北京城区气传花粉含量分季节预测模型  

Seasonal Prediction Model for Airborne Pollen Content in Beijing Urban Area

作　　者：郑祚芳 王耀庭 祁文 高华 ZHENG Zuo-fang;WANG Yao-ting;QI Wen;GAO Hua(Institute of Urban Meteorology,China Meteorological Administration,Beijing 100089,China;Key Laboratory of Urban Meteorology,China Meteorological Administration,Beijing 100089,China;Beijing Research Center for Urban Meteorological Engineering and Technology,Beijing 100089,China;Tongling Meteorological Bureau,Tongling 244061,China)

机构地区：[1]北京城市气象研究院,北京100089 [2]中国气象局城市气象重点开放实验室,北京100089 [3]北京城市气象工程技术研究中心,北京100089 [4]铜陵市气象局,铜陵244061

出　　处：《环境科学》2024年第11期6294-6300,共7页Environmental Science

基　　金：中国气象局城市气象重点开放实验室开放基金项目(LUM-2023-05)。

摘　　要：气传花粉是主要大气污染物的生物成分之一,可引起人群过敏反应,导致一系列过敏性疾病的发生,准确的花粉含量预测可给易感人群更有效的帮助.基于2021~2022年花粉季北京城区多站点实测数据,分析了花粉含量时空分布特征及与气象因子间的联系.发现花粉含量与气象因子间存在较一致的空间相关性,但这种相关性具有明显的季节性差异.在此基础上,应用格兰杰检验方法遴选出影响北京城区花粉含量的主要气象因子,结合支持向量机和多元线性回归理论分别建立了北京城区空气花粉含量分季节预测模型.应用2023年实测数据检验表明,两种分季节预测模型在2023年春季预测准确率分别为61.2%和60.1%,秋季预测准确率为68.1%和66.7%,性能均优于现有业务预测模型,尤其对重污染事件预测中的跨等级误差改善明显,为进一步完善北京地区花粉含量预测技术提供了新途径.Airborne pollen is considered to be one of the air pollutants that can cause allergic reactions in humans,leading to the occurrence or aggravation of a series of allergic diseases.The latest study showed that the positive rate of pollen allergens in allergic rhinitis patients in urban areas of Beijing exceeded 80%.Accurate prediction of pollen content could provide more effective assistance to susceptible populations.Based on the measured data from multiple stations in the urban area of Beijing during the pollen season from 2021 to 2022,the spatiotemporal distribution characteristics of pollen content were analyzed.The results showed that the main meteorological factors affecting spring pollen content in the urban area of Beijing were daily average wind speed,3-day average temperature,water vapor pressure,daily average,temperature,and accumulated temperature.The main meteorological factors affecting autumn pollen content were 3-day average temperature,water vapor pressure,minimum surface temperature,and daily average temperature.In addition,it was found that there was a consistent spatial correlation between the current air pollen content and meteorological elements in the urban area of Beijing,but this correlation had significant seasonal differences.Furthermore,the Granger causality test method was applied to select the main meteorological factors that affected airborne pollen content in the urban area of Beijing,and two prediction models for air pollen content in the Beijing urban area for different seasons were established based on the support vector machine method(SVM)and multiple linear regression theory.The test of the prediction results for 2023 showed that both the SVM model considering seasonal differences and the multiple linear regression model could predict the daily distribution trend of pollen content well.The overall correlation coefficients between the predicted pollen content and the measured values were 0.693 and 0.636(P<0.01),respectively.Additionally,both models had good predictive ability fo

关 键 词：气传花粉含量 格兰杰检验 预测模型 气象因子 机器学习 

分 类 号：X513[环境科学与工程—环境工程]