Evaluating inaccurate pollen concentrations caused by turbulence using passive sampler

Aerobiologia ◽  
2021 ◽  
Author(s):  
Kenji Miki ◽  
Shigeto Kawashima ◽  
Satoshi Kobayashi ◽  
Shinji Takeuchi ◽  
Yi-Ting Tseng ◽  
...  
Keyword(s):  
Passive Sampler ◽  
Pollen Concentrations

98. Validation of a Passive Sampler for Ketones

1999 ◽  
Author(s):  
S. Tsai ◽  
S. Que Hee
Keyword(s):  
Passive Sampler

Evaluation of Short-Term CO₂ Passive Sampler for Monitoring Atmospheric CO₂ Levels

2016 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Bongbeen Yim ◽  
Yoon-Ah Sim ◽  
Sun-Tae Kim
Keyword(s):  
Passive Sampler ◽  
Short Term

scholarly journals Comparison of a novel passive sampler to standard water-column sampling for organic contaminants associated with wastewater effluents entering a New Jersey stream

Chemosphere ◽  
2005 ◽  
Vol 61 (5) ◽  
pp. 610-622 ◽  
Author(s):  
D.A. Alvarez ◽  
P.E. Stackelberg ◽  
J.D. Petty ◽  
J.N. Huckins ◽  
E.T. Furlong ◽  
...  
Keyword(s):  
New Jersey ◽  
Water Column ◽  
Organic Contaminants ◽  
Passive Sampler ◽  
Wastewater Effluents

scholarly journals EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

2013 ◽  
Vol 6 (6) ◽  
pp. 1961-1975 ◽  
Author(s):  
K. Zink ◽  
A. Pauling ◽  
M. W. Rotach ◽  
H. Vogel ◽  
P. Kaufmann ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Birch Pollen ◽  
Small Scale ◽  
Pollen Emission ◽  
Numerical Weather ◽  
Pollen Concentrations ◽  
Scale Modelling ◽  
Reactive Trace Gases

Abstract. Simulating pollen concentrations with numerical weather prediction (NWP) systems requires a parameterization for pollen emission. We have developed a parameterization that is adaptable for different plant species. Both biological and physical processes of pollen emission are taken into account by parameterizing emission as a two-step process: (1) the release of the pollen from the flowers, and (2) their entrainment into the atmosphere. Key factors influencing emission are temperature, relative humidity, the turbulent kinetic energy and precipitation. We have simulated the birch pollen season of 2012 using the NWP system COSMO-ART (Consortium for Small-scale Modelling – Aerosols and Reactive Trace Gases), both with a parameterization already present in the model and with our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced by using EMPOL.

Post-Katrina Changes in Ragweed Pollen Concentrations and Sensitivity Levels

2009 ◽  
Vol 123 (2) ◽  
pp. S96-S96
Author(s):  
W.E. Davis ◽  
H. Weaver ◽  
E. Levetin
Keyword(s):  
Ragweed Pollen ◽  
Pollen Concentrations

scholarly journals Trends and threshold exceedances analysis of airborne pollen concentrations in Metropolitan Santiago Chile

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0123077 ◽  
Author(s):  
Richard Toro A. ◽  
Alicia Córdova J. ◽  
Mauricio Canales ◽  
Raul G. E. Morales S. ◽  
Pedro Mardones P. ◽  
...  
Keyword(s):  
Airborne Pollen ◽  
Pollen Concentrations ◽  
Threshold Exceedances

scholarly journals Neural networks for increased accuracy of allergenic pollen monitoring

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty A. de Weger ◽  
...  
Keyword(s):  
Neural Networks ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Allergenic Pollen ◽  
Herbarium Specimens ◽  
Pollen Monitoring ◽  
Pollen Concentrations ◽  
Source Of Information ◽  
Urticaceae Pollen

AbstractMonitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

A Novel Personal Passive Sampler for Collecting Gaseous Phthalates

2021 ◽  
Author(s):  
Yun Hong ◽  
Chun-Yan Chen ◽  
Chen-Chou Wu ◽  
Lian-Jun Bao ◽  
Eddy Y. Zeng
Keyword(s):  
Passive Sampler
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