say i have following causal model:

* outcome variable: Y (e.g. sales)
* treatment variable: T (e.g. price)
* covariate variable: x2 (e.g. traffic)
* unobserved variables: U (unobserved)

causal relation:  

[![enter image description here](https://i.stack.imgur.com/GsZW9.png)](https://i.stack.imgur.com/GsZW9.png)

how can I estimate the casual effect of T on Y which includes **both** T cause Y directly and T cause Y through x2? the chanllenge is that x2 may also be impacted by some other unobserved factors. is there any methodology to do this?

--update.

the below answer seems not enough. Regression Y on T alone can't remove the effect from U which is unmeasured and unobserved.  

is there any method to remove impact from U?