Soil C and N response to changes in winter precipitation in a subalpine forest ecosystem,NW Italy

Among the potential effects of climate change on subalpine forest ecosystems during the winter season, the shift in snowline towards higher altitudes and the increase in frequency of rain events on the snowpack are of particular interest. Here, we present the results of a 2‐year field experiment conducted in a forest stand (Larix decidua) in NW Italy at 2020 m a.s.l. From 2009 to 2011, we monitored soil physical characteristics (temperature and moisture), and soil and soil solution chemistry, in particular carbon (C) and nitrogen (N) forms and their change in time, as affected by simulated late snowpack accumulation and rain on snow events. Late snowpack accumulation determined a stronger effect on soil thermal and moisture regimes than rain on snow events. Also soil chemistry was significantly affected by late snowfall simulation. Although microbial biomass C and N were not reduced by soil freezing, soil contents of the more labile dissolved organic carbon and inorganic N increased when the soil was affected by mild/hard freezing. Variations in the soil solution were shifted with respect to those observed in soil, with an increase in N‐NO₃^? concentrations occurring during spring and summer. This study highlights the potential N loss in subalpine soils under changing environmental conditions driven by a changing climate. Copyright © 2013 John Wiley & Sons, Ltd.     

Large biases and inconsistent climate change signals in ENSEMBLES regional projections

In this paper we analyze some caveats found in the state-of-the-art ENSEMBLES regional projections dataset focusing on precipitation over Spain, and highlight the need of a task-oriented validation of the GCM-driven control runs. In particular, we compare the performance of the GCM-driven control runs (20C3M scenario) with the ERA40-driven ones (“perfect” boundary conditions) in a common period (1961–2000). Large deviations between the results indicate a large uncertainty/bias for the particular RCM-GCM combinations and, hence, a small confidence for the corresponding transient simulations due to the potential nonlinear amplification of biases. Specifically, we found large biases for some RCM-GCM combinations attributable to RCM in-house problems with the particular GCM coupling. These biases are shown to distort the corresponding climate change signal, or “delta”, in the last decades of the 21st century, considering the A1B scenario. Moreover, we analyze how to best combine the available RCMs to obtain more reliable projections.     

Asbestos fibre identification vs. evaluation of asbestos hazard in ophiolitic rock mélanges,a case study from the Ligurian Alps (Italy)

In recent years, the high incidence of harmful health effects through inhalation of airborne asbestos from amphibole-bearing rock mélanges has been thoroughly documented. Here, we present a field-based, multi-scale geological approach aimed at illustrating the occurrence of amphibole fibrous mineralisation in an ophiolitic suite from the Ligurian Alps (Italy) and discussing the implication on in situ determination of the asbestos hazard. The rock mélange is composed of plurimetre-sized blocks of different lithotypes (metagabbro, serpentinite, chloritoschist) juxtaposed by the meaning of tectonic structures. The geological-structural survey revealed that the fibrous mineralisation is localised in specific structural sites of the rock volume, including veins and schistosity. Both micro-chemical and crystal structure analyses on selected fibrous samples revealed that actinolite fibres grow in veins within the metagabbro and in chloritoschists, while fibrous tremolite occurs in serpentinite schistosity. The morphological features of these amphibole fibres have been analysed in TEM images and used for classifying them as “asbestiform” or “non-asbestiform”. The results show that the asbestos hazard determination is not unequivocally identified when different procedures for asbestos fibre identification and classification are applied. This may have impact on normatives and regulations in defining environmental hazards due to asbestos occurrence.     

Towards a better understanding of the evolution of the flood risk in Mediterranean urban areas: the case of Barcelona

Dam failure constitutes a grave threat to human life. However, there is still a lack of systematic and comprehensive research on the loss of life (L) caused by dam break in China. From the perspective of protecting human life, a new calculation method for L occurred in dam break floods is put forward. Fourteen dam failure cases in China are selected as the basic data by three-dimensional stratified sampling, balancing spatial, vertical elevation and temporal representations, as well as considering various conditions of the dam collapse. The method includes three progressive steps: Firstly, some impact factors of loss of life (IFL) are selected by literature survey, i.e., severity of dam break flood (S _F), population at risk (P _R), understanding of dam break (U _B), warning time (T _W) and evacuation condition (E _C). And the other IFL of weather during dam break (W _B), dam break mode (M _B), water storage (S _W), building vulnerability (V _B), dam break time (T _B) and average distance from affected area to dam (D _D) are also taken into account to get a more comprehensive consideration. According to disaster system and disaster risk, these eleven IFL are divided into four categories. Through the improved entropy method, eight key IFL are further selected out of the eleven. Secondly, four L modules are built based on four categories, which are L-causing factor module (M ₁), L-prone environment module (M ₂), affected body module (M ₃) and rescue condition module (M ₄). Eventually, by using two methods of multivariate nonlinear regression and leave-one-out cross-validation in combination with coupled four modules, the calculation method for L is established. Compared with the results of Graham method and D&M method, the result of the proposed one is much closer to the actual value and performs better in fitting effect and regional applicability. In the application, L calculation and consequence assessment are carried out in the example of Hengjiang reservoir that has already broken down. At the same time, L calculation and risk prediction are used in the analysis of Yunshan reservoir, which is under planning. The proposed method can not only be applied to estimate L and its rate (f _L ) under various types of dam break conditions in China, but also provide a reliable consequence assessment and prediction approach to reduce the risk of L.