Abstract. Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash) into the atmosphere, as well as several gases, including sulphur dioxide (SO 2 ). These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO 2 plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellitebased SO 2 detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments.
On 4 June 2011 an eruption of the Chilean volcano complex Puyehue-Cordón Caulle injected large amounts of volcanic ash into the atmosphere and affected local life as well as hemisphere-wide air traffic. Observations of the Infrared Atmospheric Sounding Interferometer IASI flown on board of the MetOp satellite have been exploited to analyze the evolution of the ash plume around the Southern Hemisphere. A novel Singular Vector based retrieval methodology, originally developed for observation of desert dust over land and ocean, has been adapted to enable remote sensing of volcanic ash. <br><br> Since IASI observations in the 8–12 μm window are applied in the retrieval, the method is insensitive to solar illumination and therefore yields twice the observation rate of the ash plume evolution compared to solar backscatter methods from polar orbiting satellites. The retrieval scheme, the emission characteristics and the circumpolar transport of the ash are examined by means of a source-receptor analysis
Abstract. During the 2003 SAGE (Stratospheric Aerosol and Gas Experiment) III Ozone Loss and Validation Experiment (SOLVE) II, the fourteen-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was mounted on the NASA DC-8 aircraft and measured spectra of total and aerosol optical depth (TOD and AOD) during the sunlit portions of eight science flights. Values of ozone column content above the aircraft have been derived from the AATS-14 measurements by using a linear least squares method that exploits the differential ozone absorption in the seven AATS-14 channels located within the Chappuis band. We compare AATS-14 columnar ozone retrievals with temporally and spatially near-coincident measurements acquired by the SAGE III and the Polar Ozone and Aerosol Measurement (POAM) III satellite sensors during four solar occultation events observed by each satellite. RMS differences are 19 DU (7% of the AATS value) for AATS-SAGE and 10 DU (3% of the AATS value) for AATS-POAM. In these checks of consistency between AATS-14 and SAGE III or POAM III Correspondence to: J. M. Livingston (jlivingston@mail.arc.nasa.gov) ozone results, the AATS-14 analyses use airmass factors derived from the relative vertical profiles of ozone and aerosol extinction obtained by SAGE III or POAM III.
Chemical-transport models are a persuasive tool to predict and study air pollution on different temporal and spatial scales. However, due to the complexity of physics and chemistry of air pollutants' interactions and lack of precise input data, these models have uncertainties. In particular, most of the emission data have a too coarse resolution and are not appropriate for application in urban scale air quality modeling. In this study, a downscaling approach is utilized for emission data in order to improve the air pollutants concentration simulation over Munich city using the POLYPHEMUS/DLR chemistry-transport model (CTM). Traffic emission from the Bavarian Emission Kataster (EKATBY) 2004 anthropogenic emissions dataset with 2 km resolution is downscaled to 100 m with regard to the highresolution OpenStreetMap roads paths and areal emission sources are relocated on the most populated and active sites which have been determined from VIIRS NOAA satellite-derived night light data. In addition, the EEA CORINE 2012 land use data is implemented with 100 m grid resolution to improve e.g. the biogenic emissions. Regarding aerosols, the SIze REsolved Aerosol Module (SIREAM) for aerosol dynamic and the Secondary Organic Aerosol Model (SORGAM) are applied. The CTM is driven by WRF 3.5 meteorological forecasts. In order to have reliable simulations, the one-way grid nesting method with four domains is employed, where the coarsest domain covers Europe and the finest covers Munich city area.
Background Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. Objectives We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. Methods To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. Results In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 μg/m3 to 15.98 μg/m3. Conclusions Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.
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