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A list of authors and their affiliations appears at the end of the paper New-particle formation is a major contributor to urban smog, but how it occurs in cities is often puzzling. If the growth rates of urban particles are similar to those found in cleaner environments (1–10 nanometres per hour), then existing understanding suggests that new urban particles should be rapidly scavenged by the high concentration of pre-existing particles. Here we show, through experiments performed under atmospheric conditions in the CLOUD chamber at CERN, that below about +5 degrees Celsius, nitric acid and ammonia vapours can condense onto freshly nucleated particles as small as a few nanometres in diameter. Moreover, when it is cold enough (below −15 degrees Celsius), nitric acid and ammonia can nucleate directly through an acid–base stabilization mechanism to form ammonium nitrate particles. Given that these vapours are often one thousand times more abundant than sulfuric acid, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. However, these high growth rates require the gas-particle ammonium nitrate system to be out of equilibrium in order to sustain gas-phase supersaturations. In view of the strong temperature dependence that we measure for the gas-phase supersaturations, we expect such transient conditions to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and by strong local sources such as traffic. Even though rapid growth from nitric acid and ammonia condensation may last for only a few minutes, it is nonetheless fast enough to shepherd freshly nucleated particles through the smallest size range where they are most vulnerable to scavenging loss, thus greatly increasing their survival probability. We also expect nitric acid and ammonia nucleation and rapid growth to be important in the relatively clean and cold upper free troposphere, where ammonia can be convected from the continental boundary layer and nitric acid is abundant from electrical storms.
Currently, the complete chemical characterization of nanoparticles (< 100 nm) represents an analytical challenge, since these particles are abundant in number but have negligible mass. Several methods for particle-phase characterization have been recently developed to better detect and infer more accurately the sources and fates of sub-100 nm particles, but a detailed comparison of different approaches is missing. Here we report on the chemical composition of secondary organic aerosol (SOA) nanoparticles from experimental studies of α-pinene ozonolysis at −50, −30, and −10 ∘C and intercompare the results measured by different techniques. The experiments were performed at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). The chemical composition was measured simultaneously by four different techniques: (1) thermal desorption–differential mobility analyzer (TD–DMA) coupled to a NO chemical ionization–atmospheric-pressure-interface–time-of-flight (CI–APi–TOF) mass spectrometer, (2) filter inlet for gases and aerosols (FIGAERO) coupled to an I− high-resolution time-of-flight chemical ionization mass spectrometer (HRToF-CIMS), (3) extractive electrospray Na+ ionization time-of-flight mass spectrometer (EESI-TOF), and (4) offline analysis of filters (FILTER) using ultra-high-performance liquid chromatography (UHPLC) and heated electrospray ionization (HESI) coupled to an Orbitrap high-resolution mass spectrometer (HRMS). Intercomparison was performed by contrasting the observed chemical composition as a function of oxidation state and carbon number, by estimating the volatility and comparing the fraction of volatility classes, and by comparing the thermal desorption behavior (for the thermal desorption techniques: TD–DMA and FIGAERO) and performing positive matrix factorization (PMF) analysis for the thermograms. We found that the methods generally agree on the most important compounds that are found in the nanoparticles. However, they do see different parts of the organic spectrum. We suggest potential explanations for these differences: thermal decomposition, aging, sampling artifacts, etc. We applied PMF analysis and found insights of thermal decomposition in the TD–DMA and the FIGAERO.
Currently, the complete chemical characterization of nanoparticles (< 100 nm) represents an analytical challenge, since these particles are abundant in number but have negligible mass. Several methods for particle-phase characterization have been recently developed to better detect and infer more accurately the sources and fates of sub-100 nm particles, but a detailed comparison of different approaches is missing. Here we report on the chemical composition of secondary organic aerosol (SOA) nanoparticles from experimental studies of α-pinene ozonolysis at −50, −30, and −10 ∘C and intercompare the results measured by different techniques. The experiments were performed at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). The chemical composition was measured simultaneously by four different techniques: (1) thermal desorption–differential mobility analyzer (TD–DMA) coupled to a NO chemical ionization–atmospheric-pressure-interface–time-of-flight (CI–APi–TOF) mass spectrometer, (2) filter inlet for gases and aerosols (FIGAERO) coupled to an I− high-resolution time-of-flight chemical ionization mass spectrometer (HRToF-CIMS), (3) extractive electrospray Na+ ionization time-of-flight mass spectrometer (EESI-TOF), and (4) offline analysis of filters (FILTER) using ultra-high-performance liquid chromatography (UHPLC) and heated electrospray ionization (HESI) coupled to an Orbitrap high-resolution mass spectrometer (HRMS). Intercomparison was performed by contrasting the observed chemical composition as a function of oxidation state and carbon number, by estimating the volatility and comparing the fraction of volatility classes, and by comparing the thermal desorption behavior (for the thermal desorption techniques: TD–DMA and FIGAERO) and performing positive matrix factorization (PMF) analysis for the thermograms. We found that the methods generally agree on the most important compounds that are found in the nanoparticles. However, they do see different parts of the organic spectrum. We suggest potential explanations for these differences: thermal decomposition, aging, sampling artifacts, etc. We applied PMF analysis and found insights of thermal decomposition in the TD–DMA and the FIGAERO.