改进湿扫法模拟福岛事故中铯-137的空气扩散

Shuhan Zhuang, Shengjiang Fang, Xinwen Dong
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引用次数: 0

摘要

湿法清除过程是福岛第一核电站事故中铯-137空气扩散模拟的关键。尽管深入研究,湿扫模拟仍然受到湿扫建模和气象输入偏差造成的不确定性的影响。为了减少这些不确定性,利用了气象研究与预报化学(WRF-Chem)模式的在线耦合建模特征,并考虑了云内和云下的清除过程。本研究将云内方案Environ和云下方案Baklanov组合成environi - bakla来模拟Cs-137的湿沉降。基于FDNPP事故观测到的Cs-137的累积沉降和环境浓度,系统地将该模型与先前采用单一Baklanov云下方案的WRF-Chem模型进行了比较。结果表明,云内清除方案显著改善了枥木、中多里等小雨地区的累积沉降模拟。对于大气浓度,云内清除并不一定会改善性能,environni - bakla仅在羽流事件下无雨或小雨时表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Wet Scavenging Schemes for Air Dispersion Modeling of Cs-137 in the Fukushima Accident
Wet scavenging process is critical for air dispersion modeling of Cs-137 in the Fukushima Daiichi Nuclear power plant (FDNPP) accident. Although intensively investigated, wet scavenging simulation is still subject to uncertainties caused by the biases in wet scavenging modeling and meteorological input. To reduce these uncertainties, the on-line coupled modeling feature of the Weather Research and Forecasting-Chemistry (WRF-Chem) model was utilized and both the in-cloud and below-cloud scavenging processes are considered. In this study, the in-cloud scheme Environ and below-cloud scheme Baklanov are combined with each other to form Environ-Bakla to simulate the wet deposition of Cs-137. The model is systematically compared with a previous WRF-Chem model with a single below-cloud scheme Baklanov, based on both the cumulative deposition and ambient concentration of Cs-137 based on the FDNPP accident observation. The results demonstrate that the in-cloud scavenging scheme substantially improves the cumulative deposition simulation in regions with light rain like Tochigi, Nakadori etc. With respect to the atmospheric concentration, the inclusion of in-cloud scavenging doesn’t necessarily improve the performances and the Environ-Bakla only shows fair performance under plume events with no rain or light rain.
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