Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China.

Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µgm-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Corrigendum: Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition.

This corrects the article DOI: 10.1038/sdata.2017.3.

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition.

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

Ice nucleation active particles are efficiently removed by precipitating clouds.

Ice nucleation in cold clouds is a decisive step in the formation of rain and snow. Observations and modelling suggest that variations in the concentrations of ice nucleating particles (INPs) affect timing, location and amount of precipitation. A quantitative description of the abundance and variability of INPs is crucial to assess and predict their influence on precipitation. Here we used the hydrological indicator δ(18)O to derive the fraction of water vapour lost from precipitating clouds and correlated it with the abundance of INPs in freshly fallen snow. Results show that the number of INPs active at temperatures ≥ -10 °C (INPs-10) halves for every 10% of vapour lost through precipitation. Particles of similar size (>0.5 µm) halve in number for only every 20% of vapour lost, suggesting effective microphysical processing of INPs during precipitation. We show that INPs active at moderate supercooling are rapidly depleted by precipitating clouds, limiting their impact on subsequent rainfall development in time and space.

Real-world emission factors for antimony and other brake wear related trace elements: size-segregated values for light and heavy duty vehicles.

Hourly trace element measurements were performed in an urban street canyon and next to an interurban freeway in Switzerland during more than one month each, deploying a rotating drum impactor (RDI) and subsequent sample analysis by synchrotron radiation X-ray fluorescence spectrometry (SR-XRF). Antimony and other brake wear associated elements were detected in three particle size ranges (2.5-10, 1-2.5, and 0.1-1 microm). The hourly measurements revealed that the effect of resuspended road dust has to be taken into account for the calculation of vehicle emission factors. Individual values for light and heavy duty vehicles were obtained for stop-and-go traffic in the urban street canyon. Mass based brake wear emissions were predominantly found in the coarse particle fraction. For antimony, determined emission factors were 11 +/- 7 and 86 +/- 42 microg km(-1) vehicle(-1) for light and heavy duty vehicles, respectively. Antimony emissions along the interurban freeway with free-flowing traffic were significantly lower. Relative patterns for brake wear related elements were very similar for both considered locations. Beside vehicle type specific brake wear emissions, road dust resuspension was found to be a dominant contributor of antimony in the street canyon.

Trace metals in ambient air: Hourly size-segregated mass concentrations determined by synchrotron-XRF.

Trace metals are ubiquitous in urban ambient air, with mass concentrations in the range of a few microg/m3 down to less than 100 pg/m3. To measure such low concentrations represents a challenge for chemical and physical analysis. In this study, ambient aerosol was collected in Zürich (Switzerland) in 1-h intervals and three size fractions (aerodynamic diameters 0.1-1 microm, 1-2.5 microm, and 2.5-10 microm), using a three-stage rotating drum impactor (RDI). The samples were analyzed by energy-dispersive Synchrotron radiation X-ray fluorescence spectrometry (SR-XRF) to obtain size-segregated hourly elemental aerosol mass concentrations for Cr, Mn, Fe, Cu, Zn, Br, and Pb, along with S, Cl, and Ca under the selected experimental conditions. The high sensitivity of SR-XRF allowed for detection limits of <50 pg/m3 for most of the above elements, with a net analysis time of only 15 s per sample. The data obtained with this technique illustrate that there is a considerable gain of relevant information when time resolution for measurements is increased from 1 day to 1 h. The individual size fractions of a specific element may show significantly different short-term patterns.