A limited literature body have estimated regional differences in air pollution mixtures. More comprehensive analyses are necessary to accurately depict differences in air pollution characteristics over space and time. Our objective is to further these efforts by investigating spatial differences of air pollution mixtures across the US. We employed spatially constrained clustering approach (based on k-means algorithm) to group air pollution monitoring sites that exhibit distinct pollutant profiles or mixtures in the US over 9 years (2008-2016). We accounted for 20 chemical components of PM2.5. The resulting clusters of pollution mixtures are characterized and validated based on source emissions represented by land-use information. Our analysis resulted in 27 clusters with different number of sites. For example, the cluster 1 has 14 sites and it covers part of the southeast, including the states of North Carolina, South Carolina, Georgia, and Florida. The southwest has a very prominent cluster with 8 sites (cluster 26), covering part of the Louisiana, Mississippi, Texas, and Arkansas. In the west coast, two clusters were highlighted in our analysis, cluster 3 in California and cluster 7 in Washington and part of Oregon. Both clusters with 5 sites. We estimated that Cu, Se, NO3-, Cr, and Ba were the top five species that divided the study area into cluster of sites more effectively. Observing the concentration ratios (concentrations of the species i/concentration of PM2.5) for some of these clusters, our results show that clusters 3 and 7 in the west coast represent sites with high Na ratios. Cluster 13 in the northwest and part of the Midwest represents sites with high SO42- ratio. The cluster 16 with a single site in northeast has the highest O-4(2-) ratio, representing almost the third quartile of the SO42- ratio. This is one of the few studies focused on spatial patterns analysis to estimate regions that exhibit distinct pollutant mixtures on a large scale. We expect that further investigations can use our findings to analyze the relationship between areas that exhibit distinct pollutant mixtures and the impact of regulations, climate change, and health effects in the US.