Beyond laboratories and courtrooms, this work ignites a paradigm shift in global environmental enforcement. Industrial polluters currently exploit two systemic flaws: the sluggish pace of ecological forensics (requiring years to establish causal liability) and the corporate bias embedded in legal databases used to train AI. Our fine-tuned models counter both by generating court-admissible evidence chains in real-time—correlating, for example, a petrochemical conglomerate’s effluent data with satellite-captured mangrove deforestation rates across sequential tidal cycles. Such capabilities could compress liability resolution from decades to months, directly accelerating habitat restoration in climate-vulnerable regions like Southeast Asia’s coral triangle or the Amazon Basin. By quantifying how Chain-of-Thought prompts increase ecological weightings by 40-55%, we equip environmental prosecutors with mathematically verifiable tools to challenge corporate "greenwashing" narratives in court. Simultaneously, our open-sourced adversarial datasets will democratize access to climate justice tools—enabling Global South communities to generate AI-powered environmental impact assessments currently monopolized by Western consulting firms.