You have a peak-shifting problem that often is an issue for basic chemometric tools such as PCA. If the variables are not aligned you will have the same problem with the PCA loadings as with univariate analysis, what point to choose? PCA will probably do an average or divide the peaks in two components, none of them solve your problem. There are peak alignment algorithms, mostly used in chromatographic data, but they're often complex and have to be tuned correctly.

What I could recommend as a midway solution is to fit a Gaussian curve to each of your samples and estimate the maximum point, then use that value for the univariate analysis.

Has your sample signal been normalized? The differences do not appear to be very pronounced. Additionally, why have you chosen to use Ti 441.492 nm? It is clear that this is not a commonly used spectral line for Ti. There are many strong peaks for Ti that could be used for univariate calibration, such as Ti I 365.35 nm, Ti I 375.29 nm, Ti I 399.86 nm, Ti II 323.45 nm, Ti II 334.94 nm, etc. Why have you not selected these? Are there other interfering peaks? Self-absorption occurs when the Ti concentration is too high, and in such cases, it is advisable not to use easily excited characteristic peaks as they are more prone to self-absorption. You can simply determine whether self-absorption is occurring by checking for peak center dips or splitting. If you need to quantify the degree of self-absorption, it can be calculated using the appropriate formula.