<p>The growing frequency of disruptions has increased the need for supply chains that are resilient to adverse events. At the same time, environmental concerns, global warming, and government regulations require decision makers to account for the environmental impact of supply chain operations. This study presents a risk-averse, multi-objective supply chain model that integrates stochastic-possibilistic elements. The model simultaneously optimizes economic and environmental performance under a cap-and-trade policy. We also examine the role of green credit financing (GCF), multiple transportation modes, and alternative production technologies with different costs and emissions. To capture risk attitudes, the model incorporates Conditional Value-at-Risk (CVaR), ensuring robust performance under worst-case scenarios. The problem is solved using an augmented epsilon-constraint method and applied to a real-world case study. Results confirm the validity of the model. Interaction between resiliency and environmental performance of the supply chain is investigated and several useful managerial implications are provided. Results show that utilizing resilient strategies will ensure better economic performance. However, using multiple suppliers and holding emergency inventories will result in better environmental performance compared to the other investigated settings. It is also concluded that the availability of GCF and multiple transportation modes improve supply chain environmental performance and cap-and-trade is an effective policy for regulating supply chain emissions.</p>