1,721,031 research outputs found
Use of Heavy Metals Contaminated Industrial Hemp (Cannabis Sativa L.) for Bioenergy Production
No full textWorldwide human-related activities have caused the heavy metals contamination of large areas. Nowadays, different soil remediation activities are undertaken to ameliorate contaminated soils. Among the various soil reclamation technologies, phytoremediation is considered one of the most cost-effective and eco-friendly practices, where the use of industrial hemp (Cannabis sativa L.) has shown promising remediation potential. However, the proper management, disposal or valorization of the contaminated biomass represents a key point for the sustainability of the entire remediation process. This study aims to assess and evaluate the energy and environmental burdens of using heavy metals contaminated industrial hemp for bioenergy production. Specifically, the cumulative energy demand and climate change impact categories were selected from the life cycle assessment methodology. The data sample comes from real heavy metals contaminated sites, located in Sardinia (Italy), which have been subjected to soil reclamation by growing industrial hemp. The energy and environmental impacts of using the contaminated biomass as an energy resource were then modeled from a “field to wire” approach. The designed scenario analyzed the processes associated with field level, transportation, combustion of the contaminated biomass in a power plant and ash disposal. The results obtained underlined that the field level represents the main impacting process, while the electricity produced from the contaminated biomass allowed to save about 32 GJ ha−1 of primary energy while avoiding emissions of 642 kg CO2e per phytoremediated hectare. The study highlights that the use of heavy metals contaminated biomass for bioenergy production, improved the sustainability of soil reclamation activities turning unproductive lands into productive areas
Soil organic carbon in Italian forests and agroecosystems: Estimating current stock and future changes with a spatial modelling approach
No full textThe soil organic carbon (SOC) is the largest carbon pool in the terrestrial biosphere, second only to oceans, containing twice as much carbon as the atmosphere and three times that stored in global vegetation. Climate change (CC) is expected to impact this carbon pool. To date, large uncertainties still persist on the effects of CC on SOC stocks. In addition, a shortage of data related to regional SOC quantities of tree-covered areas and future changes under CC conditions is recognized. In this work, we used a spatial-explicit modelling approach to estimate the current SOC stock (at 2005) and future changes (at 2095) under CC conditions of the whole forest, tree crop, grassland, and pasture covered areas of Italy. A methodology was preliminarily implemented to obtain spatialized SOC estimates at a regional scale by using the CENTURY 5 model coupled with spatialized vegetation, soil, and climate data. We ran both moderate (RCP4.5) and extreme (RCP8.5) climatic scenarios, and used three Global Circulation Models for each one of the four ecosystems described above. The current SOC stock estimates range from 51.3 (orchards) to 129.5 Mg carbon ha−1 (coniferous forests) and we found an overall SOC stock in Italy ranging from 1320.1 to 1425.1 Tg. SOC projections under CC showed a moderate carbon loss suggesting that forest, grassland, and permanent crop soils could provide an important contribution to climate change mitigation
Physiological responses of cork oak and holm oak to the infections of pathogens involved in oak decline
No full textContrasting patterns and interpretations between a fire spread simulator and a machine learning model when mapping burn probabilities: A case study for Mediterranean areas
No full textTwo main approaches are commonly used to map fire-prone areas when designing firefighting and prevention campaigns: fire spread simulators and machine learning models. Despite they used mainly the same environ-mental variables, they differ in handling them. Thus, it is worth assessing differences in results and in-terpretations for supporting reliable decision-making process. Burn probabilities (BP) were calculated in Southern Italy using FlamMap and the Random Forest algorithm. Results showed contrasting spatial patterns, with Random Forest projecting more smoothed results than Flammap, which showed medium-high BP values only across some locations. In addition, BP from FlamMap and Random Forest differ across fuel types and environmental conditions. Results suggest that decisions based on fire simulators might be more tightly linked with actions preventing fire spread. In contrast, those based on machine learning might be more linked with fire occurrence elements not necessarily related to spreading, e.g., socioeconomic causes
Trends and changes of fire danger in Italy and its relationships with fire activity (1985-2008)
No full textWild fire risk in the rural-urban interface.
No full textRural-urban interface (RUI, synonym of WUI, wildland-urban interface) are key areas in land management and planning for wildfire risk mitigation. A tool for RUI mapping was developed to help decision makers cope with risk management. Several methods for fire-risk assessment in RUI were developed, depending on the scale, the geographical context and data availability.
Methods and tools were validated based on fire simulations and are now available. In addition,
projections of future risk in RUI were obtained using land cover and climate change simulations.In the next four or five decades, mitigation of wildfire risk will depend on land managers capacity
to control RUI development
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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