Low-discrepancy sequences, and more particularly Sobolโ sequences are gold standard for drawing highly uniform samples for quasi-Monte Carlo applications. They produce so-called (๐ก,๐ )-sequences, that is, sequences of ๐ -dimensional samples whose uniformity is controlled by a non-negative integer quality factor ๐ก. The Monte Carlo integral estimator has a convergence rate that improves as ๐ก decreases. Sobolโ construction in base 2 also provides extremely fast sampling point generation using efficient xor-based arithmetic. Computer graphics applications, such as rendering, often require high uniformity in consecutive 2D projections and in higher-dimensional projections at the same time. However, it can be shown that, in the classical Sobolโ construction, only a single 2D sequence of points (up to scrambling), constructed using irreducible polynomials ๐ฅ and ๐ฅ+1, achieves the ideal ๐ก = 0 property. Reusing this sequence in projections necessarily loses high dimensional uniformity. We prove the existence and construct many 2D Sobolโ sequences having ๐ก = 1 using irreducible polynomials ๐ and ๐^2 +๐+1. They can be readily combined to produce higher-dimensional low discrepancy sequences with a high-quality ๐ก = 1, guaranteed in consecutive pairs of dimensions. We provide the initialization table that can be directly used with any existing Sobolโ implementation, along with the corresponding generator matrices, for an optimized 692-dimensional Sobolโ construction. In addition to guaranteeing the (1,2)-sequence property for all consecutive pairs, we ensure that ๐ก โค4 for consecutive 4D projections up to 215 points.