Daria Bilińska-Prałat, Małgorzata Werner, Maciej Kryza, Małgorzata Malkiewicz, Piotr Rapiejko, Kazimiera Chłopek, Katarzyna Dąbrowska-Zapart, Agnieszka Lipiec, Dariusz Jurkiewicz, Ewa Kalinowska, Barbara Majkowska-Wojciechowska, Dorota Myszkowska, Krystyna Piotrowska-Weryszko, Małgorzata Puc, Anna Rapiejko, Grzegorz Siergiejko, Elżbieta Weryszko-Chmielewska, Andrzej Wieczorkiewicz, Monika Ziemianin
{"title":"HYSPLIT模型在波兰桦树花粉建模中的应用","authors":"Daria Bilińska-Prałat, Małgorzata Werner, Maciej Kryza, Małgorzata Malkiewicz, Piotr Rapiejko, Kazimiera Chłopek, Katarzyna Dąbrowska-Zapart, Agnieszka Lipiec, Dariusz Jurkiewicz, Ewa Kalinowska, Barbara Majkowska-Wojciechowska, Dorota Myszkowska, Krystyna Piotrowska-Weryszko, Małgorzata Puc, Anna Rapiejko, Grzegorz Siergiejko, Elżbieta Weryszko-Chmielewska, Andrzej Wieczorkiewicz, Monika Ziemianin","doi":"10.1007/s10453-021-09737-0","DOIUrl":null,"url":null,"abstract":"<div><p>In this work, the HYSPLIT model was used to reproduce birch pollen concentrations in Poland for the years 2015 and 2016, where there was significant variation in terms of pollen concentrations and start/end dates of the pollen season. The analysis of pollen observations showed that the seasonal pollen integral (SPIn) was low in 2015 with a shorter season compared to 2016. In 2016, SPIn was unusually high. The HYSPLIT model simulation, with a one-hour temporal resolution, was conducted during the birch pollen season (from March to May) for 2015 and 2016. Meteorological data were obtained from the WRF model. The birch coverage map of the European Forest Institute was used. The emission, introduced to the model, covered Central Europe with a resolution of 0.3° × 0.3°. The results were compared to data from 11 observation stations in Poland. The measured birch pollen concentrations for 2015 were overestimated by HYSPLIT at 8 of the 11 stations (normalized mean bias/NMB from 0.13 to 2.53) and underestimated for three stations (NMB from − 0.44 to − 0.15). For 2016, the model highly underestimated the pollen concentrations, with NMB ranging from − 0.45 to − 0.93. In general, the results show that the model can resolve the main peaks of pollen concentrations, which is a step forward in the application of the HYSPLIT model for birch pollen forecasting over Poland. We suggest the application of methods that can reduce the bias of temperature such as meteorological data assimilation or bias correction, which could improve calculation of the start of emissions and consequently the start of the pollen season as well as pollen concentrations.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"38 1","pages":"103 - 121"},"PeriodicalIF":2.2000,"publicationDate":"2022-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10453-021-09737-0.pdf","citationCount":"2","resultStr":"{\"title\":\"Application of the HYSPLIT model for birch pollen modelling in Poland\",\"authors\":\"Daria Bilińska-Prałat, Małgorzata Werner, Maciej Kryza, Małgorzata Malkiewicz, Piotr Rapiejko, Kazimiera Chłopek, Katarzyna Dąbrowska-Zapart, Agnieszka Lipiec, Dariusz Jurkiewicz, Ewa Kalinowska, Barbara Majkowska-Wojciechowska, Dorota Myszkowska, Krystyna Piotrowska-Weryszko, Małgorzata Puc, Anna Rapiejko, Grzegorz Siergiejko, Elżbieta Weryszko-Chmielewska, Andrzej Wieczorkiewicz, Monika Ziemianin\",\"doi\":\"10.1007/s10453-021-09737-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this work, the HYSPLIT model was used to reproduce birch pollen concentrations in Poland for the years 2015 and 2016, where there was significant variation in terms of pollen concentrations and start/end dates of the pollen season. The analysis of pollen observations showed that the seasonal pollen integral (SPIn) was low in 2015 with a shorter season compared to 2016. In 2016, SPIn was unusually high. The HYSPLIT model simulation, with a one-hour temporal resolution, was conducted during the birch pollen season (from March to May) for 2015 and 2016. Meteorological data were obtained from the WRF model. The birch coverage map of the European Forest Institute was used. The emission, introduced to the model, covered Central Europe with a resolution of 0.3° × 0.3°. The results were compared to data from 11 observation stations in Poland. The measured birch pollen concentrations for 2015 were overestimated by HYSPLIT at 8 of the 11 stations (normalized mean bias/NMB from 0.13 to 2.53) and underestimated for three stations (NMB from − 0.44 to − 0.15). For 2016, the model highly underestimated the pollen concentrations, with NMB ranging from − 0.45 to − 0.93. In general, the results show that the model can resolve the main peaks of pollen concentrations, which is a step forward in the application of the HYSPLIT model for birch pollen forecasting over Poland. We suggest the application of methods that can reduce the bias of temperature such as meteorological data assimilation or bias correction, which could improve calculation of the start of emissions and consequently the start of the pollen season as well as pollen concentrations.</p></div>\",\"PeriodicalId\":7718,\"journal\":{\"name\":\"Aerobiologia\",\"volume\":\"38 1\",\"pages\":\"103 - 121\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-01-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10453-021-09737-0.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aerobiologia\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10453-021-09737-0\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerobiologia","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10453-021-09737-0","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Application of the HYSPLIT model for birch pollen modelling in Poland
In this work, the HYSPLIT model was used to reproduce birch pollen concentrations in Poland for the years 2015 and 2016, where there was significant variation in terms of pollen concentrations and start/end dates of the pollen season. The analysis of pollen observations showed that the seasonal pollen integral (SPIn) was low in 2015 with a shorter season compared to 2016. In 2016, SPIn was unusually high. The HYSPLIT model simulation, with a one-hour temporal resolution, was conducted during the birch pollen season (from March to May) for 2015 and 2016. Meteorological data were obtained from the WRF model. The birch coverage map of the European Forest Institute was used. The emission, introduced to the model, covered Central Europe with a resolution of 0.3° × 0.3°. The results were compared to data from 11 observation stations in Poland. The measured birch pollen concentrations for 2015 were overestimated by HYSPLIT at 8 of the 11 stations (normalized mean bias/NMB from 0.13 to 2.53) and underestimated for three stations (NMB from − 0.44 to − 0.15). For 2016, the model highly underestimated the pollen concentrations, with NMB ranging from − 0.45 to − 0.93. In general, the results show that the model can resolve the main peaks of pollen concentrations, which is a step forward in the application of the HYSPLIT model for birch pollen forecasting over Poland. We suggest the application of methods that can reduce the bias of temperature such as meteorological data assimilation or bias correction, which could improve calculation of the start of emissions and consequently the start of the pollen season as well as pollen concentrations.
期刊介绍:
Associated with the International Association for Aerobiology, Aerobiologia is an international medium for original research and review articles in the interdisciplinary fields of aerobiology and interaction of human, plant and animal systems on the biosphere. Coverage includes bioaerosols, transport mechanisms, biometeorology, climatology, air-sea interaction, land-surface/atmosphere interaction, biological pollution, biological input to global change, microbiology, aeromycology, aeropalynology, arthropod dispersal and environmental policy. Emphasis is placed on respiratory allergology, plant pathology, pest management, biological weathering and biodeterioration, indoor air quality, air-conditioning technology, industrial aerobiology and more.
Aerobiologia serves aerobiologists, and other professionals in medicine, public health, industrial and environmental hygiene, biological sciences, agriculture, atmospheric physics, botany, environmental science and cultural heritage.