We determine the optimal local integrability of the Hessian for planar convex Alexandrov solutions satisfying The distributional Hessian satisfies the sharp endpoint estimate This settles the weak estimate proposed by De Philippis and Figalli and identifies the larger optimal exponent . We further construct strictly convex solutions for which the distribution function of the Laplacian is comparable to for all sufficiently large . Hence both the exponent and the weak Lorentz endpoint are optimal: cannot be replaced by for any finite . As applications, we obtain sharp estimates in Minty coordinates and optimal quantitative bi-Lipschitz restrictions for gradient maps, including an optimal exceptional-mass bound in quadratic-cost transport.

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