This work has demonstrated that statistical analysis of probe sites can extract pore environments from commonly employed pore size distribution methods, as applied to crystalline representations. The approach was tested for a series of MOFs that feature hierarchical pore systems, DUT-32, DUT-75, UMCM-1 and NU-1000. It is found that separating the pore system with respect to pore size can differentiate the different pores in DUT-32, UMCM-1 and NU-1000, however cannot discern the different pores in DUT-75. The challenging case of DUT-75 highlights that for materials featuring different pore environments of roughly the same size alternative approaches are required. The different sections of pore space filled during Ar adsorption at 87 K was then examined using these pore descriptions to illustrate the cooperative behaviour present in all pores of DUT-32, the two smallest pores of UMCM-1 and an absence of pore cooperativity observed for NU-1000. To extract the pore environment, which permits a local description of adsorption, clustering was applied to the probes to obtain positions of pore centres. Computing radial distributions from the pore centres led to a comparison of adsorption mechanisms in each of these pores identifying preferential adsorption sites and a significant difference in cage mesopores and one-dimensional mesopores.