Inferring wavelength dependence of AOD and Ångström exponent over a sub-tropical station in South Africa using AERONET data: influence of meteorology, long-range transport and curvature effect

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.

An assessment of aerosol optical depth over three AERONET sites in South Africa during the year 2020

It is important to notice that the world health organization (WHO) on  the 11th of March 2020,  declared COVID-19 a global pandemic and in response governments around the world introduced lockdowns that restricted human and traffic movements including South Africa. This pandemic resulted in a total lockdown from 26 March until 16 April 2020 in South Africa with expected  decrease in atmospheric aerosols. In this present study,  the aerosol optical depth (AOD) over Southern Africa based on ground-based remotely sensed data derived from three AERONET sites (Durban, Skukuza and Upington) during 2020 were used to detrermine the restriction resopnse on atmospheric aerosol pollution  The study used data from 2019, 2018 and 2017  as base years. The AERONET derived data was complemented with the HYSPLIT Model and NCEP/NCAR Reanalysis data. The study findings show that peak increase of AOD corresponds to Angstrom exponent (AE) enhancement for two sites Durban and Skukuza during winter (JJA) while the Upington site showed a different trend where peak AOD were observed in spring (SON). The study also observed the influence of long transport airmasses particularly those originating from the Atlantic and Indian ocean moreso for the Durban and Skukuza sites (summer and autumn) thus these sites received fresh marine aerosols however this was not the case for Upington which fell under the influence of short-range inland airmasses and was likely to receive anthropogenic and dust aerosols. The major results  suggest that the lockdowns did not translate into a significant decrease in AOD levels compared to previous immediate years. The results has presented restriction response of AOD over South Africa but additional analysis is required using more locations to compare results.

An assessment of NO2 atmospheric air pollution over three cities in South Africa during 2020 COVID-19 pandemic

To contain the spread of COVID-19 in 2020, several governments around the world imposed national lockdowns including that of South Africa. The purpose of this study was to investigate and give an overview of nitrogen dioxide column levels during the year 2020 over three South African cities (Johannesburg, Durban and Cape Town) using AURA OMI derived measurements, the HYSPLIT model, complemented with NCEP/NCAR reanalysis data. Our findings were that in 2020, all the cities recorded their daily maximum mean NO₂ column levels during the winter season at 14.1 × 10¹⁵ molecules per cm², 3.1 × 10¹⁵ molecules per cm² and 1.7 × 10¹⁵ molecules per cm² for Johannesburg, Durban, and Cape Town respectively. Across all seasons, Cape Town recorded the lowest seasonal mean at 0.6 × 10¹⁵ molecules per cm² (summer 2020) while the highest seasonal mean was recorded over Johannesburg at 9 × 10¹⁵ molecules cm² (winter 2020). Furthermore, an interannual comparison analysis indicated that during summer, there were increases of 6%, 1% and 30% for Johannesburg, Durban and Cape Town respectively. During winter, Johannesburg saw an increase of 19% while a 2% increase was recorded in Durban with Cape town recording a 16% decrease in NO₂ column levels. The study also recorded that Cape Town and Durban were mainly influenced by long-range transport air masses originating from the South Atlantic Ocean, South America, Antarctica and the Indian Ocean particularly during the summer and autumn seasons possibly leading to the formation of marine nitrate aerosols.

State of ambient air quality in a low-income urban settlement of South Africa

Air pollution remains one of the leading global environmental-health challenges the world is facing today, particularly within urban environments. amidst the COVID-19 pandemic, air pollution has been brought back into the spotlight as both attack the human respiratory systems. The purpose of the study was to investigate the quality of ambient air in a low-income urban settlement of Jabavu located within the City of Johannesburg during the year 2018. Air pollution and meteorological data were gathered from the South African Air Quality System network. The study focused on three pollutants namely PM₁₀, SO₂ and O₃. Findings were that the seasonal ambient mean concentrations for PM₁₀ in summer was (28.99 µg/m³), autumn (33.32 µg/m³), winter (61.71 µg/m³) and spring (48.44 µg/m³). On the other hand, the seasonal ambient mean concentrations for SO₂ was summer (4.45ppb), autumn (3.19ppb), winter (5.65ppb) and spring (3.54ppb). The O₃ seasonal ambient mean concentrations were summer (40.97ppb), autumn (21.01ppb), winter (15.90ppb) and spring (33.59ppb). Furthermore, the study observed that in summer, winter and spring the dominant long-range transport air masses originated from the South Atlantic Ocean, Madagascar Island-India Ocean and the Indian Ocean while in autumn the dominant air masses are short-range inland air masses. For SO₂ and PM_10, ambient concentrations were found to be more problematic during winter; while for O₃ substantial levels were unexpectedly recorded in summer. When analysing the diurnal profiles of PM₁₀, SO₂ and O_3, each of these pollutants revealed a unique distribution pattern, which, despite having seasonal variance, was consistent throughout the year. For instance, irrespective of the season, PM₁₀ mostly peaked in the mornings and evenings; meanwhile SO₂ and O₃ often spiked during the midday and mid-afternoon, respectively. These findings indicate that air quality within this low-income settlement is poor. To improve air quality within low-income settlements there is a need for a shift from reliance on solid fuels to cleaner energy sources such as LP gas, biogas and solar accompanied by an increase in community awareness about air quality issues. This study contributes to knowledge building within the air quality monitoring scientific community while for policymakers it assists in policy formulation to enable air quality management.

Application of Semi-Empirical Models Based on Satellite Images for Estimating Solar Irradiance in Korea

The application of solar energy as a renewable energy source has significantly escalated owing to its abundance and availability worldwide. However, the intermittent behavior of solar irradiance is a serious disadvantage for electricity grids using photovoltaic (PV) systems. Thus, reliable solar irradiance data are vital to achieve consistent energy production. Geostationary satellite images have become a solution to this issue, as they represent a database for solar irradiance on a massive spatiotemporal scale. The estimation of global horizontal irradiance (GHI) using satellite images has been developed based on physical and semi-empirical models, but only a few studies have been dedicated to modeling GHI using semi-empirical models in Korea. Therefore, this study conducted a comparative analysis to determine the most suitable semi-empirical model of GHI in Korea. Considering their applicability, the Beyer, Rigollier, Hammer, and Perez, models were selected to estimate the GHI over Seoul, Korea. After a comparative evaluation, the Hammer model was determined to be the best model. This study also introduced a hybrid model and applied a long short-term memory (LSTM) model in order to improve prediction accuracy. The hybrid model exhibited a smaller root-mean-square error (RMSE), 97.08 W/m2, than that of the Hammer model, 103.92 W/m2, while producing a comparable mean-bias error. Meanwhile, the LSTM model showed the potential to further reduce the RMSE by 11.2%, compared to the hybrid model.

Aerosol Trends during the Dusty Season over Iran

This study assessed the aerosol climatology over Iran, based on the monthly data of aerosol optical depth (AOD) derived from the reanalysis-based Modern Era Retrospective Analysis for Research and Applications (MERRA-2) and the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS). In addition, sea level pressure, wind speed, temperature, relative humidity, precipitation, and soil moisture from the ERA5 reanalysis dataset were applied to investigate the climate-related effects on temporal AOD changes. Our analysis identified positive and negative AOD trends during 2000–2010 and 2010–2018, respectively, which are likely linked to aeolian dust changes. The dust-driven AOD trends were supported by changes in the Ångström exponent (AE) and fine mode fraction (FMF) of aerosols over Iran. During the early period (2000–2010), results of AOD-meteorology correlation analyses suggest reduced soil moisture, leading to increased dust emissions, whereas our results suggest that during the later period (2010–2018) an increase of soil moisture led to decreased AOD levels. Soil moisture appears to be a key factor in dust mobilization in the region, notably in southwestern Iran, being influenced by adjacent mineral dust sources. These phenomena were affected by large-scale sea level pressure transformations and the associated meteorology in the preceding winter seasons. Using a multiple linear regression model, AOD variability was linked to various meteorological factors in different regions. Our results suggest that climatic variations strongly affect the dust cycle, with a strong dependence on wintertime conditions in the region.

Gradient boosting machine learning to improve satellite-derived column water vapor measurement error

The atmospheric products of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm include column water vapor (CWV) at a 1 km resolution, derived from daily overpasses of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Aqua and Terra satellites. We have recently shown that machine learning using extreme gradient boosting (XGBoost) can improve the estimation of MAIAC aerosol optical depth (AOD). Although MAIAC CWV is generally well validated (Pearson's R >0.97 versus CWV from AERONET sun photometers), it has not yet been assessed whether machine-learning approaches can further improve CWV. Using a novel spatiotemporal cross-validation approach to avoid overfitting, our XGBoost model, with nine features derived from land use terms, date, and ancillary variables from the MAIAC retrieval, quantifies and can correct a substantial portion of measurement error relative to collocated measurements at AERONET sites (26.9% and 16.5% decrease in root mean square error (RMSE) for Terra and Aqua datasets, respectively) in the Northeastern USA, 2000-2015. We use machine-learning interpretation tools to illustrate complex patterns of measurement error and describe a positive bias in MAIAC Terra CWV worsening in recent summertime conditions. We validate our predictive model on MAIAC CWV estimates at independent stations from the SuomiNet GPS network where our corrections decrease the RMSE by 19.7% and 9.5% for Terra and Aqua MAIAC CWV. Empirically correcting for measurement error with machine-learning algorithms is a postprocessing opportunity to improve satellite-derived CWV data for Earth science and remote sensing applications.

The climatology of aerosol optical thickness and radiative effects in Southeast Asia from 18-years of ground-based observations

The present study utilizes 18 years of long-term (2001-2018) data collected from six active AERONET sites over the Indo-Gangetic Plain (IGP) and the North China Plain (NCP) areas in Southeast Asia. The annual mean (±SD) aerosol optical thickness at 440 nm (AOT₄₄₀) was found high at XiangHe (0.92 ± 0.69) and Taihu (0.90 ± 0.51) followed by Beijing (0.81 ± 0.69), Lahore (0.81 ± 0.43), and Kanpur (0.73 ± 0.35) and low at Karachi (0.52 ± 0.23). Seasonally, high AOT₄₄₀ with corresponding high Ångström exponent (ANG_440-870) noticed during JJA for all sites, except Kanpur, suggesting the dominance of fine-mode particles, generally associated with large anthropogenic emissions. Climatologically, an increasing (decreasing) trend was observed over IGP (NCP) sites, with the highest (lowest) percentage of departures in AOT₄₄₀ found over Beijing (Karachi). We further identified major aerosol types which showed the dominance of biomass burning, urban-industrial followed by the mixed type of aerosols. In addition, single scattering albedo (SSA), asymmetry parameter (ASP), volume size distribution (VSD), and complex aerosol refractive index (RI) showed significant temporal and spectral changes, illustrating the complexity of aerosol types. At last, the annual mean direct aerosol radiative forcing at the top, bottom, and within the atmosphere for all sites were found in the range from -17.36 ± 3.75 to -45.17 ± 4.87 W m^-2, -64.6 ± 4.86 to -93.7 ± 10.27 W m^-2, and 40.5 ± 6.43 to 68.25 ± 7.26 W m^-2, respectively, with an averaged atmospheric heating rate of 0.9-2.3 K day^-1. A large amount of anthropogenic aerosols showed a significant effect of heating (cooling) on the atmosphere (surface) results obviously, due to an increased rate of atmospheric heating. Therefore, the thermodynamic effects of anthropogenic aerosols on the atmospheric circulation and its structure should be taken into consideration for future study over the experimental sites.

Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets

With the rapid development of China's economy and high rate of industrialization, environmental pollution has become a major challenge for the country. The present study is aimed at analyzing spatiotemporal heterogeneities and changes in trends of different aerosol optical properties observed over China. To achieve this, Collection 6 Level 3 data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS; 2002-2016) and Ozone Monitoring Instrument (OMI; 2005-2016) sensors were used to investigate aerosol optical depth (AOD₅₅₀), Ångstrӧm exponent (AE_470-660), and Absorption Aerosol Index (AAI). The spatial distribution of annual mean AOD₅₅₀ was noticed to be high over economically and industrialized regions of the east, south, and northeast of China, while low aerosol loadings were located over rural and less-developed areas of the west and northeast of China. High AE_470-660 (> 1.0) values were characterized by the abundance of fine-mode particles and vice versa, likely attributed to large anthropogenic activities. Similarly, high AOD with corresponding high AE and low AAI was characterized over the urban-industrialized regions of the central, east, and south of China during most of the months, being more pronounced in June and July. On seasonal scale, AOD values were found to be high during spring, followed by the summer and autumn, and low during the winter season. It is also evident that all aerosol parameters showed a single-peak frequency distribution in all seasons over entire China. Further, the annual, monthly, and seasonal spatial trends revealed a decreasing trend in AOD over most regions of China, except in the southwest of China, which showed a positive increasing trend. Significant increasing trends were noted in AAI for all the seasons, particularly during autumn and winter, resulting in a large amount of the absorbing type of aerosols produced from biomass burning and desert dust.

Characteristics of columnar aerosol optical and microphysical properties retrieved from the sun photometer and its impact on radiative forcing over Skukuza (South Africa) during 1999-2010

The detailed analysis of columnar optical and microphysical properties of aerosols obtained from the AErosol RObotic NETwork (AERONET) Cimel sun photometer operated at Skukuza (24.98° S, 31.60° E, 150 m above sea level), South Africa was carried out using the level 2.0 direct sun and inversion products measured during 1999-2010. The observed aerosol optical depth (AOD) was generally low over the region, with high values noted in late winter (August) and mid-spring (September and October) seasons. The major aerosol types found during the study period were made of 3.74, 69.63, 9.34, 8.83, and 8.41% for polluted dust (PD), polluted continental (PC), non-absorbing (NA), slightly absorbing (SA), and moderately absorbing (MA) aerosols, respectively. Much attention was given to the aerosol fine- and coarse-modes deduced from the particle volume concentration, effective radius, and fine-mode volume fraction. The aerosol volume size distribution pattern was found to be bimodal with the fine-mode showing predominance relative to coarse-mode during the winter and spring seasons, owing to the onset of the biomass burning season. The mean values of total, fine-, and coarse-mode volume particle concentrations were 0.07 ± 0.04, 0.03 ± 0.03, and 0.04 ± 0.02 μm³ μm^-2, respectively, whereas the mean respective effective radii observed at Skukuza for the abovementioned modes were 0.35 ± 0.17, 0.14 ± 0.02, and 2.08 ± 0.02 μm. The averaged shortwave direct aerosol radiative forcing (ARF) observed within the atmosphere was found to be positive (absorption or heating effect), whereas the negative forcing in the surface and TOA depicted significant cooling effect due to more scattering type particles.

Optical and radiative properties of aerosols over Desalpar, a remote site in western India: Source identification, modification processes and aerosol type discrimination

Aerosol optical properties are analyzed for the first time over Desalpar (23.74°N, 70.69°E, 30m above mean sea level) a remote site in western India during October 2014 to August 2015. Spectral aerosol optical depth (AOD) measurements were performed using the CIMEL CE-318 automatic Sun/sky radiometer. The annual-averaged AOD₅₀₀ and Ångström exponent (α_440-870) values are found to be 0.43±0.26 and 0.69±0.39, respectively. On the seasonal basis, high AOD₅₀₀ of 0.45±0.30 and 0.61±0.34 along with low α_440-870 of 0.41±0.27 and 0.41±0.35 during spring (March-May) and summer (June-August), respectively, suggest the dominance of coarse-mode aerosols, while significant contribution from anthropogenic sources is observed in autumn (AOD₅₀₀=0.47±0.26, α_440-870=1.02±0.27). The volume size distribution and the spectral single-scattering albedo also confirm the presence of coarse-mode aerosols during March-August. An overall dominance of a mixed type of aerosols (~56%) mostly from October to February is found via the AOD₅₀₀ vs α_440-870 relationship, while marine aerosols contribute to ~18%. Spectral dependence of α and its second derivative (α') are also used for studying the aerosol modification processes. The average direct aerosol radiative forcing (DARF) computed via the SBDART model is estimated to range from -27.08Wm^-2 to -10.74Wm^-2 at the top of the atmosphere, from -52.21Wm^-2 to -21.71Wm^-2 at the surface and from 10.97Wm^-2 to 26.54Wm^-2 within the atmosphere. This atmospheric forcing translates into heating rates of 0.31-0.75Kday^-1. The aerosol properties and DARF are also examined for different trajectory clusters in order to identify the sources and to assess the influence of long-range transported aerosols over Desalpar.

Column-integrated aerosol optical properties and direct radiative forcing over the urban-industrial megacity Nanjing in the Yangtze River Delta, China

Aerosol optical properties were measured and analyzed through the ground-based remote sensing Aerosol Robotic Network (AERONET) over an urban-industrial site, Nanjing (32.21° N, 118.72° E, and 62 m above sea level), in the Yangtze River Delta, China, during September 2007-August 2008. The annual averaged values of aerosol optical depth (AOD500) and the Ångström exponent (AE440-870) were measured to be 0.94 ± 0.52 and 1.10 ± 0.21, respectively. The seasonal averaged values of AOD500 (AE440-870) were noticed to be high in summer (autumn) and low in autumn (spring). The characterization of aerosol types showed the dominance of mixed type followed by the biomass burning and urban-industrial type of aerosol at Nanjing. Subsequently, the curvature (a 2) obtained from the second-order polynomial fit and the second derivative of AE (α') were also analyzed to understand the dominant aerosol type. The single scattering albedo at 440 nm (SSA440) varied from 0.88 to 0.93 with relatively lower (higher) values during the summer (spring), suggesting an increase in black carbon and mineral dust (desert dust) aerosols of absorbing (scattering) nature. The averaged monthly and seasonal evolutions of shortwave (0.3-4.0 μm) direct aerosol radiative forcing (DARF) values were computed from the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model both at the top of atmosphere (TOA) and bottom of atmosphere (SUR) during the study period. Further, the aerosol forcing efficiency (AFE) and the corresponding atmospheric heating rates (AHR) were also estimated from the forcing within the atmosphere (ATM). The derived DARF values, therefore, produced a warming effect within the atmosphere due to strong absorption of solar radiation.

Savanna Tree Seedlings are Physiologically Tolerant to Nighttime Freeze Events

Freeze events can be important disturbances in savanna ecosystems, yet the interactive effect of freezing with other environmental drivers on plant functioning is unknown. Here, we investigated physiological responses of South African tree seedlings to interactions of water availability and freezing temperatures. We grew widely distributed South African tree species (Colophospermum mopane, Combretum apiculatum, Acacia nigrescens, and Cassia abbreviata) under well-watered and water-limited conditions and exposed individuals to nighttime freeze events. Of the four species studied here, C. mopane was the most tolerant of lower water availability. However, all species were similarly tolerant to nighttime freezing and recovered within one week following the last freezing event. We also show that water limitation somewhat increased freezing tolerance in one of the species (C. mopane). Therefore, water limitation, but not freezing temperatures, may restrict the distribution of these species, although the interactions of these stressors may have species-specific impacts on plant physiology. Ultimately, we show that unique physiologies can exist among dominant species within communities and that combined stresses may play a currently unidentified role in driving the function of certain species within southern Africa.

An overview of regional and local characteristics of aerosols in South Africa using satellite, ground, and modeling data

We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during austral spring (September-October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM₁₀ concentrations as much as 136 % higher in townships that in industrial areas. We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.

Direct radiative forcing of urban aerosols over Pretoria (25.75°S, 28.28°E) using AERONET Sunphotometer data: first scientific results and environmental impact

The present study uses the data collected from Cimel Sunphotometer of Aerosol Robotic Network (AERONET) for the period from January to December, 2012 over an urban site, Pretoria (PTR; 25.75°S, 28.28°E, 1449 m above sea level), South Africa. We found that monthly mean aerosol optical depth (AOD, τ(a)) exhibits two maxima that occurred in summer (February) and winter (August) having values of 0.36 ± 0.19 and 0.25 ± 0.14, respectively, high-to-moderate values in spring and thereafter, decreases from autumn with a minima in early winter (June) 0.12 ± 0.07. The Angstrom exponents (α440-870) likewise, have its peak in summer (January) 1.70 ± 0.21 and lowest in early winter (June) 1.38 ± 0.26, while the columnar water vapor (CWV) followed AOD pattern with high values (summer) at the beginning of the year (February, 2.10 ± 0.37 cm) and low values (winter) in the middle of the year (July, 0.66 ± 0.21 cm). The volume size distribution (VSD) in the fine-mode is higher in the summer and spring seasons, whereas in the coarse mode the VSD is higher in the winter and lower in the summer due to the hygroscopic growth of aerosol particles. The single scattering albedo (SSA) ranged from 0.85 to 0.96 at 440 nm over PTR for the entire study period. The averaged aerosol radiative forcing (ARF) computed using SBDART model at the top of the atmosphere (TOA) was -8.78 ± 3.1 W/m², while at the surface it was -25.69 ± 8.1 W/m² leading to an atmospheric forcing of +16.91 ± 6.8 W/m², indicating significant heating of the atmosphere with a mean of 0.47K/day.