<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pinho, P</style></author><author><style face="normal" font="default" size="100%">Llop, E</style></author><author><style face="normal" font="default" size="100%">Ribeiro, M C</style></author><author><style face="normal" font="default" size="100%">Cruz, C</style></author><author><style face="normal" font="default" size="100%">Soares, A</style></author><author><style face="normal" font="default" size="100%">Pereira, M J</style></author><author><style face="normal" font="default" size="100%">Branquinho, C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tools for determining critical levels of atmospheric ammonia under the influence of multiple disturbances</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Pollution</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">ammonia</style></keyword><keyword><style  face="normal" font="default" size="100%">Ammonia: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Atmosphere</style></keyword><keyword><style  face="normal" font="default" size="100%">Atmosphere: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">Critical thresholds</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Eutrophication</style></keyword><keyword><style  face="normal" font="default" size="100%">Functional groups</style></keyword><keyword><style  face="normal" font="default" size="100%">Global change</style></keyword><keyword><style  face="normal" font="default" size="100%">lichens</style></keyword><keyword><style  face="normal" font="default" size="100%">Lichens: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Lichens: classification</style></keyword><keyword><style  face="normal" font="default" size="100%">nitrogen</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier Ltd</style></publisher><volume><style face="normal" font="default" size="100%">188</style></volume><pages><style face="normal" font="default" size="100%">88-93</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Critical levels (CLEs) of atmospheric ammonia based on biodiversity changes have been mostly calculated using small-scale single-source approaches, to avoid interference by other factors, which also influence biodiversity. Thus, it is questionable whether these CLEs are valid at larger spatial scales, in a multi- disturbances context. To test so, we sampled lichen diversity and ammonia at 80 sites across a region with a complex land-cover including industrial and urban areas. At a regional scale, confounding factors such as industrial pollutants prevailed, masking the CLEs. We propose and use a new tool to calculate CLEs by stratifying ammonia concentrations into classes, and focusing on the highest diversity values. Based on the significant correlations between ammonia and biodiversity, we found the CLE of ammonia for Mediterranean evergreen woodlands to be 0.69 mgm?3, below the previously accepted value of 1.9 mgm?3, and below the currently accepted pan-European CLE of 1.0 mgm?3</style></abstract><accession-num><style face="normal" font="default" size="100%">24568792</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">de Andrés, Juan Manuel</style></author><author><style face="normal" font="default" size="100%">Borge, Rafael</style></author><author><style face="normal" font="default" size="100%">de la Paz, David</style></author><author><style face="normal" font="default" size="100%">Lumbreras, Julio</style></author><author><style face="normal" font="default" size="100%">Rodríguez, Encarnación</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementation of a module for risk of ozone impacts assessment to vegetation in the Integrated Assessment Modelling system for the Iberian Peninsula. Evaluation for wheat and Holm oak.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: toxicity</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">CMAQ WRF</style></keyword><keyword><style  face="normal" font="default" size="100%">Critical level</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">iberian peninsula</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone risk assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: toxicity</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: drug effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Stomatal conductance</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum: drug effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum: growth &amp; development</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/22398018</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">165</style></volume><pages><style face="normal" font="default" size="100%">25 - 37</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A module to estimate risks of ozone damage to vegetation has been implemented in the Integrated Assessment Modelling system for the Iberian Peninsula. It was applied to compute three different indexes for wheat and Holm oak; daylight AOT40 (cumulative ozone concentration over 40 ppb), cumulative ozone exposure index according to the Directive 2008/50/EC (AOT40-D) and POD(Y) (Phytotoxic Ozone Dose over a given threshold of Y nmol m(-2) s(-1)). The use of these indexes led to remarkable differences in spatial patterns of relative ozone risks on vegetation. Ozone critical levels were exceeded in most of the modelling domain and soil moisture content was found to have a significant impact on the results. According to the outputs of the model, daylight AOT40 constitutes a more conservative index than the AOT40-D. Additionally, flux-based estimations indicate high risk areas in Portugal for both wheat and Holm oak that are not identified by AOT-based methods.</style></abstract><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Elsevier Ltd&lt;br/&gt;accession-num: 22398018</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alonso, Rocío</style></author><author><style face="normal" font="default" size="100%">Vivanco, Marta G</style></author><author><style face="normal" font="default" size="100%">González-Fernández, Ignacio</style></author><author><style face="normal" font="default" size="100%">Bermejo, Victoria</style></author><author><style face="normal" font="default" size="100%">Palomino, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Garrido, Juan Luis</style></author><author><style face="normal" font="default" size="100%">Elvira, Susana</style></author><author><style face="normal" font="default" size="100%">Salvador, Pedro</style></author><author><style face="normal" font="default" size="100%">Artíñano, Begoña</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling the influence of peri-urban trees in the air quality of Madrid region (Spain).</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">air pollution</style></keyword><keyword><style  face="normal" font="default" size="100%">Air pollution removal</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollution: statistics &amp; numerical data</style></keyword><keyword><style  face="normal" font="default" size="100%">Air quality models</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">Cities</style></keyword><keyword><style  face="normal" font="default" size="100%">Dry deposition</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Urban forest</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier Ltd</style></publisher><volume><style face="normal" font="default" size="100%">159</style></volume><pages><style face="normal" font="default" size="100%">2138-2147</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Tropospheric ozone (O(3)) is considered one of the most important air pollutants affecting human health. The role of peri-urban vegetation in modifying O(3) concentrations has been analyzed in the Madrid region (Spain) using the V200603par-rc1 version of the CHIMERE air quality model. The 3.7 version of the MM5 meteorological model was used to provide meteorological input data to the CHIMERE. The emissions were derived from the EMEP database for 2003. Land use data and the stomatal conductance model included in CHIMERE were modified according to the latest information available for the study area. Two cases were considered for the period April-September 2003: (1) actual land use and (2) a fictitious scenario where El Pardo peri-urban forest was converted to bare-soil. The results show that El Pardo forest constitutes a sink of O(3) since removing this green area increased O(3) levels over the modified area and over down-wind surrounding areas.</style></abstract><accession-num><style face="normal" font="default" size="100%">21269745</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Figueira, Rui</style></author><author><style face="normal" font="default" size="100%">Tavares, Paula C.</style></author><author><style face="normal" font="default" size="100%">Palma, Luís</style></author><author><style face="normal" font="default" size="100%">Beja, Pedro</style></author><author><style face="normal" font="default" size="100%">Sérgio, Cecília</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of indicator kriging to the complementary use of bioindicators at three trophic levels.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Bioindicators</style></keyword><keyword><style  face="normal" font="default" size="100%">birds</style></keyword><keyword><style  face="normal" font="default" size="100%">Birds: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: instrumentation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: statistics &amp; numerical d</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicator kriging</style></keyword><keyword><style  face="normal" font="default" size="100%">Indices</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Mosses</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19477568</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">157</style></volume><pages><style face="normal" font="default" size="100%">2689 - 2696</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The use of biological indicators is widespread in environmental monitoring, although it has long been recognised that each bioindicator is generally associated with a range of potential limitations and shortcomings. To circumvent this problem, this study adopted the complementary use of bioindicators representing different trophic levels and providing different type of information, in an innovative approach to integrate knowledge and to estimate the overall health state of ecosystems. The approach is illustrated using mercury contamination in primary producers (mosses), primary consumers (domestic pigeons and red-legged partridges) and top predators (Bonelli's eagles) in southern Portugal. Indicator kriging geostatistics was used to identify the areas where mercury concentration was higher than the median for each species, and to produce an index that combines mercury contamination across trophic levels. Spatial patterns of mercury contamination were consistent across species. The combined index provided a new level of information useful in incorporating measures of overall environmental contamination into pollution studies.</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;accession-num: 19477568</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Figueira, Rui</style></author><author><style face="normal" font="default" size="100%">Tavares, Paula C</style></author><author><style face="normal" font="default" size="100%">Palma, Luís</style></author><author><style face="normal" font="default" size="100%">Beja, Pedro</style></author><author><style face="normal" font="default" size="100%">Sérgio, Cecília</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of indicator kriging to the complementary use of bioindicators at three trophic levels.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Bioindicators</style></keyword><keyword><style  face="normal" font="default" size="100%">birds</style></keyword><keyword><style  face="normal" font="default" size="100%">Birds: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: instrumentation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: statistics &amp; numerical d</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicator kriging</style></keyword><keyword><style  face="normal" font="default" size="100%">Indices</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Mosses</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">157</style></volume><pages><style face="normal" font="default" size="100%">2689-2696</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The use of biological indicators is widespread in environmental monitoring, although it has long been recognised that each bioindicator is generally associated with a range of potential limitations and shortcomings. To circumvent this problem, this study adopted the complementary use of bioindicators representing different trophic levels and providing different type of information, in an innovative approach to integrate knowledge and to estimate the overall health state of ecosystems. The approach is illustrated using mercury contamination in primary producers (mosses), primary consumers (domestic pigeons and red-legged partridges) and top predators (Bonelli's eagles) in southern Portugal. Indicator kriging geostatistics was used to identify the areas where mercury concentration was higher than the median for each species, and to produce an index that combines mercury contamination across trophic levels. Spatial patterns of mercury contamination were consistent across species. The combined index provided a new level of information useful in incorporating measures of overall environmental contamination into pollution studies.</style></abstract><accession-num><style face="normal" font="default" size="100%">19477568</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">De Nicola, F</style></author><author><style face="normal" font="default" size="100%">Maisto, G</style></author><author><style face="normal" font="default" size="100%">Prati, M V</style></author><author><style face="normal" font="default" size="100%">Alfani, a</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Leaf accumulation of trace elements and polycyclic aromatic hydrocarbons (PAHs) in Quercus ilex L.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Aromatic: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Atomic</style></keyword><keyword><style  face="normal" font="default" size="100%">biomonitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">cadmium</style></keyword><keyword><style  face="normal" font="default" size="100%">Cadmium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">chromium</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Cities</style></keyword><keyword><style  face="normal" font="default" size="100%">copper</style></keyword><keyword><style  face="normal" font="default" size="100%">Copper: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Iron</style></keyword><keyword><style  face="normal" font="default" size="100%">Iron: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Italy</style></keyword><keyword><style  face="normal" font="default" size="100%">lead</style></keyword><keyword><style  face="normal" font="default" size="100%">Lead: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">PAHs</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex L.</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrophotometry</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Unwashed and washed leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Vanadium</style></keyword><keyword><style  face="normal" font="default" size="100%">Vanadium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Zinc</style></keyword><keyword><style  face="normal" font="default" size="100%">Zinc: analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><volume><style face="normal" font="default" size="100%">153</style></volume><pages><style face="normal" font="default" size="100%">376-383</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Quercus ilex L. leaves were collected four times in one year at six urban sites and one remote area in order to determine trace element and PAH accumulation through concomitant analyses of unwashed and water-washed leaves. Both unwashed and washed leaves showed the highest amounts of trace elements and PAHs in the urban area. Unwashed leaves showed greater differences between urban and remote areas and among the urban sites than washed leaves for trace element and PAH concentrations. Water-washing resulted in a significant (P&lt;0.001) decrease in leaf concentrations of Cr, Cu, Fe, Pb, V and Zn. By contrast, Cd and total PAH concentrations showed no differences between unwashed and washed leaves.</style></abstract><accession-num><style face="normal" font="default" size="100%">17892907</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">De Nicola, F.</style></author><author><style face="normal" font="default" size="100%">Maisto, G.</style></author><author><style face="normal" font="default" size="100%">Prati, M. V.</style></author><author><style face="normal" font="default" size="100%">Alfani, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Leaf accumulation of trace elements and polycyclic aromatic hydrocarbons (PAHs) in Quercus ilex L.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Aromatic: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Atomic</style></keyword><keyword><style  face="normal" font="default" size="100%">biomonitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">cadmium</style></keyword><keyword><style  face="normal" font="default" size="100%">Cadmium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">chromium</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Cities</style></keyword><keyword><style  face="normal" font="default" size="100%">copper</style></keyword><keyword><style  face="normal" font="default" size="100%">Copper: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Iron</style></keyword><keyword><style  face="normal" font="default" size="100%">Iron: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Italy</style></keyword><keyword><style  face="normal" font="default" size="100%">lead</style></keyword><keyword><style  face="normal" font="default" size="100%">Lead: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">PAHs</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex L.</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrophotometry</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Unwashed and washed leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Vanadium</style></keyword><keyword><style  face="normal" font="default" size="100%">Vanadium: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Zinc</style></keyword><keyword><style  face="normal" font="default" size="100%">Zinc: analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17892907</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">153</style></volume><pages><style face="normal" font="default" size="100%">376 - 383</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Quercus ilex L. leaves were collected four times in one year at six urban sites and one remote area in order to determine trace element and PAH accumulation through concomitant analyses of unwashed and water-washed leaves. Both unwashed and washed leaves showed the highest amounts of trace elements and PAHs in the urban area. Unwashed leaves showed greater differences between urban and remote areas and among the urban sites than washed leaves for trace element and PAH concentrations. Water-washing resulted in a significant (P&lt;0.001) decrease in leaf concentrations of Cr, Cu, Fe, Pb, V and Zn. By contrast, Cd and total PAH concentrations showed no differences between unwashed and washed leaves.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;accession-num: 17892907</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Domínguez, María T.</style></author><author><style face="normal" font="default" size="100%">Marañón, Teodoro</style></author><author><style face="normal" font="default" size="100%">Murillo, José M.</style></author><author><style face="normal" font="default" size="100%">Schulin, Rainer</style></author><author><style face="normal" font="default" size="100%">Robinson, Brett H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Trace element accumulation in woody plants of the Guadiamar Valley, SW Spain: a large-scale phytomanagement case study.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bioaccumulation</style></keyword><keyword><style  face="normal" font="default" size="100%">biodegradation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy metal</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mass spectrometry</style></keyword><keyword><style  face="normal" font="default" size="100%">metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Mining</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea europaea</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Phytoremediation</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus alba</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17602809</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">152</style></volume><pages><style face="normal" font="default" size="100%">50 - 59</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phytomanagement employs vegetation and soil amendments to reduce the environmental risk posed by contaminated sites. We investigated the distribution of trace elements in soils and woody plants from a large phytomanaged site, the Guadiamar Valley (SW Spain), 7 years after a mine spill, which contaminated the area in 1998. At spill-affected sites, topsoils (0-25 cm) had elevated concentrations of As (129 mg kg(-1)), Bi (1.64 mg kg(-1)), Cd (1.44 mg kg(-1)), Cu (115 mg kg(-1)), Pb (210 mg kg(-1)), Sb (13.8 mg kg(-1)), Tl (1.17 mg kg(-1)) and Zn (457 mg kg(-1)). Trace element concentrations in the studied species were, on average, within the normal ranges for higher plants. An exception was white poplar (Populus alba), which accumulated Cd and Zn in leaves up to 3 and 410 mg kg(-1) respectively. We discuss the results with regard to the phytomanagement of trace element contaminated sites.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;accession-num: 17602809</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Domínguez, María T</style></author><author><style face="normal" font="default" size="100%">Marañón, Teodoro</style></author><author><style face="normal" font="default" size="100%">Murillo, José M</style></author><author><style face="normal" font="default" size="100%">Schulin, Rainer</style></author><author><style face="normal" font="default" size="100%">Robinson, Brett H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Trace element accumulation in woody plants of the Guadiamar Valley, SW Spain: a large-scale phytomanagement case study.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bioaccumulation</style></keyword><keyword><style  face="normal" font="default" size="100%">biodegradation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy metal</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mass spectrometry</style></keyword><keyword><style  face="normal" font="default" size="100%">metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Mining</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea europaea</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Phytoremediation</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus alba</style></keyword><keyword><style  face="normal" font="default" size="100%">Populus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><volume><style face="normal" font="default" size="100%">152</style></volume><pages><style face="normal" font="default" size="100%">50-59</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phytomanagement employs vegetation and soil amendments to reduce the environmental risk posed by contaminated sites. We investigated the distribution of trace elements in soils and woody plants from a large phytomanaged site, the Guadiamar Valley (SW Spain), 7 years after a mine spill, which contaminated the area in 1998. At spill-affected sites, topsoils (0-25 cm) had elevated concentrations of As (129 mg kg(-1)), Bi (1.64 mg kg(-1)), Cd (1.44 mg kg(-1)), Cu (115 mg kg(-1)), Pb (210 mg kg(-1)), Sb (13.8 mg kg(-1)), Tl (1.17 mg kg(-1)) and Zn (457 mg kg(-1)). Trace element concentrations in the studied species were, on average, within the normal ranges for higher plants. An exception was white poplar (Populus alba), which accumulated Cd and Zn in leaves up to 3 and 410 mg kg(-1) respectively. We discuss the results with regard to the phytomanagement of trace element contaminated sites.</style></abstract><accession-num><style face="normal" font="default" size="100%">17602809</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">García del Barrio, J M</style></author><author><style face="normal" font="default" size="100%">Ortega, M</style></author><author><style face="normal" font="default" size="100%">Vázquez De la Cueva, A</style></author><author><style face="normal" font="default" size="100%">Elena-Rosselló, R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The influence of linear elements on plant species diversity of Mediterranean rural landscapes: assessment of different indices and statistical approaches.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental monitoring and assessment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">Conservation of Natural Resources</style></keyword><keyword><style  face="normal" font="default" size="100%">Conservation of Natural Resources: statistics &amp; nu</style></keyword><keyword><style  face="normal" font="default" size="100%">core habitat</style></keyword><keyword><style  face="normal" font="default" size="100%">diversity</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">ecotones</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Geography</style></keyword><keyword><style  face="normal" font="default" size="100%">landscape</style></keyword><keyword><style  face="normal" font="default" size="100%">linear elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean Region</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Development</style></keyword><keyword><style  face="normal" font="default" size="100%">Poaceae</style></keyword><keyword><style  face="normal" font="default" size="100%">Poaceae: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Shannon index</style></keyword><keyword><style  face="normal" font="default" size="100%">Species richness</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: growth &amp; development</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">119</style></volume><pages><style face="normal" font="default" size="100%">137-159</style></pages><isbn><style face="normal" font="default" size="100%">1066100590192</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements--habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land--whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index. Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50x20 m2 multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators. The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p &lt; 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.</style></abstract><accession-num><style face="normal" font="default" size="100%">16763745</style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sardans, Jordi</style></author><author><style face="normal" font="default" size="100%">Penuelas, Josep</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Introduction of the factor of partitioning in the lithogenic enrichment factors of trace element bioaccumulation in plant tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental monitoring and assessment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biomass</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements: analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/16648953</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">115</style></volume><pages><style face="normal" font="default" size="100%">473 - 98</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Bioindicators are widely used in the study of trace elements inputs into the environment and great efforts have been conducted to separate atmospheric from soil borne inputs on biomass accumulation. Many monitoring studies of trace element pollution take into account the dust particles located in the plant surface plus the contents of the plant tissues. However, it is usually only the trace element content in the plant tissues that is relevant on plant health. Enrichment factor equations take into account the trace element enrichment of biomasses with respect soil or bedrocks by comparing the ratios of the trace element in question to a lithogenic element, usually Al. However, the enrichment equations currently in use are inadequate because they do not take into account the fact that Al (or whichever reference element) and the element in question may have different solubility-absorption-retention levels depending on the rock and soil types involved. This constrain will become critical when results from different sites are compared and so in this article we propose that the solubility factors of each element are taken into account in order to overcome this constrain. We analysed Sb, Co, Ni, Cr, Pb, Cd, Mn, V, Zn, Cu, As, Hg, and Al concentration in different zones of Catalonia (NE Spain) using the evergreen oak Quercus ilex and the moss Hypnum cupressiforme as target species. We compared the results obtained in rural and non industrial areas with those from the Barcelona Metropolitan Area. We observed differences in Al concentrations of soils and bedrocks at each different site, together with the differences in solubility between Al and the element in question, and a weak correlation between total soil content and water extract content through different sites for most trace elements. All these findings show the unsuitability of the current enrichment factors for calculating lithospheric and atmospheric contributions to trace element concentrations in biomass tissues. The trace element enrichment factors were calculated by subtracting the part predicted by substrate composition (deduced from water extracts from soils and bedrock) from total concentrations. Results showed that for most of the trace elements analysed, trace elements enrichment factors were higher inside the Barcelona Metropolitan Area than outside, a finding that indicates that greater atmospheric inputs occur in urban areas. The results show that the most useful and correct way of establishing a reference for lithospheric and atmospheric inputs into the plant tissues is, first, to analyse samples of the same plant species collected from a number of sites possessing similar environmental conditions (climate, vegetation type, soil type) and, second, to use this new enrichment factor obtained by subtracting from the total concentration in plant tissue the predicted contribution of soil or bedrock extracts instead of that of total soil or bedrock concentrations.</style></abstract><issue><style face="normal" font="default" size="100%">1-3</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;accession-num: 16648953</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sardans, Jordi</style></author><author><style face="normal" font="default" size="100%">Penuelas, Josep</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Introduction of the factor of partitioning in the lithogenic enrichment factors of trace element bioaccumulation in plant tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental monitoring and assessment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biomass</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryopsida: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements: analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">115</style></volume><pages><style face="normal" font="default" size="100%">473-98</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Bioindicators are widely used in the study of trace elements inputs into the environment and great efforts have been conducted to separate atmospheric from soil borne inputs on biomass accumulation. Many monitoring studies of trace element pollution take into account the dust particles located in the plant surface plus the contents of the plant tissues. However, it is usually only the trace element content in the plant tissues that is relevant on plant health. Enrichment factor equations take into account the trace element enrichment of biomasses with respect soil or bedrocks by comparing the ratios of the trace element in question to a lithogenic element, usually Al. However, the enrichment equations currently in use are inadequate because they do not take into account the fact that Al (or whichever reference element) and the element in question may have different solubility-absorption-retention levels depending on the rock and soil types involved. This constrain will become critical when results from different sites are compared and so in this article we propose that the solubility factors of each element are taken into account in order to overcome this constrain. We analysed Sb, Co, Ni, Cr, Pb, Cd, Mn, V, Zn, Cu, As, Hg, and Al concentration in different zones of Catalonia (NE Spain) using the evergreen oak Quercus ilex and the moss Hypnum cupressiforme as target species. We compared the results obtained in rural and non industrial areas with those from the Barcelona Metropolitan Area. We observed differences in Al concentrations of soils and bedrocks at each different site, together with the differences in solubility between Al and the element in question, and a weak correlation between total soil content and water extract content through different sites for most trace elements. All these findings show the unsuitability of the current enrichment factors for calculating lithospheric and atmospheric contributions to trace element concentrations in biomass tissues. The trace element enrichment factors were calculated by subtracting the part predicted by substrate composition (deduced from water extracts from soils and bedrock) from total concentrations. Results showed that for most of the trace elements analysed, trace elements enrichment factors were higher inside the Barcelona Metropolitan Area than outside, a finding that indicates that greater atmospheric inputs occur in urban areas. The results show that the most useful and correct way of establishing a reference for lithospheric and atmospheric inputs into the plant tissues is, first, to analyse samples of the same plant species collected from a number of sites possessing similar environmental conditions (climate, vegetation type, soil type) and, second, to use this new enrichment factor obtained by subtracting from the total concentration in plant tissue the predicted contribution of soil or bedrock extracts instead of that of total soil or bedrock concentrations.</style></abstract><accession-num><style face="normal" font="default" size="100%">16648953</style></accession-num></record></records></xml>