ABSTRACT
Mercury (Hg) exchange at the plant leaf-atmosphere interface is an important issue when considering vegetation as a sink or source of this global pollutant. The aim of the study described here was to clarify this process by studying Hg exchange under laboratory conditions with a plant model, namely Epipremnum aureum. The desorption and absorption processes were studied under similar conditions in natural daylight. Hg exchange was measured at the foliar surface, and micrometeorological parameters and stomatal conductance were assessed. The results of the Hg exchange study showed different rhythms for the two processes, i.e. desorption (14-196 ng m-2 day-1) was slower than absorption (170-1341 ng m-2 day-1). The daily cycle was more complex in the desorption process, with a maximum when stomatal conductance was high but also with high values during nocturnal hours and a trend to absorption in the mornings. The daily absorption cycles were relatively simple, with values that coincided with positive stomatal conductance values and null values during nocturnal hours. The main factors involved in desorption were stomatal conductance and temperature, but other factors may need to be considered. The absorption process only involved total gaseous Hg, stomatal conductance and relative humidity. A net balance of the two experiments provided data on the amount of Hg transferred per unit leaf area (167 ng m-2 for desorption and 9213 ng m-2 for absorption), which implies total amounts of 23 ng of Hg desorbed and 1280 ng absorbed during the whole experiment. Finally, the reversible/non-reversible nature of the Hg exchange process must be reconsidered bearing in mind that Hg within the leaf can be emitted if changes in ambient conditions are appropriate to favour this process.
Subject(s)
Air Pollutants/metabolism , Araceae/metabolism , Environmental Monitoring , Mercury/metabolism , Plant Leaves/physiology , Absorption, PhysiologicalABSTRACT
Techniques of remote sensing are being used to develop phenological studies. Our goal is to study the correlation among the Normalized Difference Vegetation Index (NDVI) related with oak trees included in three set data polygons (15, 25 and 50â¯km to aerobiological sampling point as NDVI-15, 25 and 50), and oak (Quercus) daily average pollen counts from 1994 to 2013. The study was developed in the SW Mediterranean region with continuous pollen recording within the mean pollen season of each studied year. These pollen concentrations were compared with NDVI values in the locations containing the vegetation under a study based on two cartographic sources: the Extremadura Forest Map (MFEx) of Spain and the Fifth National Forest Inventory (IFN5) from Portugal. The importance of this work is to propose the relationship among data related in space and time by Spearman and Granger causality tests. 9 out of 20 studied years have shown significant results with the Granger causality test between NDVI and pollen concentration, and in 12â¯years, significant values were obtained by Spearman test. The distances of influence on the contribution of Quercus pollen to the sampler showed statistically significant results depending on the year. Moreover, a predictive model by using Artificial Neural Network (ANN) was applied with better results in NDVI25 than for NDVI15 or NDVI50. The addition of NDVI25 with the lag of 5â¯days and some weather parameters in the model was applied with a RMSE of 4.26 (Spearman coefficient râ¯=â¯0.77) between observed and predicted values. Based on these results, NDVI seems to be a useful parameter to predict airborne pollen.