J4.8
MAPIT: An airborne system for urban-scale environmental monitoring

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Wednesday, 1 February 2006: 11:00 AM
MAPIT: An airborne system for urban-scale environmental monitoring
A312 (Georgia World Congress Center)
Randolph J. Evans, Siemens Energy, Inc., Orlando, FL; and J. G. Dreher, J. Manobianco, and M. Adams

Presentation PDF (144.4 kB)

This paper highlights a system of wireless, in situ, buoyant airborne probes designed for urban-scale environmental monitoring. The Mobile Airborne Probes for Identification and Tracking (MAPIT) system will feature constant altitude probes which are spherical or disk shaped and filled with lighter-than-air gas, such as helium, to provide buoyancy. Initial prototypes assembled with commercial-off-the-shelf components will have a total mass of approximately 70 gm and diameter of 50 cm. The probes will measure pressure, temperature, humidity, wind velocity, and possibly ozone, carbon dioxide, or other trace gases. While MAPIT will likely complement current and even next-generation in situ sensors and remote sensing platforms, the system has the capability to provide a 100-fold increase in three-dimensional planetary boundary layer observations especially in urban environments.

A modeling study is in progress to assess the impact of assimilating high spatial and temporal resolution probe measurements for dispersion predictions of a tracer gas release. The release of probes is simulated using the Advanced Regional Prediction System (ARPS) at 2-km grid spacing centered over Salt Lake City during the URBAN 2000 field experiment. ARPS is coupled with a Lagrangian particle model to simulate dispersion and collection of observations from an ensemble of airborne probes. Simulated wind, temperature, humidity, and pressure data are extracted from the ARPS model and then assimilated into the Pennsylvania State University/National Center for Atmospheric Research Fifth-generation Mesoscale Model (MM5) model. The dispersion model HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) is run using MM5 data with and without assimilation of probe data. Plume concentration/location predictions are compared. Additional simulations were performed that show how probes containing chemical sensors in addition to meteorological sensors could be used to identify the location of unknown sources. A description of the MAPIT system and simulation results will be presented at the conference.