基于城市冠层模型的放射性物质大气扩散模拟

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清华大学辅仁网/2017-07-07

胡啸峰,黄弘(

),申世飞

Simulations of atmospheric dispersion of radioactive materials with the urban canopy model

Xiaofeng HU,Hong HUANG(

),Shifei SHEN

Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China

摘要:

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摘要该文基于城市冠层模型对中尺度放射性物质大气扩散进行了数值模拟,并探讨了模型参数对预测结果的影响。以日本福岛核泄漏事件为案例,利用中尺度数值模型WRF及其耦合的单层和多层城市冠层模型对事故后的放射性物质的大气扩散与沉降进行了数值模拟,并基于观测数据,对不同的城市冠层模型对应的模拟结果进行了比较。结果表明: 使用多层模型可以得到与观测值最接近的风场模拟结果; 对于近源区域的¹³⁷Cs的累积沉降量,使用单层模型的模拟值比使用多层模型或不使用城市冠层模型的模拟值更接近观测值; 对于远源区域的¹³¹I日沉降量,使用单层模型可得到与观测值更为接近的模拟结果,而对于远源区域的¹³⁷Cs日沉降量,使用多层模型得到的结果更接近观测值。

关键词 ：城市冠层模型(UCM),放射性物质,大气扩散,WRF模型

Abstract：The ability of the urban canopy model (UCM) to predict meso-scale atmospheric dispersion of radioactive materials is evaluated based on the Fukushima accident using the weather research and forecasting (WRF) model coupled with the single-layer and multi-layer UCM. The deposition of the radioactive materials is compared with observations for the different UCM. The results show that the multi-layer model gives the best simulations of the wind fields. Near the source, the single-layer model gives the best predictions of the accumulated ground deposition of ¹³⁷Cs, while in the area far from the source, the single-layer model performs the best for the daily deposition of ¹³¹I and the multi-layer model performs the best for the daily deposition of ¹³⁷Cs.

Key words：urban canopy model (UCM)radioactive material atmospheric dispersion weather research and forecasting (WRF) model

收稿日期: 2013-11-19 出版日期: 2015-03-17

基金资助:国家自然科学基金项目 (71373140);国家 “八六三” 高技术项目 (2012AA050907);清华大学自主科研计划项目 (2012Z10137)

引用本文:

胡啸峰,黄弘,申世飞. 基于城市冠层模型的放射性物质大气扩散模拟[J]. 清华大学学报（自然科学版）, 2014, 54(6): 711-718.
Xiaofeng HU,Hong HUANG,Shifei SHEN. Simulations of atmospheric dispersion of radioactive materials with the urban canopy model. Journal of Tsinghua University(Science and Technology), 2014, 54(6): 711-718.

链接本文:

http://jst.tsinghuajournals.com/CN/或 http://jst.tsinghuajournals.com/CN/Y2014/V54/I6/711

图表:

3重嵌套区域示意图

不同UCM下的风场模拟结果

算例	风速PBIAS/%	风速PRMSE/%	风向MBE/(°)
1	63.78	120.24	35.81
2	37.17	96.34	34.37
3	2.89	60.95	33.97

风速与风向的误差分析结果

算例	FAC10/%	R	FMS/%	GR_n
1	91.75	0.230 6	21.33	7
2	91.21	0.264 2	28.38	4
3	90.72	0.202 8	25.64	7

近源区域累积沉降量的评价结果

不同UCM下的¹³¹I的日沉降量

不同UCM下的¹³⁷Cs的日沉降量

指标	算例	误差/%
指标	算例	山形	茨城		枥木	群马	埼玉	千叶	东京
PBIAS (¹³¹I)	1	-22.15	-87.68	-63.23	-18.94	-77.97	-76.77	-86.02	14
	2	-28.06	-86.69	-68.03	-30.53	-76.84	-74.16	-84.36	13
	3	7.60	-84.46	-72.32	-26.26	-82.03	-82.85	-85.94	15
PRMSE (¹³¹I)	1	248.87	263.89	172.63	83.38	208.42	207.34	239.91	15
	2	219.56	260.99	176.32	92.36	207.16	193.19	236.38	11
	3	248.83	253.66	181.60	85.02	214.08	221.51	239.72	16
PBIAS(¹³⁷Cs)	1	-32.92	-49.08	110.77	329.13	36.40	-46.81	-31.50	14
	2	-39.52	-34.50	120.75	306.55	55.90	-48.58	-24.81	14
	3	-31.04	-39.02	98.42	369.30	8.65	-48.70	-32.79	14
PRMSE(¹³⁷Cs)	1	67.34	157.94	780.20	1241.68	417.43	108.37	87.07	16
	2	72.02	123.21	744.39	1166.65	501.62	137.27	57.67	14
	3	57.27	134.82	707.41	1374.59	278.94	107.55	94.51	12

远源区域日沉降量的误差计算结果

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