scholarly journals Pollen Explains Flu-Like and COVID-19 Seasonality

2020 ◽  
Author(s):  
Martijn J. Hoogeveen ◽  
Eric C.M. van Gorp ◽  
Ellen K. Hoogeveen
Keyword(s):  
Solar Radiation ◽  
The Netherlands ◽  
Predictive Model ◽  
Meteorological Data ◽  
Pollen Grains ◽  
Inverse Correlation ◽  
Inverse Association ◽  
Threshold Values ◽  
Inhibitory Effects ◽  
Total Pollen

AbstractCurrent models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be antiviral, anti-influenza and allergenic, plays a role in immuno-activation, and seems to create a bio-aerosol lowering the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics including COVID-19.We tested the Pollen-Flu Seasonality Theory for 2016–2020 flu-like seasons, including COVID-19, in The Netherlands with its 17 million inhabitants. We combined changes in flu-like incidence per 100K/Dutch citizens (code: ILI) with weekly pollen counts and meteorological data. Finally, a discrete, predictive model is tested using pollen and meteorological threshold values displaying inhibitory effects on flu-like incidence.We found a highly significant inverse association of r(224) = –.38 between pollen and changes in flu-like incidence corrected for incubation period, confirming our expectations for the 2019/2020 COVID-19 season. The associations become stronger when taking into account incubation time, which satisfies the temporality criteria. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = –.48 (p < .001) when thresholds of 610 total pollen grains/m3 per week, 120 allergenic pollen grains/m3 per week, and a solar radiation of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a supportive factor, temperature makes no difference, and relative humidity associates even with flu-like incidence increases.We conclude that pollen is a predictor for the inverse seasonality of flu-like epidemics including COVID-19, and solar radiation is a co-inhibitor. The observed seasonality of COVID-19 during Spring, suggests that COVID-19 may revive in The Netherlands after week 33, the start being preceded by the relative absence of pollen, and follows standard pollen-flu seasonality patterns.

scholarly journals Data Mining Methods to Detect Airborne Pollen of Spring Flowering Arboreal Taxa

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1801
Author(s):  
Estefanía González-Fernández ◽  
Sabela Álvarez-López ◽  
Alba Piña-Rey ◽  
María Fernández-González ◽  
Francisco Javier Rodríguez-Rajo
Keyword(s):  
Airborne Pollen ◽  
Meteorological Data ◽  
Pollen Allergy ◽  
Pollen Grains ◽  
Negative Influence ◽  
Positive Influence ◽  
Pollen Types ◽  
Thermal Amplitude ◽  
Total Pollen

Variations in the airborne pollen load are among the current and expected impacts on plant pollination driven by climate change. Due to the potential risk for pollen-allergy sufferers, this study aimed to analyze the trends of the three most abundant spring-tree pollen types, Pinus, Platanus and Quercus, and to evaluate the possible influence of meteorological conditions. An aerobiological study was performed during the 1993–2020 period in the Ourense city (NW Spain) by means of a Hirst-type volumetric sampler. Meteorological data were obtained from the ‘Ourense’ meteorological station of METEOGALICIA. We found statistically significant trends for the Total Pollen in all cases. The positive slope values indicated an increase in pollen grains over the pollen season along the studied years, ranging from an increase of 107 to 442 pollen grains. The resulting C5.0 Decision Trees and Rule-Based Models coincided with the Spearman’s correlations since both statistical analyses showed a strong and positive influence of temperature and sunlight on pollen release and dispersal, as well as a negative influence of rainfall due to washout processes. Specifically, we found that slight rainfall and moderate temperatures promote the presence of Pinus pollen in the atmosphere and a marked effect of the daily thermal amplitude on the presence of high Platanus pollen levels. The percentage of successful predictions of the C5.0 models ranged between 62.23–74.28%. The analysis of long-term datasets of pollen and meteorological information provides valuable models that can be used as an indicator of potential allergy risk in the short term by feeding the obtained models with weather prognostics.

scholarly journals Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 802
Author(s):  
Kristian Skeie ◽  
Arild Gustavsen
Keyword(s):  
Solar Radiation ◽  
Web Service ◽  
Meteorological Data ◽  
Surface Wind ◽  
Building Energy ◽  
Energy Performance ◽  
Geospatial Data ◽  
Weather Data ◽  
Building Site ◽  
Incident Solar Radiation

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

scholarly journals Calibration and Validation of ArcGIS Solar Radiation Tool for Photovoltaic Potential Determination in the Netherlands

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1865
Author(s):  
Bala Bhavya Kausika ◽  
Wilfried G. J. H. M. van Sark
Keyword(s):  
Solar Radiation ◽  
The Netherlands ◽  
Urban Areas ◽  
Input Data ◽  
Solar Irradiation ◽  
Energy Yield ◽  
Atmospheric Parameters ◽  
Factors Affecting ◽  
Calibration And Validation ◽  
Solar Radiation Model

Geographic information system (GIS) based tools have become popular for solar photovoltaic (PV) potential estimations, especially in urban areas. There are readily available tools for the mapping and estimation of solar irradiation that give results with the click of a button. Although these tools capture the complexities of the urban environment, they often miss the more important atmospheric parameters that determine the irradiation and potential estimations. Therefore, validation of these models is necessary for accurate potential energy yield and capacity estimations. This paper demonstrates the calibration and validation of the solar radiation model developed by Fu and Rich, employed within ArcGIS, with a focus on the input atmospheric parameters, diffusivity and transmissivity for the Netherlands. In addition, factors affecting the model’s performance with respect to the resolution of the input data were studied. Data were calibrated using ground measurements from Royal Netherlands Meteorological Institute (KNMI) stations in the Netherlands and validated with the station data from Cabauw. The results show that the default model values of diffusivity and transmissivity lead to substantial underestimation or overestimation of solar insolation. In addition, this paper also shows that calibration can be performed at different time scales depending on the purpose and spatial resolution of the input data.

Estimation of the total solar radiation from meteorological data

Solar Energy ◽  
1977 ◽  
Vol 19 (3) ◽  
pp. 307-311 ◽  
Author(s):  
J.A. Sabbagh ◽  
A.A.M. Sayigh ◽  
E.M.A. El-Salam
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Total Solar Radiation

scholarly journals Performance of different methods for reference evapotranspiration estimation in Jaíba, Brazil

2018 ◽  
Vol 22 (2) ◽  
pp. 83-89 ◽  
Author(s):  
Gustavo H. da Silva ◽  
Santos H. B. Dias ◽  
Lucas B. Ferreira ◽  
Jannaylton É. O. Santos ◽  
Fernando F. da Cunha
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Standard Method ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Air Humidity ◽  
Method Performance ◽  
Relative Air Humidity ◽  
Evapotranspiration Estimation ◽  
Missing Variables

ABSTRACT FAO Penman-Monteith (FO-PM) is considered the standard method for the estimation of reference evapotranspiration (ET0) but requires various meteorological data, which are often not available. The objective of this work was to evaluate the performance of the FAO-PM method with limited meteorological data and other methods as alternatives to estimate ET0 in Jaíba-MG. The study used daily meteorological data from 2007 to 2016 of the National Institute of Meteorology’s station. Daily ET0 values were randomized, and 70% of these were used to determine the calibration parameters of the ET0 for the equations of each method under study. The remaining data were used to test the calibration against the standard method. Performance evaluation was based on Willmott’s index of agreement, confidence coefficient and root-mean-square error. When one meteorological variable was missing, either solar radiation, relative air humidity or wind speed, or in the simultaneous absence of wind speed and relative air humidity, the FAO-PM method showed the best performances and, therefore, was recommended for Jaíba. The FAO-PM method with two missing variables, one of them being solar radiation, showed intermediate performance. Methods that used only air temperature data are not recommended for the region.

scholarly journals The seasonal variability of the amount of global solar radiation reaching the ground in urban and rural areas on the example of Warsaw and Belsk

2016 ◽  
Vol 20 (4) ◽  
pp. 29-37
Author(s):  
Kinga Nelken ◽  
Kamil Leziak
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Rural Area ◽  
Rural Areas ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Urban Station ◽  
Reverse Relationship ◽  
Urban And Rural Areas ◽  
The Relationship

AbstractThe aim of this paper is to determine the contemporary differences in the inflow of global solar radiation in Warsaw (urban station) and Belsk (rural station). The meteorological data used comprised daily sums of global solar radiation (in MJ•m−2) and the duration of sunshine (in hours) for the period 2008 2014. On clear days in spring and summer, the rural area receives more solar radiation in comparison to the urban area, whereas in autumn a reverse relationship occurs. On cloudy days in all seasons, the rural area receives more solar radiation than the urban area, and the relationship is the strongest in winter. Differences between urban and rural areas on cloudy days are smaller than those observed on clear days.

scholarly journals Empirical model based on meteorological parameters to estimate the global solar radiation in Nepal

BIBECHANA ◽  
2014 ◽  
Vol 11 ◽  
pp. 25-33
Author(s):  
Krishna R Adhikari ◽  
Shekhar Gurung ◽  
Binod K Bhattarai
Keyword(s):  
Solar Radiation ◽  
Empirical Model ◽  
Meteorological Data ◽  
Cost Effective ◽  
Developed Countries ◽  
Global Solar Radiation ◽  
Develop Model ◽  
Sunshine Hours ◽  
Linear Regression Technique ◽  
Meteorological Characteristic

Solar radiation is the best option and cost effective energy resources of this globe. Only a few stations are there in developing and under developed countries including Nepal to monitor solar radiation and sunshine hours to generate a rational and accurate solar energy database. In this study, daily global solar radiation, and ubiquitous meteorological data (temperature and relative humidity) rather than rarely available sunshine hours have been used for Biratnagar, Kathmandu, Pokhara and Jumla to derive regression constants and hence to develop an empirical model. The model estimated global solar radiation is found to be in close agreement with measured values of respective sites. The estimated values were compared with Angstrom-Prescott model and examined using the statistical tools. Thus, the linear regression technique can be used to develop model at any location in the world. The resultant model may then be used to estimate the missing data of solar radiation for the respective sites and also can be used to estimate global solar radiation for the locations of similar geographic and meteorological characteristic. DOI: http://dx.doi.org/10.3126/bibechana.v11i0.10376   BIBECHANA 11(1) (2014) 25-33

scholarly journals The effect of environmental factors on the growth of alfalfa in the field.

1962 ◽  
Vol 10 (4) ◽  
pp. 247-253
Author(s):  
G. Stanhill
Keyword(s):  
Environmental Factors ◽  
Solar Radiation ◽  
Root Growth ◽  
Air Temperature ◽  
Meteorological Data ◽  
Crop Canopy

DM production from a heavily fertilized lucerne crop grown at Gilat and irrigated daily was compared with potential photosynthesis calculated from meteorological data [see F.C.A. 12: 1940]. After corrections were applied for losses due to respiration, root growth and light wasted beneath the crop canopy, calculated amounts agreed well with those measured. The percentage of light utilized was 33% with cutting at 31-day intervals and 46% with cutting at 48-day intervals. DM production was correlated positively with solar radiation and negatively with air temperature.-R.B. (Abstract retrieved from CAB Abstracts by CABI’s permission)

scholarly journals Estimation of monthly global solar radiation in Buenos Aires: preliminary analysis

2014 ◽  
Vol 5 (1) ◽  
pp. 669-680
Author(s):  
Susan G. Lakkis ◽  
Mario Lavorato ◽  
Pablo O. Canziani
Keyword(s):  
Solar Radiation ◽  
Buenos Aires ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Estimation Accuracy ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Third Order ◽  
Sunshine Hours

Six existing models and one proposed approach for estimating global solar radiation were tested in Buenos Aires using commonly measured meteorological data as temperature and sunshine hours covering the years 2010-2013. Statistical predictors as mean bias error, root mean square, mean percentage error, slope and regression coefficients were used as validation criteria. The variability explained (R2), slope and MPE indicated that the higher precision could be excepted when sunshine hours are used as predictor. The new proposed approach explained almost 99% of the RG variability with deviation of less than ± 0.1 MJm-2day-1 and with the MPE smallest value below 1 %. The well known Ångström-Prescott methods, first and third order, was also found to perform for the measured data with high accuracy (R2=0.97-0.99) but with slightly higher MBE values (0.17-0.18 MJm-2day-1). The results pointed out that the third order Ångström type correlation did not improve the estimation accuracy of solar radiation given the highest range of deviation and mean percentage error obtained.  Where the sunshine hours were not available, the formulae including temperature data might be considered as an alternative although the methods displayed larger deviation and tended to overestimate the solar radiation behavior.

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