Advanced search in
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
12,097 Research products, page 1 of 1,210

  • 2013-2022
  • Archivio istituzionale della ricerca - Università degli Studi di Venezia Ca' Foscari

10
arrow_drop_down
Date (most recent)
arrow_drop_down
  • Open Access English
    Authors: 
    Francesco Pietro Colelli; Malcolm Mistry;
    Country: Italy
    Project: EC | ENERGYA (756194)
  • Open Access English
    Authors: 
    Amir Yazdani; Satoshi Takahama; John K. Kodros; Marco Paglione; Mauro Masiol; Stefania Squizzato; Kalliopi Florou; Christos Kaltsonoudis; Spiro D. Jorga; Spyros N. Pandis; +1 more
    Country: Italy
    Project: EC | PyroTRACH (726165), SNSF | Characterizing functional... (172923)

    <p>Fine particulate matter (PM) affects visibility, climate, and public health. Biomass burning (BB) in the forms of residential wood burning, wildfires, and prescribed burning is a major source of primary and secondary organic matter (OM, an important fraction fine PM), and brown and black carbon (BrC and BC). The contribution of BB to the atmospheric fine PM is only expected to increase in the foreseeable future. Recent studies have highlighted the enhancement in the biomass burning organic aerosol (bbOA) concentrations with aging and reported on the chemical composition of the secondary biomass burning organic aerosol (bbSOA) formed under different conditions. However, the chemical processing of the primary biomass burning organic aerosol (bbPOA) with aging is not well characterized. This chemical processing can potentially alter the chemical composition of bbOA drastically and render its identification and quantification in the atmosphere difficult.</p><p> </p><p>             We used aerosol mass spectrometry (AMS) and Fourier transform infrared spectroscopy (FTIR) as two complementary methods to quantify the bbPOA aging in this study. AMS measures the bulk composition of OM with a relatively high temporal resolution but provides limited parent compound information due to the extensive fragmentation. FTIR, carried out on PTFE filter samples, provides detailed information about the functional group composition of the OM and certain bbOA makers at the expense of a relatively low temporal resolution. In a series of aging experiments at the Center for Studies of Air Qualities and Climate Change (C-STACC), primary emissions from wood and pellet stoves were injected into an environmental simulation chamber. Primary emissions were aged using hydroxyl and nitrate radicals simulating the atmospheric day-time and night-time oxidation.  A high-resolution time-of-flight (HR-TOF) AMS was used to identify the composition of non-refractory PM<sub>1</sub>. PM<sub>1</sub> was also collected on PTFE filters before and after aging for the off-line FTIR analysis.</p><p> </p><p>                AMS and FTIR agreed well in terms of the measured bbOA mass concentrations, elemental ratios, and the evolution of biomass burning tracers. We developed a procedure to quantify the bbPOA aging using AMS and FTIR. Using AMS, we found that up to 17 % of the bbPOA mass underwent some form of transformation with aging. This transformation was more intense under day-time conditions. FTIR detected a more extensive oxidation (up to two times that of AMS), suggesting a substantial processing of bbPOA, and revealing the limitations of AMS to capture bbPOA aging due to the extensive fragmentation. Different bbOA-related ion fragments were observed to decay at different rates under different conditions (e.g., oxidants and relative humidity). These different decay rates can potentially be used to identify the extent of bbPOA aging in the atmosphere. The bbSOA formed during the daytime oxidation was dominated by acid contributions, resembling certain atmospheric biomass burning samples. The unique, acid-dominated FTIR spectrum of bbSOA can potentially be used as another indicator of the aged bbOA in the atmosphere.</p>

  • Open Access
    Authors: 
    Matteo Cinelli; Antonio Peruzzi; Ana Lucía Schmidt; Roberta Villa; Enrico Costa; Walter Quattrociocchi; Fabiana Zollo;
    Publisher: Public Library of Science (PLoS)
    Country: Italy
    Project: EC | QUEST (824634)

    The COVID-19 pandemic made explicit the issues of communicating science in an information ecosystem dominated by social media platforms. One of the fundamental communication challenges of our time is to provide the public with reliable content and contrast misinformation. This paper investigates how social media can become an effective channel to promote engagement and (re)build trust. To measure the social response to quality communication, we conducted an experimental study to test a set of science communication recommendations on Facebook and Twitter. The experiment involved communication practitioners and social media managers from select countries in Europe, applying and testing such recommendations for five months. Here we analyse their feedback in terms of adoption and show that some differences emerge across platforms, topics, and recommendation categories. To evaluate these recommendations’ effect on users, we measure their response to quality content, finding that the median engagement is generally higher, especially on Twitter. The results indicate that quality communication strategies may elicit positive feedback on social media. A data-driven and co-designed approach in developing counter-strategies is thus promising in tackling misinformation.

  • Open Access
    Authors: 
    Komla Mawulom Agudze; Monica Billio; Roberto Casarin; Francesco Ravazzolo;
    Publisher: Elsevier BV
    Country: Italy

    Abstract This paper introduces a new dynamic panel model with multi-layer network effects. Series-specific latent Markov chain processes drive the dynamics of the observable processes, and several types of interaction effects among the hidden chains allow for various degrees of endogenous synchronization of both latent and observable processes. The interaction is driven by a multi-layer network with exogenous and endogenous connectivity layers. We provide some theoretical properties of the model, develop a Bayesian inference framework and an efficient Markov Chain Monte Carlo algorithm for estimating parameters, latent states, and endogenous network layers. An application to the US-state coincident indicators shows that the synchronization in the US economy is generated by network effects among the states. The inclusion of a multi-layer network provides a new tool for measuring the effects of the public policies that impact the connectivity between the US states, such as mobility restrictions or job support schemes. The proposed new model and the related inference are general and may find application in a wide spectrum of datasets where the extraction of endogenous interaction effects is relevant and of interest.

  • Publication . Article . Other literature type . 2022
    Open Access
    Authors: 
    Roberto Casarin; Matteo Iacopini; Monica Billio;
    Publisher: Informa UK Limited
    Country: Italy
    Project: EC | STEADY (887220)

    Modeling time series of multilayer network data is challenging due to the peculiar characteristics of real-world networks, such as sparsity and abrupt structural changes. Moreover, the impact of external factors on the network edges is highly heterogeneous due to edge- and time-specific effects. Capturing all these features results in a very high-dimensional inference problem. A novel tensor-on-tensor regression model is proposed, which integrates zero-inflated logistic regression to deal with the sparsity, and Markov-switching coefficients to account for structural changes. A tensor representation and decomposition of the regression coefficients are used to tackle the high-dimensionality and account for the heterogeneous impact of the covariate tensor across the response variables. The inference is performed following a Bayesian approach, and an efficient Gibbs sampler is developed for posterior approximation. Our methodology applied to financial and email networks detects different connectivity regimes and uncovers the role of covariates in the edge-formation process, which are relevant in risk and resource management. Code is available on GitHub. Supplementary materials for this article are available online.

  • Open Access English
    Authors: 
    Liliana Velea; Alessandro Gallo; Roxana Bojariu; Anisoara Irimescu; Vasile Craciunescu; Silvia Puiu;
    Country: Italy
    Project: EC | WeCENT (887544)

    Nature, landscape, relaxation, and outdoor activities are important motivations when choosing rural destinations for vacations. Therefore, when selecting a rural area as a vacation destination, we assume that climate features are important. We investigated the appropriateness of the holiday climate index: urban (HCI:urban) in quantitatively describing the relationship between climate and tourism fluxes in such destinations. We employed data from 94 urban and rural tourist destinations in Romania and correlated the monthly mean HCI:urban values with sectoral data (overnight tourists) for 2010–2018. The results show that weather and climate influenced tourism fluxes similarly in rural and urban destinations, supporting the hypothesis that HCI:urban may be used for rural areas as well. The information derived from HCI:urban may be useful for tourists when planning their vacations as well as for tourism investors in managing their businesses and reducing the weather and climate-related seasonality in tourism fluxes.

  • Publication . Article . 2022
    Open Access
    Authors: 
    Giacomo Trapasso; Giovanna Mazzi; Beatriz Chícharo; Mattia Annatelli; Davide Dalla Torre; Fabio Aricò;
    Publisher: American Chemical Society (ACS)
    Country: Italy
  • Open Access English
    Authors: 
    Silvia Puiu; Liliana Velea; Mihaela Tinca Udristioiu; Alessandro Gallo;
    Country: Italy

    The main objective of our research is to identify the impact of recycling and waste reduction behavior on the sustainable tourism decisions of Romanian youngsters (18–25 years old). We used the PLS-SEM method and introduced four variables in the model: sustainable tourism decisions, the interest in recycling, the interest in waste reduction, and the interest in natural and less polluted touristic destinations. The main results emphasize the direct influence of recycling and waste reduction behaviors on the decisions made by Generation Z regarding sustainable tourism and on their preference for destinations that are better preserved and less touched by human intervention. The novelty of our research consists of the fact that we introduced variables such as waste reduction from the perspective of tourists because most studies address it as a management approach of the companies in the tourism sector. The findings are useful for managers in the tourism sector to create better strategies for attracting the younger generation who are preoccupied by environmental issues and sustainability in general.

  • Open Access
    Authors: 
    Sebastiano Cattaruzzo; Mercedes Teruel;
    Publisher: Elsevier BV
    Country: Italy
    Project: EC | MFP (713679)
  • Open Access
    Authors: 
    Heidi Kreibich; Anne F. Van Loon; Kai Schröter; Philip J. Ward; Maurizio Mazzoleni; Nivedita Sairam; Guta Wakbulcho Abeshu; Svetlana Agafonova; Amir AghaKouchak; Hafzullah Aksoy; +82 more
    Countries: Sweden, Germany, Netherlands, France, Netherlands, Italy, United Kingdom
    Project: EC | SECurITY (787419)

    AbstractRisk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Send a message
How can we help?
We usually respond in a few hours.