130 research outputs found

    Atmospheric Acetaldehyde: Importance of Air-Sea Exchange and a Missing Source in the Remote Troposphere.

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    We report airborne measurements of acetaldehyde (CH3CHO) during the first and second deployments of the National Aeronautics and Space Administration (NASA) Atmospheric Tomography Mission (ATom). The budget of CH3CHO is examined using the Community Atmospheric Model with chemistry (CAM-chem), with a newly-developed online air-sea exchange module. The upper limit of the global ocean net emission of CH3CHO is estimated to be 34 Tg a-1 (42 Tg a-1 if considering bubble-mediated transfer), and the ocean impacts on tropospheric CH3CHO are mostly confined to the marine boundary layer. Our analysis suggests that there is an unaccounted CH3CHO source in the remote troposphere and that organic aerosols can only provide a fraction of this missing source. We propose that peroxyacetic acid (PAA) is an ideal indicator of the rapid CH3CHO production in the remote troposphere. The higher-than-expected CH3CHO measurements represent a missing sink of hydroxyl radicals (and halogen radical) in current chemistry-climate models

    Atmospheric Benzene Observations from an Oil and Gas Field in the Denver Julesburg Basin in July and August 2014

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    High time resolution measurements of volatile organic compounds (VOCs) were collectedusing a proton-transfer-reaction quadrupole mass spectrometry (PTR-QMS) instrument at the PlattevilleAtmospheric Observatory (PAO) in Colorado to investigate how oil and natural gas (ONG) developmentimpacts air quality within the Wattenburg Gas Field (WGF) in the Denver-Julesburg Basin. The measurementswere carried out in July and August 2014 as part of NASAs Deriving Information on Surface Conditions fromColumn and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign. ThePTR-QMS data were supported by pressurized whole air canister samples and airborne vertical and horizontalsurveys of VOCs. Unexpectedly high benzene mixing ratios were observed at PAO at ground level (meanbenzene 0.53 ppbv, maximum benzene 29.3 ppbv), primarily at night (mean nighttime benzene 0.73ppbv). These high benzene levels were associated with southwesterly winds. The airborne measurementsindicate that benzene originated from within the WGF, and typical source signatures detected in the canistersamples implicate emissions from ONG activities rather than urban vehicular emissions as primary benzenesource. This conclusion is backed by a regional toluene-to-benzene ratio analysis which associated southerlyflow with vehicular emissions from the Denver area. Weak benzene-to-CO correlations confirmed that trafficemissions were not responsible for the observed high benzene levels. Previous measurements at the BoulderAtmospheric Observatory (BAO) and our data obtained at PAO allow us to locate the source of benzeneenhancements between the two atmospheric observatories. Fugitive emissions of benzene from ONGoperations in the Platteville area are discussed as the most likely causes of enhanced benzene levels at PAO

    An online air-sea exchange model framework for trace gases powered by machine- learning

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    The ocean emits a wide range of trace gases, such as volatile organic compounds, or sulfur-,nitrogen-, and halogen-containing compounds. Many of these gases play critical roles in the atmosphere, including aerosol and cloud formation, tropospheric and stratospheric ozone budget, as well as the self-cleaning capacity of the atmosphere. Most chemistry-climate models use prescribed oceanic emissions (often derived from observations). These prescribed (offline) emissions generally do not respond to changes in local conditions. A process-level representation of the bi-directional oceanic emissions of trace gases remains challenging, mainly because the ocean biogeochemicalprocesses controlling the natural synthesis of these compounds in the seawater remain poorly understood. We present a new online air-sea exchange framework for the NCAR CESM2, with an observationally trained machine-learning emulator to couple the ocean biogeochemistry with the air-sea exchange. This machine-learning based approach so far has been tested for a number of important trace gases, including dimethyl sulfide (DMS), acetone, bromoform (CHBr 3 ), and dibromomethane (CH 2 Br 2 ), and the preliminary results are evaluated with observations around the globe. This new model framework is more skillful than the widely used top-down approaches for representing the seasonal/spatial variations and the annual means of atmospheric concentrations. The new approach improves the model predictability for the coupled earth system model, and can be used as a basis for investigating the future ocean emissions and feedbacks under climate change.Fil: Wang, Siyuan. National Center for Atmospheric Research; Estados UnidosFil: Emmons, Louisa K.. National Center for Atmospheric Research; Estados UnidosFil: Tilmes, Simone. National Center for Atmospheric Research; Estados UnidosFil: Kinnison, Douglas E.. National Center for Atmospheric Research; Estados UnidosFil: Long, Mateo C.. National Center for Atmospheric Research; Estados UnidosFil: Lamarque, Jean Francoise. National Center for Atmospheric Research; Estados UnidosFil: Apel, Eric C.. National Oceanic & Atmospheric Administration, Esrl; Estados UnidosFil: Hornbrook, Rebecca S.. Centro Nacional de Investigación Atmosférica; Estados UnidosFil: Montzka, Stephen. National Ocean And Atmospheric Administration; Estados UnidosFil: Saiz López, Alfonso. Consejo Superior de Investigaciones Científicas; EspañaFil: Fernandez, Rafael Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional de Mendoza; ArgentinaAmerican Geophysical Union Fall MeetingSan FranciscoEstados UnidosAmerican Geophysical Unio

    Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

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    Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

    Transgressive segregation reveals mechanisms of Arabidopsis immunity to Brassica-infecting races of white rust (Albugo candida)

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    Arabidopsis thaliana accessions are universally resistant at the adult leaf stage to white rust (Albugo candida) races that infect the crop species Brassica juncea and Brassica oleracea. We used transgressive segregation in recombinant inbred lines to test if this apparent species-wide (nonhost) resistance in A. thaliana is due to natural pyramiding of multiple Resistance (R) genes. We screened 593 inbred lines from an Arabidopsis multiparent advanced generation intercross (MAGIC) mapping population, derived from 19 resistant parental accessions, and identified two transgressive segregants that are susceptible to the pathogen. These were crossed to each MAGIC parent, and analysis of resulting F 2 progeny followed by positional cloning showed that resistance to an isolate of A. candida race 2 (Ac2V) can be explained in each accession by at least one of four genes encoding nucleotide-binding, leucine-rich repeat (NLR) immune receptors. An additional gene was identified that confers resistance to an isolate of A. candida race 9 (AcBoT) that infects B. oleracea. Thus, effector-triggered immunity conferred by distinct NLR-encoding genes in multiple A. thaliana accessions provides species-wide resistance to these crop pathogens

    Sources and Secondary Production of Organic Aerosols in the Northeastern United States during WINTER

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    Most intensive field studies investigating aerosols have been conducted in summer, and thus, wintertime aerosol sources and chemistry are comparatively poorly understood. An aerosol mass spectrometer was flown on the National Science Foundation/National Center for Atmospheric Research C‐130 during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) 2015 campaign in the northeast United States. The fraction of boundary layer submicron aerosol that was organic aerosol (OA) was about a factor of 2 smaller than during a 2011 summertime study in a similar region. However, the OA measured in WINTER was almost as oxidized as OA measured in several other studies in warmer months of the year. Fifty‐eight percent of the OA was oxygenated (secondary), and 42% was primary (POA). Biomass burning OA (likely from residential heating) was ubiquitous and accounted for 33% of the OA mass. Using nonvolatile POA, one of two default secondary OA (SOA) formulations in GEOS‐Chem (v10‐01) shows very large underpredictions of SOA and O/C (5×) and overprediction of POA (2×). We strongly recommend against using that formulation in future studies. Semivolatile POA, an alternative default in GEOS‐Chem, or a simplified parameterization (SIMPLE) were closer to the observations, although still with substantial differences. A case study of urban outflow from metropolitan New York City showed a consistent amount and normalized rate of added OA mass (due to SOA formation) compared to summer studies, although proceeding more slowly due to lower OH concentrations. A box model and SIMPLE perform similarly for WINTER as for Los Angeles, with an underprediction at ages \u3c6 hr, suggesting that fast chemistry might be missing from the models

    Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

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    Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1-2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements
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