separated by a distance $s$. The quantity $\xi(s)$ gives the excess probability of finding two points of a data set at a given separation distance $s$ when compared to a completely homogeneous distribution. If there is an excess of probability localized around a characteristic scale, as in the case of acoustic scale, it will appear as a bump in the $\xi(s)$ vs. $s$ plot. The location of the bump indicates the statistically preferred distance between the pairs of the studied sample.

A 3D 2PCF estimator assumes a cosmological model (flat $\Lambda$CDM, for example) to calculate the comoving distance $s$ between pairs of the data and the random catalogues. To avoid this model dependence we follow a different approach. We use the two-point angular correlation function 2PACF [@PeeblesYu] to estimate the transversal BAO contribution, analysis that is possible to be done selecting the data sample in a sufficiently thin redshift shell $\delta z$. The expression for the 2PACF estimator, $\omega(\theta)$, at mean redshift $\overline{z}$, is given by $$\begin{aligned}
\label{2PACF}
\omega(\theta) \equiv \frac{DD(\theta)-2DR(\theta)+RR(\theta)}{RR(\theta)} \, ,
\label{eq2}\end{aligned}$$ with $\theta$, the angular separation between any pair of quasars, given by $$\begin{aligned}
\,\,\theta\,=\,\arccos[\sin{\delta_{A}}\sin{\delta_{B}}+
\cos{\delta_{A}}\cos{\delta_{B}}\cos(\alpha_{A}-\alpha_{B})] \, , \nonumber\end{aligned}$$ where $\alpha_{A}, \alpha_{B}$ and $\delta_{A}, \delta_{B}$ are the 