I was reading the article titled "Mobilize for Our Lives? School Shootings and Democratic Accountability in U.S. Elections". https://www.cambridge.org/core/journ...DB555476F1FCB4
The authors state that to improve their canonical DiD, "Given this, our preferred difference-in-differences models include county, year, and individual time trends for each county.This is a standard recommendation in the difference-in-difference literature (Angrist and Pischke 2008, 204; Wing, Simon, and Bello-Gomez 2018). It controls for differential trends across counties over time. This approach allows us to relax the tenuous parallel trends assumption key to difference-in-differences specifications. Here our identifying assumption is that our outcomes deviate from county-year effects by following the trend captured by the interaction of time with each county"

Since the article didn't have equations to explain the above, I don't know what the above statement meant. In a classical DiD, I have seen Unit fixed effects (here county fixed effects) and time dummies.
1. But how do we incorporate time trends in this, that too at the county level?
2. Is it possible to have both time dummies and time trends at county level?
3. How such time trends at the unit level deal with parallel trend assumption?

Can someone share their views on this?