MODIS-derived Aerosol Optical Depth Research Articles

Assessment of COVID-19 lockdown impact on PM10 and PM2.5 concentrations in the Mexico City Metropolitan Area

PM10 and PM2.5 concentrations are regularly monitored because they cause adverse effects on human health. The concentrations of PM10 and PM2.5 vary within a city due to land use, the amount of traffic, and pollution sources. As the COVID-19 pandemic spread around the world, lockdowns were enacted to stop the spread of the virus. These lockdowns meant reduced mobility and the halt of certain economic activities which had an impact on air pollution sources. In this paper, we assess the effect of the lockdown enacted in April-May 2020 in the Mexico City Metropolitan Area on PM10 and PM2.5 concentrations, using statistical analysis tools. MODIS-derived aerosol optical depth is used to assess the change of aerosols spatial distribution during the lockdown. Furthermore, a Mann-Whitney test is applied to PM10 and PM2.5 data from ground-based monitoring stations to evaluate the effects of lockdown. A general reduction of 20 % of PM10 and 10 % in PM2.5 was found. Overall, a 15 % reduction in particulate matter was found in Mexico City due to lockdown.

The Aerosol Optical Characteristics in Different Dust Events Based on a 532 nm and 355 nm Polarization Lidar in Beijing

Extreme weather events are happening more frequently as a result of global climate change. Dust storms broke out in the spring of 2017 in China and drastically impacted the local air quality. In this study, a variety of data, including aerosol vertical profiles, surface particle concentration, meteorological parameters, and MODIS–derived aerosol optical depth, as well as backward trajectory analysis, were employed to analyze two dust events from April to May in Beijing. The dust plumes were mainly concentrated below 0.8 km, with peak PM10 values of 1000 μg·m−3 and 300 μg·m−3 in the two cases. The aerosols showed different vertical distribution characteristics. The pure dust in case 1 from 4 to 5 May 2017 had a longer duration (2 days) and presented a larger aerosol extinction coefficient (2.27 km−1 at 355 nm and 1.25 km−1 at 532 nm) than that of the mixed dust in case 2 on 17 April 2017 (2.01 km−1 at 355 nm and 1.33 km−1 at 532 nm). The particle depolarization ratio (PDR) remained constant (0.24 ± 0.03 in case 1) from the surface to 0.8 km in height. In contrast, the PDR profile in the mixed dust (case 2) layer was split into two regions—large values exceeding 0.15 above 0.6 km and small values of 0.11 ± 0.03 below 0.6 km. The influence of meteorological information on aerosol distribution was also investigated, and wind was predominant through the observing period. The pure dust in case 1 was mainly from Mongolia, with strong northwest winds, while the near-surface mixed pollution was caused by the combination of long-transported sand and local emission. Furthermore, lidar-derived profiles of dust mass concentrations in the two cases were presented. This study reveals the vertical characteristics of dust aerosols in the production and dissipation of localized dust events and confirms the efficacy of thorough observations with multiple approaches from the ground to space to monitor dust events in real time.

Dynamic Characteristics of Aerosol Optical Properties over Dibrugarh City in the North-Eastern Indian Region during 2018–2021

Aerosols play an important role in the earth's environment across the globe through their involvement in various earth system cycles. The change in the aerosol properties may cause short and long-term impacts, the knowledge of such changes is useful in the estimation of the pollution sources of any region. We have carried out the analysis of the aerosols' optical and radiative properties using AERONET station data from 2018 to 2021 in Dibrugarh City. The higher Aerosol Optical Depth (AOD) values during winter and pre-monsoon months indicate high anthropogenic activities, and biomass burning in Dibrugarh. The impact of various sources and daily meteorological parameters help in understanding the diurnal variations of the AOD, Ångström Exponent (AE), and column water (CW). Fine aerosol fractions dominate the aerosol volume, but sometimes the long-range transport of dust affects aerosol properties during pre-monsoon months (MAM). MODIS-derived AOD and AERONET AOD values show a good correlation, with R2 = 0.68. The highest volume of the aerosols reaches up to 0.11 µm3 µm-2 during pre-monsoon months, whereas it lies below 0.05 µm3 µm-2 in other seasons. SSA values indicate the presence of scattering aerosols but in 2020, a sudden decline in the SSA values shows a strong rise in the absorbing aerosols. Throughout the study period (2018–2021), the positive radiative forcing indicates a rise in atmospheric heating.

Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing

Air pollution is one of the vital problems for the sustainability of cities and public health. The lockdown caused by the COVID-19 outbreak has become a natural laboratory, enabling to investigate the impact of human/industrial activities on the air pollution. In this study, we investigated the spatio-temporal density of TROPOMI-based nitrogen dioxide (NO2) and sulfur dioxide (SO2) products, and MODIS-derived Aerosol Optical Depth (AOD) from January 2019 to September 2020 (also covering the first wave of the COVID-19) over Turkey using Google Earth Engine (GEE). The results showed a significant decrease in NO2 and AOD, while SO2 unchanged and had slightly higher concentrations in some regions during the lockdown compared to 2019. The relationship between air pollutants and meteorological parameters during the lockdown showed that air temperature and pressure were highly correlated with air pollutants, unlike precipitation and wind speed. Moreover, Purchasing Managers' Index (PMI) data, indicator of economic/industrial activities, also provided poor correlation with air pollutants. TROPOMI-based NO2 and SO2 were compared with station-based pollutants for three sites (suburban, urban, and urban-traffic classes) in Istanbul, revealing 0.83, 0.70 and 0.65 correlation coefficients for NO2, respectively, while SO2 showed no significant correlation. Besides, AOD data were validated using two AERONET sites providing 0.86 and 0.82 correlation coefficients. Overall, the satellite-based data provided significant outcomes for the spatio-temporal evaluation of air quality, especially during the first wave of the COVID-19 lockdown.

Dried bottom of Urmia Lake as a new source of dust in the northwestern Iran: Understanding the impacts on local and regional air quality

Urmia Lake, the largest inland lake in Iran has lost most of its water surface area in the last 2 decades. The desertification caused by the drying of this unique lake may lead to dust storms from the lakebed and affect the air quality of the region. In this study, MODIS derived Aerosol Optical Depth (AOD) data observed between 2000 and 2019, Ultra Violet Aerosol Index (UVAI) data from Ozone Monitoring Instrument (OMI), meteorological data from MERRA-2 and ground-level PM10 data measured in the northwestern Iran and eastern Turkey were used to investigate the effects of the drying of Urmia Lake on local and regional aerosol pollution. The results revealed significant increase in aerosol pollution over the last 10 years. An inverse relationship was observed between water level fluctuations of Urmia Lake and aerosol pollution in the northwestern Iran. In total, 177 days (27 days in the period of 2000–2009 and 150 days in the period of 2010–2019) with mean daily AOD values equal to or greater than 1 were observed over the box covering Urmia Lake Basin (ULB). During 2000–2009, when the mean AOD was 0.25, the mean water surface area of the lake was observed to be 4000 km2. When the lake dried up faster during 2010–2019 (the mean water surface area was observed 2100 km2), the mean AOD increased to 0.42.The eastern part of the lake was more polluted than western part due to the extent of salinization and desertification in this part and the prevailing wind direction from west to east. The results indicated similar trends with PM10 concentration in the northwestern Iran and eastern Turkey but the classification of PM10 values based on wind direction and wind speed rejected the influence of the lakebed on aerosol pollution in the eastern Turkey except in special meteorological conditions. These conditions occur when a low-pressure system over central Iraq and a high-pressure system located in a more northerly part of the region, mainly over the Caucasian, form a dust channel. In addition to dust storms from Iraq, Syria, Arabian Desert and local emission sources, the lakebed contributes as a new source of aerosol pollution mainly in the northwestern Iran and close regions.

Aerosols optical depth and Ångström exponent over different regions in Garhwal Himalaya, India.

Aerosol optical depth (AOD) and Ångström exponent (AE) are observed to be important parameters in understanding the status of ambient aerosol concentration over a particular location and depend not only upon the local but also on the large-scale dynamics of the atmosphere. The present article analyses the AOD and AE parameters retrieved with Moderate Resolution Imaging Spectrometer (MODIS) and Multi-angle Imaging Spectro-Radiometer (MISR) instruments onboard satellites, for the upper (Chamoli) and foothill (Dehradun) regions of Garhwal Himalaya in Uttarakhand, India, from 2006 to 2015. Aerosol properties are investigated at monthly, seasonal, and annual scales. The monthly mean values of MODIS-derived AOD and AE were observed to be 0.18 (± 0.14) and 1.05 (± 0.43) respectively over the Dehradun region. The seasonal maximums in AOD with MODIS and MISR were observed as 0.23 ± 0.06 and 0.29 ± 0.07 respectively in the pre-monsoon season, and the minimum values (0.099 ± 0.02) were observed in the post-monsoon season, over the Dehradun region. In contrast, in the Chamoli region, the maximum AOD (MODIS) was 0.21 ± 0.06 observed in the monsoon season and the minimum was 0.036 ± 0.007 in the post-monsoon season. Over a decade, the AE for Chamoli and Dehradun was found to vary from 0.07 to 0.17 and from 0.14 to 0.20 respectively. The median AE for Chamoli and Dehradun was found to be 1.49 and 1.47 respectively, marking the dominance of fine mode particles of anthropogenic origin. Observations show the presence of dust and polluted dust resulting from the long-range transport from the west. The comparison of AOD values from the two sensors shows a significant correlation (0.73) with slightly higher values from MISR over the year. The results obtained are important in understanding the climatic implications due to the atmospheric aerosols over the abovementioned Himalayan region of Uttarakhand, India.

Revisiting the levels of Aerosol Optical Depth in south-southeast Asia, Europe and USA amid the COVID-19 pandemic using satellite observations

The countries around the world are dealing with air quality issues for decades due to their mode of production and energy usages. The outbreak of COVID-19 as a pandemic and consequent global economic shutdown, for the first time, provided a base for the real-time experiment of the effect of reduced emissions across the globe in abetting the air pollution issue. The present study dealt with the changes in Aerosol Optical Depth (AOD), a marker of air pollution, because of global economic shutdown due to the coronavirus pandemic. The study considered the countries in south and south-east Asia (SSEA), Europe and the USA for their extended period of lockdown due to coronavirus pandemic. Daily Aerosol Optical Depth (AOD) from Moderate-resolution imaging spectroradiometer (MODIS) and tropospheric column density of NO2 and SO2 from Ozone monitoring instrument (OMI) sensors, including meteorological data such as wind speed (WS) and relative humidity (RH) were analyzed during the pre-lockdown (2017–2019) and lockdown periods (2020). The average AOD, NO2 and SO2 during the lockdown period were statistically compared with their pre-lockdown average using Wilcoxon-signed-paired-rank test. The accuracy of the MODIS-derived AOD, including the changing pattern of AOD due to lockdown was estimated using AERONET data. The weekly anomaly of AOD, NO2 and SO2 was used for analyzing the space-time variation of aerosol load as restrictions were imposed by the concerned countries at the different points of time. Additionally, a random forest-based regression (RF) model was used to examine the effects of meteorological and emission parameters on the spatial variation of AOD. A significant reduction of AOD (−20%) was obtained for majority of the areas in SSEA, Europe and USA during the lockdown period. Yet, the clusters of increased AOD (30–60%) was obtained in the south-east part of SSEA, the western part of Europe and US regions. NO2 reductions were measured up to 20–40%, while SO2 emission increased up to 30% for a majority of areas in these regions. A notable space-time variation was observed in weekly anomaly. We found the evidence of the formation of new particles for causing high AOD under high RH and low WS, aided by the downward vertical wind flow. The RF model showed a distinguishable relative importance of emission and meteorological factors among these regions to account for the spatial variability of AOD. Our findings suggest that the continued lockdown might provide a temporary solution to air pollution; however, to combat persistent air quality issues, it needs switching over to the cleaner mode of production and energy. The findings of this study, thus, advocated for alternative energy policy at the global scale.

Inter-annual variability in fine particulate matter pollution over China during 2013–2018: Role of meteorology

Based on the long-term observed fine particulate matter (PM2.5) data obtained from the Ministry of Environmental Protection of China, the present study focused on the analysis of annual and seasonal trends of PM2.5 over the polluted areas in China from 2013 to 2018. The MODIS-derived aerosol optical depth (AOD) data was used as an auxiliary data to supplement the analysis with surface measured PM2.5. The emission source inventory and meteorology datasets are also used and analyzed to examine the causes of changes in trends of PM2.5. The results revealed that the annually averaged values of AOD and surface PM2.5 concentrations over the high-polluted areas are decreasing year-by-year, with stable values found over the Pearl River Delta (PRD) region. The decreasing trends of PM2.5 concentration and fine particle pollution frequency over the Beijing, Tianjin, and Hebei (BTH) area are most obvious. Over the PRD region, PM2.5 concentration maintains below the annual air quality standard (35 μg/m3) with low fine particle pollution frequency. The decreasing trend of averaged PM2.5 in each region is closely related to the reduction of anthropogenic PM2.5 emissions. However, the fluctuated features in different season are mostly influenced by the meteorological conditions. Based on the weather type classifications observed from the COST733 model, the weather types under uniform pressure and eastern high pressure more likely resulted in the occurrence of fine particulate pollution over China. When the weather under the bottom with high pressure occurs, Northeast China (NEC) and BTH regions are most likely to be polluted, which is more likely to lead to heavy fine particle pollution events. The air pollution in the Yangtze River Delta (YRD) area is the most serious when the uniform pressure field weather occurs in winter.

Spaceborne Observations of the Diurnal Variation of Shortwave Aerosol Direct Radiative Effect at Top of Atmosphere Over the Dust-Dominated Arabian Sea and the Atlantic Ocean

The ScaRaB payload onboard the low-inclination Megha-Tropiques (MT) satellite has been making observations of radiative fluxes at the top of the atmosphere (TOA) for different local times (LTs) of the day over the tropics since October 2011. This provides a unique opportunity to investigate the diurnal variation of the regional instantaneous aerosol direct radiative effect efficiency (IADREE) at TOA, which is otherwise not possible using the available long-term satellite observations carried out using similar sensors onboard polar sun-synchronous satellites. In this paper, the diurnal variations of the IADREE over the Arabian Sea and the Atlantic Ocean during June–September, when both these regions are engulfed by large-scale mineral dust plumes transported from the adjoining deserts, are investigated using collocated multiyear (2012–2014) observations of the MT-ScaRaB measured shortwave fluxes and MODIS-derived aerosol optical depth. The estimates of the IADREE made using the MT-ScaRaB data at 13:30 LT are found to be in agreement with those derived from the Cloud and the Earth’s Radiant Energy System data at this LT, at which the latter observations are carried out. The IADREE derived from the MT-ScaRaB shows diurnal peak value of −53 ± 10 Wm $^{{{-2}}}\tau _{{{550}}}^{{{-1}}}$ and −40 ± 3 Wm $^{{{-2}}}\tau _{{{550}}}^{{{-1}}}$ at solar zenith angle of ~40° over the Arabian Sea and the Atlantic Ocean, respectively. Diurnal mean aerosol direct radiative effect efficiency at TOA during June–September is −22 ± 4.5 Wm $^{{{-2}}}\tau _{{{550}}}^{{{-1}}}$ over the Arabian Sea and −18 ± 3.6 Wm $^{{{-2}}}\tau _{{{550}}}^{{{-1}}}$ over the Atlantic Ocean.

Simulation of Aerosol Fields over South Asia Using CHIMERE - Part-II:Performance Evaluation

In this paper, we evaluate the performance of the chemical transport model 'CHIMERE' over large Indian region (4-37.5°N; 67-88.5°E) for multiple years (2006, 2007 and 2008) by comparing the model simulations with concurrent aerosol measurements from different locations. Model simulated near-surface black carbon mass concentrations agreed satisfactorily with measurements at various locations (oceanic, inland and island sites), in general, except during monsoon months, when the model underpredicted the measurements. Similar results were obtained when model simulated column integrated PM 10 mass concentrations were correlated with MODIS-derived aerosol optical depth (AOD), using AOD as a proxy for aerosol loading. The underperformance of the model during monsoon arises, at least partly, due to the model-simulated rainfall being higher than the actual rainfall over the Indian domain, during the monsoon season. Notwithstanding these, the general performance of the CHIMERE model to simulate aerosol loading over Indian domain during dry months is, in general, found to be satisfactory.

Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD.

Taking advantage of the continuous spatial coverage, satellite-derived aerosol optical depth (AOD) products have been widely used to assess the spatial and temporal characteristics of fine particulate matter (PM2.5) on the ground and their effects on human health. However, the national-scale ground-level PM2.5 estimation is still very limited because the lack of ground PM2.5 measurements to calibrate the model in China. In this study, a national-scale geographically weighted regression (GWR) model was developed to estimate ground-level PM2.5 concentration based on satellite AODs, newly released national-wide hourly PM2.5 concentrations, and meteorological parameters. The results showed good agreements between satellite-retrieved and ground-observed PM2.5 concentration at 943 stations in China. The overall cross-validation (CV) R (2) is 0.76 and root mean squared prediction error (RMSE) is 22.26μg/m(3) for MODIS-derived AOD. The MISR-derived AOD also exhibits comparable performance with a CV R (2) and RMSE are 0.81 and 27.46μg/m(3), respectively. Annual PM2.5 concentrations retrieved either by MODIS or MISR AOD indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions especially for the regions without PMs monitoring sites.

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new “Deep Blue” retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented.Implications: Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.

Spatial and temporal patterns of air pollutants in rural and urban areas of India

In this study, we analysed spatial and temporal patterns of Suspended Particulate Matter (SPM) concentrations across India. We have also assessed MODIS-derived aerosol optical depth (AOD) variations to characterize the air quality and relate it to SPM, NO2 and SO2 in different areas. In addition, the pollutant concentrations have been mapped using geospatial techniques. The results indicated significant differences in air pollutant levels across rural and urban areas. In general, districts of central and northern India had relatively higher SPM concentrations compared to southern India. Out of the top ten SPM polluted districts in India, nine were located in the state of Uttar Pradesh (UP). We observed significant correlations between the SPM and AOD at different sites. Although spatial and temporal patterns of NO2 and SO2 matched AOD patterns, the correlation strength (r2) varied based on location. The causes and implications of these findings are presented.

Spatio-temporal variations in the estimation of PM10 from MODIS-derived aerosol optical depth for the urban areas in the Central Indo-Gangetic Plain

Particulate air pollution poses a serious health problem to the urban centers in the central Indo-Gangetic plain (IGP) in northern India. Health management planning is constrained by the lack of availability of continuous dataset of particulate matter (PM) at a regional scale. Recently, researchers have established the strength of regression models for estimating PM from satellite-derived aerosol optical depth (AOD) and meteorological factors. The present study is focused on three cities, namely, Agra, Kanpur and Varanasi located in the central IGP. The study envisages four approaches of multi-linear regression modeling to estimate PM10 (particulates smaller than 10 µm) from AOD and the meteorological parameters. The first approach consists of four regional models, three of which estimate regional mean PM10 and the fourth one estimates the distributed PM10. These models have a weak-to-moderate coefficient of determination (R 2 = 0.37–0.63). Spatial and temporal variations in the estimators are separately addressed by the second modeling approach, i.e., city models (CMs) and the third modeling approach, i.e., seasonal models (SMs), respectively. R 2 of these models varies from 0.40 to 0.68. Finally, the spatio-temporal variability of the estimators are addressed by the fourth modeling approach, i.e., city-wise seasonal models (CSMs) which exhibited better results (R 2 = 0.49–0.88). Remarkable variations in the regression estimators of the CSMs are observed both spatially and temporally. The model adequacy checks and the validation studies also support CSMs for more reliable estimation of PM10 in the central IGP. The proposed methodology can, therefore, be reliably used in generating the regional PM10 concentration maps for health impact studies.

A robust calibration approach for PM<sub>10</sub> prediction from MODIS aerosol optical depth

Abstract. Investigating the human health effects of atmospheric particulate matter (PM) using satellite data are gaining more attention due to their wide spatial coverage and temporal advantages. Such epidemiological studies are, however, susceptible to bias errors and resulted in poor predictive output in some locations. Current methods calibrate aerosol optical depth (AOD) retrieved from MODIS to further predict PM. The recent satellite-based AOD calibration uses a mixed effects model to predict location-specific PM on a daily basis. The shortcomings of this daily AOD calibration are for areas of high probability of persistent cloud cover throughout the year such as in the humid tropical region along the equatorial belt. Contaminated pixels due to clouds causes radiometric errors in the MODIS AOD, thus causes poor predictive power on air quality. In contrary, a periodic assessment is more practical and robust especially in minimizing these cloud-related contaminations. In this paper, a simple yet robust calibration approach based on monthly AOD period is presented. We adopted the statistical fitting method with the adjustment technique to improve the predictive power of MODIS AOD. The adjustment was made based on the long-term observation (2001–2006) of PM10-AOD residual error characteristic. Furthermore, we also incorporated the ground PM measurement into the model as a weighting to reduce the bias of the MODIS-derived AOD value. Results indicated that this robust approach with monthly AOD calibration reported an improved average accuracy of PM10 retrieval from MODIS data by 50% compared to widely used calibration methods based on linear regression models, in addition to enabling further spatial patterns of periodic PM exposure to be undertaken.

Post-launch calibration of the INSAT-3A-CCD geostationary satellite sensor

Post-launch calibration was carried out for red and near infrared (NIR) bands of an Indian National Satellite System (INSAT)-3A-CCD camera over the Bay of Bengal (BOB) region. For this purpose, a coupled ocean–atmosphere radiative transfer (COART) model constrained by in situ measurements was used to simulate top-of-atmosphere (TOA) radiance for red and NIR bands. Comparisons were made between the simulated radiance and the charge-coupled device (CCD)-measured radiance. Analysis shows that for clear deep ocean pixels, the CCD camera overestimates TOA radiance in the NIR band by 74.8%, while it underestimates the radiance in the red band by 20.6% with respect to simulated radiances. Calibration factors were computed for the red and NIR bands of the CCD camera. Differences in simulated radiance and satellite-derived radiance were limited to 2.6% for the red band and up to 2.25% for the NIR band by applying these calibration factors. Validation of the calibrated radiance was done by performing a comparative analysis of aerosol optical depth (AOD) at 550 nm calculated from the calibrated INSAT-3A-CCD radiance, with in situ measured AOD (550 nm) and MODIS-derived AOD (550 nm). It was also found that the difference in uncalibrated radiance for the red band overestimated AOD (550 nm) by 155.65% when compared with in situ measurements, which was brought down to 1.48% after calibration. A comparison of INSAT-3A-CCD-estimated AOD (550 nm) was also done with MODIS-TERRA-derived τa (550 nm). Spatial distribution of AOD after this calibration process matches well with spatial distribution of MODIS-derived AOD products for 550 nm. A good correlation was observed with R 2 = 0.94 with root mean square error (RMSE) of ±0.036 between the INSAT- and MODIS-derived AODs.

Characterization and transport of aerosols over the Bay of Bengal during the winter monsoon: a comparative study using in-situ and satellite measurements

Natural processes, such as dust storms and sea salt spray, and anthropogenic activities, such as the burning of fossil fuels and biomass, introduce aerosols into the atmosphere. Their concentration, geographic distribution and particle size promote significant climatic consequences. Aerosol transport processes, from landmasses to oceans, are scarcely understood because of inadequate in-situ observations. This study reports the results of spectral aerosol optical depth (AOD) measurements using a five-channel (380, 440, 500, 675 and 870 nm) handheld MICROTOPS Sun-photometer used during a sea-truth data collection campaign conducted in the central Bay of Bengal (BOB) during the northeastern monsoon period (10 November to 13 December 2007). For the entire cruise period, the mean values of the daily average of the AODs at 500 nm and 870 nm were 0.39 ± 0.065 and 0.22 ± 0.047, respectively, the mean value of the Angstrom exponent (α) was 1.23 ± 0.2 and the turbidity parameter (β) was 0.183 ± 0.044. A smaller α value together with a larger β value suggests the presence of an abundance of smaller aerosol particles near the coast. An air mass back-trajectory analysis was undertaken to identify the potential source regions of the aerosols. Analysis of the results demonstrated the effect of the aerosol transport and source regions on the spectral behaviour of the AODs. In-situ measured AOD (550 nm) and α (550 nm, 865 nm) values were further compared with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived parameters. The in-situ and MODIS-derived AOD values were found to be in good agreement, with a coefficient of determination (R 2) of 0.78 and a standard error of 0.05, while the R 2 for α was 0.68 with a standard error of 0.14.

Satellite monitoring of the biomass-burning aerosols during the wildfires of August 2007 in Greece: Climate implications

Abstract Biomass burning and associated emissions of aerosols into the atmosphere play a vital role in atmospheric composition and climate change. During summer of 2007, Greece faced the worst natural disaster recorded in recent decades in terms of human losses, number of fire outbreaks and extent of the estimated burned area (more than 12% of the total forested areas in Greece). The present study aims at analyzing the impact of these fire events in western Peloponnese on atmospheric aerosol concentrations using satellite data. MODIS-derived Aerosol Optical Depth (AOD), effective radius, Angstrom exponent, mass concentration, cloud-condensation nuclei (CCN) and OMI Aerosol Index (AI), single scattering albedo, absorption and extinction optical depths were analyzed. MODIS data showed smoke plumes traversing thousands of kilometers southwards influencing the central Mediterranean as well as the north African coastal regions. These thick smoke plumes dramatically affected AOD and aerosol-mass concentrations over the region and altered the microphysical aerosol properties, such as the effective radius and absorption coefficient. Model calculations suggested that the shortwave radiation at the ground was reduced by ∼50 Wm2, while that at the top of the atmosphere was reduced by ∼20 Wm2 resulting in atmospheric heating of ∼30 Wm2 over the areas affected by the smoke plumes.

Regional-scale relationships between aerosol and summer monsoon circulation, and precipitation over northeast Asia

We investigated the regional-scale relationships between columnar aerosol loads and summer monsoon circulation, and also the precipitation over northeast Asia using aerosol optical depth (AOD) data obtained from the 8-year MODIS, AERONET Sun/sky radiometer, and precipitation data acquired under the Global Precipitation Climatology Project (GPCP). These high-quality data revealed the regional-scale link between AOD and summer monsoon circulation, precipitation in July over northeast Asian countries, and their distinct spatial and annual variabilities. Compared to the mean AOD for the entire period of 2001–2008, the increase of almost 40–50% in the AOD value in July 2005 and July 2007 was found over the downwind regions of China (Yellow Sea, Korean peninsula, and East Sea), with negative precipitation anomalies. This can be attributable to the strong westerly confluent flows, between cyclone flows by continental thermal low centered over the northern China and anticyclonic flows by the western North Pacific High, which transport anthropogenic pollution aerosols emitted from east China to aforementioned downwind high AOD regions along the rim of the Pacific marine airmass. In July 2002, however, the easterly flows transported anthropogenic aerosols from east China to the southwestern part of China in July 2002. As a result, the AOD off the coast of China was dramatically reduced in spite of decreasing rainfall. From the calculation of the cross-correlation coefficient between MODIS-derived AOD anomalies and GPCP precipitation anomalies in July over the period 2001–2008, we found negative correlations over the areas encompassed by 105–115°E and 30–35°N and by 120–140°E and 35–40°N (Yellow Sea, Korean peninsula, and East Sea). This suggests that aerosol loads over these regions are easily influenced by the Asian monsoon flow system and associated precipitation.

Synergy between CALIOP and MODIS instruments for aerosol monitoring: application to the Po Valley

Abstract. In this study aerosol optical properties are studied over the Po Valley from June 2006 to February 2009 using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIPSO/CALIOP) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra. The choice of the Po valley has been driven by the numerous occurrences of pollutant events leading to a mean MODIS-derived aerosol optical depth (AOD) of 0.27 (±0.17) at 550 nm over a large area of ~120 000 km2. AOD derived from MODIS, AERONET and CALIOP have been compared. The comparison with AERONET sun-photometers has highlighted an overestimation of AOD from MODIS radiometers of 0.047 for Aqua and 0.088 for Terra. A systematic underestimation of AOD derived from CALIOP Level-2 products has been observed in comparison to Aqua (0.060) and Terra (0.075) MODIS values. Considering those discrepancies a synergistic approach combining CALIOP level-1 data and MODIS AOD has been developed for the first time over land to retrieve the equivalent extinction-to-backscatter ratio at 532 nm (LR). MODIS-derived AOD were indeed used to constrain CALIOP profiles inversion. A significant number of CALIOP level-1 vertical profiles have been averaged (~200 individual laser shots) in the Po Valley, leading to a signal-to-noise ratio (SNR) higher than 10 in the planetary boundary layer (PBL), which is sufficient to invert the mean lidar profiles. The mean LR (together with the associated variabilities) over the Po Valley retrieved from the coupling between CALIOP/MODIS-Aqua and CALIOP/MODIS-Terra are ~78±22 sr and ~86±27 sr, respectively. The total uncertainty on LR retrieval has been assessed to be ~12 sr using a Monte Carlo approach. The mean LR determined from a look-up table through a selection algorithm in CALIOP level 2 operational products (~63±8 sr) show a good agreement for daytime inversion (70±11 sr for Aqua and 74±14 sr for Terra). These values appear close to what is expected for pollution aerosols in an urban area. Contrarily large differences are observed when considering nighttime CALIOP profiles inverted with daytime AOD from MODIS (63±7 sr for CALIOP level-2 compared with 89±28 sr for CALIOP/Aqua and 103±32 sr for CALIOP/Terra synergies). They can be explained by a significant evolution of AOD between lidar and radiometer passing times. In most of cases, the mean aerosol extinction coefficient in the PBL significantly differs between the level-2 operational products and the result CALIPSO/MODIS synergy results. Mean differences of 0.10 km−1 (~50%) and 0.13 km−1 (~60%) have indeed been calculated using MODIS-Aqua/CALIOP and MODIS-Terra/CALIOP coupling studies, respectively. Such differences may be due to the identification of the aerosol model by the operational algorithm and thus to the choice of the LR.