Graphene NMS and their composites, as mentioned in previous chapters, play a pivotal role in the adsorptive removal process of heavy metal ions from different ecosystems. Despite exhibiting immense potential in environmental remediation applications, graphene-based adsorbents are often associated with various challenges which hinder their efficiency. There are several drawbacks, including synthesis techniques which exhibit economic and environmental challenges, as different toxic chemicals are involved in their production process, as well as costly infrastructure and techniques for composite development are involved. Besides, various technical challenges such as changed behaviour of graphene-based adsorbents in multi-metallic environment when tested from laboratory scale to actual environmental conditions, as targeted metal often co-exists with other metal ions. Moreover, various challenges are linked with the chemical modifications of these NMS for enhancing their metal ion chelation capacity. The variable abiotic environmental factors, such as ph variation, have a significant impact on the adsorptive capacity of the graphene-based NMS. In addition, there are significant challenges linked with the scalability, sustainability, and toxicity impact of these NMS, which need to be addressed for industrial-scale implementation of graphene-based technology in the removal of HMIS across the ecosystems. It is estimated that integrating nanotechnology with the emerging technologies such as artificial intelligence (AI) and machine learning (ML) can shape the future of environmental remediation through optimisation of different factors crucial for HMIS adsorption and removal.