Artificial Intelligence (AI) possesses immense potential for addressing a wide spectrum of environmental challenges and facilitating sustainable practices. Within the realm of Environmental Science, AI has emerged as a transformative force, offering innovative solutions to pressing ecological concerns. This comprehensive book delves into the myriad applications of AI in Environmental Science, spotlighting its pivotal role in diverse domains. The initial segment of the book provides a succinct overview of its contents, setting the stage for an in-depth exploration of AI's environmental applications. The subsequent sections spotlight AI-driven modelling, prediction, and monitoring techniques, leveraging environmental data across various sectors. Employing AI-powered sensors and remote sensing technologies, substantial volumes of environmental data, encompassing air and water quality, deforestation rates, and climate dynamics, can be harnessed and analysed. Machine learning algorithms process this information to discern trends, anomalies, and forecast potential environmental issues. The book's third section concentrates on the integration of AI into environmental management. Ecosystem preservation, natural disaster mitigation, waste management, and resource conservation take centre stage. AI's prowess in ecosystem analysis, encompassing biodiversity, species distribution, and habitat alterations, enables informed conservation decisions and sustainable land and resource administration. Harnessing historical data, AI algorithms predict natural calamities ranging from hurricanes to wildfires thus facilitating timely alerts and effective disaster response strategies. Diverse themes form the purview of the fourth section, embracing facets such as environmental impact assessment and carbon footprint reduction. Here, AI's automation capabilities shine through in evaluating the environmental repercussions of projects spanning construction, infrastructure development, and urban planning. By delineating potential consequences and proposing mitigation tactics, AI optimizes environmentally conscious decision-making. Moreover, the book delves into cutting-edge topics like AI-driven reduction of carbon footprints and the application of AI in agricultural data processing for enhanced crop yield. Precision agriculture benefits from AI's analysis of satellite, drone, and sensor data to fine-tune crop yields, manage irrigation, and curtail pesticide employment. Ultimately, this insightful tome caters to a broad spectrum of readers—ranging from academicians, students, and researchers to ardent AI enthusiasts operating within the sphere of environmental science. As AI continues its meteoric rise, its symbiotic relationship with environmental science emerges as an indispensable instrument for a sustainable future.