Well, you can use angles in loading plot (or biplot) to estimate pairwise correlation, but I think you should be careful in doing that: in addition to angles, you have also to take in account the relevance of variables in the PCs (i.e.: distances from axes). So two co-linear variables, one of which is near the origin and the other very far, could be very little correlated, most of all because the first isn't relevant for those PCs and the second has a great relevance. Remember that PCA is a qualitative analysis!

As an example, my usual software doesn't use lines to indicate the variables, but only dots, so my only way to estimate correlations is watching the distances between variables, possibly on more than two PCs.

I repeat that to assess correlation between variables, it is better to calculate a correlation matrix, which gives **numerical** values for correlations and doesn't have "spatial" problems