Changes in precipitating snow chemistry with location and elevation in the California Sierra Nevada

Orographic snowfall in the Sierra Nevada Mountains is an important source of water for California and can vary significantly on an annual basis. The microphysical properties of orographic clouds and subsequent formation of precipitation are impacted, in part, by aerosols of varying size, number, and chemical composition, which are incorporated into clouds formed along the Sierra barrier. Herein, the physicochemical properties and sources of insoluble residues and soluble ions found in precipitation samples were explored for three sites of variable elevation in the Sierra Nevada during the 2012–2013 winter season. Residues were characterized using a suite of physicochemical techniques to determine the size‐resolved number concentrations and associated chemical composition. A transition in the aerosol sources that served as cloud seeds or were scavenged in‐cloud and below‐cloud was observed as a function of location and elevation. Anthropogenic influence from the Central Valley was dominant at the two lowest elevation sites (1900 and 2200 m above mean sea level (AMSL)), whereas long‐range transported mineral dust was a larger contributor at the highest elevation site where cleaner conditions were observed (2600 m AMSL). The residues and soluble ions observed provide insight into how multiple aerosol sources can impact cloud and precipitation formation processes, even over relatively small spatial scales. The transition with increasing elevation to aerosols that serve as ice nucleating particles may impact the properties and extent of snowfall in remote mountain regions where snowpack provides a vital supply of water.Key PointsPhysiochemical properties of particles found in precipitation were determinedBoth anthropogenic and natural sources contributed to the snow residue chemistrySnow residue sources varied depending on location and elevationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/133563/1/jgrd53083-sup-0001-SI.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133563/2/jgrd53083_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133563/3/jgrd53083.pd

Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility.

Genome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk

Computer-controlled Raman microspectroscopy (CC-Raman): A method for the rapid characterization of individual atmospheric aerosol particles

<p>The ability of an atmospheric aerosol particle to impact climate by acting as a cloud condensation nucleus (CCN) or an ice nucleus (IN), as well as scatter and absorb solar radiation is determined by its physicochemical properties at the single particle level, specifically size, morphology, and chemical composition. The identification of the secondary species present in individual aerosol particles is important as aging, which leads to the formation of these species, can modify the climate relevant behavior of particles. Raman microspectroscopy has a great deal of promise for identifying secondary species and their mixing with primary components, as it can provide detailed information on functional groups present, morphology, and internal structure. However, as with many other detailed spectroscopic techniques, manual analysis by Raman microspectroscopy can be slow, limiting single particle statistics and the number of samples that can be analyzed. Herein, the application of computer-controlled Raman (CC-Raman) for detailed physicochemical analysis that increases throughput and minimizes user bias is described. CC-Raman applies automated mapping to increase analysis speed allowing for up to 100 particles to be analyzed in an hour. CC-Raman is applied to both laboratory and ambient samples to demonstrate its utility for the analysis of both primary and, most importantly, secondary components (sulfate, nitrate, ammonium, and organic material). Reproducibility and precision are compared to computer controlled-scanning electron microscopy (CCSEM). The greater sample throughput shows the potential for CC-Raman to improve particle statistics and advance our understanding of aerosol particle composition and mixing state, and, thus, climate-relevant properties.</p> <p>© 2017 American Association for Aerosol Research</p

Surface Enhanced Raman Spectroscopy Enables Observations of Previously Undetectable Secondary Organic Aerosol Components at the Individual Particle Level

The first use of surface enhanced Raman spectroscopy (SERS) to detect trace organic and/or inorganic species in ambient atmospheric aerosol particles is presented. This new analytical method provides direct, spectroscopic detection of species present at attogram to femtogram levels in individual submicrometer atmospheric particles. An array of spectral features resulting from organic functional groups in secondary organic aerosol (SOA) material were observed in individual particles impacted on silver nanoparticle-coated substrates. The results demonstrate the complexity of organic and inorganic species in SOA formed by oxidation of biogenic volatile organic compounds (BVOCs) at the single particle level. While SOA composition is frequently assumed to be homogeneous between and within individual particles, substantial particle-to-particle variability in SOA composition and changes on scales <1 μm were observed. The observations obtained with this new method demonstrate the power of SERS to probe difficult to detect inter- and intraparticle variability in ambient SOA particles

Isoprene-Derived Organosulfates: Vibrational Mode Analysis by Raman Spectroscopy, Acidity-Dependent Spectral Modes, and Observation in Individual Atmospheric Particles

Isoprene, the most abundant biogenic volatile organic compound (BVOC) in the atmosphere, and its low-volatility oxidation products lead to secondary organic aerosol (SOA) formation. Isoprene-derived organosulfates formed from reactions of isoprene oxidation products with sulfate in the particle phase are a significant component of SOA and can hydrolyze forming polyols. Despite characterization by mass spectrometry, their basic structural and spectroscopic properties remain poorly understood. Herein, Raman microspectroscopy and density functional theory (DFT) calculations (CAM-B3LYP level of theory) were combined to analyze the vibrational modes of key organosulfates, 3-methyltetrol sulfate esters (racemic mixture of two isomers), and racemic 2-methylglyceric acid sulfate ester, and hydrolysis products, 2-methyltetrols, and 2-methylglyceric acid. Two intense vibrational modes were identified, ν­(RO–SO₃) (846 ± 4 cm^–1) and ν_s(SO₃) (1065 ± 2 cm^–1), along with a lower intensity δ­(SO₃) mode (586 ± 2 cm^–1). For 2-methylglyceric acid and its sulfate esters, deprotonation of the carboxylic acid at pH values above the p<i>K</i>_a decreased the carbonyl stretch frequency (1724 cm^–1), while carboxylate modes grew in for ν_s(COO^–) and ν_a(COO^–) at 1413 and 1594 cm^–1, respectively. The ν­(RO–SO₃) and ν_s(SO₃) modes were observed in individual atmospheric particles and can be used in future studies of complex SOA mixtures to distinguish organosulfates from inorganic sulfate or hydrolysis products

Atomic Force Microscopy-Infrared Spectroscopy of Individual Atmospheric Aerosol Particles: Subdiffraction Limit Vibrational Spectroscopy and Morphological Analysis

Chemical analysis of atmospheric aerosols is an analytical challenge, as aerosol particles are complex chemical mixtures that can contain hundreds to thousands of species in attoliter volumes at the most abundant sizes in the atmosphere (∼100 nm). These particles have global impacts on climate and health, but there are few methods available that combine imaging and the detailed molecular information from vibrational spectroscopy for individual particles <500 nm. Herein, we show the first application of atomic force microscopy with infrared spectroscopy (AFM-IR) to detect trace organic and inorganic species and probe intraparticle chemical variation in individual particles down to 150 nm. By detecting photothermal expansion at frequencies where particle species absorb IR photons from a tunable laser, AFM-IR can study particles smaller than the optical diffraction limit. Combining strengths of AFM (ambient pressure, height, morphology, and phase measurements) with photothermal IR spectroscopy, the potential of AFM-IR is shown for a diverse set of single-component particles, liquid–liquid phase separated particles (core–shell morphology), and ambient atmospheric particles. The spectra from atmospheric model systems (ammonium sulfate, sodium nitrate, succinic acid, and sucrose) had clearly identifiable features that correlate with absorption frequencies for infrared-active modes. Additionally, molecular information was obtained with <100 nm spatial resolution for phase separated particles with a ∼150 nm shell and 300 nm core. The subdiffraction limit capability of AFM-IR has the potential to advance understanding of particle impacts on climate and health by improving analytical capabilities to study water uptake, heterogeneous reactivity, and viscosity

Rapid Kinetics of Size and pH-Dependent Dissolution and Aggregation of Silver Nanoparticles in Simulated Gastric Fluid

As silver nanoparticles (AgNPs) are used in a wide array of commercial products and can enter the human body through oral exposure, it is important to understand the fundamental physical and chemical processes leading to changes in nanoparticle size under the conditions of the gastrointestinal (GI) tract. Rapid AgNP growth was observed using nanoparticle tracking analysis with 30 s resolution over a period of 17 min in simulated gastric fluid (SGF) to explore rapid kinetics as a function of pH (SGF at pH 2, 3.5, 4.5 and 5), size (20 and 110 nm AgNPs), and nanoparticle coating (citrate and PVP). Growth was observed for 20 nm AgNP at each pH, decreasing in rate with increasing pH, with the kinetics shifting from second-order to first-order. The 110 nm AgNP showed growth at ≤3.5 pH, with no growth observed at higher pH. This behavior can be explained by the generation of Ag⁺ in acidic environments, which precipitates with Cl^–, leading to particle growth and facilitating particle aggregation by decreasing their electrostatic repulsion in solution. These results highlight the need to further understand the importance of initial size, physicochemical properties, and kinetics of AgNPs after ingestion to assess potential toxicity