Background: Seasonal pollen is a common cause of allergic respiratory disease. In the United States, pollen monitoring occurs via manual counting, a method which is both labor-intensive and has a considerable time delay. In this paper, we report the field-testing results of a new, automated, real-time pollen imaging sensor in Atlanta, GA. Methods: We first compared the pollen concentrations measured by an automated real-time pollen sensor (APS-300, Pollen Sense LLC) collocated with a Rotorod M40 sampler in 2020 at an allergy clinic in northwest Atlanta. An internal consistency assessment was then conducted with two collocated APS-300 sensors in downtown Atlanta during the 2021 pollen season. We also investigated the spatial heterogeneity of pollen concentrations using the APS-300 measurements. Results: Overall, the daily pollen concentrations reported by the APS-300 and the Rotorod M40 sampler with manual counting were strongly correlated (r = 0.85) during the peak pollen season. The APS-300 reported fewer tree pollen taxa, resulting in a slight underestimation of total pollen counts. Both the APS-300 and Rotorod M40 reported Quercus (Oak) and Pinus (Pine) as dominant pollen taxa during the peak tree pollen season. Pollen concentrations reported by APS-300 in the summer and fall were less accurate. The daily total and speciated pollen concentrations reported by two collocated APS-300 sensors were highly correlated (r = 0.93–0.99). Pollen concentrations showed substantial spatial and temporal heterogeneity in terms of peak levels at three locations in Atlanta. Conclusions: The APS-300 sensor was able to provide internally consistent, real-time pollen concentrations that are strongly correlated with the current gold-standard measurements during the peak pollen season. When compared with manual counting approaches, the fully automated sensor has the significant advantage of being mobile with the ability to provide real-time pollen data. However, the sensor’s weed and grass pollen identification algorithms require further improvement.

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Field Evaluation of an Automated Pollen Sensor

Studies on the association of greenness with respiratory health are scarce in developing countries, and previous studies in China have focused on only one or two indicators of lung function.The study aims to evaluate the associations of residential greenness with full-spectrum lung function indicators and prevalence of chronic obstructive pulmonary disease (COPD).This nationwide cross-sectional survey included 50,991 participants from the China Pulmonary Health study. Lung function indicators included four categories: indicators of obstructive ventilatory dysfunction (FEV1, FVC and FEV1/FVC); an indicator of large-airway dysfunction (PEF); indicators of small-airway dysfunction (FEF25-75% and FEV3/FEV6); and other indicators. Residential greenness was assessed by the Normalized Difference Vegetation Index (NDVI). Multivariable linear regression models and logistic regression models were used to analyze associations of greenness with lung function and COPD prevalence.Within the 500 m buffer, an interquartile range (IQR) increase in NDVI was associated with higher FEV1 (24.76 mL), FVC (16.52 mL), FEV1/FVC (0.38), FEF50% (56.34 mL/s), FEF75% (33.43 mL/s), FEF25-75% (60.73 mL/s), FEV3 (18.59 mL), and FEV6 (21.85 mL). However, NDVI was associated with lower PEF. In addition, NDVI was significantly associated with 10% lower odds of COPD. The stratified analyses found that the associations were only significant in middle-young people, females, and nonsmokers. The associations were influenced by geographic regions.Residential greenness was associated with better lung function and lower odds of COPD in China. These findings provide a scientific basis for healthy community planning. 

Associations of residential greenness with lung function and chronic obstructive pulmonary disease in China.

Influence of meteorological parameters and air pollutants on the airborne pollen of city Chandigarh, India

Proposing a sustainable urban 3D model to minimize the potential risk associated with green infrastructure by applying engineering tools

Castanopsis is diffusely spread in tropical and subtropical regions and is an important nectar source plant in China. The Castanopsis honey (CH) is characterized by its bitter taste. However, its composition and functions remain unclear. In this study, the physicochemical parameters, chemical composition, and antioxidant capacity of CH were comprehensively investigated, with the anti-inflammatory effects of the Castanopsis honey extract (CHE) evaluated based on the RAW 264.7 cell inflammatory model. The results revealed a high level of quality in CH based on the quality standards. Among a total of 84 compounds identified in CH, 5 high response compounds and 29 phenols were further quantified by UPLC-Q/TOF-MS. The high content of phenylethylamine (117.58 ± 64.81 mg kg-1) was identified as a potential marker of CH. Furthermore, the CH showed evident antioxidant activities, and the anti-inflammatory activities of CHE were observed to inhibit the release of nitric oxide (NO) and reduce the content of tumor necrosis factor alpha (TNF-α) and improve the content of interleukin-10 (IL-10) by regulating the NF-κB pathway. Our study indicates that CH has sound physicochemical properties and biological activities with a high level of quality, providing strong experimental evidence to support the further economic and agricultural development and application of CH.

Chemical composition and anti-inflammatory activities of Castanopsis honey.

Pollen is an important component of bioaerosol and the distribution of pollen and its relationship with meteorological parameters can be analyzed to better prevent hay fever. Pollen assemblages can also provide basic data for analyzing the relationship between bioaerosol and PM. We collected 82 samples of airborne pollen using a TSP large flow pollen collector from June 1, 2015 to June 1, 2016, from central Zhanjiang city in South China. We also conducted a survey of the nearby vegetation at the same time, in order to characterize the major plant types and their flowering times. We then used data on daily temperature, relative humidity, precipitation, vapor pressure and wind speed from a meteorological station in the center of Zhanjiang City to assess the relationship between the distribution of airborne pollen and meteorological parameters. Our main findings and conclusions are as follows: (1) We identified 15 major pollen types, including Pinus, Castanopsis, Myrica, Euphorbiaceae, Compositae, Gramineae, Microlepia and Polypodiaceae. From the vegetation survey, we found that the pollen from these taxa represented more than 75% of local pollen, while the pollen of Podocarpus, Dacrydium and other regional pollen types represented less than 25%. (2) The pollen concentrations varied significantly in different seasons. The pollen concentrations were at a maximum in spring, consisting mainly of tree pollen; the pollen concentrations were at an intermediate level in autumn and winter, consisting mainly of herb pollen and fern spores; and the pollen concentrations in summer were the lowest, consisting mainly of fern spores. (3) Analysis of the relationship between airborne pollen concentrations and meteorological parameters showed that variations in the pollen concentrations were mainly affected by temperature and relative humidity. In addition, there were substantial differences in these relationships in different seasons. In spring, pollen concentrations were mainly affected by temperature; in summer, they were mainly affected by the direction of the maximum wind speed; in autumn, they were mainly affected by relative humidity and temperature; and in winter, they were mainly affected by relative humidity and wind speed. Temperature and relative humidity promote plant growth and flowering. Notably, the variable wind direction in summer and the increased wind speed in winter and spring are conductive to pollen transmission. (4) Of the 15 major pollen types, Moraceae, Artemisia and Gramineae are the main allergenic pollen types, with peaks in concentration during April-May, August-September, and October-December, respectively. (5) Atypical weather conditions have substantial effects on pollen dispersal. In South China, the pollen concentrations in the sunny day were usually significantly higher than that of the rainy day. The pollen concentrations increased in short rainy days, which usually came from the Herb and Fern pollen. The pollen concentrations decreased in continuous rainy days especially for the Tree and Shrub pollen. the pollen concentrations in the sunny days were usually significantly higher than that in the rainy days. The pollen concentrations increased in short and strong rainfall.

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Chen Chixin

Papers

Relationship between airborne pollen assemblages and major meteorological parameters in Zhanjiang, South China.