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Reconstructing the VOC–Ozone Research Framework Through a Systematic Review of Observation and Modeling

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  • Xiangwei Zhu

    (College of Chemical Engineering and Environment, China University of Petroleum, Beijing 102249, China
    Karamay Ecological Environment Monitoring Station, Karamay 834000, China
    These authors contributed equally to this work.)

  • Huiqin Wang

    (College of Engineering, China University of Petroleum (Beijing) at Karamay, Karamay 834000, China
    These authors contributed equally to this work.)

  • Yi Han

    (Karamay Ecological Environment Bureau, Karamay 834000, China)

  • Donghui Zhang

    (Institute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, China)

  • Senhao Liu

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Zhijie Zhang

    (School of Geography, Development and Environment, The University of Arizona, Tucson, AZ 85719, USA)

  • Yansheng Liu

    (College of Chemical Engineering and Environment, China University of Petroleum, Beijing 102249, China)

Abstract

Tropospheric ozone (O 3 ), a secondary pollutant of mounting global concern, emerges from complex, nonlinear photochemical reactions involving nitrogen oxides (NO x ) and volatile organic compounds (VOCs) under dynamically evolving meteorological conditions. Accurately characterizing and effectively regulating O 3 formation necessitates not only precise and multi-dimensional precursor observations but also modeling frameworks that are structurally coherent, chemically interpretable, and sensitive to regime variability. Despite significant technological progress, current research remains markedly fragmented: observational platforms often operate in isolation with limited vertical and spatial interoperability, while modeling paradigms—ranging from mechanistic chemical transport models (CTMs) to data-driven machine learning approaches—frequently trade interpretability for predictive performance and struggle to capture regime transitions across heterogeneous environments. This review provides a dual-perspective synthesis of recent advances and enduring challenges in the VOC–O 3 research landscape. We first establish a typology of ground-based, airborne, and satellite-based VOC monitoring systems, evaluating their capabilities, limitations, and roles within a vertically structured sensing architecture. We then examine the evolution of O 3 modeling strategies, from empirical and semi-mechanistic models to hybrid frameworks that integrate physical knowledge with algorithmic flexibility. By diagnosing the structural decoupling between observation and inference, we identify key methodological bottlenecks and advocate for a system-level redesign of the VOC–O 3 research paradigm. Finally, we propose a forward-looking framework for next-generation atmospheric governance—one that fuses cross-platform sensing, regime-aware modeling, and policy-relevant diagnostics into an integrated, adaptive, and chemically robust decision-support system.

Suggested Citation

  • Xiangwei Zhu & Huiqin Wang & Yi Han & Donghui Zhang & Senhao Liu & Zhijie Zhang & Yansheng Liu, 2025. "Reconstructing the VOC–Ozone Research Framework Through a Systematic Review of Observation and Modeling," Sustainability, MDPI, vol. 17(16), pages 1-42, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7512-:d:1728308
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