Laser de-coating is rapidly emerging as a transformative technology for coating and contaminant removal from surfaces, supporting bonding processes and advancing circular economy objectives. In support of the net-zero transition, this  research introduces a novel, energy-centric optimization framework designed to enhance laser cleaning processes while minimizing environmental impact. The framework facilitates efficient laser material interaction with minimal thermal damage through the integration of material characterization and laser absorption maximization. A fractional factorial design was employed as part of a broader energy optimization framework to systematically investigate the effects of key laser parameters such as pulse energy, scanning speed, repetition rate, and beam overlap on the thermophysical dynamics of laser-material interaction. This statistical approach enabled the identification of parameter combinations that minimize energy demand and Scope 2 emissions while maintaining optimal ablation efficiency and surface quality. The study found that pulse energy and scanning speed were significant influences of cleanliness and surface integrity. Experimental confirmation of optimized parameters showed a 47% reduction in energy consumption for the selective diamond-like carbon (DLC) coating removal. The system level specific energy consumption was 14 MJ/cm3. The proposed framework provides a roadmap for laser de-coating while advancing the goals of low carbon manufacturing and high-performance surface engineering.