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<p>Quantifying commercial cooking emissions is non-negligible for mitigating urban PM<sub>2.5</sub> and O<sub>3</sub> pollution, given their significant and spatiotemporally concentrated releases of PM<sub>2.5</sub> and volatile organic compounds (VOCs). However, the accuracy of existing commercial cooking emission inventories remains unsatisfactory because generalized estimation parameters fail to represent the dynamic emission variations of this sector. Here, we develop a unified online-source framework (UOS) that simultaneously refines emission magnitudes and spatiotemporal allocations by integrating samplebased calibrated online oil fumes monitoring and point-of-interest data. Our framework corrected a 5.95-and 2.09-fold underestimation of VOCs and PM<sub>2.5</sub> emissions in Guangdong Province in 2023 compared to the legacy version, in which hourly-scale emission factors significantly increased up to 159.13 g/h for VOCs and 52.47 g/h for PM<sub>2.5</sub>, respectively. Moreover, the spatial distribution was optimized to 70% of emission hotspots captured in the Pearl River Delta (PRD) region relative to the 50% population-based allocation of the legacy inventory. With improved spatiotemporal performance in simulated PM<sub>2.5</sub> and O<sub>3</sub>, the UOS framework demonstrated a substantially greater annual contribution of commercial cooking emissions to PM<sub>2.5</sub> (2.93 µg/m<sup>3</sup>) than to O<sub>3</sub> (1.02 µg/m<sup>3</sup>), as well as more pronounced contributions of both PM<sub>2.5</sub> (12.06 µg/m<sup>3</sup>) and O<sub>3</sub> (8.39 µg/m<sup>3</sup>) in high-emission areas during pollution episodes. This work offers a scalable methodology to develop accurate commercial cooking emission inventories, thereby providing a scientific foundation for making targeted emission-reduction policies in commercial cooking.</p>

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Estimating commercial cooking contribution to urban PM2.5 and O3 with a refined emission inventory from a unified online-source framework

  • 期刊论文

  • 发表日期：

    2026年5月15日

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  • Yingzhi Yuan,
  • Yun Zhu,
  • Ji-Cheng Jang,
  • Dian Ding,
  • Zhaoxin Dong,
  • Meijun Chen,
  • Bin Zhao,
  • Jiaqian Hu,
  • Xiansheng Shi

摘要

Quantifying commercial cooking emissions is non-negligible for mitigating urban PM2.5 and O3 pollution, given their significant and spatiotemporally concentrated releases of PM2.5 and volatile organic compounds (VOCs). However, the accuracy of existing commercial cooking emission inventories remains unsatisfactory because generalized estimation parameters fail to represent the dynamic emission variations of this sector. Here, we develop a unified online-source framework (UOS) that simultaneously refines emission magnitudes and spatiotemporal allocations by integrating samplebased calibrated online oil fumes monitoring and point-of-interest data. Our framework corrected a 5.95-and 2.09-fold underestimation of VOCs and PM2.5 emissions in Guangdong Province in 2023 compared to the legacy version, in which hourly-scale emission factors significantly increased up to 159.13 g/h for VOCs and 52.47 g/h for PM2.5, respectively. Moreover, the spatial distribution was optimized to 70% of emission hotspots captured in the Pearl River Delta (PRD) region relative to the 50% population-based allocation of the legacy inventory. With improved spatiotemporal performance in simulated PM2.5 and O3, the UOS framework demonstrated a substantially greater annual contribution of commercial cooking emissions to PM2.5 (2.93 µg/m3) than to O3 (1.02 µg/m3), as well as more pronounced contributions of both PM2.5 (12.06 µg/m3) and O3 (8.39 µg/m3) in high-emission areas during pollution episodes. This work offers a scalable methodology to develop accurate commercial cooking emission inventories, thereby providing a scientific foundation for making targeted emission-reduction policies in commercial cooking.