Consider the diffusion process \begin{equation*} dX_ε(t) = \mss b(X_ε(t)) \, dt + \sqrt{2\, ε\, \mss a(X_ε(t))} \, dW_{t}, \end{equation*} on the one-dimensional torus $\bb T = [0,1)$. Here $ε$ is the temperature, $W_{t}$ a Brownian motion on $\bb T$ and $\mss a$, $\mss b$ functions of class $C^{2}(\bb T)$ satisfying further conditions. Denote by $\mss P(\bb T)$ the set of probability measures on $\bb T$ equipped with the weak topology, and by $\ms I_ε\colon \mss P(\bb T)\to [0,+\infty)$ the level two large deviation rate functional of the diffusion $X_ε(\cdot)$. We derive a full $Γ-$expansion of $\ms I_ε$, as $ε\to 0$, expressing it as \begin{equation*} \ms I_ε = \frac{1}ε \;\ms J^{(-1)} \; +\; \ms J^{(0)} \;+\; \sum_{p=1}^{\widehat{\mf q}}\frac{1}{θ^{(p)}_ε}\;\ms J^{(p)}\,, \end{equation*} where $\ms J^{(-1)}$, $\ms J^{(0)}$, $\ms J^{(p)} \colon \mss P(\bb T)\to [0,+\infty]$ represent rate functionals, independent of $ε$, and $θ^{(p)}_ε$ are the time-scales at which the Markov process $X_ε(\cdot)$ exhibits a metastable behaviour.