As an exercise, I am considering a real-world example and I am thinking if I can model it through metric spaces, but apparently it is not possible (or I may be very wrong in my reasoning).
Say that I have a bunch of cities and I measure the CO2 levels at some point of the day in all the cities. This leads me to a set of numbers which I can use for my metric space.
Then, I also want know how "far" are two cities in terms of measured CO2 levels. I can take the absolute value of the difference of any pair of cities to see how "far" they are. By that, I think I should have defined a metric space.
However, I cannot figure if one city is more or less polluted than another, which is something desirable to know. I could remove the absolute value from my distance function, but then the function I am using is no longer a distance.
Am I using a wrong mathematical structure? Or what shall I do to capture that? What if I am interested in both CO2 and NOx for which my measurements would be 2D vectors?
EDIT: I tried to pick $d(x,y)=exp(x-y)$ but then I would have $d(x,x)=1$ and therefore that is not a good distance function.