The use of big data in environmental quality monitoring and its impact on policy development: a bibliometric analysis
Abstract Incorporating big data analytics into environmental quality monitoring systems is gaining traction because it improves evidence-based policymaking. Nevertheless, monitoring research activities, key players, and new emerging issues is still lacking. This gap will be solved through a comprehe...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-07265-x |
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| Summary: | Abstract Incorporating big data analytics into environmental quality monitoring systems is gaining traction because it improves evidence-based policymaking. Nevertheless, monitoring research activities, key players, and new emerging issues is still lacking. This gap will be solved through a comprehensive bibliometric analysis in this study following the PRISMA methodology. Scopus was chosen as the central database for this research. Relevant literature published between 2015 and 2024 was collected, and after inclusion and exclusion processes, a final sample of 125 articles was subjected to analysis. The results demonstrate that research activity is rising, especially in China, the United States, and South Korea. Important thematic groups use big data for climate change monitoring, innovative environmental governance, and analytics for government policy forecasting in the aforementioned countries. Developed findings show the growing intersection of data science, environmental policy, and artificial intelligence but remain relatively dormant in assessing the effectiveness of qualitative policy impacts, data-driven governance in practice, and policy formulation. Data science is poised to enable better regulation frameworks and, through machine learning, achieve responsible policymaking to support real-world challenges. This study maps the evolution of research domains, identifies key scholars, and offers public policy recommendations for data-driven reality concerning environmental governance. Such insights are important for researchers, public authorities, and practitioners. |
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| ISSN: | 3004-9261 |