Carbon Capture and Storage (CCS) is a pivotal technology for reducing greenhouse gas emissions. While developments have been made in capture and storage capabilities , the planning and development of an optimized transport pipeline network for linking emission sources to storage sites remains understudied. This study aims to extend the capabilities of SimCCS, a widely-used CCS planning tool, to incorporate environmental, social, and cultural considerations alongside economic costs of pipeline networks. Utilizing multi-objective optimization, we introduce an additional objective function that minimizes environmental and social impacts. This function integrates spatial data layers representing critical habitats, protected areas, and other socio-ecological factors. Preliminary results illustrate the model's capacity for multi-objective optimization. The annual expense for maintaining a sample pipeline network increased from $434 million to $622 million, with pipeline lengths of 1986 kilometers and 2878 kilometers, respectively, when shifting focus from cost to environmental and social impacts. This research contributes a more comprehensive framework for the planning of future CCS infrastructure that is both economically and environmentally sustainable.