Characterization of satellite-based proxies for estimating nucleation mode particles over South Africa

Abstract. Proxies for estimating nucleation mode number concentrations and further simplification for their use with satellite data have been presented in Kulmala et al. (2011). In this paper we discuss the underlying assumptions for these simplifications and evaluate the resulting proxies over an area in South Africa based on a comparison with a suite of ground-based measurements available from four different stations. The proxies are formulated in terms of sources (concentrations of precursor gases (NO2 and SO2) and UVB radiation intensity near the surface) and a sink term related to removal of the precursor gases due to condensation on pre-existing aerosols. A-Train satellite data are used as input to compute proxies. Both the input data and the resulting proxies are compared with those obtained from ground-based measurements. In particular, a detailed study is presented on the substitution of the local condensation sink (CS) with satellite aerosol optical depth (AOD), which is a column-integrated parameter. One of the main factors affecting the disagreement between CS and AOD is the presence of elevated aerosol layers. Overall, the correlation between proxies calculated from the in situ data and observed nucleation mode particle number concentrations (Nnuc) remained low. At the time of the satellite overpass (13:00–14:00 LT) the highest correlation is observed for SO2/CS (R2 = 0.2). However, when the proxies are calculated using satellite data, only NO2/AOD showed some correlation with Nnuc (R2 = 0.2). This can be explained by the relatively high uncertainties related especially to the satellite SO2 columns and by the positive correlation that is observed between the ground-based SO2 and NO2 concentrations. In fact, results show that the satellite NO2 columns compare better with in situ SO2 concentration than the satellite SO2 column. Despite the high uncertainties related to the proxies calculated using satellite data, the proxies calculated from the in situ data did not better predict Nnuc. Hence, overall improvements in the formulation of the proxies are needed.

[1]  Nickolay A. Krotkov,et al.  Global satellite analysis of the relation between aerosols and short-lived trace gases , 2011 .

[2]  A. Venter.  Air quality assessment of the industrialized western Bushveld Igneous Complex , 2011 .

[3]  Andrew A. Lacis,et al.  Scattering, Absorption, and Emission of Light by Small Particles , 2002 .

[4]  M. Utell,et al.  Acute health effects of ambient air pollution: the ultrafine particle hypothesis. , 2000, Journal of aerosol medicine : the official journal of the International Society for Aerosols in Medicine.

[5]  Re-evaluating the NO2 hotspot over the South African Highveld , 2012 .

[6]  Pasi Aalto,et al.  Atmospheric Chemistry and Physics on the Growth of Nucleation Mode Particles: Source Rates of Condensable Vapor in Polluted and Clean Environments , 2022 .

[7]  D. Worsnop,et al.  Source region plume characterisation of the interior of South Africa as observed at Welgegund , 2013 .

[8]  Miikka Dal Maso,et al.  Formation and growth of fresh atmospheric aerosols: eight years of aerosol size distribution data from SMEAR II, Hyytiälä, Finland , 2005 .

[9]  A. Kokhanovsky,et al.  Atmospheric Aerosol Monitoring from Satellite Observations: A History of Three Decades , 2009 .

[10]  Jeffrey S. Reid,et al.  Critical evaluation of the MODIS Deep Blue aerosol optical depth product for data assimilation over North Africa , 2012 .

[11]  N. Fuchs,et al.  HIGH-DISPERSED AEROSOLS , 1971 .

[12]  L. Remer,et al.  The Collection 6 MODIS aerosol products over land and ocean , 2013 .

[13]  J. Beukes,et al.  New particle formation events in semi-clean South African savannah , 2010 .

[14]  Robert C. Levy,et al.  Evaluating the assumptions of surface reflectance and aerosol type selection within the MODIS aerosol retrieval over land: The problem of dust type selection , 2010 .

[15]  M. Kulmala,et al.  On the formation and growth of atmospheric nanoparticles , 2008 .

[16]  P. Zyl,et al.  Spatial and temporal assessment of gaseous pollutants in the Highveld of South Africa , 2011 .

[17]  A. Kokhanovsky,et al.  Satellite Aerosol Remote Sensing Over Land , 2009 .

[18]  Kai Yang,et al.  Band residual difference algorithm for retrieval of SO/sub 2/ from the aura ozone monitoring instrument (OMI) , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[19]  J. Beukes,et al.  Long-term observations of aerosol size distributions in semi-clean and polluted savannah in South Africa , 2012 .

[20]  P. Zyl,et al.  An air quality assessment in the industrialised western Bushveld Igneous Complex, South Africa , 2012 .

[21]  J. Beukes,et al.  Characterisation of sub-micron particle number concentrations and formation events in the western Bushveld Igneous Complex, South Africa , 2012 .

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

[23]  J. Beukes,et al.  Multiple daytime nucleation events in semi-clean savannah and industrial environments in South Africa: analysis based on observations , 2013 .

[24]  G. Leeuw,et al.  Seasonal cycle, size dependencies, and source analyses of aerosol optical properties at the SMEAR II measurement station in Hyytiälä, Finland , 2010 .

[25]  K. Lehtinen,et al.  One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa , 2015 .

[26]  K. Lehtinen,et al.  On the concept of condensation sink diameter , 2003 .

[27]  G. Leeuw,et al.  The first estimates of global nucleation mode aerosol concentrations based on satellite measurements , 2011 .

[28]  James F. Gleason,et al.  Evaluation of OMI operational standard NO 2 column retrievals using in situ and surface-based NO 2 observations , 2014 .

[29]  Margarita López Martínez,et al.  Unified equations for the slope, intercept, and standard errors of the best straight line , 2004 .

[30]  G. Leeuw,et al.  South African EUCAARI measurements: seasonal variation of trace gases and aerosol optical properties , 2012 .

[31]  C. Liousse,et al.  Spatial and temporal assessment of organic and black carbon at four sites in the interior of South Africa , 2015 .

[32]  James F. Gleason,et al.  A new stratospheric and tropospheric NO2 retrieval algorithm for nadir-viewing satellite instruments : applications to OMI , 2013 .

[33]  Hanna Vehkamäki,et al.  Formation and growth rates of ultrafine atmospheric particles: a review of observations , 2004 .

[34]  Brittany McClure,et al.  Validation of SO2 Retrievals from the Ozone Monitoring Instrument over NE China , 2008 .

[35]  Nickolay A. Krotkov,et al.  Estimation of SO2 emissions using OMI retrievals , 2011 .

[36]  T. Petäjä,et al.  Sulfuric acid and OH concentrations in a boreal forest site , 2008 .

[37]  A. Peters,et al.  Daily measurement of organic compounds in ambient particulate matter in Augsburg, Germany: new aspects on aerosol sources and aerosol related health effects , 2009, Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals.

[38]  T. Petäjä,et al.  Basic characteristics of atmospheric particles, trace gases and meteorology in a relatively clean Southern African Savannah environment , 2008 .

[39]  D. Winker,et al.  Initial performance assessment of CALIOP , 2007 .

[40]  J. Burrows,et al.  The remote sensing of tropospheric composition from space , 2011 .

[41]  Jay R. Herman,et al.  Surface ultraviolet irradiance from OMI , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[42]  W. MacNee,et al.  Particulate air pollution and acute health effects , 1995, The Lancet.

[43]  Ville Vakkari,et al.  Transportable Aerosol Characterization Trailer with Trace Gas Chemistry: Design, Instruments and Verification , 2013 .

[44]  Satellite‐derived estimates of ultrafine particle concentrations over eastern North America , 2013 .