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End date: 2019 × Start date: 2010 × Has files: Yes × Type: Text × Publisher: Göttingen : Copernicus GmbH × Subject: quantitative analysis ×

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Now showing 1 - 3 of 3
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    Water savings potentials of irrigation systems: Global simulation of processes and linkages
    (Göttingen : Copernicus GmbH, 2015) Jägermeyr, J.; Gerten, D.; Heinke, J.; Schaphoff, S.; Kummu, M.; Lucht, W.
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    Development of an online-coupled MARGA upgrade for the 2 h interval quantification of low-molecular-weight organic acids in the gas and particle phases
    (Göttingen : Copernicus GmbH, 2019) Stieger, B.; Spindler, G.; Van Pinxteren, D.; Grüner, A.; Wallasch, M.; Herrmann, H.
    A method is presented to quantify the lowmolecular- weight organic acids such as formic, acetic, propionic, butyric, pyruvic, glycolic, oxalic, malonic, succinic, malic, glutaric, and methanesulfonic acid in the atmospheric gas and particle phases, based on a combination of the Monitor for AeRosols and Gases in ambient Air (MARGA) and an additional ion chromatography (Compact IC) instrument. Therefore, every second hourly integrated MARGA gas and particle samples were collected and analyzed by the Compact IC, resulting in 12 values per day for each phase. A proper separation of the organic target acids was initially tackled by a laboratory IC optimization study, testing different separation columns, eluent compositions and eluent flow rates for both isocratic and gradient elution. Satisfactory resolution of all compounds was achieved using a gradient system with two coupled anion-exchange separation columns. Online pre-concentration with an enrichment factor of approximately 400 was achieved by solid-phase extraction consisting of a methacrylate-polymer-based sorbent with quaternary ammonium groups. The limits of detection of the method range between 0.5 ngm3 for malonate and 17.4 ngm3 for glutarate. Precisions are below 1.0 %, except for glycolate (2.9 %) and succinate (1.0 %). Comparisons of inorganic anions measured at the TROPOS research site in Melpitz, Germany, by the original MARGA and the additional Compact IC are in agreement with each other (R2 D0.95-0.99). Organic acid concentrations from May 2017 as an example period are presented. Monocarboxylic acids were dominant in the gas phase with mean concentrations of 306 ngm3 for acetic acid, followed by formic (199 ngm3), propionic (83 ngm3), pyruvic (76 ngm3), butyric (34 ngm3) and glycolic acid (32 ngm3). Particulate glycolate, oxalate and methanesulfonate were quantified with mean concentrations of 26, 31 and 30 ngm3, respectively. Elevated concentrations of gas-phase formic acid and particulate oxalate in the late afternoon indicate photochemical formation as a source.
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    Characterizing the evolution of climate networks
    (Göttingen : Copernicus GmbH, 2014) Tupikina, L.; Rehfeld, K.; Molkenthin, N.; Stolbova, V.; Marwan, N.; Kurths, J.
    Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, ErdA's-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks.