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Influence of environmental factors on spatial and temporal variability of allergenic Artemisia pollen in Beijing, China
Agricultural and Forest Meteorology ( IF 6.2 ) Pub Date : 2021-12-11 , DOI: 10.1016/j.agrformet.2021.108690
Xiaoxin Qin 1 , Yiyin Li 1
Affiliation  

Artemisia pollen is an important allergen source of respiratory allergy in Beijing, China. However, there are few pollen stations using Burkard pollen traps in Beijing, and few reports on Artemisia pollen. This research is to analyze annual, daily and diurnal variations in Artemisia pollen concentration in four monitoring stations of Beijing during 2015–2018, and then to investigate their affecting factors. Artemisia pollen season starts in late July or early August, and ends in late September and early October. Daily peak appeared in late August or early September, and diurnal peak emerged during 06:00 - 10:00 or 17:00 - 20:00. Difference in vegetation coverage between urban (less than 1%) and suburban (27.2%) stations within 500 m greatly determined difference in SPI (Seasonal pollen index) between urban and suburban. Temperature and rainfall in the period prior to pollen season, together with the frequency and wind speed of dominant wind direction were responsible for annual variations of SPI. On a daily timescale, temperature was the most important factor influencing pollen concentration, explaining 18.6–43.9% of variance. In the course of the day, increase in temperature and decrease in relative humidity contributed to dehiscence of the anther in the early morning, leading to diurnal peak after sunrise. Wind may dilute or give a rise to the locally released pollen grains depending on the wind speed. High-intensity rainfall (intensity: > 2 mm h-1) had washing-off effects on pollen concentration in the atomosphere, Besides air masses originated from the southerly, northerly and northwesterly directions influenced daily pollen peak by long-range transport. Multiple regression model for each station was constructed to predict daily pollen concentration using previous pollen concentrations and previous meteorological variables in three years, explaining 51.8–75.3% of variance.

更新日期:2021-12-11
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