Changes in aerosol properties at the El Arenosillo site in Southern Europe as a result of the 2023 Canadian forest fires

From the beginning of May 2023 to the end of August 2023, the Northern Hemisphere experienced significant wildfire activity with the most widespread fires occurring in Canada. Forest fires in Canada destroyed more than 15.6 million hectares of forests. These wildfires worsened air quality across the region and other parts of the world. The smoke reached southern Europe by the end of June 2023. To better understand the consequences of such forest fires far from the site of origin, aerosol optical, microphysical and radiative properties were analyzed during this event for southern Europe using data from the Visible Infrared Imaging Radiometer Suite (VIIRS), TROPOspheric Monitoring Instrument (TROPOMI), and Aerosol Robotic Network (AERONET). TROPOMI aerosol index (AI) and the carbon monoxide (CO) product confirm that the smoke originated directly from these forest fires. AERONET data from the El Arenosillo site in southern Spain showed maximum aerosol optical depth (AOD) values on June 27 reached 2.36. Data on Angstrom Exponent (AE), aerosol volume size distribution (VSD), single scattering albedo (SSA), fine mode fraction (FMF), volume particle concentration, effective radius (REff), absorption AOD (AAOD), extinction AE (EAE) and absorption AE (AAE) showed that fine-mode particles with carbonaceous aerosols contribution predominated in the atmosphere above the El Arenosillo site. Direct aerosol radiative forcing (DARF) at the top (DARFTOA) and bottom of atmosphere (DARFBOA) were -103.1 and -198.93 Wm-2, respectively. The atmospheric aerosol radiative forcing (DARFATM) was found to be 95.83 Wm-2 and with a heating rate 2.69 K day-1, which indicates the resulting warming of the atmosphere.

An improved meteorological variables-based aerosol optical depth estimation method by combining a physical mechanism model with a two-stage model

A two-stage model integrating a spatiotemporal linear mixed effect (STLME) and a geographic weight regression (GWR) model is proposed to improve the meteorological variables-based aerosol optical depth (AOD) retrieval method (Elterman retrieval model-ERM). The proposed model is referred to as the STG-ERM model. The STG-ERM model is applied over the Beijing-Tianjin-Hebei (BTH) region in China for the years 2019 and 2020. The results show that data coverage increased by 39.0% in 2019 and 40.5% in 2020. Cross-validation of the retrieval results versus multi-angle implementation of atmospheric correction (MAIAC) AOD shows the substantial improvement of the STG-ERM model over earlier meteorological models for AOD estimation, with a determination coefficient (R2) of daily AOD of 0.86, root mean squared prediction error (RMSE) and the relative prediction error (RPE) of 0.10 and 36.14% in 2019 and R2 of 0.86, RMSE of 0.12 and RPE of 37.86% in 2020. The fused annual mean AOD indicates strong spatial variation with high value in south plain and low value in northwestern mountainous areas of the BTH region. The overall spatial seasonal mean AOD ranges from 0.441 to 0.586, demonstrating strongly seasonal variation. The coverage of STG-ERM retrieved AOD, as determined in this exercise by leaving out part of the meteorological data, affects the accuracy of fused AOD. The coverage of the meteorological data has smaller impact on the fused AOD in the districts with low annual mean AOD of less than 0.35 than that in the districts with high annual mean AOD of greater than 0.6. If available, continuous daily meteorological data with high spatiotemporal resolution can improve the model performance and the accuracy of fused AOD. The STG-ERM model may serve as a valuable approach to provide data to fill gaps in satellite-retrieved AOD products.

Quality Assessment and Application Scenario Analysis of AGRI Land Aerosol Product from the Geostationary Satellite Fengyun-4B in China

The Advanced Geostationary Radiation Imager (AGRI) sensor on board the geostationary satellite Fengyun-4B (FY-4B) is capable of capturing particles in different phases in the atmospheric environment and acquiring aerosol observation data with high spatial and temporal resolution. To understand the quality of the Land Aerosol (LDA) product of AGRI and its application prospects, we conducted a comprehensive evaluation of the AGRI LDA AOD. Using the 550 nm AGRI LDA AOD (550 nm) of nearly 1 year (1 October 2022 to 30 September 2023) to compare with the Aerosol Robotic Network (AERONET), MODIS MAIAC, and Himawari-9/AHI AODs. Results show the erratic algorithmic performance of AGRI LDA AOD, the correlation coefficient (R), mean error (Bias), root mean square error (RMSE), and the percentage of data with errors falling within the expected error envelope of ±(0.05+0.15×AODAERONET) (within EE15) of the LDA AOD dataset are 0.55, 0.328, 0.533, and 34%, respectively. The LDA AOD appears to be overestimated easily in the southern and western regions of China and performs poorly in the offshore areas, with an R of 0.43, a Bias of 0.334, a larger RMSE of 0.597, and a global climate observing system fraction (GCOSF) percentage of 15% compared to the inland areas (R = 0.60, Bias = 0.163, RMSE = 0.509, GCOSF = 17%). Future improvements should focus on surface reflectance calculation, water vapor attenuation, and more suitable aerosol model selection to improve the algorithm's accuracy.

Land surface temperature and transboundary air pollution: a case of Bangkok Metropolitan Region

In a rapidly urbanizing world, heavy air pollution and increasing surface temperature pose significant threats to human health and lives, especially in densely populated cities. In this study, we took an information theory perspective to investigate the causal relationship between diel land surface temperature (LST) and transboundary air pollution (TAP) from 2003 to 2020 in the Bangkok Metropolitan Region (BMR), which includes Bangkok Metropolis and its five adjacent provinces. We found an overall increasing trend of LST over the study region, with the mean daytime LST rising faster than nighttime LST. Evident seasonal variations showed high aerosol optical depth (AOD) loadings during the dry period and low loadings at the beginning of the rainy season. Our study revealed that TAP affected diel surface temperature in Bangkok Metropolis significantly. Causality tests show that air pollutants of two adjacent provinces west of Bangkok, i.e., Nakhon Pathom and Samut Sakhon, have a greater influence on the LST of Bangkok than other provinces. Also, the bidirectional relationship indicates that air pollution has a greater impact on daytime LST than nighttime LST. While LST has an insignificant influence on AOD during the daytime, it influences AOD significantly at night. Our study offers a new approach to understanding the causal impact of TAP and can help policymakers to identify the most relevant locations that cause pollution, leading to appropriate planning and management.

Influence of industrial sustainability transition on air quality in a typical resource-exhausted city

The industrial transition of resource-exhausted cities is the focus of attention, and air quality has naturally become an important indicator to measure the sustainable development quality. Aerosol optical depth (AOD) is an important parameter to indicate air quality. This paper aimed to study the influence of industrial transition on air quality and provide a list of recommendations and management strategies for sustainable development in resource-exhausted cities. Results showed the secondary industry played important roles for economic development before 2015, however, it decreased after 2014, and the tertiary industry played more and more important roles from 2015. Analyses of the spatial distribution of AOD in each year showed that AOD was relatively higher in urban areas with concentrated population, and the threshold range of AOD value with high area ratio in spatial distribution decreased gradually, which was consistent with the analysis results of time series. Results of correlation analyses indicated that air temperature and land surface temperature were the main natural meteorological factors influencing AOD. Gross population, SO2 emission and the cultivated land area were the main socio-economic factors influencing AOD. It could be concluded that the industrial transition of the city has achieved good results, the economic structure has been gradually optimized and adjusted, and the air quality has gradually improved over industrial sustainability transition. Scientific exploitation, energy conservation, application of clean energy and industrial structure optimization would be effective measures for sustainable development.

Sources, variability, long-term trends, and radiative forcing of aerosols in the Arctic: implications for Arctic amplification

Atmospheric pollution in the Arctic has been an important driver for the ongoing climate change there. Increase in the Arctic aerosols causes the phenomena of Arctic haze and Arctic amplification. Our analysis of aerosol optical depth (AOD), black carbon (BC), and dust using ground-based, satellite, and reanalysis data in the Arctic for the period 2003-2019 shows that the lowest amount of all these is found in Greenland and Central Arctic. There is high AOD, BC, and dust in the northern Eurasia and parts of North America. All aerosols show their highest values in spring. Significant positive trends in AOD (> 0.003 year-1) and BC (0.0002-0.0003 year-1) are found in the northwestern America and northern Asia. Significant negative trends are observed for dust (- 0.0001 year-1) around Central Arctic. Seasonal analysis of AOD, BC, and dust reveals an increasing trend in summer and decreasing trend in spring in the Arctic. The major sources of aerosols are the nearby Europe, Russia, and North America regions, as assessed using the potential source contribution function (PSCF). Anthropogenic emissions from the transport, energy, and household sectors along with natural sources such as wildfires contribute to the positive trends of aerosols in the Arctic. These increasing aerosols in the Arctic influence Arctic amplification through radiative effects. Here, we find that the net aerosol radiative forcing is high in Central Arctic, Greenland, Siberia, and Canadian Arctic, about 2-4 W/m2, which can influence the regional temperature. Therefore, our study can assist policy decisions for the mitigation of Arctic haze and Arctic amplification in this environmental fragile region of the Earth.

Long-term observation of columnar aerosol optical properties over the remote South China Sea

The South China Sea (SCS) is a receptor of pollution sources from various parts of Asia and is heavily impacted by strong meteorological systems, which thus dictate aerosol variability over the region. This study analyzes long-term aerosol optical properties observed at Dongsha Island (a representative site in northern SCS) from 2009 to 2021 and Taiping Island (a representative site in southern SCS) from 2012 to 2021 to better apprehend the temporal evolution of columnar aerosols over the SCS. The noticeable difference in loadings, optical properties, and compositions of aerosols between northern and southern SCS was due to the influence of dissimilar emission sources and transport mechanisms. Column-integrated aerosol optical depth (AOD) over northern SCS (range of monthly mean at 500 nm; 0.12-0.51) was significantly greater than southern SCS (0.09-0.21). The maximum AOD in March (0.51 ± 0.28) at Dongsha was attributed to westerlies coupled with biomass-burning (BB) emissions from peninsular Southeast Asia, whereas the maximum AOD at Taiping in September (0.21 ± 0.25) was owing to various pollution from the Philippines, Malaysia, and Indonesia. Fine-mode aerosol dominated over northern SCS (range of monthly mean Angstrom exponent for 440-870 nm: 0.85-1.36) due to substantial influence from continental sources including anthropogenic and BB emissions while coarse-mode particles dominated over southern SCS (0.54-1.28) due to relatively more influence from marine source. More absorbing columnar aerosols prevailed over northern SCS (range of monthly mean single scattering albedo at 675 nm: 0.92-0.99) compared to southern SCS (0.95-0.98) owing to differences in aerosol composition with respect to sources. Special pollution events showcased possible significant impacts on marine ecosystems and regional climate. This study encourages the establishment of more ground-based aerosol monitoring networks and the inclusion of modeling simulations to comprehend the complex nature of aerosol over this vast marginal sea.

A gradual increase of aerosol pollution in the Third Pole during the past four decades: Implication for regional climate change

We analyse the long-term (1980-2020) changes in aerosols over the Third Pole (TP) and assess the changes in radiative forcing (RF) using satellite, ground-based and reanalysis data. The annual mean aerosol optical depth (AOD) varies from 0.06 to 0.24, with the highest values of around 0.2 in the north and southwest TP, which are dominated by dust from Taklimakan and Thar deserts, respectively. However, Organic Carbon (OC), Black Carbon (BC) and sulphate aerosols have significant contributions to the total AOD in the south and east TP. High amounts of dust are observed in spring and summer, but BC in winter. Trajectory analysis reveals that the air mass originated from East and South Asia carries BC and OC, whereas the air from South Asia, Central Asia and Middle East brings dust to TP. Significant positive trends in AOD is found in TP, with high values of about 0.002/yr in the eastern and southern TP. There is a gradual increase in BC and OC concentrations during 1980-2020, but the change from 2000 is phenomenal. The RF at the top of the atmosphere varies from -10 to 2 W/m2 in TP, and high positive RF of about 2 W/m2 is estimated in Pamir, Karakoram and Nyainquentanglha mountains, where the massive glacier mass exists. The RF has increased in much of TP during recent decades (2001-2020) with respect to previous decades (1981-2000), which can be due to the rise in BC and dust during the latter period. Therefore, the positive trend in BC and its associated change in RF can amplify the regional warming, and thus, the melting of glaciers or ice in TP. This is a great concern as it is directly connected to the water security of many South Asian countries.

Retrieval of nighttime aerosol optical depth by simultaneous consideration of artificial and natural light sources

Aerosol Optical Depth (AOD) is a critical optical parameter that quantifies the degree of light attenuation by aerosols and serves as a fundamental indicator of atmospheric quality. Therefore, accurate quantification and retrieval of AOD is crucial for relevant studies. However, current satellite-based AOD retrieval algorithms suffer from inapplicability under low-light conditions, limiting the development of nighttime AOD retrieval. Under this context, we proposed a novel algorithm, namely Simultaneous Consideration of Artificial and Natural light Sources (SCANS), to obtain nighttime AOD. The core of the SCANS algorithm is considering the synergy of both the natural and artificial light sources to obtain nighttime AOD by integrating atmospheric radiative transfer simulation into an extinction method and performing multiple iterations. SCANS was applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) and the retrieved nighttime AOD was validated with in-situ measurements from five AERONET sites. Results indicate that the Mean Bias Errors (MBEs) of the retrieved nighttime AOD range from 0.0 to 0.08 and the corresponding Root Mean Square Errors (RMSEs) range from 0.11 to 0.17, which exhibit better accuracy than that of the nighttime MERRA-2 AOD. We further compared the retrieved nighttime AOD with the corresponding Air Quality Index (AQI) measurements at six environment monitoring stations and obtained high correlation coefficients (i.e., ranging from 0.733 to 0.940), indicating SCANS's reliability and high accuracy. The proposed SCANS algorithm can effectively obtain nighttime AOD with high quality, thereby advancing research on the diurnal variation of crucial Earth's key elements.

Aerosols heat up the Himalayan climate

The impact of aerosols, especially the absorbing aerosols, in the Himalayan region is important for climate. We closely examine ground-based high-quality observations of aerosol characteristics including radiative forcing from several locations in the Indo-Gangetic Plain (IGP), the Himalayan foothills and the Tibetan Plateau, relatively poorly studied regions with several sensitive ecosystems of global importance, as well as highly vulnerable large populations. This paper presents a state-of-the-art treatment of the warming that arises from these particles, using a combination of new measurements and modeling techniques. This is a first-time analysis of its kind, including ground-based observations, satellite data, and model simulations, which reveals that the aerosol radiative forcing efficiency (ARFE) in the atmosphere is clearly high over the IGP and the Himalayan foothills (80-135 Wm-2 per unit aerosol optical depth (AOD)), with values being greater at higher elevations. AOD is >0.30 and single scattering albedo (SSA) is ∼0.90 throughout the year over this region. The mean ARFE is 2-4 times higher here than over other polluted sites in South and East Asia, owing to higher AOD and aerosol absorption (i.e., lower SSA). Further, the observed annual mean aerosol-induced atmospheric heating rates (0.5-0.8 Kelvin/day), which are significantly higher than previously reported values for the region, imply that the aerosols alone could account for >50 % of the total warming (aerosols + greenhouse gases) of the lower atmosphere and surface over this region. We demonstrate that the current state-of-the-art models used in climate assessments significantly underestimate aerosol-induced heating, efficiency and warming over the Hindu Kush - Himalaya - Tibetan Plateau (HKHTP) region, indicating a need for a more realistic representation of aerosol properties, especially of black carbon and other aerosols. The significant, regionally coherent aerosol-induced warming that we observe in the high altitudes of the region, is a significant factor contributing to increasing air temperature, observed accelerated retreat of the glaciers, and changes in the hydrological cycle and precipitation patterns over this region. Thus, aerosols are heating up the Himalayan climate, and will remain a key factor driving climate change over the region.

Aeolus winds impact on volcanic ash early warning systems for aviation

Forecasting volcanic ash atmospheric pathways is of utmost importance for aviation. Volcanic ash can interfere with aircraft navigational instruments and can damage engine parts. Early warning systems, activated after volcanic eruptions can alleviate the impacts on aviation by providing forecasts of the volcanic ash plume dispersion. The quality of these short-term forecasts is subject to the accuracy of the meteorological wind fields used for the initialization of regional models. Here, we use wind profiling data from the first high spectral resolution lidar in space, Aeolus, to examine the impact of measured wind fields on regional NWP and subsequent volcanic ash dispersion forecasts, focusing on the case of Etna's eruption on March 2021. The results from this case study demonstrate a significant improvement of the volcanic ash simulation when using Aeolus-assimilated meteorological fields, with differences in wind speed reaching up to 8 m/s when compared to the control run. When comparing the volcanic ash forecast profiles with downwind surface-based aerosol lidar observations, the modeled field is consistent with the measurements only when Aeolus winds are assimilated. This result clearly demonstrates the potential of Aeolus and highlights the necessity of future wind profiling satellite missions for improving volcanic ash forecasting and hence aviation safety.

A study on optical properties, classification, and transport of aerosols during the smog period over South Asia using remote sensing

Over the past few years, South Asian region has experienced frequent and thick smog events because of rapid population growth and enhanced anthropogenic activities, particularly in the Indo-Gangetic Plain (IGP). Therefore, the present study investigates aerosol properties such as aerosol optical depth (AOD) (500 nm), Angstrom exponent (AE) (440-870 nm), single scattering albedo (SSA), fine-mode fraction (FMF), absorption aerosol optical depth (AAOD), and absorption aerosol exponent (AAE) over selected AERONET sites namely Bhola (2012-2021), Dhaka (2012-2021), Jaipur (2011-2021), Kanpur (2011-2021), Karachi (2011-2021), Lahore (2011-2021), and Pokhara (2011-2021) in the IGP during the smog period (October, November, and December). Additionally, different aerosol types were categorized using AERONET direct sun (AOD, AE) and inversion products (VSD, SSA, RI, FMF, and ASY). The monthly mean AOD, AE, and FMF varied from ⁓0.33 to 1.07, ⁓0.3 to 1.4, and 0.6-0.9 µm over all selected AERONET sites during the smog period. Moreover, the outcomes revealed the dominance of biomass-burning and urban/ industrial aerosols over Lahore, Karachi, Dhaka, and Bhola during the smog period. Contrary to this, dust and mixed aerosols were abundant over Jaipur and Karachi, respectively. Furthermore, HYSPLIT cluster analysis is used to trace the transmission paths and potential sources of aerosols over selected sites.

Long-range transport of CO and aerosols from Siberian biomass burning over northern Japan during 18-20 May 2016

High CO concentration and dense aerosol layers at 1-6 km altitude in the free troposphere were observed over Rikubetsu, Japan, in ground-based Fourier transform spectrometer (FTS) and lidar measurements during 18-20 May 2016, days after intense wildfires east of Lake Baikal, Siberia. The column-averaged dry-air mole fraction of CO (XCO) was observed to be ∼150 ppb from 11:15 to 13:50 JST on 19 May, and peak aerosol optical depths (AODs) of 1.41 and 1.28 were observed at 15:40 JST 18 May and 11:20 JST 19 May, respectively. We used the HYSPLIT model to calculate five-day backward trajectories from Rikubetsu on May 18, 2016 at 2, 3 and 5 km altitude. The results show that the air parcels passed over the Siberian wildfires during 16-17 May. It was found that the high CO concentrations originated from forest fires were transported to the upper layers of Hokkaido. This will contribute to the understanding of the regional effects of air pollution in northern Japan due to air masses originating from forest fires. By combining these independent datasets such as AERONET aerosol optical thickness (AOT), MODIS fire data, and Infrared Atmospheric Sounding Interferometer (IASI) total CO columns, we confirmed that the lidar measurements of enhanced aerosol concentrations and FTS measurements of maximum XCO over Rikubetsu resulted from a persistent smoke plume transported from Siberian wildfires. Relatively large-scale forest fires have been frequently occurring in Siberia recently. However, the effects of CO and other gases released from them over northern Japan are not well known. We observed high concentrations of CO over the TCCON station in Rikubetsu, Japan, which we believe to be of forest fire origin. Therefore, we analyzed it as a case study to confirm its origin and impact on the upper atmosphere over northern Japan.

Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 2001-2018

East Africa (EA) suffers from the inadequate characterization of atmospheric aerosols, with far-reaching consequences of its inability to quantify precisely the impacts of these particles on regional climate. The current study aimed at characterizing absorption and radiative properties of aerosols using the long-term (2001-2018) AErosol RObotic NETwork (AERONET) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data over three environmentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD_{440 nm}), absorption Angstrom Exponent (AAE_{440-870 nm}), total effective radius (R_Eff), and total volume concentration (μm³/μm²) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols compared to the coarse-mode particles. The monthly variation in SSA_{440 nm} over EA explains the strength in absorption aerosols that range from moderate to strong absorbing aerosols. The aerosols exhibited significant variability over the study domain, with the dominance of absorbing fine-mode aerosols over Mbita accounting for ∼40 to ∼50 %, while weakly absorbing coarse-mode particles accounted for ∼8.2 % over Malindi. The study conclusively determined that Mbita was dominated by AAOD mainly from biomass burning in most of the months, whereas Malindi was coated with black carbon. The direct aerosol radiative forcing (DARF) retrieved from both the AERONET and MERRA-2 models showed strong cooling at the top of the atmosphere (TOA; -6 to -27 Wm^-2) and the bottom of the atmosphere (BOA, -7 to -66 Wm^-2). However, significant warming was noticed within the atmosphere (ATM; +14 to +76 Wm^-2), an indication of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and radiative characteristics over EA and can form the basis of other related studies over the domain and beyond.

Radiative effects of absorbing aerosol types over South Asia

A comprehensive study on classifying the aerosol types and absorbing aerosol types, and quantifying the effect of absorbing aerosols on aerosol optical and radiative properties using four years (2015-2016, 2018-2019) of high-quality Aerosol Robotic Network (AERONET) datasets over Kanpur (urban) and Gandhi College (rural) in the Indo-Gangetic Plain (IGP) region is conducted on a seasonal scale, for the first time. Biomass burning (BB), urban-industrial, and mixed aerosol types are always present, whereas dust aerosol and mostly dust absorbing aerosol types are only present in pre-monsoon and monsoon seasons. During winter and post-monsoon seasons, BB aerosols and mostly black carbon (MBC) absorbing aerosols dominate, and the contribution of aerosol optical depth (AOD) and single scattering albedo (SSA) corresponding to MBC to total AOD and SSA are higher. SSA for MBC varies over a broader range due to mixing of BC with water-soluble aerosols. During pre-monsoon and monsoon seasons, mixing of dust with anthropogenic aerosols increases the amount of mixed aerosol type. Surface cooling and atmospheric heating efficiency for mixed aerosols are higher than MBC and dust aerosols due to enhancement in aerosol absorption over both locations. Seasonal analysis of aerosol radiative properties showed that during winter and post-monsoon, MBC absorbing aerosols are the major contributor in controlling/influencing the total aerosol radiative forcing (ARF) and heating rate (HR). During the other seasons, each absorbing aerosol type significantly influences ARF depending on their AOD and SSA values. In addition to Kanpur and Gandhi College, data from seven other AERONET sites located at Karachi, Lahore, Jaipur, Lumbini, Pokhara, Bhola, and Dhaka in South Asia are analysed to conduct a regional-scale examination of aerosol optical parameters and radiative effects due to different absorbing aerosol types. As the aerosol characteristics and trends are similar over these sites, the findings from such a regional-scale analysis can be an appropriate representative for the South Asian region. The regional analysis revealed that the annual mean atmospheric ARF (ARF_ATM) and ARF efficiency (ARFE_ATM), and HR are higher for MBC, followed by mixed and MD aerosols over South Asia due to higher AOD, and higher absorbing efficiency of MBC aerosols. In comparison, mixed aerosols exhibit higher ARF_ATM over East Asia. This quantification of absorbing aerosol types over a global aerosol hotspot will be useful for an accurate quantification of climate impacts of aerosols.

Characterization of columnar aerosol over a background site in Central Asia

Ground-based observational characterization of atmosphere aerosols over Central Asia is very limited. This study investigated the columnar aerosol characteristics over Issyk-Kul, Kyrgyzstan, a background site in Central Asia using the long-term (∼14 years: August 2007-November 2021) data acquired with the Cimel sunphotometer. The mean aerosol optical depth (AOD) and Ångström exponent (AE) during the observation period were 0.14 ± 0.10 and 1.19 ± 0.41, respectively. Both AOD and AE varied across seasons, with highest AOD in spring (0.17 ± 0.17). Regarding the aerosol types, clean continental aerosols were dominant type (65%), followed by mixed aerosols (∼19%), clean marine aerosols (∼14%), dust (0.8%), and urban/industrial and biomass burning aerosol (0.7%). The aerosol volume size distribution was bimodal indicating the influence of both anthropogenic and natural aerosols with clear dominance of coarse mode during the spring season. Mainly dust and mixed aerosols were present during high aerosol episodes while the coarse mode aerosol volume concentration was 7.5 (strong episodes) and ∼19 (extreme episodes) times higher than the whole period average. Aerosol over this background sites were from local and regional sources with some contribution of long-range transport.

Comprehensive study of aerosols properties over various terrain types

Aerosols are a crucial part of the climate system. Numerous factors, including aerosols, govern Earth's radiation balance. Different aerosols have distinct radiational effects on the earth system, and thus the slight change in their composition may lead to a drastic change in their radiative effects. Aerosols' chemical and physical properties also depend on generation processes, generation source, and geographical location. Significant spatio-temporal inconsistency is noticed in the distribution of aerosols. It makes it much difficult task to assess their radiative properties. We attempted to explore aerosol's optical properties and wavelength dependence over different locations. We have used AERONET (Aerosol Robotic Network) data over various stations (Kanpur, Jaipur, Gandhi College, Pune) with varying terrain properties in the Indian continent. We have studied the variation of different optical parameters: aerosol optical depth (AOD), single scattering albedo (SSA), and Angstrom exponent (α), and their wavelength dependence. This study indicated that Jaipur is the cleanest site, with dust aerosols as a primary aerosol. Though over Pune also aerosol concentration was relatively low but the anthropogenic aerosols contributed primarily over this site. Over the Indo-Gangetic Plain (IGP) sites, dust aerosols dominated the pre-monsoon season, while anthropogenic aerosols dominated the post-monsoon and winter seasons. The scatter plot of AOD with α gives the details of different aerosols (desert dust, continental aerosols, mixed aerosol, biomass burning aerosols, and sulfate aerosols) in the different seasons and places. This study provides an overview of aerosol properties, dominant aerosols in the aerosol system, and their seasonal and spectral variation.

Validation and Analysis of MISR and POLDER Aerosol Products over China

Multi-angle polarization measurement is an important technical means of satellite remote sensing applied to aerosol monitoring. By adding angle information and polarization measurements, aerosol optical and microphysical properties can be more comprehensively and accurately retrieved. The accuracy of aerosol retrieval can reflect the advantages and specific accuracy improvement of multi-angle polarization. In this study, the Multi-angle Imaging SpectroRadiometer (MISR) V23 aerosol products and the Polarization and Directionality of the Earth’s Reflectance (POLDER) GRASP “high-precision” archive were evaluated with the Aerosol Robotic Network (AERONET) observations over China. Validation of aerosol optical depth (AOD), absorbing aerosol optical depth (AAOD), and the Ångström exponent (AE) properties was conducted. Our results show that the AOD inversion accuracy of POLDER-3/GRASP is higher with the correlation coefficient (R) of 0.902, slope of 0.896, root mean square error (RMSE) of 0.264, mean absolute error (MAE) of 0.190, and about 40.71% of retrievals within the expected error (EE, ± 0.05+0.2×AODAERONET) lines. For AAOD, the performance of two products is poor, with better results for POLDER-3/GRASP data. POLDER-3/GRASP AE also has higher R of 0.661 compared with that of MISR AE (0.334). According to the validation results, spatiotemporal distribution, and comparison with other traditional scalar satellite data, the performance of multi-angle polarization observations is better and is suitable for the retrieval of aerosol properties.

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.

Trends in the types and absorption characteristics of ambient aerosols over the Indo-Gangetic Plain and North China Plain in last two decades

The sixth assessment report released by the Intergovernmental Panel on Climate Change (IPCC) in 2021 states that our inadequate understanding of magnitudes and trends of atmospheric aerosols, particularly over Asia, is a major source of uncertainty in climate change. In this study, the climatology and trends in different types of aerosols with focus on absorbing aerosols over Kanpur located in the Indo-Gangetic Plain (IGP) in South Asia and Beijing in the North China Plain (NCP) in East Asia are derived for the first time. We perform a first analysis of high-quality time series of columnar aerosols observations over a period of nearly two-decades, along with satellite observations to provide a broader regional perspective. The satellite retrieved aerosol Ångström exponent (AE) values have increased (10-20%) suggesting an increasing contribution of fine aerosols to aerosol optical depth (AOD) over Asia in last 2-decades. Among the three aerosol types [urban-industrial (UI), biomass burning (BB), and dust (DU)], only UI and BB aerosols are present over Kanpur throughout the year, while DU is present along with UI and BB aerosols only during pre-monsoon and monsoon. Overall, there is a positive trend in BB aerosols over both Kanpur and Beijing, a positive (negative) trend in UI aerosols over Kanpur (Beijing), and positive (negative) trend in dust over Beijing (Kanpur). However, only the positive trend in BB aerosol type over Kanpur is statistically significant. Further, among the three absorbing aerosol types [mostly black carbon (MBC), mostly dust (MDU), and mixed (MIX) containing BC and dust], only MBC and MIX are present in post-monsoon and winter over IGP, and MDU is present along with MBC and MIX only during pre-monsoon and monsoon, which is in agreement with aerosol types found. Trends in MBC, MIX and MDU over Kanpur in IGP and in MIX over Beijing are statistically significant. These trends are attributed mainly to the changes in anthropogenic aerosol emissions, and not to natural and climatic factors as their changes are relatively small. These findings on hitherto unavailable climatology and trends in aerosols and absorbing aerosols over two global aerosol hotspots and identified contrasts will be crucial in model simulations to better decipher the aerosol-climate interactions over Asia.

Enhanced Light Absorption and Radiative Forcing by Black Carbon Agglomerates

The climate models of the Intergovernmental Panel on Climate Change list black carbon (BC) as an important contributor to global warming based on its radiative forcing (RF) impact. Examining closely these models, it becomes apparent that they might underpredict significantly the direct RF for BC, largely due to their assumed spherical BC morphology. Specifically, the light absorption and direct RF of BC agglomerates are enhanced by light scattering between their constituent primary particles as determined by the Rayleigh-Debye-Gans theory interfaced with discrete dipole approximation and recent relations for the refractive index and lensing effect. The light absorption of BC is enhanced by about 20% by the multiple light scattering between BC primary particles regardless of the compactness of their agglomerates. The resulting light absorption agrees very well with the observed absorption aerosol optical depth of BC. ECHAM-HAM simulations accounting for the realistic BC morphology and its coatings reveal high direct RF = 3-5 W/m² in East, South Asia, sub-Sahara, western Africa, and the Arabian peninsula. These results are in agreement with satellite and AERONET observations of RF and indicate a regional climate warming contribution by 0.75-1.25 °C, solely due to BC emissions.

Spatiotemporal Analysis of MODIS Aerosol Optical Depth Data in the Philippines from 2010 to 2020

Satellite remote sensing for air quality assessment provides information over a large spatial coverage and time period that shows the trends and effects of anthropogenic activities. Using data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite from the years 2010 to 2020, the spatiotemporal variations to aerosol optical depth (AOD) in Koronadal City and Quezon City were studied. Validation showed a strong relationship between the MODIS AOD values and the Aerosol Robotic Network (AERONET) AOD values (R2 = 0.83) and a low root mean square error (RMSE) of 0.26. Annual variation in the AOD of the two study areas showed a peak AOD value in 2015 due to an immense biomass burning in Indonesia and a low AOD value in 2020 due to the COVID-19 lockdown. Koronadal City experienced a high AOD value during the fall season due to aerosols from biomass burning in Indonesia that were carried by the southwest monsoon. Quezon City experienced a high AOD value during spring from increased local sources, as well as long-range transport pollutants from East Asia that were carried by northeasterly winds. Overall, this study provides an understanding of the spatiotemporal variations in aerosols in the Philippines, which could be used in environmental management, air quality regulations, and health assessment studies. This shows the urgency of monitoring and mitigating poor air quality in the Philippines.

Contrasting seasonal pattern between ground-based PM2.5 and MODIS satellite-based aerosol optical depth (AOD) at an urban site in Hanoi, Vietnam

This study investigated the seasonal variations of the ground-based PM_2.5 concentration measured at an urban site and Terra MODIS satellite-based aerosol optical depth (AOD) in Hanoi, Vietnam, during the year 2016. The findings showed the large differences in terms of the seasonal variation of both PM_2.5 concentration and columnar AOD. Clearly, the ground-based PM_2.5 concentrations decreased during the summer period and highly increased during the late fall and winter periods. The Terra MODIS AOD values also decreased in summer, however, significantly increased in spring. Interestingly, the increasing trend of AOD which in contrast to the decreasing trend of PM_2.5 concentration was found during the spring period, and vice versa for the winter period. The seasonal analysis of meteorological factors including relative humidity (RH), precipitation, and boundary layer height (BLH) as well as regional fire activities expressed that the increased columnar AOD in spring was largely influenced by the hygroscopic growth of aerosol induced by the increased RH, the larger BLH causing the more effective transport and mixing of atmospheric particles to higher altitudes, and especially the intensive fire activities in the Southeast Asian region during the spring period, whereas the significantly increased surface PM_2.5 concentration in winter was partly attributed to the impact from the highly industrialized and polluted source region in the Pearl River Delta of China. Different from the spring and winter periods, the abundant precipitation amount and the dominance of maritime air masses arrived in Hanoi in summer were the main reasons for the low AOD and surface PM_2.5 concentration during this period.

Study of aerosol optical properties at two urban areas in the north of Vietnam with the implication for biomass burning impacts

The spatiotemporal distribution and characterization of aerosol optical properties in the north of Vietnam were investigated extensively using the long-term measurements obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) (from 2010 to 2019) and two Aerosol Robotic Network (AERONET) stations (Nghia Do, Hanoi City, from 2010 to 2019 and Son La from 2012 to 2019) located in fast-developing urban areas. This study also analyzed the tendency of AOD over different wavelengths as well as the influences of meteorological parameters and boundary layer height (BLH) on AOD and Ångström exponent (AE). The annual mean AOD₅₀₀ at Nghia Do and Son La stations were 0.81 and 0.78, respectively. Our results revealed the existence of particles emitted from anthropogenic activities in Hanoi and Son La with the dominance of fine particles (more than 90% of the AE_440-870 were larger than 1). Besides, a high percentage of AE_440-870 larger than or approximately 1.5 during the dry and transition months in Son La indicated the existence of biomass-burning aerosol particles due to forest fires and burning of agriculture residuals. The classification results for aerosol types showed the presence of both biomass burning and urban/industrial aerosol types at Nghia Do and Son La sites. Among the investigated meteorological parameters, surface solar radiation expressed a significant correlation with AE_440-870 in all three seasons at the two sites due to the secondary formation of fine particles induced by the high solar radiation condition. The impacts of meteorological parameters and BLH on AOD were not observed simultaneously during three seasons at Nghia Do and Son La stations.

Optical and Microphysical Properties of the Aerosol Field over Sofia, Bulgaria, Based on AERONET Sun-Photometer Measurements

An analysis of the optical and microphysical characteristics of aerosol passages over Sofia City, Bulgaria, was performed on the basis of data provided by the AErosol RObotic NETwork (AERONET). The data considered are the result of two nearly complete annual cycles of passive optical remote sensing of the atmosphere above the Sofia Site using a Cimel CE318-TS9 sun/sky/lunar photometer functioning since 5 May 2020. The values of the Aerosol Optical Depth (AOD) and the Ångström Exponent (AE) measured during each annual cycle and the overall two-year cycle exhibited similar statistics. The two-year mean AODs were 0.20 (±0.11) and 0.17 (±0.10) at the wavelengths of 440 nm (AOD440) and 500 nm, respectively. The two-year mean AEs at the wavelength pairs 440/870 nm (AE440/870) and 380/500 nm were 1.45 (±0.35) and 1.32 (±0.29). The AOD values obtained reach maxima in winter-to-spring and summer and were about two times smaller than those obtained 15 years ago using a hand-held Microtops II sun photometer. The AOD440 and AE440/870 frequency distributions outline two AOD and three AE modes, i.e., 3 × 2 groups of aerosol events identifiable using AOD–AE-based aerosol classifications, additional aerosol characteristics, and aerosol migration models. The aerosol load over the city was estimated to consist most frequently of urban (63.4%) aerosols. The relative occurrences of desert dust, biomass-burning aerosols, and mixed aerosols were, respectively, 8.0%, 9.1% and 19.5%.

Using Objective Analysis for the Assimilation of Satellite-Derived Aerosol Products to Improve PM2.5 Predictions over Europe

We used the objective analysis method in conjunction with the successive correction method to assimilate MODerate resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data into the Chimère model in order to improve the modeling of fine particulate matter (PM2.5) concentrations and AOD field over Europe. A data assimilation module was developed to adjust the daily initial total column aerosol concentrations based on a forecast-analysis cycling scheme. The model is then evaluated during one-month winter period to examine how such a data assimilation technique pushes the model results closer to surface observations. This comparison showed that the mean biases of both surface PM2.5 concentrations and the AOD field could be reduced from −34 to −15% and from −45 to −27%. The assimilation, however, leads to false alarms because of the difficulty in distributing AOD550 over different particle sizes. The impact of the influence radius is found to be small and depends on the density of satellite data. This work, although preliminary, is important in terms of near-real time air quality forecasting using the Chimère model and can be further developed to improve modeled PM2.5 and ozone concentrations.

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.

A meteorological dataset of the West African monsoon during the 2016 DACCIWA campaign

As part of the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project, extensive in-situ measurements of the southern West African atmospheric boundary layer (ABL) have been performed at three supersites Kumasi (Ghana), Savè (Benin) and Ile-Ife (Nigeria) during the 2016 monsoon period (June and July). The measurements were designed to provide data for advancing our understanding of the relevant processes governing the formation, persistence and dissolution of nocturnal low-level stratus clouds and their influence on the daytime ABL in southern West Africa. An extensive low-level cloud deck often forms during the night and persists long into the following day strongly influencing the ABL diurnal cycle. Although the clouds are of a high significance for the regional climate, the dearth of observations in this region has hindered process understanding. Here, an overview of the measurements ranging from near-surface observations, cloud characteristics, aerosol and precipitation to the dynamics and thermodynamics in the ABL and above, and data processing is given. So-far achieved scientific findings, based on the dataset analyses, are briefly overviewed.

Comparison of Scanning LiDAR with Other Remote Sensing Measurements and Transport Model Predictions for a Saharan Dust Case

The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in southwest Germany (8.4298°E, 49.0953°N) from 7 to 9 April 2018, combining a scanning LiDAR (90°, 30°), a vertically pointing LiDAR (90°), a sun photometer, and the transport model ICON-ART. Based on this Saharan dust case, we discuss the advantages of a scanning aerosol LiDAR and validate a method to determine LiDAR ratios independently. The LiDAR measurements at 355 nm showed that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm−1 sr−1, extinction coefficients of 40 ± 0.8 Mm−1, a LiDAR ratio of 46 ± 5 sr, and a linear particle depolarisation ratio of 0.27 ± 0.023. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the transport model predicted the plume arrival time, its layer height, and its structure quite well. The comparison of dust plume backscatter values from the ICON-ART model and observations for two days showed a correlation with a slope of 0.9 ± 0.1 at 355 nm. This work will be useful for future studies to characterise aerosol particles employing scanning LiDARs.

Polarization Raman lidar for atmospheric correction during remote sensing satellite calibration: instrument and test measurements

A compact polarization Raman lidar has been designed and constructed for using it for atmospheric correction measurements during satellite optical sensor calibration in areas with high altitude and extremely low aerosol loading. The parameters of this lidar, such as laser wavelength, telescope diameter and interference filter bandwidth, were simulated and optimized for the best observation performance. The instrument has low weight, is small in size, and requires air cooling instead of commonly used water-cooling of the laser. Thus, the instrument is suitable for autonomous operation in remote sites. The lidar prototype was installed in Lijiang (26°43' N, 100°01' E), China, a potential observation site for calibrations of optical sensors of satellites. This observation site has been shown to be an appropriate place for remote sensing and satellite calibration activities with low aerosol loading, thin air and a comparably high proportion of cloud-free days. A field campaign carried out between November 2019 and April 2020 allowed for thoroughly testing the instruments. The results of test observations show that complete overlap between emitted laser beam and field-of-view of the receiver unit is achieved at relatively low heights above ground. The measurement accuracy is comparably high. Thus, this instrument is suitable for operating in areas with relatively clean atmospheric conditions.

Extensive characterization of aerosol optical properties and chemical component concentrations: Application of the GRASP/Component approach to long-term AERONET measurements

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93-1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Towards Early Detection of Tropospheric Aerosol Layers Using Monitoring with Ceilometer, Photometer, and Air Mass Trajectories

A near-real-time automatic detection system, based on the synergy of continuous measurements taken by a ceilometer and a photometer, has been implemented in order to detect lofted atmospheric aerosol layers and estimate the aerosol load. When heavy-loaded conditions are detected (defined by a significant deviation of the optical properties from a 10-year climatology), obtained for aerosol layers above 2500 m, an automatic alert is sent to scientists of the Romanian Lidar Network (ROLINET) to further monitor the event. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectory calculations are used to establish the possible pollution source. The aerosol transport events are considered to be major when various optical properties provided by the photometer are found outside the climatological values. The aerosol types over the three years for all the events identified revealed that the contribution to the pollution was 31%, 9%, and 60% from marine, dust, and continental types. Considering only the ‘outside climatology limits’ events, the respective contribution was 15%, 12%, and 73% for marine, dust, and continental types, respectively.

Insights into recent aerosol trends over Asia from observations and CMIP6 simulations

Aerosols continue to contribute the largest uncertainty in climate change. Over Asia, a global aerosol hotspot, spatial patterns of aerosol emissions are changing mainly because of changes in anthropogenic emissions, producing a dipole in atmospheric aerosol loading between East (decrease in emissions) and South Asia (increase in emissions). The resultant aerosol radiative effects are expected to be different as compared to the last decades of the 20^th century because of this emerging Asian aerosol dipole. The projection and assessments of radiative and climate impacts of aerosols rely on simulating accurately the aerosol properties, thus, making it imperative that current climate models involved in climate assessments including the Intergovernmental Panel on Climate Change Assessment Reports, simulate well the magnitude and trends in changing aerosol properties. For the first time, in this study we analyze trends in aerosol properties over Asia from satellite and ground-based observations, and simulations from climate models in Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment with state-of-the-art treatment of aerosol chemistry, physics and meteorology. The results reveal large inter-model differences in model estimates, and discrepancies between model simulations and observations as most models are not able to capture the recent observed magnitudes and trends in aerosol optical depth (AOD) and single scattering albedo (SSA) over Asia. The absolute and the relative (percent) trends (positive and/or negative) in AOD are significantly higher than the trends in SSA. The aerosol-induced effective radiative forcing within the atmosphere simulated with three CMIP6 models show a positive (increasing) trend over Asia. A positive trend in atmospheric heating due to aerosols in model simulations is consistent with model simulated trends in AOD (positive) and SSA (negative). These results on model-observations comparison need to be taken into account while examining the projected/expected future climate impacts due to aerosols, and potential value of various mitigation measures, in particular on regional and decadal climate change in Asia which is largely uncertain. MAIN FINDING: Our analysis of satellite and ground-based observations, and simulations from climate models in CMIP6 experiment with state-of-the-art treatment of aerosol chemistry, physics and meteorology reveal large difference in model calculations, and most models are not able to capture the recent observed trends in aerosol optical depth and single scattering albedo over Asia during 2000-2018.

Progress in Dust Modelling, Global Dust Budgets, and Soil Organic Carbon Dynamics

Dust emission is an important corollary of the soil degradation process in arid and semi-arid areas worldwide. Soil organic carbon (SOC) is the main terrestrial pool in the carbon cycle, and dust emission redistributes SOC within terrestrial ecosystems and to the atmosphere and oceans. This redistribution plays an important role in the global carbon cycle. Herein, we present a systematic review of dust modelling, global dust budgets, and the effects of dust emission on SOC dynamics. Focusing on selected dust models developed in the past five decades at different spatio-temporal scales, we discuss the global dust sources, sinks, and budgets identified by these models and the effect of dust emissions on SOC dynamics. We obtain the following conclusions: (1) dust models have made considerable progress, but there are still some uncertainties; (2) a set of parameters should be developed for the use of dust models in different regions, and direct anthropogenic dust should be considered in dust emission estimations; and (3) the involvement of dust emission in the carbon cycle models is crucial for improving the accuracy of carbon assessment.

Potential of AOD Retrieval Using Atmospheric Emitted Radiance Interferometer (AERI)

Aerosols in the atmosphere play an essential role in the radiative transfer process due to their scattering, absorption, and emission. Moreover, they interrupt the retrieval of atmospheric properties from ground-based and satellite remote sensing. Thus, accurate aerosol information needs to be obtained. Herein, we developed an optimal-estimation-based aerosol optical depth (AOD) retrieval algorithm using the hyperspectral infrared downwelling emitted radiance of the Atmospheric Emitted Radiance Interferometer (AERI). The proposed algorithm is based on the phenomena that the thermal infrared radiance measured by a ground-based remote sensor is sensitive to the thermodynamic profile and degree of the turbid aerosol in the atmosphere. To assess the performance of algorithm, AERI observations, measured throughout the day on 21 October 2010 at Anmyeon, South Korea, were used. The derived thermodynamic profiles and AODs were compared with those of the European center for a reanalysis of medium-range weather forecasts version 5 and global atmosphere watch precision-filter radiometer (GAW-PFR), respectively. The radiances simulated with aerosol information were more suitable for the AERI-observed radiance than those without aerosol (i.e., clear sky). The temporal variation trend of the retrieved AOD matched that of GAW-PFR well, although small discrepancies were present at high aerosol concentrations. This provides a potential possibility for the retrieval of nighttime AOD.

Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas

The SEMARA approach, an integration of the Simplified and Robust Surface Reflectance Estimation (SREM) and Simplified Aerosol Retrieval Algorithm (SARA) methods, was used to retrieve aerosol optical depth (AOD) at 550 nm from a Landsat 8 Operational Land Imager (OLI) at 30 m spatial resolution, a Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 m resolution, and a Visible Infrared Imaging Radiometer Suite (VIIRS) at 750 m resolution over bright urban surfaces in Beijing. The SEMARA approach coupled (1) the SREM method that is used to estimate the surface reflectance, which does not require information about water vapor, ozone, and aerosol, and (2) the SARA algorithm, which uses the surface reflectance estimated by SREM and AOD measurements obtained from the Aerosol Robotic NETwork (AERONET) site (or other high-quality AOD) as the input to estimate AOD without prior information on the aerosol optical and microphysical properties usually obtained from a look-up table constructed from long-term AERONET data. In the present study, AOD measurements were obtained from the Beijing AERONET site. The SEMARA AOD retrievals were validated against AOD measurements obtained from two other AERONET sites located at urban locations in Beijing, i.e., Beijing_RADI and Beijing_CAMS, over bright surfaces. The accuracy and uncertainties/errors in the AOD retrievals were assessed using Pearson’s correlation coefficient (r), root mean squared error (RMSE), relative mean bias (RMB), and expected error (EE = ± 0.05 ± 20%). EE is the envelope encompassing both absolute and relative errors and contains 68% (±1σ) of the good quality retrievals based on global validation. Here, the EE of the MODIS Dark Target algorithm at 3 km resolution is used to report the good quality SEMARA AOD retrievals. The validation results show that AOD from SEMARA correlates well with AERONET AOD measurements with high correlation coefficients (r) of 0.988, 0.980, and 0.981; small RMSE of 0.08, 0.09, and 0.08; and small RMB of 4.33%, 1.28%, and −0.54%. High percentages of retrievals, i.e., 85.71%, 91.53%, and 90.16%, were within the EE for Landsat 8 OLI, MODIS, and VIIRS, respectively. The results suggest that the SEMARA approach is capable of retrieving AOD over urban areas with high accuracy and small errors using high to medium spatial resolution satellite remote sensing data. This approach can be used for aerosol monitoring over bright urban surfaces such as in Beijing, which is frequently affected by severe dust storms and haze pollution, to evaluate their effects on public health.

Monetary quantification of COVID-19 impacts on sustainable development goals: Focus on air pollution and climate change

COVID-19 epidemic struck without warning, wreaking havoc on all aspects of society. The chapter discusses the quantification of impacts of COVID-19-induced control strategies and restricted resource consumption on sustainable development goals (SDGs), focusing on SDG-3 (Good Health and Wellbeing) and SDG-13 (Climate Action). The impacts of reduced PM_2.5 emission are monitored using moderate resolution imaging spectroradiometer (MODIS) satellite data for India (2020–21) and the reduction in the morbidity and mortality is valued using the cost of illness (COI), disability-adjusted life years (DALY), and value of statistical life (VSL). The reported reduction of CO₂e emissions of about 40% during the year, in the cities, is quantified for the country and monetized using the regional values of the social cost of carbon (SCC). The chapter also lays a framework for quantifying and valuing such impacts related to other SDGs and can be used by policymakers for implementation and quantified decision-making.

A New Algorithm for Simultaneous Retrieval of Aerosols and Marine Parameters

We present an algorithm for simultaneous retrieval of aerosol and marine parameters in coastal waters. The algorithm is based on a radiative transfer forward model for a coupled atmosphere-ocean system, which is used to train a radial basis function neural network (RBF-NN) to obtain a fast and accurate method to compute radiances at the top of the atmosphere (TOA) for given aerosol and marine input parameters. The inverse modelling algorithm employs multidimensional unconstrained non-linear optimization to retrieve three marine parameters (concentrations of chlorophyll and mineral particles, as well as absorption by coloured dissolved organic matter (CDOM)), and two aerosol parameters (aerosol fine-mode fraction and aerosol volume fraction). We validated the retrieval algorithm using synthetic data and found it, for both low and high sun, to predict each of the five parameters accurately, both with and without white noise added to the top of the atmosphere (TOA) radiances. When varying the solar zenith angle (SZA) and retraining the RBF-NN without noise added to the TOA radiance, we found the algorithm to predict the CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction with correlation coefficients greater than 0.72, 0.73, 0.93, 0.67, and 0.87, respectively, for 45∘≤ SZA ≤ 75∘. By adding white Gaussian noise to the TOA radiances with varying values of the signal-to-noise-ratio (SNR), we found the retrieval algorithm to predict CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction well with correlation coefficients greater than 0.77, 0.75, 0.91, 0.81, and 0.86, respectively, for high sun and SNR ≥ 95.

The influence of dusts on radiation and temperature over the eastern Asia with a regional climate model

In order to investigate the climate effects of dusts, a regional climate model (RegCM 4.6) with the dust scheme was used to simulate the direct radiative forcing and air temperature response at 2 m near surface of dusts over the eastern Asia. Two sets of experiments were conducted, one with and one without dust aerosols. The experiment covered the main dust occurrence months from March to May for 8 years (2011-2018), and the simulation results were evaluated against ground station, reanalysis and satellite data. The model captured the spatiotemporal distribution of dust AOD and mass loading over the eastern Asia. However, it tended to underestimate the dust AOD and mass loading over the downwind of the dust source region and the Taklimakan Desert, and overestimate them over the north Xinjiang. The direct net radiative forcing including shortwave and longwave was up to -20 W·m^-2 at the surface and -10 W·m^-2 at the TOA over the dust source region due to the dominant negative shortwave forcing. The only exception of positive forcing at the TOA was observed along the western boundaries of the Tibetan Plateau due to the semi-persistent ice and snow cover. The dusts tended to warm the atmosphere more than 18 W·m^-2 and cool the surface locally up to -0.7 °C. Among the 5 sub-areas, the largest averaged regional direct radiative forcing induced by dusts appeared over the central Inner Mongolia in May with the value of -3.0 ± 2.1, -12.2 ± 4.1 and 9.2 ± 4.4 W·m^-2 at the TOA, surface and in the atmosphere, respectively. The results indicated that the model simulation for dusts should be further improved and the dust effects should be included in the estimates of climate change over the eastern Asia.

Fine resolution air quality dynamics related to socioeconomic and land use factors in the most polluted desert metropolitan in the American Southwest

Air pollution kills approximately 4.2 million people every year. As air pollution varies significantly in different urban areas, the assessment of urban emissions is key to taking appropriate actions and formulating policies for sustainable built environments and to promote the wellbeing of people. The overarching goal of this study was to generate fine resolution aerosol optical depth (AOD) using Landsat imagery and examine both the socioeconomic inequalities of air pollution exposure and the air quality variation related to different land-use categories. This study has focused on a period of unusual population growth, 2000-2010, in the Phoenix Metropolitan Area. It was found that socioeconomic factors, vegetation indexes, and land use land cover types are all strong predictors of AOD, and the negative coefficients of socioeconomic values reveal insight into the social inequality of air pollution exposure. Results suggest that the government regulation on air pollution during the study period helped to improve air quality. Meanwhile, planting vegetation to mitigate air pollution should be carefully examined in order to find the right vegetation species and spatial configuration of vegetation cover in urban settings.

Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region

We examine the impact of atmospheric aerosols and clouds on the surface solar radiation and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of ground-based AERONET Sun Photometer and satellite observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat Second Generation (MSG), with radiative transfer model (RTM) simulations and 1 day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). Clouds and aerosols are one of the most common sources of solar irradiance attenuation and hence causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The outputs of RTM results presented with high accuracy under clear, cloudy sky and dust conditions for global horizontal (GHI) and beam horizontal irradiance (BHI). On an annual basis the total aerosol attenuation was found to be up to 105 kWh m−2 for the GHI and 266 kWh m−2 for BHI, respectively, while the cloud effect is much stronger with an attenuation of 245 and 271 kWh m−2 on GHI and BHI. The results of this study will support the Indian solar energy producers and electricity handling entities in order to quantify the energy and financial losses due to cloud and aerosol presence.

Space-Time Machine Learning Models to Analyze COVID-19 Pandemic Lockdown Effects on Aerosol Optical Depth over Europe

The recent COVID-19 pandemic affected various aspects of life. Several studies established the consequences of pandemic lockdown on air quality using satellite remote sensing. However, such studies have limitations, including low spatial resolution or incomplete spatial coverage. Therefore, in this paper, we propose a machine learning-based scheme to solve the pre-mentioned limitations by training an optimized space-time extra trees model for each year of the study period. The results have shown that our trained models reach a prediction accuracy up to 95% when predicting the missing values in the MODIS MCD19A2 Aerosol Optical Depth (AOD) product. The outcome of the mentioned scheme was a geo-harmonized atmospheric dataset for aerosol optical depth at 550 nm with 1 km spatial resolution and full coverage over Europe. As an application, we used the proposed machine learning based prediction approach in AOD levels analysis. We compared the mean AOD levels between the lockdown period from March to June in 2020 and the mean AOD values of the same period for the past 5 years. We found that AOD levels dropped over most European countries in 2020 but increased in several eastern and western countries. The Netherlands had the most significant average decrease in AOD levels (19%), while Spain had the highest average increase (10%). Moreover, we analyzed the relationship between the relative percentage difference of AOD and four meteorological variables. We found a positive correlation between AOD and relative humidity and a negative correlation between AOD and wind speed. The value of the proposed prediction scheme is further emphasized by taking into consideration that the reconstructed dataset can be used for future air quality studies concerning Europe.

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.

Sensors and systems for air quality assessment monitoring and management: A review

Air quality (AQ) is a global concern for human health management. Therefore, air quality monitoring (AQM) and its management is a must-needed activity for the current world environment. A systematic review of various sensors and systems for AQ management may strengthen our understanding of the monitoring and management of AQ. Thus, the current review presents details on sensors/systems available for AQ assessment, monitoring, and management. First, we had gone through the published literature based on special keywords including AQM, Particulate Matter (PM), Carbon Mono-oxide (CO), Sulfur di-Oxide (SO2), and Nitrogen di-Oxide (NO2) among others, and identified the current scenario of research in AQ management. We discussed various sensors/systems available for the AQ management based on self-conceptualised five major categories including, ground-based AQS (wet chemistry) systems, ground-based digital sensors systems, aerial sensors systems, satellite-based sensors systems, and integrated systems. The prospects in the field of AQ assessment and management (AQA&M) were then discussed in detail. We concluded that the AQA&M can be better achieved by coupling new technologies like ground-based smart sensors, satellite remote sensing sensors, Geospatial technologies, and computational technologies like machine learning, Artificial intelligence, and Internet of Things (IoT). The current work may lead to a junction of information for connecting these sensors/systems, which is expected to be beneficial in future AQ research and management.

Aerosol Characterization during the Summer 2017 Huge Fire Event on Mount Vesuvius (Italy) by Remote Sensing and In Situ Observations

During the summer of 2017, multiple huge fires occurred on Mount Vesuvius (Italy), dispersing a large quantity of ash in the surrounding area ensuing the burning of tens of hectares of Mediterranean scrub. The fires affected a very large area of the Vesuvius National Park and the smoke was driven by winds towards the city of Naples, causing daily peak values of particulate matter (PM) concentrations at ground level higher than the limit of the EU air quality directive. The smoke plume spreading over the area of Naples in this period was characterized by active (lidar) and passive (sun photometer) remote sensing as well as near-surface (optical particle counter) observational techniques. The measurements allowed us to follow both the PM variation at ground level and the vertical profile of fresh biomass burning aerosol as well as to analyze the optical and microphysical properties. The results evidenced the presence of a layer of fine mode aerosol with large mean values of optical depth (AOD > 0.25) and Ångstrom exponent (γ > 1.5) above the observational site. Moreover, the lidar ratio and aerosol linear depolarization obtained from the lidar observations were about 40 sr and 4%, respectively, consistent with the presence of biomass burning aerosol in the atmosphere.

Simultaneous measurements of PM1 and PM10 aerosol scattering properties and their relationships in urban Beijing: A two-year observation

The aerosol scattering properties of submicron (PM₁) and sub-10 μm particles (PM₁₀) under dry conditions (RH <30%) were investigated in Beijing from 2018 to 2019. Using the simultaneous measurement of PM₁ and PM₁₀, the scattering properties of super micron (PM_10-1) particles were also calculated. At 550 nm, the average of scattering coefficient (σ_sp) and asymmetry parameter (g) were 208.7 ± 204.9 Mm^-1 and 0.61 ± 0.04 for PM₁₀, 140.6 ± 130.2 Mm^-1 and 0.60 ± 0.04 for PM₁, and 69.8 ± 82.2 Mm^-1 and 0.62 ± 0.04 for PM_10-1, respectively, while the backscattering ratio (b) values were 0.13 ± 0.02 for PM₁₀ and PM₁, and 0.12 ± 0.02 for PM_10-1. The mass scattering efficiencies (MSE) for PM₁₀, PM₁ and PM_10-1 were 2.43 ± 2.37, 3.67 ± 0.96, and 1.73 ± 1.82 m² g^-1, respectively. In 2019, σ_sp decreased by approximately 18.4% for PM₁₀, and 16.7% for PM₁ compared with those in 2018, which was quite similar to the decrease of 17% and 19% for PM₁₀ and PM_2.5 mass concentrations during the same time period. The scattering Ångström exponent (SAE_450/700), which was 1.88 ± 0.29 for PM₁ and 1.50 ± 0.27 for PM₁₀ indicated size distributions dominated by fine mode aerosols. This is also evidenced by the high submicron scattering ratio (Rsp) (71.1% ± 7.9%). The high SAE, Rsp, and high PM₁ σ_sp in the study suggest that control of fine particle pollution is important to reduce overall PM pollution in urban Beijing. In addition, with an increase in σ_sp, b, Rsp, and SAE gradually decreased, while g and MSE increased. The clearly scattering coefficient-dependent MSE suggests that high aerosol loading and high MSE both play an important role in degraded visibility during heavy pollution periods.

Aerosol Optical Properties around the East China Seas Based on AERONET Measurements

Understanding aerosols optical properties over the oceans is vital for enhancing our knowledge of aerosol effects on climate and pollutant transport between continents. In this study, the characteristics of aerosol optical thickness (AOT) at 500 nm (τ500nm), Ångström exponent for the wavelength pair 440–870 nm (α) and volume size distribution (VSD), are presented and analyzed over the East China seas based on the observations at four AERONET sites during 1999–2019. The main results are: (1) the mean τ500nm (α) value ranged from 0.31 to 0.36 (1.17–1.31); (2) the distribution of τ500nm (α) is similar to a log-normal distribution with a right-skewed long tail larger than 0.5 (closer to the normal distribution); (3) large AOT (τ500nm>0.6) was frequently observed in summer (June and July) and spring (March to May), followed by autumn and winter; (4) all aerosol types were observed, and urban/industrial aerosols and mixed types were dominant throughout the period. The atmospheric column aerosol was characterized by a bimodal lognormal size distribution with a fine mode at effective radius, Reff = 0.16 ± 0.01 μm, and coarse mode at Reff = 2.05 ± 0.1 μm.

An Aerosol Climatology and Implications for Clouds at a Remote Marine Site: Case Study Over Bermuda

Aerosol characteristics and aerosol-cloud interactions remain uncertain in remote marine regions. We use over a decade of data (2000-2012) from the NASA AErosol RObotic NETwork, aerosol and wet deposition samples, satellite remote sensors, and models to examine aerosol and cloud droplet number characteristics at a representative open ocean site (Bermuda) over the Western North Atlantic Ocean (WNAO). Annual mean values were as follows: aerosol optical depth (AOD) = 0.12, Ångström Exponent (440/870 nm) = 0.95, fine mode fraction = 0.51, asymmetry factor = 0.72 (440 nm) and 0.68 (1020 nm), and Aqua-MODIS cloud droplet number concentrations = 51.3 cm-3. The winter season (December-February) was characterized by high sea salt optical thickness and the highest aerosol extinction in the lowest 2 km. Extensive precipitation over the WNAO in winter helps contribute to the low FMFs in winter (~0.40-0.50) even though air trajectories often originate over North America. Spring and summer had more pronounced influence from sulfate, dust, organic carbon, and black carbon. Volume size distributions were bimodal with a dominant coarse mode (effective radii: 1.85-2.09 μm) and less pronounced fine mode (0.14-0.16 μm), with variability in the coarse mode likely due to different characteristic sizes for transported dust (smaller) versus regional sea salt (larger). Extreme pollution events highlight the sensitivity of this site to long-range transport of urban emissions, dust, and smoke. Differing annual cycles are identified between AOD and cloud droplet number concentrations, motivating a deeper look into aerosol-cloud interactions at this site.

Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria

Globally, ambient air pollution claims ~9 million lives yearly, prompting researchers to investigate changes in air quality. Of special interest is the impact of COVID-19 lockdown. Many studies reported substantial improvements in air quality during lockdowns compared with pre-lockdown or as compared with baseline values. Since the lockdown period coincided with the onset of the rainy season in some tropical countries such as Nigeria, it is unclear if such improvements can be fully attributed to the lockdown. We investigate whether significant changes in air quality in Nigeria occurred primarily due to statewide COVID-19 lockdown. We applied a neural network approach to derive monthly average ground-level fine aerosol optical depth (AOD_f) across Nigeria from year 2001-2020, using the Multi-angle Implementation of Atmospheric Correction (MAIAC) AODs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellites, AERONET aerosol optical properties, meteorological and spatial parameters. During the year 2020, we found a 21% or 26% decline in average AOD_f level across Nigeria during lockdown (April) as compared to pre-lockdown (March), or during the easing phase-1 (May) as compared to lockdown, respectively. Throughout the 20-year period, AOD_f levels were highest in January and lowest in May or June, but not April. Comparison of AOD_f levels between 2020 and 2019 shows a small decline (1%) in pollution level in April of 2020 compare to 2019. Using a linear time-lag model to compare changes in AOD_f levels for similar months from 2002 to 2020, we found no significant difference (Levene's test and ANCOVA; α = 0.05) in the pollution levels by year, which indicates that the lockdown did not significantly improve air quality in Nigeria. Impact analysis using multiple linear regression revealed that favorable meteorological conditions due to seasonal change in temperature, relative humidity, planetary boundary layer height, wind speed and rainfall improved air quality during the lockdown.