Abstract: Forests were shown to play an important role in influencing atmospheric concentrations and transport of persistent organic pollutants (POPs) in the environment. World forests cover more than 4 billion hectares and contain up to 80% of the above ground organic carbon. Given the lipophilic nature of POPs, this suggests that forests can influence the environmental fate of POPs at a global scale. POP accumulation in forest canopies still presents points of concern given the complexity of these ecosystems. In particular, the role of ecological parameters such as LAI (leaf area index) and SLA (specific leaf area) and their dynamics during the growing season was not sufficiently investigated yet. This paper reviews, compares and interprets a unique case study in which air and leaf concentrations and deposition fluxes for selected polychlorinated biphenyls (PCBs) were measured in three different forest types exposed to the same air masses. In order to trace the air-leaf-soil path of these compounds, a dynamic model of POP accumulation into forest canopy was applied. The dynamics of the canopy biomass strongly affected the trend of leaf concentration with time. Growth dilution effect can prevent the more chlorinated compounds from reaching the partitioning equilibrium before litter fall, while the more volatile compounds can approach equilibrium in the range of few weeks. An amount of up to 60 ng of PCBs per square metre of ground surface was predicted to be stored in each of the selected forests at fully developed canopy. Dry gaseous deposition fluxes to forest canopy were estimated to reach a maximum value of about 0.5-1.5 ng m(-2) d(-1) during the spring period.
Abstract: In pipeline management the accurate prediction of weak displacements is a crucial factor
in drawing up a prevention policy since the accumulation of these displacements over a period of
several years can lead to situations of high risk. This work addresses the specific problem related to
the prediction of displacements induced by rainfall in unstable areas, of known geology, and crossed
by underground pipelines. A neural model has been configured which learns of displacements from
instrumented sites (where inclinometric measurements are available) and is able to generalise to other
sites not equipped with inclinometers
Abstract: Biomass burning constitutes a major contribution to global emissions of carbon dioxide,
carbon monoxide, methane, greenhouse gases and aerosols. Furthermore, biomass burning has an
impact on health, transport, the environment and land use. Vegetation fires are certainly not recent
phenomena and the impacts are not always negative. However, evidence suggests that fires are becoming
more frequent and there is a large increase in the number of fires being set by humans for
a variety of reasons. Knowledge of the interactions and feedbacks between biomass burning, climate
and carbon cycling is needed to help the prediction of climate change scenarios. To obtain this
knowledge, the scientific community requires, in the first instance, information on the spatial and
temporal distribution of biomass burning at the global scale. This paper presents an inventory of
burned areas at monthly time periods for the year 2000 at a resolution of 1 kilometer (km) and is
available to the scientific community at no cost. The burned area products have been derived from
a single source of satellite-derived images, the SPOT VEGETATION S1 1 km product, using algorithms
developed and calibrated at regional scales by a network of partners. In this paper, estimates
of burned area, number of burn scars and average size of the burn scar are described for each month
of the year 2000. The information is reported at the country level. This paper makes a significant
contribution to understanding the effect of biomass burning on atmospheric chemistry and the storage
and cycling of carbon by constraining one of the main parameters used in the calculation of gas
emissions.
Abstract: The operational application of remote sensing technologies to lake water quality monitoring requires products derived from remote sensing to be quantitatively self-consistent and have a certified accuracy. Fundamental elements in this quality assurance framework are sensor radiometric calibration and atmospheric correction models, which are briefly discussed in the paper. In order to evaluate the accuracy of present operational techniques to retrieve basic parameters from satellite data, such as water-leaving radiance and reflectance, an experiment was organised in the frame of SAtellite remote sensing for Lake MONitoring (SALMON), a European Union co-funded research project. A series of ship-based radiometric and atmospheric measuring campaigns were conducted on Lake Iseo and Lake Garda (Italy) together with limnological sampling. Four Landsat-5 Thematic Mapper (TM) scenes were acquired during different seasons and simultaneous in situ measurements were made. After the radiometric calibration procedure, satellite digital images were processed by applying two entirely image-based atmospheric correction models. These models account for the effects of both additive scattering and multiplicative transmittance effects in the atmosphere on the at-satellite measured signal. The results achieved using these procedures were evaluated by comparing satellite-based estimates with in situ measurements of water reflectance. The root mean square difference between Landsat TM-derived reflectance values and ground measurements was close to 0.010 reflectance for each TM spectral band. Such image-based correction models, requiring no in situ field measurements during the satellite overpass, constitute a valid method of lake water monitoring.
Abstract: Some bio-physical parameters, such as chlorophyll a concentration, Secchi disk depth and water surface temperature were mapped in the sub-alpine Lake Iseo (Italy) using Landsat Thematic Mapper (TM) data acquired on the 7 March 1997. In order to adequately investigate the water-leaving radiance, TM data were atmospherically corrected using a partially image-based method, and the atmospheric transmittance was measured in synchrony with the satellite passage. An empirical approach of relating atmospherically corrected TM spectral reflectance values to in situ measurements, collected during the satellite data acquisition, was used. The models developed were used to map the chlorophyll concentration and Secchi disk depth throughout the lake. Both models gave high determination coefficients (R2 = 0.99 for chlorophyll and R2 = 0.85 for the Secchi disk) and the spatial distribution of chlorophyll concentration and Secchi disk depth was mapped with contour intervals of 1 mg/m3 and 1 m, respectively. A scene-independent procedure was used to derive the surface temperature of the lake from the TM data with a root mean square error of 0.3 degrees C.
