Mining complexes face increasing pressure to reduce environmental impacts, yet most short-term stochastic optimization frameworks in mining complexes neglect environmental objectives, focusing solely on economic and operational performance. This work extends the framework by incorporating carbon footprint and pricing schemes under uncertainty, explicitly accounting for variability in emission factors and truck trip distributions. A parallelized reactive GRASP metaheuristic solution approach is adapted and used for its scalability, flexibility, and effectiveness in navigating large, nonlinear search spaces. Experimental results for a gold mining complex demonstrate up to 4% emission reductions from truck and shovels operation with only a 0.4% loss in profit.