<p>Methanol is a significant chemical and an energy carrier with substantial potential for global market growth. The dependence on fossil fuel-based feedstocks to produce methanol poses a significant barrier to decarbonizing the chemical sector. In Particular, natural gas-based methanol is currently among the most economically competitive production pathways. Consequently, the production of low-carbon methanol requires developing new production pathways that adopt more sustainable feedstocks, incorporate novel technologies, and utilize renewable energy sources. Most existing low-carbon methanol studies do not evaluate the environmental performance under uncertainty, particularly with respect to renewable energy, CO₂ recycling, and water reuse. This study introduces a novel system design to produce both blue and green methanol. The proposed design integrates a green methanol synthesis unit with the existing methanol process to recycle and reuse CO₂. An electrolyzer is integrated to generate green hydrogen to react with the recycled CO₂. To enhance the sustainability of the system design and operation, flowback and produced water resources from natural/shale gas production are treated using reverse osmosis (RO) technology and used within the process. Heat integration is conducted to minimize external heating and cooling requirements. Furthermore, a heat pump (HP) is employed to utilize waste heat and further reduce the external heating and cooling utilities. The energy system configuration for supplying heat and electricity is designed to ensure steady-state operation for the overall operational units by addressing the uncertainty in predicting solar energy availability and weather conditions. The energy system includes parabolic trough collectors (PTC), thermal energy storage, a steam generator, a natural gas boiler, and a backpressure turbine. A multi-scenario stochastic mixed-integer nonlinear programming (MINLP) model is developed under uncertainty to maximize the annual net profit. However, the core flowsheet in the Aspen simulation was fixed, the stochastic optimization focused on the energy and water systems. A case study was conducted based on Barnett Shale in the Fort Worth Basin, Texas. The results of the stochastic MINLP formulation, including and excluding heat pump, are compared to a deterministic case and other selected stochastic cases. The proposed system demonstrated economic and environmental benefits. Furthermore, the outcomes of this study show the potential merits of electrifying and decarbonizing methanol production.</p> Graphical Abstract <p></p>