scholarly journals Minimizing aerosol effects on the OMI tropospheric NO<sub>2</sub> retrieval – An improved use of the 477 nm O<sub>2</sub>-O<sub>2</sub> band and an estimation of the aerosol correction uncertainty

2018 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
Pieternel F. Levelt
Keyword(s):  
Air Quality ◽  
Spectral Band ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aerosol Model ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Aerosol Parameters

Abstract. Global mapping of satellite tropospheric NO2 vertical column density (VCD), a key gas in air quality monitoring, requires accurate retrievals over complex urban and industrialized areas. The high abundance of aerosol particles in regions dominated by anthropogenic fossil fuel combustion, mega-cities and biomass burning affects the space-borne spectral measurement. Minimizing the tropospheric NO2 VCD biases under such conditions are one of the main challenges for the retrieval from air quality satellite instruments. In this study, reference Ozone Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free scenes, by applying new aerosol correction parameters retrieved from the 477 nm O2-O2 band, over east China and South America for 2 years (2006–2007). These new parameters are based on two different and separate algorithms developed during the last two years in view of an improved use of the 477 nm O2-O2 band: (1) the updated OMCLDO2 algorithm which derives improved effective cloud parameters, (2) the aerosol neural network (NN) giving explicit aerosol parameters by assuming a more physical aerosol model. The OMI aerosol NN is a step ahead to OMCLDO2 by retrieving primarily an explicit aerosol layer height (ALH), and secondly an aerosol optical thickness τ for cloud-free observations. Overall, it was found that all the considered aerosol correction parameters reduce the biases identified in DOMINO-v2 over scenes in China with high aerosol abundance and scattering particles: e.g. from [−20 : −40] % to [0 : 20] % in summertime. The use of the retrieved OMI aerosol parameters leads in general to a more explicit aerosol correction and higher tropospheric NO2 VCD values, in the range of [0 : 40] %, than from the implicit correction with the updated OMCLDO2. This number overall represents an estimation of the aerosol correction strategy uncertainty nowadays for tropospheric NO2 VCD retrieval from space-borne visible measurements. The explicit aerosol correction theoretically includes more realistic aerosol multiple scattering and absorption effects, especially over scenes dominated by strongly absorbing particles, where the correction based on OMCLDO2 seems to remain insufficient. However, the use of ALH and τ from the OMI NN aerosol algorithm is not a straightforward operation and future studies are required to identify the optimal methodology. Several elements to be considered are recommended in this paper. Overall, we demonstrate the possibility to apply a more explicit aerosol correction by considering aerosol parameters directly derived from the 477 nm O2-O2 spectral band, measured by the same satellite instrument. Such an approach can, in theory, easily be transposed to the new-generation of space-borne instruments (e.g. TROPOMI on-board Sentinel-5 Precursor), enabling a fast reprocessing of tropospheric NO2 data over cloud-free scenes (cloudy pixels need to be filtered out), as well as for other trace gas retrievals (e.g. SO2, HCHO).

scholarly journals Minimizing aerosol effects on the OMI tropospheric NO<sub>2</sub> retrieval – An improved use of the 477 nm O<sub>2</sub> − O<sub>2</sub> band and an estimation of the aerosol correction uncertainty

2019 ◽  
Vol 12 (1) ◽  
pp. 491-516 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
Pieternel F. Levelt
Keyword(s):  
Air Quality ◽  
Eastern China ◽  
Spectral Band ◽  
Aerosol Layer ◽  
Atmospheric Conditions ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aerosol Model ◽  
Tropospheric No2 ◽  
Aerosol Parameters

Abstract. Global mapping of satellite tropospheric NO2 vertical column density (VCD), a key gas in air quality monitoring, requires accurate retrievals over complex urban and industrialized areas and under any atmospheric conditions. The high abundance of aerosol particles in regions dominated by anthropogenic fossil fuel combustion, e.g. megacities, and/or biomass-burning episodes, affects the space-borne spectral measurement. Minimizing the tropospheric NO2 VCD biases caused by aerosol scattering and absorption effects is one of the main retrieval challenges from air quality satellite instruments. In this study, the reference Ozone Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free scenes, by applying new aerosol correction parameters retrieved from the 477 nm O2−O2 band, over eastern China and South America for 2 years (2006–2007). These new parameters are based on two different and separate algorithms developed during the last 2 years in view of an improved use of the OMI 477 nm O2−O2 band: the updated OMCLDO2 algorithm, which derives improved effective cloud parameters, the aerosol neural network (NN), which retrieves explicit aerosol parameters by assuming a more physical aerosol model. The OMI aerosol NN is a step ahead of OMCLDO2 because it primarily estimates an explicit aerosol layer height (ALH), and secondly an aerosol optical thickness τ for cloud-free observations. Overall, it was found that all the considered aerosol correction parameters reduce the biases identified in DOMINO-v2 over scenes in China with high aerosol abundance dominated by fine scattering and weakly absorbing particles, e.g. from [-20%:-40%] to [0 %:20 %] in summertime. The use of the retrieved OMI aerosol parameters leads in general to a more explicit aerosol correction and higher tropospheric NO2 VCD values, in the range of [0 %:40 %], than from the implicit correction with the updated OMCLDO2. This number overall represents an estimation of the aerosol correction strategy uncertainty nowadays for tropospheric NO2 VCD retrieval from space-borne visible measurements. The explicit aerosol correction theoretically includes a more realistic consideration of aerosol multiple scattering and absorption effects, especially over scenes dominated by strongly absorbing particles, where the correction based on OMCLDO2 seems to remain insufficient. However, the use of ALH and τ from the OMI NN aerosol algorithm is not a straightforward operation and future studies are required to identify the optimal methodology. For that purpose, several elements are recommended in this paper. Overall, we demonstrate the possibility of applying a more explicit aerosol correction by considering aerosol parameters directly derived from the 477 nm O2−O2 spectral band, measured by the same satellite instrument. Such an approach can, in theory, easily be transposed to the new-generation of space-borne instruments (e.g. TROPOMI on board Sentinel-5 Precursor), enabling a fast reprocessing of tropospheric NO2 data over cloud-free scenes (cloudy pixels need to be filtered out), as well as for other trace gas retrievals (e.g. SO2, HCHO).

scholarly journals Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China

2018 ◽  
Vol 10 (11) ◽  
pp. 1789 ◽  
Author(s):  
Hugo Mak ◽  
Joshua Laughner ◽  
Jimmy Fung ◽  
Qindan Zhu ◽  
Ronald Cohen
Keyword(s):  
Air Quality ◽  
Column Density ◽  
Southern China ◽  
A Priori ◽  
Wrf Model ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Spatial Gradients ◽  
Tropospheric No2 ◽  
R Value

Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR-HK) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. There are two major objectives and goals: (1) developing new BEHR-HK v3.0C product for retrieving tropospheric NO2 vertical column density (TVCD) within part of southern China, for four months of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI); and (2) evaluating BEHR-HK v3.0C retrieval result through validation, by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. Results show that all BEHR-HK retrieval algorithms (with R-value of 0.9839 for v3.0C) are of higher consistency with MAX-DOAS measurements than OMI-NASA retrieval (with R-value of 0.7644). This opens new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.

scholarly journals The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 444 ◽  
Author(s):  
Chunjiao Wang ◽  
Ting Wang ◽  
Pucai Wang
Keyword(s):  
Eastern China ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
The North ◽  
Annual Range ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Long Term Trends ◽  
Increasing Trends ◽  
No2 Pollution

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

scholarly journals Novel application of satellite and in-situ measurements to map surface-level NO<sub>2</sub> in the Great Lakes region

2011 ◽  
Vol 11 (22) ◽  
pp. 11761-11775 ◽  
Author(s):  
C. J. Lee ◽  
J. R. Brook ◽  
G. J. Evans ◽  
R. V. Martin ◽  
C. Mihele
Keyword(s):  
Qualitative Data ◽  
Great Lakes Region ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Surface Level ◽  
Suburban Areas ◽  
The Us ◽  
Tropospheric No2 ◽  
Vertical Column Density

Abstract. Ozone Monitoring Instrument (OMI) tropospheric NO2 vertical column density data were used in conjunction with in-situ NO2 concentrations collected by permanently installed monitoring stations to infer 24 h surface-level NO2 concentrations at 0.1° (~11 km) resolution. The region examined included rural and suburban areas, and the highly industrialised area of Windsor, Ontario, which is situated directly across the US-Canada border from Detroit, MI. Photolytic NO2 monitors were collocated with standard NO2 monitors to provide qualitative data regarding NOz interference during the campaign. The accuracy of the OMI-inferred concentrations was tested using two-week integrative NO2 measurements collected with passive monitors at 18 locations, approximating a 15 km grid across the region, for 7 consecutive two-week periods. When compared with these passive results, satellite-inferred concentrations showed an 18% positive bias. The correlation of the passive monitor and OMI-inferred concentrations (R=0.69, n=115) was stronger than that for the passive monitor concentrations and OMI column densities (R=0.52), indicating that using a sparse network of monitoring sites to estimate concentrations improves the direct utility of the OMI observations. OMI-inferred concentrations were then calculated for four years to show an overall declining trend in surface NO2 concentrations in the region. Additionally, by separating OMI-inferred surface concentrations by wind direction, clear patterns in emissions and affected down-wind regions, in particular around the US-Canada border, were revealed.

scholarly journals Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF), Part I: Case Study of Southern China

2018 ◽  
Author(s):  
Hugo Wai Leung Mak ◽  
Joshua L. Laughner ◽  
Jimmy Chi Hung Fung ◽  
Qindan Zhu ◽  
Ronald C. Cohen
Keyword(s):  
Air Quality ◽  
Column Density ◽  
Southern China ◽  
A Priori ◽  
Wrf Model ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Global Missions ◽  
Spatial Gradients ◽  
Tropospheric No2

Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR v3.0A, v3.0B and v3.0C) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. We retrieved tropospheric NO2 vertical column density (TVCD) within part of southern China, for four seasons of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI). Retrieval results are validated by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. BEHR retrieval algorithms are more consistent with MAX-DOAS measurements than OMI-NASA retrieval, opening new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.

scholarly journals FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals

2008 ◽  
Vol 8 (21) ◽  
pp. 6565-6576 ◽  
Author(s):  
P. Wang ◽  
P. Stammes ◽  
R. van der A ◽  
G. Pinardi ◽  
M. van Roozendael
Keyword(s):  
Rayleigh Scattering ◽  
Cloud Fraction ◽  
Retrieval Algorithm ◽  
Minor Effect ◽  
Vertical Column ◽  
Cloud Parameters ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
The Difference ◽  
A Minor

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column density (VCD) retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO2VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014molec cm−2.

scholarly journals Novel application of satellite and in-situ measurements to map surface-level NO<sub>2</sub> in the Great Lakes region

2011 ◽  
Vol 11 (6) ◽  
pp. 17245-17287
Author(s):  
C. J. Lee ◽  
J. R. Brook ◽  
G. J. Evans ◽  
R. V. Martin ◽  
C. Mihele
Keyword(s):  
Qualitative Data ◽  
Great Lakes Region ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Surface Level ◽  
Suburban Areas ◽  
The Us ◽  
Tropospheric No2 ◽  
Vertical Column Density

Abstract. Ozone Monitoring Instrument (OMI) tropospheric NO2 vertical column density data were used in conjunction with in-situ NO2 concentrations collected by permanently installed monitoring stations to infer 24 h surface-level NO2 concentrations at 0.1° (~ 11 km) resolution. The region examined included rural and suburban areas, and the highly industrialised area of Windsor, Ontario, which is situated directly across the US-Canada border from Detroit, MI. Photolytic NO2 monitors were collocated with standard NO2 monitors to provide qualitative data regarding NOz interference during the campaign. To test the accuracy of the OMI-inferred concentrations, two-week integrative NO2 measurements were collected using passive monitors at 18 locations, approximating a 15 km grid across the region, for 7 consecutive two-week periods. When compared with these passive results, satellite-inferred concentrations showed an 18 % positive bias. The correlation of the passive monitor and OMI-inferred concentrations (R = 0.69, n = 115) was stronger than that for the passive monitor concentrations and OMI column densities (R = 0.52), indicating that using a sparse network of monitoring sites to estimate concentrations improves the direct utility of the OMI observations. OMI-inferred concentrations were then calculated for four years to show an overall declining trend in surface NO2 concentrations in the region. Additionally, by separating OMI-inferred surface concentrations by wind direction, clear patterns in emissions and affected down-wind regions, in particular around the US-Canada border, were revealed.

scholarly journals A high spatial resolution retrieval of NO<sub>2</sub> column densities from OMI: method and evaluation

2011 ◽  
Vol 11 (4) ◽  
pp. 12411-12440 ◽  
Author(s):  
A. R. Russell ◽  
A. E. Perring ◽  
L. C. Valin ◽  
E. Bucsela ◽  
E. C. Browne ◽  
...  
Keyword(s):  
Boundary Layer ◽  
The Arctic ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aircraft Observations ◽  
Vertical Column Density ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Better Than

Abstract. We present a new retrieval of tropospheric NO2 vertical column density from the Ozone Monitoring Instrument (OMI) based on high spatial and temporal resolution terrain and profile inputs. We find non-negligible impacts on the retrieved NO2 column for terrain pressure (±20%), albedo (±40%), and NO2 vertical profile (−75%–+10%). We compare our NO2 product, the Berkeley High-Resolution (BEHR) product, with operational retrievals and find that the operational retrievals are biased high (30%) over remote areas and biased low (8%) over urban regions. We validate the operational and BEHR products using boundary layer aircraft observations from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-CA) field campaign which occurred in June 2008 in California. Results indicate that columns derived using our boundary layer extrapolation method show good agreement with satellite observations (R2 = 0.65–0.83; N = 68) and provide a more robust validation of satellite-observed NO2 column than those determined using full vertical spirals (R2 = 0.26; N = 5) as in previous work. Agreement between aircraft observations and the BEHR product (R2 = 0.83) is better than agreement with the operational products (R2 = 0.65–0.72). We also show that agreement between satellite and aircraft observations for all products can be further improved (e.g. BEHR: R2 = 0.91) using cloud information from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument instead of the OMI cloud product. These results indicate that much of the variance in the operational products can be attributed to coarse resolution terrain and profile parameters.

scholarly journals Anthropogenic and volcanic point source SO<sub>2</sub> emissions derived from TROPOMI onboard Sentinel 5 Precursor: first results

2020 ◽  
Author(s):  
Vitali Fioletov ◽  
Chris A. McLinden ◽  
Debora Griffin ◽  
Nicolas Theys ◽  
Diego G. Loyola ◽  
...  
Keyword(s):  
Absolute Magnitude ◽  
Point Sources ◽  
Ozone Monitoring Instrument ◽  
So2 Emissions ◽  
Large Area ◽  
Vertical Column ◽  
Very High Spatial Resolution ◽  
First Results ◽  
Vertical Column Density ◽  
Very High

Abstract. The paper introduces the first TROPOMI-based sulfur dioxide (SO2) emissions estimates for point sources. A total of about 500 continuously emitting point sources releasing from about 10 kT y−1 to more than 2000 kT y−1 of SO2 per year, previously identified from Ozone Monitoring Instrument (OMI) observations, were analysed using TROPOMI measurements for one full year, from April 2018 to March 2019. The annual emissions from these sources were estimated and compared to similar estimates from OMI and Ozone Mapping Profiling Suite (OMPS) measurements. Note that emissions from many of these 500 sources declined significantly since 2005 making their quantification more challenging. We were able to identify 278 sources where annual emissions are significant and can be reliably estimated from TROPOMI. The standard deviations of TROPOMI vertical column density data, about 1 Dobson Unit (DU, where 1 DU = 2.69 × 1016 molecules/cm2) over tropics and 1.5 DU over high latitudes, are larger than those of OMI (0.6–1 DU) and OMPS (0.3–0.4 DU). Due to its very high spatial resolution, TROPOMI produces 12–20 times more observations over a certain area than OMI and 96 times more than OMPS. Despite higher uncertainties of individual TROPOMI observations, TROPOMI data averaged over a large area have roughly two-three times lower uncertainties compared to OMI and OMPS data. Similarly, TROPOMI annual emissions can be estimated with uncertainties that are 1.5–2 times lower than the uncertainties of annual emissions estimates from OMI. While there are area biases in TROPOMI data over some regions that have to be removed for emission calculations, the absolute magnitude of these are modest, typically within ±0.25 DU, it can be comparable to SO2 values over large sources.

scholarly journals Model Selection in Atmospheric Remote Sensing with Application to Aerosol Retrieval from DSCOVR/EPIC. Part 2: Numerical Analysis

2020 ◽  
Vol 12 (21) ◽  
pp. 3656
Author(s):  
Sruthy Sasi ◽  
Vijay Natraj ◽  
Víctor Molina García ◽  
Dmitry S. Efremenko ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Model Selection ◽  
Aerosol Layer ◽  
Angular Variation ◽  
Aerosol Model ◽  
A Value ◽  
Aerosol Retrieval ◽  
Atmospheric Remote Sensing ◽  
The One ◽  
Aerosol Parameters

An algorithm for retrieving aerosol parameters by taking into account the uncertainty in aerosol model selection is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements from the EPIC sensor onboard the Deep Space Climate Observatory. The synthetic measurements are generated using aerosol models derived from AERONET measurements at different sites, while other commonly used aerosol models, such as OPAC, GOCART, OMI, and MODIS databases are used in the retrieval. The numerical analysis is focused on the estimation of retrieval errors when the true aerosol model is unknown. We found that the best aerosol model is the one with a value of the asymmetry parameter and an angular variation of the phase function around the viewing direction that is close to the values corresponding to the reference aerosol model.

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