This article reports on numerical studies to evaluate and compare optical remote sensing configurations for tomographically reconstructing pollutant concentrations in indoor air. With a remote sensing/computed tomography system, two-dimensional maps of pollutant concentrations with good spatial resolution can be created for an entire room. The successful use of such a system for exposure assessment, ventilation assessment, or source monitoring depends on the remote sensing configuration. A systematic method was developed to evaluate the performance of 10 configurations. One hundred and twenty test maps were reconstructed with an algebraic reconstruction method using all 10 configurations; reconstruction quality was evaluated using 4 criteria. Reconstruction quality was related to the number and location of detectors in the room and the complexity of the test maps. Configurations using the same number of detectors placed in different locations resulted in reconstructions that differed in quality. The effect of reducing the number density of rays on reconstruction quality was studied. Based on these simulations, two configurations that used four detectors to scan the room were selected, and their performance was evaluated in the presence of various levels of measurement noise. Two configurations that used four detectors were most suited for exposure assessment. It was found that when designing a configuration, the number and independence of rays should be maximized. Results underscored the need to thoroughly test configurations through numerical studies prior to field implementation; a wide variety of concentration maps, relevant to the application, should be tested under both ideal and nonideal sampling conditions.