Assessment of AOD variability over Saudi Arabia using MODIS Deep Blue products

Long-term quantification of springtime aerosols over Saudi Arabia using multi-satellite remotely sensed data

A comprehensive analysis of aerosol characteristics over Saudi Arabia from 2005 to 2022, utilizing high-resolution satellite-based observations and reanalysis datasets, examining the distribution of aerosols and their subtypes across the three dimensions (temporal, spatial, and altitude based) for March, April, and May. This study focuses on the analysis of parameters such as aerosol optical depth (AOD), angstrom exponent (AE), absorption aerosol optical depth (AAOD), and Ultraviolet Aerosol Index (UVAI), revealing significant spatial disparities, with elevated aerosol concentrations in the central and eastern regions and comparatively lower concentrations along the western coastal areas. In this study, the spatial patterns and temporal trends are analyzed through trajectory modeling. The study also investigates the composition of aerosols in various Saudi cities. Aerosols prevailing in a dozen Saudi Arabian cities were systematically categorized into six sub-types, considering their particle size and UV-absorbing properties. Notably, two major aerosol sub-types, absorbing coarse (AC) aerosols (UVAI > 0.25, AE < 0.70) treated as mineral dust and absorbing mixed (AM) aerosols (0.70 < AE < 1.25) along with neutral fine (NF) particles (- 0.5 < UVAI < 0.25, AE > 1.25) treated as urban, predominate across the Kingdom of Saudi Arabia.

Evaluation of MERRA-2 data for aerosols patterns over the Kingdom of Saudi Arabia

Aerosol is one of the major climate-forcing parameters which affect the Kingdom of Saudi Arabia in particular. The most relevant consideration that characterizes the aerosol properties and distribution is the Aerosol Optical Depth (AOD). In this study Modern Era Retrospective Analysis for Research and Applications (MERRA-2) AOD product from the year 1980-2021 is used to investigate aerosols pattern over the Kingdom of Saudi Arabia. The validation of the MERRA-2 AOD product is made by using AOD data retrieved from Aerosol Robotic Network (AERONET) stations located at Solar Village (SV) and at King Abdullah University of Science and Technology (KAUST). Various statistical analyses are performed to test the reliability of MERRA-2 data in the study region. The results of the statistical analysis indicate that MERRA-2 is highly correlated with both AERONET stations data. Thus, annual and seasonal aerosol climatology maps based on 41 years of MERRA-2 data are prepared and analyzed over the study region. The annual and seasonal aerosol climatology analysis of MERRA-2 data shows high density of AOD at southern and eastern regions while the low density emerges over the western and northern regions of the country during the study period. The results of the study are very encouraging, which increases our confidence level to use historical MERRA-2 AOD product to improve the knowledge on aerosols distribution over the region in future.

Identification of dust aerosols, their sources, and the effect of soil moisture in Central Asia

Dust aerosols in Central Asia are an important factor in global climate change and attribution studies. Identifying the source of dust in Central Asia is crucial for understanding the ecological environment and climate, locally and globally. In this study, daily dust aerosol data were calculated and extracted for Central Asia from 2003 to 2018. The multi-year trends of dust aerosols were analyzed, dust sources were identified, the characteristics of dust aerosols in dust sources were analyzed, and the influence of soil moisture on sand initiation was explored. The results show that there are distinct seasonal characteristics in the spatial distribution of dust aerosols in Central Asia. The proportion of the area in the zone of high dust aerosols was the greatest in spring. Nearly half of the dust aerosol areas exhibited an increasing trend. A high incidence of dust sources was mainly distributed in the southern Xinjiang region. The trend of change in the dust area first increased and then decreased. With the increase in soil moisture under different wind speed conditions, the aerosols from dust sources all showed an exponentially decreasing trend, and the increase in soil moisture led to an increase in the wind speed threshold of sand initiation. This study provides basic data support for the study of dust aerosols, identifies dust sources, and provides a basis for studying the radiative forcing and climate effects of dust aerosols in Central Asia.

Spatiotemporal changes in aerosols over Bangladesh using 18 years of MODIS and reanalysis data

In this study, combined Dark Target and Deep Blue (DTB) aerosol optical depth at 550 nm (AOD_{550 nm}) data the Moderate Resolution Imaging Spectroradiometer (MODIS) flying on the Terra and Aqua satellites during the years 2003-2020 are used as a reference to assess the performance of the Copernicus Atmosphere Monitoring Services (CAMS) and the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) AOD over Bangladesh. The study also investigates long-term spatiotemporal variations and trends in AOD, and determines the relative contributions from different aerosol species (black carbon: BC, dust, organic carbon: OC, sea salt: SS, and sulfate) and anthropogenic emissions to the total AOD. As the evaluations suggest higher accuracy for CAMS than for MERRA-2, CAMS is used for further analysis of AOD over Bangladesh. The annual mean AOD from both CAMS and MODIS DTB is high (>0.60) over most parts of Bangladesh except for the eastern areas of Chattogram and Sylhet. Higher AOD is observed in spring and winter than in summer and autumn, which is mainly due to higher local anthropogenic emissions during the winter to spring season. Annual trends from 2003-2020 show a significant increase in AOD (by 0.006-0.014 year^-1) over Bangladesh, and this increase in AOD was more evident in winter and spring than in summer and autumn. The increasing total AOD is caused by rising anthropogenic emissions and accompanied by changes in aerosol species (with increased OC, sulfate, and BC). Overall, this study improves understanding of aerosol pollution in Bangladesh and can be considered as a supportive document for Bangladesh to improve air quality by reducing anthropogenic emissions.

Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China

The Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) algorithm was developed for aerosol retrieval on bright surfaces. Although the global validation accuracy of the DB product is satisfactory, there are still some regions found to have very low accuracy. To this end, DB has updated the surface database in the latest version of the Collection 6.1 (C6.1) algorithm. Some studies have shown that DB aerosol optical depth (AOD) of the old version Collection 6 (C6) has been seriously underestimated in Northwestern China. However, the status of the new version of the C6.1 product in this region is still unknown. This study aims to comprehensively evaluate the performance of the MODIS DB product in Northwestern China. The DB AOD with high quality (Quality Flag = 2 or 3) was selected to validate against the 23 sites from the China Aerosol Remote Sensing Network (CARSNET) and Aerosol Robotic Network (AERONET) during the period 2002–2014. By the overall analysis, the results indicate that both C6 and C6.1 show significant underestimation with a large fraction of more than 54% of collocations falling below the Expected Error (EE = ±(0.05 + 20% AODground)) envelope and with a large negative Mean Bias (MB) of less than −0.14. Furthermore, the new C6.1 products failed to achieve reasonable improvements in the region of Northwestern China. Besides, C6.1 has slightly fewer collocations than C6 due that some pixels with systematic biases have been removed from the new surface reflectance database. From the analysis of the site scale, the scatter plot of C6.1 is similar to that of C6 in most sites. Furthermore, a significant underestimation of DB AOD was observed at most sites, with the most severe underestimation at two sites located in the Taklimakan Desert region. Among 23 sites in Northwestern China, there are only two sites where C6.1 has largely improved the underestimation of C6. Furthermore, it is interesting to note that there are also two sites where the accuracy of the new C6.1 has declined. Moreover, it is surprising that there is one site where a large overestimation was observed in C6 and improved in C6.1. Additionally, we found a constant value of about 0.05 for both C6 and C6.1 at several sites with low aerosol loading, which is an obvious artifact. The significant improvements of C6.1 were observed in the Middle East and Central Asia but not in most sites of Northwestern China. The results of this study will be beneficial to further improvements in the MODIS DB algorithm.

Monsoon-seasonal validation of MODIS aerosol optical depth and characterization using AERONET observation retrieve over Italy

This study used Angstrom Exponent (AE) relationship with Aerosol Optical Depth (AOD) obtained from space-based direct sky-radiometer of Moderate Resolution Imaging Spectroradiometer (MODIS) and direct Sun algorithm surface-based AERONET network (level 2.0 version 3) to evaluate monsoon season (June-September) aerosol optical depth and characterization at 7 Italy sites: IMAA_POTENZA (40.60N, 15.72E), ISPRA (45.80N, 8.62E), LAMPEDUSA (35.51N, 12.63E), MESSINA (38.19N, 15.56E), MODENA (44.63N, 10.94E), ROME_TOR_VERGATA (41.83N, 12.64E) and VENISE (45.31N, 12.50E) from 2010 to 2019. Standardized anomaly and the standard deviation ratio method of analysis to address the robustness of AE were identified to classify aerosols typing. The extracted monsoon AOD correlation between MODIS and AERONET is (r = 0.95) which is plausible to determine discrepancy in data handling. In order to remove large influence of annual cycle, the data were first detrend. The results show that standard deviation value > 1 indicates monthly dominance than climatology. The standardized anomaly records (-0.22 ± 0.13) for MODIS and AERONET AODs with corresponding correlation of (r = 0.96) in June. There is disparity in AOD data handling from MODIS in some periods, which could attribute that space-based interpretation, should be validated with ground-base observation over Italy. The fine mode aerosols due to high AE values interestingly present the characteristic of AOD dominance, but experience trans-seasonal change, where MODIS has weak correlation.

Study on Vertically Distributed Aerosol Optical Characteristics over Saudi Arabia Using CALIPSO Satellite Data

The optical characteristics of vertically distributed aerosols over Saudi Arabia were investigated using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data from 2007 to 2019. The study region was divided into three parts (Region I: Tabuk, Makkah, Al Madinah, Asir, Al Bahah, Jizan, Riyadh, Mecca, Medina, the eastern region, Kassim, Hale, Asir, Baha, Tabuk, the northern border region, Jizan, Najilan, and Jufu. Region II: Ar, Al, Ha, Al, and Najran. Region III Al Hudud ash Shamaliyah and Ash Sharqiyah) to understand regional aerosol characteristics by performing interannual and seasonal analysis for nine aerosol types during the day and nighttime. We found that the aerosol optical depth (AOD) estimates were the highest over eastern Saudi Arabia (region III) and were seemingly driven by the presence of an expansive desert in the region. As anticipated, the AOD observations were substantially higher in spring and summer than in autumn and winter owing to the frequent occurrence of dust events during the former. Daytime observations exhibited higher AOD values than those at nighttime, which might be related to higher daytime anthropogenic activities. The estimates of the base height of the lowest aerosol layer (HB1) and the top altitude of the highest aerosol layer (TAH) were altered depending on the topography (the higher the altitude, the higher the annual mean value of HB1 and TAH). The aerosol layers (N) were relatively abundant over region III, seemingly due to the relatively stronger atmospheric convection over this region. The volume depolarization ratio of the lowest aerosol layer (VDR1) was considerable during the night due to deposition at nighttime, and VDR1 was relatively substantial in spring and summer. The color ratio of the lowest aerosol layer (CR1) estimates over regions II and III was higher at night. We report a weak positive correlation between the thickness of the lowest aerosol layer (HTH1) and the AOD of the lowest aerosol layer (AOD1) in the three regions, a strong positive correlation between TAH and N, and a negative correlation between the AOD proportion of the lowest aerosol layer (PAOD1) and N in Saudi Arabia. In this paper, the optical and physical properties of aerosols in Saudi Arabia have been studied for 13 years. Our results could provide references for researchers and the government, and relevant departments with data support on the aerosol layer to help control air pollution in Saudi Arabia.

Identification of Aerosol Pollution Hotspots in Jiangsu Province of China

Aerosol optical depth (AOD) is an important atmospheric parameter for climate change assessment, human health, and for total ecological situation studies both regionally and globally. This study used 21-year (2000–2020) high-resolution (1 km) Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm-based AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra and Aqua satellites. MAIAC AOD was evaluated against Aerosol Robotic Network (AERONET) data across three sites (Xuzhou-CUMT, NUIST, and Taihu) located in Jiangsu Province. The study also investigated the spatiotemporal distributions and variations in AOD, with associated trends, and measured the impact of meteorology on AOD in the 13 cities of Jiangsu Province. The evaluation results demonstrated a high correlation (r = 0.867~0.929) between MAIAC AOD and AERONET data, with lower root mean squared error (RMSE = 0.130~0.287) and mean absolute error (MAE = 0.091~0.198). In addition, the spatial distribution of AOD was higher (>0.60) in most cities except the southeast of Nantong City (AOD < 0.4). Seasonally, higher AOD was seen in summer (>0.70) than in spring, autumn, and winter, whereas monthly AOD peaked in June (>0.9) and had a minimum in December (<0.4) for all the cities. Frequencies of 0.3 ≤ AOD < 0.4 and 0.4 ≤ AOD < 0.5 were relatively common, indicating a turbid atmosphere, which may be associated with anthropogenic activities, increased emissions, and changes in meteorological circumstances. Trend analysis showed significant increases in AOD during 2000–2009 for all the cities, perhaps reflecting a booming economy and industrial development, with significant emissions of sulfur dioxide (SO2), and primary aerosols. China’s strict air pollution control policies and control of vehicular emissions helped to decrease AOD from 2010 to 2019, enhancing air quality throughout the study area. A notably similar pattern was observed for AOD and meteorological parameters (LST: land surface temperature, WV: water vapor, and P: precipitation), signifying that meteorology plays a role in terms of increasing and decreasing AOD.

Prevalence and Associated Risk Factor of COVID-19 and Impacts of Meteorological and Social Variables on Its Propagation in Punjab, Pakistan

The current study identifies the spatial distribution of COVID-19 cases and its association with meteorological and social variables in Punjab (densely populated province of Pakistan). To identify the COVID-19 propagation, the weekly growth, recovery, and deaths rate have also been calculated. The geographic information system (GIS) has used to determine COVID-19 impacts on gender (male/female), age groups, and causalities over an affected population (km^-2) for the period of 11th March to 12th August, 2020 in each district of province. Our results show that 43 peak days (where daily positive cases were above 900) have been observed in Punjab during 27th May to 8th July, 2020. The high population density districts, i.e., Lahore and Islamabad, have been affected (five persons per square kilometers) due to COVID-19, whereas the maximum death tolls (> 50 persons per millions) have also been observed in these urban districts. The meteorological variables (temperature, humidity, heat index, and ultraviolet index) show negative significant relationship to basic reproduction number (R0), whereas daily COVID-19 cases are positively correlated to aerosols concentration at 95% confidence level. The government intervention (stringency index) shows a positive impact to reduce the COVID-19 cases over the province. Keeping in view the COVID-19 behavior and climatology of the region, it has been identified that the COVID-19 cases may likely to increase during the dry period (high concentration of aerosols) i.e., October-December, 2020 and post-spring season (April to June), 2021 in urban areas of Pakistan. This study provides an overview on districts vulnerability that would help the policy makers, health agencies to plan their activities to reduce the COVID-19 impacts.

Estimation of ground-level PM2.5 concentration using MODIS AOD and corrected regression model over Beijing, China

To establish a new model for estimating ground-level PM2.5 concentration over Beijing, China, the relationship between aerosol optical depth (AOD) and ground-level PM2.5 concentration was derived and analysed firstly. Boundary layer height (BLH) and relative humidity (RH) were shown to be two major factors influencing the relationship between AOD and ground-level PM2.5 concentration. Thus, they are used to correct MODIS AOD to enhance the correlation between MODIS AOD and PM2.5. When using corrected MODIS AOD for modelling, the correlation between MODIS AOD and PM2.5 was improved significantly. Then, normalized difference vegetation index (NDVI), surface temperature (ST) and surface wind speed (SPD) were introduced as auxiliary variables to further improve the performance of the corrected regression model. The seasonal and annual average distribution of PM2.5 concentration over Beijing from 2014 to 2016 were mapped for intuitively analysing. Those can be regarded as important references for monitoring the ground-level PM2.5 concentration distribution. It is obviously that the PM2.5 concentration distribution over Beijing revealed the trend of "southeast high and northwest low", and showed a significant decrease in annual average PM2.5 concentration from 2014 to 2016.

Characteristics of aerosol optical depth over land types in central Asia

Aerosols are an important contributor to global atmospheric changes and have critical effects on the climate system. Regionally, aerosols in central Asia comprise a significant portion of global aerosols. Based on aerosol optical depth (AOD)Level 2 daily product data and land cover type product data, the long-term AOD characteristics of six major land use/cover types and their relationships with landscape metrics are discussed. Contribution analysis is applied to quantitatively estimate the effects of land use/cover on regional AOD over central Asia. The results show that series of daily AODs over six land uses/covers display remarkable annual cyclic variations and obvious seasonal changes. The annual average AODs for barren land and cropland are highest, followed by regional AODs. There are different frequencies and times of occurrence for high AOD values of various land types. Urban areas are one of the major contributors to the regional atmosphere in winter; grasslands have a great influence on regional AOD decreases. Barren land always has a high contribution to the regional AOD. The land use types affected by anthropogenic activities were smaller contributors to regional aerosols than barren lands affected by climate factors. This paper advances the understanding of relationship between aerosols and land use/cover and facilitates land use decision making.

Exploring the spatial-temporal characteristics of the aerosol optical depth (AOD) in Central Asia based on the moderate resolution imaging spectroradiometer (MODIS)

Central Asia has become a key node of the belt and road corridor. It is located in arid and semi-arid climate regions, and it is a region where the contribution of global aerosols of sand and dust is continuous. However, few studies have been conducted on the Central Asian aerosol optical depth. Therefore, this paper relied on the belt and road sustainable development dataset to analyze the spatial-temporal variations in the AOD in Central Asia and provide spatial-temporal characteristics of the AOD for environmental services. We analyzed the spatial and temporal variation in the aerosol optical depth (AOD) in Central Asia by using MODIS/AQUA C6 MYD08_M3 images from 2008 to 2017. The results showed that (1) the annual average AOD in Central Asia in the past decade varied from 0.183 to 0.232, which indicated a slow decline starting in 2014. The percentage of average annual decline was approximately 0.18%, and the regular distinct revealed the distribution characteristics of AOD. In different years, the Central Asian region exhibited the similar monthly change characteristics: from July to December, the AOD decreased, and from December to February, it increased. In different seasons, the Central Asian region exhibited the different seasonal change characteristics: the AOD value was higher in the spring and summer. The mean values in the spring, summer, autumn, and winter were 0.273, 0.240, 0.155, and 0.183, respectively, and the standard deviations were 0.036, 0.038, 0.025, and 0.048, respectively. (3) Based on spatial distribution characteristics, the Tarim Basin, Aral Sea region, and Ebinur Lake area were high value areas, and Kazakhstan was a low value area. The AOD of the surrounding area of the Aral Sea had increased in the last 5 years, while that of Kazakhstan, Uzbekistan, and Turkmenistan had decreased. The AOD of the Taklamakan area exhibited an inter-annual change. Sand dust aerosols were the largest contributors to the AOD in the Taklamakan area. The rising trend of the AOD in the Aral Sea area was clear, with an average annual increase of 0.234%, and the contribution of salt dust aerosols to the AOD increased. The average annual AOD in the Ebinur Lake area remained stable.

Long-Term Aerosol Trends and Variability over Central Saudi Arabia Using Optical Characteristics from Solar Village AERONET Measurements

Natural and anthropogenic aerosols over the Kingdom of Saudi Arabia (KSA) play a major role in affecting the regional radiation budget. The long-term variability of these aerosols’ physical and optical parameters, including aerosol optical depth (AOD) and Ångström exponent (α), were measured at a location near central KSA using the Solar Village (SV) AERONET (Aerosol Robotic Network) station during the period December 1999–January 2013. The AERONET measurements show an overall increase in AOD on an annual basis. This upward trend is mainly attributed to a prolonged increase in the monthly/seasonal mean AOD during March–June and during August–September. In contrast, lower AOD values were observed during November–December. This can be attributed to a low frequency of dust outbreaks and higher precipitation rates. An overall, weak declining trend in α was observed, except during the summer. The spring and summer seasons experienced a pronounced increase in the number of coarse particles (~2 µm) during April 2006–January 2013 as compared to December 1999–March 2006, suggesting an increase in natural aerosol loadings. Using the HYSPLIT model, it was found that the March 2009 dust storm contributed to the mixing of long-transported dust with anthropogenic local emissions near the SV. The results suggest that extensive industrial activity contributed to the increase of anthropogenic emissions over KSA during the period April 2006–January 2013.

Understanding the Spatial-Temporal Patterns and Influential Factors on Air Quality Index: The Case of North China

North China has become one of the worst air quality regions in China and the world. Based on the daily air quality index (AQI) monitoring data in 96 cities from 2014–2016, the spatiotemporal patterns of AQI in North China were investigated, then the influence of meteorological and socio-economic factors on AQI was discussed by statistical analysis and ESDA-GWR (exploratory spatial data analysis-geographically weighted regression) model. The principal results are as follows: (1) The average annual AQI from 2014–2016 exceeded or were close to the Grade II standard of Chinese Ambient Air Quality (CAAQ), although the area experiencing heavy pollution decreased. Meanwhile, the positive spatial autocorrelation of AQI was enhanced in the sample period. (2) The occurrence of a distinct seasonal cycle in air pollution which exhibit a sinusoidal pattern of fluctuations and can be described as “heavy winter and light summer.” Although the AQI generally decreased in other seasons, the air pollution intensity increased in winter with the rapid expansion of higher AQI value in the southern of Hebei and Shanxi. (3) The correlation analysis of daily meteorological factors and AQI shows that air quality can be significantly improved when daily precipitation exceeds 10 mm. In addition, except for O₃, wind speed has a negative correlation with AQI and major pollutants, which was most significant in winter. Meanwhile, pollutants are transmitted dynamically under the influence of the prevailing wind direction, which can result in the relocation of AQI. (4) According to ESDA-GWR analysis, on an annual scale, car ownership and industrial production are positively correlated with air pollution; whereas increase of wind speed, per capita gross domestic product (GDP), and forest coverage are conducive to reducing pollution. Local coefficients show spatial differences in the effects of different factors on the AQI. Empirical results of this study are helpful for the government departments to formulate regionally differentiated governance policies regarding air pollution.

Comparison of Aerosol Optical Depth Products from Multi-Satellites over Densely Populated Cities of Pakistan

Air pollution in Pakistan is causing damage to health, environment and quality of life. Air pollution in Pakistan is not effectively monitored due to heavy cost involved in setting up ground stations. However, Satellite remote sensing can effectively monitor the air pollution in terms of Aerosol Optical Depth (AOD) at regional as well as global level. However, algorithms used to derive AOD from different sensors have some inherited differences which can pose challenges in monitoring regional AOD at high temporal resolution using more than one sensor. Therefore, this study focuses on comparison of four major satellite based AOD products namely Moderate Resolution Imaging SpectroRadiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR), Ozone Monitoring Instrument multiwavelength (OMI) aerosol product and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) with the ground based AErosol RObotic NETwork (AERONET) AOD which is only available from Lahore and Karachi in Pakistan. The correlation of various AOD products with AERONET AOD is estimated statistically through coefficient of determination (R2), Root Mean Square Error (RMSE), slope and intercept. It is noticed that MODIS is relatively accurate and reliable for monitoring air quality on operational bases over the land cover area of Lahore (R2 = 0.78; RMSE = 0.18 ), whereas MISR over the coastal areas of Karachi (R2 = 0.82; RMSE = 0.20 ). The results of the study will help the stakeholders in planning additional ground stations for operational monitoring of air quality at regional level.

Comparison of Aerosol Optical Depth Products from Multi-Satellites over Densely Populated Cities of Pakistan

Air pollution in Pakistan is causing damage to health, environment and quality of life. Air pollution in Pakistan is not effectively monitored due to heavy cost involved in setting up ground stations. However, Satellite remote sensing can effectively monitor the air pollution in terms of Aerosol Optical Depth (AOD) at regional as well as global level. However, algorithms used to derive AOD from different sensors have some inherited differences which can pose challenges in monitoring regional AOD at high temporal resolution using more than one sensor. Therefore, this study focuses on comparison of four major satellite based AOD products namely Moderate Resolution Imaging SpectroRadiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR), Ozone Monitoring Instrument multiwavelength (OMI) aerosol product and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) with the ground based AErosol RObotic NETwork (AERONET) AOD which is only available from Lahore and Karachi in Pakistan. The correlation of various AOD products with AERONET AOD is estimated statistically through coefficient of determination (R2), Root Mean Square Error (RMSE), slope and intercept. It is noticed that MODIS is relatively accurate and reliable for monitoring air quality on operational bases over the land cover area of Lahore (R2= 0.78; RMSE = 0.18 ), whereas MISR over the coastal areas of Karachi (R2= 0.82; RMSE = 0.20 ). The results of the study will help the stakeholders in planning additional ground stations for operational monitoring of air quality at regional level.