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The industrial period and modern age is characterized by combustion of coal, oil, and natural gas for primary energy and transportation leading to rising levels of atmospheric of CO2. This increase, which is being carefully measured, has ramifications throughout the biological world. Through remote sensing, it is possible to measure how many molecules of CO2 lie in a defined column of air. However, other gases and particles are present in the atmosphere, such as aerosols and water, which make such measurements more complicated1. Understanding the detailed geometry and path length of the observation is vital to computing the concentration of CO2. Comparing these satellite readings with ground-truth data (TCCON) the systematic errors arising from these sources can be assessed. Once the error is understood, it can be scaled for in the retrieval algorithms to create a set of data, which is closer to the TCCON measurements1. Using this process, the algorithms are being developed to reduce bias, within.1% worldwide of the true value. At this stage, the accuracy is within 1%, but through correcting small errors contained in the algorithms, such as accounting for the scattering of sunlight, the desired accuracy can be achieved.