ファイトレメディエーション研究の進化：重金属除去から微生物支援型自然由来ソリューションへ
Evolution of phytoremediation research: from heavy metal removal to microbiome-assisted nature-based solutions (原題)
V. V. Kozyrev, О. В. Данчук, Andriy Grafov, Sofiia Zherebchuk, Taras Zhygailo, О.О. Пілярська
🤖 gxceed AI 要約
日本語
本研究は、ファイトレメディエーション研究の進化を文献計量学的手法で分析し、2015年以降の研究増加、中国の主要貢献、研究トピックの微生物支援型技術やAI・デジタル技術への移行を明らかにした。将来の研究方向として、AI駆動予測モデルやPFAS汚染、戦争汚染土壌の修復などを特定している。
English
This bibliometric study analyzes the evolution of phytoremediation research, revealing a surge in publications post-2015, China's leading role, and a shift toward microbiome-assisted techniques, biochar, remote sensing, AI, and digital twins. It identifies research gaps in AI-driven modeling, mixed contaminants, PFAS, war-contaminated soils, and climate adaptation, positioning phytoremediation as a multidisciplinary field integrating sustainability and digital technologies.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、東日本大震災後の除染や工場跡地の土壌汚染対策に関連し、自然由来の修復技術は持続可能な環境管理の選択肢として注目される。AI・デジタル技術の統合は、日本の環境ビジネスやスマートシティ構想にも示唆を与える。
In the global GX context
Globally, this paper aligns with the growing emphasis on nature-based solutions and digitalization in environmental remediation, relevant to ISSB and CSRD reporting on biodiversity and ecosystem restoration. It highlights the role of AI and digital twins in advancing sustainable remediation, offering insights for climate adaptation and contaminated land management.
👥 読者別の含意
🔬研究者:Provides a comprehensive overview of phytoremediation research trends and emerging topics, useful for identifying collaboration and funding opportunities.
🏢実務担当者:Offers insights into innovative remediation technologies and digital tools that could enhance corporate sustainability and environmental compliance.
🏛政策担当者:Highlights research priorities and gaps that could inform funding allocation and environmental policy development.
📄 Abstract（原文）
Phytoremediation has become one of the most promising nature-based approaches for restoring contaminated ecosystems by combining environmental sustainability, economic feasibility, and ecosystem resilience.The aim of this study was to comprehensively analyze the evolution of phytoremediation research, identify major scientific trends, research hotspots, geographical distribution of scientific production, funding patterns, international collaboration, and future research directions using bibliometric methods.The results reveal a substantial increase in scientific output, particularly after 2015, reflecting the growing global interest in ecological restoration and sustainable environmental management.China emerged as the leading contributor to phytoremediation research, followed by the United Землеробство, рослинництво, овочівництво та баштанництво States, India, and several European countries.Funding analysis demonstrated the significant role of major national and international research programmes in advancing phytoremediation studies.Keyword mapping illustrates a clear evolution of research priorities from heavy metal uptake and plant physiology toward microbiome-assisted phytoremediation, biochar applications, remote sensing, Geographic Information Systems, artificial intelligence, machine learning, Digital Twins, and Nature-based Solutions.The analysis also identified important research gaps related to AI-driven predictive modelling, digital environmental monitoring, remediation of mixed contaminants and PFAS, war-contaminated soils, and climate adaptation.The findings demonstrate that phytoremediation has evolved from a narrow plant-based remediation technology into a multidisciplinary scientific field integrating environmental science, microbiology, digital technologies, and sustainability concepts.Bibliometric analysis not only reveals the historical evolution of scientific knowledge but also provides valuable insights into emerging research themes and future directions for sustainable environmental remediation.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.32782/2226-0099.2026.150.13first seen 2026-09-01 05:13:35
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