Fitting of the particle size distributions by lognormal functions in the frameworks of empirical classification of the “aerosol weather” types

Variability of the volume distribution functions in the submicron and coarse size ranges in each season and under four type of “aerosol weather”: «background», «Haze-S», «Smog» и «Smoke haze» is analyzed on the basis of the data on daily mean values of the number concentration of the near-ground atmospheric aerosol obtained by means of an optical counter at the Aerosol Monitoring Station of IAO SB RAS in 2000-2017. The analyzed data arrays were formed in the «σd–Р» coordinates, where σd is the scattering coefficient of the aerosol dry matter at the wavelength of λ = 0.51 μm), P is the ratio of the mass concentration of the absorbing substance to the mass concentration of submicron particles. The fitting of the particle volume distribution was carried out as a superposition of two broad lognormal distributions of submicron and coarse particles. The average values of the fitting parameters are presented for all seasons (winter, spring, summer, autumn) and all types of the aerosol weather.

[1]  M. Kerker,et al.  Response calculations for light-scattering aerosol particle counters. , 1975, Applied optics.

[2]  H. Quenzel.  Influence of refractive index on the accuracy of size determination of aerosol particles with light-scattering aerosol counters. , 1969, Applied optics.

[3]  R. A. Bakhanova,et al.  The calibration curve of photoelectric counters and computation of particle size distribution when the relationship between particle size and electrical pulse amplitude is ambiguous , 1973 .

[4]  J. Raymond Hodkinson,et al.  Response calculations for light-scattering aerosol counters and photometers , 1965 .

[5]  H. Carlsen,et al.  Introducing the Transnational Climate Impacts Index: Indicators of country-level exposure – methodology report , 2016 .

[6]  David J. Delene,et al.  Variability of Aerosol Optical Properties at Four North American Surface Monitoring Sites , 2002 .

[7]  Philippe Ciais,et al.  Opinion: In the wake of Paris Agreement, scientists must embrace new directions for climate change research , 2016, Proceedings of the National Academy of Sciences.

[8]  J. Heyder,et al.  Optimization of response functions of light scattering instruments for size evaluation of aerosol particles. , 1979, Applied optics.

[9]  K. Bullrich,et al.  Scattered Radiation in the Atmosphere and the Natural Aerosol , 1964 .

[10]  T. Novakov,et al.  The aethalometer — An instrument for the real-time measurement of optical absorption by aerosol particles , 1983 .

[11]  Distribution and temporal behavior of particulate matter over the urban area of Buenos Aires , 2010 .

[12]  Boris D. Belan,et al.  Annual dynamics of aerosol organic components in the free atmosphere over South-Western Siberia , 2016 .

[13]  Mass fraction of black carbon in submicron aerosol as an indicator of influence of smoke from remote forest fires in Siberia , 2008 .

[14]  F. T. Gucker,et al.  Influence of the collecting lens aperture on the light-scattering diagrams from single aerosol particles , 1968 .

[15]  D. Pozdniakov,et al.  Aerosol models of the atmosphere , 1981 .

[16]  D. W. Nelson,et al.  A characterization of Arctic aerosols on the basis of aerosol optical depth and black carbon measurements , 2014 .

[17]  K. I. Kondratʹev,et al.  Atmospheric Aerosol Properties: Formation, Processes and Impacts , 2005 .

[18]  O. Edenhofer,et al.  Climate change 2014 : mitigation of climate change , 2014 .

[19]  Michael Cusack,et al.  Variability of Particle Number, Black Carbon, and PM10, PM2.5, and PM1 Levels and Speciation: Influence of Road Traffic Emissions on Urban Air Quality , 2010 .