Artificial intelligence and environmental science: paving the way to a sustainable future
In an era of rapid technological progress, artificial intelligence (AI) has emerged as a transformative force across multiple fields, including environmental science. The launch of the journal Artificial Intelligence and Environment (AI&E) is evidence of this promising integration. Launched in November 2025 and co-edited by renowned academics Professor Guang-Guo Ying and James P. Lewis, AI&E aims to uncover transformative synergies between AI applications and the critical environmental challenges facing the world. The journal aims to foster academic collaboration and knowledge sharing and advance the ecological sustainability agenda through advanced computational tools and methodologies.
The journal is broad in scope but narrow in focus. By integrating cutting-edge AI strategies into different environmental contexts, we aim to enhance the methodological toolkit available to environmental scientists and practitioners. Whether it’s ecological conservation, climate change mitigation, water management, pollution control, or sustainable development, AI&E is dedicated to advancing research that not only improves understanding but also creates practical solutions. As environmental problems become increasingly complex, so too must our approaches to addressing them. The journal therefore accepts submissions from researchers around the world and fosters a community that thrives on diverse perspectives and innovative ideas.
The first issue of AI&E features a collection of seminal papers that provides a roadmap for the future of interdisciplinary collaboration between AI and environmental science. Each paper considers a different aspect of how AI methods can reshape traditional environmental practices, demonstrating both the potential and necessity of this integration. The editorial published in this issue aptly characterizes AI as a tool that complements, rather than replaces, human intelligence in environmental research. The editorial articulates a vision that AI will enable scientists to navigate the complexity of multifaceted environmental data, ultimately leading to more informed and impactful decisions.
In one featured paper, the authors take a closer look at a phenomenon known as intelligent identification of non-target pollutants. Here they advocate a paradigm shift in environmental analytical chemistry. In a world full of diverse and complex organic pollutants, traditional methods of qualitative and quantitative analysis are inadequate due to the lack of reference standards. Researchers have launched an innovative approach that can streamline the identification of harmful contaminants without the need for predefined criteria by using machine learning techniques to predict mass spectra and infer molecular structures. This is a pivotal moment in the evolution of analytical technology, allowing scientists to explore uncharted territory in environmental monitoring.
Moreover, the transformation of the microplastics research chain represents another important area of exploration in the inaugural issue. In this Perspective paper, we introduce a pan-microplastic AI framework and explain how artificial intelligence can uniquely address the multifaceted “triple crisis” of microplastic pollution, climate change, and biodiversity loss. Researchers are proposing a comprehensive strategy to tackle one of the most pressing environmental challenges of our time by integrating AI into areas ranging from hyperspectral identification of pollutants to neurotoxicity assessment and global risk assessment. Through such innovative methodologies, this framework reveals how AI can fill gaps in existing research and provide holistic solutions.
Digging deeper, the journal also reviews the deployment of AI methods across various environmental domains, including air, water, soil, and waste management. A systematic assessment of the role of AI in these situations reveals its potential to transform traditional environmental practices through advanced data processing techniques. Among the recommendations provided is a “5-point standard” for effectively deploying AI models. The standard covers stages from data preparation to interpretability and clarity, essentially advocating transparency in what is often considered a “black box” system. As scientists begin to realize the importance of clarity and interpretability in AI applications, trust in these technology-driven solutions will grow in both the academic and public spheres.
The interesting research presented in this issue focuses on the emerging role of household pet hair as an indicator of indoor pollution levels. This ingenious approach leverages text mining, machine learning, and high-resolution mass spectrometry to demonstrate that household pets can serve as sensors for accidental exposure to indoor chemicals. The results of this study suggest significant overlap in chemical exposure characteristics between pets and their owners, revealing an interesting avenue for individual environmental health assessment. As more studies like this are published, they highlight the innovative potential for integrating AI to inform public health in unexpected ways.
The journal also critically examines the global impact of AI development paradigms, particularly the differences between China, the United States, and the European Union. This policy-oriented discussion highlights the need for a collaborative approach to environmental governance in the context of different technological ecosystems. As the landscape of AI innovation becomes more diverse, there is an urgent need to coordinate efforts toward a common goal of addressing climate change and ensure we develop coherent strategies that encompass the complexity of global environmental challenges, not just piecemeal solutions.
Therefore, the AI & Environment mission is important. In addition to providing a forum for academic debate, we also aim to foster a broader movement towards sustainable practices through AI interventions. Our greatest hope is that the research published in AI&E will inspire practical applications that provide environmental professionals with cutting-edge tools and algorithms that will yield quantitative benefits in our collective fight against the ecological crisis.
The journal will continue to accept submissions and welcomes contributions that address relevant research questions and propose new applications of AI in environmental science. Calling for special issues from experts in the field represents a continued effort to foster specialized themes within the journal and encourages in-depth exploration of relevant issues at the intersection of AI and environmental research. AI&E’s collaborative spirit ensures that it is a valuable resource for researchers, policy makers, and practitioners alike.
In conclusion, the emergence of “artificial intelligence and the environment” heralds a new era in the integration of technology and environmental management. As interdisciplinary research flourishes in this field, the real-world impact of such innovations will redefine our approach to ecological sustainability and enhance our understanding of environmental complexity. We stand on the precipice of breakthrough change. AI is not only used for analytical purposes, but also to guide strategic decision-making and create a path towards a healthier, more sustainable future for our planet.
Research theme: Application of artificial intelligence in environmental science
Article title: Artificial intelligence and environmental science: paving the way to a sustainable future
News publication date:October 2023
Web reference: Not applicable
References: Not applicable
image credits: James P. Lewis, Chang’er Chen, Yin Guangguo
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Artificial intelligence, environmental science, sustainability, ecological protection, climate change mitigation, pollution prevention, microplastics, machine learning, data science.
Tags: Advances in environmental methodology Application of AI in environmental challenges Artificial intelligence in environmental science Climate change mitigation technology Ecological conservation innovation The future of AI in sustainability Integrating AI and ecology Journal on AI and the environment Pollution control with artificial intelligence Academic collaboration in ecological research Sustainable development strategies Water management solutions using AI
