摘要: |
以2015年5月—2022年12月福清核电厂周边气溶胶总β活度浓度逐月监测数据为基础,运用统计学斯皮尔曼(Spearman)秩相关系数法探讨了监测点之间、监测点与对照点之间的相关关系,利用一元线性回归法分析了总β活度浓度与降雨量之间的关系。结果表明,总β活度浓度监测值与降雨量均表现为负相关,且没有明显的季节性。调研并比对分析了国内及美国压水堆核电厂周边气溶胶中总β放射性水平。探讨了整合移动平均自回归模型(ARIMA)在分析预测核电厂周围气溶胶中总β活度浓度的应用,建立并优化了适合福清核电厂周边气溶胶中总β活度浓度的预测模型ARIMA(2,1,1)(0,1,1),有助于开展福清核电厂周边气溶胶中总β活度浓度的预报和预警。 |
关键词: 福清核电厂 气溶胶 总β 整合移动平均自回归模型 |
DOI:DOI:10.3969/j.issn.1674-6732.2024.04.005 |
分类号:X837 |
基金项目:福建省新型智库项目(23MZKB26) |
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Analysis on Gross β Radioactivity Level in the Aerosol around Fuqing Nuclear Power Plant and Optimization of ARIMA Model Construction |
WANG Chunmei
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Fujian Radiation Environment Supervision Station, Fuzhou, Fujian 350013, China
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Abstract: |
Based on the monthly monitoring data of gross β activity concentration of aerosol around Fuqing nuclear power plant from May 2015 to December 2022, the correlation between monitoring points and between monitoring points and control points was discussed by statistical Spearman rank correlation coefficient method. The relationship between gross β and rainfall was analyzed by linear regression method. The monitoring value of gross β activity concentration was negatively correlated with rainfall, and there was no obvious seasonality. The gross β radioactivity levels in aerosols around PWR nuclear power plants in China and the United States were investigated and compared. The application of integrated moving average autoregressive model(ARIMA) in the analysis and prediction of gross β activity concentration in aerosol aroundnuclear power plant was discussed. The prediction model ARIMA(2,1,1)(0,1,1) suitable for the prediction of gross β activity concentration in aerosol around Fuqing nuclear power plant was established and optimized, which will be helpful for the prediction and early warning of gross β activity concentration in aerosol around Fuqing nuclear power plant. |
Key words: Fuqing Nuclear Power Plant Aerosol Gross β ARIMA |