Species and quantity of airborne pollens in Shanghai as monitored by gravitational and volumetric methods

Sun, Lan; Xu, Yanhua; Wang, Yiwei; Lou, Yueyan; Guo, Yao

doi:10.12932/ap0743

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Previous studies have shown that pollen concentrations evaluated by volumetric samplers and passive samplers have clear correlations (Bricchi et al, 2000;Sun et al, 2017). Conversely, it has been stated that volumetric and gravitational methods have virtually no correlation (Cornell et al, 1961).…”

Section: Introductionmentioning

confidence: 99%

Evaluating inaccurate pollen concentrations caused by turbulence using passive sampler

et al. 2021

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Understanding the atmospheric concentration of pollen (which is one of the most common vectors of allergens) is necessary to determine the atmospheric allergen level. Airborne pollen concentrations were predominantly evaluated using volumetric and gravitational particle samplers. However, no previous studies have successfully shown whether these sampling methods can be used to evaluate actual airborne pollen concentrations. In this study, the relationship between wind speed and sampling efficiency was investigated to determine whether the influence of ambient wind speed on sampling efficiency was significant. To this end, the influence of wind speed was analyzed by comparing a volumetric sampler and a gravitational sampler. The experimental results indicate that an increase in the wind speed results in an increase in the sampling efficiency of the gravitational sampler because of fluctuations in the turbulence. Our simulation shows that when pollen is entrained in the turbulence, the changes in the wind speed, turbulence amplitude, and turbulence length influence the deposition rate of pollen on the gravitational sampler. These influences can be explained by the turbulence vibration model. These results show the inadequacy of existing evaluation methods, not only for pollen deposition data, but also for all types of bioaerosol deposition data.

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Section: Introductionmentioning

confidence: 99%

Evaluating inaccurate pollen concentrations caused by turbulence using passive sampler

et al. 2021

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“…However, while these instruments can improve the portability of the systems, they still rely on the same off-line particle enrichment and manual counting methods used in the traditional samplers [23,24]. The particle counting with a microscope requires well-trained operators and is highly time-consuming and labor-intensive [25,26].…”

Section: Introductionmentioning

confidence: 99%

An integrated system for automated measurement of airborne pollen based on electrostatic enrichment and image analysis with machine vision

Yang

Klinkenberg

Pan

et al. 2022

Talanta

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“…Several studies of pollen diversity illustrated the variation of dominant airborne pollen types collected from different regions and in different seasons. Countries/cities that reported tree pollen as the dominant type during pollen season include Japan (e.g., Japanese cedar and Japanese cypress), Shanghai (e.g., Broussonetia), and most parts of America (e.g., oak, ash, and birch) (13)(14)(15). On the other hand, grass pollen is dominant in Portugal, North-West Turkey, West Bengal (India), South Korea, and Thailand (16)(17)(18)(19)(20).…”

Section: Introductionmentioning

confidence: 99%

Exploring the effects of seasons, diurnal cycle, and heights on airborne pollen load in a Southeast Asian atmospheric condition

Juprasong

Sirirakphaisarn

Siriwattanakul

et al. 2022

Front. Public Health

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IntroductionAeropollen can induce detrimental effects, particularly in respiratory airways. Monitoring local aeropollen is essential for the management of pollen allergic patients in each area. However, without resources for constant monitoring, pollen counts are subjected to biases imposed by the choices of sampling season, time of collection, and location. Therefore, the effects of these factors must be better understood. This study investigated the dynamics of aeropollen types through seasonal variation, diurnal cycle and different heights from the ground in Bangkok, Thailand.MethodsAeropollen samples were collected for 12 months at the Faculty of Science, Mahidol University in Bangkok, using a RotoRod Sampler®. For the investigation of diurnal effect, pollen was collected at 7 a.m., 10 a.m., 1 p.m., 4 p.m., and 7 p.m. For the study of height effect, data were collected at 2, 10, and 18 meters above ground.Results and discussionThis is the first study of the effects of diurnal cycle and height variation on airborne pollen count in Southeast Asia. The results showed the highest concentration of aeropollen was observed in November, which was at the beginning of the northeast monsoon season in Bangkok, whereas the lowest concentration was recorded in July (rainy season). Interestingly, the lowest airborne pollen concentration recorded in July was greater than the high level of most standards. Grass pollen was found as the major aeropollen. The highest total pollen concentration was detected at 1 p.m. The maximum pollen quantity was detected at 10 meters from the ground. However, the total aeropollen concentration was extremely high (>130 grains/m3) at all elevated heights compared to other studies that mostly found at lower height (approximately 1–2 m above ground). The result suggested that pollen concentrations of most pollen types increased as height increased. This study also illustrated the correlation between aeropollen quantity and local meteorological factors.ConclusionThis aeropollen survey reported that pollen concentration and diversity were affected by seasonal variation, diurnal cycle, and height from the ground. Understanding these relationships can help with predictions of aeropollen type and quantity.

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Species and quantity of airborne pollens in Shanghai as monitored by gravitational and volumetric methods

Cited by 6 publications

References 12 publications

Evaluating inaccurate pollen concentrations caused by turbulence using passive sampler

Evaluating inaccurate pollen concentrations caused by turbulence using passive sampler

An integrated system for automated measurement of airborne pollen based on electrostatic enrichment and image analysis with machine vision

Exploring the effects of seasons, diurnal cycle, and heights on airborne pollen load in a Southeast Asian atmospheric condition

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