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We present a new mobile environmental reaction chamber for the simulation of the atmospheric aging of different emission sources without limitation from the instruments or facilities available at any single site. Photochemistry is simulated using a set of 40 UV lights (total power 4 KW). Characterisation of the emission spectrum of these lights shows that atmospheric aging of emissions may be simulated over a range of temperatures (−7 to 25 °C). A photolysis rate of NO<sub>2</sub>, <i>J</i><sub>NO<sub>2</sub></sub>, of (8.0 ± 0.7) × 10<sup>−3</sup> s<sup>−1</sup> was determined at 25 °C. We demonstrate the utility of this new system by presenting results on the aging (OH = 12 × 10<sup>6</sup> cm<sup>−3</sup> h) of emissions from a modern (Euro 5) gasoline car operated during a driving cycle (New European Driving Cycle, NEDC) on a chassis dynamometer in a vehicle test cell. Emissions from the entire NEDC were sampled and aged in the chamber. Total organic aerosol (OA; primary organic aerosol (POA) emission + secondary organic aerosol (SOA) formation) was (369.8–397.5)10<sup>−3</sup> g kg<sup>−1</sup> fuel, or (13.2–15.4) × 10<sup>−3</sup> g km<sup>−1</sup>, after aging, with aged OA/POA in the range 9–15. A thorough investigation of the composition of the gas phase emissions suggests that the observed SOA is from previously unconsidered precursors and processes. This large enhancement in particulate matter mass from gasoline vehicle aerosol emissions due to SOA formation, if it occurs across a wider range of gasoline vehicles, would have significant implications for our understanding of the contribution of on-road gasoline vehicles to ambient aerosols.
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X-ray photons emitted during solar flares cause ionization in the lower ionosphere (~60 to 100 km) in excess of what is expected to occur due to a quiet sun. Very low frequency (VLF) radio wave signals reflected from the D-region of the ionosphere are affected by this excess ionization. In this paper, we reproduce the deviation in VLF signal strength during solar flares by numerical modeling. We use GEANT4 Monte Carlo simulation code to compute the rate of ionization due to a M-class flare and a X-class flare. The output of the simulation is then used in a simplified ionospheric chemistry model to calculate the time variation of electron density at different altitudes in the D-region of the ionosphere. The resulting electron density variation profile is then self-consistently used in the LWPC code to obtain the time variation of the change in VLF signal. We did the modeling of the VLF signal along the NWC (Australia) to IERC/ICSP (India) propagation path and compared the results with observations. The agreement is found to be very satisfactory.
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Nutrification of the open ocean originates mainly from deposited aerosol in which the bio-avaliable iron is likely to be an important factor. The relatively insoluble iron in dust from arid soils becomes more soluble after atmospheric processing and, through its deposition in the ocean, could contribute to marine primary production. To numerically simulate the atmospheric route of iron from desert sources to sinks in the ocean, we developed a regional atmospheric dust-iron model that included parameterization of the transformation of iron to a soluble form caused by dust mineralogy, cloud processes and solar radiation. When compared with field data on the aerosol iron, which were collected during several Atlantic cruises, the results from the higher-resolution simulation experiments showed that the model was capable of reproducing the major observed patterns.
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In this study, a high resolution version of the Cambridge p-TOMCAT chemical transport model is used, along with measurement data from the 2008 NERC-funded Oxidant and Particle Photochemical Processes (OP3) project, to examine the potential impact of the expansion of oil palm in Borneo on atmospheric composition. Several model emission scenarios are run for the OP3 measurement period, incorporating emissions from both global datasets and local flux measurements. Using the OP3 observed isoprene fluxes and OH recycling chemistry in p-TOMCAT substantially improves the comparison between modelled and observed isoprene and OH concentrations relative to using MEGAN isoprene emissions without OH recycling. However, a similar improvement was also achieved without using HO<sub>x</sub> recycling, by fixing boundary layer isoprene concentrations over Borneo to follow the OP3 observations. An extreme hypothetical future scenario, in which all of Borneo is converted to oil palm plantation, assessed the sensitivity of the model to changes in isoprene and NO<sub>x</sub> emissions associated with land-use change. This scenario suggested a 70% upper limit on surface ozone increases resulting from land-use change on Borneo, excluding the impact of future changes in emissions elsewhere. Although the largest changes in this scenario occurred directly over Borneo, the model also calculated notable regional changes of O<sub>3</sub>, OH and other species downwind of Borneo and in the free troposphere.
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We investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (AOD) (factor 2–3 enhancement over wintertime AOD) is not present in surface mass concentrations (25–55% summertime enhancement). Goldstein et al. (2009) previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ∼35% of fine particulate matter (smaller than 2.5 μm in aerodynamic diameter, PM<sub>2.5</sub>) and exhibits similar seasonality to total surface PM<sub>2.5</sub>. The GEOS-Chem model generally reproduces these surface aerosol measurements, but underrepresents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing, we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer.
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Aerosol absorption properties are of high importance to assess aerosol impact on regional climate. This study presents an analysis of aerosol absorption products obtained over the Mediterranean basin or land stations in the region from multi-year ground-based AERONET observations with a focus on the Absorbing Aerosol Optical Depth (AAOD), Single Scattering Albedo (SSA) and their spectral dependence. The AAOD and Absorption Angström Exponent (AAE) dataset is composed of daily averaged AERONET level 2 data from a total of 22 Mediterranean stations having long time series, mainly under the influence of urban-industrial aerosols and/or soil dust. This dataset covers the 17-yr period 1996–2012 with most data being from 2003–2011 (~89% of level-2 AAOD data). Since AERONET level-2 absorption products require a high aerosol load (AOD at 440 nm > 0.4), which is most often related to the presence of desert dust, we also consider level-1.5 SSA data, despite their higher uncertainty, and filter out data with an Angström exponent < 1.0 in order to study absorption by carbonaceous aerosols. The SSA dataset includes AERONET level-2 products. Sun-photometer observations show that values of AAOD at 440 nm vary between 0.024 ± 0.01 (resp. 0.040 ± 0.01) and 0.050 ± 0.01 (0.055 ± 0.01) for urban (dusty) sites. Analysis shows that the Mediterranean urban-industrial aerosols appear "moderately" absorbing with values of SSA close to ~0.94–0.95 ± 0.04 (at 440 nm) in most cases except over the large cities of Rome and Athens, where aerosol appears more absorbing (SSA ~0.89–0.90 ± 0.04). The aerosol Absorption Angström Exponent (AAE, estimated using 440 and 870 nm) is found to be larger than 1 for most sites over the Mediterranean, a manifestation of mineral dust (iron) and/or brown carbon producing the observed absorption. AERONET level-2 sun-photometer data indicate a possible East-West gradient, with higher values over the eastern basin (AAE<sub>East</sub> = 1.39/AAE<sub>West</sub> = 1.33). The North-South AAE gradient is more pronounced, especially over the western basin. Our additional analysis of AERONET level-1.5 data also shows that organic absorbing aerosols significantly affect some Mediterranean sites. These results indicate that current climate models treating organics as nonabsorbing over the Mediterranean certainly underestimate the warming effect due to carbonaceous aerosols.
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We present a global data set of free tropospheric ozone–CO correlations with 2° × 2.5° spatial resolution from the Ozone Monitoring Instrument (OMI) and Atmospheric Infrared Sounder (AIRS) satellite instruments for each season of 2008. OMI and AIRS have near-daily global coverage of ozone and CO respectively and observe coincident scenes with similar vertical sensitivities. The resulting ozone–CO correlations are highly statistically significant (positive or negative) in most regions of the world, and are less noisy than previous satellite-based studies that used sparser data. Comparison with ozone–CO correlations and regression slopes (<i>d</i>O<sub>3</sub>/<i>d</i>CO) from MOZAIC (Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by in-service AIrbus airCraft) aircraft profiles shows good general agreement. We interpret the observed ozone–CO correlations with the GEOS (Goddard Earth Observing System)-Chem chemical transport model to infer constraints on ozone sources. Driving GEOS-Chem with different meteorological fields generally shows consistent ozone–CO correlation patterns, except in some tropical regions where the correlations are strongly sensitive to model transport error associated with deep convection. GEOS-Chem reproduces the general structure of the observed ozone–CO correlations and regression slopes, although there are some large regional discrepancies. We examine the model sensitivity of <i>d</i>O<sub>3</sub>/<i>d</i>CO to different ozone sources (combustion, biosphere, stratosphere, and lightning NO<sub>x</sub>) by correlating the ozone change from that source to CO from the standard simulation. The model reproduces the observed positive <i>d</i>O<sub>3</sub>/<i>d</i>CO in the extratropical Northern Hemisphere in spring–summer, driven by combustion sources. Stratospheric influence there is also associated with a positive <i>d</i>O<sub>3</sub>/<i>d</i>CO because of the interweaving of stratospheric downwelling with continental outflow. The well-known ozone maximum over the tropical South Atlantic is associated with negative <i>d</i>O<sub>3</sub>/<i>d</i>CO in the observations; this feature is reproduced in GEOS-Chem and supports a dominant contribution from lightning to the ozone maximum. A major model discrepancy is found over the northeastern Pacific in summer–fall where <i>d</i>O<sub>3</sub>/<i>d</i>CO is positive in the observations but negative in the model, for all ozone sources. We suggest that this reflects a model overestimate of lightning at northern midlatitudes combined with an underestimate of the East Asian CO source.
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We present the application of a global carbon cycle modeling system to the estimation of monthly regional CO<sub>2</sub> fluxes from the column-averaged mole fractions of CO<sub>2</sub> (<i>X</i><sub>CO<sub>2</sub></sub>) retrieved from spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to observed atmospheric CO<sub>2</sub> seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface <i>p</i>CO<sub>2</sub> distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO<sub>2</sub> fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from GOSAT FTS SWIR Level 2 <i>X</i><sub>CO<sub>2</sub></sub> retrievals (ver. 02.00) gridded to 5° × 5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO<sub>2</sub> data. Our result indicated that adding the GOSAT <i>X</i><sub>CO<sub>2</sub></sub> retrievals to the GLOBALVIEW data in the flux estimation brings changes to fluxes of tropics and other remote regions where the surface-based data are sparse. The uncertainties of these remote fluxes were reduced by as much as 60% through such addition. Optimized fluxes estimated for many of these regions, were brought closer to the prior fluxes by the addition of the GOSAT retrievals. In most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variabilities estimated with the component models.
