The environmental impact of plastic waste has become a significant concern worldwide, prompting innovative approaches to address sustainability challenges, particularly within architectural design. This research paper delves into assessing the environmental impact and sustainability implications of using hard-to-recycle plastic packaging waste in architectural design practices. This study aims to evaluate the feasibility, challenges, and potential benefits of repurposing hard-to-recycle plastic packaging waste as building materials in an architectural context. The paper presents a compelling case study showcasing innovative architectural projects that have successfully integrated hard-to-recycle plastic waste. It offers recommendations for future research directions and policy interventions to promote the adoption of hard-to-recycle plastics in environmentally conscious architecture, thereby advancing sustainability goals and fostering a circular economy paradigm within the construction industry. The research paper also highlights a specific experiment conducted using hard-to-recycle plastic waste, illustrating the potential for creative solutions in sustainable architectural design. This study provides valuable insights into the environmental impact and feasibility of repurposing hard-to-recycle plastics as building materials, contributing to ongoing efforts to address sustainability challenges.

Urban green infrastructure design faces growing challenges posed by climate change and urbanization, necessitating precise, site-specific plant selection. Existing approaches rely on general guidelines and lack integration of environmental data with reproducible decision-making methods. This study proposes a data-driven parametric framework combining Grasshopper with environmental analysis plugins (Ladybug, Honeybee, Gismo) and a custom rule-based plant suitability model. A botanical database of over 100 species was developed to encode environmental requirements, growth characteristics, and maintenance parameters. The system processes site-specific solar radiation, soil conditions, microclimate, and water availability to evaluate plant–environment compatibility and generate spatially explicit planting configurations. The framework was validated in an urban case study, demonstrating improved alignment between plant requirements and site conditions and reduced selection time compared to conventional approaches. Integrating environmental data with parametric tools supports more transparent and reproducible decision-making in climate-responsive urban vegetation design.