Industrial symbiosis coupled with emission footprint minimization and resource conservation strategies is a highly acclaimed means of sustainably tackling global concerns of environmental pollution and depleting resources. Setting carbon reduction targets is the primary means policymakers employ to reduce emissions. The reduction is achieved by many pathways which include energy efficiency, fuel switching, carbon capture utilization and storage (CCUS), renewable energy (RE) and more recently, negative emission technologies (NETs). An eco-industrial park (EIP) incorporates industrial symbiosis to implement these solutions by synergistically exchanging resources between its entities. While many works have integrated a single resource in EIPs, the integration of multiple resources is an emerging area with remarkable potential to achieve sustainable benefits. This work introduces an extension to multiple resource integration by allowing it to translate over a time horizon. Policies are designed to achieve a target over a specified time horizon. The emerging reduction pathways will therefore change over time either by adapting to a policy or by modifying itself to improve performance, thereby making policies critical to an EIP’s design during its lifetime. The proposed method will employ a mixed-integer linear programming model to optimize network configurations and planning strategies for a set of objectives over multiple time periods. The model will also assess the network's economic and environmental benefits to allow stakeholders to assess and implement changes in their facilities. The model is illustrated by developing a CO2 converting network that maximizes total profit and minimizes emissions while simultaneously adapting to systematic changes in environmental policies.