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Titel Organohalogen emissions from saline environments – spatial extrapolation using remote sensing as most promising tool
VerfasserIn K. Kotte, F. Löw, S. G. Huber, T. Krause, I. Mulder, H. F. Schöler
Medientyp Artikel
Sprache Englisch
ISSN 1726-4170
Digitales Dokument URL
Erschienen In: Biogeosciences ; 9, no. 3 ; Nr. 9, no. 3 (2012-03-29), S.1225-1235
Datensatznummer 250006857
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/bg-9-1225-2012.pdf
 
Zusammenfassung
Due to their negative water budget most recent semi-/arid regions are characterized by vast evaporates (salt lakes and salty soils). We recently identified those hyper-saline environments as additional sources for a multitude of volatile halogenated organohalogens (VOX). These compounds can affect the ozone layer of the stratosphere and play a key role in the production of aerosols. A remote sensing based analysis was performed in the Southern Aral Sea basin, providing information of major soil types as well as their extent and spatial and temporal evolution. VOX production has been determined in dry and moist soil samples after 24 h. Several C1- and C2 organohalogens have been found in hyper-saline topsoil profiles, including CH3Cl, CH3Br, CHBr3 and CHCl3. The range of organohalogens also includes trans-1,2-dichloroethene (DCE), which is reported here to be produced naturally for the first time. Using MODIS time series and supervised image classification a daily production rate for DCE has been calculated for the 15 000 km2 ranging research area in the southern Aralkum. The applied laboratory setup simulates a short-term change in climatic conditions, starting from dried-out saline soil that is instantly humidified during rain events or flooding. It describes the general VOX production potential, but allows only for a rough estimation of resulting emission loads. VOX emissions are expected to increase in the future since the area of salt affected soils is expanding due to the regressing Aral Sea. Opportunities, limits and requirements of satellite based rapid change detection and salt classification are discussed.
 
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