An  increasingly  popular  subcategory  of  Artificial  Intelligence  (AI)  is  Generative  AI (GAI),  which  encompasses  technologies capable of creating new content, such as images, text, and music, often resembling outputs made by humans. The  potential  impact  by  GAI  on  sustainability  is  multifaceted.  On  the  positive  side,  generative  AI  can  aid  in  optimizing  processes, developing innovative solutions, and identifying patterns in large datasets related to sustainability. This can lead to  more  efficient  resource  management,  reduced  energy  consumption,  and  the  creation  of  more  sustainable  products.  However,  there  are  also  potential  negative  impacts,  such  as  increased  energy  consumption  associated  with  training  and  running  generative  AI  models,  as  well  as  the  potential  for  unintended  consequences  or  biases  in  the  generated  content.  Additionally,  overreliance  on  generative  AI  may  lead  to  reduced  human  oversight,  which  could  undermine  holistic,  interdisciplinary, and collaborative approaches to sustainability. The aim of this paper is to explore the potential impacts on sustainability by generative artificial intelligence through a review of prior research on the topic. The study was conducted with a scoping literature review approach to identify potential impacts by generative AI on sustainability. Data were collected through  a  search  in  the  database  Scopus  during  the  spring  semester  of  2024.  Keywords,  relevant  for  the  study,  were  combined  with  Boolean  operators.  Papers  identified  through  the  search  underwent  a  manual  screening  process  by  the  authors, in which papers were selected for inclusion or exclusion in the study based on a set of criteria. Included paper were then analyzed with thematic analysis, according to the guidelines by Braun and Clarke. A categorization matrix, based in prior research  on  sustainability,  supported  the  analysis  and  deductive  coding  of  collected  data. Results  of  the  study  highlight  generative AI’s potential impact on sustainability that relate to both environmental aspects, economic aspects, and social aspects of sustainability. These different aspects of sustainability impact make this research an important contribution for deepening  the  understanding  of  generative  AI  and  its  potential  consequences  for  society.  Findings  of  the  study  provide  theoretical  contribution,  implications  for  practice,  and  recommendations  for  future  research  on  generative  AI  and  sustainability. 

In a GraphQL Web API, a so-called GraphQL schema defines the types of data objects that can be queried, and socalled resolver functions are responsible for fetching the relevant data from underlying data sources. Thus, we can expect to use GraphQL not only for data access but also for data integration, if the GraphQL schema reflects the semantics of data from multiple data sources, and the resolver functions can obtain data from these data sources and structure the data according to the schema. However, there does not exist a semantics-aware approach to employ GraphQL for data integration. Furthermore, there are no formal methods for defining a GraphQL API based on an ontology. In this work, we introduce a framework for using GraphQL in which a global domain ontology informs the generation of a GraphQL server that answers requests by querying heterogeneous data sources. The core of this framework consists of an algorithm to generate a GraphQL schema based on an ontology and a generic resolver function based on semantic mappings. We provide a prototype, OBG-gen, of this framework, and we evaluate our approach over a real-world data integration scenario in the materials design domain and two synthetic benchmark scenarios (Link & ouml;ping GraphQL Benchmark and GTFS-Madrid-Bench). The experimental results of our evaluation indicate that: (i) our approach is feasible to generate GraphQL servers for data access and integration over heterogeneous data sources, thus avoiding a manual construction of GraphQL servers, and (ii) our data access and integration approach is general and applicable to different domains where data is shared or queried via different ways.

We present an interdisciplinary exploration of technostress in knowledge-intensive organizations, including both business and healthcare settings, and its impact on a healthy working life. Technostress, a contemporary form of stress induced by information and communication technology, is associated with reduced job satisfaction, diminished organizational commitment, and adverse patient care outcomes. This article aims to construct an innovative framework, called The Integrated Technostress Resilience Framework, designed to mitigate technostress and promote continuous learning within dynamic organizational contexts. In this perspective article we incorporate a socio-technical systems approach to emphasize the complex interplay between technological and social factors in organizational settings. The proposed framework is expected to provide valuable insights into the role of transparency in digital technology utilization, with the aim of mitigating technostress. Furthermore, it seeks to extend information systems theory, particularly the Technology Acceptance Model, by offering a more nuanced understanding of technology adoption and use. Our conclusion includes considerations for the design and implementation of information systems aimed at fostering resilience and adaptability in organizations undergoing rapid technological change.

The purpose of the study was to Identify decisive attributes that influence electric vehicles (EVs) purchase in emerging markets.  The study was conducted in Brazil using the Free Word Association Technique (FWAT). 

The aim of the study was to identify the criteria consumers consider when purchasing electric vehicles (EVs). The study was conducted in Brazil using the Free Word Association Technique (FWAT) that investigated the criteria consumers consider while purchasing EVs. 

Timber, a renewable resource with a low carbon footprint, has a giant potential to replace reinforced concrete (RC) structures in housing, which can decrease the environmental impact and lead to a healthier construction work environment. However, connections, as part of timber frames, are majorly made of steel and adhesives, which emit harmful pollution and negatively impact the timber structures. This study focuses on enhancing sustainability in construction by proposing adhesive-free timber connections for glued-laminated timber (glulam) panels. The study aims to contribute toward sustainable construction practices by reducing the reliance on adhesives and exploring alternative connection methods for glulam panels. This article presents four-point out-of-plane bending tests on glulam panels with innovative adhesive-free timber connections. The studied specimens compromised fabricated glulam panels and densified wood connectors made of pine and beech, respectively. Six different adhesive-free wood connections were designed and applied independently. Each connection was connected to two glulam panels by their end-grain sides. Therefore, twelve glulam panels, connected using these six connections, were tested. The panels had identical dimensions and materials. The connections were applied at the mid-span of the two connected panels. The experimental results on the flexural behavior, ultimate load, strength, and displacement of the six specimens are presented. The obtained mean load-carrying capacity of the specimens in the current research was greatly higher than that of the other specimens with different timber connections, such as timber-timber connections using compressed wood connectors. Additionally, the failure modes of the specimens were analyzed, which mostly exhibited the shear failure and delamination behavior. Most of the tested specimens failed in a ductile manner with a high ductility, which is suitable for the earthquake regions. The findings demonstrated the potential of using adhesive-free timber connections in glulam panels and contributing to the development of zero-energy buildings and sustainable construction practices while maintaining the structural integrity.

Geopolymer concrete (GPC) has been developed using supplementary cementitious materials to reduce the carbon footprint associated with conventional concrete production. This study aimed to explore the production and simultaneous modeling of the properties of GPC using fly ash (FA) as the primary binder and ordinary Portland cement (OPC) as a partial replacement. Mechanical tests revealed that replacing FA with up to 30% OPC resulted in a 28-day compressive strength (CS) of 33.52 MPa and a flexural strength (FS) of 15.21 MPa. X-ray diffraction (XRD) analysis indicated the formation of nepheline and albite, which are associated with sodium aluminosilicate hydrate gel, a primary strength giving product in GPC. Additionally, gene expression programming (GEP), an artificial intelligence technique, was employed to predict the mechanical properties utilizing the experimental data. The prediction models demonstrated high accuracy, with a correlation coefficient greater than 0.90. The study’s results provide valuable insights into the performance of OPC-blended FA-based GPC and propose easy-to-use empirical formulations for standard mix design and proportioning of alternative blended GPC, promoting the application of sustainable concrete.

This article investigates the development of geopolymers as a modern, environmentally sustainable binder with ceramic-like properties, offering exceptional thermal and fire-resistant characteristics. The study primarily utilized fly ash (FA) in combination with glass powder (GP) and steel slag (SS). The SS content varied between 30 % and 40 %, while the molarity of NaOH was set at 10 M, 12 M, and 14 M. Based on these variables, a total of eighteen mixes incorporating GP and SS were formulated. The samples were subjected to elevated temperatures of 200 ⸰C, 400 ◦C, 600 ◦C, and 800 ◦C, after which their compressive strengths were measured. To better understand the material formation, analyses were conducted by using scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and thermogravimetry differential thermal analysis. The investigation examined the influence of oxide ratios (Na/Si, Si/Al, H2O/Na2O, and Na/Al) on the compressive strength at elevated temperatures. Additionally, the research sought to develop a predictive model, elucidating the relationship between these oxide ratios and the compressive strength of geopolymers. To achieve this, ten machine learning techniques were applied, revealing the complex connection between oxide ratios and the strength properties of geopolymers. The support vector regressor (SVR) model outperformed other regression and boosting models, obtaining a high coefficient of determination (R2) value of 0.95, indicating superior predictive accuracy. The reduced error levels and high R2 values highlighted the enhanced performance of the SVR model. A sensitivity analysis was done to understand the contributions of each parameter to the outcome predictions further. Employing machine learning techniques to predict the compressive strength of geopolymer blocks under various elevated temperature conditions improves predictive accuracy and optimizes resource utilization, leading to significant time savings.

Urban forms, as a physical proxy of human mobility and activity, are crucial for understanding the mechanisms and factors behind urban dynamics. The rapid expansion of urban sensors and big data has significantly advanced our comprehension of cities and societies. Currently, the development of complexity sciences has led to more sophisticated simulation models, presenting new opportunities for understanding complex urban phenomena. This dissertation integrates fractal geometry theory, deep learning models, and agent-based modelling (ABM) to enhance the understanding and future generative design of sustainable urban forms. Three models were developed in this dissertation based on: Graph-based fractality index (GFI), Spatio-structural self-similarity, Simple agents–complex emergent path systems (SACP), as well as a model and web-based tool for road evaluation by desire path system (RED-PaSS). (1) The GFI model, grounded in fractal theory and deep learning techniques, is capable to characterize the complexity of building groups; (2) the spatio-structural self-similarity model examines self-similarity from a spatial and structural perspective, correcting long-standing misinterpretations in classical statistical fractal theories. The spatio-structural self-similarity model is capable to understand historical urban forms through validation with data from London building groups and US street networks; (3) the SACP model is based on ABM and simulates pedestrian movement based on visibility parameters and simple principles of global destination awareness and local environmental adaptation. The findings of SACP indicate that the angle of vision is crucial for path pattern emergence; and (4) the RED-PaSS model and tool that evaluates road networks by simulating optimal pedestrian paths based on the SACP model. Case studies of 708 US neighbourhood-scale road networks demonstrate RED-PaSS's potential to evaluate, rank, and enhance road networks, improving pedestrian mobility and convenience. This dissertation's holistic approach not only aids in the characterization of current urban patterns but also in generative design of future urban landscapes that are sustainable and resilient. The integration of advanced computational techniques, such as deep learning and ABM, enables exploration of urban dynamics at unprecedented scales and resolutions. The continuous advancement of these models is crucial for addressing urbanization challenges and fostering sustainable, liveable cities.

Background

The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) multimodal lifestyle intervention yielded cognitive and other health benefits in older adults at risk of cognitive decline. The two-year multinational randomized controlled LETHE trial evaluates the feasibility of a digitally supported, adapted FINGER intervention among at-risk older adults. Technology is used to complement in-person activities, streamline the intervention delivery, personalize recommendations, and collect digital biomarkers.

Methods

Trial includes older adults (60–77 years) with digital readiness/experience with smart devices and increased dementia risk but without substantial cognitive impairment. Participants are enrolled at four sites (Austria, Finland, Italy, Sweden). At baseline, participants were randomized 1:1 ratio to 1) intervention i.e., structured multimodal lifestyle program (including diet, exercise, cognitive training, vascular/metabolic risk management, social stimulation, sleep/stress management) where in-person activities led by professionals are supported with an Android mobile phone application developed by the consortium (the LETHE App); or 2) control i.e., self-guided program (regular health advice; simplified App with no personalized/interactive content). All participants wear smartwatches to gather passive data (e.g., physical activity, sleep). Primary outcomes are retention, adherence, and change in validated dementia risk scores. Secondary outcomes include changes in lifestyle, cognition, stress, sleep, health-related quality of life, and health literacy. Additional outcomes (exploratory) include e.g. participant experiences and dementia-related biomarkers (Alzheimer’s disease blood markers, neuroimaging). A sub-study explores the feasibility of novel interactive technology (audio glasses, social robot).

Results

Recruitment began in September 2022, and the last participant was randomized in June 2023. In total, 156 individuals were randomized (mean age 69 years, 65% women; balanced recruitment across the four sites). Vascular and lifestyle risk factors were common (e.g., 65% with hypertension, 69% with hypercholesterolemia, 39% physically inactive), indicating successful recruitment of a population with risk reduction potential. Trial will be completed by summer 2025. Retention until the first post-baseline visit at 6 months is high (n = 2 discontinued, retention 98.7%).

Conclusion

LETHE provides crucial information about the feasibility of technology and a digitally supported FINGER lifestyle program to promote brain health. Digital tools specifically designed for older adults could offer potential for large-scale, cost-effective prevention programs.

Trial registration

ClinicalTrials.gov (NCT05565170).

This study aims to investigate and disentangle the impact of land use and climate variability on the Baltic Sea coastal zone from a millennial perspective. To assess the environmental status of the coastal zone we make use of siliceous microfossils (mainly diatoms), stable nitrogen and carbon isotopes, organic carbon accumulation rates, and lithological changes analyzed in a sediment core collected in Gamlebyviken, Swedish east coast, dated to cover the last 3000 years. Changes in land use and vegetation cover are modelled using pollen stratigraphical data to obtain the percentage coverage of coniferous woodland (Pinus and Picea), deciduous woodland, wetland (Cyperaceae), grassland (including Juniperus) and cropland (cereals) while changes in climatic conditions are assessed through well-documented climatic periods that have occurred in the Baltic Sea region. The reconstructed regional vegetation cover shows that already 3000 years ago, humans used the landscape for both animal husbandry (grasslands) and farming (cropland), but the impact on the Baltic coastal waters was minor. The diatom accumulation rates were quite high (∼3100–2600 cal yr BP) containing taxa indicative of high nutrient conditions/upwelling, and stable carbon isotopes show that the carbon was produced in the basin but did not result in elevated organic carbon accumulation rates. A gradual change to less marine conditions in Gamlebyviken from about 2500 to 1400 cal yr BP can be attributed to the ongoing land uplift which resulted in a more enclosed embayment with only a narrow inlet area today. The Medieval Climate Anomaly (1000–700 cal yr BP/950–1250 CE) is a time where extensive eutrophication is registered in the open Baltic Sea, but afforestation is recorded between 1000 and 500 cal yr BP and attributed to the expansion of spruce favored by land-use reorganization with a transition from a one-course rotation system to the three-course rotation system fully established in southern Sweden in the 13th century, and only minor environmental change is recorded in the coastal zone. The Little Ice Age is documented in our data between 400 and 250 cal yr BP/1550–1700 CE as a decrease in regional cropland (cereals) cover, possibly indicating years of poor crop harvest, and changes in the Baltic coastal zone are evidenced as low carbon and diatom accumulation rates, increase in benthic diatom taxa (low turbidity), and high abundance in diatom taxa associated with sea ice indicating a cold climate. The most significant changes occurred from about 100 cal yr BP/1850 CE up to present, with a maximum regional cover of grassland and cropland (ca. 35%) at the expense of deciduous woodland, and major changes indicative of a highly eutrophic environment recorded in the coastal zone. Organic carbon accumulation rates peaked in 1968 CE at approximately 134 g C m2 yr−1 before subsequently declining to present-day values of 53 g C m2 yr−1, mirroring a similar trend observed in diatom accumulation rates. The high organic carbon accumulation rate shows that deep unvegetated accumulation bottoms in the coastal Baltic Sea serve as carbon sinks and are worth exploring for their potential in mitigating climate change. Variation partitioning shows that 26% of the variance in the diatom assemblages is associated with land use changes. The variables grassland, cropland, and stable nitrogen isotopes are accordingly strong predictors of environmental change in the Baltic coastal zone as reflected by the diatom assemblages.

 In this paper, we suggest the following generalisation of Mikhalkin’s simple Harnack curves: a generalised simple Harnack curve is a parametrised real algebraic curve in (ℂ^*)2 with totally real logarithmic Gauss map. First, we investigate which of the many properties of simple Harnack curves survive this generalisation. Then, we construct new examples using tropical geometry. Eventually, since generalised Harnack curves can develop arbitrary singularities, in contrast with the original definition, we pay a special attention to the simplest new instance of generalised Harnack curves, namely curves with a single hyperbolic node. In particular, we determine the topological classification of such curves for any given degree.

The need to decarbonise and reduce pollutant emissions from maritime transport is facilitating the studies of ground effect vehicles. Technical development in recent decade concerning unmanned flights in drones has supported this development. These vehicles could have much higher speed than sea vessels and they are estimated to be less costly compared to air transport. Unmanned operations without passengers enable wider range of transport connections (even in difficult conditions). In this research we analyse prototype vehicle called Airship and its possible use in different routes of intra Canary Islands’ transport. We suggest the most lucrative routes and cargo groups. Initial cost and revenue considerations are made over the life-cycle of Airship. As a result, we can point that there are three main factors determine the success of the transport operations. They are: the number of journeys per day, business days operating per year and freight price.

Virtual reality provides students with the opportunity to have simulated experiences in a safe setting and is mostly used to teach direct practice skills. One of the most advanced ways of using virtual simulation in social work education is to interact with avatars. Aim: The overall aim of this scoping review was to find out what is known about the use of dialogue with avatars in virtual reality in simulation-based social work education. Materials: Using Arksey and O’Malley’s scoping review framework, 11 articles were included in this review. Results: The skills taught with the avatars varied, as did the ways of preparing students for the sessions. The training was assessed as meaningful learning in a safe and comfortable environment, offering an opportunity to train in practical skills. According to the pre- and post-tests, in several studies the students’ skills seemed to have improved after the training. The qualitative data also pointed to skill developments. Conclusion: Training with avatars seems to be a useful way of preparing students for their future profession and seems to hold great potential in preparing students for demanding situations that cannot be easily trained for in a classroom. The results also point to technical elements that would benefit from development.

Greenhouse Gas (GHG) emissions significantly impact the environment and human health, but many people are unaware of how their daily choices affect climate change. Carbon calculators estimate emissions in sectors like construction, digital health, transportation, and food production. However, they are still developing and face challenges that require attention from both industry and academia. Researchers highlight the absence of a unified framework for assessing these tools, leading to simplistic binary evaluations, which result in inaccuracies in household tool evaluations. In the current study, an assessment framework has been created by integrating existing binary frameworks and incorporating the MCDA method for weighted multi-criteria evaluation, offering a quantitative scoring system for qualitative criteria. This dual-criteria framework addresses both practical and academic aspects of the evaluated tools. The framework was used to evaluate 15 tools chosen for their prominence in search engine results and their impact on scientific publications. Findings revealed that tools such as Svalna, WWF calculator, and Carbon Savvy produce comparable results, while others, like the UN CF calculator, show deviations up to 136 tons. The study highlights challenges related to feasibility, availability of resources, and user engagement, noting that the criterion for accessibility for special groups received a score of zero across all CF tools. The work is expected to yield enhanced understanding that will aid in the selection of appropriate CF tools, foster sustainable practices, and offer developers direction to ensure their designs conform to established standards.

In recent years, accessibility to services and activities using sustainable transport modes has become an important goal for land use and transport planning policies. Traditional approaches rely on objective measures, such as travel time, distance, costs, and other spatial data, overlooking personal preferences, experiences, demographic features, and socio-cultural and economic dynamics. Attributes that affect perceptions of accessibility require attention but our understanding of the factors influencing perceived accessibility is inadequate, particularly in Australia’s expanding suburbs. Through a literature review and questionnaire surveys, this study aims to take into account various travel characteristics and enhance the understanding of how perceived safety and service quality impact mobility behaviour and perceived accessibility within the Australian context. The study found that perceived safety and service quality have significant impacts on perceived accessibility and hence influence the use of public transport. We have identified critical factors that require proper consideration in transport and land use planning and policies to enable a better contribution from public transport to the liveability and well-being of residents in Australian suburbs.

Background

The number of older adults with complex healthcare needs is growing alongside limited resources available in health services. To meet this challenge, it is urgent that healthcare staff are motivated and able to continuously translate new knowledge and working methods into daily practice. To facilitate such implementation, supportive measures responding to the healthcare personnel’s needs seem essential. The present study aims to translate, contextualize and test a Swedish version of the Implementation Process Assessment Tool (IPAT) for measuring the facilitation needs among staff implementing a new working process in municipal elderly care.

Methods

A mixed-method design was used. First, the existing instrument was translated into Swedish. Thereafter, twelve staff members with different professions working in healthcare and at the municipal elderly care were interviewed using Think-aloud interviews to contextualize and test the face validity of the translated instrument. Lastly, the adjusted instrument (Swe-IPAT) was psychometrically evaluated through a cross-sectional survey among 305 staff members working in municipal elderly care.

Results

The psychometric evaluation of the Swe-IPAT revealed satisfying properties. Three factors, largely in line with the original IPAT, are suggested. Internal consistency assessed using Cronbach’s alpha was 0.93 for the factor individual phases for behavioral change and perception of the intervention, 0.84 for the factor individual activities, and 0.95 for the factor collective readiness and support.

Conclusions

The 27-item Swe-IPAT, translated into Swedish and contextualized, demonstrated satisfactory psychometric properties when tested in an elderly care context. The instrument is suggested to be useful in providing feedback to managers in tailoring support and assessing implementation efforts among healthcare staff in elderly care. However, more research is needed to evaluate its properties throughout the entire implementation process and to test the usability of Swe-IPAT in other settings.

Gender differences in pain reporting and prevalence have been demonstrated. As gender of examiner also affects reporting of pain on palpation, the aim of this study was to evaluate the effects of examiner gender on palpation performance using three different palpation methods. Examiners of both genders were instructed on the correct technique for each palpation method by either a female or male instructor. The target was to achieve a pressure of 100 kPa, corresponding to the 1 kg of force for muscle palpation described in the diagnostic criteria for temporomandibular disorders (DC/TMD). All examiners performed traditional palpation with the index finger, palpation with a palpometer, and a novel bimanual palpation with visual feedback, in a randomized order. The examiner's gender, and its interaction with the gender of the instructor did not significantly affect magnitude, accuracy, or precision of the pressure applied. The method of palpation was the only factor that significantly impacted all metrics. The palpometer achieved the lowest palpation magnitude (mean pressure applied = 113.7  kPa, 95% CI: 109.8–117.6), the highest accuracy (absolute difference = 15.7  kPa, 95% CI: 12.3–19.1), and the highest precision (mean coefficient of variation = 6.8, 95% CI: 6.0–7.6), followed by bimanual palpation and traditional palpation. The results suggest that gender differences in pain reporting in patients are not likely to be a result of the technical aspects associated with the gender of the examiner. Instead, these differences may be attributed to other factors, such as sociocultural influences.

This methodological article focuses on how to effectively map pre-service teachers’ use of discursive resources in professional identity production. By adopting a discourse analytical approach, this study views identity construction as a situational, real-time process occurring in interaction. The aim is to contribute knowledge about how to systematically map and analyze the resources that pre-service teachers use to construct their teacher identities during their education. Drawing on the framework of Mediated Discourse Analysis, this article presents a model that integrates two key concepts: discourse domains, which refer to the types of discourse commonly used in teacher education, and layers of discourse, which address societal levels in identity construction. The results suggest that using these concepts to map students’ use of discursive resources highlights how their knowledge of the teaching profession, their education and everyday experiences can be assets when constructing their teacher identities. While the model can be further refined and developed to better show the complexity of discursive resources in identity construction processes, it shows promise as a fruitful approach. By mapping and visualizing discursive resources through this model, this study offers valuable methodological insights into how to approach professional identity development among pre-service teachers.

Svenskarna oroas av klimatförändringen och vill tidigare lägga det svenska klimatmålet samt se ökade satsningar på ett fossilfritt samhälle. Omställningen ses som en utmaning men än mer som en möjlighet. Lägre bränslepriser står inte högt i kurs. Det framgår av en ny stor undersökning med över 5000 personer, gjord av forskningsprogrammet Fairtrans.

This study adapted the mean age of air, a time scale widely utilized in evaluating indoor ventilation, to assess the impact of building layouts on urban ventilation capacity. To distinguish it from its applications in enclosed indoor environments, the adapted index was termed the effective mean age of air (T_E). Based on an experimentally validated method, computational fluid dynamic (CFD) simulations were performed for parametric studies on four generic parameters that describe urban morphologies, including building height, building density, and variations in the heights or frontal areas of adjacent buildings. At the breathing level (z = 1.7 m), the results indicated three distinct distribution patterns of insufficiently ventilated areas: within recirculation zones behind buildings, in the downstream sections of the main road, or within recirculation zones near lateral facades. The spatial heterogeneity of ventilation capacity was emphasized through the statistical distributions of T_E. In most cases, convective transport dominates the purging process for the whole canopy zone, while turbulent transport prevails for the pedestrian zone. Additionally, comparisons with a reference case simulating an open area highlighted the dual effects of buildings on urban ventilation, notably through the enhanced dilution promoted by the helical flows between buildings. This study also serves as a preliminary CFD practice utilizing T_E with the homogenous emission method, and demonstrates its capability for assessing urban ventilation potential in urban planning.

Trap nets are a large, stationary, and fixed type of passive fishing gear that has traditionally been used for catching fish in shallow coastal environments. Despite their large size, catches are often retrieved using small boats, making them less energy demanding compared to active gear types. This, along with the stationary nature of the trap, allows for fishing with relatively low environmental impact due to minimal disturbance of the benthic community. The combination of minimal benthic impact, live catch, low fuel, and selectivity offers great potential for the development of sustainable coastal fisheries. Here, we describe the development of the hovering pontoon trap, a fishing gear with a robust design to resist strong waves and currents, and usable in both shallow and deep waters to catch both pelagic and benthic species. We present results from early case studies targeting benthic Baltic Sea species, including perch (Percha fluventaliis), Atlantic cod (Gadus morhua) and vendace (Coregonus albula), showing similar or improved catches in relation to earlier studies. Further, we show that the hovering pontoon trap was able to withstand harsher conditions than previous bottom-set models, making it a possible solution for the targeting of benthic fish communities in coastal environments.