Single particle diversity and mixing state measurements

Abstract. A newly developed framework for quantifying aerosol particle diversity and mixing state based on information-theoretic entropy is applied for the first time to single particle mass spectrometry field data. Single particle mass fraction estimates for black carbon, organic aerosol, ammonium, nitrate and sulfate, derived using single particle mass spectrometer, aerosol mass spectrometer and multi-angle absorption photometer measurements are used to calculate single particle species diversity (Di). The average single particle species diversity (Dα) is then related to the species diversity of the bulk population (Dγ) to derive a mixing state index value (χ) at hourly resolution. The mixing state index is a single parameter representation of how internally/externally mixed a particle population is at a given time. The index describes a continuum, with values of 0 and 100% representing fully external and internal mixing, respectively. This framework was applied to data collected as part of the MEGAPOLI winter campaign in Paris, France, 2010. Di values are low (~ 2) for fresh traffic and wood-burning particles that contain high mass fractions of black carbon and organic aerosol but low mass fractions of inorganic ions. Conversely, Di values are higher (~ 4) for aged carbonaceous particles containing similar mass fractions of black carbon, organic aerosol, ammonium, nitrate and sulfate. Aerosol in Paris is estimated to be 59% internally mixed in the size range 150–1067 nm, and mixing state is dependent both upon time of day and air mass origin. Daytime primary emissions associated with vehicular traffic and wood-burning result in low χ values, while enhanced condensation of ammonium nitrate on existing particles at night leads to higher χ values. Advection of particles from continental Europe containing ammonium, nitrate and sulfate leads to increases in Dα, Dγ and χ. The mixing state index represents a useful metric by which to compare and contrast ambient particle mixing state at other locations globally.

[1]  R. Healy.  Supplement of Single particle diversity and mixing state measurements , 2014 .

[2]  Matthew West,et al.  Quantifying aerosol mixing state with entropy and diversity measures , 2013 .

[3]  G. Evans,et al.  Quantitative determination of carbonaceous particle mixing state in Paris using single-particle mass spectrometer and aerosol mass spectrometer measurements , 2013 .

[4]  K. Prather,et al.  Air quality impact and physicochemical aging of biomass burning aerosols during the 2007 San Diego wildfires. , 2013, Environmental science & technology.

[5]  J. Seinfeld,et al.  The mixing state of carbonaceous aerosol particles in northern and southern California measured during CARES and CalNex 2010 , 2012 .

[6]  D. Ceburnis,et al.  Characterization of urban aerosol in Cork city (Ireland) using aerosol mass spectrometry , 2012 .

[7]  Jean Sciare,et al.  A one-year comprehensive chemical characterisation of fine aerosol (PM 2.5 ) at urban, suburban and rural background sites in the region of Paris (France) , 2012 .

[8]  J. Schneider,et al.  Wintertime aerosol chemical composition and source apportionment of the organic fraction in the metropolitan area of Paris , 2012 .

[9]  J. Seinfeld,et al.  Flight-based chemical characterization of biomass burning aerosols within two prescribed burn smoke plumes , 2011 .

[10]  A. Stohl,et al.  Sources and mixing state of size-resolved elemental carbon particles in a European megacity: Paris , 2011 .

[11]  G. Evans,et al.  Quantification of aerosol chemical composition using continuous single particle measurements , 2011 .

[12]  J. Seinfeld,et al.  Measurements of isoprene-derived organosulfates in ambient aerosols by aerosol time-of-flight mass spectrometry - part 1: single particle atmospheric observations in Atlanta. , 2011, Environmental science & technology.

[13]  J. D. de Gouw,et al.  Contribution of isoprene-derived organosulfates to free tropospheric aerosol mass , 2010, Proceedings of the National Academy of Sciences.

[14]  Stig Hellebust,et al.  Source apportionment of PM 2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements , 2010 .

[15]  A. Zelenyuk,et al.  In situ characterization of cloud condensation nuclei, interstitial, and background particles using the single particle mass spectrometer, SPLAT II. , 2010, Analytical chemistry.

[16]  David R. Musicant,et al.  Environmental chemistry through intelligent atmospheric data analysis , 2010, Environ. Model. Softw..

[17]  Ying Wang,et al.  Characterization of the single particle mixing state of individual ship plume events measured at the Port of Los Angeles. , 2010, Environmental science & technology.

[18]  K. Prather,et al.  Real-time, single-particle volatility, size, and chemical composition measurements of aged urban aerosols. , 2009, Environmental science & technology.

[19]  Jay R. Turner,et al.  Estimating the contribution of point sources to atmospheric metals using single-particle mass spectrometry , 2009 .

[20]  T. Tuch,et al.  Design and performance of an automatic regenerating adsorption aerosol dryer for continuous operation at monitoring sites , 2009 .

[21]  K. Prather,et al.  In-situ measurements of the mixing state and optical properties of soot with implications for radiative forcing estimates , 2009, Proceedings of the National Academy of Sciences.

[22]  U. Lohmann,et al.  Subarctic atmospheric aerosol composition: 2. Hygroscopic growth properties , 2009 .

[23]  K. Prather,et al.  Seasonal volatility dependence of ambient particle phase amines. , 2009, Environmental science & technology.

[24]  Hiroshi Furutani,et al.  Impact of emissions from the Los Angeles port region on San Diego air quality during regional transport events. , 2009, Environmental science & technology.

[25]  Dirk Richter,et al.  Organic aerosol formation in urban and industrial plumes near Houston and Dallas, Texas , 2009 .

[26]  Delbert J. Eatough,et al.  Source apportionment of 1 h semi-continuous data during the 2005 Study of Organic Aerosols in Riverside (SOAR) using positive matrix factorization , 2008 .

[27]  M. Johnston,et al.  Ion formation mechanism in laser desorption ionization of individual nanoparticles , 2008, Journal of the American Society for Mass Spectrometry.

[28]  Murray V. Johnston,et al.  Source characterization and identification by real-time single particle mass spectrometry. , 2007 .

[29]  K. Prather,et al.  Assessment of the relative importance of atmospheric aging on CCN activity derived from field observations , 2007 .

[30]  M. Molina,et al.  Measurement of ambient aerosols in northern Mexico City by single particle mass spectrometry , 2007 .

[31]  Katrin Fuhrer,et al.  Field-deployable, high-resolution, time-of-flight aerosol mass spectrometer. , 2006, Analytical chemistry.

[32]  P. Bhave,et al.  Comparison of two methods for obtaining quantitative mass concentrations from aerosol time-of-flight mass spectrometry measurements. , 2006, Analytical chemistry.

[33]  M. Frank,et al.  Fast determination of the relative elemental and organic carbon content of aerosol samples by on-line single-particle aerosol time-of-flight mass spectrometry. , 2006, Environmental science & technology.

[34]  A. Wexler,et al.  Identification of sources of atmospheric PM at the Pittsburgh Supersite, Part I: Single particle analysis and filter-based positive matrix factorization , 2006 .

[35]  K. Prather,et al.  Improvements in ion signal reproducibility obtained using a homogeneous laser beam for on-line laser desorption/ionization of single particles. , 2004, Rapid communications in mass spectrometry : RCM.

[36]  Andreas Petzold,et al.  Multi-angle absorption photometry—a new method for the measurement of aerosol light absorption and atmospheric black carbon , 2004 .

[37]  K. Prather,et al.  Development and characterization of an aerosol time-of-flight mass spectrometer with increased detection efficiency. , 2004, Analytical chemistry.

[38]  W. P. Ball,et al.  Characterization of carbonaceous aerosols outflow from India and Arabia: Biomass/biofuel burning and fossil fuel combustion , 2003 .

[39]  K. Prather,et al.  Aerosol time‐of‐flight mass spectrometry during the Atlanta Supersite Experiment: 2. Scaling procedures , 2003 .

[40]  M. Feldman,et al.  Genetic Structure of Human Populations , 2002, Science.

[41]  Jeffrey R. Whiteaker,et al.  Effects of meteorological conditions on aerosol composition and mixing state in Bakersfield, CA. , 2002, Environmental science & technology.

[42]  M. Johnston,et al.  Size and composition biases on the detection of individual ultrafine particles by aerosol mass spectrometry , 2000 .

[43]  K. Prather,et al.  Variations in the Size and Chemical Composition of Nitrate-Containing Particles in Riverside, CA , 2000 .

[44]  K. Prather,et al.  Interpretation of mass spectra from organic compounds in aerosol time-of-flight mass spectrometry , 2000, Analytical Chemistry.

[45]  D. S. Gross,et al.  Relative sensitivity factors for alkali metal and ammonium cations in single-particle aerosol time-of-flight mass spectra. , 2000, Analytical chemistry.

[46]  A. Wiedensohler,et al.  DESIGN OF A DMA-BASED SIZE SPECTROMETER FOR A LARGE PARTICLE SIZE RANGE AND STABLE OPERATION , 1999 .

[47]  B. Morrical,et al.  Real-Time Analysis of Individual Atmospheric Aerosol Particles: Design and Performance of a Portable ATOFMS , 1997 .

[48]  Mohsen Attaran,et al.  Industrial diversity and economic performance in U.S. areas , 1986 .

[49]  R. H. Whittaker,et al.  Dominance and Diversity in Land Plant Communities , 1965, Science.