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    Contributions of transported Prudhoe Bay oil field emissions to the aerosol population in Utqiaġvik, Alaska
    (Katlenburg-Lindau : EGU, 2017) Gunsch, Matthew J.; Kirpes, Rachel M.; Kolesar, Katheryn R.; Barrett, Tate E.; China, Swarup; Sheesley, Rebecca J.; Laskin, Alexander; Wiedensohler, Alfred; Tuch, Thomas; Pratt, Kerri A.
    Loss of sea ice is opening the Arctic to increasing development involving oil and gas extraction and shipping. Given the significant impacts of absorbing aerosol and secondary aerosol precursors emitted within the rapidly warming Arctic region, it is necessary to characterize local anthropogenic aerosol sources and compare to natural conditions. From August to September 2015 in Utqiaġvik (Barrow), AK, the chemical composition of individual atmospheric particles was measured by computer-controlled scanning electron microscopy with energy-dispersive X-ray spectroscopy (0.13-4 μm projected area diameter) and real-time single-particle mass spectrometry (0.2-1.5 μm vacuum aerodynamic diameter). During periods influenced by the Arctic Ocean (70 % of the study), our results show that fresh sea spray aerosol contributed ∼ 20 %, by number, of particles between 0.13 and 0.4 μm, 40-70 % between 0.4 and 1 μm, and 80-100 % between 1 and 4 μm particles. In contrast, for periods influenced by emissions from Prudhoe Bay (10 % of the study), the third largest oil field in North America, there was a strong influence from submicron (0.13-1 μm) combustion-derived particles (20-50 % organic carbon, by number; 5-10 % soot by number). While sea spray aerosol still comprised a large fraction of particles (90 % by number from 1 to 4 μm) detected under Prudhoe Bay influence, these particles were internally mixed with sulfate and nitrate indicative of aging processes during transport. In addition, the overall mode of the particle size number distribution shifted from 76 nm during Arctic Ocean influence to 27 nm during Prudhoe Bay influence, with particle concentrations increasing from 130 to 920 cm-3 due to transported particle emissions from the oil fields. The increased contributions of carbonaceous combustion products and partially aged sea spray aerosol should be considered in future Arctic atmospheric composition and climate simulations.
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    Simulating the formation of carbonaceous aerosol in a European Megacity (Paris) during the MEGAPOLI summer and winter campaigns
    (München : European Geopyhsical Union, 2016) Fountoukis, Christos; Megaritis, Athanasios G.; Skyllakou, Ksakousti; Charalampidis, Panagiotis E.; van der Gon, Hugo A.C.Denier; Crippa, Monica; Prévôt, André S.H.; Fachinger, Friederike; Wiedensohler, Alfred; Pilinis, Christodoulos; Pandis, Spyros N.
    We use a three-dimensional regional chemical transport model (PMCAMx) with high grid resolution and high-resolution emissions (4 × 4 km2) over the Paris greater area to simulate the formation of carbonaceous aerosol during a summer (July 2009) and a winter (January/February 2010) period as part of the MEGAPOLI (megacities: emissions, urban, regional, and global atmospheric pollution and climate effects, and Integrated tools for assessment and mitigation) campaigns. Model predictions of carbonaceous aerosol are compared against Aerodyne aerosol mass spectrometer and black carbon (BC) high time resolution measurements from three ground sites. PMCAMx predicts BC concentrations reasonably well reproducing the majority (70 %) of the hourly data within a factor of two during both periods. The agreement for the summertime secondary organic aerosol (OA) concentrations is also encouraging (mean bias = 0.1 µg m−3) during a photochemically intense period. The model tends to underpredict the summertime primary OA concentrations in the Paris greater area (by approximately 0.8 µg m−3) mainly due to missing primary OA emissions from cooking activities. The total cooking emissions are estimated to be approximately 80 mg d−1 per capita and have a distinct diurnal profile in which 50 % of the daily cooking OA is emitted during lunch time (12:00–14:00 LT) and 20 % during dinner time (20:00–22:00 LT). Results also show a large underestimation of secondary OA in the Paris greater area during wintertime (mean bias =  −2.3 µg m−3) pointing towards a secondary OA formation process during low photochemical activity periods that is not simulated in the model.
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    Regional modelling of Saharan dust and biomass-burning smoke, Part I: Model description and evaluation
    (Milton Park : Taylor & Francis, 2017) Heinold, Bernd; Tegen, Ina; Schepanski, Kerstin; Tesche, Matthias; Esselborn, Michael; Freudenthaler, Volker; Gross, Silke; Kandler, Konrad; Knippertz, Peter; Müller, Detlef; Schladitz, Alexander; Toledano, Carlos; Weinzierl, Bernadett; Ansmann, Albert; Althausen, Dietrich; Müller, Thomas; Petzold, Andreas; Wiedensohler, Alfred
    The spatio-temporal evolution of the Saharan dust and biomass-burning plume during the SAMUM-2 field campaign in January and February 2008 is simulated at 28 km horizontal resolution with the regional model-system COSMOMUSCAT. The model performance is thoroughly tested using routine ground-based and space-borne remote sensing and local field measurements. Good agreement with the observations is found in many cases regarding transport patterns, aerosol optical thicknesses and the ratio of dust to smoke aerosol. The model also captures major features of the complex aerosol layering. Nevertheless, discrepancies in the modelled aerosol distribution occur, which are analysed in detail. The dry synoptic dynamics controlling dust uplift and transport during the dry season are well described by the model, but surface wind peaks associated with the breakdown of nocturnal low-level jets are not always reproduced. Thus, a strong dust outbreak is underestimated. While dust emission modelling is a priori more challenging, since strength and placement of dust sources depend on on-line computed winds, considerable inaccuracies also arise in observation-based estimates of biomass-burning emissions. They are caused by cloud and spatial errors of satellite fire products and uncertainties in fire emission parameters, and can lead to unrealistic model results of smoke transport.