Environment-, process-, and energy-specific multi-objective optimization of the industrial large-scale natural gas dehydration process

• Optimization of industrial large-scale natural gas dehydration process. • Bi-, Tri-, Four-, Five-, Six-objective optimization study and analysis. • Process, energy, emissions, and environment-based multi-objective optimization. • Best, middle and worst optimal solutions using TOPSIS method of the Pareto ranking. • 1st study considering emissions, energy and GWP for natural gas dehydration process. The industrial natural gas dehydration process using triethylene glycol (TEG) is characterized by fundamental conflicts between environmental goals and energy consumption. The study employs a multi-objective optimization (MOO) framework to systematically map these trade-offs by simultaneously optimizing six conflicting objectives: to minimize energy consumption, water content in dry gas, BTEX emissions, global warming potential (GWP), and TEG makeup, while maximizing hydrocarbon recovery. The optimization study showed that achieving a drier gas (lower water content) invariably demands higher energy. While lower regeneration temperatures reduce energy use and GWP, they simultaneously increase BTEX emissions and compromise dehydration efficiency. Pareto ranking analysis using the TOPSIS method was employed to identify optimal solutions, confirming that while energy and water content are dominant drivers, explicitly prioritizing environmental objectives significantly shifts the optimal conditions toward lower-emission operations. This work provides insights for designing sustainable and efficient natural gas dehydration processes that navigate the inherent conflicts between environmental responsibility and operational performance.