ACKNOWLEDGEMENTS We are grateful to the MOPITT team, especially the groups at University of Toronto and the National Center for Atmospheric Research (NCAR), for their many years' work on the CO data. Daniel Ziskin kindly provided the MOPITT raw data in ASCII format. AVHRR data from Canada Centre for Remote Sensing (CCRS) (Z. Li, R. Fraser, J. Cihlar, and J. Jin) are greatly appreciated. For more information, please contact: Prof. J. R. Drummond Jane Liu Jane Liu and James R. Drummond Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, Canada M5S 1A7 MOPITT DETECTION OF CARBON MONOXIDE EMITTED FROM BIOMASS BURNING: A CASE STUDY  This study shows that MOPITT can detect the CO emission from biomass burning. The detected CO increases with the size of fires. A plume of CO is observable in the CO image when the fire size is over 40 km 2, i. e., 8% of a MOPITT pixel. The relative CO increase in this case can reach as high as 26%.  The spatial CO distribution during the fire events closely agrees with other data, such as wind direction, the location and density of hotspots and the burned areas.  MOPITT provides snapshots on global CO status at discrete times. More work is needed to interpret the snapshots as useful information. The work will benefit from using combined knowledge and approaches in multiple disciplines and data from different sources. RESULTS AND DISCUSSION DATA PROCESSING CONCLUSION MOPITT CO DATA DAILY IMAGES OVER THE FIRE AREA THREE-DAY COMPOSITES FILLING GAPS IN THE COMPOSITES MOPITT DETECTED CO EMISSION FROM BIOMASS BURNING DAILY AVHRR FIRE IMAGES AT 1KM AND LCC PROJECTION RESAMPLE THE IMAGES TO MATCH MOPITT DATA SPATIALLY THREE-DAY COMPOSITES Both CO and hotspot data were extracted for the area from the corresponding database from July 16 to September 9, The image size is 70 pixels by 70 lines at 0.25 degree interval. The georeference are 55  N and  W for the upper left pixel and 37.5  N and 100  W for the lower right pixel. The major land cover types in the area are coniferous forest, grassland, cropland, and barren land. Fig. 1 Total number of hotspots and maximum number of hotspots in a pixel (0.25 * 0.25 degree) in the images for the study area from July 16 to September 9, The development of the fires from emergence to diminishment in the study area can be viewed in Fig. 1, with the number of detected hotspots in the 3- day fire composite images from July 16 to September 9, Fig. 2 Examples of MOPITT detected CO emission from severe fires (lower part), compared to that from less severe fires (upper part). Distributions of hotspots for the same periods and area are displayed on the right side. Fig. 3 Wind field on August 25, 2000 at 500 mb (after NOAA Air Resource Laboratory, 2000). Fig. 4 Total burned area in year 2000 for the study area. (km 2 ) The CO emitted from these fires was detected by MOPITT. Fig. 2 shows examples of CO distribution in August 25-27, 2000 with severe fires (lower part), versus that in July 22-24, 2000 with less severe fires (upper part). The locations and density of hotspots during the same periods are displayed on the panels on the right side. Note with severe fires, the maximum number of hotspots reached 50 counts per pixel and a tilted V shape plume on the CO image expands toward the northeast. Fig. 5 The gap-filled images of CO distribution from 16 July to 9 September Fig. 6 Relative change of CO from the background compared to the total number of hotspots from July 16 to September 9, Wind field data were examined at surface, 850 mb, 500 mb and 200 mb. The typical wind field on August 25, 2000 with severe fires is showed in Fig. 3. The wind direction, the location of maximum hotspots, and the spatial CO pattern were closely correlated. The location of the fires in those days also matches the ground data of burned areas (Fig. 4). Total area burned is about 1,500 km 2. The vegetation where the maximum hotspots occurred was coniferous forest, as found in a land cover map. To quantify the CO emission from the fire events, an attempt was made to fill the gaps in the images, shown above. The missed CO values were interpolated with the nearest data points in all 8 directions weighted inversely by their corresponding distances, for all the 3-day composites from 16 July to September 9, 2000 (Fig. 5). Then, the change of CO content from the background was calculated for each composite, taking the CO content in the composite of September 4-6 as background level (Fig. 6). The CO content was close to background at the beginning of the period, it increased and decreased, and peaked on the composites of August 1-4, August 16-18, and August After these, the CO magnitude subsided to the background level. The relative change of CO reached as high as 26% on August The change of CO was closely related to the number of hotspots most of the time, especially from August 10 to September 9, except for the period from July 25 to August 9, The exception may be due to that CO was transported from other locations outside the images. It appears that MOPITT can satisfactorily detect CO released The study area covers 2.65 *10 6 km 2, with a center close to the joint borders of Idaho, Montana, and Wyoming in the United States (  W and  N). A series of large fires were detected in the area from the satellite in the summer of STUDY AREA INTRODUCTION The EOS Measurements Of Pollution In The Troposphere (MOPITT) is the first free-flying instrument for global measurement of carbon monoxide (CO) in the atmosphere from space. Because biomass burning is one of the major sources of CO to the atmosphere, the capacity of MOPITT to detect CO released from biomass burning is important and is the subject of this investigation. A study area with a series of fire events in the year of 2000 in the northwest United States is selected. Fire data, detected with spaceborne Advanced Very High Resolution Radiometer (AVHRR), were acquired and processed to spatially and temporally match the CO data. In this poster, some preliminary results from this case study are presented to demonstrate the usefulness and limitations of MOPITT for detecting CO emission from biomass burning. from active fires, if the fire size is over 20 km 2 and covered with dense vegetation; the burning time closely matches with MOPITT overpass time; and the sky is not blocked by clouds. Future work will combine MOPITT data with meteorological data, ground measurement to resolve absolute CO emission from biomass burning, using knowledge and approaches in multiple disciplines, such as remote sensing and atmospheric chemistry modeling.