how to calculate pairwise coloumbic interactions

In my simulation i want to break total force felt by a group into electrostatic and van der waal components. However when i do that (using group/group pair no kspace yes), I can see that results vary quite a lot with pppm tolerance factor. I want to know
1) Is there anyway i can make lammps to calculate all coulombic forces in pairwise fashion instead of kspace solver? (to get a 'correct' baseline to see how much error is present in my current simulation)
2) what will be most accurate settings for kspace long range solver (irregardless of speed, something like fix tune for accuracy)?

In my simulation i want to break total force felt by a group into electrostatic and van der waal components. However when i do that (using group/group pair no kspace yes), I can see that results vary quite a lot with pppm tolerance factor. I want to know

with a setting of "pair no kspace yes" you only compute the long-range
contributions to the coulomb potential and are missing the realspace
part.

1) Is there anyway i can make lammps to calculate all coulombic forces in pairwise fashion instead of kspace solver? (to get a 'correct' baseline to see how much error is present in my current simulation)

you need to use "pair yes kspace yes". however, in your production
calculation, this will also include other pairwise interactions, e.g.
lennard-jones. so the only we to separate these out, is to record your
trajectory and then doing the analysis with the "rerun" command, while
setting e.g. the LJ epsilon coefficients to zero.

2) what will be most accurate settings for kspace long range solver (irregardless of speed, something like fix tune for accuracy)?

the smaller the convergence factor, the more accurate. i.e. 1.0e-6
will give you a more accurate coulomb than 1.0e-4. also, using more
bits resolution or turning coulomb tables off, will improve accuracy.
however, there is a limit in the current implementation of the
analytic coulomb, as erfc() is approximated at about single precision
accuracy (~1.0e-7).

but also keep in mind, that the parameterization is usually truncated
at 4-5 significant digits, so while you may improve the numerical
accuracy, you cannot overcome the systematic error of parameterization
and - of course - the model itself.

axel.