Ozone Monitoring Instrument aerosol products: a comparison study with ground-based airborne sun photometer measurements over Europe

Airborne sun photometer measurements are used to evaluate retrievals of extinction aerosol optical depth (AOD). These data are extracted from spatially coincident and temporally near-coincident measurements by the Ozone Monitoring Instrument (OMI) aboard the Aura satellite taken during 2005. OMI-measured top of atmosphere (TOA) reflectances are routinely inverted to yield aerosol products such as AOD using two different retrieval techniques: the Aura OMI Near-Ultraviolet Aerosol Data Product, OMAERUV, and the multi-wavelength Aura OMI Aerosol Data Product, OMAERO. In this work, we propose a study that specifically compares the instantaneous aerosol optical thicknesses retrieved from OMI at several locations containing sites and those of the Aerosol Robotic Network (AERONET). The result of the comparison shows that, just over Europe, OMI aerosol optical thicknesses are better retrieved in the multi-wavelength retrieval than in the near-ultraviolet. Correlations have been improved by applying a simple criterion to avoid scenes probably contaminated by thin clouds, and surface scattering. The ultraviolet irradiance positive bias in the OMI data is corrected using a procedure based on global climatological fields of aerosol absorption optical depth. The results generally show a bias significantly reduced by 5–20%, a lower variability and an unchanged, high correlation coefficient.     

Retrieval of aerosol optical thickness from HJ-1 CCD data based on MODIS-derived surface reflectance

The successfully launched Huanjing-1 (HJ-1) satellite by China in 2008 provides a new source of data for monitoring the environment. In this article, we develop a new algorithm for retrieving the aerosol optical thickness (AOT) using HJ-1 charge-coupled device (CCD) data with the assistance of the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and the bidirectional reflectance distribution function (BRDF) data products. This algorithm is then used to retrieve AOT in a delta region of the Yangtze River. The retrieved results are assessed for their accuracy by comparison with ground-measured data using sun photometers. Comparison of such derived AOT with in situ AOT measured using sun photometers indicates a root mean squared error (RMSE) of 0.123, and their regression relation has a correlation coefficient of 0.896 that is statistically significant at the 0.01 level. Such a relatively high level of retrieval accuracy suggests that HJ-1 CCD data can be used competently and effectively to retrieve AOT with the assistance of MODIS products that are used to construct the surface reflectance model. This study successfully demonstrates the feasibility of synergistically retrieving AOT from data acquired by different sensors. The lower dependence on data from a sole source means that the retrieval is less restrictive by data availability.     

Intercomparison of CALIOP,MODIS, and AERONET aerosol optical depth over China during the past decade

ABSTRACT

Aerosol optical depth (AOD) data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were intercompared and validated against ground-based measurements from Aerosol Robotic Network (AERONET) as well as space-based Moderate Resolution Imaging Spectroradiometer (MODIS) over China during June 2006 to December 2015. This article aims to evaluate CALIOP daytime AOD using MODIS and AERONET AODs. Comparing the AOD between CALIOP and AERONET in different regions over China using quality control flags to screen the AOD data, we find that CALIOP AOD is generally lower than AERONET AOD especially at optical depths over 0.4 likely due to differences in the cloud screening algorithms and general retrieval uncertainty. Comparison between CALIOP AOD and MODIS AOD results show that the overall spatio-temporal distribution of CALIOP AOD and MODIS AOD is basically consistent. As for the spatial distribution, both data sets show several high-value regions and low-value regions in China. CALIOP is systematically lower than MODIS over China, especially over high AOD value regions for all seasons. As for the temporal variation, both data sets show a significant seasonal variation: AOD is largest in spring, then less in summer, and smallest in winter and autumn. A long-term linear trend analysis based on the domain averaged monthly mean CALIOP and MODIS AOD shows agreement among CALIOP and MODIS for the trends over the 10-year period in four regions examined. The trends in AOD derived from CALIOP and MODIS indicate a decline in aerosol loading in China since 2006. It is found from frequency comparison that CALIOP and MODIS AOD generally exhibit a degree of correlation over China. Statistical frequency analysis shows that CALIOP AOD frequency distribution shows a higher peak than MODIS AOD when AOD < 0.4. For the most part, mean MODIS AOD is higher than mean CALIOP AOD. Evaluation of CALIOP AOD retrievals provides the prospect for application of CALIOP data. The intercomparison suggests that CALIOP has systematically underestimated daytime AOD retrievals, especially deteriorating with increasing AOD, and therefore, CALIOP daytime AOD retrievals should be treated with some degree of caution when the AOD is over 0.4.     

Study on spatial-temporal variation of aerosol optical depth over the Yangtze Delta and the impact of land-use/cover

Aerosol optical depth (AOD) is a principal indicator used to describe the atmospheric condition and effect of aerosols on radiative transfer in the Earth’s atmosphere. In this study, the spatial-temporal variation of AOD of the Yangtze Delta during 2000–2011 and the impact of land cover were studied. The results show that Moderate Resolution Imaging Spectroradiometer (MODIS) AOD was in good agreement with data obtained from six ground-based Aerosol Robotic Network (AERONET) sun photometers (R > 0.75). The AOD over the Yangtze Delta presented an obvious one year cycle variation from 2000 to 2011. The largest value often appeared in May or June, and the smallest often appeared in December or January. The AOD over main cities has increased gradually over the years. The AOD over urban areas increased faster than that in rural areas. A change of land-use/cover leads to a change of AOD. Areas of land-use/cover with increased intense human activity leads to changes in higher AOD whereas an increase in forested areas leads to an AOD change to a lower value. Forest land has a purification effect against atmospheric aerosols.     

Spatial and temporal variations of aerosol optical depth in China during the period from 2003 to 2006

Spatial and temporal variations of aerosol optical depth (AOD, or τ) in China were investigated using MODIS-derived aerosol data for a period of 2003–2006. The geographical distribution patterns of 4-year mean AOD for total, τ_0.55 (AOD at 0.55 μm), fine, τ_0.55-fine, and coarse, τ_0.55-coarse, aerosols over China were addressed. These results indicate that the distribution of aerosol was largely affected by population, urban/industrial activity, agricultural biomass burning, spring dust, topography and humidity. τ_0.55-fine in eastern China is significantly higher than in western China. Distribution of τ_0.55-coarse reflected the influence of spring dust and urban/industrial pollution. The overall AOD in summer was higher than that in winter due to strong photochemical reactions producing secondary aerosols. In northern China, dust contributed to the mean τ_0.55 in spring months. In some places, aggregated precipitation in the summer months caused a pronounced drop in the temporal profile of AOD. Coal combustion, industrial emission and vehicle exhaust produced coarse aerosols, while fine aerosols are mainly dominated by secondary particles. Smoke from open-fire straw burning produced fine aerosols in the harvest season.     

Development and validation of a technique for merging satellite derived aerosol optical depth from SeaWiFS and MODIS

Merging time series of satellite derived aerosol products from independent missions can support aerosol science by combining in a consistent way temporally overlapping data sets and by increasing data coverage. A merging technique applied to satellite aerosol optical depth τ_a is presented and tested with SeaWiFS and MODIS-Aqua data. The technique relies on least squares fitting of the available τ_a spectra onto a linear or second-order polynomial relation between log-transformed τ_a and wavelengths. First, the sensor specific products are compared with field observations collected by a sun-photometer installed on the Acqua Alta Oceanographic Tower in the northern Adriatic Sea. Mean absolute percentage differences are approximately 21% at 412 and 443 nm, and increase with wavelength, with large overestimates in the red and near-infrared bands. The mean absolute differences are typically 0.04. When inter-compared, the 2 satellite products agree well, with mean absolute percentage differences lower than 20% at all wavelengths and little bias. The results of the comparison of the merger outputs with the field data are well in line with the validation results of the sensor specific products, and are comparable for the various merging procedures. The benefits of merging in terms of data coverage are briefly illustrated for the Mediterranean basin.     

Observation of an agricultural biomass burning in central and east China using merged aerosol optical depth data from multiple satellite missions

Agricultural biomass burning (ABB) in central and east China occurs every year from May to October and peaks in June. During the period from 26 May to 16 June 2007, one strong ABB procedure happened mainly in Anhui, Henan, Jiangsu and Shandong provinces. This article focuses on analysis of this ABB procedure using a comprehensive set of aerosol optical depth (AOD) data merged by using the optimal interpolation method from the Moderate Resolution Imaging Spectroradiometer, the Multi-angle Imaging Spectroradiometer (MIRS) as well as Sea-viewing Wide Field-of-view Sensor (SeaWiFS)-derived AOD products. In addition, the following additional data are used: fire data from the National Satellite Meteorological Centre of China Meteorological Administration, the mass trajectory analyses from hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model and ground-based AOD and Ångström data derived from the Aerosol Robotic Network and China Aerosol Remote Sensing Network. The results show that merged satellite AOD values can expand the spatial coverage of agricultural biomass aerosol distributions with good accuracy (R = 0.93, root mean square error = 0.37). Based on the merged AOD images, the highest AOD values were found concentrated in central China as well as in eastern China before 6 June and further extended to northeast China after 12 June. AODs from ground measurement show that eastern China always keeps high AOD values (>1.0), with a maximum exceeding 3.0 and extending as high as nearly 5.0 during this ABB event. With the help of the HYSPLIT model, we analysed the ABB sources and examined how transport paths affect the concentrations of air pollutants in some sites. The results show that Henan, Jiangsu and Anhui provinces are the three main sources in this ABB.     

Validation of satellite and model aerosol optical depth and precipitable water vapour observations with AERONET data over Pune,India

ABSTRACT

The present work concerns with a detailed study of the validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) and model products, and investigates the spatial and temporal variations in the correlation coefficient of the validation results obtained from the analysis of Aerosol Robotic Network (AERONET) sun–sky radiometer data archived at Pune during 2005–2015. Combining the confidence intervals and prediction levels, the ground-based AERONET aerosol optical depth (AOD) at 550 nm and precipitable water vapour (PWV) have been used to validate the MODIS, model AOD (550 nm), and PWV (cm) observations. The correlation coefficients (r) of AOD for the linear regression fits are 0.73, 0.75, and 0.79, and of PWV are 0.88, 0.89, and 0.97 for Terra, Aqua, and model simulations, respectively. Month-to-month/seasonal variation of AOD (550 nm) and PWV observations of satellite and model observations are also compared with AERONET observations. Additionally, various statistical metrics, including the root mean square error, mean absolute error, and root mean bias values were calculated using AERONET, satellite, and model simulations data. Furthermore, a frequency distribution of AOD (550 nm) and PWV observations are studied from AERONET, satellite, and model data. The study emphasizes that the globally distributed AERONET observations help to improve the satellite retrievals and model predictions to enrich our knowledge of aerosols and their impact on climate, the hydrological cycle, and air quality.     

Characterisation of aerosol constituents from wildfires using satellites and model data: a case study in Knysna,South Africa

Strong winds and dry conditions make it difficult to contain wild fires worldwide. Such fires could cause devastating effects on landscape structures around many urban/peri-urban areas. The greater impact of such fires is commonly felt when landscape elements such as forest vegetation biomass fuel increase the wild fire risk to people and their properties. In order to mitigate the impact of a wild fire at local level, it is imperative to understand its spatial distribution and fuel load dynamics surrounding it. This study aimed at exploring the possibility of integrating various satellites and model data to characterise the aerosols emissions from wild fires which occurred at Knysna (South Africa). The Moderate Resolution Imaging Spectroradiometer (MODIS), the Sentinel-2 normalized difference vegetation index (NDVI), the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the Hybrid Single-Particle Lagrangian Intergrated trajectory (HYSPLIT) model and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) model were employed to characterise the Knysna fires, and the resultant atmospheric conditions that prevailed at altitudes lower than 10 km. Large flames and high amounts of smoke were observed at the Knysna forests by the Sentinel-2 optical data. Our findings showed that there was an apparent reduction in the green vegetation biomass coverage of up to 20.2% following the wildfires as observed by Sentinel-2 data analysis. Biomass burning (BB) aerosols and smoke were observed to reach high altitudes of 2–4 km by CALIPSO. Pyrocumulus clouds were also observed at altitudes of 7.2 km. These clouds were a result of the mixing of the smoke and clouds in the mid-troposphere. The HYSPLIT model and MERRA-2 model showed that the emitted BB aerosols and smoke did not travel inland but rather dispersed in an eastward and south-eastward direction into the Indian Ocean from the source. A multi-satellite data approach proved to be a valuable resource to study the extent of wild fires and to determine their atmospheric impact and thus contributing to climate change. The transport models data was resourceful in determining the destination of the wild fires emissions.     

Study of aerosol optical depth,ozone, and precipitable water vapour content over Sinhagad,a high-altitude station in the Western Ghats

This article reports the results of a study related to variations in columnar aerosol optical depth (AOD), total column ozone (TCO), and precipitable water content (PWC) over a high-altitude station, Sinhagad (18° 21′ N, 73° 45′ E, 1450 m above mean sea level (AMSL)), employing a microprocessor-based total ozone portable spectrometer, MICROTOPS-II, comprising both a sun photometer and ozonometer, during November 2009–April 2010. The aerosol optical depth at 500 nm (AOD_{500 nm}) portrayed seasonal variation with higher values (0.39) in summer and lower values (0.15) in winter. The TCO and PWC also exhibited lower values in winter and started increasing by the pre-monsoon season. The Ångström wavelength exponent, α, was found to be high (1.79) during February, indicating the relative dominance of accumulation-mode particles. During the summer season, the lower value (0.94) of the Ångström wavelength exponent indicates the relative dominance of coarse-mode particles. The ground-based observations from MICROTOPS-II revealed good correlation with satellite observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI). The observed short-wave solar flux at the bottom of the atmosphere decreased due to aerosol extinction and was found to be 19 and 78 W m^–2 for the winter and pre-monsoon seasons, respectively. This implies that greater concentrations of accumulation-mode particles – which are due to local anthropogenic sources – affected the down-welling radiation than those from natural sources – which are due to long-range transport processes – over the experimental location.     

Retrieval and analysis of aerosol optical characteristics in Hubei Province,China, based on CALIPSO

The aerosol optical characteristics in Hubei Province, China, derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), are investigated. Through this spaceborne lidar, some limitations of airborne and ground-based systems can be overcome and a global survey of clouds and aerosol can be provided. First, a lidar ratio selection algorithm is introduced. Since the lidar ratio (the aerosol extinction-to-backscatter ratio, S _a) is an important parameter used in aerosol retrieval, it is required for a reliable aerosol model. After retrieving the original signal, aerosol optical parameters are obtained. Based on these steps, the impacts of atmospheric motion on aerosol diffusion in different layers, the distribution of these aerosols, as well as their time-changing characteristic in Hubei Province are discussed. The studies show that in areas of plains aerosols are easily influenced by wind; furthermore, aerosol distribution in the western Hubei Province is usually influenced by biomass burning and in eastern Hubei by industrial emission. Although errors still exist, the aerosol optical characteristics in different regions are strongly related to the ground surface, wind direction and visible distinctions exist in urban and country areas.     

A dryland cover state mapping using catastrophe model in a spectral endmember space of OLI: a case study in Minqin,China

Alternative state theory with catastrophe conceptual model is very attractive for dryland zero net land degradation (ZNLD) management, but practically challenging for mapping cover state and pathway with conventional approaches. This paper developed a methodological framework in the generic spectral endmember space (SVD, soils and substrates, vegetation, and dark surface endmembers ) of Landsat-8 OLI (operational land imager) imagery to concretize the catastrophe model of dryland cover state based on the co-development of plant and soil variables in a landscape. A cover function index (LCI) was proposed together with cover type growth form as cover variables in multi-seasonal SVD space. Furthermore, ecological site (ES) and topographic wetness index (TWI) were used as the landscape variables. The four variables as the explanatory variates, soil organic matter (SOM) as a slow response variable of dryland cover state, were explored by classification and regression trees (CART) for the state space. Using the Minqin dryland system in China as a case study, CART explored 65.9% amounts of SOM variance of 85 training samples with the four explanatory variables, and the measured SOM had liner relationship with CART predicted SOM at 0.05 significant level with the explained 39% SOM variance for 10 test samples. In the learned transparent tree, the two alternative stable states were identified correctly and validated by another soil intrinsic clay content variable independently, one was the current highest average SOM (26.757 g kg^?1) of perennial forest/shrub covers, the other was the bared or sparse vegetation cover with low average SOM (≤8.518 g kg^?1) as a critical SOM limit in a given ecological site type. The mean clay content of the undesirable alternative states was all below 60 g kg^?1 with severe soil physical degradation, and had a clear breaking gap with other states. Moreover, the SOM-LCI plane projected the unstable states being folded in the basins of the attraction of two alternative stable states (i.e. 0.39–0.76 LCI) with relative resilience analysis of pathways. In the 10 test sites, only 1 site of the state was not predicted correctly. The results suggest the model has a level of predictability for dryland cover state and its pathway. According to the estimated states, there has 12.74% study area improved and continued to recovering the desirable states, and the study area has already net improvement at the landscape level.

Therefore, without the comparable series of historical data for adaptive management, the developed framework in SVD of Landsat imagery is a cost-effective and time-saving tool, which helps managers to assess and develop appropriate management with a more spatially diversified strategy for zero net land degradation using a space-for-time substitution in an era of unprecedented change.     

An application of MODIS data to snow cover monitoring in a pastoral area: A case study in Northern Xinjiang, China

Snow is an important land cover on the earth's surface. It is characterized by its changing nature. Monitoring snow cover extent plays a significant role in dynamic studies and prevention of snow-caused disasters in pastoral areas. Using NASA EOS Terra/MODIS snow cover products and in situ observation data during the four snow seasons from November 1 to March 31 of year 2001 to 2005 in northern Xinjiang area, the accuracy of MODIS snow cover mapping algorithm under varied snow depth and land cover types was analyzed. The overall accuracy of MODIS daily snow cover mapping algorithm in clear sky condition is high at 98.5%; snow agreement reaches 98.2%, and ranges from 77.8% to 100% over the 4-year period for individual sites. Snow depth (SD) is one of the major factors affecting the accuracy of MODIS snow cover maps. MODIS does not identify any snow for SD less than 0.5 cm. The overall accuracy increases with snow depth if SD is equal to or greater than 3 cm, and decreases for SD below 3 cm. Land cover has an important influence in the accuracy of MODIS snow cover maps. The use of MOD10A1 snow cover products is severely affected by cloud cover. The 8-day composite products of MOD10A2 can effectively minimize the effect of cloud cover in most cases. Cloud cover in excess of 10% occurs on 99% of the MOD10A1 products and 14.7% of the MOD10A2 products analyzed during the four snow seasons. User-defined multiple day composite images based on MOD10A1, with flexibilities of selecting composite period, starting and ending date and composite sequence of MOD10A1 products, have an advantage in effectively monitoring snow cover extent for regional snow-caused disasters in pastoral areas.     

Statistical problems in the discrimination of land cover from satellite images: a case study in lowland Britain

Abstract

This paper discusses underlying statistical problems in identifying land classes from satellite imagery. Problems in assessing accuracy of automatic classifiers are illustrated using results from analysis of two Landsat Thematic mapper (TM) subscenes collected for the same areas within Cambridgeshire in the summer and autumn of 1984. Problems arising from between-site variability of training sites are discussed. Use of rejection thresholds is also discussed. Recommendations are given for improving choice of training data to attempt lo overcome some of these problems.     

Impact of climate model uncertainties on socioeconomics: A case study with a medium mitigation scenario

Carbon dioxide (CO₂) emissions are strongly associated with economy. The amount of CO₂ that human society can emit in order to achieve a climate target depends on physical and biogeochemical properties in the climate system; these vary among climate models or earth system models (ESMs). Thus, uncertainties in such models, the spread remained when we both consider the range of existing models and observational data for key variables, can affect analysis of future global economy. In this study, using a computable general equilibrium model, we analyze the impacts on socioeconomics under a medium climate mitigation scenario by following three emission pathways considering uncertainties in existing ESMs (the lower and upper bounds as well as the mean). The results indicate that the impacts are larger in the lower bound case, despite the fact that economic and energy demands will increase continuously. In a comparison between the upper and lower bound cases, the carbon price of the latter case is approximately three times higher than that of the former case in 2100. Consequently, primary/final energy demand in the lower bound case becomes 1.0%/14% lower, and more renewables and carbon capture and storage are required to be used. Furthermore, the gross domestic product in the lower bound case is 4.1% smaller. Thus, within the scenario, the socioeconomic impacts caused by ESM uncertainties are not insignificant, but are smaller than the differences in annual and cumulative emissions.     

Giant landslide displacement analysis using a point cloud set conflict technique: a case in Xishancun landslide,Sichuan, China

Landslides, threatening millions of human lives, are geological phenomena on earth, occurred frequently. An increasing number of techniques are being used to monitor landslide deformation. Among these, Light Detection and Ranging (LiDAR) stands out for its high efficiency and accuracy in displacement detection, particularly for giant landslides. In this work, we collected two temporal datasets of terrain laser scanning and proposed a flowchart for giant landslide displacement analysis using the point cloud set conflict（PCSC） technique. First, the terrestrial points were obtained by performing registration and off-terrain point filtering. Second, the landslide displacement field was acquired using the proposed method based on its surface roughness. The displacement results from our established methodological system are comparable with the ones of Interferometric Synthetic Aperture Radar (InSAR)-derived deformations. The differences estimated from two systems are at the centimetre level. Cross-analysis on the trigger factor with landslide occurred mechanism could be achieved based on the results as well. Therefore, this work provides a novel system to analyse the displacement of a giant landslide in the future study.     

Satellite observations of the aerosol direct radiative effect during a pollution episode in Nanjing,China, using high-resolution HJ-1 CCD imagery

The charge-coupled device imageries from the Chinese environmental satellites (HJ-1) with 30 m spatial resolution are used in this study to investigate the shortwave aerosol direct radiative effect (ADRE) during a pollution episode in March 2013 over Nanjing City. The Deep Blue algorithm is used to retrieve the aerosol optical depth (AOD) and the results are then validated using ground-based data. The mean values of the AOD in Nanjing at 550 nm are 0.41, 0.54, and 0.79 on 3, 4, and 7 March 2013, respectively, with fitting degree 0.796. The spatial aerosol distribution indicates that the pollution is induced by local emission, accumulated as a result of suitable weather conditions, and then spread by the wind. The ADRE results at the surface and at the top of the atmosphere (TOA) are then calculated using radiative transfer model. The mean values and standard deviations of the ADRE on 3, 4, and 7 March are ?75.6 ± 21.3, ?98.8 ± 16.6, and ?138.1 ± 26.0 W m^?2 at the surface and ?3.7 ± 3.8, ?5.2 ± 4.6, and ?8.1 ± 5.9 W m^?2 at the TOA, respectively. The results show that although aerosols can cause warming at the TOA over a highly reflectivity surface, the total radiative effect corresponds to the cooling of both the Earth-atmosphere system and the surface at the expense of heating the atmosphere.     

Spatiotemporal heterogeneity of Moso bamboo aboveground carbon storage with Landsat Thematic Mapper images: a case study from Anji County,China

Bamboo forest, especially Moso bamboo forest (Phyllostachys heterocycla var. pubescens), has a powerful carbon sequestration capability and plays an important role in the global carbon sink. This research examines the spatiotemporal heterogeneity of Moso bamboo aboveground carbon storage (AGC) in Anji County of Zhejiang Province, China. Five dates of Landsat Thematic Mapper images and field measurements were used to estimate Moso bamboo AGC between 1986 and 2008. Geostatistics were used to analyse AGC spatiotemporal heterogeneity. The results indicate that Moso bamboo AGC increases gradually and its spatial heterogeneity over five dates has moderate autocorrelation. Spatial heterogeneity increased dramatically after 1986, implying the influence of random factors such as management on the spatiotemporal heterogeneity of AGC. This research provides an alternative insight into the carbon cycling process of a bamboo forest ecosystem, and has implications for ongoing efforts in regard to carbon sequestration management.     

Relationships between aerosol index,ozone, solar zenith angle and surface reflectivity: a case study of satellite observations over Lagos

Surface reflectivity (RFL), solar zenith angle (SZA), ozone and aerosol index (AI) daily data over Lagos (6.60° N, 3.33° E) measured by the Total Ozone Mapping Spectrometer (TOMS) were examined to determine the relationship between the parameters. We found that aerosol distribution can fully account for changes in RFL in the presence of ozone when other factors are held constant. We also showed that dust distribution over Lagos varies seasonally, reaching a maximum during the local dry season and a minimum during the local wet season whereas ozone peaks during the wet season and decreases to a minimum during the dry season. Aerosol variation was further linked to the seasonal transport of sahelian dust by the northeasterly wind that arrives at the location during the dry season and the eventual cloud washout during the wet season while the ozone distribution was attributed to the near balance between production and loss of the pollutant as a consequent of local wind transport.