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Global warming is exacerbating weather, and climate extremes events and is projected to aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering cumulative and interactive impacts on a variety of natural and human systems. An improved understanding of risk interactions and dynamics is required to support decision makers in their ability to better manage current and future climate change risks. To face this issue, the research community has been starting to test new methodological approaches and tools, including the application of Machine Learning (ML) leveraging the potential of the large availability and variety of spatio-temporal big data for environmental applications. Given the increasing attention on the application of ML methods to Climate Change Risk Assessment (CCRA), this review mapped out the state of art and potential of these methods to this field of research. Scientometric and systematic analysis were jointly applied providing an in-depth review of publications across the 2000–2020 timeframe. The resulting output from the analysis showed that a huge variety of ML algorithms have been already applied within CCRA, among them, the most recurrent are Decision Tree, Random Forest, and Artificial Neural Network. These algorithms are often applied in an ensemble or hybridized way to analyze most of all floods and landslides risk events. Moreover, the application of ML to deal with remote sensing data is consistent and effective across reviewed CCRA applications, allowing the identification and classification of targets and the detection of environmental and structural features. On the contrary concerning future climate change scenarios, literature seems not to be very widespread into scientific production, compared to studies evaluating risks under current conditions. The same lack can be noted also for the assessment of cascading and compound hazards and risks, since these concepts are recently emerging in CCRA literature but not yet in combination with ML-based applications.
Federica Zennaro; Elisa Furlan; Christian Simeoni; Silvia Torresan; Sinem Aslan; Andrea Critto; Antonio Marcomini. Exploring machine learning potential for climate change risk assessment. Earth-Science Reviews 2021, 220, 103752 .
AMA StyleFederica Zennaro, Elisa Furlan, Christian Simeoni, Silvia Torresan, Sinem Aslan, Andrea Critto, Antonio Marcomini. Exploring machine learning potential for climate change risk assessment. Earth-Science Reviews. 2021; 220 ():103752.
Chicago/Turabian StyleFederica Zennaro; Elisa Furlan; Christian Simeoni; Silvia Torresan; Sinem Aslan; Andrea Critto; Antonio Marcomini. 2021. "Exploring machine learning potential for climate change risk assessment." Earth-Science Reviews 220, no. : 103752.
This paper contributes to the critical literature that links greening initiatives with the risk of gentrification. As urban areas become greener and provide high quality amenities, they attract wealthier residents, thus channelling the benefits of greening to a few. Most existing research has analysed the results of greening initiatives once they have been completed. This article explores green gentrification as a form of strategic action, by analysing the emerging Green Tree Strategy (GTS) for Porto Marghera, Italy. This area has undergone historical greening initiatives, beginning with the “garden city” of Enebezeer Howard (1902). The GTS is the newest green regeneration initiative in Porto Marghera. The data were collected via semi-structured interviews and through an online social network survey. The results show that the GTS has a clear ideological core – built around a new strategy of perception – but also that its appeal can be challenged in terms of industrial and employment displacement. The support for the GTS is fragmented and lacks consensus in Porto Marghera. However, if local actors are to successfully resist further attempts at green gentrification, they likely need to build an alternative vision, organized around a balanced development between green infrastructures and social inclusiveness.
Filip M. Alexandrescu; Lisa Pizzol; Andrea Critto. Green gentrification as strategic action: Exploring the emerging discursive and social support for the Green Tree Strategy in Porto Marghera, Italy. Cities 2021, 118, 103352 .
AMA StyleFilip M. Alexandrescu, Lisa Pizzol, Andrea Critto. Green gentrification as strategic action: Exploring the emerging discursive and social support for the Green Tree Strategy in Porto Marghera, Italy. Cities. 2021; 118 ():103352.
Chicago/Turabian StyleFilip M. Alexandrescu; Lisa Pizzol; Andrea Critto. 2021. "Green gentrification as strategic action: Exploring the emerging discursive and social support for the Green Tree Strategy in Porto Marghera, Italy." Cities 118, no. : 103352.
Freshwater ecosystems are negatively affected by climate change and human interventions modifying together supply and demand of ecosystem services (ES). Research on ES focused on assessing risks arising from the interaction among both stressors, integrating empirical data with expert knowledge. This work aims at incorporating Bayesian Networks (BN) approaches into ES appraisal, identifying key factors driving changes and trade-offs among ES potential under different scenarios. Applying the designed BN to the Taro River basin (TRB) in Italy, the outcomes showed a limited space to improve ES potential, as well as trade-offs between water yield and nutrient retention services due to changes in precipitation and land use patterns. Moreover, the analysis of key input variables highlighted that precipitation is the main driver affecting provisioning services while land use for the regulating ones. The results imply a low capacity to provide services in the medium term for the TRB where water was exploited for multiple competing objectives. Therefore, “win-win” spatial planning and water management strategies are needed to improve freshwater ES potential. The designed BN model represents a valuable decision support tool to quickly perform ES assessment and to identify the most suitable management plan to maintain benefits from freshwater ecosystems.
Hung Vuong Pham; Anna Sperotto; Elisa Furlan; Silvia Torresan; Antonio Marcomini; Andrea Critto. Integrating Bayesian Networks into ecosystem services assessment to support water management at the river basin scale. Ecosystem Services 2021, 50, 101300 .
AMA StyleHung Vuong Pham, Anna Sperotto, Elisa Furlan, Silvia Torresan, Antonio Marcomini, Andrea Critto. Integrating Bayesian Networks into ecosystem services assessment to support water management at the river basin scale. Ecosystem Services. 2021; 50 ():101300.
Chicago/Turabian StyleHung Vuong Pham; Anna Sperotto; Elisa Furlan; Silvia Torresan; Antonio Marcomini; Andrea Critto. 2021. "Integrating Bayesian Networks into ecosystem services assessment to support water management at the river basin scale." Ecosystem Services 50, no. : 101300.
Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps". 2021, 1 .
AMA StyleStefano Terzi, Janez Sušnik, Stefan Schneiderbauer, Silvia Torresan, Andrea Critto. Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps". . 2021; ():1.
Chicago/Turabian StyleStefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. 2021. "Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps"." , no. : 1.
Water management in mountain regions is facing multiple pressures due to climate change and anthropogenic activities. This is particularly relevant for mountain areas where water abundance in the past allowed for many anthropogenic activities, exposing them to future water scarcity. To better understand the processes involved in water scarcity impact, an innovative stochastic System Dynamics Modelling (SDM) explores water stored and turbined in the S.Giustina reservoir (Province of Trento, Italy). The integration of outputs from climate change simulations as well as from a hydrological model and statistical models into the SDM is a quick and effective tool to simulate past and future water availability and demand conditions. Short-term RCP4.5 simulations depict conditions of highest volume and outflow reductions starting in spring (−16.1 % and −44.7 % in May compared to the baseline). Long-term RCP8.5 simulations suggest conditions of volume and outflow reductions starting in summer and lasting until the end of the year. The number of events with stored water below the 30th and above the 80th quantiles suggest a general reduction both in terms of low and high volumes. These results call for the need to adapt to acute short-term water availability reductions in spring and summer while preparing for hydroelectric production reductions due to the chronic long-term trends affecting autumn and mid-winter. This study provides results and methodological insights for potential SDM upscaling across strategic mountain socio-economic sectors (e.g., hydropower, agriculture and tourism) to expand water scarcity assessments and prepare for future multi-risk conditions and impacts.
Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps. 2021, 2021, 1 -25.
AMA StyleStefano Terzi, Janez Sušnik, Stefan Schneiderbauer, Silvia Torresan, Andrea Critto. Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps. . 2021; 2021 ():1-25.
Chicago/Turabian StyleStefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. 2021. "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps." 2021, no. : 1-25.
Extreme weather and climate related events, from river flooding to droughts and tropical cyclones, are likely to become both more severe and more frequent in the coming decades, and the damages caused by these events will be felt across all sectors of society. In the face of this threat, policy- and decision-makers are increasingly calling for new approaches and tools to support risk management and climate adaptation pathways that can capture the full extent of the impacts. In the frame of the LODE DG ECHO project (https://www.lodeproject.polimi.it/), a GIS-based Bayesian Network (BN) approach is presented for the capturing and modelling of multi-sectoral flooding damages against future ‘what-if’ scenarios. Building on a risk-based conceptual framework, the BN model was trained and validated by exploiting data collected from the 2014 Secchia River flooding event, as well as other contextual variables. Moreover, a novel approach to defining the structure of the BN was performed, reconfiguring the model according to expert judgment and data-based validation. The model showed a good predictive capacity for damages in the agricultural, industrial and residential sectors, predicting the severity of damages with a classification accuracy of about 60% for each of these assessment endpoints. ‘What-if’ scenario analysis was performed to understand the potential impacts of future changes in i) land use patterns and ii) increasing flood depths resulting from more severe flood events. The output of the model showed a rising probability of experiencing high monetary damages under both scenarios. In spite of constraints within the case study dataset, the results of the appraisal show good promise, and together with the designed BN model itself represent a valuable support for disaster risk management and reduction actions against extreme river flooding events, enabling better informed decision making.
Remi Harris; Elisa Furlan; Hung Vuong Pham; Silvia Torresan; Jaroslav Mysiak; Andrea Critto. A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis. 2021, 1 .
AMA StyleRemi Harris, Elisa Furlan, Hung Vuong Pham, Silvia Torresan, Jaroslav Mysiak, Andrea Critto. A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis. . 2021; ():1.
Chicago/Turabian StyleRemi Harris; Elisa Furlan; Hung Vuong Pham; Silvia Torresan; Jaroslav Mysiak; Andrea Critto. 2021. "A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis." , no. : 1.
Understanding how natural and human-induced drivers will contribute to rising vulnerability and risks in coastal areas requires a broader use of future projections capturing the spatio-temporal dynamics which drive changes in the different vulnerability dimensions, including the socio-demographic and economic spheres. To go beyond the traditional approaches for coastal vulnerability appraisal, a Multi-dimensional Coastal Vulnerability Index (MDim-CVI) - integrating a composite set of physical, environmental and socio-economic indicators - is proposed to rank Italian coastal provinces according to their relative vulnerability to extreme sea level scenarios, in 2050. Specifically, information on hazard-prone areas, potentially inundated by sea level rise and extreme water levels (under the RCP8.5 climate scenario) is combined with indicators of geomorphic vulnerability (e.g. elevation, distance from coastline, shoreline evolution trend) exposure, and adaptive capacity (e.g. sensible segments of the population, GDP, land use patterns). The methodology is applied to a reference timeframe, representing current climate and land use condition, and a future scenario for the year 2050, integrating both climate projections and data simulating potential evolution of the environmental and socio-economic systems. Results show that most vulnerable provinces are located in the North Adriatic, the Gargano area and other Southern parts of Italy, mostly due to the very high vulnerability scores reported by climate-related indicators (e.g. extreme sea level). The number of vulnerable provinces as well as the magnitude of vulnerability is expected to increase in the future due to the worsening of climate, environmental, and socio-economic conditions (e.g. land use variations and increase of the elderly population). These outcomes can timely inform integrated coastal zone management and support climate adaptation planning.
E. Furlan; P. Dalla Pozza; M. Michetti; S. Torresan; A. Critto; A. Marcomini. Development of a Multi-Dimensional Coastal Vulnerability Index: Assessing vulnerability to inundation scenarios in the Italian coast. Science of The Total Environment 2021, 772, 144650 .
AMA StyleE. Furlan, P. Dalla Pozza, M. Michetti, S. Torresan, A. Critto, A. Marcomini. Development of a Multi-Dimensional Coastal Vulnerability Index: Assessing vulnerability to inundation scenarios in the Italian coast. Science of The Total Environment. 2021; 772 ():144650.
Chicago/Turabian StyleE. Furlan; P. Dalla Pozza; M. Michetti; S. Torresan; A. Critto; A. Marcomini. 2021. "Development of a Multi-Dimensional Coastal Vulnerability Index: Assessing vulnerability to inundation scenarios in the Italian coast." Science of The Total Environment 772, no. : 144650.
Climate change threatens coastal areas, posing significant risks to natural and human systems, including coastal erosion and inundation. This paper presents a multi-risk approach integrating multiple climate-related hazards and exposure and vulnerability factors across different spatial units and temporal scales. The multi-hazard assessment employs an influence matrix to analyze the relationships among hazards (sea-level rise, coastal erosion, and storm surge) and their disjoint probability. The multi-vulnerability considers the susceptibility of the exposed receptors (wetlands, beaches, and urban areas) to different hazards based on multiple indicators (dunes, shoreline evolution, and urbanization rate). The methodology was applied in the North Adriatic coast, producing a ranking of multi-hazard risks by means of GIS maps and statistics. The results highlight that the higher multi-hazard score (meaning presence of all investigated hazards) is near the coastline while multi-vulnerability is relatively high in the whole case study, especially for beaches, wetlands, protected areas, and river mouths. The overall multi-risk score presents a trend similar to multi-hazard and shows that beaches is the receptor most affected by multiple risks (60% of surface in the higher multi-risk classes). Risk statistics were developed for coastal municipalities and local stakeholders to support the setting of adaptation priorities and coastal zone management plans.
Valentina Gallina; Silvia Torresan; Alex Zabeo; Andrea Critto; Thomas Glade; Antonio Marcomini. A Multi-Risk Methodology for the Assessment of Climate Change Impacts in Coastal Zones. Sustainability 2020, 12, 3697 .
AMA StyleValentina Gallina, Silvia Torresan, Alex Zabeo, Andrea Critto, Thomas Glade, Antonio Marcomini. A Multi-Risk Methodology for the Assessment of Climate Change Impacts in Coastal Zones. Sustainability. 2020; 12 (9):3697.
Chicago/Turabian StyleValentina Gallina; Silvia Torresan; Alex Zabeo; Andrea Critto; Thomas Glade; Antonio Marcomini. 2020. "A Multi-Risk Methodology for the Assessment of Climate Change Impacts in Coastal Zones." Sustainability 12, no. 9: 3697.
We assess the relative vulnerability of the Mediterranean shoreline of Egypt (about 1000km length) to climate change (i.e., sea level rise, storm surge flooding, and coastal erosion) by using a Climate‐improved Coastal Vulnerability Index (CCVI). We integrate information relative to a multi‐dimensional set of physical, geological, and socio‐economic variables, and add to the mainstream literature the consideration of both a reference and a climate change scenario, assuming the RCP8.5 emissions concentration pathway for the 21st century in the Mediterranean region. Results report that ~1% (~43km²) of the mapped shoreline is classifiable as having a high or very high vulnerability, while ~80% (4652km²) shows very low vulnerability. As expected, exposure to inundation and erosion is especially relevant in highly developed and urbanized coastal areas. Along the shoreline, while the Nile Delta region is the most prone area to coastal erosion and permanent/occasional inundations (both in the reference and in the climate scenario), the Western Desert area results less vulnerable due to its geological characteristics (i.e. rocky/cliffed coasts, steeper coastal slope). The application of the CCVI in the coast of Egypt can be considered as a first screening of the hot spot risk areas at the national scale. The results of the analysis, including vulnerability maps and indicators, can be used to support the development of climate adaptation and integrated coastal zone management strategies. This article is protected by copyright. All rights reserved.
Silvia Torresan; Elisa Furlan; Andrea Critto; Melania Michetti; Antonio Marcomini. Egypt's Coastal Vulnerability to Sea‐Level Rise and Storm Surge: Present and Future Conditions. Integrated Environmental Assessment and Management 2020, 16, 761 -772.
AMA StyleSilvia Torresan, Elisa Furlan, Andrea Critto, Melania Michetti, Antonio Marcomini. Egypt's Coastal Vulnerability to Sea‐Level Rise and Storm Surge: Present and Future Conditions. Integrated Environmental Assessment and Management. 2020; 16 (5):761-772.
Chicago/Turabian StyleSilvia Torresan; Elisa Furlan; Andrea Critto; Melania Michetti; Antonio Marcomini. 2020. "Egypt's Coastal Vulnerability to Sea‐Level Rise and Storm Surge: Present and Future Conditions." Integrated Environmental Assessment and Management 16, no. 5: 761-772.
Freshwater ecosystems can be negatively affected by climate change and human interventions through the alteration of water supply and demand. There is an urgent need to protect the ecosystems, and the services they provide, to maintain their essential contribution to human wellbeing and economic prosperity, especially in a rapid and unpredictable global change context. In this work, we developed an integrated approach, coupling the outputs of ecosystem services (InVEST), climate (COSMO-CLM) and land use (LUISA) change models utilizing Bayesian Networks (BNs), to map freshwater-related Ecosystem Services (ESs), namely, water yield, nitrogen and phosphorus retention, and to assess their changes until 2050 under different management scenarios. First, InVEST was calibrated and validated with climate and land-use data to map and quantify ESs. Second, outputs of the ES model were integrated into the BN and the changes induced by different learning techniques and input settings were investigated. Finally, thousands of different scenarios were simulated testing multiple input variables configurations, thus allowing to describe the uncertainty of climate conditions, land-use change and water demand. Two types of inferences were conducted, namely, diagnostic and prognostic inference. The former permitted to find the best combination of the key drivers (i.e. precipitation, land-use, and water demand) so that ESs are maximized while the latter concentrated on the quantification of ESs under different scenarios. This approach was applied and validated in the Taro River basin in Italy. The results show that the values of all the three types of ESs would decline in the medium-term period under most scenarios. Moreover, there would be a limit of space to improve those values, especially for nutrient retention services. The obtained results provide valuable support to identify and prioritize the best management practices for sustainable water use, balancing the tradeoffs among services. This analysis allows decision-makers to pick up one scenario with a specific configuration of land-use and water demand to optimize relevant ESs within their basin. Finally, these decisions are transformed into a “decision space” where the values of selected services are plotted in the space of ES to represent the gain/loss of each decision.
Andrea Critto; Hung Vuong Pham; Anna Sperotto; Silvia Torresan; Elisa Furlan; Antonio Marcomini. An ecosystem-based approach to support water quality assessment and management under climate and land-use condition. 2020, 1 .
AMA StyleAndrea Critto, Hung Vuong Pham, Anna Sperotto, Silvia Torresan, Elisa Furlan, Antonio Marcomini. An ecosystem-based approach to support water quality assessment and management under climate and land-use condition. . 2020; ():1.
Chicago/Turabian StyleAndrea Critto; Hung Vuong Pham; Anna Sperotto; Silvia Torresan; Elisa Furlan; Antonio Marcomini. 2020. "An ecosystem-based approach to support water quality assessment and management under climate and land-use condition." , no. : 1.
The concept of circular economy (CE) has recently gained momentum in the political, scientific, and economic debate, especially in China and Europe. As a result, organizations and scholars have started to establish different sets of principles for its adoption. For this reason, it is important to identify and assess the differences and similarities among existing sets of CE principles, and how organizations and individuals understand and translate them into practice. In this paper, we firstly present a brief review and analysis of the coherence among six existing sets of principles. Our analysis finds that, despite the mixed degree of coherence, all sets describe the necessity to implement CE principles at all levels of a company. We then present the results of an in-depth qualitative survey that investigates how 19 key informants representing small, medium, and multinational companies based in China understand and carry out the CE principles laid out by the BSI standard BS 8001:2017; how these principles can transform the culture and processes of these companies; and what are the opportunities and threats that such transformation can bring. Results describe a good awareness and knowledge of the CE principles and an optimistic outlook concerning their adoption. At the same time, numerous barriers and threats that the implementation of these principles might entail are presented. Overall, respondents confirm the complexity of implementing the principles of the CE in an integrated and consistent way in the management and strategies of Chinese companies and highlight the challenges that might arise during their implementation.
Marco Pesce; Ilaria Tamai; Deyan Guo; Andrea Critto; Daniele Brombal; Xiaohui Wang; Hongguang Cheng; Antonio Marcomini. Circular Economy in China: Translating Principles into Practice. Sustainability 2020, 12, 832 .
AMA StyleMarco Pesce, Ilaria Tamai, Deyan Guo, Andrea Critto, Daniele Brombal, Xiaohui Wang, Hongguang Cheng, Antonio Marcomini. Circular Economy in China: Translating Principles into Practice. Sustainability. 2020; 12 (3):832.
Chicago/Turabian StyleMarco Pesce; Ilaria Tamai; Deyan Guo; Andrea Critto; Daniele Brombal; Xiaohui Wang; Hongguang Cheng; Antonio Marcomini. 2020. "Circular Economy in China: Translating Principles into Practice." Sustainability 12, no. 3: 832.
Oceans are changing faster than even observed before. Unprecedented climate variability is interacting with long-term trends, all against a backdrop of rising anthropogenic use of marine space. The growth of maritime activities is taking place without the full understanding of complex interactions between natural and human-induced changes, leading to a progressive decline of biodiversity and degradation of marine ecosystems. Against this complex interplay, marine managers and policy makers are increasingly calling for new approaches and tools allowing a multi-scenario assessment of environmental impacts arising from the complex interaction between natural and anthropogenic drivers, also in consideration of multiple marine plans objectives. Responding to this need, for the Adriatic Sea we developed a GIS-based Bayesian Network to evaluate the probability (and related uncertainty) of cumulative impacts under four ‘what-if’ scenarios representing different marine management options and climate conditions. We addressed issues concerning consequences of potential planning measures, as well as management programmes required to achieve environmental status targets, as required by relevant EU acquis. Results from the scenario analysis highlighted that an integrated approach to maritime spatial planning is required, combining more sustainable management options of marine spaces and resources with climate adaptation strategies. This approach to planning would allow to reduce human pressures on the marine environment and rise resilience of natural ecosystems to climate and human-induced disturbances, which would result in an overall decrease of cumulative impacts.
Elisa Furlan; Debora Slanzi; Silvia Torresan; Andrea Critto; Antonio Marcomini. Multi-scenario analysis in the Adriatic Sea: A GIS-based Bayesian network to support maritime spatial planning. Science of The Total Environment 2019, 703, 134972 .
AMA StyleElisa Furlan, Debora Slanzi, Silvia Torresan, Andrea Critto, Antonio Marcomini. Multi-scenario analysis in the Adriatic Sea: A GIS-based Bayesian network to support maritime spatial planning. Science of The Total Environment. 2019; 703 ():134972.
Chicago/Turabian StyleElisa Furlan; Debora Slanzi; Silvia Torresan; Andrea Critto; Antonio Marcomini. 2019. "Multi-scenario analysis in the Adriatic Sea: A GIS-based Bayesian network to support maritime spatial planning." Science of The Total Environment 703, no. : 134972.
With increasing evidence of climate change affecting the quality of water resources, there is the need to assess the potential impacts of future climate change scenarios on water systems to ensure their long-term sustainability. The study assesses the uncertainty in the hydrological responses of the Zero river basin (northern Italy) generated by the adoption of an ensemble of climate projections from 10 different combinations of a global climate model (GCM)–regional climate model (RCM) under two emission scenarios (representative concentration pathways (RCPs) 4.5 and 8.5). Bayesian networks (BNs) are used to analyze the projected changes in nutrient loadings (NO3, NH4, PO4) in mid- (2041–2070) and long-term (2071–2100) periods with respect to the baseline (1983–2012). BN outputs show good confidence that, across considered scenarios and periods, nutrient loadings will increase, especially during autumn and winter seasons. Most models agree in projecting a high probability of an increase in nutrient loadings with respect to current conditions. In summer and spring, instead, the large variability between different GCM–RCM results makes it impossible to identify a univocal direction of change. Results suggest that adaptive water resource planning should be based on multi-model ensemble approaches as they are particularly useful for narrowing the spectrum of plausible impacts and uncertainties on water resources.
Anna Sperotto; Josè Luis Molina; Silvia Torresan; Andrea Critto; Manuel Pulido-Velazquez; Antonio Marcomini. Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks. Sustainability 2019, 11, 4764 .
AMA StyleAnna Sperotto, Josè Luis Molina, Silvia Torresan, Andrea Critto, Manuel Pulido-Velazquez, Antonio Marcomini. Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks. Sustainability. 2019; 11 (17):4764.
Chicago/Turabian StyleAnna Sperotto; Josè Luis Molina; Silvia Torresan; Andrea Critto; Manuel Pulido-Velazquez; Antonio Marcomini. 2019. "Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks." Sustainability 11, no. 17: 4764.
Coastal erosion is an issue of major concern for coastal managers and is expected to increase in magnitude and severity due to global climate change. This paper analyzes the potential consequences of climate change on coastal erosion (e.g., impacts on beaches, wetlands and protected areas) by applying a Regional Risk Assessment (RRA) methodology to the North Adriatic (NA) coast of Italy. The approach employs hazard scenarios from a multi-model chain in order to project the spatial and temporal patterns of relevant coastal erosion stressors (i.e., increases in mean sea-level, changes in wave height and variations in the sediment mobility at the sea bottom) under the A1B climate change scenario. Site-specific environmental and socio-economic indicators (e.g., vegetation cover, geomorphology, population) and hazard metrics are then aggregated by means of Multi-Criteria Decision Analysis (MCDA) with the aim to provide an example of exposure, susceptibility, risk and damage maps for the NA region. Among seasonal exposure maps winter and autumn depict the worse situation in 2070–2100, and locally around the Po river delta. Risk maps highlight that the receptors at higher risk are beaches, wetlands and river mouths. The work presents the results of the RRA tested in the NA region, discussing how spatial risk mapping can be used to establish relative priorities for intervention, to identify hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies.
Valentina Gallina; Silvia Torresan; Alex Zabeo; Jonathan Rizzi; Sandro Carniel; Mauro Sclavo; Lisa Pizzol; Antonio Marcomini; Andrea Critto. Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part II: Consequences for Coastal Erosion Impacts at the Regional Scale. Water 2019, 11, 1300 .
AMA StyleValentina Gallina, Silvia Torresan, Alex Zabeo, Jonathan Rizzi, Sandro Carniel, Mauro Sclavo, Lisa Pizzol, Antonio Marcomini, Andrea Critto. Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part II: Consequences for Coastal Erosion Impacts at the Regional Scale. Water. 2019; 11 (6):1300.
Chicago/Turabian StyleValentina Gallina; Silvia Torresan; Alex Zabeo; Jonathan Rizzi; Sandro Carniel; Mauro Sclavo; Lisa Pizzol; Antonio Marcomini; Andrea Critto. 2019. "Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part II: Consequences for Coastal Erosion Impacts at the Regional Scale." Water 11, no. 6: 1300.
Climate change is likely to strongly affect both the qualitative and quantitative characteristics of water resources. However, while potential impacts of climate change on water availability have been widely studied in the last decades, their implication for water quality have been just poorly explored since now. Accordingly, an integrated assessment based on Bayesian Networks (BNs) was implemented in the Zero river basin (Northern Italy) to capture interdependencies between future scenarios of climate change with water quality alterations (i.e. changes in nutrients loadings). Bayesian Networks were used as integrative tool for structuring and combining the information available in existing hydrological models, climate change projections, historical observations and expert opinion producing alternative risk scenarios to communicate the probability (and uncertainty) of changes in the amount nutrients (i.e. NO3−, NH4+, PO43−) delivered from the basin under different climate change projections (i.e. RCP 4.5 and 8.5) The model predictive accuracy and uncertainty were evaluated through a cross comparison with existing observed data and hydrological models’ simulations (i.e. SWAT) available for the case study and, in addition, sensitivity analysis was performed to identify key input variables, knowledge gaps in model structurers and data. Simulated scenarios show that seasonal changes in precipitation and temperature are likely to modify both the hydrology and nutrient loadings of the Zero river with a high probability of an increase of freshwater discharge, runoff and nutrient loadings in autumn and a decrease in spring and summer with respect to the current conditions 1983–2012. Greater increase for both river flow and nutrients loadings are predicted under the medium and long term RCP8.5 scenarios. Diffuse pollution sources play a key role in determining the amount of nutrients loaded: both NH4+ and PO43− loadings are mainly influenced by changes in hydrological variables (i.e. runoff) while NO3− loadings, despite being highly dependent on flow conditions, are also influenced by agronomic practices and land use (i.e. irrigation, fertilization). Highlighting key components and processes from a multi-disciplinary perspective, BN outputs could support water managers in tracking future trends of water quality and prioritizing stressors and pollution sources thus paving the way for the identification of targeted typologies of management and adaptation strategies to maintain good water quality status under climate change conditions.
A. Sperotto; J.L. Molina; S. Torresan; A. Critto; M. Pulido-Velazquez; A. Marcomini. A Bayesian Networks approach for the assessment of climate change impacts on nutrients loading. Environmental Science & Policy 2019, 100, 21 -36.
AMA StyleA. Sperotto, J.L. Molina, S. Torresan, A. Critto, M. Pulido-Velazquez, A. Marcomini. A Bayesian Networks approach for the assessment of climate change impacts on nutrients loading. Environmental Science & Policy. 2019; 100 ():21-36.
Chicago/Turabian StyleA. Sperotto; J.L. Molina; S. Torresan; A. Critto; M. Pulido-Velazquez; A. Marcomini. 2019. "A Bayesian Networks approach for the assessment of climate change impacts on nutrients loading." Environmental Science & Policy 100, no. : 21-36.
Climate scenarios produce climate change-related information and data at a geographical scale generally not useful for coastal planners to study impacts locally. To provide a suitable characterization of climate-related hazards in the North Adriatic Sea coast, a model chain, with progressively higher resolution was developed and implemented. It includes Global and Regional Circulation Models representing atmospheric and oceanic dynamics for the global and sub-continental domains, and hydrodynamic/wave models useful to analyze physical impacts of sea-level rise and coastal erosion at a sub-national/local scale. The model chain, integrating multiple types of numerical models running at different spatial scales, provides information about spatial and temporal patterns of relevant hazard metrics (e.g., sea temperature, atmospheric pressure, wave height), usable to represent climate-induced events causing potential environmental or socio-economic damages. Furthermore, it allows the discussion of some methodological problems concerning the application of climate scenarios and their dynamical downscaling to the assessment of the impacts in coastal zones. Based on a balanced across all energy sources emission scenario, the multi-model chain applied in the North Adriatic Sea allowed to assess the change in frequency of exceedance of wave height and bottom stress critical thresholds for sediment motion in the future scenario (2070–2100) compared to the reference period 1960 to 1990. As discussed in the paper, such projections can be used to develop coastal erosion hazard scenarios, which can then be applied to risk assessment studies, providing valuable information to mainstream climate change adaptation in coastal zone management.
Silvia Torresan; Valentina Gallina; Silvio Gualdi; Debora Bellafiore; Georg Umgiesser; Sandro Carniel; Mauro Sclavo; Alvise Benetazzo; Elisa Giubilato; Andrea Critto. Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part I: A Multi-Model Chain for the Definition of Climate Change Hazard Scenarios. Water 2019, 11, 1157 .
AMA StyleSilvia Torresan, Valentina Gallina, Silvio Gualdi, Debora Bellafiore, Georg Umgiesser, Sandro Carniel, Mauro Sclavo, Alvise Benetazzo, Elisa Giubilato, Andrea Critto. Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part I: A Multi-Model Chain for the Definition of Climate Change Hazard Scenarios. Water. 2019; 11 (6):1157.
Chicago/Turabian StyleSilvia Torresan; Valentina Gallina; Silvio Gualdi; Debora Bellafiore; Georg Umgiesser; Sandro Carniel; Mauro Sclavo; Alvise Benetazzo; Elisa Giubilato; Andrea Critto. 2019. "Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part I: A Multi-Model Chain for the Definition of Climate Change Hazard Scenarios." Water 11, no. 6: 1157.
Assessing and managing cumulative impacts produced by interactive anthropogenic and natural drivers is a major challenge to achieve the sustainable use of marine spaces in line with the objectives of relevant EU acquis. However, the complexity of the marine environment and the uncertainty linked to future climate and socio-economic scenarios, represent major obstacles for understanding the multiplicity of impacts on the marine ecosystems and to identify appropriate management strategies to be implemented. Going beyond the traditional additive approach for cumulative impact appraisal, the Cumulative Impact Index (CI-Index) proposed in this paper applies advanced Multi-Criteria Decision Analysis techniques to spatially model relationships between interactive climate and anthropogenic pressures, the environmental exposure and vulnerability patterns and the potential cumulative impacts for the marine ecosystems at risk. The assessment was performed based on spatial data characterizing location and vulnerability of 5 relevant marine targets (e.g. seagrasses and coral beds), and the distribution of 17 human activities (e.g. trawling, maritime traffic) during a reference scenario 2000–2015. Moreover, projections for selected physical and biogeochemical parameters (temperature and chlorophyll ‘a’) for the 2035–2050 timeframe under RCP8.5 scenario, were integrated in the assessment to evaluate index variations due to changing climate conditions. The application of the CI-Index in the Adriatic Sea, showed higher cumulative impacts in the Northern part of the basin and along the Italian continental shelf, where the high concentration of human activities, the seawater temperature conditions and the presence of vulnerable benthic habitats, contribute to increase the overall impact estimate. Moreover, the CI-Index allowed understanding which are the phenomena contributing to synergic pressures creating potential pathways of environmental disturbance for marine ecosystems. Finally, the application in the Adriatic case showed how the output of the CI-Index can provide support to evaluate multi-risk scenarios and to drive sustainable maritime spatial planning and management.
Elisa Furlan; Silvia Torresan; Andrea Critto; Tomas Lovato; Cosimo Solidoro; Paolo Lazzari; Antonio Marcomini. Cumulative Impact Index for the Adriatic Sea: Accounting for interactions among climate and anthropogenic pressures. Science of The Total Environment 2019, 670, 379 -397.
AMA StyleElisa Furlan, Silvia Torresan, Andrea Critto, Tomas Lovato, Cosimo Solidoro, Paolo Lazzari, Antonio Marcomini. Cumulative Impact Index for the Adriatic Sea: Accounting for interactions among climate and anthropogenic pressures. Science of The Total Environment. 2019; 670 ():379-397.
Chicago/Turabian StyleElisa Furlan; Silvia Torresan; Andrea Critto; Tomas Lovato; Cosimo Solidoro; Paolo Lazzari; Antonio Marcomini. 2019. "Cumulative Impact Index for the Adriatic Sea: Accounting for interactions among climate and anthropogenic pressures." Science of The Total Environment 670, no. : 379-397.
Climate change has already led to a wide range of impacts on our society, the economy and the environment. According to future scenarios, mountain regions are highly vulnerable to climate impacts, including changes in the water cycle (e.g. rainfall extremes, melting of glaciers, river runoff), loss of biodiversity and ecosystems services, damages to local economy (drinking water supply, hydropower generation, agricultural suitability) and human safety (risks of natural hazards). This is due to their exposure to recent climate warming (e.g. temperature regime changes, thawing of permafrost) and the high degree of specialization of both natural and human systems (e.g. mountain species, valley population density, tourism-based economy). These characteristics call for the application of risk assessment methodologies able to describe the complex interactions among multiple hazards, biophysical and socio-economic systems, towards climate change adaptation. Current approaches used to assess climate change risks often address individual risks separately and do not fulfil a comprehensive representation of cumulative effects associated to different hazards (i.e. compound events). Moreover, pioneering multi-layer single risk assessment (i.e. overlapping of single-risk assessments addressing different hazards) is still widely used, causing misleading evaluations of multi-risk processes. This raises key questions about the distinctive features of multi-risk assessments and the available tools and methods to address them. Here we present a review of five cutting-edge modelling approaches (Bayesian networks, agent-based models, system dynamic models, event and fault trees, and hybrid models), exploring their potential applications for multi-risk assessment and climate change adaptation in mountain regions. The comparative analysis sheds light on advantages and limitations of each approach, providing a roadmap for methodological and technical implementation of multi-risk assessment according to distinguished criteria (e.g. spatial and temporal dynamics, uncertainty management, cross-sectoral assessment, adaptation measures integration, data required and level of complexity). The results show limited applications of the selected methodologies in addressing the climate and risks challenge in mountain environments. In particular, system dynamic and hybrid models demonstrate higher potential for further applications to represent climate change effects on multi-risk processes for an effective implementation of climate adaptation strategies.
Stefano Terzi; Silvia Torresan; Stefan Schneiderbauer; Andrea Critto; Marc Zebisch; Antonio Marcomini. Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation. Journal of Environmental Management 2018, 232, 759 -771.
AMA StyleStefano Terzi, Silvia Torresan, Stefan Schneiderbauer, Andrea Critto, Marc Zebisch, Antonio Marcomini. Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation. Journal of Environmental Management. 2018; 232 ():759-771.
Chicago/Turabian StyleStefano Terzi; Silvia Torresan; Stefan Schneiderbauer; Andrea Critto; Marc Zebisch; Antonio Marcomini. 2018. "Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation." Journal of Environmental Management 232, no. : 759-771.
The recently developed modelling tool MERLIN-Expo was applied to support the exposure assessment of an aquatic food web to trace metals in a coastal environment. The exposure scenario, built on the data from Daliao River estuary in the Liaodong Bay (Bohai Sea, China), affected by long-term and large-scale industrial activities as well as rapid urbanization in Liao River watershed, represents an interesting case-study for ecological exposure modelling due to the availability of local data on metal concentrations in water and sediment. The bioaccumulation of selected trace metals in aquatic organisms was modelled and compared with field data from local aquatic organisms. Both model results and experimental data demonstrated that As, Cd, Cu, Ni, Pb and Zn, out of examined metals, were accumulated most abundantly by invertebrates and less by higher trophic level species. The body parts of the sampled animals with the highest measured concentration of metals were predominantly muscles, intestine and liver and fish skin in the case of Cr. The Morris and extended Fourier Analysis (EFAST) were used to account for variability in selected parameters of the bioaccumulation model. Food assimilation efficiency and slopes and intercepts of two sub-models for calculating metal specific BCFs (BCFmetal-exposure concentration) and fish weight (Weightfish-Lengthfish) were identified as the most influential parameters on ecological exposure to selected metals.
Artur Radomyski; Kai Lei; Elisa Giubilato; Andrea Critto; Chunye Lin; Antonio Marcomini. Bioaccumulation of trace metals in aquatic food web. A case study, Liaodong Bay, NE China. Marine Pollution Bulletin 2018, 137, 555 -565.
AMA StyleArtur Radomyski, Kai Lei, Elisa Giubilato, Andrea Critto, Chunye Lin, Antonio Marcomini. Bioaccumulation of trace metals in aquatic food web. A case study, Liaodong Bay, NE China. Marine Pollution Bulletin. 2018; 137 ():555-565.
Chicago/Turabian StyleArtur Radomyski; Kai Lei; Elisa Giubilato; Andrea Critto; Chunye Lin; Antonio Marcomini. 2018. "Bioaccumulation of trace metals in aquatic food web. A case study, Liaodong Bay, NE China." Marine Pollution Bulletin 137, no. : 555-565.
Freshwater ecosystem services are negatively affected by factors such as climate change (e.g. changes in temperature, precipitation, and sea level rise) and human interventions (e.g. agriculture practices, impoundment of dams, and land use/land cover change). Moreover, the potential synergic impacts of these factors on ecosystems are unevenly distributed, depending on geographical, climatic and socio-economic conditions. The paper aims to review the complex effects of climatic and non-climatic drivers on the supply and demand of freshwater ecosystem services. Based on the literature, we proposed a conceptual framework and a set of indicators for assessing the above-mentioned impacts due to global change, i.e. climate change and human activities. Then, we checked their applicability to the provisioning services of two well-known case studies, namely the Po River basin (Italy) and the Red River basin (Vietnam). To define the framework and the indicators, we selected the most relevant papers and reports; identified the major drivers and the most relevant services; and finally summarized the fundamental effects of these drivers on those services. We concluded that the proposed framework was applicable to the analyzed case studies, but it was not straightforward to consider all the indicators since ecosystem services were not explicitly considered as key assessment endpoints in these areas. Additionally, the supply of ecosystem services was found to draw much more attention than their demand. Finally, we highlighted the importance of defining a common and consistent terminology and classification of drivers, services, and effects to reduce mismatches among ecosystem services when conducting a risk assessment.
Hung Vuong Pham; Silvia Torresan; Andrea Critto; Antonio Marcomini. Alteration of freshwater ecosystem services under global change – A review focusing on the Po River basin (Italy) and the Red River basin (Vietnam). Science of The Total Environment 2018, 652, 1347 -1365.
AMA StyleHung Vuong Pham, Silvia Torresan, Andrea Critto, Antonio Marcomini. Alteration of freshwater ecosystem services under global change – A review focusing on the Po River basin (Italy) and the Red River basin (Vietnam). Science of The Total Environment. 2018; 652 ():1347-1365.
Chicago/Turabian StyleHung Vuong Pham; Silvia Torresan; Andrea Critto; Antonio Marcomini. 2018. "Alteration of freshwater ecosystem services under global change – A review focusing on the Po River basin (Italy) and the Red River basin (Vietnam)." Science of The Total Environment 652, no. : 1347-1365.