In multispectral photoacoustic imaging (PAI), the illumination spectrum inside biological tissue varies spatially, leading to poor quantification accuracy of blood oxygen saturation (SO2). The key to solving this problem is to invert light diffusion, which is extremely complicated and inaccurate due to the limited information available in PAI. Despite the great effort devoted, to date, the few available methods are all limited in terms of in vivo performance and physical insights. Here, we introduce an analytical Monte Carlo method, with which we prove that the light spectrum in biological tissue mathematically lies in a high dimensional convex cone set. The model offers new insights into the origin of the spectral deterioration, and we find it possible to calculate blood oxygen saturation (SO2) accurately by using only the photoacoustic data at a single spatial location when signal to noise ratio is sufficient. The method was demonstrated numerically, and our preliminary phantom experiment results also confirmed its effectiveness.