Precise and rapid air quality simulation and forecasting are limited by the computation performance of air quality model, and the gas-phase chemistry module is the most time consuming part in air quality model. In this study, we designed a new frame for the widely used Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the Single Instruction Multiple Data (SIMD) technology in the next generation processors for improving its calculation performance. And the optimization is aimed to implement the fine-grain level parallelization of CBM-Z by improving its vectorization ability. Through constructing loops and integrating the main branches, multiple spatial points in the model could be operated simultaneously on vector processing units (VPU). The Intel Xeon E5-2697 V4 CPU and Intel Xeon Phi 7250 Knight Landing (KNL) are used as the benchmark processors. The validation of model outputs indicated that the relative errors were in an acceptable range (<0.05%). The results showed that the optimization led to 4.24x speedup on single CPU core and 17.33x speedup on single KNL core. For the node, the speedup on CPU could reach 113.42x using Multiple Point Interface (MPI) and 118.13x using OpenMP, and the speedup on KNL node could further reach 170.31x using MPI and 179.95x using OpenMP. The speedup of optimized CBM-Z is generally 50~52% higher on 1-socket KNL platform than on 2-socket CPU platform. This work improves the performance of the CBM-Z chemical kinetics kernel as well as the calculation efficiency of air quality model, which could directly improve the practical value of air quality model in scientific simulation and routine forecasting. Furthmore, since this optimization aimed to improve the utilization of VPU, the model will be more suitable for the new generation processors adapting the more advanced SIMD technology.