Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean Basin and Middle East from direct-sun AERONET observations

Basart, Sara; García‐Pando, Carlos Pérez; Cuevas, E.; Baldasano, J. M.; Gobbi, Gian Paolo

doi:10.5194/acp-9-8265-2009

Cited by 229 publications

(237 citation statements)

References 72 publications

Supporting

Mentioning

216

Contrasting

Unclassified

Order By: Relevance

“…Backward-trajectories analysis and images of MODIS sensor on board of TERRA and AQUA satellites (http://modis.gsfc.nasa.gov) (graphs not shown) revealed that these data are mainly associated with Saharan dust intrusions. The work of Basart et al (2009) showed that for sunphotometry measurements at the Sahara-Sahel deserts, mineral dust particles presented δα approximately between −0.5 and 0.1, α < 0.3, η < 40 % and r f ∼ 0.3. The differences between these values and those obtained in this study can be explained by the mixture of dust with local anthropogenic particles, and by the deposition of the larger particles during their transport to the study area.…”

Section: Seasonal Evolution Of Aerosol Optical Propertiesmentioning

confidence: 99%

Columnar aerosol properties from sun-and-star photometry: statistical comparisons and day-to-night dynamic

et al. 2012

View full text Add to dashboard Cite

Abstract. This work presents the first analysis of longterm correlative day-to-night columnar aerosol optical properties. The aim is to better understand columnar aerosol dynamic from ground-based observations, which are poorly studied until now. To this end we have used a combination of sun-and-star photometry measurements acquired in the city of Granada (37.16 • N, 3.60 • W, 680 m a.s.l.; South-East of Spain) from 2007 to 2010. For the whole study period, mean aerosol optical depth (AOD) around 440 nm (±standard deviation) is 0.18 ± 0.10 and 0.19 ± 0.11 for daytime and nighttime, respectively, while the mean Angström exponent (α) is 1.0 ± 0.4 and 0.9 ± 0.4 for daytime and nighttime. The ANOVA statistical tests reveal that there are no significant differences between AOD and α obtained at daytime and those at nighttime. Additionally, the mean daytime values of AOD and α obtained during this study period are coherent with the values obtained in the surrounding AERONET stations. On the other hand, AOD around 440 nm present evident seasonal patterns characterised by large values in summer (mean value of 0.20 ± 0.10 both at daytime and nighttime) and low values in winter (mean value of 0.15 ± 0.09 at daytime and 0.17 ± 0.10 at nighttime). The Angström exponents also present seasonal patterns, but with low values in summer (mean values of 0.8 ± 0.4 and 0.9 ± 0.4 at dayand night-time) and relatively large values in winter (mean values of 1.2 ± 0.4 and 1.0 ± 0.3 at daytime and nighttime). These seasonal patterns are explained by the differences in the meteorological conditions and by the differences in the strength of the aerosol sources. To take more insight about the changes in aerosol particles between day and night, the spectral differences of the Angström exponent as function of the Angström exponent are also studied. These analyses reveal increases of the fine mode radius and of the fine mode contribution to AOD during nighttime, being more remarkable in the summer seasons. These variations are explained by the changes of the local aerosol sources and by the meteorological conditions between daytime and nighttime, as well as aerosol aging processes. Case studies during summer and winter for different aerosol loads and types are also presented to clearly illustrate these findings.

show abstract

Section: Seasonal Evolution Of Aerosol Optical Propertiesmentioning

confidence: 99%

Columnar aerosol properties from sun-and-star photometry: statistical comparisons and day-to-night dynamic

et al. 2012

View full text Add to dashboard Cite

show abstract

“…The increase in AOD with R f and η infer the hydration of aerosol particles, while increase in AOD with increasing R f and decreasing α suggests aging and/or coagulation and, the reverse, i.e. increase in AOD with decreasing R f and increasing α, corresponds to freshly emitted fine aerosols (Gobbi et al, 2007;Basart et al, 2009;Kaskaoutis et al, 2011). Based on the aforementioned criteria the aerosol optical properties and the modification (Fig.…”

Section: Classification Of Aerosolsmentioning

confidence: 99%

“…The scheme applied to eight different AERONET stations in three continents revealed different aerosol modification processes depending on the aerosol types and compositions. This technique was further applied for aerosol characterization of different AERONET data sets obtained from Northern Africa, Northeastern Atlantic, Mediterranean Basin and the Middle East (Basart et al, 2009) in Arabian Sea and Bay of Bengal during ICARB and W-ICARB cruise campaigns, (Kaskaoutis et al, , 2011.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of aerosols over Hyderabad in southern Peninsular India: synergy in the classification techniques

et al. 2012

View full text Add to dashboard Cite

Abstract. The present study focuses on analyzing the seasonal changes in aerosol characteristics using a classification scheme proposed by Gobbi et al. (2007). This scheme is based on the correlation between theÅngström exponent (α) in the 440-870 nm range and the difference in α values [dα = α (440-675 − α(675-870)] including the size of finemode particles (R f ) and the fine-mode fraction (η). The classification scheme can therefore provide information on the aerosol characteristics and their modification in transit. Spectral aerosol measurements using the Microtops-II sun photometer (MT-II) have systematically been conducted in Hyderabad, India during April 2009-March 2010 and analysed to study the seasonal effects. The results reveal a seasonal dependence, i.e. the presence of fine-mode aerosols under turbid atmospheres in winter and post-monsoon, a mixture of fine and coarse aerosol types in pre-monsoon and a significant influence of marine mixed with dust air masses during the monsoon season. The identification of the aerosol source type and the modification processes are discussed along with clustered air-mass trajectory analysis. Furthermore, we have also checked the consistency of this scheme with the findings arrived from the columnar size distributions (CSDs) computed by numerical inversion of spectral AOD using King's inversion algorithm and the scatter plot between AOD and spectral α. The comparison clearly demonstrates the usefulness of the classification scheme and highlights its advantages for the monitoring and study of seasonal variation of the aerosol types and the modification processes in the atmosphere.

show abstract

“…Taking into account previous studies in the literature Basart et al, 2009;Guirado et al, 2014;Cesnulyte et al, 2014;Cuevas et al, 2015) and AERONET climatology tables (https://aeronet.gsfc.nasa.gov/cgi-bin/climo_ menu_v2_new), AOD desert stations such as Tamanrasset (Algeria), Ouarzazate (Morocco), Dakar (Senegal) and Solar Village (Saudi Arabia) show monthly and seasonal values typically ranging between 0.04 (Ouarzazate in January) and 0.67 (Dakar in June), with sporadic AOD maxima > 1 associated with strong desert dust outbreaks or local dust resuspension. Therefore, we have focused our sensitivity study in AOD conditions varying between 0.5, which corresponds to hazy conditions by dust, and 1, indicating strong dust intrusions.…”

Section: Instrumental Error Sensitivitymentioning

confidence: 99%

“…However, the proximity to the Saharan desert introduces an important influence of mineral dust on its aerosol climatology. As Basart et al (2009) (Basart et al, 2009), increasing AOD and reducing α values. Following the work developed by Guirado et al (2014), those situations with AOD 500 nm > 0.15 and α < 0.5 can be considered prevalent dust conditions at this station.…”

Section: Test Sitesmentioning

confidence: 99%

A new zenith-looking narrow-band radiometer-based system (ZEN) for dust aerosol optical depth monitoring

et al. 2017

View full text Add to dashboard Cite

Abstract.A new zenith-looking narrow-band radiometer based system (ZEN), conceived for dust aerosol optical depth (AOD) monitoring, is presented in this paper. The ZEN system comprises a new radiometer (ZEN-R41) and a methodology for AOD retrieval (ZEN-LUT). ZEN-R41 has been designed to be stand alone and without moving parts, making it a low-cost and robust instrument with low maintenance, appropriate for deployment in remote and unpopulated desert areas. The ZEN-LUT method is based on the comparison of the measured zenith sky radiance (ZSR) with a look-up table (LUT) of computed ZSRs. The LUT is generated with the LibRadtran radiative transfer code. The sensitivity study proved that the ZEN-LUT method is appropriate for inferring AOD from ZSR measurements with an AOD standard uncertainty up to 0.06 for AOD 500 nm ∼ 0.5 and up to 0.15 for AOD 500 nm ∼ 1.0, considering instrumental errors of 5 %. The validation of the ZEN-LUT technique was performed using data from AErosol RObotic NETwork (AERONET) Cimel Electronique 318 photometers (CE318). A comparison between AOD obtained by applying the ZEN-LUT method on ZSRs (inferred from CE318 diffuse-sky measurements) and AOD provided by AERONET (derived from CE318 direct-sun measurements) was carried out at three sites characterized by a regular presence of desert mineral dust aerosols: Izaña and Santa Cruz in the Canary Islands and Tamanrasset in Algeria. The results show a coefficient of determination (R 2 ) ranging from 0.99 to 0.97, and root mean square errors (RMSE) ranging from 0.010 at Izaña to 0.032 at Tamanrasset. The comparison of ZSR values from ZEN-R41 and the CE318 showed absolute relative mean bias (RMB) < 10 %. ZEN-R41 AOD values inferred from ZEN-LUT methodology were compared with AOD provided by AERONET, showing a fairly good agreement in all wavelengths, with mean absolute AOD differences < 0.030 and R 2 higher than 0.97.

show abstract

Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean Basin and Middle East from direct-sun AERONET observations

Cited by 229 publications

References 72 publications

Columnar aerosol properties from sun-and-star photometry: statistical comparisons and day-to-night dynamic

Columnar aerosol properties from sun-and-star photometry: statistical comparisons and day-to-night dynamic

Characteristics of aerosols over Hyderabad in southern Peninsular India: synergy in the classification techniques

A new zenith-looking narrow-band radiometer-based system (ZEN) for dust aerosol optical depth monitoring

Contact Info

Product

Resources

About