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The studies related to aerosol and cloud properties are rare over the South Eastern African continent despite their significant influence on the regional climate. The present work is aimed at analyzing the spatiotemporal correlations between aerosol and cloud properties during 2008–2017 derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) over the Republic of Malawi, Southeast Africa. The annual mean aerosol optical depth at 550 nm (AOD550) was found high (>0.23) around the Lake Malawi and its environments, and in the southern parts of the study domain, characterized by dense population and increased anthropogenic activities. Whereas, low AOD centers were noticed over the high-altitude locations of central Malawi. The seasonal mean AOD550 was found high during September-October-November (SON) (0.32) and June-July-August (JJA) (0.24) December-January-February (DJF) (0.2), and lowest in March-April-May (MAM) (0.16). The Angstrom exponent (AE412-470) sensitive to fine-mode particles was found high (>1.2) in most of the regions during the study period. The trend analysis from the linear regression technique found a general increase in AOD, except during SON was characterized by decreasing AOD. Besides, we investigated on understanding the relationship between AOD and cloud microphysical properties over the domain. The AOD550 exhibited a negative correlation with cloud fraction (CF) and the cloud effective radius (CER). However, it showed a positive correlation with cloud top temperature (CTT) in areas of high AOD. Finally, the results from the backward trajectory analysis revealed that aerosols over Malawi were associated with long-range transport from the Arabian Deserts, Madagascar Island, Central Africa, and the Indian Ocean, along with locally produced aerosols during different seasons. The findings may be useful to better understand the sources and climatic effects of atmospheric aerosols in southeast Africa.

The present study focused on investigating the aerosol optical properties and direct aerosol radiative forcing (DARF) using the AERONET Sunphotometer measurements conducted during 2011–2017 over an urban-industrial city, Pretoria (25.75° S, 28.28° E) located in the Northwest of South Africa (SA). Results revealed high aerosol optical depth (AOD440) and Angstrom exponent (AE440–870) during SON (0.28 ± 0.09, 1.46 ± 0.16) and DJF (0.24 ± 0.07, 1.48 ± 0.18) indicating the dominance of anthropogenic fine-mode aerosols from biomass burning. The single scattering albedo (SSA440) reached a maximum of 0.90 ± 0.05 in DJF and minimum (0.85 ± 0.04) during JJA. The source analysis from the concentration-weighted trajectory (CWT) model exhibited large heterogeneity in all seasons. However, the region is influenced by distinct aerosol types with the abundance of anthropogenic fine absorbing aerosols (86%) and the invisible ratio of dust particles. In addition, the aerosol volume size distribution (VSD) increased with an increasing AOD, exhibiting a bimodal lognormal structure, with a more pronounced peak in fine- relative to coarse-mode particles. Further, the inversion products showed a strong spectral dependence in SSA with substantial heterogeneity in all seasons. At last, the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model showed that the DARF within the atmosphere was more pronounced during SON (46.71 W m−2) and JJA (46.39 W m−2) due to significant differences in AOD and SSA, with an annual mean value of 33.16 W m−2, and the corresponding atmospheric heating rate of 0.96 K day−1. The study provides information on the existing aerosol distribution and their potential impact on climatic change over an urban city in the Northwest of SA and could form a basis for policymaking over the region.

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

The unprecedented increase in anthropogenic activities, coupled with the prevailing climatic conditions, has increased the aerosol load over East Africa (EA). Given this, the present study examined the trends in total, absorption, scattering, and total aerosol extinction optical depth (TAOD, AAOD, SAOD, and TAEOD) over EA, alongside trends in single scattering albedo (SSA). For this purpose, the AOD of different optical properties retrieved from multiple sensors and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) model between January 2001 to December 2019 were utilized to estimate trends and assess their statistical significance. The spatial patterns of seasonal mean AOD from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor and MERRA-2 model were generally characterized with high (0.35) and low (0.2) AOD centers over EA observed during the local dry and wet seasons, respectively. Also, the spatial trend analysis revealed a general increase in TAOD, being positive and significant over the arid and semi-arid zones of the northeastern part of EA, which is majorly dominated by locally derived dust. The local dry (wet) months generally experienced positive (negative) trends in TAOD, associated with seasonal cycles of rainfall. High and significant positive trends in AAOD were dominated over the study domain, attributed to an increased amount of biomass burning, variations in soil moisture, and changes in the rainfall pattern. The trends in TAEOD showed a distinct pattern, except over some months that depicted significant increasing trends attributed to changes in climatic conditions and anthropogenic activities. At last, the study domain exhibited decreasing trends in SSA, signifying strong absorption of direct solar radiation resulting in a warming effect. The study revealed patterns of trends in aerosol optical properties and forms the basis for further research in aerosols over EA.

Air stagnation modulates the frequency and duration of haze events. Based on meteorological and environmental observation data during 1980 to 2013, the present study analyzed the relationship between the interannual variations of Sea Surface Temperature (SST) over tropical central-eastern Pacific and the number of winter haze days (WHD) over the Southern China (SC) region. The potential preceding signal of Sea Surface Temperature anomalies (SSTAs) in Nino3.4 region associated with ENSO can be used as a predictor of haze occurrences in winter. Results indicate that the detrended WHD in the SC is significantly correlated (r = −0.55) with the contemporary SSTAs in Nino3.4 region. The winters with warm Nino3.4 SSTAs in (El Nino) tend to be accompanied with less haze events in the SC, resulting from more local precipitation and enhanced mid-level winds, which helps to build an unstable condition that is conductive for the decrease of haze occurrence. The precursory signal of WHD variability can be detected in the tropical central-eastern Pacific SST, which is amplified since August to winter season. Based on the August–October mean SSTAs in Nino3.4 and three other identified predictors, we developed a seasonal prediction model of the WHD using RF regression method. The model accounted for 90% of the total variance of the WHD in the SC and ranked the SSTAs in Nino3.4 as the most important predictor. This implies that the SSTAs tropical Pacific play a significant role in the variability of WHD in the SC. Since the predictors can be readily monitored in real time, the model provides a real time forecast tool and could brighten the prospects for seasonal forecast of haze anomalies in vulnerable regions such as the SC.

The paucity of reliable ground based datasets remains a major challenge over Kenya. In the advent of extreme wetness or drought events, reliable precipitation estimates for local characterization is a long overdue process. In the present study, four Satellite derived Precipitation Estimates (SPE): TMPA V7 3B42, PERSIANN-CDR, CHIRPS, and ARC2, are assessed over four homogeneous zones in Kenya with gauge based data during 1998 -2016. Results show that variations of SPE products are based on complex geomorphology of different climatic zones. All SPE products depict bimodal annual precipitation pattern with west-east gradient representing heavier to lighter precipitation events. The Monthly analysis reveal good statistical agreement with reference datasets despite underestimation of precipitation in most regions. Seasonal precipitation events show that the PERSIANN-CDR perform better along low altitude humid climate and western zones around Lake Basin while ARC2 has uniform performance as gauge stations over highlands regions. Strong positive linear relationship on annual scale is evident in most SPE products with CHIRPS, ARC2, and TMPA exhibiting relatively high correlation (r) and minimum root mean squareerror (RMSE), except for PERSIANN-CDR. Overall, the findings of this study show the potentials of SPE products for applications over study domain. The TMPA V7 and PERSIANN-CDR could be useful in understanding individual floods events. Since the CHIRPS perform relatively well over ASAL regions, it could be utilized in monitoring droughts events.

The Republic of Kazakhstan, by geographical and climatological conditions, is a key location for the characterization of atmospheric aerosols due to an unprecedented increase of aerosol's concentrations in the recent years. This study presents a 13-year (2003-2015) analysis of the spatiotemporal distributions and trends of aerosol and cloud properties derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)–Aqua (Dark Target–DT) and Ozone Monitoring Instrument (OMI) over Kazakhstan. The spatial patterns of annual mean AOD were generally characterized with low ( 035) AOD centers over Kazakhstan. The respective maximum and minimum values of AOD550 were observed in July (0.22 ± 0.07) and November (0.12 ± 0.03), with an annual mean of 0.18 ± 0.03. The seasonal mean values of AOD was noticed to be maximum (0.21 ± 0.02) during summer and minimum (0.14 ± 0.01) during autumn seasons. The inter-annual variations in AOD showed enhanced AOD values during 2012 (0.23) followed by 2014 (0.21) and low during 2003 (0.15) and 2004 (0.14). The spatial trend analysis revealed an increase in AOD over most parts of the study domain. Also, the most important cloud parameters such as cloud fraction (CF) and cloud effective radius (CER) were investigated to assess their relationship with the AOD over Kazakhstan. It was found that the CF and CER were negatively and positively correlated with AOD over most parts of the study domain attributed to the strong influence of dust and continental background aerosols, respectively. The backward trajectories obtained from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model showed air parcels originating from the Barents Sea, Russia, Europe, China, and the mainland of Kazakhstan. The results derived from the present study gives a sense of aerosol and cloud properties, and form a basis for further research over this unique and unexplored landmass of the Asian Continent.

In the present study, the spatial-temporal distribution and estimation of trends of different aerosol optical properties, and related impact factors were investigated over three countries: Ghana, Togo, and Benin along the Gulf of Guinea Coast in Southern West Africa (SWA). For this purpose, long-term satellite derived aerosol optical properties (aerosol optical depth at 550 nm; AOD550, Angstrom exponent at 470–660 nm; AE470-660, and absorption aerosol index; AAI) retrieved from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) during January 2005–December 2015 were utilized. The annual mean spatial distribution of AOD550 was found to be high (>0.55) over the southern coastal area, moderate-to-high (0.35–0.55) over the central, and low (

A better understanding of aerosol optical, microphysical and radiative properties is a crucial challenge for climate change studies. In the present study, column-integrated aerosol optical and radiative properties observed at a rural site, Mbita (0.42°S, 34.20 °E, and 1125 m above sea level) located in Kenya, East Africa (EA) are investigated using ground-based Aerosol Robotic Network (AERONET) data retrieved during January, 2007 to December, 2015. The annual mean aerosol optical depth (AOD500 nm), Angstrom exponent (AE440–870 nm), fine mode fraction of AOD500 nm (FMF500 nm), and columnar water vapor (CWV, cm) were found to be 0.23 ± 0.08, 1.01 ± 0.16, 0.60 ± 0.07, and 2.72 ± 0.20, respectively. The aerosol optical properties exhibited a unimodal distribution with substantial seasonal heterogeneity in their peak values being low (high) during the local wet (dry) seasons. The observed data showed that Mbita and its environs are significantly influenced by various types of aerosols, with biomass burning and/or urban-industrial (BUI), mixed (MXD), and desert dust (DDT) aerosol types contributing to 37.72%, 32.81%, and 1.40%, respectively during the local dry season (JJA). The aerosol volume size distribution (VSD) exhibited bimodal lognormal structure with a geometric mean radius of 0.15 μm and 3.86–5.06 μm for fine- and coarse-mode aerosols, respectively. Further, analysis of single scattering albedo (SSA), asymmetry parameter (ASY) and refractive index (RI) revealed dominance of fine-mode absorbing aerosols during JJA. The averaged aerosol direct radiative forcing (ARF) retrieved from the AERONET showed a strong cooling effect at the bottom of the atmosphere (BOA) and significant warming within the atmosphere (ATM), representing the important role of aerosols played in this rural site of Kenya. Finally, the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model revealed that aerosols from distinct sources resulted in enhanced loading during JJA.

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), Angstrӧm exponent (AE470–660), 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 AE470–660 (> 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.

Over the last two decades, a number of space-borne sensors have been used to retrieve aerosol optical depth (AOD). The reliability of these datasets over East Africa (EA), however, is an important issue in the interpretation of regional aerosol variability. This study provides an intercomparison and validation of AOD retrievals from the MODIS-Terra (DT and DB), MISR and OMI sensors against ground-based measurements from the AERONET over three sites (CRPSM_Malindi, Nairobi, and ICIPE_Mbita) in Kenya, EA during the periods 2008–2013, 2005–2009 and 2006–2015, respectively. The analysis revealed that MISR performed better over the three sites with about 82.5% of paired AOD data falling within the error envelope (EE). MODIS-DT showed good agreement against AERONET with 59.05% of paired AOD falling within the sensor EE over terrestrial surfaces with relatively high vegetation cover. The comparison between MODIS-DB and AERONET revealed an overall lower performance with lower Gfraction (48.93%) and lower correlation r = 0.58; while AOD retrieved from OMI showed less correspondence with AERONET data with lower Gfraction (68.89%) and lowest correlation r = 0.31. The monthly evaluation of AODs retrieved from the sensors against AERONET AOD indicates that MODIS-DT has the best performance over the three sites with highest correlation (0.71–0.84), lowest RMSE and spread closer to the AERONET. Regarding seasonal analysis, MISR performed well during most seasons over Nairobi and Mbita; while MODIS-DT performed better than all other sensors during most seasons over Malindi. Furthermore, the best seasonal performance of most sensors relative to AERONET data occurred during June–August (JJA) attributed to modulations induced by a precipitation-vegetation factor to AOD satellite retrieval algorithms. The study revealed the strength and weakness of each of the retrieval algorithm and forms the basis for further research on the validation of satellite retrieved aerosol products over EA.

The present study is aimed at analyzing spatial and temporal characteristics of aerosols retrieved from MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) sensors over East Africa (EA). Data spanning for a period of 15 years during 2001–2015 was used to investigate aerosol optical depth (AOD550), Angstrom exponent (AE470-660) and absorption aerosol Index (AAI) over EA and selected locations within EA. Validation results of MODIS-Terra versus the Aerosol Robotic NETwork (AERONET) AOD550 revealed that the former underestimated aerosol loading over the studied regions due to uncertainties in surface reflectance. The annual mean AOD550, AAI, and AE470-660 were found to be 0.20 ± 0.01, 0.81 ± 0.03, and 1.39 ± 0.01, respectively with peak values observed during the local dry seasons. The spatial seasonal distributions of mean AOD550 suggested high (low) values during the local dry (wet) periods. The high AOD values found along the borders of southwest of Uganda were attributed to smoke particles; while higher (lower) values of AE470-660 (AAI) dominated most parts of the study domain. Low AOD (0.1–0.2) centers were located in high-altitude regions with relatively high vegetation cover over western and central parts of Kenya, and central and northern parts of Tanzania. Furthermore, latitudinal and longitudinal gradients in AOD550 showed a “southern low and northern high” and a “western low and eastern high” profile, respectively during JJA, as other seasons showed heterogeneous variations. Trend analysis revealed a general increase in AOD and AAI and a decrease in AE; while impact factors significantly affected AOD distribution over EA. HYSPLIT back trajectory analyses revealed diverse transport pathways originated from the Arabian Deserts, central Africa, and southwest of Indian Ocean along with locally produced aerosols during different seasons.

Monitoring of particulate matter (PM) is important in air quality, public health, and epidemiological studies and in decision-making for policy implementation. In the present study, the temporal variability of surface-measured PM concentrations ([PM]) and their relationship with meteorological variables and aerosol optical depth (AOD), with the aid from source apportionment studies, are investigated at four urban cities in the Chinese Yangtze River Delta (YRD) region during January 2014 to December 2017. The annual mean concentrations of [PM2.5] ([PM10]) observed at Shanghai (SH), Nanjing (NJ), Hangzhou (HZ), and Hefei (HF) were 46.98 ± 12.21, 54.84 ± 46.14, 52.82 ± 16.98, and 64.03 ± 20.57 μg m−3 (68.07 ± 14.33, 96.48 ± 26.86, 83.08 ± 22.38, and 97.61 ± 20.19 μg m−3), respectively. However, the [PM] exceeded the Chinese National Air Quality Standards of GB3095-2012, being higher (lower) during winter (summer). The [PM] was found higher in the morning (08:00–10:00 LT) and evening (18:00–20:00 LT) and lower in early morning (04:00 LT) and afternoon (14:00 LT) attributed to the dynamics of boundary layer height and varied emission sources. With an annual mean of 0.6–0.7, the PM ratio (PMr = PM2.5/PM10) was observed to have a single peak distribution in all seasons indicating the dominance of fine particles (PM2.5). Further, the [PM10] and [PM2.5] were highly correlated (r ≥ 0.90) in all cities, with slope > 0.70 representing the abundance of fine particles, except for NJ (