The Analysis of Aerosol Distribution Using Modis AOD (Aerosol Optical Depth) With SARA (Simplified High Resolution Modis Retrieval Algorithm) for Air Quality Monitoring On 2017 (Study Case: Surabaya City, Indonesia)

Abstract. Airborne sunphotometer measurements acquired by the NASA Ames Airborne Tracking Sunphotometer (AATS-14) aboard the NASA P-3 research aircraft are used to evaluate dark-target over-land retrievals of extinction aerosol optical depth (AOD) from spatially and temporally near-coincident measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the summer 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. The new MODIS Collection 6 aerosol data set includes retrievals of AOD at both 10 km × 10 km and 3 km × 3 km (at nadir) resolution. In this paper we compare MODIS and AATS AOD at 553 nm in 58 10 km and 134 3 km retrieval grid cells. These AOD values were derived from data collected over Canada on four days during short time segments of five (four Aqua and one Terra) satellite overpasses of the P-3 during low-altitude P-3 flight tracks. Three of the five MODIS–AATS coincidence events were dominated by smoke: one included a P-3 transect of a well-defined smoke plume in clear sky, but two were confounded by the presence of scattered clouds above smoke. The clouds limited the number of MODIS retrievals available for comparison, and led to MODIS AOD retrievals that underestimated the corresponding AATS values. This happened because the MODIS aerosol cloud mask selectively removed 0.5 km pixels containing smoke and clouds before the aerosol retrieval. The other two coincidences (one Terra and one Aqua) occurred during one P-3 flight on the same day and in the same general area, in an atmosphere characterized by a relatively low AOD (< 0.3), spatially homogeneous regional haze from smoke outflow with no distinguishable plume. For the ensemble data set for MODIS AOD retrievals with the highest-quality flag, MODIS AOD agrees with AATS AOD within the expected MODIS over-land AOD uncertainty in 60% of the retrieval grid cells at 10 km resolution and 69% at 3 km resolution. These values improve to 65 % and 74%, respectively, when the cloud-affected case with the strongest plume is excluded. We find that the standard MODIS dark-target over-land retrieval algorithm fails to retrieve AOD for thick smoke, not only in cloud-contaminated regions but also in clear sky. We attribute this to deselection, by the cloud and/or bright surface masks, of 0.5 km resolution pixels that contain smoke.

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Improving GOES Advanced Baseline Imager (ABI) Aerosol Optical Depth (AOD) Retrievals using an Empirical Bias Correction Algorithm

10.5194/amt-2020-115 ◽

2020 ◽

Author(s):

Hai Zhang ◽

Shobha Kondragunta ◽

Istvan Laszlo ◽

Mi Zhou

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Bias Correction ◽

Land Surface ◽

Infrared Imaging ◽

Retrieval Algorithm ◽

Correction Algorithm ◽

Time Step ◽

Modis Aod ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) series enables retrieval of aerosol optical depth (AOD) from geostationary satellites using a multi-band algorithm similar to those of polar-orbiting satellites’ sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Therefore, ABI AOD is expected to have accuracy and precision comparable to MODIS AOD and VIIRS AOD. However, this work demonstrates that the current version of GOES-16 (GOES-East) ABI AOD has diurnally varying biases due to errors in the land surface reflectance relationship between the bands used in the ABI AOD retrieval algorithm, which vary with respect to the Sun-satellite geometry. To reduce these biases, an empirical bias correction algorithm has been developed based on the lowest observed ABI AOD of an adjacent 30-day period and the background AOD at each time step and at each pixel. The bias correction algorithm improves the performance of ABI AOD compared to AErosol RObotic NETwork (AERONET) AOD, especially for the high and medium (top 2) quality ABI AOD. AOD data for the period August 6 to December 31, 2018 are used to validate the bias correction algorithm. For the top 2 qualities ABI AOD, after bias correction, the correlation between ABI AOD and AERONET AOD improves from 0.87 to 0.91, the mean bias improves from 0.04 to 0.00, and root mean square error (RMSE) improves from 0.09 to 0.05. These results for the bias corrected top 2 qualities ABI AOD are comparable to those of the uncorrected high-quality ABI AOD. Thus, by using the top 2 qualities of ABI AOD in conjunction with the bias correction algorithm, the area coverage of ABI AOD is substantially increased without loss of data accuracy.

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Investigation of air quality over the largest city in central China using high resolution satellite derived aerosol optical depth data

Atmospheric Pollution Research ◽

10.1016/j.apr.2017.12.011 ◽

2018 ◽

Vol 9 (3) ◽

pp. 584-593 ◽

Cited By ~ 7

Author(s):

Kun Sun ◽

Xiaoling Chen ◽

Jialin Wang ◽

Tianhao Zhang ◽

Zhongmin Zhu

Keyword(s):

Air Quality ◽

High Resolution ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Central China ◽

Depth Data ◽

Aerosol Optical Depth Data

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MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

10.20944/preprints201705.0157.v1 ◽

2017 ◽

Author(s):

Yi WANG ◽

Jun Wang ◽

Robert C Levy ◽

Xiaoguang Xu ◽

Jeffrey S Reid

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Coastal Water ◽

Visible Spectrum ◽

Single Scattering ◽

Retrieval Algorithm ◽

Modis Aod ◽

Moderate Resolution ◽

Moderate Resolution Imaging Spectroradiometer ◽

Large Water

We present a new approach to retrieve Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently don’t conduct any AOD retrieval in the regions with large water-leaving radiances in the visible spectrum. Over the global coastal water regions in all cloud-free conditions, this unavailability of AOD retrievals due to the inherent limitation in existing DT algorithm is ~20%. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 μm is negligible regardless of water turbidity. This refinement, with the assumption that the aerosol single scattering properties over coastal turbid water are similar to that over the adjacent open-ocean pixels, yields ~18% more of MODIS-AERONET collocated pairs for six AEROENT stations in the coastal water regions. Furthermore, comparison with these AERONET observations show that the new AOD retrievals are in either equivalent or better accuracy than those retrieved by the MODIS operational algorithm (over coastal land and non-turbid coastal water). Combining the new retrievals with the existing MODIS operational retrievals not only yield an overall improvement of AOD over those coastal water regions, but also successfully extend the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides, and thereby, aerosol impacts on regional air quality and climate are expected to be significant.

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Evaluation of MODIS-Retrieved Aerosol Optical Depth in Alaska: Implications for Surface Air Quality Applications

10.20944/preprints201805.0123.v1 ◽

2018 ◽

Author(s):

Alyson McPhetres ◽

Srijan Aggarwal

Keyword(s):

Air Quality ◽

Aerosol Optical Depth ◽

Optical Depth ◽

National Parks ◽

Urban Areas ◽

Ground Level ◽

Modis Data ◽

Particulate Pollution ◽

Modis Aod ◽

Pollution Concentrations

The air quality monitoring network in Alaska is currently limited to ground-based observations in urban areas and national parks leaving a large proportion of the state unmonitored. The use of MODIS aerosol optical depth (AOD) to estimate ground-level particulate pollution concentrations has been successfully demonstrated around the world, and could potentially be used in Alaska. In this work, MODIS AOD measurements at 550 nm were validated against AOD derived from AERONET ground-based sunphotometers in Barrow and Bonanza Creek to determine if MODIS AOD from the Terra and Aqua satellites could be used to estimate ground-level particulate pollution concentrations. The MODIS AOD was obtained from MODIS collection 6 using the dark target Land and Ocean algorithms from 2000 to 2014. MODIS data could only be obtained between the months of April and October; therefore, it could only be validated for those months. Individual and combined Terra and Aqua MODIS data were considered. The results showed that MODIS collection 6 products at 10 km resolution for Terra and Aqua combined are not valid over land but are valid over the ocean. On the other hand, the individual Terra and Aqua MODIS collection 6 AOD products at 10 km resolution are valid over land individually but not when combined. Results also suggest the MODIS collection 6 AOD products at 3 km resolution are valid over land and ocean and perform better over land than the 10-km product. These findings indicate that MODIS collection 6 AOD products can be used quantitatively in air quality applications in Alaska during the summer months.

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Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas

Remote Sensing ◽

10.3390/rs13204140 ◽

2021 ◽

Vol 13 (20) ◽

pp. 4140

Author(s):

Hao Lin ◽

Siwei Li ◽

Jia Xing ◽

Jie Yang ◽

Qingxin Wang ◽

...

Keyword(s):

High Resolution ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Spatial Resolution ◽

Urban Areas ◽

Retrieval Algorithm ◽

Landsat 8 ◽

Beijing City ◽

Spatial Coverage ◽

Sentinel 2

Recent studies have shown that the high-resolution satellite Landsat-8 has the capability to retrieve aerosol optical depth (AOD) over urban areas at a 30 m spatial resolution. However, its long revisiting time and narrow swath limit the coverage and frequency of the high resolution AOD observations. With the increasing number of Earth observation satellites launched in recent years, combining the observations of multiple satellites can provide higher temporal-spatial coverage. In this study, a fusing retrieval algorithm is developed to retrieve high-resolution (30 m) aerosols over urban areas from Landsat-8 and Sentinel-2 A/B satellite measurements. The new fusing algorithm was tested and evaluated over Beijing city and its surrounding area in China. The validation results show that the retrieved AODs show a high level of agreement with the local urban ground-based Aerosol Robotic Network (AERONET) AOD measurements, with an overall high coefficient of determination (R2) of 0.905 and small root mean square error (RMSE) of 0.119. Compared with the operational AOD products processed by the Landsat-8 Surface Reflectance Code (LaSRC-AOD), Sentinel Radiative Transfer Atmospheric Correction code (SEN2COR-AOD), and MODIS Collection 6 AOD (MOD04) products, the AOD retrieved from the new fusing algorithm based on the Landsat-8 and Sentinel-2 A/B observations exhibits an overall higher accuracy and better performance in spatial continuity over the complex urban area. Moreover, the temporal resolution of the high spatial resolution AOD observations was greatly improved (from 16/10/10 days to about two to four days over globe land in theory under cloud-free conditions) and the daily spatial coverage was increased by two to three times compared to the coverage gained using a single sensor.

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An empirical relationship between PM2.5 and aerosol optical depth from MODIS satellite images for spatial simulation over Ho Chi Minh city

Vietnam Journal of Science Technology and Engineering ◽

10.31276/vjste.63(4).72-78 ◽

2021 ◽

Vol 63 (4) ◽

pp. 72-78

Author(s):

Vo Quoc Bao ◽

◽

Tran Thi Van ◽

◽

...

Keyword(s):

Air Quality ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Fine Particles ◽

Empirical Relationship ◽

Green Light ◽

Monitoring Network ◽

Ambient Air ◽

Ho Chi Minh City ◽

Modis Aod

Air quality in megacities has been a pressing concern of environmental managers and scientists for decades. Indeed, particulate matter (PM), especially PM2.5, is considered a dangerousparticle that is harmful to human health. The current sparse monitoring network in Ho Chi Minh city (HCMC) does not accurately reflect the spatial distribution of fine particles in ambient air. Therefore, this research examines the relationship between ground-based station data and aerosol optical depth (AOD) imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra/Aqua satellite to establish a PM2.5 distribution map of HCMC. PM2.5 concentration values monitored from two ground stations were collocated by time and space with Terra/MODIS AOD data from the period of 2016-2020. Pairs of values were checked for correlation and then fit to several regression functions. The most suitable function was chosen to simulate the quantified PM2.5distributions in the study area. A high correlation between PM2.5 concentrations and AOD at the wavelength of green light (R2=0.810) was found with a linear regression model. The results showed that the highest concentration of PM2.5 was in February, and the mean value was higher than QCVN 05:2013 (32.5 μg/m3compared with 25 μg/m3, annual mean). These results support the need for essential air quality monitoring in HCMC.

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A Study of Air Quality in the Southeastern Hampton–Norfolk–Virginia Beach Region with Airborne Lidar Measurements and MODIS Aerosol Optical Depth Retrievals

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2119.1 ◽

2010 ◽

Vol 49 (1) ◽

pp. 3-19 ◽

Cited By ~ 5

Author(s):

Jasper Lewis ◽

Russell De Young ◽

D. Allen Chu

Keyword(s):

Air Quality ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Airborne Lidar ◽

Eastern United States ◽

Modis Aod ◽

Virginia Beach ◽

Lidar Measurements ◽

Langley Research Center ◽

Linear Regressions

Abstract A study of air quality was performed using a compact, aircraft aerosol lidar designed in the Science Directorate at NASA Langley Research Center and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals. Five flights of lidar measurements conducted in the Hampton–Norfolk–Virginia Beach, Virginia, region showed complex regional aerosol distributions. Comparisons with MODIS AOD at 10 km × 10 km and 5 km × 5 km resolutions show good agreement, with correlation R2 values of 0.82 and 0.88, respectively. Linear regressions of particulate matter with a diameter of less than 2.5 μm (PM2.5) and AOD within the ranges of 5–40 μg m−3 and 0.05–0.7, respectively, result in R2 values of ∼0.64 and ∼0.82 for MODIS and the Compact Aerosol Lidar, respectively. The linear regressions reflect approximately 51 μg m−3 to 1 AOD. These relationships are in agreement with previous findings for air pollution aerosols in the eastern United States and in northern Italy. However, large vertical variation is seen case by case, with planetary boundary layer heights ranging between 0.7 and 2 km and uncertainties ranging between 0.1 and 0.4 km. The results of the case studies suggest that AOD can be used as an indicator of surface measurements of PM2.5 but with larger uncertainties associated with small aerosol loading (AOD < 0.3).

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