A comprehensive emissions inventory is not prepared for every year, so most modeling projects use the most recently available modeling platform with some project-specific updates. Depending on the country of interest, you may get different pieces corresponding to different years, regardless if it is stamped with "2015". It's up to the modeler to decide whether emissions need to be updated for various categories. Your project goals should help you identify which emissions are of most importance, and whether they should be updated for your project.

In regards to using 2015 for a 2019 scenario, it depends on the pollutants you are studying and the region of interest. A lot changed over those few years, but you can't update all sectors so you have to prioritize. For instance, ship emissions underwent huge reductions in sulfur emissions during the latter part of that decade. Vehicle NOx emissions will also have changed, since the fleet would be cleaner (newer vehicles) despite the increase in population. You could also screen your point source data for any new large facility startups or shutdowns. Point source data are often reported every year by large facilities and you could get more recent information. Wildfire is very year specific so if you are doing anything PM2.5 related, you should use a 2019-specific fire inventory.

Emissions processors that I'm familiar with will allow for the user to input adjustment factors that are sector specific, but it will not interpolate between two different emissions inventory years. It's easiest to just provide the actual emissions, as it can be quite complicated to implement adjustment factors. Though, you could also make brute-force adjustments to your emissions intermediate files, before they are merged. For example, if you expect 2019 NOx vehicle emissions to be 30% less than 2015 values, you could process the vehicle emissions and then run an update script on your gridded emissions file. It's crude, but it can also be very difficult to create year-specific mobile vehicle emissions.

Finally, any good modeling project should undergo a test-run, to identify any major deficiencies (e.g. by matching up with surface monitors of interest). Emissions updates should be made if anything stands out (e.g. a persistent over-bias in a large region). Though, keep in mind that the emissions processor will augment annual emissions based on meteorology and temporal profiles, depending on the category. So, sometimes adjusting annual emissions is not enough to deal with the problem.