The global climate model ECHAM MESSy Atmospheric Chemistry (EMAC) is used to study climate change and air quality scenarios. The EMAC model is constituted by a nonlocal dynamical part with low scalability, and local physical-chemical processes with high scalability. The EMAC chemistry-climate model does not benefit from the support of accelerators which are nowadays installed in many HPC systems. We study strategies to offload the calculation of the atmospheric chemistry to accelerator technologies (GPU and Intel MIC), as in typical model configurations this is the most computational resource-demanding subtask. The proposed solutions extend the Kinetic Pre Processor (KPP) general purpose open-source software tool used in atmospheric chemistry.