Tomographic reconstruction of air pollutants: evaluation of measurement geometries.

We use numerical studies to evaluate 13 novel optical remote-sensing geometries for tomographically reconstructing chemical pollutants in air. We simulate the imaging process from data acquisition to reconstruction using a battery of test images. We evaluate the reconstructions generated by each geometry for locating chemical leaks, identifying plumes, and evaluating human chemical exposures. This approach uses three numerical image-quality measures for both static and time-varying concentration maps. Visual evaluation is the most useful method of evaluating the geometries. The numerical measures are not always consistent with one another or with the visual evaluation. This research demonstrates the feasibility of using geometries with only a few detectors for tomographic imaging of air pollutants.