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• W4377201210 abstract "PDF HTML阅读 XML下载 导出引用 引用提醒 北京主要气传致敏花粉年浓度峰值日期预测 DOI: 10.5846/stxb202202220416 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 北京市科技计划课题（Z191100009119013） Prediction of date of annual maximum concentration of main airborne allergenic pollen in Beijing Author: Affiliation: Fund Project: Beijing Municipal Science and Technology Project(Z191100009119013) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:花粉是我国北方引发过敏性鼻炎最主要过敏原，花粉症发病期与花粉浓度高峰期吻合。基于北京地区2012至2020年花粉季多站、逐日分类花粉浓度观测数据分析，得出北京地区花粉浓度在3月上旬至5月中旬（可进一步划分为3月中旬至4月上旬和4月下旬至5月上旬两个高峰期）和8月中旬至9月中旬分别存在两个高峰期，第一个高峰期内优势致敏花粉种类为柏科、杨柳科和松科，第二个高峰期内优势致敏花粉种类为桑科、菊科蒿属和藜科。根据优势致敏花粉年浓度峰值日期观测数据，使用与花粉采样站点位置相匹配的逐日气象观测数据累积值，基于作物模型概念和模糊逻辑原理建立了北京地区主要气传致敏花粉年浓度峰值日期预测模型。经检验，柏科、杨柳科、松科、桑科、菊科蒿属和藜科花粉模型预测准确率分别为87.8%、80.0%、64.4%、86.7%、78.8%和81.8%。基于北京地区主要气传致敏花粉年浓度峰值日期预测模型可为本地花粉症防治提供理论参考。 Abstract:The prevalence and severity of pollen-induced pollinosis has been increasing yearly worldwide in recent years. Pollen is the main allergen causing allergic rhinitis in North China and the onset period of airborne allergenic pollen-induced pollinosis coincides with the peak period of pollen concentration. As one of the mega-cities in the northern region of China, Beijing is becoming increasingly aware of the problems caused by allergenic pollen. Based on the analysis of 12 pollen sampling stations daily classified pollen concentration observation data during pollen season in Beijing from 2012 to 2020, there were two peak periods of pollen concentration in Beijing from early March to mid-May (it could be further divided into two peak periods from mid-March to early April and from late April to early May) and from mid-August to mid-September, respectively. The dominant allergenic pollen species in the first peak period were Cupressaceae, Salicaceae (from early March to mid-April, the annual average concentration accounted for 39.1% and 18.2% respectively) and Pinaceae (from mid-April to early May, the annual average concentration accounted for 18.2%), and the dominant allergenic pollen species in the second peak period were Moraceae, Artemisia and Chenopodiaceae (from mid-August to mid-September, the annual average concentration accounted for 34.4%, 30.4% and 12.7% respectively). The annual maximum concentration of dominant airborne allergenic pollen in Beijing varied significantly among stations and pollen seasons, and fluctuated significantly. In contrast, the variation of the dates of annual maximum pollen concentration of the same species is relatively stable, and its prediction research work is more meaningful for pollen-induced pollinosis control. Based on the observation data of annual maximum concentration of dominant airborne allergenic pollen and the cumulative value of daily meteorological observation data matched with the location of pollen sampling stations, a prediction model of date of annual maximum concentration of main airborne allergenic pollen in Beijing is established based on the principle of crop growth model and fuzzy logic. The results showed that the prediction accuracy of pollen models of Cupressaceae, Salicaceae, Pinaceae, Moraceae, Artemisia and Chenopodiaceae were 87.8%, 80.0%, 64.4%, 86.7%, 78.8% and 81.8%, respectively. Using a model based on fuzzy logic principle and driven by the cumulative values of daily meteorological elements for pollen annual maximum concentration date, combined with the high-resolution regional numerical weather prediction model in Beijing, we can make a reasonable prediction of the time of maximum pollen concentration of different airborne allergenic pollens and provide a theoretical reference for the prevention and control of local airborne allergenic pollen-induced pollinosis. 参考文献 相似文献 引证文献" @default.
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• W4377201210 title "Prediction of date of annual maximum concentration of main airborne allergenic pollen in Beijing" @default.
• W4377201210 doi "https://doi.org/10.5846/stxb202202220416" @default.
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