<p>Achieving coordinated control of road traffic pollutants and carbon emissions through emission allowance allocation is critical for urban sustainability. However, the existing methods used for road traffic emission allowance allocation often overlook the variability in individual vehicle travel behavior, multigas interrelationships, and the time-varying nature of travel, leading to limited incentives for efficiency improvements and imbalances in allocated allowances relative to preset multigas targets. To address these limitations, a digital twin-driven framework for the dynamic and coordinated allocation of urban-level individual vehicle multigas emission allowances is proposed. The framework leverages high-resolution travel, multigas emission, and allowance allocation states for individual vehicles derived through digital twin modeling. Using data envelopment analysis, candidate sets of benchmarks representing the optimal emission efficiency for multiple gases are established. The framework then dynamically selects the optimal coordinated benchmark that minimizes disparities in the allocated multigas allowances and computes the coordinated allowances in real time. The experiments results demonstrate that, compared with traditional methods, the proposed method provides stronger incentives for efficiency improvements and reduces imbalances in multigas allowance allocation. This method supports the enhancement of traffic emission efficiency and the implementation of integrated pollution reduction and carbon neutrality policies.</p>