Air pollution increases mortality risk up to 18 percent due to cardiovascular causes. Poor air quality occurs more when meteorological components prevent the dispersal of pollutants in the lower atmosphere. The atmospheric and hydrological patterns change as global warming alters the pattern of circulations seasonally. The purpose of this study was to use an air stagnation index (ASI) to quantify the meteorological conditions that allow poor air quality. We examined ASI by season given that each season is dominated by the distinct synoptic meteorological phenomenon. By looking at these phenomena, we aimed to better explain the change of stagnation events. Here, we applied the ASI to the bias-corrected Coupled Model Intercomparison Project (CMIP5) ensemble prediction data. An exploratory analysis of CMIP5 model biased data suggested that the trend of stagnation days and duration of stagnation events have different seasonal patterns, and fluctuated spatially and seasonally. Our result suggests that global climate change will alter the air stagnation occurrence in the different season. Stagnation is very likely to increase among various regions of the world, including those areas with historical pollution issue. To complete this study, we will apply statistical analyses in conjunction with multi-model agreement criteria to quantify the robustness of air stagnation change. Future work might include tuning the ASI Metric for specific regions of interest.