Major challenges in the shale gas supply chains are identification of the relationship between different stake-holders and evaluation of the environmental impacts under uncertainties. This study develops a stochastic decentralized fractional programming (SDFP) for the life cycle shale gas energy system planning, where the downstream optimization problem is treated as the upper-level model, and the upstream optimization problem is formulated as the lower-level model. Stochastic uncertainties in the estimated ultimate recovery (EUR) and greenhouse gas (GHG) emissions are considered into the decision making process. A SDFP based energy and environmental workflow is then formulated for a real-work case study of Marcellus shale play in Beaver County. Design and operational decisions for both leader and follower are generated in a sequential manner, involving well drilling schedule, energy flows, water resources management, and GHG emissions control. Results reveal that a higher certainty level of EUR value would correspond to a higher reliably in shale gas production, then to increased GHG emissions and economic benefits. Compared with the decentralized linear programs, the SDFP would provide more sustainable strategies, while the linear programs would generate either environment-oriented or economics-oriented strategies. These findings can help stakeholders to achieve the overall satisfaction of the supply chains and to provide useful information for regional GHG emissions control.