Browsing by Author "Alaa Mhawish"

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Aerosol characteristics from earth observation systems: A comprehensive investigation over South Asia (2000–2019)
(Elsevier Inc., 2021) Alaa Mhawish; Meytar Sorek-Hamer; Robert Chatfield; Tirthankar Banerjee; Muhammad Bilal; Manish Kumar; Chandan Sarangi; Meredith Franklin; Khang Chau; Michael Garay; Olga Kalashnikova
The present study summarizes two decades (2000–2019) of climatology and trends in aerosol loading and optical properties using a high spatial resolution data obtained from NASA's MODIS MAIAC and MISR aerosol products supplemented by moderate resolution aerosol data from OMI sensor over South Asia (SA). MISR AOD showed good agreement against AERONET AOD with 68.68% of the retrievals falling within the expected error and high Pearson's correlation coefficient (R = 0.83). The 20 years geometric mean of MAIAC and MISR AOD revealed higher loading of aerosols over the Indo-Gangetic Plain (IGP) and Eastern coast of India by 30% to 44% compared to the mean AOD over the entire SA. The highest mean AOD under cloud-free conditions was noted during monsoon season, followed by pre-monsoon, post-monsoon, and winter. The high contribution of coarse-mode AOD (cAOD) mainly from natural aerosol emission and small-mode AOD (sAOD) from local anthropogenic emissions are the main driver to high AOD in monsoon and pre-monsoon seasons. Besides, the presence of high humidity during the monsoon season favors the hygroscopic growth of the particles and leads to higher AOD values over SA. The high spatial resolutions of MODIS/MAIAC and MISR aerosol products enabled the identification of previously unobserved aerosol hotspots over Bihar, West Bengal, and the eastern Indian coastal state of Odisha, which is mainly dominated by small aerosol particles. The contributions of smaller aerosol particles to the total aerosol loading were found to be higher during post-monsoon and winter over most states in India, Nepal, and Bangladesh. In contrast, the contribution of coarser particles was higher over Pakistan during pre-monsoon and monsoon seasons. Smaller particles were predominantly retrieved over the Indian states dominated by mining industries, including Jharkhand and Odisha. A typical dominance of absorbing carbonaceous aerosols was also noted over the northwestern region of IGP during post-monsoon, which otherwise was mainly affected by mixed dust aerosols and carbonaceous aerosols in pre-monsoon and monsoon seasons. A statistically significant positive temporal trend in AOD was observed for the whole study period, over most of the SA region, which was influenced by the increase in small particles over India and Bangladesh. Urban/industrial weakly absorbing aerosols were found to be the main contributor to a similarly positive trend over Central India and East coast Indian states. Overall, recent advancements in high spatial resolution satellite-based aerosol optical properties showed good potential to identify the aerosol hotspots and constrain aerosol types across a highly polluted SA region. © 2021
Aerosol Climatology Over South and Southeast Asia: Aerosol Types, Vertical Profile, and Source Fields
(Blackwell Publishing Ltd, 2021) Tirthankar Banerjee; A.S. Shitole; Alaa Mhawish; A. Anand; R. Ranjan; Md F. Khan; T. Srithawirat; Mohd T. Latif; R.K. Mall
Aerosol climatology during typical haze dominating period over South and Southeast Asia was explored using several Earth-Observing A-Train satellite products retrieved in between 2010 and 2020. Comparatively high aerosol optical depth (AOD) with dominance of fine and UV-absorbing aerosols are noted across the Indo-Gangetic plain, South Asia (IGP; AOD: 0.58; UVAI: 0.74) against weak UV-absorbing fine aerosols over Southeast Asia (SEA; AOD: 0.26; UVAI: 0.07). Among inland IGP sites, decadal mean AOD resembles in Lahore (0.72 ± 0.45), Delhi (0.81 ± 0.46), Kanpur (0.84 ± 0.42), and Varanasi (0.78 ± 0.45); all exhibiting bimodal AOD distribution with a first peak in early November followed by a second in early January. In contrast, except mainland site Chiang Mai, all SEA maritime cities resemble in having typical September-October AOD peak, with the presence of fine and UV-neutral aerosols. Urban hotspots across IGP and SEA (except Dhaka, Chiang Mai) denote a spatially consistent minor increasing trend in AOD (0.2–1.8 × 10−2 year−1) while increase in UVAI is more prominent over upper IGP. Dust aerosols dominate only in Karachi (46%) against strong UV-absorbing smoke aerosols over rest of the IGP (71–91%), and UV-neutral smoke aerosols across SEA (84–92%). Vertical stratification of aerosol types is noted across IGP as in lower atmosphere (<4 km) polluted dust/urban aerosols remain abundant, with gradual decrease in dust aerosols from upper to lower IGP and consequent increase in smoke aerosols. At upper atmosphere (>4 km), however, dust aerosols clearly dominate. Over SEA, smoke are the most abundant aerosols across the atmospheric column followed by polluted dust. No evidence of intracontinental transport of aerosols from IGP to Southeast Asia or vice versa is, however, noted. © 2021. American Geophysical Union. All Rights Reserved.
Airborne particulate in Varanasi over middle Indo-Gangetic Plain: variation in particulate types and meteorological influences
(Springer International Publishing, 2017) Vishnu Murari; Manish Kumar; Alaa Mhawish; S.C. Barman; Tirthankar Banerjee
The variation in particulate mass and particulate types (PM2.5 and PM10) with respect to local/regional meteorology was analyzed from January to December 2014 (n = 104) for an urban location over the middle Indo-Gangetic Plain (IGP). Both coarser (mean ± SD; PM10 161.3 ± 110.4 μg m−3, n = 104) and finer particulates (PM2.5 81.78 ± 66.4 μg m−3) revealed enormous mass loading with distinct seasonal effects (range: PM10 12–535 μg m−3; PM2.5 8–362 μg m−3). Further, 56% (for PM2.5) to 81% (for PM10) of monitoring events revealed non-attainment national air quality standard especially during winter months. Particulate types (in terms of PM2.5/PM10 0.49 ± 0.19) also exhibited temporal variations with high PM2.5 loading particularly during winter (0.62) compared to summer months (0.38). Local meteorology has clear distinguishing trends in terms of dry summer (March to June), wet winter (December to February), and monsoon (July to September). Among all the meteorological variables (average temperature, rainfall, relative humidity (RH), wind speed (WS)), temperature was found to be inversely related with particulate loading (rPM10 −0.79; rPM2.5 −0.87) while RH only resulted a significant association with PM2.5 during summer (rPM10 0.07; rPM2.5 0.55) and with PM10 during winter (rPM10 0.53; rPM2.5 0.24). Temperature, atmospheric boundary layer (ABL), and RH were cumulatively recognized as the dominant factors regulating particulate concentration as days with high particulate loading (PM2.5 >150 μg m−3; PM10 >260 μg m−3) appeared to have lower ABL (mean 660 m), minimum temperature (<22.6 °C), and high RH (∼79%). The diurnal variations of particulate ratio were mostly insignificant except minor increases during night having a high wintertime ratio (0.58 ± 0.07) over monsoon (0.34 ± 0.05) and summer (0.30 ± 0.07). Across the region, atmospheric visibility appeared to be inversely associated with particulate (rPM2.5 −0.84; rPM10 −0.79) for all humid conditions, while at RH ≥80%, RH appeared as the most dominant factor in regulating visibility compared to particulate loading. The Lagrangian particle dispersion model was further used to identify possible regions contributing particulate loading through regional/transboundary movement. © 2017, Springer International Publishing Switzerland.
Association of aerosols, trace gases and black carbon with mortality in an urban pollution hotspot over central Indo-Gangetic Plain
(Elsevier Ltd, 2021) Nidhi Singh; Alaa Mhawish; Tirthankar Banerjee; Santu Ghosh; R.S. Singh; R.K. Mall
The short term effect of multiple air pollutants e.g. aerosols (black carbon, BC; PM2.5 and PM10) and trace gases (NO2, SO2, and O3) on all-cause mortality was systematically investigated in a typical urban pollution hotspot over central Indo-Gangetic Plain (IGP). To our knowledge, this would be the first report of mortality estimates for exposure to BC aerosols and multiple trace gases over South Asia. Daily all-cause mortality and ambient air quality were analyzed from 2009 to 2016 following a semiparametric quasi-Poisson regression model adjusting mean temperature (Tmean), relative humidity (RH), and long term time trend (Time) as potential confounders. Single pollutant model clearly established the significant impact of BC aerosols (against 10-unit increase in pollutant; 4.95%, 95% CI: 2.16–7.74), NO2 (2.38%, 95% CI: 0.88–3.87%) and PM2.5 exposure (1.06%, 95% CI: 0.45–1.66%) on mortality. The inclusion of co-pollutants in the multi-pollutant model increased the individual mortality risks for BC aerosols (7.3%). Mortality estimates were further stratified considering different effect modifiers viz. sex, age, place of death, and season. Almost in all the cases statistically insignificant differences in effect modification were noted for all the pollutants except PM10. We also explored a distributed lag nonlinear model to estimate the lag effect and all the pollutants showed significant lag up to 3 days while BC showed lag effect up to 5 days. The exposure-response curves for individual air pollutants were mostly linear, while a considerable increase in mortality was noted for an exposure >15 μg m−3 for BC aerosols and >60 μg m−3 for PM2.5. The effect estimates of air pollutants during haze and no-haze days were also defined. During haze days, mortality rose to 6.11% and 3.06% for each 10-unit increase in BC and NO2 exposure, respectively. Significant effect of BC aerosol exposure on human mortality was established which reaffirms its inclusion as a potential health regulator for epidemiological studies. © 2020 Elsevier Ltd
Attributing mortality from temperature extremes: A time series analysis in Varanasi, India
(Elsevier B.V., 2019) Nidhi Singh; Alaa Mhawish; Santu Ghosh; Tirthankar Banerjee; R.K. Mall
Climate extremes are often associated with increased human mortality and such association varies considerably with space and time. We therefore, aimed to systematically investigate the effects of temperature extremes, daily means and diurnal temperature variations (DTV) on mortality in the city of Varanasi, India during 2009–2016. Time series data on daily mortality, air quality (SO 2 , NO 2 , O 3 and PM 10 ) and weather variables were obtained from the routinely collected secondary sources. A semiparametric quasi-Poisson regression model estimated the effects of temperature extremes on daily all-cause mortality adjusting nonlinear confounding effects of time trend, relative humidity and air pollution; stratified by seasons. An effect modification by age, gender and place of death as semi-economic indicator were also explored. Daily mean temperature was strongly associated with excess mortality, both during summer (5.61% with 95% CI: 4.69–6.53% per unit increase in mean temperature) and winter (1.53% with 95% CI: 0.88–2.18% per unit decrease in mean temperature). Daily mortality was found to be increased by 12.02% (with 95% CI: 4.21–19.84%) due to heat wave. The DTV has exhibited downward trend over the years and showed a negative association with all-cause mortality. Significant association of mortality and different metric of temperature extreme along with decreasing trend in DTV clearly indicate the potential impact of climate change on human health in the city of Varanasi. The finding may well be useful to prioritize the government policies to curb the factors that causes the climate change and for developing early warning system. © 2019 Elsevier B.V.
Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia
(Elsevier Inc., 2019) Alaa Mhawish; Tirthankar Banerjee; Meytar Sorek-Hamer; Alexei Lyapustin; David M. Broday; Robert Chatfield
The Multiangle Implementation of Atmospheric Correction (MAIAC) is a new generic algorithm applied to collection 6 (C6) MODIS measurements to retrieve Aerosol Optical Depth (AOD) over land at high spatial resolution (1 km). This study is the first evaluation of the MAIAC AOD from MODIS Aqua (A) and Terra (T) satellites between 2006 and 2016 over South Asia. The retrieval accuracy of MAIAC was assessed by comparing it to ground-truth AErosol RObotic NETwork (AERONET) AOD, as well as to AOD retrieved by the two operational MODIS algorithms: Dark Target (DT) and Deep Blue (DB). MAIAC AOD showed higher spatial coverage and retrieval frequency than either the DT or the DB AOD retrievals. The high spatial resolution of the MAIAC retrievals enhances the capability to distinguish aerosol sources and to determine fine aerosol features, such as wildfire smoke plumes and haze over complex geographical regions, and provides more retrievals in conditions that are cloudy or when the surface is partially covered by snow. In comparison to AERONET AOD, MAIAC AOD shows a better accuracy than both DT and DB AOD. A higher number of MAIAC-AERONET AOD matchups demonstrate the capability of MAIAC to retrieve AOD over varied surfaces, different aerosol types and loadings. Our results demonstrate high retrieval accuracy in term of the Expected Error (EE) (A/T, EE: 72.22%, 73.50%), and low root mean square error (A/T, RMSE: 0.148, 0.164), root mean bias (RMB) (A/T, RMB: 0.978, 1.049) and mean absolute error (MAE) (A/T, MAE: 0.098, 0.096). Moreover, MAIAC has a lower bias as a function of the viewing geometry and the aerosol type among the three retrieval algorithms. MAIAC performed well over bright and vegetated land surfaces, showing the highest retrieval accuracy over dense vegetation and particularly well in retrieving smoke AOD, yet it underestimated dust AOD. In conclusion, MAIAC's ability to provide AOD at high spatial resolution appears promising over South Asia, thus having advantage over contemporary aerosol retrieval algorithms for epidemiological and climatological studies. Capsule: In comparison with MODIS DT and DB AOD, and AERONET AOD, MAIAC shows improved accuracy and lower bias over South Asia, as well as with greater spatial coverage. © 2019 Elsevier Inc.
Estimation of High-Resolution PM2.5over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables
(American Chemical Society, 2020) Alaa Mhawish; Tirthankar Banerjee; Meytar Sorek-Hamer; Muhammad Bilal; Alexei I. Lyapustin; Robert Chatfield; David M. Broday
Very high spatially resolved satellite-derived ground-level concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) have multiple potential applications, especially in air quality modeling and epidemiological and climatological research. Satellite-derived aerosol optical depth (AOD) and columnar water vapor (CWV), meteorological parameters, and land use data were used as variables within the framework of a linear mixed effect model (LME) and a random forest (RF) model to predict daily ground-level concentrations of PM2.5 at 1 km × 1 km grid resolution across the Indo-Gangetic Plain (IGP) in South Asia. The RF model exhibited superior performance and higher accuracy compared with the LME model, with better cross-validated explained variance (R2 = 0.87) and lower relative prediction error (RPE = 24.5%). The RF model revealed improved performance metrics for increasing averaging periods, from daily to weekly, monthly, seasonal, and annual means, which supported its use in estimating PM2.5 exposure metrics across the IGP at varying temporal scales (i.e., both short and long terms). The RF-based PM2.5 estimates showed high PM2.5 levels over the middle and lower IGP, with the annual mean exceeding 110 μg/m3. As for seasons, winter was the most polluted season, while monsoon was the cleanest. Spatially, the middle and lower IGP showed poorer air quality compared to the upper IGP. In winter, the middle and lower IGP experienced very poor air quality, with mean PM2.5 concentrations of >170 μg/m3. Copyright © 2020 American Chemical Society.
Evaluation of MODIS Collection 6 aerosol retrieval algorithms over Indo-Gangetic Plain: Implications of aerosols types and mass loading
(Elsevier Inc., 2017) Alaa Mhawish; Tirthankar Banerjee; David M. Broday; Amit Misra; Sachchida N. Tripathi
This study evaluates the performance of MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6) AOD retrieval algorithms, including Dark Target (DT) aerosol optical depth (AOD) at 3 and 10 km spatial resolutions, Deep Blue (DB) AOD at 10 km, and the merged DT-DB AOD at 10 km across the Indo-Gangetic Plain (IGP), South Asia. A total of 14,736 collocated Aqua MODIS C6 AOD at 550 nm were evaluated against AOD from six AERONET stations over IGP, measured during the satellite overpass (± 1 h) from 2006 to 2015. The effects of aerosol heterogeneity, in terms of both aerosol loading and the aerosol type, on the uncertainty of the satellite-borne AOD retrieval were examined. The DT algorithm at both resolutions (3 km and 10 km) overestimated the AOD by 14–25%, with only 51.37–61.29% of the retrievals falling within the expected error (EE). The DT 3 km algorithm underestimates the surface reflectance in comparison to the DT 10 km, with the latter outperforming the former both in terms of number of collocations and retrieval accuracy, especially over urban areas. The DB 10 km was able to retrieve AOD over both arid/desert regions and vegetated surfaces even under low aerosol loading conditions. Yet, its performance was still poor, with retrieval accuracy of 53.76%, low RMSE (0.214), and generally underestimated AOD across the IGP. The merged DT-DB AOD product was mostly dominated by DT retrievals (73%–100%), except over bright land surfaces and 56.03% of the merged DT-DB retrievals fell within the EE. The retrieval accuracy of MODIS C6 products was found to be strongly dependent on the estimated surface reflectance and the aerosol type. Across IGP, DB predicted the surface reflectance better while DT at both resolutions overestimated the surface reflectance at varying extent. For high aerosol loading conditions with varying aerosol size, retrieval accuracy of DT 10 km poses lower sensitivity while DT at 3 km exhibits larger uncertainty in estimating surface reflectance. In contrast, DB 10 km shows greater bias that depends on the aerosol size. For very high aerosol loading conditions, dominated by fine or mixed aerosols, all the algorithms have errors in the aerosol model. The DT 10 km, DB 10 km and the merged AOD performed almost equally within the threshold level while the DT 3 km showed the poorest performance in terms of retrieval accuracy and RMSE. We conclude that across IGP, DB 10 km AOD has the highest accuracy in retrieving fine mode aerosols while DT 10 km AOD has almost identical accuracy in retrieving varying aerosol types. For coarse dominated aerosols, when the dissimilarity between DT and DB remains highest, the merged AOD is found to have higher accuracy in retrieving AOD across IGP. © 2017 Elsevier Inc.
Impact of environmental attributes on the uncertainty in MAIAC/MODIS AOD retrievals: A comparative analysis
(Elsevier Ltd, 2021) Somaya Falah; Alaa Mhawish; Meytar Sorek-Hamer; Alexei I. Lyapustin; Itai Kloog; Tirthankar Banerjee; Fadi Kizel; David M. Broday
This work examines the impact of different environmental attributes on the uncertainty in satellite-based Aerosol Optical Depth (AOD) retrieval against the benchmark Aerosol Robotic Network (AERONET) AOD measurements at 21 sites across North Africa, California and Germany, in the years 2007–2017. As a first step, we studied the effects of spatial averaging the Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD retrievals, and of temporal averaging the AERONET AOD around the satellite (Aqua) overpass, on the agreement between the two products. AERONET AOD averaging over a time-window of ±15 min around the satellite overpass and the 1 × 1 km2 spatial grid of MAIAC were found to provide the best AOD retrieval performance. Next, MAIAC AOD were stratified according to different co-measured environmental attributes (aerosol loading, dominant particle size, vegetation cover, and prevailing particle type) and analyzed against the AERONET AOD. The envelope of the expected retrieval error varied considerably among different environmental attributes categories, with more accurate AOD retrievals obtained over highly vegetated areas (i.e. less surface reflectance) than over arid areas. Moreover, the retrieval accuracy was found to be sensitive to the aerosol loading and particle size, with a large bias between the MAIAC and AERONET AOD during high aerosol loading of coarse particles. In addition, the retrieval accuracy of MAIAC AOD was found to depend on the aerosol type due to the aerosol model assumptions regarding their optical properties. © 2021 Elsevier Ltd
Intercomparison of Aerosol Types Reported as Part of Aerosol Product Retrieval over Diverse Geographic Regions
(MDPI, 2022) Somaya Falah; Alaa Mhawish; Ali H. Omar; Meytar Sorek-Hamer; Alexei I. Lyapustin; Tirthankar Banerjee; Fadi Kizel; David M. Broday
This study examines uncertainties in the retrieval of the Aerosol Optical Depth (AOD) for different aerosol types, which are obtained from different satellite-borne aerosol retrieval products over North Africa, California, Germany, and India and Pakistan in the years 2007–2019. In particular, we compared the aerosol types reported as part of the AOD retrieval from MODIS/MAIAC and CALIOP, with the latter reporting richer aerosol types than the former, and from the Ozone Monitoring Instrument (OMI) and MODIS Deep Blue (DB), which retrieve aerosol products at a lower spatial resolution than MODIS/MAIAC. Whereas MODIS and OMI provide aerosol products nearly every day over of the study areas, CALIOP has only a limited surface footprint, which limits using its data products together with aerosol products from other platforms for, e.g., estimation of surface particulate matter (PM) concentrations. In general, CALIOP and MAIAC AOD showed good agreement with the AERONET AOD (r: 0.708, 0.883; RMSE: 0.317, 0.123, respectively), but both CALIOP and MAIAC AOD retrievals were overestimated (36–57%) with respect to the AERONET AOD. The aerosol type reported by CALIOP (an active sensor) and by MODIS/MAIAC (a passive sensor) were examined against aerosol types derived from a combination of satellite data products retrieved by MODIS/DB (Angstrom Exponent, AE) and OMI (Aerosols Index, AI, the aerosol absorption at the UV band). Together, the OMI-DB (AI-AE) classification, which has wide spatiotemporal cover, unlike aerosol types reported by CALIOP or derived from AERONET measurements, was examined as auxiliary data for a better interpretation of the MAIAC aerosol type classification. Our results suggest that the systematic differences we found between CALIOP and MODIS/MAIAC AOD were closely related to the reported aerosol types. Hence, accounting for the aerosol type may be useful when predicting surface PM and may allow for the improved quantification of the broader environmental impacts of aerosols, including on air pollution and haze, visibility, climate change and radiative forcing, and human health. © 2022 by the authors.
Organic aerosols over Indo-Gangetic Plain: Sources, distributions and climatic implications
(Elsevier Ltd, 2017) Nandita Singh; Alaa Mhawish; Karine Deboudt; R.S. Singh; Tirthankar Banerjee
Organic aerosol (OA) constitutes a dominant fraction of airborne particulates over Indo-Gangetic Plain (IGP) especially during post-monsoon and winter. Its exposure has been associated with adverse health effects while there are evidences of its interference with Earth's radiation balance and cloud condensation (CC), resulting possible alteration of hydrological cycle. Therefore, presence and effects of OA directly link it with food security and thereby, sustainability issues. In these contexts, atmospheric chemistry involving formation, volatility and aging of primary OA (POA) and secondary OA (SOA) have been reviewed with specific reference to IGP. Systematic reviews on science of OA sources, evolution and climate perturbations are presented with databases collected from 82 publications available throughout IGP till 2016. Both gaseous and aqueous phase chemical reactions were studied in terms of their potential to form SOA. Efforts were made to recognize the regional variation of OA, its chemical constituents and sources throughout IGP and inferences were made on its possible impacts on regional air quality. Mass fractions of OA to airborne particulate showed spatial variation likewise in Lahore (37 and 44% in fine and coarse fractions, respectively), Patiala (28 and 37%), Delhi (25 and 38%), Kanpur (24 and 30%), Kolkata (11 and 21%) and Dhaka. Source apportionment studies indicate biomass burning, coal combustion and vehicular emissions as predominant OA sources. However, sources represent considerable seasonal variations with dominance of gasoline and diesel emissions during summer and coal and biomass based emissions during winter and post-monsoon. Crop residue burning over upper-IGP was also frequently held responsible for massive OA emission, mostly characterized by its hygroscopic nature, thus having potential to act as CC nuclei. Conclusively, climatic implication of particulate bound OA has been discussed in terms of its interaction with radiation balance. © 2017 Elsevier Ltd
Remote Sensing of Aerosols From Space: Retrieval of Properties and Applications
(Elsevier Inc., 2018) Alaa Mhawish; Manish Kumar; Akhila K. Mishra; Prashant K. Srivastava; Tirthankar Banerjee
Atmospheric aerosols are multicomponent mixtures typically composed of liquid and/or solid particles suspended in the atmosphere. Aerosols originate from numerous sources, having successively evolved through various microphysical processes before being removed either by wet or dry depositions. The implications of these airborne particulates on the regional and global climate are many but most notably through regulating the atmospheric heat budget either by absorbing/scattering insolation or by modifying cloud microphysical properties. Global distributions of aerosols are typically regional; thereby, they pose a strong regional signature that induces additional uncertainties in estimating aerosols, induced climate forcing. Satellite remote sensing of aerosols has extensive applications in identifying aerosol columnar properties, especially in terms of optical depth, composition, morphology, and vertical distribution. This ultimately provides evidence in establishing the source-transport-receptor relations of aerosols over a synoptic scale. Further, satellite data of atmospheric compositions are often used for identifying pollutant emissions, transboundary movement, forecasting air quality, and, more recently, in associating air quality with human health. The principles of remote sensing of aerosols are quite different from that of trace gases as the extinction of light by aerosols is a function of wavelength. With the gradual advancement of sensing technologies, monitoring of atmospheric aerosols has become more precise. Therefore, it has become more widely applied in various academic disciplines, studies, policies, and decision-making processes. This article emphasizes the state of the art in the field of satellite remote sensing, specifically in terms of polar-orbiting satellites for tropospheric aerosols including both active- and passive-based observations; associated complexities and uncertainties; brief descriptions of data products; and the subsequent applications in climate science. © 2018 Elsevier Inc. All rights reserved.
Three-dimensional nature of summertime aerosols over South Asia
(Elsevier B.V., 2022) Abhishek Singh; Avinash Anchule; Tirthankar Banerjee; Kumari Aditi; Alaa Mhawish
Three-dimensional (temporal-spatial-vertical) climatology of South Asian summertime (MAMJ, 2010–2019) aerosols and aerosol sub-types was explored using multiple high-resolution satellite-based observations and reanalysis dataset. Vertical stratification of aerosol layer and aerosol sub-types was identified using observation from space-borne lidar. Aerosol optical depth (AOD) was particularly high across the Indo-Gangetic Plain (IGP; AOD ± SD: 0.56 ± 0.12) and over eastern coast of India (AOD: 0.6–0.8), with prevalence of heterogeneous aerosol sub-types having strong spatial gradient. Clearly, aerosols over north-western arid part were highly absorbing (Ultra-violet Aerosol Index, UVAI > 0.80) and coarse (Ångström exponent, AE < 0.8), with an indication of desert/−mineral dust aerosols. In contrast, fine and moderate to non-absorbing aerosols (UVAI: 0.20–0.50) dominate from central to lower IGP, including in Bangladesh, with signature of anthropogenic emissions. Prevailing aerosols over twelve South Asian cities were classified into six aerosol sub-types constraining their particle size and UV-absorbing potential. Overall, mineral dust, smoke and urban aerosols were the three major aerosol sub-types that prevail across South Asia during summer. In particular, 58–70 % of retrieval days over Karachi and Multan were dust dominated; 57–64 % days were dust or urban aerosols dominated over Lahore, Delhi, Kanpur and Varanasi, and 56–77 % days were smoke or urban aerosols dominated over Dhaka, Kathmandu, Chennai, Mumbai, Colombo and Nagpur. Prevailing aerosols were vertically stratified as 50–70 % of total AOD was retrieved <2 km from the surface except in few cities where 70–80 % of AOD was retrieved <3 km height. Mineral dust and/or urban aerosols emerged as the most abundant aerosol types near the surface (<1 km) in all the cities except in Chennai, with their abundance remained as a function of emission sources and geographical location. © 2022 Elsevier B.V.
Vertical distribution of smoke aerosols over upper Indo-Gangetic Plain
(Elsevier Ltd, 2020) K.S. Vinjamuri; Alaa Mhawish; Tirthankar Banerjee; Meytar Sorek-Hamer; David M. Broday; Rajesh K. Mall; Mohd Talib Latif
Attenuated backscatter profiles retrieved by the space borne active lidar CALIOP on-board CALIPSO satellite were used to measure the vertical distribution of smoke aerosols and to compare it against the ECMWF planetary boundary layer height (PBLH) over the smoke dominated region of Indo-Gangetic Plain (IGP), South Asia. Initially, the relative abundance of smoke aerosols was investigated considering multiple satellite retrieved aerosol optical properties. Only the upper IGP was selectively considered for CALIPSO retrieval based on prevalence of smoke aerosols. Smoke extinction was found to contribute 2–50% of the total aerosol extinction, with strong seasonal and altitudinal attributes. During winter (DJF), smoke aerosols contribute almost 50% of total aerosol extinction only near to the surface while in post-monsoon (ON) and monsoon (JJAS), relative contribution of smoke aerosols to total extinction was highest at about 8 km height. There was strong diurnal variation in smoke extinction, evident throughout the year, with frequent abundance of smoke particles at lower height (<4 km) during daytime compared to higher height during night (>4 km). Smoke injection height also varied considerably during rice (ON: 0.71 ± 0.65 km) and wheat (AM: 2.34 ± 1.34 km) residue burning period having a significant positive correlation with prevailing PBLH. Partitioning smoke AOD against PBLH into the free troposphere (FT) and boundary layer (BL) yield interesting results. BL contribute 36% (16%) of smoke AOD during daytime (nighttime) and the BL-FT distinction increased particularly at night. There was evidence that despite travelling efficiently to FT, major proportion of smoke AOD (50–80%) continue to remain close to the surface (<3 km) thereby, may have greater implications on regional climate, air quality, smoke transport and AOD-particulate modelling. Smoke aerosols were most abundant over upper Indo-Gangetic Plain and 50–80% of smoke AOD remain close (<3 km) to the surface. © 2019 Elsevier Ltd
Vertical Profiling of Aerosol and Aerosol Types Using Space-Borne Lidar
(Springer Nature, 2020) Alaa Mhawish; K.S. Vinjamuri; Nandita Singh; Manish Kumar; Tirthankar Banerjee
Aerosol remote sensing has become a powerful tool to characterize the optical and microphysical properties of aerosols. Several satellite sensors such as MODIS, MISR, OMI, Tropomi and PARASOL utilize the solar electromagnetic radiation for retrieving aerosol properties from space. These instruments have high spatial coverage and can provide aerosol properties globally on a repeated basis. However, these passive sensors mostly lack the information regarding vertical distribution of aerosol and its types. Using active remote sensing technique however, provide valuable information to understand the vertical distribution of aerosols which is very useful to predict the lifetime of atmospheric aerosols, long-range transport and subsequent interaction with cloud droplets. CALIOP is an active sensor flying on board CALIPSO satellite provide height-dependent aerosol extinction repeatedly on a global basis. CALIOP aerosol retrieval algorithm retrieves aerosol information in 5 km horizontal resolution and 30–60 m vertical resolution. The latest updated CALIOP aerosol retrieval algorithm version 4 (V4) has the ability to identify ten aerosol subtypes; six for tropospheric aerosols and four for stratospheric aerosols. In this context, the annual, seasonal and diurnal variation of smoke aerosol have been investigated over central Indo-Gangetic Plain (IGP), South Asia using ten years V4 CALIOP profile data. We noted that for all the seasons, the highest smoke aerosol extinction observed near surface and contributed 40–60% to the total aerosol extinction during winter (DJF) and postmonsoon seasons (ON). In premonsoon (MAM) and monsoon (JJAS) seasons the highest contribution of smoke to the total extinction coefficient found at relatively higher altitude (premonsoon: 60% at 7–9 km, monsoon: 75% at 5–8 km). The day-night occurrence frequency of smoke aerosol found higher during the day time in winter at 4 km, while during monsoon the occurrence of the smoke was found higher at night time. © 2020, Springer Nature Singapore Pte Ltd.