Interdisciplinary Applications of Computational Science in Environmental Sustainability

Environmental sustainability is a critical global challenge, and computational science offers transformative solutions across various sectors. This paper explores interdisciplinary applications of computational science in environmental sustainability, focusing on Pakistan's context. We examine the integration of artificial intelligence (AI), machine learning (ML), and data analytics in areas such as climate modeling, resource management, and pollution control. The study highlights collaborative efforts among academia, industry, and government to develop sustainable solutions tailored to Pakistan's unique environmental challenges. Through case studies and data-driven analyses, we demonstrate how computational tools can enhance decision-making processes, optimize resource utilization, and mitigate environmental impacts. The findings underscore the importance of interdisciplinary approaches in achieving long-term environmental sustainability.