As environmental challenges grow more complex and interconnected, big data analytics has emerged as a transformative force in advancing sustainable environmental management. By enabling the real-time collection, integration, and analysis of massive, heterogeneous datasets—from satellites, sensors, social media, and citizen science platforms—big data supports enhanced monitoring, predictive modeling, and evidence-based decision-making across a wide range of environmental domains. This article offers a comprehensive overview of the key benefits and practical applications of big data analytics in air quality monitoring, climate change modeling, biodiversity conservation, waste management, and water resource governance. It also examines critical cross-cutting challenges, including data integration, infrastructure disparities, algorithmic transparency, privacy concerns, and evolving legal frameworks. Looking ahead, the article explores emerging frontiers such as artificial intelligence, blockchain, edge computing, and the expanding roles of citizen science and international cooperation. The findings highlight the urgent need for responsible, equitable, and inclusive data-driven approaches to environmental protection and global sustainability.
Yang et al. (Wed,) studied this question.
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