Magnetic and elemental characterization of the particulate matter deposited on leaves of urban trees in Santiago, Chile.

Airborne particulate matter is a serious threat to human health, especially in fast-growing cities. In this study, we carried out a magnetic and elemental study on tree leaves used as passive captors and urban dust from various sites in the city of Santiago, Chile, to assess the reliability of magnetic and elemental measurements to characterize particulate matter pollution from vehicular origin. We found that the magnetic susceptibility and saturation isothermal remanent magnetization measured on urban tree leaves is a good proxy for tracing anthropogenic metallic particles and allow controlling the exposure time for particulate matter collection, in agreement with other studies carried out in large cities. Similar measurements on urban soil can be influenced by particles of detritic (natural) origin, and therefore, magnetic measurements on tree leaves can help to identify hotspots where fine particles are more abundant. Elemental particle-induced X-ray emission analysis of tree leaves showed the presence of a number of elements associated with vehicular emissions, in particular Cu, Zn, Fe, K and S which are present at every site, and As, Se, V, Ni, Sr, Zr, Mo and Pb identified at some sites. We observed a correlation between magnetic parameters and the concentrations of S and Br as well as Cu to a smaller extent. Moreover, this study shows the importance of selecting carefully the tree species as well as the location of trees in order to optimize phytoremediation.

One-class land-cover classification using MaxEnt: the effect of modelling parameterization on classification accuracy.

Multiple-class land-cover classification approaches can be inefficient when the main goal is to classify only one or a few classes. Under this scenario one-class classification algorithms could be a more efficient alternative. Currently there are several algorithms that can fulfil this task, with MaxEnt being one of the most promising. However, there is scarce information regarding parametrization for performing land-cover classification using MaxEnt. In this study we aimed to understand how MaxEnt parameterization affects the classification accuracy of four different land-covers (i.e., built-up, irrigated grass, evergreen trees and deciduous trees) in the city of Santiago de Chile. We also evaluated if MaxEnt manual parameterization outperforms classification results obtained when using MaxEnt default parameters setting. To accomplish our objectives, we generated a set of 25,344 classification maps (i.e., 6,336 for each assessed land-cover), which are based on all the potential combination of 12 different classes of features restrictions, four regularization multipliers, four different sample sizes, three training/testing proportions, and 11 thresholds for generating the binary maps. Our results showed that with a good parameterization, MaxEnt can effectively classify different land covers with kappa values ranging from 0.68 for deciduous trees to 0.89 for irrigated grass. However, the accuracy of classification results is highly influenced by the type of land-cover being classified. Simpler models produced good classification outcomes for homogenous land-covers, but not for heterogeneous covers, where complex models provided better outcomes. In general, manual parameterization improves the accuracy of classification results, but this improvement will depend on the threshold used to generate the binary map. In fact, threshold selection showed to be the most relevant factor impacting the accuracy of the four land-cover classification. The number of sampling points for training the model also has a positive effect on classification results. However, this effect followed a logarithmic distribution, showing an improvement of kappa values when increasing the sampling from 40 to 60 points, but showing only a marginal effect if more than 60 sampling points are used. In light of these results, we suggest testing different parametrization and thresholds until satisfactory kappa or other accuracy metrics values are achieved. Our results highlight the huge potential that MaxEnt has a as a tool for one-class classification, but a good understanding of the software settings and model parameterization is needed to obtain reliable results.

A comparative study of cambium histology of Ceiba speciosa (A. St.-Hil.) Ravenna (Malvaceae) under urban pollution.

Air pollution is considered to be one of the main causes of forest decline. The cambium is responsible for increase in tree girth, and its functioning is determined by environmental pressures. This study compared cambium histology of Ceiba speciosa (A. St.-Hil.) Ravenna (Malvaceae) in polluted and preserved sites in the Atlantic Rainforest domain. Samples were obtained during periods of cambial activity and dormancy and were processed and examined according to standard light microscopy techniques. In addition to differences typically observed in cambium during periods of activity and dormancy, the fusiform initials were shorter in trees of the polluted site. Furthermore, cambial rays were shorter, but larger, in the polluted site. It should be noted that all parameters related to cambial rays showed significant differences between the study sites. This is the first report of the effects of pollution on cambial activity in a South American species. The results suggest a tolerance of C. speciosa to pollution and reveal this species to be an important biomarker for environmental monitoring studies.

Flora alergógena urbana y polen atmosférico de Diamante (Argentina) / Allergenic urban flora and airborne pollen in the air of Diamante (Argentina)

El polen del aire produce rinitis, conjuntivitis y asma, lo que lleva a una disminución en la calidad de vida. Las especies más abundantes de la vegetación son en general, las que aportan mayoritariamente al registro atmosférico de polen. Sin embargo, esta relación puede variar dependiendo de la cercanía de las fuentes y de la estrategia reproductiva de las plantas emisoras. En este trabajo realizado en la ciudad de Diamante (Entre Ríos, Argentina), se analizó la vegetación arbórea en cuanto a abundancia, diversidad, distribución territorial, tipo de polinización y potencialidad alergénica, para luego evaluar su relación con el polen que se registró en la atmósfera durante un ciclo anual, utilizando un método aerobiológico volumétrico y continuo bajo estándares internacionales. Se observó que la vegetación analizada presenta una gran diversidad. Los representantes de las familias más abundantes en la vegetación tienen polinización entomófila, como Tabebuia impetiginosa y Tecoma stans. Por otra parte, el 34% de los árboles correspondió a familias de polinización anemófila. Los árboles cercanos al muestreador aerobiológico (dentro de las áreas local y extralocal) son las principales fuentes de polen que contribuyen al espectro atmosférico, especialmente los árboles anemófilos. Entre ellos cabe mencionar: Fraxinus pennsylvanica, Ulmus procera y Broussonetia papyrifera. El polen de especies anemófilas en su mayoría tiene características alergénicas y son potencialmente perjudiciales para la salud. Los resultados obtenidos no sólo son importantes para ajustar el modelo aerobiológico de la ciudad, sino que sirven de fundamento para planificar el arbolado urbano.(AU)

Airborne pollen produces rhinitis, conjunctivitis and asthma, leading to a decreased quality of life. In general, the most abundant vegetation species are also present in greater amounts in the pollen spectrum. However, this relationship can vary depending on the proximity of the sources and the plant reproductive strategy. This work was carried out in Diamante city (Entre Ríos, Argentina). Abundance, diversity, territorial distribution, type of pollination, and allergenic potential of vegetation were analyzed to finally assess the relationship with the pollen recorded in the atmosphere during one annual cycle. A volumetric and continuous aerobiological method under international protocols was used to sample the airborne pollen. It was observed that urban vegetation is diverse. Families more abundant in vegetation have insect-pollinated species as representatives: Tabebuia impetiginosa and Tecoma stans. On the other hand, 34% of the trees corresponded to wind-pollinated families. The trees near the aerobiological sampler (within local and extralocal areas) were the main pollen sources contributing to the atmospheric pollen spectrum, especially those wind-pollinated tree species as Fraxinus pennsylvanica, Ulmus procera and Broussonetia papyrifera. Pollen from wind-pollinated species is most likely to be allergenic and so, potentially harmful to health. The results are important not only to adjust the aerobiological model of the city, but also as a basis to plan urban forest(AU)