17,051 research outputs found

    Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

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    Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km<sup>2</sup> spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Tropical broadleaf trees contribute almost half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which have a widespread distribution. The annual global isoprene emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene (440 to 660 Tg carbon) depending on the driving variables which include temperature, solar radiation, Leaf Area Index, and plant functional type. The global annual isoprene emission estimated using the standard driving variables is ~600 Tg isoprene. Differences in driving variables result in emission estimates that differ by more than a factor of three for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models, due to the substantial uncertainties in other model components, but at least some global models produce reasonable results when using isoprene emission distributions similar to MEGAN estimates. In addition, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and land-use) demonstrates the potential for large future changes in emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions

    Which processes drive observed variations of HCHO columns over India?

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    We interpret HCHO column variations observed by the Ozone Monitoring Instrument (OMI), aboard the NASA Aura satellite, over India during 2014 using the GEOS-Chem atmospheric chemistry and transport model. We use a nested version of the model with a horizontal resolution of approximately 25 km. HCHO columns are related to local emissions of volatile organic compounds (VOCs) with a spatial smearing that increases with the VOC lifetime. Over India, HCHO has biogenic, pyrogenic, and anthropogenic VOC sources. Using a 0-D photochemistry model, we find that isoprene has the largest molar yield of HCHO which is typically realized within a few hours. We also find that forested regions that neighbour major urban conurbations are exposed to high levels of nitrogen oxides. This results in depleted hydroxyl radical concentrations and a delay in the production of HCHO from isoprene oxidation. We find that propene is the only anthropogenic VOC emitted in major Indian cities that produces HCHO at a comparable (but slower) rate to isoprene. The GEOS-Chem model reproduces the broad-scale annual mean HCHO column distribution observed by OMI (<i>r</i> = 0.6), which is dominated by a distinctive meridional gradient in the northern half of the country, and by localized regions of high columns that coincide with forests. Major discrepancies are noted over the Indo-Gangetic Plain (IGP) and Delhi. We find that the model has more skill at reproducing observations during winter (JF) and pre-monsoon (MAM) months with Pearson correlations <i>r</i> &gt; 0.5 but with a positive model bias of  <mo form="infix">≃</mo> 1×10<sup>15</sup> molec cm<sup>−2</sup>. During the monsoon season (JJAS) we reproduce only a diffuse version of the observed meridional gradient (<i>r</i> = 0.4). We find that on a continental scale most of the HCHO column seasonal cycle is explained by monthly variations in surface temperature (<i>r</i> = 0.9), suggesting a role for biogenic VOCs, in agreement with the 0-D and GEOS-Chem model calculations. We also find that the seasonal cycle during 2014 is not significantly different from the 2008 to 2015 mean seasonal variation. There are two main loci for biomass burning (the states of Punjab and Haryana, and northeastern India), which we find makes a significant contribution (up to 1×10<sup>15</sup> molec cm<sup>−2</sup>) to observed HCHO columns only during March and April over northeastern India. The slow production of HCHO from propene oxidation results in a smeared hotspot over Delhi that we resolve only on an annual mean timescale by using a temporal oversampling method. Using a linear regression model to relate GEOS-Chem isoprene emissions to HCHO columns we infer seasonal isoprene emissions over two key forest regions from the OMI HCHO column data. We find that the a posteriori emissions are typically lower than the a priori emissions, with a much stronger reduction of emissions during the monsoon season. We find that this reduction in emissions during monsoon months coincides with a large drop in satellite observations of leaf phenology that recovers in post monsoon months. This may signal a forest-scale response to monsoon conditions

    Seasonal distribution and drivers of surface fine particulate matter and organic aerosol over the Indo-Gangetic Plain

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    The Indo-Gangetic Plain (IGP) is home to 9 % of the global population and is responsible for a large fraction of agricultural crop production in Pakistan, India, and Bangladesh. Levels of fine particulate matter (mean diameter &lt;2.5 µm, PM2.5) across the IGP often exceed human health recommendations, making cities across the IGP among the most polluted in the world. Seasonal changes in the physical environment over the IGP are dominated by the large-scale south Asian monsoon system that dictates the timing of agricultural planting and harvesting. We use the WRF-Chem model to study the seasonal anthropogenic, pyrogenic, and biogenic influences on fine particulate matter and its constituent organic aerosol (OA) over the IGP that straddles Pakistan, India, and Bangladesh during 2017–2018. We find that surface air quality during pre-monsoon (March–May) and monsoon (June–September) seasons is better than during post-monsoon (October–December) and winter (January–February) seasons, but all seasonal mean values of PM2.5 still exceed the recommended levels, so that air pollution is a year-round problem. Anthropogenic emissions influence the magnitude and distribution of PM2.5 and OA throughout the year, especially over urban sites, while pyrogenic emissions result in localised contributions over the central and upper parts of IGP in all non-monsoonal seasons, with the highest impact during post-monsoon seasons that correspond to the post-harvest season in the agricultural calendar. Biogenic emissions play an important role in the magnitude and distribution of PM2.5 and OA during the monsoon season, and they show a substantial contribution to secondary OA (SOA), particularly over the lower IGP. We find that the OA contribution to PM2.5 is significant in all four seasons (17 %–30 %), with primary OA generally representing the larger fractional contribution. We find that the volatility distribution of SOA is driven mainly by the mean total OA loading and the washout of aerosols and gas-phase aerosol precursors that result in SOA being less volatile during the pre-monsoon and monsoon season than during the post-monsoon and winter seasons.</p

    Mapping isoprene emissions over North America using formaldehyde column observations from space

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    We present a methodology for deriving emissions of volatile organic compounds (VOC) using space-based column observations of formaldehyde (HCHO) and apply it to data from the Global Ozone Monitoring Experiment (GOME) satellite instrument over North America during July 1996. The HCHO column is related to local VOC emissions, with a spatial smearing that increases with the VOC lifetime. Isoprene is the dominant HCHO precursor over North America in summer, and its lifetime (≃1 hour) is sufficiently short that the smearing can be neglected. We use the Goddard Earth Observing System global 3-D model of tropospheric chemistry (GEOS-CHEM) to derive the relationship between isoprene emissions and HCHO columns over North America and use these relationships to convert the GOME HCHO columns to isoprene emissions. We also use the GEOS-CHEM model as an intermediary to validate the GOME HCHO column measurements by comparison with in situ observations. The GEOS-CHEM model including the Global Emissions Inventory Activity (GEIA) isoprene emission inventory provides a good simulation of both the GOME data (r2 = 0.69, n = 756, bias = +11%) and the in situ summertime HCHO measurements over North America (r2 = 0.47, n = 10, bias = −3%). The GOME observations show high values over regions of known high isoprene emissions and a day-to-day variability that is consistent with the temperature dependence of isoprene emission. Isoprene emissions inferred from the GOME data are 20% less than GEIA on average over North America and twice those from the U.S. EPA Biogenic Emissions Inventory System (BEIS2) inventory. The GOME isoprene inventory when implemented in the GEOS-CHEM model provides a better simulation of the HCHO in situ measurements than either GEIA or BEIS2 (r2 = 0.71, n = 10, bias = −10%)

    ERISA Preemption Doctrine as Health Policy

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    Irradiated Interfaces in the Ara OB1, Carina, Eagle Nebula, and Cyg OB2 Massive Star Formation Regions

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    Regions of massive star formation offer some of the best and most easily-observed examples of radiation hydrodynamics. Boundaries where fully-ionized H II regions transition to neutral/molecular photodissociation regions (PDRs) are of particular interest because marked temperature and density contrasts across the boundaries lead to evaporative flows and fluid dynamical instabilities that can evolve into spectacular pillar-like structures. When detached from their parent clouds, pillars become ionized globules that often harbor one or more young stars. H2 molecules at the interface between a PDR and an H II region absorb ultraviolet light from massive stars, and the resulting fluoresced infrared emission lines are an ideal way to trace this boundary independent of obscuring dust. This paper presents H2 images of four regions of massive star formation that illustrate different types of PDR boundaries. The Ara OB1 star formation region contains a striking long wall that has several wavy structures which are present in H2, but the emission is not particularly bright because the ambient UV fluxes are relatively low. In contrast, the Carina star formation region shows strong H2 fluorescence both along curved walls and at the edges of spectacular pillars that in some cases have become detached from their parent clouds. The less-spectacular but more well-known Eagle Nebula has two regions that have strong fluorescence in addition to its pillars. While somewhat older than the other regions, Cyg OB2 has the highest number of massive stars of the regions surveyed and contains many isolated, fluoresced globules that have head-tail morphologies which point towards the sources of ionizing radiation. These images provide a collection of potential astrophysical analogs that may relate to ablated interfaces observed in laser experiments of radiation hydrodynamics

    Gravitational Laser Back-Scattering

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    A possible way of producing gravitons in the laboratory is investigated. We evaluate the cross section electron + photon \rightarrow electron + graviton in the framework of linearized gravitation, and analyse this reaction considering the photon coming either from a laser beam or from a Compton back-scattering process.Comment: 11 pages, 2 figures (available upon request), RevTeX, IFT-P.03/9

    Relativistic Particle-In-Cell Simulation Studies of Prompt and Early Afterglows from GRBs

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    Nonthermal radiation observed from astrophysical systems containing relativistic jets and shocks e.g. gamma-ray bursts (GRBs) active galactic nuclei (AGNs) and microquasars commonly exhibit power-law emission spectra. Recent PIC simulations of relativistic electron-ion (or electron-positron) jets injected into a stationary medium show that particle acceleration occurs within the downstream jet. In collisionless relativistic shocks particle (electron, positron and ion) acceleration is due to plasma waves and their associated instabilities (e.g. the Weibel (filamentation) instability) created in the shock region. The simulations show that the Weibel instability is responsible for generating and amplifying highly non-uniform small-scale magnetic fields. These fields contribute to the electron's transverse deflection behind the jet head. The resulting ``jitter'' radiation from deflected electrons has different properties compared to synchrotron radiation which assumes a uniform magnetic field. Jitter radiation may be important for understanding the complex time evolution and/or spectra in gamma-ray bursts, relativistic jets in general and supernova remnants.Comment: 19 pages,7 figures, contributed talk at Seventh European Workshop on Collisionless Shocks, Paris, 7- 9 November 2007. High resolution version can be obtained at http://gammaray.nsstc.nasa.gov/~nishikawa/shockws07.pd
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