Search

This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM’s application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period.

This paper follows a bibliometric assessment methodology to provide a systematic review of studies devoted to cultural heritage (CH) buildings that simultaneously refer to hygrothermal conditions and/or behavior and climate change (CC) scenarios. Moreover, this paper aims at identifying the main research trend and research gaps in this combined research field, and to provide a critical discussion of previous works relating to CH, hygrothermal behavior, and CC. Scopus database was used for data gathering and export, followed by VOSviewer for network visualization. The advanced search on the database showed that only 36 documents have considered the study of these three subjects together, as of 2022. The majority of research has been carried out in Italy (27% of the relevant documents). This paper further describes some funded research projects on the topic of CH, hygrothermal behavior, and CC. It was concluded that the investigation on this combined research topic is very recent and scarcely unexplored, and further research is required to assess how future CC scenarios will affect the hygrothermal behavior of CH buildings. These new understandings are fundamental for all stakeholders involved in topics related to heritage conservation and assessment of the hygrothermal behavior of buildings.

Several factors control the vulnerability of historic geostructures to climate change. These factors are both temporally and spatially variable depending on construction techniques and climatic conditions. This paper provides a review of both the historical construction practices on the UK transport network and recent developments in the understanding of climate change effects, allowing for an assessment of the impact of climate change on existing geostructures. Geostructures in the UK can be split between pre-regulation and post-regulation construction techniques. In general, highways were constructed after the implementation of modern regulations and are therefore less vulnerable to climate change due to formalisation of construction methods. In comparison, the performance of the railway network has shown to be inferior due to historic construction practices including poor or absent compaction, lack of consideration for foundations, or selection of fill materials. Recent findings have shown that the impacts of climate change are also a multiscale problem, influenced not only by regional geology but also the pore structure of soils and its evolution. While the research into these impacts is critical, the limitations of common methods employed to survey these structures and study the behaviour of their constituent materials requires consideration. In this paper, these aspects are examined in detail in a bid to integrate holistically the complexity of the systems involved.

Waste-to-energy (WtE) incineration is an important technique in waste management systems and waste hierarchy. It is used to treat approximately 63% of the waste in European countries. The flue gas volumetric rate and its composition are essential to determine and monitor the emissions from waste incineration plants. This paper presents two methodologies used to evaluate the emissions from incinerators during the design phase. The first consists of a set of equations applicable in Excel (calculation model), while the second is the built-in components in Ebsilon 13.2 software which simulates the emissions from a furnace. This paper also proposes a comprehensive flue gas cleaning system for a simulated waste incineration plant in Jordan. According to Ebsilon, the results showed that for a 25 kg/s loading rate, there was 258,514 mg/Nm3, 749.90 mg/Nm3, 890.20 mg/Nm3, and 717 mg/Nm3 of CO2, NO2, SO2, and HCL, respectively. It was noted that these values relate to 1.5 of excess air ratio, where the effect of excess air ratio as the main driver for any combustion process was examined. The calculation method (set of equations) evaluated the flue gas volumetric rate, the CO2 emissions, and N2O and SO2 levels. Ebsilon allows for simulation of the treatment stages and calculates the amount of materials required. Selective non-catalytic reduction (SNCR) (a built-in component in the Ebsilon library) was used to treat the NO2 emissions. For 1.5 of excess air ratio, those emissions were reduced from 749 mg/Nm3 to 180 mg/Nm3, while the Ca(OH)2 injector used to treat the SO2 and HCL emissions reduced emissions from 890.20 mg/Nm3 and 717 mg/Nm3 to 44 mg/Nm3 and 7.16 mg/Nm3, respectively. Regarding the reduction in CO2, the spherical carbon absorption concept was simulated using 9.4 kg/s of carbon which was adequate to verify a 91% reduction rate of CO2. Furthermore, the calculation model was validated and approved as a valuable model to predict the flue gas volume, the oxygen required, and flue gas emissions at the design stage.

This paper investigates the capabilities and limitations of different software tools simulating landscape design adaptability. The evaluation of tools is based on the ISO 25010 framework, which investigates software functionality, reliability, performance efficiency, usability, compatibility, and information quality. These quality characteristics of software are analysed during objective experiments where five software tools are used for a case study project at the conceptual design phase. These experiments reveal that the existing software tools for climate adaptation planning are focused on different aspects of climate adaptability, generating different types of information. Moreover, all tools deal with some limitations in terms of compatibility, performance efficiency, and functional operations. The ISO 25010 quality model provides a comprehensive framework to compare the capabilities of different software tools for climate adaptation planning. This paper is part of a wider study including an analysis of the needs of project stakeholders regarding climate adaptation software tools. However, this article focuses on technical capabilities of current climate adaptation software tools.

Climate change due to the greenhouse effect will affect meteorological variables, which in turn will affect the demand for electrical energy and its generation in coming years. These impacts will become increasingly important in accordance with the increasing penetration of renewable, non-programmable energy sources (e.g., wind and solar). Specifically, the speed and amplitude of power system transformation will be different from one country to another according to many endogenous and exogenous factors. Based on a literature review, this paper focuses on the impact of climate change on the current, and future, Italian power system. The paper shows a wide range of results, due not just to the adopted climate change models used, but also to the models used to assess the impact of meteorological variables on electricity generation and demand. Analyzing and interpreting the reasons for such differences in the model results is crucial to perform more detailed numerical analyses on the adequacy and reliability of power systems. Concerning Italian future scenarios, the double impact of uncertainties in national policies and changes in power plant productivity and demand, has been considered and addressed.

Peatlands can become valuable resources and greenhouse gas sinks through the use of different management practices. Peatlands provide carbon sequestration; however, they are also among the greatest greenhouse gas emissions sources. The estimated annual carbon dioxide equivalent emissions from peat worldwide are 220 million tons. Novel strategies, methods, and technologies must be developed to enhance the sustainable use of peatlands and achieve climate targets by 2050, as set forth by the European Commission. There is no consensus in the scientific literature on which strategies included in the policy documents are more fruitful for reducing emissions. There are uncertainties and knowledge gaps in the literature that summarise the cons and benefits of each strategy regarding the potential of GHG emission reduction. Currently, peat is undervalued as a resource in the bioeconomy and innovation—a way that could save costs in peatland management. This review paper aims to analyse existing and potential strategies to minimise greenhouse gas emissions from peatlands. Studies show significant debates in the literature on whether the rewetting of peatlands and afforestation of previously drained peatlands can be defined as restoration. A more effective management of peatland restoration should involve combining restoration methods. The rewetting of peatlands should be realised in combination with top-soil removal to minimise methane emissions. The rewetting of peatlands should be used only in combination with revegetation after rewetting. One of the promising solutions for methane emission reduction could be paludiculture using sphagnum species. Products from paludiculture biomass can reduce GHG emissions and store long-term emissions in products. Paludiculture can also be the solution for further income for landowners and innovative products using the biomass of harvested paludiculture plants.

This paper offers a comprehensive overview of machine learning (ML) methodologies and algorithms, highlighting their practical applications in the critical domain of water resource management. Environmental issues, such as climate change and ecosystem destruction, pose significant threats to humanity and the planet. Addressing these challenges necessitates sustainable resource management and increased efficiency. Artificial intelligence (AI) and ML technologies present promising solutions in this regard. By harnessing AI and ML, we can collect and analyze vast amounts of data from diverse sources, such as remote sensing, smart sensors, and social media. This enables real-time monitoring and decision making in water resource management. AI applications, including irrigation optimization, water quality monitoring, flood forecasting, and water demand forecasting, enhance agricultural practices, water distribution models, and decision making in desalination plants. Furthermore, AI facilitates data integration, supports decision-making processes, and enhances overall water management sustainability. However, the wider adoption of AI in water resource management faces challenges, such as data heterogeneity, stakeholder education, and high costs. To provide an overview of ML applications in water resource management, this research focuses on core fundamentals, major applications (prediction, clustering, and reinforcement learning), and ongoing issues to offer new insights. More specifically, after the in-depth illustration of the ML algorithmic taxonomy, we provide a comparative mapping of all ML methodologies to specific water management tasks. At the same time, we include a tabulation of such research works along with some concrete, yet compact, descriptions of their objectives at hand. By leveraging ML tools, we can develop sustainable water resource management plans and address the world’s water supply concerns effectively.

Machine learning is often used to predict crop yield based on the sowing date and weather parameters in non-irrigated crops. In the context of climate change, regression algorithms can help identify correlations and plan agricultural activities to maximise production. In the case of sunflower crops, we identified datasets that are not very large and have many missing values, generating a low-performance regression model. In this paper, our aim is to study and compare several approaches for missing-value imputation in order to improve our regression model. In our experiments, we compare nine imputation methods, using mean values, similar values, interpolation (linear, spline, pad), and prediction (linear regression, random forest, extreme gradient boosting regressor, and histogram gradient boosting regression). We also employ four unsupervised outlier removal algorithms and their influence on the regression model: isolation forest, minimum covariance determinant, local outlier factor and OneClass-SVM. After preprocessing, the obtained datasets are used to build regression models using the extreme gradient boosting regressor and histogram gradient boosting regression, and their performance is compared. The evaluation of the models shows an increased R2 from 0.723 when removing instances with missing data, to 0.938 for imputation using Random Forest prediction and OneClass-SVM-based outlier removal.

This paper presents a multidisciplinary approach to understand the impacts of temperature increase on the retention of particulate pollutants, such as heavy metals and microplastics, by the road pavement material. A soil with a particle size distribution similar to road dust was selected. A Wheel Tracking device was used to assess the permanent deformation behavior of prismatic specimens and the retention of the dust, at controlled temperatures of 40 °C and 60 °C, likely to occur on pavement in the future. The soil representing road pollutants was placed at the top of the slabs prior to the Wheel Tracking Test (WTT), based on the European Standard EN 12697-22:2020. After the WTT, two common methods were used, in order to evaluate the soil retention (pollution accumulation) on road pavement. The results confirm that the viscoelastic behavior of bituminous mixtures under increased temperatures can contribute to particle retention at the pavement. Future studies are needed to understand the phenomena, the retention characteristics by different bituminous mixtures, and the efficiency of pollutants capture. The work opens the opportunity to develop innovative road pavement bituminous mixtures that can reduce the discharge of road particulate pollutants, and have increased resilience and sustainability in extreme weather conditions.

A render is the first protective layer of exterior walls against the outdoor climate, which, due to its constitution, aims to gradually slow down the liquid moisture penetration to prevent it from reaching the wall inner layers. Due to the future expected changes in the outdoor climate, today’s exterior mortar might not be adequately designed to protect these walls. This paper aims to analyse the influence of mortars on the hygrothermal performance of solid brick walls under current and future climates. The study includes four types of assemblies and three types of mortars, and it was carried out for Lisbon and three other climates by using a computational simulation tool. Finally, the moisture gains and respective reach due to the future wind-driven rain (WDR) spells were assessed by means of using future weather files for Lisbon’s climate. It was shown that the solid brick layer is influenced differently depending on the characteristics of the mortar layers and outdoor conditions. In terms of WDR spells, aside from the precipitation and the spell period, the distribution of the WDR events within the spell also conditions the dryness of the assembly. The depth that the outdoor moisture was able to reach varies between 94 and 200 mm.

The world’s population keeps growing together with the construction rate of buildings that need to reduce their environmental footprint in order to mitigate global warming. This paper analyses if the spread of green buildings can be used as an indicator of broader sustainable development. The study is carried out with data taken from Eurostat Database and green buildings directories for 27 EU countries in the 10-year period spanning from 2010 to 2019. The relationship between the indicators is examined through simple linear regressions, and the results confirm the Environmental Kuznets Curve hypothesis: in developed countries, a growing economy (more GDP) is related to an environmental improvement (fewer GHG emissions). In addition, this study proves that the variance of green buildings expresses with a consistent probability the variance of GDP per capita (p-value = 0.0004 and R2 = 0.8475) and the variance of GHG emissions (p-value = 0.0002 and R2 = 0.8825), meaning that green buildings are indeed an indicator of sustainable development. This is due to the upfront cost required to implement advanced construction technologies that ultimately cut GHG emissions during the building lifecycle. This also points out that policy makers should encourage green building implementation through tax relieves and grants.

Coastal regions in Southwest Europe have experienced major interventions and transformations of the territory with unprecedented urban development, primarily related to growing tourism activity. The coast is the place where marine and terrestrial processes converge, making it highly vulnerable to the effects of climate change. However, the lack of information on the frequency of these extreme weather events and their impacts on the coast hampers an accurate analysis of the consequences of global change. This paper provides a detailed analysis of the extreme weather events (EWE) that have affected the Atlantic and Mediterranean coasts of Southwest Europe during the period from 1 January 2009 to 28 February 2020, as well as a quantification of their impacts: fatalities, injuries and economic damage. Official sources from France, Portugal and Spain were consulted, along with technical reports, scientific articles, etc., to generate a unified database. A total of 95 significant extreme events have caused 168 fatalities, 137 injuries and almost €4000 M in direct economic losses. Cyclone Xynthia (February 2010) on the French Atlantic coast stands out, having caused 47 fatalities, 79 injuries and substantial economic losses valued at €3000 M. The study shows a slight upward trend in the number of events recorded, especially during the last three years of the analysis, as well as in human losses and damages. The results reveal a higher exposure of the Mediterranean coast of Southwest Europe when compared to the Atlantic, especially the Spanish Mediterranean coast, with 61% of the fatalities recorded there during the study period. This is primarily due to a model of exponential tourism growth on the Mediterranean coast, with an enormous urban and infrastructure development during the last decades. Traditionally, the Mediterranean coast is less prepared to reduce the effects of marine storms, extreme events that are becoming more frequent and virulent in the context of climate and global change. This work highlights the need to create a continuous monitoring system–at the European level–of the impacts of extreme weather events on the coast, where 40% of the European population is concentrated. This observatory should serve as a source of information for risk mitigation policies (predictive, preventive and corrective), as well as for emergency management during disasters.

The increasing presence of non-programmable renewable energy plants increases the intermittency of the electricity supply and thus threatens the adequacy of a power system. Hydropower can solve this problem due to its flexibility. This paper applies statistical approaches to assess water availability in the context of hydropower generation and adequacy analysis on a seasonal basis for one site in Sicily and the other in Sardinia, where major hydroelectric plants are present. First, an empirical relationship between soil moisture content (SMC) and potential evapotranspiration (ET0) is evaluated through linear regression analysis. Then, precipitation trends over the last twenty years are analyzed to determine any effects of global warming on water availability. Finally, Monte Carlo algorithms are used for the stochastic generation of hourly precipitation, direct runoff profiles, and daily SMC profiles. Strong positive and negative correlations between ET0 and SMC (p < 0.05), and R2 ≥ 0.5 are found for both sites, except for summer, and R2 ≥ 0.5 is obtained. The cumulative pH-historical precipitation shows changes in seasonal trends, with evidence of a decrease at the annual level. The algorithms used to synthetically generate hourly precipitation and direct runoff profiles, as well as daily SMC profiles, effectively simulate the statistical variability of the historical profiles of these physical quantities.

Water temperature in lakes is their basic property that determines many processes. Changes in average values are thoroughly investigated using a long-term approach. Knowledge of extreme situations such as temperature minimums is still insufficient. This paper analyses changes in the minimum temperature in 10 lakes in Poland in the period 1972–2021. The obtained results show variability over the course of the parameter, both at the annual and monthly scale. In the first case, half of the analysed set showed statistically significant increasing trends (on average 0.10 °C per decade). In the latter case, the greatest changes occurred in the months of the warm half-year (on average 0.57 °C per decade). The reported situation is caused by the individual conditions of particular lakes, i.e., their location, morphometric parameters, or the dynamics of the occurrence of ice phenomena. A successive increase in the minimum temperature in lakes has its consequences for biotic and abiotic processes. Exceeding specific thresholds results in the evident transformation of these ecosystems.

Energy retrofits can enhance the liveability and efficiency of historic buildings while preserving their historic and aesthetic values. However, measures like improved insulation and airtightness may increase their vulnerability to overheating and climate change may further worsen their performance in the future. This paper investigates indoor overheating risks brought by climate change in retrofitted historic buildings and proposes effective adaptation strategies. Firstly, local weather conditions are analysed to identify homogenous climatic zones. For each climatic zone, “a business-as-usual” emissions scenario is adopted, and most representative regional climate models are selected to obtain hourly output of future climate projection. A comparative study is adopted where typical alpine residential buildings, “Portici house”, are simulated with regard to future energy use and indoor thermal state using the dynamic model in EnergyPlus. Energy use and indoor thermal conditions are compared before and after energy retrofit, as well as under present and future climate conditions. The results demonstrate that retrofit interventions could significantly improve energy efficiency of historic buildings in both present and future scenarios. A change in climate together with retrofit interventions will, however, result in higher risk of indoor overheating in South Tyrol. Potential negative side effects of energy retrofit could be controlled by adopting adequate shading and ventilation approaches that minimise, or eliminate, the risk of overheating during high temperature periods while optimising historic buildings’ energy performance.

When climate change became a global concern in the 1980s, mitigation was considered the best strategy to address all challenges. For a long time, it was thought possible to stabilize atmospheric concentrations of greenhouse gases (GHGs), which, according to many experts, brought on an unfit adaptation. There are international agreements designed to significantly reduce CO2 emissions and achieve carbon neutrality by 2050, but the policy measures taken so far are insufficient to achieve this goal. In addition, the crisis caused by the COVID-19 pandemic highlighted the relevance of placing this issue at the core of international policies and the need for bottom-up measures and options. The purpose of this paper is to explore how collaborative planning can contribute to adapting the urban tourism sector to climate change in the Porto Metropolitan Area (PMA), located in the northern region of mainland Portugal. In this investigation, we used mixed methods based on the following: (1) the discussion of urban tourism’s adaptation planning to climate change with undergraduate students; (2) the application of a modified Delphi questionnaire survey, to 47 international researchers and technicians in the first round and 35 international researchers and technicians in the second round, about the predictability of the adaptation measures; and (3) a theoretical-practical workshop aimed to discuss the main action intentions and ways of adaptation in the short and medium term. All empirical data were collected during the year of 2021. This research highlights the need for more detailed information, the weak interaction between stakeholders and the limitation of resources. Our research identifies the main impacts and local vulnerabilities and determines priorities for adaptation and implementation of actions, aimed at mitigating the effects of climate change and maintaining tourism attractiveness in urban areas. In addition, this investigation allowed the definition of a research agenda, which seeks to guide the area of tourism climatology regarding the new challenges imposed by the COVID-19 pandemic.

Extreme droughts have a strong impact on agricultural production. In France, the 2003 drought generated records of yield losses at a national scale for grassland (more than 30%) and for cereals (more than 10% for soft winter wheat and winter barley). These extreme events raise the question of farm resilience in the future. Studying them makes it possible to adapt risk management policy to climate change. Therefore, the objective of this paper was to analyze the frequency and the intensity of extreme drought in 2050 and their impact on crop yield losses (grassland and cereals) in France. We used the DOWKI (Drought and Overwhelmed Water Key Indicator) meteorological index based on a cumulative water anomaly, which can explain droughts and their consequences on agricultural yield losses at a departmental scale. Then, using the ARPEGE-Climat Model developed by Meteo-France, DOWKI was projected in 2050 and grassland, soft winter wheat, and winter barley yield losses were simulated. The results compare the frequency and intensity of extreme droughts between the climate in 2000 and 2050. Our results show that the frequency of extreme droughts (at least as intense as in 2003) doubled in 2050. In addition, the yield losses due to 10-year droughts increased by 35% for grassland and by more than 70% for cereals.

The increasing need for food in recent years means that environmental protection and sustainable agriculture are necessary. For this, smart agricultural systems and autonomous robots have become widespread. One of the most significant and persistent problems related to robots is 3D path planning, which is an NP-hard problem, for mobile robots. In this paper, efficient methods are proposed by two metaheuristic algorithms (Incremental Gray Wolf Optimization (I-GWO) and Expanded Gray Wolf Optimization (Ex-GWO)). The proposed methods try to find collision-free optimal paths between two points for robots without human intervention in an acceptable time with the lowest process costs and efficient use of resources in large-scale and crowded farmlands. Thanks to the methods proposed in this study, various tasks such as tracking crops can be performed efficiently by autonomous robots. The simulations are carried out using three methods, and the obtained results are compared with each other and analyzed. The relevant results show that in the proposed methods, the mobile robots avoid the obstacles successfully and obtain the optimal path cost from source to destination. According to the simulation results, the proposed method based on the Ex-GWO algorithm has a better success rate of 55.56% in optimal path cost.

This paper introduces a climatic multi-hazard risk assessment for Greece, as the first-ever attempt to enhance scientific knowledge for the identification and definition of hazards, a critical element of risk-informed decision making. Building on an extensively validated climate database with a very high spatial resolution (5 × 5 km2), a detailed assessment of key climatic hazards is performed that allows for: (a) the analysis of hazard dynamics and their evolution due to climate change and (b) direct comparisons and spatial prioritization across Greece. The high geographical complexity of Greece requires that a large number of diverse hazards (heatwaves—TX, cold spells—TN, torrential rainfall—RR, snowstorms, and windstorms), need to be considered in order to correctly capture the country’s susceptibility to climate extremes. The current key findings include the dominance of cold-temperature extremes in mountainous regions and warm extremes over the coasts and plains. Extreme rainfall has been observed in the eastern mainland coasts and windstorms over Crete and the Aegean and Ionian Seas. Projections of the near future reveal more warm extremes in northern areas becoming more dominant all over the country by the end of the century.

Continuous Descent Approach (CDA) is the flight technique for aircraft to continuously descend from cruise altitude with an idle thrust setting and without level-offs, contrary to the staircase-like Step-down Descent Approach (SDA). Important for air transportation sustainability, using CDA reduces noise, fuel consumption, and pollution. Nevertheless, CDA has been limited to low traffic levels at airports, often at night, because it requires more separation distance between aircraft arrivals and, thus, could decrease throughput. Insufficient attention has been given to helping air traffic controllers decide when CDA may be used. In this paper, we calculate the probability that an aircraft arriving during a particular brief period of time (e.g., 15 min) will need to revert to SDA when the controller tentatively plans to permit CDA for all aircrafts arriving during that time period. If this probability is low enough, the controller may plan to permit CDA during that time period. We utilize an analytical approach and queueing theory framework that considers factors such traffic and weather conditions to estimate the probability. We also provide the number of aircrafts that can be accommodated within the airport’s stacking space using CDA. This number provides insight into whether a particular aircraft may use CDA.

Within an E.U.-funded project, BESS (Pocket Beach Management and Remote Surveillance System), the notion of a geographic information system is an indispensable tool for managing the dynamics of georeferenced data and information for any form of territorial planning. This notion was further explored with the creation of a WebGIS portal that will allow local and regional stakeholders/authorities obtain an easy remote access tool to monitor the status of pocket beaches (PB) in the Maltese Archipelago and Sicily. In this paper, we provide a methodological approach for the implementation of a WebGIS necessary for very detailed dynamic mapping and visualization of geospatial coastal data; the description of the dataset necessary for the monitoring of coastal areas, especially the PBs; and a demonstration of a case study for the PBs of Sicily and Malta by using the methodology and the dataset used during the BESS project. Detailed steps involved in the creation of the WebGIS are presented. These include data preparation, data storage, and data publication and transformation into geo-services. With the help of different Open Geospatial Consortium protocols, the WebGIS displays different layers of information for 134 PBs including orthophotos, sedimentological/geomorphological beach characteristics, shoreline evolution, geometric and morphological parameters, shallow water bathymetry, and photographs of pocket beaches. The WebGIS allows not only for identifying, evaluating, and directing potential solutions to present and arising issues, but also enables public access and involvement. It reflects a platform for future local and regional coastal zone monitoring and management, by promoting public/private involvement in addressing coastal issues and providing local public administrations with an improved technology to monitor coastal changes and help better plan suitable interventions.