Numerical modelling of birch pollen dispersion in Canada.

Simulating allergenic tree pollen is important to protect sensitive population and to support bioaerosols monitoring effort. Using the regional air quality model GEM-MACH, a simulation was conducted adopting two new main hypotheses: 1) the use of vertical correlation concept to force the vertical dispersion (a method normally used in tracer data assimilation) and, 2) the use of a puff instead of a continuous pollen release. The simulation was compared with pollen observations in Montreal and with the corresponding statistical forecasts (issued daily by the Weather Network) at several locations in the province of Quebec and elsewhere. The comparison with the simulation was found satisfactory (outperform forecasts based on persistence or pollen calendar and is also superior to numerical simulation of tree pollen done elsewhere in North America). Simulation shows that, for the 2012 pollen season, the majority (88%) of the Betula pollen measured in Montreal originated from the Laurentides region. Another result of scientific importance obtained here is that Betula pollen episodes (observed or simulated birch pollen) in Montreal occur only when the average daily temperature is in the range of 10° to 18 °C. This research is considered as a first step in forecasting bioaerosols in Canada within an air quality model.

Trace elements in the pollen of Ambrosia artemisiifolia: what is the effect of soil concentrations?

Concentrations of nine trace elements (Ba, Cd, Cr, Cu, Mn, Ni, Pb, Tl and Zn) were measured in a plant bearing allergenic pollens (ragweed) and their transfers from soils to the roots and then to the pollens were investigated. The soil, roots and pollens collected from flowers were sampled at 26 urban sites. Soil pH, soil organic carbon and total-recoverable trace elements (TE) in soil, roots and pollens were measured. The three biogeochemical compartments are well discriminated according to their TE concentrations. The concentrations (in µg g(-1)) in pollens decreased as follow: Zn (59.5-205)>Mn (19.4-117)>Ba≈Cr≈Cu≈Ni≈Pb (0.54-27.7)>Cd (0.06-0.77)>>Tl (0.0015-0.0180). Mean elemental allocation within ragweed always favored roots over pollen but, at site level, inverse pattern is also observed mostly for Zn and slightly for Cu and Ni. Significant predictive models of TE concentrations in pollens were obtained using soil or root properties only for Cd, Ni and Pb. They all involved positive relationships between TE concentrations in pollens and in soil or roots. Estimates of short-term exposure of human to TE carried out by ragweed pollens indicate TE absorption of less than 50 ng, far below thresholds of air quality criteria. Investigating the TE chemistry of pollens is a required first step to validate the impact of TE in pollens on human health and on the prevalence and intensity of allergy symptoms and atopic diseases.

Bioclimatic indices as a tool in pollen forecasting.

The use of bioclimatic indices could be a major step forward in the methodology of pollen forecasting. The basis for this proposal is that simple meteorological parameters do not reflect the global status of the atmosphere, but merely some static measurements. However, pollen dispersal is, above all, a dynamic phenomenon, and this fact should be reflected in the variables we used to explain it. Here, we test the two methodologies for routine pollen forecasting by comparing correlation coefficients using the same daily Poaceae airborne pollen data base from León (6 years, from 1994 to 1999) as the dependent variable and either simple daily meteorological variables or compound daily bioclimatic indices as independent variables. Both simple and compound indices reproduced the same profile of evolution of plant eco-physiological requirements, as the length of the study period during the pollen season increased. However, for time frames larger than the main pollen period, bioclimatic indices gave superior coefficients, which seems to indicate that these could be more valuable for pre-season pollen forecasting. The continentality index produced the highest mean coefficient, higher than those generated by any meteorological variable. Furthermore, at least for a Mediterranean climate, site location and evapotranspiration in relation to precipitation seem to be the most promising factors for increasing success when forecasting Poaceae airborne pollen concentration.