Yapay Zekâ Tabanlı Yöntemlerle Hava Kirliliği Araştırmalarının Gelişimi ve Gelecek Perspektifleri: Bibliyometrik Bir İnceleme

Abstract

Kentleşme, enerji tüketimi, sanayileşme ve nüfus artışıyla birlikte hava kirliliği ve hava kalitesindeki düşüş, halk sağlığı ve çevre üzerinde ciddi bir tehdit oluşturmaktadır. Kirleticilerin tespiti ve kontrolü, günümüzün öncelikli sorunlarından biri haline gelmiş ve bu bağlamda yapay zekâ tabanlı yöntemlerin hava kirliliği araştırmalarında artan önemi dikkat çekmiştir. Bu çalışma, 2004–2024 yılları arasında yapay zekâ tabanlı yöntemlerin kullanıldığı hava kirliliği araştırmalarındaki öncelikli temaların gelişimini ve gelecekteki araştırmalara yön verebilecek alanları kapsamlı bir şekilde incelemiştir. Bibliyometrik analiz ve atıf analizi yöntemleri kullanılarak yapılan bu araştırma, literatürün sistematik bir değerlendirmesini sunmuş ve hava kirliliği ile ilgili yapay zekâ uygulamalarının zamanla üstel bir artış gösterdiğini ortaya koymuştur. Araştırma sonuçları, 2014 sonrası dönemde yapay zekâ tabanlı yöntemlerin literatürde bir paradigma değişimi yaratarak hava kirliliği tahminleri ve modellemelerinde merkezi bir rol üstlendiğini göstermektedir. Aynı zamanda, disiplinler arası iş birliği eğilimlerinin güçlenmekte olduğunu ve yapay zekâ tabanlı yöntemlerin yalnızca yenilikçi bir çözüm sunmakla kalmayıp, aynı zamanda literatürdeki evrimi şekillendiren bir dönüşüm sağladığını ortaya koymaktadır. Bu analiz, alanın mevcut durumunu anlamak ve gelecekteki araştırma yönelimlerini belirlemek için değerli bir bilgi kaynağı sunmakta, yapay zekâ tabanlı yöntemlerin hava kirliliği çalışmalarında daha geniş ve etkili bir şekilde kullanılabileceğini güçlü bir şekilde desteklemektedir.

Keywords

• Hava Kirliliği
• Hava Kalitesi
• Yapay Zekâ
• Bibliyometrik Analiz

Development and Future Perspectives of Air Pollution Research Using Artificial Intelligence-Based Methods: A Bibliometric Review

Abstract

Urbanization, energy consumption, industrialization, and population growth, along with air pollution and the decline in air quality, pose a serious threat to public health and the environment. The detection and management of pollutants have become urgent global concerns, underscoring the growing significance of artificial intelligence (AI)-based methods in air pollution research. This study presents a thorough review of the evolution of key themes in AI-driven air pollution research from 2004 to 2024, highlighting areas for future investigation. Through bibliometric and citation analyses, the study systematically examines the literature, revealing an exponential growth in AI applications in air pollution research over time. The findings indicate that after 2014, AI-based methods have led to a paradigm shift, playing a critical role in air pollution forecasting and modeling. At the same time, the study reveals that interdisciplinary collaboration trends are strengthening and that AI-based approaches not only offer innovative solutions but also serve as a transformative force shaping the evolution of the literature. This analysis provides valuable insights into the current state of air pollution research and presents guidance for future directions, emphasizing the need for broader and more effective integration of AI techniques in this area.

Keywords

• Air Pollution
• Air Quality
• Artificial Intelligence
• Bibliometric Analysis

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