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Riskbedömning och prioritering av avloppsreningsverk avseende recipientkontroll
No full textUtsläpp av avloppsvatten bidrar till en rad olika miljöproblem. För att undersöka hur stor påverkan ett avloppsreningsverk har på sin recipient krävs provtagningar i recipienten. I Kiruna kommun genomförs provtagning via ett gemensamt provtagningsprogram. Det har dock konstaterats att det finns ett behov av att undersöka vilka av de 16 mindre reningsverk i kommunen som bedöms ha de största riskerna att påverka sin recipient negativt. Målet med arbetet är att skapa ett förslag på ett recipientkontrollprogram baserat på en riskbedömning som sen kan användas för att avgöra vilka reningsverk som bör prioriteras i ett framtida provtagningsprogram. Förslaget ska inkludera lämpliga parametrar, platser och frekvens för provtagning. Under arbetet genomfördes en riksinventering och en modell för riskbedömning togs fram. Dessutom undersöktes förekomsten av läkemedelsrester genom provtagning vid avloppsreningsverket i Vittangi. Metoden som används är en litteraturstudie kombinerat med datainsamling från databaser och rapporter för de aktuella anläggningarna. Information om reningsverken och recipienterna har samlats in från bland annat miljörapporter, VISS och SMHI. En modell för riskklassning utvecklades baserat på sex kriterier som i sin tur innefattar olika riskfaktorer. Modellen utvärderar risker kopplade till anläggningen samt risker för recipienten, och genererar en riskpoäng för varje reningsverk. En känslighetsanalys genomfördes för att utvärdera hur olika riskfaktorer påverkar riskklassningen. Resultaten visar att de reningsverk med högst riskpoäng är Svappavaara, Lainio, Abisko och Övre Soppero. Några av faktorerna som bedöms bidra till de höga riskpoängen är bräddning, dimensionering, utsläppsvillkor och recipientens närhet till känsliga områden. Provtagning vid Vittangi reningsverk visade att koncentrationerna av läkemedel och hormoner var under rapporteringsgränsen. I och med att inga koncentrationer kunde rapporteras antas läkemedelsrester inte utgöra en betydande risk för recipienten men ytterligare provtagningar krävs med lägre rapporteringsgräns för att säkerställa antagandet. I diskussionsdelen analyseras modellens styrkor och svagheter. Faktorer som brist på tillgänglig data, komplexiteten i att bedöma vissa risker och behovet av uppdaterad information diskuteras. Slutsatsen är att modellen ger en indikation på potentiella risker och bör användas för att prioritera åtgärder för att skydda recipienten men ger ingen direkt bild av de faktiska riskerna. Modellen innehåller även många förenklingar och är endast anpassad för de aktuella anläggningarna för studien. Rapporten rekommenderar att recipientkontroll bör prioriteras vid reningsverken i Abisko, Lainio och Övre Soppero. Analyser av kväve, fosfor, metaller och andra relevanta parametrar föreslås för att bedöma reningsverkens påverkan på recipienterna. Rapporten poängterar även vikten av att regelbundet utvärdera och uppdatera recipientkontrollprogrammet baserat på ny information och förändrade förutsättningar.Wastewater discharge contributes to various environmental issues. To assess the impact of a wastewater treatment plant on its receiving body of water, sampling within the recipient is required. In Kiruna Municipality, sampling is conducted via a monitoring program that includes several different companies. However, it has been determined that there is a need to evaluate which of the 16 smaller treatment plants in the municipality that pose the greatest risks to their respective recipients. The objective of the report is to propose a recipient monitoring program based on a risk assessment of the treatment plants, which can then be used to prioritize facilities for a future sampling program. The proposal includes appropriate parameters, locations, and sampling frequencies. During this study, various risks were compiled, and a model for risk assessment was developed. Additionally, the presence of pharmaceutical residues was investigated through sampling at the wastewater treatment plant in Vittangi. The method involved a literature review combined with data collection from different databases and reports. Information about the treatment plants and their recipients was gathered from environmental reports, the VISS database, and the Swedish Meteorological and Hydrological Institute (SMHI). A model for risk assessment was developed based on six criteria, each containing different risk factors. The model evaluates risks associated with the facility as well as risks for the recipient and it generates a risk score for each treatment plant. A sensitivity analysis was performed to evaluate how different risk factors influence the risk classification. The results show that the treatment plants with the highest risk scores were Svappavaara, Lainio, Abisko, and Övre Soppero. Factors contributing to the high risk scores include overflow events, design capacity, how well the facility complies with the emission restrictions, and the recipient's nearness to sensitive areas. Sampling at the Vittangi treatment plant showed that concentrations of pharmaceuticals and hormones were below the reporting limit. Since no concentrations could be reported, pharmaceutical residues are not considered to pose a significant risk to the recipient. However, additional sampling with lower reporting limits is required to confirm this assumption. The discussion section analyses the strengths and weaknesses of the model. Issues such as data uncertainty, the complexity of assessing certain risks, and the need for updated information are discussed. The conclusion is that the model provides an indication of potential risks and should be used to prioritize actions to protect the recipient but does not offer a direct depiction of actual risks. The model also includes many simplifications and is tailored specifically to the facilities studied. The report recommends prioritizing recipient monitoring at the treatment plants in Abisko, Lainio, and Övre Soppero. Analyses of nitrogen, phosphorus, metals, and other relevant parameters are suggested to evaluate the impact of the treatment plants on the recipients. The report also emphasizes the importance of regularly evaluating and updating the recipient monitoring program based on new information and changing conditions.
Examining Digital Government Maturity Models: Evaluating the Inclusion of Citizens
No full textDigital transformation affects nearly every sector of society and is seen as a strategic approach to addressing evolving demands, including those of citizens, demographic shifts, and skill shortages. To tackle these challenges, governments have begun shifting from a government-centric to a citizen-centric approach, tailoring e-services to citizens’ life events and actively involving them in decision-making processes. Digital government maturity models (DGMMs) are essential tools for assessing digital readiness and guiding transformation, but their attention to citizen-centricity varies significantly. This study examines 18 DGMMs, revealing that 17% do not mention citizens, 33% reference them minimally, and only 50% integrate citizen considerations extensively. This research identifies seven themes where citizens were explicitly addressed in the DGMM, and these themes are maturity stages, areas of focus, enablers, constraints, metrics, insights, and recommendations. Despite the increased policy emphasis on citizen-centricity, gaps remain in translating this into actionable frameworks within DGMMs. This research contributes a thematic matrix and actionable insights to advance citizen-centric approaches, fostering public value creation, transparency, and trust. The findings offer guidance for researchers and practitioners to develop improved frameworks that align digital transformation efforts with citizens’ needs, ensuring inclusive and effective public sector transformation.Validerad;2025;Nivå 1;2025-02-24 (u5);Full text license: CC BY 4.0;</p
Development of lightweight architecture of geopolymer via extrusion-based 3D printing for CO2 capture
No full textMitigation of CO2 emissions has been a major societal concern in recent decades, and post-combustion capture of CO2 is an effective strategy proposed by the research community. Hierarchical porous geopolymer monoliths were fabricated using extrusion-based 3D printing for CO2 capture. The kaolin-based viscoelastic paste was first formulated using alkali activators and plasticizer, and it was observed that the viscosity increased over time. Second, the 3D printed porous monoliths were treated using different post-processing conditions like thermal curing, hydrothermal curing, and high-temperature thermal treatment and their physico-mechanical properties and CO2 adsorptive were investigated. Thermally cured and heated specimens exhibited an amorphous phase, while zeolite phases were observed in the hydrothermally treated specimens. Printed and subsequently hydrothermally treated mechanically stable specimens showed significantly higher CO2 adsorption (1.22 mmol/g) than conventionally casted geopolymer (0.66 mmol/g). Combining 3D printing with geopolymer technology could offer a sustainable approach design and structure adsorbents for CO2 capture.Validerad;2025;Nivå 2;2025-02-10 (u5);Full text license: CC BY 4.0;</p
Evaluating battery minerals future supply through production predicting in the context of the green energy transition
No full textA global transition from the current “brown economy” to a “green economy” has been perceived as an ineluctable carbon neutrality strategy to deal with climate change and its global devastating impacts. This global ambition of green economy necessitates large-scale electrification which imposes growing demand for lithium-ion batteries as state-of-the-art energy storage technologies. Thereupon, the developing market of batteries reinforces the concern over the resilient and consistent supply of battery raw materials. By the reason of the interdependencies of all the stages involved in a value chain of a battery, it is critical to identify the battery material supply-disruptive risks and uncertainties, and subsequently to analyze the impacts of the perpetuation of the supply issues on the future market of batteries. In this research study, to contribute to these processes necessary for overcoming the ongoing supply sustainability challenges, the focus is on lithium, nickel, graphite, and cobalt, which are among the battery raw materials with high supply risks. After analyzing and categorizing the driving forces behind the historical and current bottlenecks to their mining production, the regional and global mining production of those battery materials have been predicted for twenty years ahead using three time series forecasting techniques including Seasonal Autoregressive Integrated Moving Average, Holt's linear trend, and Holt-Winters’ methods. Forecasting possible future production trends of those battery raw materials is indisputably imperative to resolve planning strategies while dealing with uncertainties and supply risks. Reliable supply forecasting results provide more uncertainty and risk management achievements since the stakeholders and policymakers can use the outcomes as a source of information in the decision-making process at any stage of a lithium-ion battery value chain.Validerad;2025;Nivå 1;2025-10-15 (u2);Full text: CC BY license;</p
Data Reduction in Proportional Hazards Models Applied to Reliability Prediction of Centrifugal Pumps
No full textThis paper presents the use of proportional hazards regression models for predicting the Mean Time Between Failures (MTBF) of centrifugal pumps in the oil and gas industry. To that end, a dataset collected over 8 years including both design and operational variables from 675 pumps in an oil refinery was used to fit statistical models. Parametric and non-parametric transformations and restricted cubic splines were used to fit the covariates, thereby relaxing linearity assumptions and potentiating predictors with strong nonlinear effects on the outcome. Standard Principal Component Analysis (PCA) and sparse robust PCA methods were used for data reduction to simplify the fitted models and minimize overfitting. Models fitted with sparse robust PCA on non-parametrically transformed variables using an additive variance stabilizing (AVAS) method are suggested for further investigation. The complexity of the fitted models was reduced by 85% while at the same time providing for a more robust model as indicated by an improvement of the calibration slope from 0.830 to 0.936 with an essentially stable Akaike information criterion (AIC) (0.34% increase).Validerad;2025;Nivå 2;2025-03-10 (u2);Full text: CC BY license;</p
Numerical modelling of shear cutting in complex phase high strength steel sheets: A comprehensive study using the Particle Finite Element Method
No full textThe study examines the shear cutting process of Advanced High Strength Steel using the Particle Finite Element Method. Shear cutting, a crucial process in sheet metal forming, often leads to microcracks and plastic deformation that degrades the material performance in subsequent applications, such as cold forming, crashworthiness, and fatigue resistance. This work utilises the Particle Finite Element Method as an alternative to conventional Finite Element Methods to address the challenges of large deformation solid mechanics, offering high predictive accuracy in localised shearing deformation and fracture. The model was validated against experimental data from sheet punching tests, with evaluations at both macroscopic and mesoscopic levels, including cut edge profiles and microstructural deformation within the shear-affected zone. The Particle Finite Element Method approach demonstrated a high level of accuracy in predicting cut edge shape and shear-induced damage across various cutting conditions. As an unconventional numerical technique, usage of the Particle Finite Element Method advances modelling of large deformations solid mechanics and providing a robust tool for optimising manufacturing processes of materials sensitive to sheared edge damage.Validerad;2025;Nivå 2;2025-03-10 (u8);Funder: EU Research Fund for Coal and Steel (RFCS) (847213);Full text license: CC BYCuttingEdge4.0Steel4FatigueFatigue4Ligh
Challenges and possibilities when doing research on active school travel interventions in a school setting - a non-randomized pilot study assessing feasibility of an evaluation design
No full textBackground: A wide range of school interventions have been launched to increase childrens’ physical activity. Evaluation of the effectiveness of interventions requires suitable study designs and feasible quantitative evaluations relating to the school setting. The purpose of this study was to assess the evaluation design and methods for data collection, in order to make decisions about approaching forthcoming studies of the effectiveness of active school travel (AST) interventions. Methods: Children from four Swedish schools in fifth grade (11–12 years old) participated in this non-randomized pilot study, two schools received an AST intervention and two schools were controls. The school-based AST intervention Sustainable Innovation for Children Transporting Actively (SICTA) was conducted by teachers in the classroom setting during four weeks. To assess feasibility of the evaluation design and methods for data collection a combination of quantitative and qualitative methods were applied, using participation- and response rates, a feasibility questionnaire and focus group interviews. Results: Out of 25 potential schools, four schools accepted participation with explicit allocation requests preventing randomization. Out of 181 children, 107 children (59%) accepted participation. A total of 82% of the participating children reported active travel before the AST intervention, and 80% found reporting of daily school travels in the web-based survey to be easy. The children were in general positive about participating in the study and the methods for data collection were considered easy for the participating children to conduct and to blend well with usual school activities. There was an imbalance in reporting rates between intervention and control schools as well as a decrease in reporting rates during the study period. Conclusions: Our results highlight the complexity and challenges in conducting controlled research among school children. Although children were positive about participation and found reporting to be easy, our results invoke the need to use alternative research designs and recruitment strategies that also attract children using non-active modes of travel when evaluating AST interventions in school contexts.Validerad;2025;Nivå 2;2025-03-12 (u5);Full text license: CC BY</p
Banging on Closed Doors or Beating the Drum? Social Movements’ Interpretations of Opportunities in Legal Appeal Processes
No full textSocial movements and interest groups in Europe are increasingly using litigation as a form of legal mobilization in their campaigns. Current literature often depicts this as a result of favourable opportunities in movements’ legal contexts, with activists responding to rising prospects of legal success. This comparative study of fifteen cases of mobilizations against mineral exploration projects in Sweden explores a puzzle in relation to this view: Why do movements frequently litigate even when the prospects of legal success seem non-existent? Using frame analysis within a multi-institutional politics (MIP) approach, this study explores how movements interpret opportunities in appeal processes linked to mineral exploration projects. While confirming that the prospect of legal success is a relevant motivator in several cases, the results also indicate that some movements interpret the court as a democratic arena, presenting opportunities to mobilize adherents and signal popular resistance to policy makers and extractive companies. These diverging interpretations of the court are tentatively connected to organizational needs for mobilizing adherents, previous experiences of litigating and available institutional logics in society. Building upon the MIP approach, this study introduces the idea that the democratic understanding of the appeal process signifies a ‘creative infringement’. A democratic institutional logic is imported into the court, an arena typically dominated by an institutional legal-bureaucratic logic. Movements’ increasing use of litigation may thus be driven not only by goals of legal success, but also by creative reinterpretations of legal processes as arenas in which goals of popular participation and democracy may be achieved.Validerad;2025;Nivå 2;2025-03-12 (u5);Full text: CC BY license;</p
Towards Robust and Domain-aware Self-supervised Representation Learning
No full textSelf-supervised representation learning (SSL) has emerged as a fundamental paradigm in representation learning, enabling models to learn meaningful representations without requiring labeled data. Despite its success, SSL remains constrained by two core challenges: (i) lack of robustness against real-world distribution shifts and adversarial perturbations, and (ii) lack of domain-awareness, limiting its usability beyond natural scenes. These limitations arise from the generic invariance assumptions in SSL, which rely on predefined augmentations to learn representations but suffer to generalize when exposed to unseen environmental distortions, adversarial attacks, and domain-specific nuances. Existing SSL approaches—whether contrastive learning, knowledge distillation, or information maximization—do not explicitly account for these factors, making them vulnerable in real-world applications and suboptimal in specialized domains. This thesis aims to enhance both robustness and domain-awareness in a modular, plug-and-play manner, ensuring that the advancements are applicable across different joint embedding architecture and method (JEAM)-based SSL approaches and adaptable to future developments in SSL. To achieve this, this thesis follows a guiding principle-leveraging invariant representations to improve robustness and domain-awareness in a modular and plug-and-play manner without altering fundamental SSL objectives. This principle guides that improvements can be seamlessly integrated into existing and future SSL approaches. To systematically address the above-stated core challenges, this thesis begins with a foundational study of SSL approaches, identifying the common schema that underlies different SSL approaches. This unification provides a conceptual view of SSL methods, allowing us to isolate the domain-sensitive and domain-agnostic components across approaches. This conceptual outcome set the stage to establish precisely where improvements are needed to enhance robustness and domain-awareness across methods as current SSL methods fail under real-world challenges. Next, the thesis conducts a large-scale empirical evaluation of existing SSL methods against relevant robustness benchmarks, uncovering their failures under distribution shifts caused by real-world environmental challenges. This evaluation reveals a significant decline in the robustness performance of existing SSL methods across different SSL approaches. It establishes the fundamental research gap and motivates the advancements introduced in this thesis. The first advancement focuses on robustness against distribution shifts, particularly geometric distortions such as perspective distortion (PD), which are prevalent in real-world environment but not addressed by existing SSL methods. Since PD introduces nonlinear spatial transformations, standard affine augmentations fail to model these effects, leading to degraded representation stability. To address this, this thesis introduces Möbius-based mitigating perspective distortion (MPD) and log conformal maps (LCM), mathematically grounded transformations that enable robustness without requiring perspective-distorted training data and estimation of camera parameters. These methods are additionally adapted to multiple real-world computer vision applications—including crowd counting, object detection, person re-identification, and fisheye view recognition—showcasing their effectiveness. Further, addressing the non-availability of dedicated perspectively distorted benchmark, ImageNet-PD robustness benchmark is developed to fill the gap. Beyond environmental challenges, another critical real-world challenge is adversarial attacks. SSL methods are highly susceptible to adversarial attacks, as the learned representations lack perturbation-invariant constraints. Existing adversarial training approaches in SSL rely on brute-force attack strategies, which fail to adapt dynamically. To address this, this thesis introduces adversarial self-supervised training with adaptive-attacks (ASTrA), where attack strategies evolve dynamically based on the model’s learning dynamics and establish a correspondence between attack parameters and training examples, optimizing adversarial perturbations in a learnable manner. Unlike conventional adversarial training, ASTrA ensures robustness while maintaining SSL’s efficiency and scalability. While robustness, in this thesis, focuses on real-world challenges in natural scenes, domain-awareness focuses on specialized visual domains beyond natural scenes. Standard SSL augmentations are designed for variations in natural scenes, making them ill-suited for specialized fields such as medical imaging and industrial mining material inspection. This thesis introduces domain-awareness in SSL that incorporates domain-specific information into SSL’s view generation process. Particularly, (i) magnification prior contrastive similarity (MPCS) makes learned representations invariant to magnifications for histopathology images by inducing varying magnifications in the view generation process, improving breast cancer recognition. (ii) depth contrast explicitly enforces modality alignment between material images and attained height of materials on conveyor belt, ensuring that the learned representations become aware of physical properties, thereby improving material classification. Beyond robustness and domain-awareness, SSL’s ability to generalize with limited data is advantageous for its practicality. While the loss objective in SSL is generally domain-agnostic, its effectiveness relies on large-scale data. In this direction, this thesis explores functional knowledge transfer (FKT), where self-supervised and supervised learning objectives are jointly optimized, enabling SSL representations to adapt dynamically to supervised tasks. This approach enhances generalization in low-data regimes. In conclusion, this thesis provides a foundation for robust and domain-aware self-supervised representation learning in a modular manner, highlighting its applicability to existing and future JEAM-based SSL approaches, which can inherit these advancements and adapt to emerging challenges
A Transfer Learning Approach to Create Energy Forecasting Models for Building Fleets
No full textThe creation of accurate energy prediction models plays a signifcant role in achieving sustainability in smart cities. However, stakeholders such as municipalities face the problem of creating individual energy forecasting models for multiple building feets which leads to an increased amount of computational resources and time spent to prepare each model. This research proposes a method using Hierarchical clustering with Dynamic time warping (DTW) to group similar buildings according to their consumption values and the integration of Transfer Learning (TL) to share the model weights from a source building to other target buildings. Several TL models using diferent portions of the target data were tested against a standard workfow without TL for predicting electricity and district heating for several school buildings using a Multivariate LSTM model. The performance metrics show minor diferences between the TL and standard models. Results indicate that using 20% to 40% of the target data is sufcient for training. The models achieved average RMSE improvements of 20% and 5% for district heating and electricity respectively, indicating a potential for reduced data requirements without sacrifcing predictive accuracy and demonstrating TL’s efciency to streamline the energy forecasting process for building feets