Aerosol characteristics over urban Cairo: Seasonal variations as retrieved from Sun photometer measurements

[1] During the Cairo Aerosol Characterization Experiment an automated Sun photometer belonging to the NASA Aerosol Robotic Network has been implemented for the first time in the megacity of Cairo, Egypt. The inversion of the measurements performed by this instrument several times a day and over a duration of more than 1 year (from the end of October 2004 to the end of January 2006) provides a way of determining the temporal variability of aerosol characteristics such as size distribution, complex refractive index, single-scattering albedo, and asymmetry parameter. The analysis of the results reveals that Cairo's aerosol is a mixture of three individual components produced by different mechanisms: “background pollution” aerosol produced by local urban activities, “pollution-like” aerosol resulting from biomass burning in the Nile delta, and “dust-like” aerosol released by wind erosion in the Sahara. It is also shown that the variations in the overall aerosol properties are in fact due to changes in the proportions of this mixture. In particular, short-duration dust storms and biomass-burning episodes explain the largest observed aerosol optical depths (AOD) (AOD > 0.7) through the extreme enhancements of concentrations in dust-like aerosols characterized by low Angstrom's exponent values (α < 0.5) and in “biomass-burning” aerosols (1.0 < α < 1.5). When averaged over longer (monthly and yearly) time periods, the effects of these high-frequency modifications are smoothed. In particular, an average “mixed aerosol” type is defined for the whole duration of the measurements period. The low single-scattering albedo (SSA) of this average aerosol and its marked spectral dependence clearly indicate that, at least on a yearly basis, the aerosol is dominated by its two light absorbing pollution components (background pollution and pollution-like) and to such an extent that it compares well with values obtained in other polluted megacities (e.g., Mexico City). This general dominance of the absorbing components can be challenged at shorter timescales. Indeed, the occurrence of several dust storms in springtime, and particularly in April, causes a significant increase in SSA and a parallel decrease in spectral dependence during this month. Conversely, the October biomass-burning events are not able to cause such important deviations from the yearly averaged mixed aerosol model that its optical properties can no longer be used for this month.

[1]  Richard Betts,et al.  The science of climate change , 2010 .

[2]  M. Wahab,et al.  Origin of black carbon concentration peaks in Cairo (Egypt) , 2008 .

[3]  T. El-Araby,et al.  Seasonality of major aerosol species and their transformations in Cairo megacity , 2008 .

[4]  Dimitris G. Kaskaoutis,et al.  Aerosol climatology and discrimination of different types over Athens, Greece, based on MODIS data , 2007 .

[5]  Jean-François Léon,et al.  Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust , 2006 .

[6]  Yoram J. Kaufman,et al.  Dust and pollution aerosols over the Negev desert, Israel: Properties, transport, and radiative effect , 2006 .

[7]  B. Holben,et al.  Aerosol Properties Over Japan Determined by Sun/Sky Photometry , 2005 .

[8]  Alexander Smirnov,et al.  Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid‐Pacific , 2005 .

[9]  Chen Hongbin,et al.  Aerosol properties and their spatial and temporal variations over North China in spring 2001 , 2005 .

[10]  Paola Formenti,et al.  Iron oxides and light absorption by pure desert dust: An experimental study , 2004 .

[11]  A. Zakey,et al.  Atmospheric turbidity over Egypt , 2004 .

[12]  T. Cokacar,et al.  Optical properties of mineral dust outbreaks over the northeastern Mediterranean , 2003 .

[13]  D. Tanré,et al.  Spatial and temporal variability of aerosol: size distribution and optical properties , 2003 .

[14]  M. Tadros,et al.  Determination of Ångström coefficients from spectral aerosol optical depth at two sites in Egypt , 2002 .

[15]  D. Lowenthal,et al.  A preliminary apportionment of the sources of ambient PM10, PM2.5, and VOCs in Cairo , 2002 .

[16]  Oleg Dubovik,et al.  Non‐spherical aerosol retrieval method employing light scattering by spheroids , 2002 .

[17]  T. Eck,et al.  Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations , 2002 .

[18]  T. Eck,et al.  Atmospheric Aerosol Optical Properties in the Persian Gulf , 2002 .

[19]  V. Cachorro,et al.  A quantitative comparison of α-Å turbidity parameter retrieved in different spectral ranges based on spectroradiometer solar radiation measurements , 2001 .

[20]  S. A. El-Wakil,et al.  Atmospheric turbidity of urban and desert areas of the Nile Basin in the aftermath of Mt. Pinatubo’s eruption , 2001 .

[21]  Michael D. King,et al.  A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements , 2000 .

[22]  T. Eck,et al.  Accuracy assessments of aerosol optical properties retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance measurements , 2000 .

[23]  J. Prospero.  Long‐term measurements of the transport of African mineral dust to the southeastern United States: Implications for regional air quality , 1999 .

[24]  Irina N. Sokolik,et al.  Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths , 1999 .

[25]  Ramaswamy,et al.  Tropospheric Aerosol Climate Forcing in Clear-Sky Satellite Observations over the Oceans. , 1999, Science.

[26]  Yoram J. Kaufman,et al.  Interannual variation of ambient aerosol characteristics on the east coast of the United States , 1999 .

[27]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[28]  J. Seinfeld,et al.  Atmospheric Chemistry and Physics: From Air Pollution to Climate Change , 1998 .

[29]  J. Garrison,et al.  Critical evaluation of precipitable water and atmospheric turbidity in Canada using measured hourly solar irradiance , 1998 .

[30]  Jay R. Herman,et al.  Earth surface reflectivity climatology at 340–380 nm from TOMS data , 1997 .

[31]  I. H. Blifford,et al.  A reinforced coagulation-sedimentation model for stratospheric aerosols , 1975 .

[32]  M. Griggs,et al.  Measurements of atmospheric aerosol optical thickness over water using ERTS-1 data. , 1975, Journal of the Air Pollution Control Association.

[33]  C. Junge,et al.  THE SIZE DISTRIBUTION AND AGING OF NATURAL AEROSOLS AS DETERMINED FROM ELECTRICAL AND OPTICAL DATA ON THE ATMOSPHERE , 1955 .

[34]  K. H. Soliman.  Rainfall over Egypt , 1953 .

[35]  M. G. Elfandy.  The formation of depressions of the khamsin type , 1940 .

[36]  M. Wahab,et al.  Extreme Variability of Aerosol Optical Properties: The Cairo Aerosol Characterization Experiment Case Study , 2006 .

[37]  P. Devara,et al.  Retrieval of Aerosol Size Index From High-Resolution Spectroradiometer Observations , 1997 .

[38]  John D. Spengler,et al.  Particles in our air : concentrations and health effects , 1996 .

[39]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

[40]  M. Iqbal.  An introduction to solar radiation , 1983 .