Quantifying the Influence of a Burn Event on Ammonia Concentrations Using a Machine-Learning Technique

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Abstract

Although combustion is considered a common source of ammonia (NH3) in the atmo-sphere, field measurements quantifying such emissions of NH3 are still lacking. In this study, online measurements of NH3 were performed by a cavity ring-down spectrometer, in the cold season at a rural site in Xianghe on the North China Plain. We found that the NH3 concentrations were mostly below 65 ppb during the study period. However, from 18 to 21 November 2017, a close burn event (~100 m) increased the NH3 concentrations to 145.6 ± 139.9 ppb. Using a machine-learning technique, we quantified that this burn event caused a significant increase in NH3 concentrations by 411%, compared with the scenario without the burn event. In addition, the ratio of ∆NH3 /∆CO during the burn period was 0.016, which fell in the range of biomass burning. Future investigations are needed to evaluate the impacts of the NH3 combustion sources on air quality, ecosystems, and climate in the context of increasing burn events worldwide.

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Hu, J., Liao, T., Lü, Y., Wang, Y., He, Y., Shen, W., … Pan, Y. (2022). Quantifying the Influence of a Burn Event on Ammonia Concentrations Using a Machine-Learning Technique. Atmosphere, 13(2). https://doi.org/10.3390/atmos13020170

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