Fig 1.
(1) Pollen-sampling location. (2) Location of the meteorological monitoring station. Map sources: USGS The National Map Viewer (http://viewer.nationalmap.gov) and USGS Global Web—Enable LANSAT data (http://globalweld.cr.usgs.gov).
Table 1.
Pollen taxa analyzed in the Santiago de Chile Metropolitan Area in Chile.
Fig 2.
Time series of the total daily concentration of the airborne pollen grains (equal to the sum of the pollen grains from trees, grasses, weeds and indeterminate sources in grains m–3 day–1) collected over the study period (from the January 1, 2009, to December 31, 2013).
(a) Time series per year (top axis). (b) Average daily counts of the airborne pollen grains with their corresponding standard deviations for the five-year (bottom axis) and annual relative contribution of each group of pollens by the season, and (c) the relative contribution of each group per annual season (top axis). Average daily relative contribution of tree, grass, weed and indeterminate source pollens to the total amount of airborne pollen (bottom axis).
Table 2.
Total counts of the airborne pollen grains and counts of the airborne pollen grains per group (tree, grass, weed and indeterminate sources) per year and for the entire period of the study (expressed as grains m–3 year–1) and their corresponding average and standard deviation (SD) per year (expressed as grains m–3 year–1).
Fig 3.
Time series of the daily concentration of the airborne pollen grains (expressed as grains m–3 day–1) from trees, grasses, weeds and indeterminate sources over the period of the study (from January 1, 2009, to December 31, 2013).
(a) Time series of the tree pollen concentration (top axis); (b) time series of the concentrations of pollen from grasses, weeds and indeterminate sources (top axis); (c) average tree pollen grain counts per day and the corresponding standard deviations; (d) average grass-pollen and weed-pollen grain counts per day and their corresponding standard deviations; and (e) average counts of the pollen grains from indeterminate sources per day and their corresponding standard deviations.
Fig 4.
Average daily counts and relative contribution of the tree airborne pollen.
(a to j) Average daily counts of the pollen grains from the most representative tree taxa and their corresponding standard deviations (expressed as grains m–3 day–1). (k) Relative contribution of each tree taxon to the daily counts of the tree pollen grains.
Fig 5.
Average daily counts and relative contribution of the weed airborne pollen.
(a to j) Average daily counts of the pollen grains from the most representative weed taxa and their corresponding standard deviations (expressed as grains m–3 day–1). (k) Relative contribution of each taxon to the daily counts of the weed pollen grains.
Table 3.
Summary of the time trend analysis using the deseasoned Theil—Sen method from 2009–2013 for the pollen concentrations.
The table shows the median slope in % year−1.
Table 4.
Summary of the annual average (Avg), annual maximum (Max) and minimum (Min), with their respective standard deviations (SD) and the trend analysis using the deseasoned Theil—Sen method from 2009–2013 for the meteorological variables (temperature (T), daily average relative humidity (RH), daily predominant wind speed (ws) and wind direction (wd)).
Fig 6.
Bivariate polar plot of the weighted mean of the total pollen grain counts for the study site (concentric circles represent the wind speed in m s–1).
Table 5.
Summary of the total and average pollen grain counts for this study and for the study by Rojas and Roure (2001).
Fig 7.
Calendar of risk levels of the average total airborne pollen concentration per day (estimated from the data collected daily from 2009 to 2014) for the groups: (a) trees, (b) grasses, and (c) weeds. (d) total pollen.