measured at 675, 870, 1020, and 1640 nm, while AOD in shorter wavelengths cannot be retrieved. Highest AOD on September 23 was 6.19 at 675 nm, which is associated with the red sky in the previous day. Thirdly, SSA was near 1, indicating purely aerosol scattering due to coagulated fine-mode particles due to high humidity.

GFIT3: a full physics retrieval algorithm for remote sensing of greenhouse gases in the presence of aerosols

Remote sensing of greenhouse gases (GHGs) in cities, where high GHG emissions are typically associated with heavy aerosol loading, is challenging due to retrieval uncertainties caused by the imperfect characterization of scattering by aerosols. We investigate this problem by developing GFIT3, a full physics algorithm to retrieve GHGs (CO2 and CH4) by accounting for aerosol scattering effects in polluted urban atmospheres. In particular, the algorithm includes coarse- (including sea salt and dust) and fine- (including organic carbon, black carbon, and sulfate) mode aerosols in the radiative transfer model. The performance of GFIT3 is assessed using high-spectral-resolution observations over the Los Angeles (LA) megacity made by the California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS-FTS). CLARS-FTS is located on Mt. Wilson, California, at 1.67 km a.s.l. overlooking the LA Basin, and it makes observations of reflected sunlight in the near-infrared spectral range. The first set of evaluations are performed by conducting retrieval experiments using synthetic spectra. We find that errors in the retrievals of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) due to uncertainties in the aerosol optical properties and atmospheric a priori profiles are less than 1 % on average. This indicates that atmospheric scattering does not induce a large bias in the retrievals when the aerosols are properly characterized. The methodology is then further evaluated by comparing GHG retrievals using GFIT3 with those obtained from the CLARS-GFIT algorithm (used for currently operational CLARS retrievals) that does not account for aerosol scattering. We find a significant correlation between retrieval bias and aerosol optical depth (AOD). A comparison of GFIT3 AOD retrievals with collocated ground-based observations from AErosol RObotic NETwork (AERONET) shows that the developed algorithm produces very accurate results, with biases in AOD estimates of about 0.02. Finally, we assess the uncertainty in the widely used tracer–tracer ratio method to obtain CH4 emissions based on CO2 emissions and find that using the CH4/CO2 ratio effectively cancels out biases due to aerosol scattering. Overall, this study of applying GFIT3 to CLARS-FTS observations improves our understanding of the impact of aerosol scattering on the remote sensing of GHGs in polluted urban atmospheric environments. GHG retrievals from CLARS-FTS are potentially complementary to existing ground-based and spaceborne observations to monitor anthropogenic GHG fluxes in megacities.

New correction method for the scattering coefficient measurements of a three-wavelength nephelometer

The aerosol scattering coefficient is an essential parameter for estimating aerosol direct radiative forcing and can be measured by nephelometers. Nephelometers are problematic due to small errors of nonideal Lambetian light source and angle truncation. Hence, the observed raw scattering coefficient data need to be corrected. In this study, based on the random forest machine learning model and taking Aurora 3000 as an example, we have proposed a new method to correct the scattering coefficient measurements of a three-wavelength nephelometer under different relative humidity conditions. The result shows that the empirical corrected values match Mie-calculation values very well at all three wavelengths and under all of the measured relative humidity conditions, with more than 85 % of the corrected values having less than 2 % error. The correction method obtains a scattering coefficient with high accuracy and there is no need for additional observation data.

THE PROGRAM FOR CALCULATING THE ASYMMETRY COEFFICIENTS OF AEROSOL SCATTERING IN THE RED AND NEAR IR REGIONS OF THE SPECTRUM

В настоящей работе представлено программное обеспечение, реализующее методику определения аэрозольного коэффициента асимметрии из результатов наблюдений интегрального коэффициента рассеянных световых потоков, оптической толщи и альбедо местности интерполяционным путем без применения аппарата решения обратных задач. В качестве исходных используются данные измерений углового хода яркости дневного безоблачного неба в солнечном альмукантарате при разной спектральной прозрачности атмосферы и альбедо подстилающей поверхности. Наблюдения выполняются в длинах волн 675, 870 и 1020 нм при зенитных углах Солнца 65÷750, при этом яркость может измеряться в любых единицах, включая непосредственно отсчеты фотометра. При обработке результатов мониторинговых наблюдений даже на одной длине волны требуется производить значительное количество однотипных вычислений, что делает задачу автоматизации расчетов атмосферных параметров, в частности, коэффициентов асимметрии, безусловно актуальной. Изложены требования к входным данным, представлена блок-схема алгоритма и описание интерфейса пользователя программы. Результаты расчетов выводятся в табличной форме. Программаобеспечивает приемлемую погрешность определения коэффициентов асимметрии и может быть использована в геофизике и климатологии при проведении расчетов поступления рассеянной солнечной радиации на земную поверхность с целью последующей оценки размеров частиц. In this paper, software is presented that implements the method for determining the aerosol asymmetry coefficient from the results of observations of the integral coefficient of scattered light fluxes, optical depth and albedo of the terrain by interpolation without using an apparatus for solving inverse problems. The data of measurements of the angular variation of the brightness of the daytime cloudless sky in the solar almucantar with different spectral transparency of the atmosphere and the albedo of the underlying surface are used as the initial data. Observations are carried out at wavelengths of 675, 870 and 1020 nm at zenith angles of the Sun 65 ÷ 750, while the brightness can be measured in any unit, including directly the readings of the photometer. When processing the results of monitoring observations, even at one wavelength, it is required to perform a significant number of calculations of the same type, which makes the task of automating the calculations of atmospheric parameters, in particular, the asymmetry coefficients, undoubtedly relevant. Requirements for the input data are stated, a block diagram of the algorithm and a description of the user interface of the program are presented. The calculation results are displayed in tabular form. The program provides an acceptable error in determining the asymmetry coefficients and can be used in geophysics and climatology when calculating the arrival of scattered solar radiation on the earth's surface in order to further estimate the particle size.

Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China

The Gridpoint Statistical Interpolation data assimilation (DA) system was developed for the four size bin sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol mechanism in the Weather Research and Forecasting-Chemistry (WRF-Chem) model. The forward and tangent linear operators for the aerosol optical depth (AOD) analysis were derived from WRF-Chem aerosol optical code. We applied three-dimensional variational DA to assimilate the multi-wavelength AOD, ambient aerosol scattering coefficient, and aerosol absorption coefficient, measured by the sun–sky photometer, nephelometer, and aethalometer, respectively. These measurements were undertaken during a dust observation field campaign at Kashi in northwestern China in April 2019. The results showed that the DA analyses decreased the model aerosols' low biases; however, it had some deficiencies. Assimilating the surface particle concentration increased the coarse particles in the dust episodes, but AOD and the coefficients for aerosol scattering and absorption were still lower than those observed. Assimilating aerosol scattering coefficient separately from AOD improved the two optical quantities. However, it caused an overestimation of the particle concentrations at the surface. Assimilating the aerosol absorption coefficient yielded the highest positive bias in the surface particle concentration, aerosol scattering coefficient, and AOD. The positive biases in the DA analysis were caused by the forward operator underestimating aerosol mass scattering and absorption efficiency. As compensation, the DA system increased particle concentrations excessively to fit the observed optical values. The best overall improvements were obtained from the simultaneous assimilation of the surface particle concentration and AOD. The assimilation did not substantially change the aerosol chemical fractions. After DA, the clear-sky aerosol radiative forcing at Kashi was −10.4 W m−2 at the top of the atmosphere, which was 55 % higher than the radiative forcing value before DA.