Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s importan...Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and Ångström Exponent Anomaly (ÅEA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and ÅEA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and ÅEA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.展开更多
Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), Ångström Exponent (ÅE)...Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), Ångström Exponent (ÅE) and Precipitation Rate (PR) over selected East African sites from 2000 to 2014. The selected sites of study are Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0° - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). GHSOM analysis reveals a marked spatial variability in AOD and ÅE that is associated to changing PR, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Furthermore, spatial variability in AOD, ÅE and PR is distinct since each variable corresponds to a unique level of classification. On the other hand, GHSOM algorithm efficiently discriminated by means of clustering between AOD, ÅE and PR during Long and Short rain spells and dry spell over each variable emphasizing their temporal evolution. The utilization of GHSOM therefore confirms the fact that regional aerosol characteristics are highly variable be it spatially or temporally and as well modulated by PR received over each variable.展开更多
Dust aerosols play a critical role in atmospheric processes,influencing air quality,climate,and weather patterns through their interactions with radiation and cloud formation.This study aimed at characterizing the spa...Dust aerosols play a critical role in atmospheric processes,influencing air quality,climate,and weather patterns through their interactions with radiation and cloud formation.This study aimed at characterizing the spatiotemporal distribution of dust and quantifying its radiative forcing over Kenya using a combination of satellite observations and model-based measurements.Multi-year datasets from MERRA-2 and MODIS were utilized to analyze dust loading and spatial variability.Additionally,radiative forcing(RF)derived from MERRA-2 and satellite observations was estimated to assess dust-induced changes in surface of-atmosphere(BOA),top-of-atmosphere(TOA)and within atmosphere(ATM).The findings on spatiotemporal variability of dust over Kenya,highlight high concentrations in northern regions during dry months and reductions during wet seasons(MAM and OND).While on particle size distribution,the analysis shows coarse-mode dominance in dry periods,depicting dominance of dust.On the other hand,dust mass concentrations peak in the northwest part of the study domain.Further,RF analysis indicates dust induces BOA and TOA cooling but atmospheric heating,with peak heating in June to July,local dry months.This study therefore recommends an enhanced integrated dust monitoring and modeling system,especially during dry seasons,to capture Dust AOD,size,and mass concentration.Further,targeted mitigation measures like afforestation,land-use planning and early warning systems should be prioritized to reduce dust emissions,improve climate model accuracy,and protect public health in vulnerable regions.展开更多
The deforestation has profound implications on aerosol properties and climaticvariables.Deforestation disrupts local climate by altering temperature,aerosol optical properties and impacting air quality and modifies pr...The deforestation has profound implications on aerosol properties and climaticvariables.Deforestation disrupts local climate by altering temperature,aerosol optical properties and impacting air quality and modifies precipitationpatterns;and degrades vegetation health.However,the long-term impacts ofdeforestation on aerosol optical properties and climate variables over Mau remainnot very well investigated,especially considering the context of alteredanthropogenic and natural emission sources.This study bridges this gapthrough a comprehensive assessment of deforestation impacts on aerosol opticalproperties and climate variables over Mau Forest complex bounded by(0.2S,35.2E)and(0.8S,35.8E)using multisensory data from 2001-2024.Thefindings by the present study reveal predominantly negative trends of NDVI,recorded by season JF,JJAS and OND of value-6.63032E-4±0.00137,-1.356E-4±0.00101 and-1.31586E-4±7.59717E-4,respectively,indicatinga decrease in vegetation health and density over the year often linked to rainfallpatterns.Decline in NDVI is influenced by deforestation,which furtherexacerbates the impacts of natural reduction in vegetation cover.Conversely,during the season of MAM,the trend of NDVI is generally weak positive trendof value 4.70595E-4±0.00193 year^(-1) indicating an increase in vegetationhealth and density.Furthermore,the spatial trends over domain region ischaracterized by Aerosol optical depth(<0.2)and high value of Angstrom exponent(>1)and moderate value>0.7,is attributed by 1)deforestation for exampleanthropogenic activities and human activities hence released significantamounts of aerosols particles into the atmosphere 2)climate change occasionedby meteorological parameters such as temperature inversions accompaniedby reduced precipitation which are favorable conditions for increasedaerosol emissions leading to the enhanced AOD.Correlation between NDVI and AOD is negative,attributed to increase in deforestation rate that resultsin reduced NDVI values.The statistically significant impacts of deforestationon aerosols optical properties and NDVI prove the modulating role of aerosoloptical properties in regional climate processes.Policymakers must prioritizeemission control actions targeted at biomass burning and scientists must keepinvestigating high-resolution aerosol optical properties,climate interactionsusing integrated ground and satellite observations to advance climate impactassessment over Mau Forest complex in Kenya.展开更多
Aerosols play a critical role in Earth’s climate system.They influence cloud formation,atmospheric dynamics and Earth’s energy balance.This study presents a comprehensive spatiotemporal analysis of aerosol optical d...Aerosols play a critical role in Earth’s climate system.They influence cloud formation,atmospheric dynamics and Earth’s energy balance.This study presents a comprehensive spatiotemporal analysis of aerosol optical depth(AOD),Angstrom Exponent(AE),Single scattering Albedo(SSA)and their associations with primary climate variables such as Surface Air Temperature(SAT)and Rainfall Rates(RR).The present study derived its data from both satellites based remote sensing data and ground based observation,i.e.,Moderate Resolution Imaging Spectrometer(MODIS),Modern Era Retrospective Analysis for Research and Application 2(MERRA-2)and Tropical Rainfall Mission(TRMM)between the years 2000 to 2022.These data platforms are run and maintained by National Aeronautics and Space Administration(NASA).The researcher examined monthly and annual trends.Hidden Markov models were employed to determine the patterns and potential cause of variabilities and the link between aerosol optical properties and climate variables.The researcher determined trends in AOP and evaluated the trends in climate variables using HMM.Satellite-based dataset provided enhanced spatial resolution,accurate and observation.The findings gave more insight into aerosol dynamics and accurate climate modelling;the researcher addressed critical gaps in understanding the interactions between aerosols and climate variables in Kenya,a region highly vulnerable to the impacts of climate change and air quality degradation,hence better environment planning policy.Identified hidden patterns and transitions that were often overlooked by traditional methods.The methodological innovation is not only relevant for Kenya but also adaptable to other regions facing similar environmental challenges,thereby contributing to the broader field of atmospheric sciences.展开更多
Black carbon(BC),which is one of the short-lived climate forcers,largely influencesthe local modulation of the climate,particularly in regions that aresensitive such as East Africa.However,the long-term trends and met...Black carbon(BC),which is one of the short-lived climate forcers,largely influencesthe local modulation of the climate,particularly in regions that aresensitive such as East Africa.However,the long-term trends and meteorologicalimpacts of BC in this region remain not very well investigated,especiallyconsidering the context of altered anthropogenic and natural emissionsources.This study bridges this gap through a comprehensive spatio-temporalexamination of BC surface mass concentration for East Africa from 1980 to2023 using data from the Modern-Era Retrospective Analysis for Research andApplications,Version 2(MERRA-2).It has also established statistical correlationbetween BC concentrations and the selected meteorological parameters,i.e.,surface air temperature,specific humidity,surface wind speed,and totalsurface precipitation.Time-series analysis,spatial visualization,and Pearsoncorrelation were applied to analyze the MERRA-2 datasets.Results showedpronounced intra-and inter-annual variability in BC distribution with highconcentrations(>8×10^(-12)kg/m^(3))mostly over western Uganda and northwesternKenya and Tanzania during boreal winter.Such space hotspots werelinked to both local sources(biomass burning,automobile pollution)andlong-range atmospheric transport from Asian and Middle Eastern industrialregions.The effect of natural sources such as West African bushfires and Saharandust storms,was also reflected by transboundary dispersion patternsdue to wind systems in operation.Correlation analysis found that surface windspeed showed a statistically significant negative correlation with BC concentrationsduring all seasons,particularly March-May(r=-0.57,R^(2)=0.31)andJune-August(r=-0.51,R^(2)=0.24),indicating high winds favour BC dispersion.Specific humidity in addition to precipitation was moderately positivelycorrelated with BC,particularly during the September-November season(r=0.47,R^(2)=0.20),showing complex interactions between atmospheric moistureand aerosol lifecycles.Surface air temperature was most strongly seasonallycorrelated with BC during the short rains(r=0.55,R^(2)=0.29),showing thetwo-way effect of BC on atmospheric warming and radiative forcing.In short,the investigation indicates that BC concentrations over East Africa exhibit distinctspatial and temporal patterns driven by both human and natural processes.The statistically significant correlations with meteorological parametersprove the modulating role of BC in regional climate processes.Policymakersmust prioritize emission control actions targeted at biomass burning andurban pollution,and scientists must keep investigating high-resolution BCclimateinteractions using integrated ground and satellite observations to advanceclimate impact assessment in East Africa.展开更多
Atmospheric aerosols have contributed to radiative forcing through direct and indirect mechanisms. Aerosol effects are important in computing radiative forcing estimates for the past, current and future climate. In th...Atmospheric aerosols have contributed to radiative forcing through direct and indirect mechanisms. Aerosol effects are important in computing radiative forcing estimates for the past, current and future climate. In this study, a comprehensive assessment of regional aerosol radiative forcing, Optical Properties of Aerosol and Clouds (OPAC) model (wavelength range of 0.25 - 4.0 μm) over selected sites in East Africa was done. Aerosol optical properties constituted the inputs of a Radiative Transfer Model (RTM). Op-tical properties investigated included Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Asymmetry Parameter (AP). Aerosol Radiative Forcing (ARF) during the study period at the surface (SFC), top of the atmosphere (TOA) and the atmosphere (ATM) was estimated to be -18.4 ± 1.4 W·m-2, +1.1 ± 0.3 W·m-2 and +19.5 ± 2.5 W·m-2, respectively. This corresponds to an increment in net atmospheric forcing at a heating rate of about 0.55 ± 0.05 K/day (0.41 ± 0.03 to 0.78 ± 0.03 K/day) in the lower troposphere. The study points out the significant role played by atmospheric aerosols in climate modification over the area of study. It is recommended that a further assessment be done in view of uncertainties that may impact on the findings and which were not within the scope of this research.展开更多
文摘Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and Ångström Exponent Anomaly (ÅEA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and ÅEA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and ÅEA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.
基金This work was supported by the National Council for Science and Technology Grant funded by the Government of Kenya(NCST/ST&I/RCD/4TH call PhD/201).
文摘Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), Ångström Exponent (ÅE) and Precipitation Rate (PR) over selected East African sites from 2000 to 2014. The selected sites of study are Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0° - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). GHSOM analysis reveals a marked spatial variability in AOD and ÅE that is associated to changing PR, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Furthermore, spatial variability in AOD, ÅE and PR is distinct since each variable corresponds to a unique level of classification. On the other hand, GHSOM algorithm efficiently discriminated by means of clustering between AOD, ÅE and PR during Long and Short rain spells and dry spell over each variable emphasizing their temporal evolution. The utilization of GHSOM therefore confirms the fact that regional aerosol characteristics are highly variable be it spatially or temporally and as well modulated by PR received over each variable.
文摘Dust aerosols play a critical role in atmospheric processes,influencing air quality,climate,and weather patterns through their interactions with radiation and cloud formation.This study aimed at characterizing the spatiotemporal distribution of dust and quantifying its radiative forcing over Kenya using a combination of satellite observations and model-based measurements.Multi-year datasets from MERRA-2 and MODIS were utilized to analyze dust loading and spatial variability.Additionally,radiative forcing(RF)derived from MERRA-2 and satellite observations was estimated to assess dust-induced changes in surface of-atmosphere(BOA),top-of-atmosphere(TOA)and within atmosphere(ATM).The findings on spatiotemporal variability of dust over Kenya,highlight high concentrations in northern regions during dry months and reductions during wet seasons(MAM and OND).While on particle size distribution,the analysis shows coarse-mode dominance in dry periods,depicting dominance of dust.On the other hand,dust mass concentrations peak in the northwest part of the study domain.Further,RF analysis indicates dust induces BOA and TOA cooling but atmospheric heating,with peak heating in June to July,local dry months.This study therefore recommends an enhanced integrated dust monitoring and modeling system,especially during dry seasons,to capture Dust AOD,size,and mass concentration.Further,targeted mitigation measures like afforestation,land-use planning and early warning systems should be prioritized to reduce dust emissions,improve climate model accuracy,and protect public health in vulnerable regions.
文摘The deforestation has profound implications on aerosol properties and climaticvariables.Deforestation disrupts local climate by altering temperature,aerosol optical properties and impacting air quality and modifies precipitationpatterns;and degrades vegetation health.However,the long-term impacts ofdeforestation on aerosol optical properties and climate variables over Mau remainnot very well investigated,especially considering the context of alteredanthropogenic and natural emission sources.This study bridges this gapthrough a comprehensive assessment of deforestation impacts on aerosol opticalproperties and climate variables over Mau Forest complex bounded by(0.2S,35.2E)and(0.8S,35.8E)using multisensory data from 2001-2024.Thefindings by the present study reveal predominantly negative trends of NDVI,recorded by season JF,JJAS and OND of value-6.63032E-4±0.00137,-1.356E-4±0.00101 and-1.31586E-4±7.59717E-4,respectively,indicatinga decrease in vegetation health and density over the year often linked to rainfallpatterns.Decline in NDVI is influenced by deforestation,which furtherexacerbates the impacts of natural reduction in vegetation cover.Conversely,during the season of MAM,the trend of NDVI is generally weak positive trendof value 4.70595E-4±0.00193 year^(-1) indicating an increase in vegetationhealth and density.Furthermore,the spatial trends over domain region ischaracterized by Aerosol optical depth(<0.2)and high value of Angstrom exponent(>1)and moderate value>0.7,is attributed by 1)deforestation for exampleanthropogenic activities and human activities hence released significantamounts of aerosols particles into the atmosphere 2)climate change occasionedby meteorological parameters such as temperature inversions accompaniedby reduced precipitation which are favorable conditions for increasedaerosol emissions leading to the enhanced AOD.Correlation between NDVI and AOD is negative,attributed to increase in deforestation rate that resultsin reduced NDVI values.The statistically significant impacts of deforestationon aerosols optical properties and NDVI prove the modulating role of aerosoloptical properties in regional climate processes.Policymakers must prioritizeemission control actions targeted at biomass burning and scientists must keepinvestigating high-resolution aerosol optical properties,climate interactionsusing integrated ground and satellite observations to advance climate impactassessment over Mau Forest complex in Kenya.
文摘Aerosols play a critical role in Earth’s climate system.They influence cloud formation,atmospheric dynamics and Earth’s energy balance.This study presents a comprehensive spatiotemporal analysis of aerosol optical depth(AOD),Angstrom Exponent(AE),Single scattering Albedo(SSA)and their associations with primary climate variables such as Surface Air Temperature(SAT)and Rainfall Rates(RR).The present study derived its data from both satellites based remote sensing data and ground based observation,i.e.,Moderate Resolution Imaging Spectrometer(MODIS),Modern Era Retrospective Analysis for Research and Application 2(MERRA-2)and Tropical Rainfall Mission(TRMM)between the years 2000 to 2022.These data platforms are run and maintained by National Aeronautics and Space Administration(NASA).The researcher examined monthly and annual trends.Hidden Markov models were employed to determine the patterns and potential cause of variabilities and the link between aerosol optical properties and climate variables.The researcher determined trends in AOP and evaluated the trends in climate variables using HMM.Satellite-based dataset provided enhanced spatial resolution,accurate and observation.The findings gave more insight into aerosol dynamics and accurate climate modelling;the researcher addressed critical gaps in understanding the interactions between aerosols and climate variables in Kenya,a region highly vulnerable to the impacts of climate change and air quality degradation,hence better environment planning policy.Identified hidden patterns and transitions that were often overlooked by traditional methods.The methodological innovation is not only relevant for Kenya but also adaptable to other regions facing similar environmental challenges,thereby contributing to the broader field of atmospheric sciences.
文摘Black carbon(BC),which is one of the short-lived climate forcers,largely influencesthe local modulation of the climate,particularly in regions that aresensitive such as East Africa.However,the long-term trends and meteorologicalimpacts of BC in this region remain not very well investigated,especiallyconsidering the context of altered anthropogenic and natural emissionsources.This study bridges this gap through a comprehensive spatio-temporalexamination of BC surface mass concentration for East Africa from 1980 to2023 using data from the Modern-Era Retrospective Analysis for Research andApplications,Version 2(MERRA-2).It has also established statistical correlationbetween BC concentrations and the selected meteorological parameters,i.e.,surface air temperature,specific humidity,surface wind speed,and totalsurface precipitation.Time-series analysis,spatial visualization,and Pearsoncorrelation were applied to analyze the MERRA-2 datasets.Results showedpronounced intra-and inter-annual variability in BC distribution with highconcentrations(>8×10^(-12)kg/m^(3))mostly over western Uganda and northwesternKenya and Tanzania during boreal winter.Such space hotspots werelinked to both local sources(biomass burning,automobile pollution)andlong-range atmospheric transport from Asian and Middle Eastern industrialregions.The effect of natural sources such as West African bushfires and Saharandust storms,was also reflected by transboundary dispersion patternsdue to wind systems in operation.Correlation analysis found that surface windspeed showed a statistically significant negative correlation with BC concentrationsduring all seasons,particularly March-May(r=-0.57,R^(2)=0.31)andJune-August(r=-0.51,R^(2)=0.24),indicating high winds favour BC dispersion.Specific humidity in addition to precipitation was moderately positivelycorrelated with BC,particularly during the September-November season(r=0.47,R^(2)=0.20),showing complex interactions between atmospheric moistureand aerosol lifecycles.Surface air temperature was most strongly seasonallycorrelated with BC during the short rains(r=0.55,R^(2)=0.29),showing thetwo-way effect of BC on atmospheric warming and radiative forcing.In short,the investigation indicates that BC concentrations over East Africa exhibit distinctspatial and temporal patterns driven by both human and natural processes.The statistically significant correlations with meteorological parametersprove the modulating role of BC in regional climate processes.Policymakersmust prioritize emission control actions targeted at biomass burning andurban pollution,and scientists must keep investigating high-resolution BCclimateinteractions using integrated ground and satellite observations to advanceclimate impact assessment in East Africa.
文摘Atmospheric aerosols have contributed to radiative forcing through direct and indirect mechanisms. Aerosol effects are important in computing radiative forcing estimates for the past, current and future climate. In this study, a comprehensive assessment of regional aerosol radiative forcing, Optical Properties of Aerosol and Clouds (OPAC) model (wavelength range of 0.25 - 4.0 μm) over selected sites in East Africa was done. Aerosol optical properties constituted the inputs of a Radiative Transfer Model (RTM). Op-tical properties investigated included Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Asymmetry Parameter (AP). Aerosol Radiative Forcing (ARF) during the study period at the surface (SFC), top of the atmosphere (TOA) and the atmosphere (ATM) was estimated to be -18.4 ± 1.4 W·m-2, +1.1 ± 0.3 W·m-2 and +19.5 ± 2.5 W·m-2, respectively. This corresponds to an increment in net atmospheric forcing at a heating rate of about 0.55 ± 0.05 K/day (0.41 ± 0.03 to 0.78 ± 0.03 K/day) in the lower troposphere. The study points out the significant role played by atmospheric aerosols in climate modification over the area of study. It is recommended that a further assessment be done in view of uncertainties that may impact on the findings and which were not within the scope of this research.
