Detecting anomalous CO 2 flux using space borne spectroscopy Prasun K. Gangopadhyay *, Freek van der Meer, Paul van Dijk ESA Department, International Institute for Geo-Information Science and Earth Observation (ITC), Hengelostraat, P.O. Box 6, 7500 AA Enschede, The Netherlands 1. Introduction The earth’s atmospheric CO 2 concentration has varied over the long time-scale resolved by several geochemical processes such as sedimentation of organic materials, wreathing of silicate rock and volcanic activity (Berner, 1993, 1997). It has observed from Vostok ice core samples that cover past four glacial/interglacial cycles (420 kyear), atmospheric CO 2 concentration was low during glacial period (180 ppmv) and higher in interglacial period (300 ppmv) (Petit et al., 1999; Fischer et al., 1999). Several researchers suggested that the concentration of CO 2 in the atmosphere has unambiguously increased (from 350 to 375 ppmv) since the industrial revolution (Keeling and Whorf, 1999; Etheridge et al., 1996). Except industrialization, few geo-natural events such as volcanic activity, leakage from hydrocarbon reservoir and natural occurrence of coalfires could have significant contribution in global CO 2 budget. The observational foundation of global carbon studies in the National Oceanic and Atmospheric Administration Climate Mon- itoring and Diagnostic Laboratory cooperate air sampling network of worldwide measurements for carbon cycle GHGs (Conway et al., 1994). Approximately 56 fixed base observatories complemented with ship and aircraft are distributed over the globe. Their in situ measurements are quite accurate but for assessing the global process their distribution is very limited over space and time. Based on this network the observed uncertainty of the global carbon budget is 2–3 GtC year 1 (Tans et al., 1990; Rayner and O’Brien, 2001; Gurney et al., 2002). Numerous instruments such as Fourier transform spectro- meter, lasers, hyperspectral sensors are being used, boarded on air/ satellite-based platforms for estimation of different atmospheric gases with a proper analysis of atmospheric spectra and reliable retrievals. Few models (such as band rationing) are developed to retrieve columnar water vapour data from hyperspectral remote sensing data such as AVIRIS and have been standardized (Gao and International Journal of Applied Earth Observation and Geoinformation 11 (2009) 1–7 ARTICLE INFO Article history: Received 18 August 2007 Accepted 27 March 2008 Keywords: CO 2 emission Coalfire FASCOD Hyperion ABSTRACT Over the time-scale, earth’s atmospheric CO 2 concentration has varied and that is mostly determined by balance among the geochemical processes including burial of organic carbon in sediments, silicate rock weathering and volcanic activity. The best recorded atmospheric CO 2 variability is derived from Vostok ice core that records last four glacial/interglacial cycles. The present CO 2 concentration of earth’s atmosphere has exceeded far that it was predicted from the ice core data. Other than rapid industrialization and urbanization since last century, geo-natural hazards such as volcanic activity, leakage from hydrocarbon reservoirs and spontaneous combustion of coal contribute a considerable amount of CO 2 to the atmosphere. Spontaneous combustion of coal is common occurrence in most coal producing countries and sometimes it could be in an enormous scale. Remote sensing has already proved to be a significant tool in coalfire identification and monitoring studies. However, coalfire related CO 2 quantification from remote sensing data has not endeavoured yet by scientific communities because of low spectral resolution of commercially available remote sensing data and relatively sparse CO 2 plume than other geological hazards like volcanic activity. The present research has attempted two methods to identify the CO 2 flux emitted from coalfires in a coalmining region in north China. Firstly, a band rationing method was used for column atmospheric retrieval of CO 2 and secondly atmospheric models were simulated in fast atmospheric signature code (FASCOD) to understand the local radiation transport and then the model was implemented with the inputs from hyperspectral remote sensing data. It was observed that retrieval of columnar abundance of CO 2 with the band rationing method is faster as less simulation required in FASCOD. Alternatively, the inversion model could retrieve CO 2 concentration from a (certain) source because it excludes the uncertainties in the higher altitude. ß 2008 Elsevier B.V. All rights reserved. * Corresponding author. Tel.: +31 53 4874248; fax: +31 53 4874336. E-mail addresses: prasun@itc.nl (P.K. Gangopadhyay), vdmeer@itc.nl (F. van der Meer), vandijk@itc.nl (P. van Dijk). Contents lists available at ScienceDirect International Journal of Applied Earth Observation and Geoinformation journal homepage: www.elsevier.com/locate/jag 0303-2434/$ – see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jag.2008.03.004