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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.

This study presents the spectral monthly and seasonal variation of aerosol optical depth (τAOD), single scattering albedo (SSA), and aerosol absorption optical depth (AAOD) between 2010 and 2018 obtained from the Aerosol Robotic Network (AERONET) over Pokhara, Nepal. The analysis of these column-integrated aerosol optical data suggests significant monthly and seasonal variability of aerosol physical and optical properties. The pre-monsoon season (March to May) has the highest observed τAOD(0.75 ± 0.15), followed by winter (December to February, 0.47 ± 0.12), post-monsoon (October and November, 0.39 ± 0.08), and monsoon seasons (June to September, 0.27 ± 0.13), indicating seasonal aerosol loading over Pokhara. The variability of Ångström parameters, α, and β, were computed from the linear fit line in the logarithmic scale of spectral τAOD, and used to analyze the aerosol physical characteristics such as particle size and aerosol loading. The curvature of spectral τAOD, α’, computed from the second-order polynomial fit, reveals the domination by fine mode aerosol particles in the post-monsoon and winter seasons, with coarse mode dominating in monsoon, and both modes contributing in the pre-monsoon. Analysis of air mass back trajectories and observation of fire spots along with aerosol optical data and aerosol size spectra suggest the presence of mixed types of transboundary aerosols, such as biomass, urban-industrial, and dust aerosols in the atmospheric column over Pokhara.

Atmospheric aerosols affect climate change, air quality, and human health. The aerosol optical depth (AOD) is a widely utilized parameter for estimating the concentration of atmospheric aerosols. Consequently, continuous AOD monitoring is crucial for environmental studies. However, a method to continuously monitor the AOD throughout the day or night remains a challenge. This study introduces a method for estimating the All-Day AOD using ground air quality and meteorological data. This method allows for the hourly estimation of the AOD throughout the day in the Beijing–Tianjin–Hebei (BTH) region and addresses the lack of high temporal resolution monitoring of the AOD during the nighttime. The results of the proposed All-Day AOD estimation method were validated against AOD measurements from Advanced Himawari Imager (AHI) and Aerosol Robotic Network (AERONET). The R[sup.2] between the estimated AOD and AHI was 0.855, with a root mean square error of 0.134. Two AERONET sites in BTH were selected for analysis. The results indicated that the absolute error between the estimated AOD and AERONET was within acceptable limits. The estimated AOD showed spatial and temporal trends comparable to those of AERONET and AHI. In addition, the hourly mean AOD was analyzed for each city in BTH. The hourly mean AOD in each city exhibits a smooth change at night. In conclusion, the proposed AOD estimation method offers valuable data for investigating the impact of aerosol radiative forcing and assessing its influence on climate change.

The purpose of this study is to validate the daily Terra-MODIS level 2 combined dark target (DT) and deep blue (DB) aerosol optical depth (AOD) retrievals with a spatial resolution of 10 km against the ground-based AERONET AOD data to be used in evaluating the air pollution and impact of meteorological variables over Qena, Egypt, in 2019. The regression analysis demonstrated an accepted agreement between the MODIS and AERONET AOD data with a correlation coefficient ( R ) of 0.7118 and 74.22% of the collocated points fall within the expected error (EE) limits. Quality flag filtering and spatial and temporal collocation were found to have a significant impact on the regression results. Quality flag filtering increased R by 0.2091 and % within EE by 17.97, spatial collocation increased R by 0.0143 and % within EE by 1.13, and temporal collocation increased R by 0.0089 and % within EE by 4.43. By validating the MODIS AOD data seasonally and analyzing the temporal distribution of the seasonal AOD data to show the retrieval accuracy variations between seasons, it was found that the MODIS AOD observations overestimated the AERONET AOD values in all seasons, and this may be because of underestimating the surface reflectance. Perhaps the main reason for the highest overestimation in summer and autumn is the transportation of aerosols from other regions, which changes the aerosol model in Qena, making accurate aerosol-type assumptions more difficult. Therefore, this study recommends necessary improvements regarding the aerosol model selection and the surface reflectance calculations. Temperature and relative humidity were found to have a strong negative relationship with a correlation of − 0.735, and both have a moderate association with AOD with a correlation of 0.451 and − 0.356, respectively. Because Qena is not a rainy city, precipitation was found to have no correlation with the other variables.

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

Smoke haze events have increasingly affected Australia’s environmental quality, having demonstrable effects on air quality, climate, and public health. This study employs a hybrid methodology, merging satellite-based aerosol optical depth (AOD) data with Chemical Transport Model (CTM) simulations to comprehensively characterize these events. The AOD data are sourced from the Japan Aerospace Exploration Agency (JAXA), Copernicus Atmosphere Monitoring Service (CAMS), and the Commonwealth Scientific and Industrial Research Organization (CSIRO), and they are statistically evaluated using mean, standard deviation, and root mean square error (RMSE) metrics. Our analysis indicates that the combined dataset provides a more robust representation of smoke haze events than individual datasets. Additionally, the study investigates aerosol distribution patterns and data correlation across the blended dataset and discusses possible improvements such as data imputation and aerosol plume scaling. The outcomes of this investigation contribute to enhancing our understanding of the impacts of smoke haze on various environmental factors and can assist in developing targeted mitigation and management strategies.

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.

Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004-2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.

Black carbon (BC) absorption aerosol optical depth (AAODBC) defines the contribution of BC in light absorption and is retrievable using sun/sky radiometer measurements provided by Aerosol Robotic Network (AERONET) inversion products. In this study, we utilized AERONET-retrieved depolarization ratio (DPR, δp), single scattering albedo (SSA, ω), and Ångström Exponent (AE, å) of version 3 level 2.0 products as indicators to estimate the contribution of BC to the absorbing fractions of AOD. We applied our methodology to the AERONET sites, including North and South America, Europe, East Asia, Africa, India, and the Middle East, during 2000–2018. The long-term AAODBC showed a downward tendency over Sao Paulo (−0.001 year−1), Thessaloniki (−0.0004 year−1), Beijing (−0.001 year−1), Seoul (−0.0015 year−1), and Cape Verde (−0.0009 year−1) with the highest values over the populous sites. This declining tendency in AAODBC can be attributable to the successful emission control policies over these sites, particularly in Europe, America, and China. The AAODBC at the Beijing, Sao Paulo, Mexico City, and the Indian sites showed a clear seasonality indicating the notable role of residential heating in BC emissions over these sites during winter. We found a higher correlation between AAODBC and fine mode AOD at 440 nm at all sites except for Beijing. High pollution episodes, BC emission from different sources, and aggregation properties seem to be the main drivers of higher AAODBC correlation with coarse particles over Beijing.

Emissions of atmospheric pollutants are rapidly increasing over South Asia. A greater understanding of seasonal variability in aerosol concentrations over South Asia is a scientific challenge and has consequences due to a lack of monitoring and modelling of air pollutants. Therefore, this study investigates aerosol patterns and trends over some major cities in the Indo-Gangetic Plain of the South Asia, i.e., Islamabad, Lahore, Delhi, and Dhaka, by using simulations from the Modern -Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) model and satellite measurements (Moderate Resolution Imaging Spectroradiometer, (MODIS)) from 2000 to 2020. The results show that seasonal MODIS–aerosol optical depth (AOD) during 2000−2020 in Lahore is 0.5, 0.52, 0.92, and 0.71, while in Islamabad 0.25, 0.32, 0.45, and 0.38, in Delhi 0.68, 0.6, 1.0, and 0.77, and in Dhaka 0.79, 0.75, 0.78 and 0.55 values are observed during different seasons, i.e., winter, spring, summer, and autumn, respectively. The analysis reveals a significant increase in aerosol concentrations by 25%, 24%, 19%, and 14%, and maximum AOD increased by 15%, 14%, 19%, and 22% during the winter of the last decade (2011–2020) over Islamabad, Lahore, Delhi, and Dhaka, respectively. In contrast, AOD values decreased during spring by −5%, −12%, and −5 over Islamabad, Lahore, and Delhi, respectively. In Dhaka, AOD shows an increasing trend for all seasons. Thus, this study provides the aerosol spatial and temporal variations over the South Asian region and would help policymakers to strategize suitable mitigation measurements.