Satellite measurements of atmospheric chemical constituents have enhanced our understanding of how natural and human activities affect climate and air quality in the earth system. The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua was launched in 2002 with its primary goal of determining the vertical profiles of temperature and water vapor in the Earth’s atmosphere to improve weather forecasts, as well as providing remotely sensed atmospheric chemistry compositions for climate and air quality studies (Aumann, et al., 2003). AIRS makes measurements at wide swaths (1650km), and combined with its cloud-clearing algorithm it can achieve twice daily and global coverage (Susskind et al., 2003). The monitoring of tropospheric Carbon Monoxide (CO), identified as a good pollution tracer and a precursor of ozone, provides significant value in air quality studies. Our focus has been to understand the quality of the retrievals through validation and error analysis, and subsequently refine the algorithms to best use the measurement signals and prior information. We present in this talk an improved retrieval algorithm for AIRS CO products using the Optimal Estimation (OE) technique (Rodgers, 2000), which is different from the AIRS operational algorithm. We are in the process to produce and distribute this alternative product for the entire AIRS data record. We also present in this talk the preliminary results from our ongoing research such as: the impact of cloud on the tropospheric CO variability, merging CO profiles from satellite measurements without using a model, and the development of new products.