Carbon-negative technologies (CNTs) are vital to achieving net-zero climate goals. However, regional disparities in CNT innovation capacity remain insufficiently understood. This study maps the innovation landscape of CNTs across 18 European countries from 2013 to 2023 using a novel multidimensional, data-driven approach. A real-coded accelerated genetic algorithm is integrated with projection pursuit to construct a high-dimensional evaluation model capable of handling nonlinear, nonnormal data distributions. Thirteen indicators across innovation input, output, and environment are selected to quantify national innovation capacities. Results show that Germany, France, and Italy consistently outperform others in CNT innovation, driven by high R&D investment, patent activity, and strong economic foundations. In contrast, countries like Portugal, Slovenia, and Luxembourg exhibit lower innovation capacities. Cluster analysis reveals a clear stratification into high-, medium-, and low-performing countries, highlighting structural differences in policy support and industrial development. It reveals the “club convergence” characteristic of negative carbon technology innovation capabilities across 18 countries, meaning these nations can be clearly divided into three hierarchical innovation echelons (high, medium, and low) rather than exhibiting continuous geographical agglomeration. Further mechanism analysis indicates significant differences in the innovation-driven factors among countries of different echelons: leading nations are driven by their macroeconomic foundation, while catching-up nations rely more heavily on government R&D investment and human resources. Temporal trends indicate overall growth in innovation capacity, with temporary declines linked to Brexit and the COVID-19 pandemic. This research contributes a robust methodological framework and a comparative evaluation of CNT innovation in Europe, offering critical insights for policymakers and stakeholders aiming to strengthen cross-border collaboration and accelerate the deployment of CNTs.
Li et al. (Tue,) studied this question.