69 research outputs found

    Asset pricing under uncertainty about shock propagation : [version 18 november 2013]

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    We analyze the equilibrium in a two-tree (sector) economy with two regimes. The output of each tree is driven by a jump-diffusion process, and a downward jump in one sector of the economy can (but need not) trigger a shift to a regime where the likelihood of future jumps is generally higher. Furthermore, the true regime is unobservable, so that the representative Epstein-Zin investor has to extract the probability of being in a certain regime from the data. These two channels help us to match the stylized facts of countercyclical and excessive return volatilities and correlations between sectors. Moreover, the model reproduces the predictability of stock returns in the data without generating consumption growth predictability. The uncertainty about the state also reduces the slope of the term structure of equity. We document that heterogeneity between the two sectors with respect to shock propagation risk can lead to highly persistent aggregate price-dividend ratios. Finally, the possibility of jumps in one sector triggering higher overall jump probabilities boosts jump risk premia while uncertainty about the regime is the reason for sizeable diffusive risk premia

    Long Term Aerosol Composition Measurements at the CESAR Tower at Cabauw, NL

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    In this work, intensive mass spectrometric measurements of PM1 aerosol size distribution and chemical composition were performed at Cabauw, the Netherlands, using a High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS), an Aerosol Chemical Speciation Monitor (ACSM), a Thermal-Desorption Proton-Transfer-Reaction Time-of- Flight Mass Spectrometer (TD-PTR-ToF-MS), and supplementary instruments. The field campaigns took place in November 2011, during May to July 2012 (both periods with the AMS and the collocated TD-PTR-MS) and between July 2012 and June 2013 (ACSM). Average total aerosol mass loadings of 9.26 μg m−3, 6.40 μg m−3, and 9.50 μg m−3 were observed during the campaign periods, respectively. Within the ACSM campaign, 12 exceedances of the PM2.5 daily mean limit, established by the World Health Organization (WHO), were observed. In almost all campaigns, the highest contribution to total mass were seen by nitrate (21% - 39 %, mainly as ammonium nitrate) and organic compounds (23% - 33 %) on average, especially in periods with relatively high total mass loadings (> 25 μg m−3). The presence of organic nitrate and excess ammonium indicate the high impact of nitrogen containing compounds on the formation and composition of ambient aerosols in Cabauw. Factor analysis was applied to organic aerosols (OA) for all data sets. AMS and ACSM data showed that secondary organic aerosols (SOA, 53% - 84% average contribution to OA) dominated the organic fraction throughout all campaigns. A factor which is attributed to humic-like substances (HULIS) was identified as a highly oxidised background aerosol in Cabauw. Primary organic aerosols (POA) were mainly emitted by traffic (8% - 35% average contribution to OA) and biomass burning (8% - 23 %). A first approach of the application of factor analysis to TD-PTR-MS data was performed in this work, showing good agreement with factors obtained from the collocated AMS. The dominance of secondary aerosol in PM1 shows the high importance of atmospheric ageing processes of aerosol concentration at this rural site. Due to the large secondary fraction of aerosol reduction of particulate mass is challenging on a local scale

    Data Descriptor : Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

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    Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.Peer reviewe
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