1. Monitoring CO, PM 2.5, CO 2 from low intensity fires for the development of modeling tools for predicting smoke dispersion John Hom 1, Greg Starr 2, Robert Mitchell 3, Matthew Patterson 1, Andres Baron 3, Ross Atkinson 3, and Matt McCorvey 3 1 USFS Northern Research Station, 2 U of Alabama, Dept. of Biological Science, 3 Joseph W. Jones Ecological Research Center, Forest Ecology II Lab Introduction This field study provides validation and support for the development of modeling tools for predicting smoke dispersion from low-intensity fires. Smoke models rely on measurements of PM 2.5, carbon monoxide (CO), and CO 2 as analogs for smoke. The approach is a three year modeling and field validation study using tall towers (10m, 20m, 30m), and short towers (3m), including the Eddy Covariance Towers at the Jones Center, inside and outside of fire perimeter equipped with smoke sensors, temperature, RH sensors and sonic anemometers. We will give results from field tests, comparing the performance of low cost CO monitors, modified smoke monitors, and CO 2 analyzers against reference PM 2.5 monitors at prescribed fires in the Joseph W. Jones Ecological Research Center at Ichauway, located in the Coastal Plain of southwestern Georgia. Smoke monitoring Smoke models rely on measurements such as carbon monoxide (CO), PM 2.5, and CO 2 as analogs for smoke. Typically PM 2.5 monitors are used to monitor smoke and particulates. Placing air quality PM 2.5 monitors within the fire would be risky and prohibitively expensive. An array of inexpensive, expendable, fast response and low power CO sensors, based on carbon monoxide transducers from residential alarms was designed and built to provide a spatial grid over the wide range of CO concentrations (up to 1000 ppm) expected within the fire. The CO sensors, based on the Figaro TGS5042 transducer, was designed and built with a signal conditioning amplifier board (Data Design Group, La Jolla) Each is individually calibrated using CO reference gas (Scott Gas). Objective The purpose of this study is to monitor low level smoke from prescribed burn: wind turbulence, temperature profile, PM 2.5 for validation of smoke transport models. Similar datasets will be generated and shared for evaluating and validating different modeling tools Inexpensive Figaro CO sensors show good response and a wide range. As passive monitors, they must be in close proximity to the smoke plume, as seen in difference in response with position on 30 m tower. dataRam PM 2.5 monitors on perimeter show good sensitivity farther away from plume (ug/m3), with similar response as the inexpensive CO sensors The Li-Cor 840 CO 2 analyzer (black) with active (pump) sampling corresponded well with CO and temperature peaks. The inexpensive DCS CO 2 monitors (blue) had an embedded auto calibration function which complicated observations, as seen in the changing baseline after the fire. Conclusions Overall, results from the array of inexpensive CO and PM sensors within the burn yielded good results compared to the more expensive reference air quality PM 2.5 monitors, with the ability to show the spatial and temporal dynamics within the burn. PM 2.5 monitoring showed a direct effect of distance from the smoke to the concentration of particles thru time, correlated with wind direction and speed. Compatible monitoring strategies will allow for easier scientific analyses and comparisons. PM 2.5, CO, CO 2, Thermocouple profile of 30m, sonic anemometer and net radiometer located at the Baker Woods Eddy Covariance Tower. PM 2.5, CO and UCB particulate monitors co-located at NC and NJ smoke studies to correlate PM 2.5 with less expensive sensors that can be placed inside the burn. Photography courtesy of A. Baron Rxburn at Dubignion unit, Feb 18 th, 2013. Photography courtesy of M. Patterson Rxburn at Baker Woods, Mar 15 th, 2013, and Red Dirt, Feb 15 th, 2013. Photography courtesy of R. Atkinson, and M. Patterson dataRAM 2.5PM sensor, registering at Red Dirt Rxburn, Feb 15 th, 2013. Photography courtesy of M. Patterson Instrumentation Three 30m instrumented Eddy Covariance Towers (Baker Woods, Red Dirt, Dubignion) Six-PM 2.5 monitors: two Met EBAM, four dataRAM per tower Six soil thermocouples per tower Ten Temperature/RH probes on profile Three RMY Sonic Anemometers at 3m, per tower One NETRAD at 3m, per tower Three Smoke alarms (CO) per tower. One at 3m, one at 1om, and one at 30m LI-840/820 CO 2 sensor at the base of each tower Three CS-3000 dataloggers, one at each tower One thermocouple profile per tower: underground 20cm, 2cm, ground level, 1m above, 12m above, 16m above, 20m above, 25m above, and 30m above Collins Pond Block (100ha approx.) Mean suface wind direction This block is E from the BW tower site. Rxburn technique used: Spot fire. Burn was started using a backfire running W-E, with a safety line running S- N. Fire lines were established inside the unit, following a W-E direction. The most evident smoke that reached the dataRAMs occurred from 10:30am until 10:45am (mainly due to the backfire line running W-E Results Sampling design (Collins Pond block Rx burn monitoring) UCB monitor (EME Systems) modified smoke alarm photocell (mv) shows broad response, similar to CO 2 monitor. It has been well correlated with other CO and with PM 2.5 monitors in the literature.