| 摘要: |
| 目的 建立科学有效的雾霾影响因素分析方法,解决成渝地区区域性中轻度大气污染问题。 方法 获取成渝
地区双城经济圈 2014—2022 年空气质量逐时监测数据,结合数据的嵌套结构特征,构建年度时间-站点-地区三水
平层次贝叶斯发展模型,并进行经典 OLS、IGLS 估计,经验贝叶斯和完全贝叶斯的对比分析,论证了完全贝叶斯方
法的优势。 结果 PM2. 5 浓度受大气污染物、气象、人口、经济、产业结构、农业生产综合因素影响,PM2. 5 浓度变化速
率受到 CO、SO2 和城镇化率的影响。 结论 利用层次模型建模分析具有嵌套多层次结构的雾霾监测数据,更科学合
理,再借助贝叶斯统计具有利用先验信息和学习机理的优势,更有助于提高模型参数估计和预测精度。 |
| 关键词: 层次贝叶斯 成渝地区双城经济圈 雾霾影响因素 |
| DOI： |
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| Analysis of Influencing Factors of Haze Monitoring in Chengdu-Chongqing Economic Circle Based onHierarchical Bayesian Model |
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LUO Lin1；YANG Haolan2；LI Yong3
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1. School of Big Data and Statistics Sichuan Tourism University Chengdu 610100 China
2. CMB Network Technology Chengdu 610095 China
3. School of Statistics Chengdu University of Information Technology Chengdu 610103 China
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| Abstract: |
| Objective A scientific and effective method for analyzing haze influencing factors is established to solve the
regional moderate and mild air pollution in the Chengdu-Chongqing area. Methods The hourly monitoring data of air
quality from 2014 to 2022 in Chengdu-Chongqing Economic Circle were obtained and the nested structure characteristics
of the monitoring data were used to construct a three-level Bayesian development model at the annual time-site-region
level and the comparative analysis of classical OLS IGLS estimation empirical Bayesian and complete Bayesian was
carried out which demonstrated the advantages of the complete Bayesian method. Results The PM2. 5
concentration is affected by comprehensive factors including air pollutants meteorology population economy industrial structure and
agricultural production and the change rate of PM2. 5 concentration is affected by CO SO2
and urbanization rate. Conclusion The use of hierarchical modeling to analyze haze monitoring data with nested multi-level structures is more scientific and reasonable. By incorporating Bayesian statistics which allows for the utilization of prior information and learning mechanisms it can further enhance the accuracy of model parameter estimation and prediction. |
| Key words: hierarchical Bayes Chengdu-Chongqing Economic Circle haze influencing factors |
