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Multi-point analysis of airborne Japanese cedar (Cryptomeria japonica D. Don) pollen by Pollen Robo and the relationship between pollen count and the severity of symptoms

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Abstract

An important theme related to aerobiology is the spatial distribution of airborne pollen, which is a final goal of our research efforts. In relation to this, pursuing the severity of pollinosis symptoms and problems with airborne pollen and allergens is required. In the past, we simulated the distribution of airborne Japanese cedar (Cryptomeria japonica D. Don) pollen (Kawashima and Takahashi in Grana 34:142–150, 1995, Grana 38:316–324, 1999). The simulation results of recent years will be published in the near future. At the time, it was not possible to compare the results of actual airborne pollen data observed from multiple points at the same time. However, now we can achieve this objective if using C. japonica pollen characteristics. The pollen is dispersed in large quantities over a long distance, remains in the air for a long time, and most airborne pollen at this time is C. japonica pollen. Recently, several automatic C. japonica pollen monitoring systems have been developed and deployed nationwide. Pollen Robo is one and is the most widely installed nationwide. In this study, we addressed Pollen Robo. First, we examined whether Pollen Robo can accurately count C. japonica pollen and found that Pollen Robo was useful during the major pollen season. However, it sometimes counts non-pollen particles and other pollen rather than C. japonica pollen. Therefore, it is not useful when a small amount of pollen is dispersed such as the start day of the pollen season. Next, we examined the daily dispersion of C. japonica pollen and it was shown that it is related to the distance between sampling locations. However, factors other than distance may be involved. Another matter of concern is the relationship between the number of airborne pollen and pollinosis symptoms. Symptoms began to appear from approximately the start day of the pollen season in moderate and light cases. The most serious symptoms occurred when the pollen count was the highest. Meanwhile, in severe cases, symptoms were observed at the time the pollen was scarcely detected and plateaued when the pollen count reached 100 counts/m3 on average over 6 days. Thus, Pollen Robo was not useful when symptoms began in severe cases. This problem was solved using pollen antigen measurement. The time for the symptoms to begin in severe cases is between 2 and 4 weeks before the start day of the pollen season. The amount of Cry j 1 on the start day during some years was considerably larger than that calculated from the number of pollen. The results obtained in this study will be the basic data used for achieving our final goal.

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Acknowledgements

We thank Dr. Sahashi, N., the Executive Secretary of the Pollen Information Association, Mr. Nakanishi, H. the Managing Director of “Hanakosan”, and the Atmospheric Environmental Division, Ministry of the Environment of Japan, who permitted the use of the pollen data. We appreciate suggestive comments of two anonymous reviewers. We would like to thank Editage (www.editage.jp) for English language editing.

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Authors and Affiliations

  1. Department of Otolaryngology, Head and Neck Surgery, Faculty of Medicine, Yamagata University, Yamagata, 990-9585, Japan

    Yuichi Takahashi, Yusuke Suzuki & Seiji Kakehata

  2. Department of Otolaryngology, Tohoku Medical and Pharmaceutical University, Sendai, 981-8558, Japan

    Nobuo Ohta

  3. Graduate School of Agriculture, Kyoto University, Kyoto, 611-0011, Japan

    Shigeto Kawashima

  4. The Yamagata Prefectural Institute of Public Health, Yamagata, 990-0031, Japan

    Kumiko Mogami

  5. Pollen Project Team, Weathernews Inc, Chiba, 261-0023, Japan

    Yuya Yamashita, Ayumi Kusada & Shingo Ozu

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  1. Yuichi Takahashi
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Correspondence to Yuichi Takahashi.

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Takahashi, Y., Suzuki, Y., Ohta, N. et al. Multi-point analysis of airborne Japanese cedar (Cryptomeria japonica D. Don) pollen by Pollen Robo and the relationship between pollen count and the severity of symptoms. Aerobiologia 35, 635–646 (2019). https://doi.org/10.1007/s10453-019-09603-0

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  • DOI: https://doi.org/10.1007/s10453-019-09603-0

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