As global climate change severely impacts our world, there is an increasing demand to monitor trace gases with a high spatial resolution and accuracy. At the same time, these instruments need to be compact in order have constellations for short revisit times. Here we present a new spectrometer instrument concept for trace gas detection, where photonic crystals filters replace traditional diffraction based optical elements. In this concept, 2D photonic crystal slabs with unique transmission profiles are bonded on a detector inside a regular telescope. As the instrument flies over the earth, different integrated intensities for each filter are measured for a single ground resolution element with a regular telescope. From this detector data, trace gas concentrations are retrieved. As an initial test case we focused on methane and carbon dioxide retrieval and estimated the performance of such an instrument. We derive the Cramér-Rao lower bound for trace-gas retrieval for such a spectrometer using Fisher information and compare this with the achieved performance. We furthermore set up a framework how to select photonic crystal filters based on maximizing the Fisher information carried by the filters and how to use the Cramér-Rao lower bound to find good filter sets. The retrieval performance of such an instrument is found to be between 0.4% to 0.9% for methane and 0.2% to 0.5% for carbon dioxide detection for a 300×300 m² ground resolution element and realistic instrument parameters.

Recently a spectrometer concept has been invented which uses compressive sensing in combination with photonic crystal filters. Here we present an adaption of this concept in push-broom configuration for earth observation. This implementation allows for a compact design, while maintaining a high spatial resolution and high signal-to-noise ratio compared to other traditional implementations. The photonic crystals have a unique transmission profile and act as a spectral filter, which allows for the computational reconstruction of the input spectrum with a limited number of filters. We show, using simulations, that our approach is able to reconstruct input radiance spectra with high accuracy and assess the performance for different number of filter sets. We furthermore show proof-of-principle measurements of the transmission profile of a manufactured photonic crystal. Future research will focus on the effect of noise on the reconstruction algorithm as well as further filter set optimization by combining the filter selection process with trace gas concentration retrieval.