Effects of meteorological conditions and topography on the bioaccumulation of PAHs and metal elements by native lichen (Xanthoria parietina)

The bioaccumulation of PAHs and metal elements in the indigenous lichens Xanthoria parietina was monitored during two years at a quarterly frequency, in 3 sites of contrasted anthropic influence. The impact of the meteorological factors (temperature, relative humidity, rainfall, wind speed) was first estimated through principal component analysis, and then by stepwise multilinear regressions to include wind directions. The pollutants levels reflected the proximity of atmospheric emissions, in particular from a large industrial harbor. High humidity and mild temperatures, and in a lower extent low wind speed and rainfall, also favored higher concentration levels. The contributions of these meteorological aspects became minor when including wind direction, especially when approaching major emission sources. The bioaccumulation integration time towards meteorological variations was on a seasonal basis (1–2 months) but the wind direction and thus local emissions also relied on a longer time scale (12 months). This showed that the contribution of meteorological conditions may be prevalent in remote places, while secondary in polluted areas, and should be definitely taken into account regarding long-term lichen biomonitoring and inter-annual comparisons. In the same time, a quadruple sampling in each site revealed a high homogeneity among supporting tree species and topography. The resulting uncertainty, including sampling, preparation and analysis was below 30% when comfortable analytical conditions were achieved. Finally, the occurrence of unexpected events such as a major forest fire, permitted to evaluate that this type of short, although intense, events did not have a strong influence on PAH and metals bioaccumulation by lichen.     

Speciation of mercury in South African coals

Total mercury (Hg_TOT) concentrations were determined by inductively coupled plasma mass spectrometry (ICP MS) for South African Highveld coals. The distribution of Hg in coals was investigated using a four-stage sequential leaching protocol and isotope dilution/gas chromatography coupled to ICP MS (ID-GC-ICP MS). The results show that Hg_TOT ranged from 144 to 303?µg?kg^?1 with a mean of 199?±?26?µg?kg^?1, while Hg_TOT leached from coals using different solvents ranged between 103 and 310?µg?kg^?1 (mean: 218?±?60?µg?kg^?1). Hg leaching rates of 53–78% were achieved in crushed coals. Hg⁰, Hg²⁺, and CH₃Hg⁺ were identified in all coals. CH₃Hg⁺ in studied coals ranged between 0.1 and 0.4 (mean: 0.2) µg?kg^?1. GC ICP MS chromatograms also showed unknown Hg peaks which were identified as other organomercury species such as ethylmercury. Modes of occurrence of Hg in coals were variable with the organic-bound (37–40%) and the sulfide-bound (37–39%) being the dominant mercury forms. Increasing the HCl concentration in the used protocol increased the amount of Hg leached (16%) during this step.     

Use of a physiologically based extraction test to estimate the human bioaccessibility of potentially toxic elements in urban soils from the city of Glasgow,UK

A simple, two-stage, physiologically based extraction has been applied to assess the human bioaccessibility of potentially toxic elements (PTE) in 20 urban soils from a major UK city. Chromium and iron bioaccessibilities were found to be markedly higher in the intestinal phase, whilst lead and zinc bioaccessibilities were higher in the stomach. Copper and manganese bioaccessibilities were generally similar under both extraction conditions. Principal component analysis was used to study relationships amongst bioaccessible element concentrations and land use. Distinctions could be observed between the distributions of the urban metals—copper, lead and zinc—and metals predominantly of geogenic origin, such as iron. There was no clear delineation between roadside soils and soils obtained from public parks. Bioaccessible analyte concentrations were found to be correlated with pseudototal (aqua regia soluble) analyte concentrations for all elements except iron. Results of the BCR sequential extraction did not, in general, provide a good indication of human bioaccessibility. Comparison of bioaccessible PTE concentrations with toxicological data indicated that lead is the element of greatest concern in these soils but that levels are unlikely to pose a health risk to children with average soil intake.     

RASTER-BASED HYDROLOGIC MODELING OF SPATIALLY-VARIED SURFACE RUNOFF1

ABSTRACT: The proliferation of watershed databases in raster Geographic Information System (GIS) format and the availability of radar-estimated rainfall data foster rapid developments in raster-based surface runoff simulations. The two-dimensional physically-based rainfall-runoff model CASC2D simulates spatially-varied surface runoff while fully utilizing raster GIS and radar-rainfall data. The model uses the Green and Ampt infiltration method, and the diffusive wave formulation for overland and channel flow routing enables overbank flow storage and routing. CASC2D offers unique color capabilities to display the spatio-temporal variability of rainfall, cumulative infiltrated depth, and surface water depth as thunderstorms unfold. The model has been calibrated and independently verified to provide accurate simulations of catchment response to moving rainstorms on watersheds with spatially-varied infiltration. The model can accurately simulate surface runoff from flashfloods caused by intense thunderstorms moving across partial areas of a watershed.     

Examining the Factors Affecting Air Pollution Emission Growth in China

In this study, a structural decomposition method was applied to research the factors affecting the changes in air pollution emissions in China. Based on 1995–2009 data from the World IO Database, we combine China’s (Import) Noncompetitive IO Table and the Environmental Account Table. The results indicate that emission intensities represent the most important factor for reducing air pollution emissions in China. In contrast, economies of scale and the intermediate input product structure constitute the major causes for acceleration in the growth of air pollution emissions in China. From the perspective of final demand, the economic scale effect caused by investment demand is the main reason for this accelerated growth in China’s air pollution emissions in recent years. Consumption-driven economic growth is cleaner, while investment-driven economic growth is dirtier. This study constructed a structure decomposition model based on the input-output tables, which is suitable for studying the driving forces of various economic indicators, such as energy, carbon dioxide, and economic growth. At the same time, this method is helpful for analyzing the factors that influence changes in economic indicators that result from different economic pull modes, such as the final demand mode. However, the model does have limitations; for example, it does not consider the difference between general trade and processing trade in exports.     

A neural network experiment on the simulation of daily nitrate-nitrogen and suspended sediment fluxes from a small agricultural catchment

In this paper, we report an application of neural networks to simulate daily nitrate-nitrogen and suspended sediment fluxes from a small 7.1 km² agricultural catchment (Melarchez), 70 km east of Paris, France. Nitrate-nitrogen and sediment losses are only a few possible consequences of soil erosion and biochemical applications associated to human activities such as intensive agriculture. Stacked multilayer perceptrons models (MLPs) like the ones explored here are based on commonly available inputs and yet are reasonably accurate considering their simplicity and ease of implementation. Note that the simulation does not resort on water quality flux observations at previous time steps as model inputs, which would be appropriate, for example, to predict the water chemistry of a drinking water plant a few time steps ahead. The water quality fluxes are strictly mapped to historical mean flux values and to hydro-climatic variables such as stream flow, rainfall, and soil moisture index (12 model input candidates in total), allowing its usage even when no flux observations are available. Self-organizing feature maps based on the network structure established by Kohonen were employed first to produce the training and the testing data sets, with the intent to produce statistically close subsets so that any difference in model performance between validation and testing has to be associated to the model and not to the data subsets. The stacked MLPs reached different levels of performance simulating the nitrate-nitrogen flux and the suspended sediment flux. In the first instance, 2-input stacked MLP nitrate-nitrogen simulations, based on the same-day stream flow and on the 80-cm soil moisture index, have a performance of almost 90% according to the efficiency index. On the other hand, the performance of 3-input stacked MLPs (same-day stream flow, same-day historical flux, and same-day stream flow increment) reached a little more than 75% according to the same criterion. The results presented here are deemed already promising enough, and should encourage water resources managers to implement simple models whenever appropriate.     

Using OpenMI and a Model MAP to Integrate WaterML2 and NetCDF Data Sources into Flood Modeling of Genoa,Italy

Extreme hydrometeorological events such as flash floods have caused considerable loss of life and damage to infrastructure over recent years. Flood events in the Mediterranean region between 1990 and 2006 caused over 4,500 fatalities and cost over €29 billion in damage, with Italy one of the worst affected countries. The Distributed Computing Infrastructure for Hydro‐Meteorology (DRIHM) project is a European initiative aiming at providing an open, fully integrated eScience environment for predicting, managing, and mitigating the risks related to such extreme weather phenomena. Incorporating both modeled and observational data sources, it enables seamless access to a set of computing resources with the objective of providing a collection of services for performing experiments with numerical models in meteorology, hydrology, and hydraulics. The purpose of this article is to demonstrate how this flexible modeling architecture has been constructed using a set of standards including the NetCDF and WaterML2 file formats, in‐memory coupling with OpenMI, controlled vocabularies such as CF Standard Names, ISO19139 metadata, and a Model MAP (Metadata, Adaptors, Portability) gateway concept for preparing numerical models for standardized use. Hydraulic results, including the impact to buildings and hazards to people, are given for the use cases of the severe and fatal flash floods, which occurred in Genoa, Italy in November 2011 and October 2014.     

Fate of metal-associated POM in a soil under arable land use contaminated by metallurgical fallout in northern France

Organic matter is a major metal-retaining constituent in soils. Among the diversity of organic components in soils, particulate organic matter (POM) accumulates large amounts of metals, but the fate of such metal-associated POM is unknown. We studied different POM size fractions and their corresponding mineral size-fractions isolated from the surface horizon of a soil affected by metallurgical fallout. Analyses of total and EDTA extractible metal contents performed on all size fractions demonstrated that with decreasing POM size, larger metal concentrations were observed but they were less extractable. Micromorphological study revealed the occurrence of opaque parts in decaying POM fragments and their individualization as fine, irregularly shaped opaque fragments in the soil matrix. This work suggested a mutual sequestration of metal pollutants and organic carbon as micro-meter sized, metal-enriched organic particles derived from POM, representing an original pathway for natural attenuation of risk related to metal contaminated soils.     

Faecal contamination of water and sediment in the rivers of the Scheldt drainage network

The INSHORE system (INtegrated System for High Operational REsolution in shore monitoring) is a land-base survey system designed and developed for the specific task of monitoring the evolution in time of sandy shores. This system was developed with two main objectives: (1) to produce highly accurate 3D coordinates of surface points (in the order of 0.02 to 0.03 m); and (2) to be extremely efficient in surveying a beach stretch of several kilometres. Previous tests have demonstrated that INSHORE systems fulfil such objectives. Now, the usefulness of the INSHORE system as a survey tool for the production of Digital Elevation Models (DEMs) of sandy shores is demonstrated. For this purpose, the comparison of DEMs obtained with the INSHORE system and with other relevant survey techniques is presented. This comparison focuses on the final DEM accuracy and also on the survey efficiency and its impact on the costs associated with regular monitoring programmes. The field survey method of the INSHORE system, based on profile networks, has a productivity of about 30 to 40 ha/h, depending on the beach surface characteristics. The final DEM precision, after interpolation of the global positioning system profile network, is approximately 0.08 to 0.12 m (RMS), depending on the profile network's density. Thus, this is a useful method for 3D representation of sandy shore surfaces and can permit, after interpolation, reliable calculations of volume and other physical parameters.