Annual Aerosol Optical Depth Research Articles

Unveiling soil coherence patterns along Etihad Rail using Sentinel-1 and Sentinel-2 data and machine learning in arid region

This research applies machine learning to predict soil coherence for Etihad Rail, marking the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By integrating Sentinel-1 SAR and Sentinel-2 data with MODIS Aerosol Optical Depth (AOD) observations, the study develops detailed models that depict complex soil coherence patterns crucial for urban planning and risk assessment. Findings show variations in soil coherence between operational and under-construction phases, influenced by seasonal changes in aerosol dynamics and sand dust levels. Higher soil coherence is linked with lower annual sand dust deposition and AOD measurements, emphasizing the importance of this data for informed decision-making. The study employs a unique combination of data sources and machine learning algorithms to predict soil coherence, including Support Vector Machine (SVM), Extreme Gradient Boosting (XGBOOST), Gaussian Process Regression (GPR), Random Forest (RF), and 1D Convolutional Neural Network (CNN), with the Random Forest model achieving the lowest root mean squared error (RMSE) of 0.0826. These contributions enhance our understanding and provide a valuable framework for infrastructure development in similar environments.

Annual and Seasonal Variations in Aerosol Optical Characteristics in the Huai River Basin, China from 2007 to 2021

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China’s environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality.

Combined use of HYSPLIT model and MODIS aerosols optical depth to study the spatiotemporal circulation patterns of Saharan dust events over Central Europe

Mineral dust released from the desert region and transported into the atmosphere has a crucial impact on the Earth's climate system's biogeochemical cycle. It has serious adverse effects on human health. The Sahara is one of the world's dustiest areas. This investigation intends to uncover the underlying reasons for atmospheric dust dispersion throughout the year by tracking the dusttransport and deposition in Central Europe, focusing on arid areas of North Africa. In this paper, we use the GDAS (Global Data Assimilation System) archival meteorological database to compute the analytical forward trajectories and configure the particle concentrations using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model. Besides, we investigate the synoptic meteorological conditions of acute Saharan dust episodes to determine the dynamic atmospheric system during their onset. The forward trajectories reveal the seasonality of wind-blown dust throughout the year. Dust storms are typically more prevalent in the spring, with a second peak in the Summer. As a result, particle transport takes various paths as the seasons and climatic conditions change. The most dust-laden masses, which reach high altitudes from the source areas, are often transported to Central Europe, where their seasonal distribution is relatively similar to that of the studied African region. However, the intensity and frequency of Saharan dust events (SDEs) have significantly changed in the previous decades, with an increased number of intense winter storms. According to the synoptic analysis, this variability is strongly linked to two factors. (1) The intensity and lifetime variation of the Mediterranean cyclones and (2) Climate change triggered lee-side (Sharav) cyclogenesis modified by the topographic complexity of Atlas. This study also confirmed the effectiveness of the HYSPLIT model in simulating atmospheric dust after comparing it with annual aerosol optical depth measurements from MODIS (Moderate-Resolution Imaging Spectroradiometer) data.

Exploring the Trend of Aerosol Optical Depth and its Implication on Urban Air Quality Using Multi-spectral Satellite Data During the Period from 2009 to 2020 over Dire Dawa, Ethiopia

This study focuses on atmospheric aerosols, especially aerosol optical depth (AOD), over Dire Dawa, Ethiopia, from 2009 to 2020. At first, a correlation between the four satellite sensors and AERONET was made for validation purposes and to determine the sensor that best represents Dire Dawa. Intercomparisons were also made among the four satellite sensors. After all statistical tests, annual, seasonal, and decadal trend analyses were made. The validation results indicated that the AOD of MODIS-terra showed the best correlation with AERONET with R2 (0.78), RMSE (0.03), and MBE of 0.02 and represented the area better than the rest. The inter-comparison of AOD retrieved from multi-spectral satellite sensors showed a positive and satisfactory correlation between MODIS-Terra and OMI. Only MODIS-Aqua showed a linearly increasing mean annual AOD with R2 = 0.43. In three seasons (summer, autumn, and spring), AOD showed linear increments over the 12 years, with R2 ranging between 0.3 and 0.5. The three seasons also had nearly identical AODs of 0.23-0.28. However, winter had the lowest value of 0.2. MODIS-terra, out of the four sensors, exhibited increasing decadal tendency over the 2009-2020 period. Monthly analysis revealed that August had the highest AOD (0.265), and January had the lowest (0.14). The value of AOD obtained from this study over Dire Dawa shows a higher value during all seasons except during winter. Thus, this study gives a glimpse into the use of multi-spectral satellite sensors to monitor air quality over a semi-arid urban region.

Spatio-temporal correspondence of aerosol optical depth between CMIP6 simulations and MODIS retrievals over India.

In the present work, the aerosol optical depth (AOD) at 550nm of the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite was utilised to evaluate the AOD simulations of newly emerged general circulation models (GCMs) of coupled model intercomparison project-phase 6 (CMIP6) over the Indian landmass. Further, the AOD from the CMIP6 models has been compared with its previous generation models from CMIP5 to examine the extent of uncertainties in AOD with reference to the MODIS AOD datasets. The evolution of aerosols over India using the different shared socioeconomic pathways (SSPs) has also been studied till the year 2050. The results show that the CMIP5 and CMIP6 models underestimated the mean annual AOD of the Indian region as a whole. A multi-model mean (MMM) of thirteen GCMs from CMIP6 showed an underestimation of AOD by 40 to 60% over the Indo-Gangetic plains, while an overestimation of 60 to 80% in AOD was observed over the Peninsular and Central Indian regions in comparison with MODIS for the study period of 2001 to 2014. In future simulations, the pathway SSP370 has shown a significant increasing trend of AOD whereas SSP126 and SSP585 have shown significant decreasing trends of AOD by the year 2050. In the future, the changes in the AOD will mainly be contributed by the anthropogenic aerosols (AOA, BC, and Sulphates) emissions in all SSPs. The large bias of MMM with the MODIS requires further research in terms of analysing the accuracy of emission datasets that have been used to simulate the AODs by the CMIP6 models over the Indian region.

The Aerosol Pollution Of The Atmosphere On The Example Of Lidar Sensing Data In St. Petersburg (Russia), Kuopio (Finland), Minsk (Belarus)

The results of lidar sensing of aerosol pollution in St. Petersburg (Russia) were compared with ones located in Minsk (Belarus) and Kuopio (Finland) to assess the impact of large cities on atmospheric pollution by aerosol particles. For comparison, aerosol optical depth (AOD) data obtained at the three stations from 2014 to 2021 were used. Lidar sounding of atmospheric aerosols was carried out using aerosol Nd:YAG lasers operating at three wavelengths: 355, 532 and 1064 nm. Due to differences in the lidar station equipment characteristics and, consequently, in the lower limit for determining aerosols, the aerosol optical depth was compared in the range of heights from 800 to 1600 m at 355 and 532 nm. Since the compared stations do not have data for all years, the period from 2014 to 2016 was analyzed separately. The average annual AOD 355 in Minsk in the period 2014-2016 is almost the same as the average annual AOD in St. Petersburg. When comparing data in St. Petersburg and Minsk for the period 2014-2020, AOD 355 in St. Petersburg exceeds AOD 355 in Minsk by 1.46 times. AOD 532 nm in Minsk is larger than in St. Petersburg, regardless of the chosen comparison period. The average annual AOT 355 in Kuopio is lower than in Minsk and St. Petersburg by 2.1 times, while at a wavelength of 532 nm they are 3.6 times lower than in Minsk and 2.6 times in St. Petersburg. The calculated Angstrom exponent coefficient shows that the coarse mode in Minsk is higher than in St. Petersburg. The atmosphere over Kuopio has a lower content of aerosol particles. Since 2017, there was a steady excess of aerosol content over St. Petersburg compared to Minsk. Additionally, a comparison of the lidar data with the total AOD of AERONET stations located in Kuopio, Minsk and Peterhof (25 km from the lidar station in St. Petersburg) was carried out. The AOD obtained by lidar and AERONET method is in good agreement.

Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.

Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia

Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. The average annual aerosol optical depth (AOD) of sites in China, Korea, and Japan was 1.15, 1.02 and 0.94, respectively, and the corresponding proportion of absorbing aerosol optical depth (AAOD) was 8.61%, 6.69%, and 6.49%, respectively. The influence of absorbing aerosol on ultraviolet (UV) radiation mainly focused on UV-A band (315–400 nm). Under the influence of such radiative effect, the annual mean near-surface J[NO2] (J[O1D]) of sites in China, Korea, and Japan decreased by 16.95% (22.42%), 9.61% (13.55%), and 9.63% (13.79%), respectively. In Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) region, the annual average AOD was 1.48 and 1.29, and the AAOD was 0.14 and 0.13, respectively. The UV radiative forcing caused by aerosols dominated by black carbon (BC-dominated aerosols) on the surface was −3.19 and −2.98 W m−2, respectively, accounting for about 40% of the total aerosol radiative forcing, indicating that the reduction efficiency of BC-dominated aerosols on solar radiation was higher than that of other types of aerosols. The annual mean J[NO2] (J[O1D]) decreased by 14.90% (20.53%) and 13.71% (18.20%) due to the BC-dominated aerosols. The daily maximum photolysis rate usually occurred near noon due to the diurnal variation of solar zenith angle and, thus, the daily average photolysis rate decreased by 2–3% higher than that average during 10:00–14:00.

Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Aerosol Optical Depth (AOD), quantifying the amount of aerosol in the atmosphere, is widely regarded as a crucial indicator for research on atmospheric physics and regional air quality. At present, the inversion of AOD from observation of satellite remote sensing sensors has become the main technology for large-scale monitoring of aerosol load. The Huaihai Economic Zone is the connecting belt of two key areas of atmospheric governance (the Yangtze River Delta and the Beijing-Tianjin-Hebei region, China), and it has been suffering from air pollution for many years and few studies of AOD focus on this region. Therefore, the spatial and temporal characteristics of the AOD are explored using MODIS AOD data and AVHRR AOD data in this region during the period from 1982 to 2021 in this study. The correlation coefficients between the AOD of satellite observation and actual air pollution were analyzed by combining PM2.5 pollutant concentration and air quality index (AQI) data. The results showed that the AOD is higher in the northwest than in the southeast, and it is different from season to season. The annual variation of AOD in the Huaihai Economic Zone is a W-shaped trend from 1982 to 2011, while the trend of annual AOD is decreasing after 2011. In terms of seasons, the whole differences in AOD are evident, exhibiting AOD values in summer > those in spring > those in autumn > and those in winter. Furthermore, it indicated that the quarterly and monthly variation of the AOD tends to be flat in recent years. Since 2015, the concentration of PM2.5 has continued to decline, the same as that of AQI. Meanwhile, the quarterly and monthly differences in PM2.5 are still obvious, with higher PM2.5 in winter and lower PM2.5 in summer. However, it also represented that PM2.5 is significantly higher in spring than in autumn from 2015 to 2018, which is the opposite for 2019 to 2021. Lastly, the correlation between AOD and PM2.5/AQI is also given; i.e., the correlation coefficients of AOD with PM2.5/AQI are 0.84/0.82, with the highest correlation coefficient in autumn (R = 0.86/0.91) and the lowest in winter (R = 0.46/0.48).

Trend relationship between mountain normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) across two decades: implication for water quality within the Lesotho Highlands, Drakensberg, South Africa

There are growing concerns on contribution of vegetation dynamics to atmospheric turbidity and quality of regional water towers. The study sought to determine the trends in the MODIS/TERRA-derived normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) for Lesotho Highland over 2000-2020. The predictive relationship between the two variables was also examined using regression analysis. Irrespective of yearly AOD patterns, the AOD showed biphasic patterns peaking between mid-winter to early spring (July-October) (highest) and autumn (Feb-April) (next highest), and lowest in the summer (Nov-January). The monthly NDVI was largest in January-March (summer-early fall) with smaller values in winter and spring. This seasonality can be related to the peak of anthropogenic biomass combustion during the winter and strong winds during the spring and early summer. The AOD relationship with NDVI showed quadratic patterns peaking and plunging with changes in season. About 30-80% (R2 = 0.3-0.8%) changes in annual AOD from 2000 to 2020 were explainable by the dynamics of NDVI indicating that increased NDVI contributes to about a 50% decrease in AOD in the Lesotho Highlands. However, an outlier trend was observed in 2007 (R2 = 13%). Incidences of high AOD in months of high NDVI may be indicative of traveling aerosols, i.e., aerosols from non-local sources/activity. On the other hand, high AOD in months of low NDVI implicates local aerosol sources. Trend relationship studies on vegetation loss and AOD in mountain areas of other regions could improve knowledge of contaminant dynamics and risk implications for downstream populations.

Aerosol Optical Depth Spatial and Temporal Variability Using Satellite Data Over Indian Major Cities

Introduction: The study’s main aim is to investigate the long-term variation of Aerosol Optical Depth (AOD). It also aims to show the relationship between meteorological parameters. This study evaluates long-term (2010 to 2021) special and temporal changes over major Indian regions using satellite-based data from NASA’s Terra Satellite.
 Materials and Methods: This study was carried out during 2010-2021 using MODIS data for long-term analysis. Variation of AOD with meteorological parameters was also performed to show the impact of these parameters (Temperature and Relative Humidity) on AOD by the MERRA-II model.
 Results: Based on Terra AOD data, in all the studied regions, especially the eastern region (Kolkata), the mean AOD was high (0.9-1.2). In the western region (Mumbai, Ahmedabad, and Surat), the mean AOD was low to moderate during all seasons. Furthermore, the impact of meteorological parameters on AOD shows significant variation in average annual AOD in Kolkata (0.70 ± 0.09), while other regions reported lower than average AOD values during the study period. Mumbai and Surat had average AODs (0.44 ± 0.13), (0.45 ± 0.14), while Ahmedabad and Jaipur reported average AOD of 0.45 ± 0.14 and 0.23 ± 0.11 during the study period, respectively.
 Conclusion: Generally, AOD values vary from season to season due to aerosol’s optical and microphysical properties being affected by meteorological conditions and surface albedo. This study examined the spatial and temporal distribution of AOD over five major Indian cities.

Extended validation and evaluation of the OLCI–SLSTR SYNERGY aerosol product (SY_2_AOD) on Sentinel-3

Abstract. We present the first extended validation of a new SYNERGY global aerosol product (SY_2_AOD), which is based on synergistic use of data from the Ocean and Land Color Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR) sensors aboard the Copernicus Sentinel-3A (S3A) and Sentinel-3B (S3B) satellites. Validation covers period from 14 January 2020 to 30 September 2021. Several approaches, including statistical analysis, time series analysis, and comparison with similar aerosol products from the other spaceborne sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied for validation and evaluation of S3A and S3B SY_2 aerosol products, including aerosol optical depth (AOD) provided at different wavelengths, AOD pixel-level uncertainties, fine-mode AOD, and Angström exponent. Over ocean, the performance of SY_2 AOD (syAOD) retrieved at 550 nm is good: for S3A and S3B, Pearson correlation coefficients with the Maritime Aerosol Network (MAN) component of the AErosol RObotic NETwork (AERONET) are 0.88 and 0.85, respectively; 88.6 % and 89.5 % of pixels fit into the MODIS error envelope (EE) of ±0.05 ± 0.2 × AOD. Over land, correlation coefficients with AERONET AOD (aAOD) are 0.60 and 0.63 for S3A and S3B, respectively; 51.4 % and 57.9 % of pixels fit into MODIS EE. Reduced performance over land is expected since the surface reflectance and angular distribution of scattering are higher and more difficult to predict over land than over ocean. The results are affected by a large number of outliers. Evaluation of the per-retrieval uncertainty with the χ2 test indicates that syAOD prognostic uncertainties (PU) are slightly underestimated (χ2 = 3.1); if outliers are removed, PU describes the syAOD error well (χ2 = 1.6). The regional analysis of the Angström exponent, which relates to the aerosol size distribution, shows spatial correlation with expected sources. For 40 % of the matchups with AERONET in the Northern Hemisphere (NH) and for 60 % of the matchups in the Southern Hemisphere (SH), which fit into the AE size range of [1, 1.8], an offset between SY_2 AE (syAE) and AERONET AE (aAE) is within ±0.25. General overestimation of low (< 0.5) syAE and underestimation of high (> 1.8) syAE results in high (0.94, globally) overall bias. Good agreement (bias < 0.03) was observed between Sy_2 fine-mode AOD (syFMAOD) and AERONET fine-mode AOD (aFMAOD) for aFMAOD < 1. At aFMAOD > 1, syFMAOD is considerably underestimated (by 0.3–0.5 in different aFMAOD ranges) in the NH. In the SH, only a few aFMAOD values above 1 are measured. The fine-mode fraction (FMF) in the SY_2 AOD product (syFMF) in the range of [0, 0.7] is overestimated; the positive offset of 0.3–0.5 for low (< 0.25) FMF gradually decreases. Differences between the annual and seasonal AOD values from SY_2 and MODIS (mod) Dark Target and Deep Blue products are within 0.02 for the study area (30∘ S–60∘ N, 80∘ W–45∘ E). The agreement is better over ocean; however, a difference up to 0.6 exists between syFMF and modFMF. Over bright land surface (Saharan desert) the difference in AOD between the two products is highest (up to 0.11); the sign of the difference varies over time and space. For both S3A and S3B AOD products, validation statistics are often slightly better in the Southern Hemisphere. In general, the performance of S3B is slightly better.

Comprehensive Validation and Comparison of Three VIIRS Aerosol Products over the Ocean on a Global Scale

Three parallel Visible/Infrared Imager Radiometer Suite (VIIRS) aerosol products (SOAR, NOAA, and AERDT) provided data since 2012. It is necessary to study the performances and advantages of different products. This study aims to analyze the accuracy and error of these products over the ocean and compare them with each other. The results show that the three VIIRS ocean aerosol retrievals (including total aerosol optical depth (AOD), fine mode fraction, Ångström exponent (AE), and fine AOD (AODF)) correlate well with AErosol RObotic NETwork (AERONET) retrievals (e.g., correlation >0.895 for AOD and >0.825 for AE), which are comparable to the newest moderate-resolution imaging spectro-radiometer (MODIS) retrievals. Overall, the SOAR retrievals with quality filtering have the best validation accuracy of all parameters. Therefore, it is more recommended to use. The differences in the annual AOD spatial patterns of different products are small (bias < 0.016), but their AE spatial patterns are evidently different (bias > 0.315), indicating the large uncertainty of VIIRS AE. Error analysis shows that the scattering angle and wind speed affect aerosol retrieval. Application of the non-spherical dust model may reduce the dependence of retrieval bias on the scattering angle. Overall, this study provides validation support for VIIRS products usage and possible algorithm improvements.

Interaction of aerosol with meteorological parameters and its effect on the cash crop in the Vidarbha region of Maharashtra, India

Regional weather variability depends on various meteorological variables such as temperature and rainfall. The current research focuses on the variability and trends in annual aerosol optical depth (AOD), temperature (T), and rainfall (RF) in 11 Vidarbha districts. The annual trend analysis of AOD, T, and R is determined using the non-parametric Sen slope and Mann-Kendall (MK) test at a 5% significant level from 1980 to 2019. Annual T and AOD indicate a substantial increase in this study, whereas rainfall shows a non-significant trend (MK, test) over the study period. According to Sen's slope trends, the relatively high rainfall area (Chandrapur = 1.273 and Garchiroli = 4.06) got positive trends, but Gondia and Bhandara districts have negative (Sen's slope = - 2.79 and - 2.56) trends. The moderate rainfall areas are showing a less negative Sen slope (Wardha = - 0.21, Washim = - 1.13 and Yavatmal = - 2.75), whereas Nagpur districts' Sen's slope shows a positive value (Sens's slope = 0.72). The assured rainfall area districts show Sen's slope trends are positive (Akola = 0.45, Amravati = 1.17 and Buldana = 0.42). Sen's slope trend indicates rising rainfall, whereas negative trends indicate decreasing rainfall in the time series. This study has also looked at the effect of RF, AOD, and T on the last two decades' cash crop production (2000-2019) for Vidarbha districts. The relationship between rainfall departure (DRF) and cash crop yield has also been highlighted. Five cash crops, such as cotton (Ct), total cereals (TCrl), total oilseeds (TOsd), total pulses (TPS), and sugarcane (Sc), are selected for the present study.

Analyses of a Lake Dust Source in the Middle East through Models Performance

Drying lakes have become a new source of dust, causing severe problems in surrounding areas. From 2000 to 2017, a statistical study was conducted on Lake Urmia in Iran in the Middle East. The results indicated a significant increase in the annual number of dusty days in stations around the lake and the mean annual aerosol optical depth (AOD) at 550 nm. The sharp decrease in annual snowfall rate over the Lake Urmia area since 2007 has been linked to the lake’s decreasing water level and drying. During a dust storm event from 27 October to 31 October 2017, a local dust storm originated from Lake Urmia before another large-scale dust storm originated from the An-Nafud desert. According to MODIS true-color images, dust particles were lifted from Lake Urmia and transported eastward to the Caspian Sea and the HYSPLIT model. The comparison of the four models under the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) revealed that the models overestimated surface dust concentrations compared to ground-based PM10 measurements. Nevertheless, the NOAA/WRF-Chem and DREAMABOL models simulated higher dust concentrations during the dust period. More emphasis should be placed on the development of dust models for SDS-WAS models in Lake Urmia.

Climatological Characteristics and Aerosol Loading Trends from 2001 to 2020 Based on MODIS MAIAC Data for Tianjin, North China Plain

The North China Plain (NCP) in East Asia has a severe air pollution problem. In this study, the long-term spatial distribution and interannual trends of aerosol optical depth (AOD) were investigated using the MODIS MAIAC (multiangle implementation of the atmospheric correction) dataset from 2001 to 2020 for Tianjin, a city on the NCP. The annual AOD in Tianjin was 0.59 from 2001 to 2020. The average AOD of Tianjin was the highest in summer (0.96), followed by spring (0.58) and autumn (0.51). The annual AOD in Tianjin increased significantly in 2008 (approximately 0.77), and the minimum annual AOD was observed in 2020 (0.41). In summer, AOD in the 11 districts of Tianjin significantly increased from 2001 to 2010 and gradually decreased from 2011 to 2020. The occurrence frequency of AOD in the range of 0.2–0.5 was high in Tianjin accounting for almost 40% of the total proportion. In Tianjin, AOD exhibited a positive trend from 2001 to 2008 and an obvious negative growth trend from 2009 to 2020 due to anthropogenic emission. The findings are valuable for analyzing the climatological characteristics of aerosol loading and their optical properties at the district level of cities on the NCP.

Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia.

Satellite-based aerosol optical depth (AOD) is columnar light extinction by aerosol absorption and scattering and has become the most important variable for the assessment of the spatiotemporal distribution of aerosols at a regional and global level. In this paper, we have used AOD observations of multiangle imaging spectroradiometer (MISR) from September 2002 to May 2017, moderate resolution imaging spectroradiometer (MODIS) from September 2002 to December 2020, and sea-viewing wide field-of-view sensor (SeaWiFS) from September 2002 to December 2010 over South Asia. We have observed the association of AOD with enhanced vegetation index (EVI) and meteorological variables (temperature (TEMP), wind speed (WS), and relative humidity (RH)) acquired from Giovanni during the period September 2002-December 2020. The satellite observations of Terra-, MISR-, and SeaWiFS-AOD were also compared with Aqua-AOD. The findings show that AOD in eastern Pakistan is higher than in the western Pakistan due to increase in population density and biomass burning. Mean annual peak AOD (˃ 0.7) has been observed over the IGB region because of the significant increase in economical, industrial, and agricultural activities while AOD of ˃ 0.6 is observed over Bangladesh. The lowest mean annual AOD of ˂ 0.3 is observed over northeastern Afghanistan, western Nepal, and Bhutan whereas the AOD of 0.3 is seen over Sri Lanka. The highest seasonal mean AOD of 0.8 has been seen over Bihar, India, and AOD of ~ 0.7 is observed over Bangladesh while the lowest AOD is observed over Afghanistan, Sri Lanka, Nepal, and Bhutan during the winter season. However, the mean AOD over eastern Pakistan is maximum in both monsoon and post-monsoon season but relatively low in pre-monsoon and winter. The highest positive seasonal AOD anomalies were observed over South Asia in winter season followed by post-monsoon, pre-monsoon, and least being monsoon. The higher mean AOD anomaly value is found to be 0.2 over eastern Pakistan and western India. In northeastern Pakistan and central India, AOD and RH are positively correlated (r ˃ 0.54) while negatively correlated over Afghanistan, southwestern region of Pakistan, eastern India, Nepal, Bhutan, and Bangladesh. AOD is negatively correlated (r = ~ - 0.3) with EVI over eastern Pakistan and western India. The highest correlation coefficient (r) obtained among Terra and Aqua is 0.97, MISR and Aqua is 0.93, and SeaWiFS and Aqua is 0.58 over South Asia.

Characteristics of aerosol optical depth dynamics and their causes over typical cities along the 21st Century Maritime Silk Road.

Atmospheric aerosols, i.e., suspension of liquid and/or solid particles in air, have serious impacts on human health. Exploring the variation and patterns of regional atmospheric aerosols is of great significance to monitor and evaluate atmosphere quality, especially in urban areas with large population. Here, with nine typical pivotal cities along the 21st Century Maritime Silk Road through Southeast Asia, South Asia to West Asia as case studies, based on MCD19A2 550 nm AOD products, combined meteorological factors, land use data, and nighttime light data, we analyzed the spatio-temporal distribution, variation features, influencing and/or driving factors of aerosols in developed urban areas over Asia. The results showed that the descending sequence of the annual aerosol optical depth (AOD) of the nine cities was Karachi, Doha, Chittagong, Bangkok, Colombo, Ho Chi Minh, Singapore, Gwadar, and Yangon during 2013-2018. Due to the influence of regional climate system and atmospheric aerosol types, the time series of annual, seasonal, and monthly AODs were significantly different. The high values of AODs in most cities were mainly located in the urban center or rapid socio-economic (e.g., industrial and agricultural) development regions. The effects of different meteorological factors on the AODs varied in different cities. The rainfall, relative humidity, and wind speed had great impacts on AODs in Ho Chi Minh, Bangkok, Singapore, and Yangon. Temperature, relative humidity, and wind speed had close correlations with AODs in Chittagong, Colombo, Karachi, and Gwadar of South Asia and Doha in West Asia. The urban area's AOD was influenced by the combined and synergistic effects of socio-economy, urbanization, and meteorological factors, with that in Karachi being the most significant.

Long-term multi-source data analysis about the characteristics of aerosol optical properties and types over Australia

Abstract. The spatiotemporal distributions of aerosol optical properties and major aerosol types, along with the vertical distribution of major aerosol types over Australia, are investigated based on multi-year Aerosol Robotic Network (AERONET) observations at nine sites, the Moderate Resolution Imaging Spectroradiometer (MODIS), Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and back-trajectory analysis from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT). During the observation period from 2001–2020, the annual aerosol optical depth (AOD) at most sites showed increasing trends (0.002–0.029 yr−1), except for that at three sites, Canberra, Jabiru, and Lake Argyle, which showed decreasing trends (−0.004 to −0.014 yr−1). In contrast, the annual Ångström exponent (AE) showed decreasing tendencies at most sites (−0.045 to −0.005 yr−1). The results showed strong seasonal variations in AOD, with high values in the austral spring and summer and relatively low values in the austral fall and winter, and weak seasonal variations in AE, with the highest mean values in the austral spring at most sites. Monthly average AOD increases from August to December or the following January and decreases during March–July. Spatially, the MODIS AOD showed obvious spatial heterogeneity, with high values appearing over the Australian tropical savanna regions, Lake Eyre Basin, and southeastern regions of Australia, while low values appeared over the arid regions in western Australia. MERRA-2 showed that carbonaceous aerosol over northern Australia, dust over central Australia, sulfate over densely populated northwestern and southeastern Australia, and sea salt over Australian coastal regions are the major types of atmospheric aerosols. The nine ground-based AERONET sites over Australia showed that the mixed type of aerosols (biomass burning and dust) is dominant in all seasons. Moreover, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) showed that polluted dust is the dominant aerosol type detected at heights 0.5–5 km over the Australian continent during all seasons. The results suggested that Australian aerosol has similar source characteristics due to the regional transport over Australia, especially for biomass burning and dust aerosols. However, the dust-prone characteristic of aerosol is more prominent over central Australia, while the biomass-burning-prone characteristic of aerosol is more prominent in northern Australia.

Spatio-temporal changes of PM10 trends in South Korea caused by East Asian atmospheric variability

Atmospheric dust loadings strongly depend on the amount of dust emissions and on the atmospheric variability. This study examines trends in PM10 (i.e., a particulate matter with the aerodynamic diameter equal to or less than 10 μm) mass concentrations for South Korea with respect to the East Asian atmospheric variability due to climate warming. The PM10 mass concentrations were used by the nationwide monitoring network of the Korean Ministry of Environment (KME) over the two-decade period of 1999–2018. Annual PM10 in South Korea was found to decrease to −0.61±0.08 μg m−3 yr−1 over the two decades of 1999–2018. Such an overall decrease was more associated with a decreasing trend during spring and summer than during other seasons. An empirical orthogonal function (EOF) analysis of wind speed at 850 hPa accounted for the spatial structure wherein the decrease of wind speeds in Mongolia and China was consistent with those in South Korea during the spring season. Furthermore, the next highest PM10 reduction rate during the stagnant and humid summer period was caused by a warmer air mass over the northwest Pacific Ocean. In eastern China, the annual aerosol optical depth (AOD) reflected by primary and secondary particulate matters showed high values and increased to 0.01 (r2=0.60) for the period of 2000–2013. However, annual AOD values increased negligibly in the Yellow Sea and the Korean Peninsula due more likely to decreasing wind speeds from eastern China. The policy limiting emissions in China since 2014 as well as continuous efforts to reduce air pollution in South Korea affected the AOD decreasing trend. Therefore, the reduced transport and local emissions most likely explain the sharp decreasing trends of PM10 in South Korea during the recent 5-year period of 2014–2018.