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Conventional democratic institutions are unable to sufficiently incorporate citizens’ views in the context of a changing climate. The lack of a shared understanding of what citizen participation entails and what it should look like limits the potential for effective engagement. Postulating that citizen participation in policy-making processes could contribute to better decisions regarding flood risk management and climate change adaptation, this study aims to explore how citizens and professionals understand participatory processes, and how aligning their expectations can inform the design of such approaches. This study uses an explorative case study in the context of two flood-prone municipalities in Sweden and the Netherlands, i.e. Gävle and Roermond. Here, professionals and citizens are interviewed to gain insights into their perspectives and expectations. The results of this study indicate a willingness among both groups for greater and earlier involvement of citizens, but the suggested degree of influence and form differs. The lack of technical knowledge among citizens and the responsibility governments have to protect residents are presented as barriers. To avoid ambiguity, disappointment, and mistrust, citizens’ expectations should be well managed from the beginning. In addition, achieving a representative and diverse audience to promote inclusivity is identified as a great challenge in public engagement. Based on these results, local authorities can work on the implications for practice, aimed at transparency throughout the process, expectation management, and a revaluation of local knowledge., Managing tomorrow’s floods: improving cooperation between citizens and governments Engaging with citizens is increasingly seen as a way to tackle the challenges caused by climate change. However, stereotypes about citizen participation, such as citizens not having any technical knowledge, or that governments invite citizens only symbolically persist. Using a case study in Roermond, the Netherlands, and Gävle, Sweden, this study found that people have different understandings of participation, which mostly limits the opportunities for successful participation. The data is collected through semi-structured interviews with 23 people, both professionals and citizens. This study looks at four main themes: what is participation, who is involved, when can input be given, and how is it conducted? Citizen participation is seen as including citizens in the policy-making process, but the roles and impact of this inclusion are not agreed upon. It is difficult to gain a broad diversity of opinions since certain groups, such as middle-aged, white, high-educated men often dominate participation. People who are feeling the effects of climate change, such as through flooded basements or badly insulated houses, are insufficiently heard in decision-making. When to involve citizens in a project is a dilemma since in the beginning, the plans might be too abstract for citizens to understand what they can contribute, whereas possibilities for impact decrease when a project develops. Despite these challenges, there is consensus on involving citizens earlier to improve the quality of decisions. To avoid disappointment among citizens and a decline in trust, everyone’s expectations must be managed beforehand. Finally, there are challenges in how participation is organised, for example in the time it costs to prepare and attend meetings, the option of online input, the knowledge that is required, and the ways of interaction between citizens and governments. People have different ideas about ho

Youth's climate change awareness is rising, but so are their concerns about the future, with climate anxiety being common in young adults and adolescents. Engaging adolescents in climate action is considered one strategy to mitigate these concerns but for them to become active they need to be aware of the issue. This research aims to answer if an increase in knowledge affects the climate change concerns the youth have and if participation in collective action helps in dealing with these concerns. It took place in a project by barnfonden and ChildFund Cambodia in Cambodia. An explanatory mixed methods approach was used by conducting a quantitative pre/post survey followed by one focus group discussion. The results showed a significant increase in the knowledge and belief in action but no significant increase in concerns and perceived personal affectedness due to the training. This could be due to various other factors influencing concern next to knowledge which led to an already high concern level in the first survey round. The increase in the belief that action can help deal with emotions and combat climate change indicates it to be a useful coping tool. The findings of this study show the complexity of climate change concerns and accentuate the importance of well-thought-through training when talking about climate change., This thesis studied whether learning about climate change affects how concerned youth are about the topic and how their beliefs in action against climate change are influenced by this knowledge. The results showed that knowledge about the topic and their belief in action increased due to the training but that the youth’s concern and perceived affectedness did not significantly rise. This could be due to other factors that influence concern levels and that could have led to the already high concern level before the training. However, the youth said they only engaged with the topic because of this project. This shows that knowledge does influence concerns to some extent and that it is important to have well-thought-through and holistic training on climate change that focuses on action and creating hope. Climate change is an increasingly important topic and one reason why youth are concerned for their future. Engaging them in climate action is considered to help them deal with these worries. To become active against climate change, they need to learn about the impacts of climate change first. This is why this thesis looked at how learning about climate change affects concern and belief in collective action helping them to deal with these feelings. The research took place in Cambodia in a project by barnfonden and ChildFund Cambodia. A survey before and after the training as well as one focus group discussion was used to look at the youth’s concerns, perceived affectedness, knowledge and their belief in action. As expected, the knowledge of the youth increased due to the training as did their belief that being active can be a good coping method. However, their concerns and perceived affectedness did not increase significantly. This could be because of factors such as values and worldview or even their age and gender influencing their concern level before the training. A slight increase in concern was seen due to the training and because of that, knowledge might still pl

Despite a persistent reliance on conventional grey infrastructure solutions, there is increasing recognition of the vital role of nature-inclusive urban planning in managing climate risks such as floods and heatwaves while simultaneously promoting biodiversity, human health, and well-being. This multifunctionality underscores nature's intrinsic importance, reframing it as a fundamental necessity for societies rather than just a "nice to have" within urban areas. Therefore, this study delves into urban nature practices and prospects within Finnish municipalities to provide holistic insights into the developments. Employing a mixed-method approach, utilizing an online questionnaire, the research reveals an increasing integration of nature-based solutions (NBS) in municipal planning, zoning, and construction practices across 13 municipalities. Moreover, urban nature is considered vital, even as critical infrastructure. The insights underscore the importance of consistency and precise indications for NBS in land-use planning. However, since NBS requires collaboration, differing knowledge, priorities, and perceptions of risks and opportunities can impede progress. The challenges are compounded by urban structures and historical processes. On the other hand, shortcomings in monitoring and evaluating NBS may hinder the identification of necessary enhancements and mainstreaming of successful solutions into practices. Meanwhile, clear goals with contextual indicators could enhance the tracking of NBS progress and deepen learning about the broader outcomes, thereby informing decision-making. Based on the insights and scholarly literature, overarching recommendations are discussed., Nature-based Solutions (NBS) leverage natural processes to deliver societal benefits, including climate adaptation and mitigation, enhanced human health, and the promotion of biodiversity. For instance, urban green can cool the air, manage stormwater, and boost children's immunity all at once, which is crucial in urban areas where space is often limited. Indeed, nature is not merely a 'nice to have' in urban areas but crucial for addressing pressing societal challenges. This study examined urban planners' perspectives on NBS practices and prospects in 13 Finnish municipalities. The results indicate notable efforts to integrate NBS into urban planning, supported by municipal strategies and regulatory measures in zoning and construction. However, the need to enhance the knowledge base and planning methods is still evident, necessitating increased collaboration among various stakeholders. Furthermore, developing city-wide visions of desirability could streamline communication and address historical barriers and perceptions of risks and opportunities that may hinder progress. For instance, since the 1970s, there has been a tendency to artificially create urban nature, overlooking the importance of preserving and integrating more "wild nature" for ecological and health benefits. Additionally, densification combined with limited blue-green elements has posed challenges in current urban structures. Hence, integrating NBS would be essential in challenging areas, even as smaller-scale projects. Furthermore, critically reflecting on history to learn from it is crucial to prevent repeating mistakes. Moreover, while notable initiatives also exist, their successful implementation necessitates recognizing the diverse values inherent in urban nature to foster public and political support. NBS are not just about planting trees; they require understanding the diverse benefits and trade-offs to ensure effective and equitable development. Hence, this study underscores the importance o

Urban green infrastructure (UGI) is gaining popularity for disaster risk reduction and climate change adaptation in urban contexts, but dense development obstructs the realisation of large-scale greening measures. This thesis investigates the potential of small-scale, site-specific urban greening in a residential area in Cologne, Germany, to improve ecosystem service supply. The objective is to assess how much the capacity for heat mitigation and biodiversity conservation can be increased through small-scale solutions, such as grass, shrubs, trees, green roofs and green facades. A spatial analysis is conducted to inventory the current UGI and map opportunities for functional upgrading, i.e. increasing, enriching, and connecting the existing UGI, resulting in a maximal greening scenario. Heat mitigation and biodiversity conservation are quantified based on the spatial dimensions of the UGI, using published supply rates and indicators. The urban surface exhibits enormous potential for UGI implementation, which is currently underutilised, particularly regarding roofs, facades and streets. Through small-scale interventions, about 1.2 million square meters of UGI can be added, increasing the green cover of the urban surface from 8 to 23%. The cooling capacity can be more than doubled, largely due to building-based solutions. The increase in tree canopy also contributes significantly, but a deficit remains regarding the provision of shadow. The biodiversity conservation can be improved through greater habitat, larger patches, and a significant increase in connectivity (proximity index increases by five times). Public and private efforts are required to utilise this potential and participatory processes are recommended to ensure environmental justice., Transforming roofs, facades and streets into green spaces can significantly cool cities and enhance biodiversity. Discover how small-scale greening interventions can improve urban life and create resilient cities. GREEN SUPERPOWERS TO TACKLE URBAN CHALLENGES As cities grow and the planet warms, urban areas are increasingly at risk from disasters like heatwaves, while global and local biodiversity is shrinking due to habitat loss. This makes new urban planning strategies essential for sustainable and safe living conditions. One promising approach is to improve the urban green infrastructure (UGI), which can offer multiple benefits: cooling through evapotranspiration and shading, air filtration, noise reduction, carbon storage, flood mitigation, and enhanced recreational and aesthetic value. These "superpowers" make urban greening a powerful tool in urban resilience strategies. However, implementing these solutions often faces challenges, such as limited space and insufficient data on their benefits. The city of Cologne, Germany, aims to increase greenery to combat heat, conserve biodiversity, and provide other ecosystem services. Considering the dense development, this thesis explores how small-scale greening interventions—like greening roofs and facades, and planting street trees—can enhance heat mitigation and biodiversity conservation. ENORMOUS UNTAPPED POTENTIAL By conducting a case-study in two of the least-greened neighbourhoods in Cologne, this study finds enormous potential for small-scale greening. In the study area, around 90% of the roof area and at least 7% of the facade space can be greened, amounting to ca. 1.1 million square meters of additional green surface, and around 1,900 street trees can be planted. By applying these measures, the overall green area can be tripled, leading to double the current cooling capacity, and a five-fold increase in the green space connectivity, which improves biodiversity. Additionally, some great co-benefits can be expec

Malawi is prone to compounding climate shocks, the main climate risks being extreme rainfall/floods and dry spells. To provide support to poor and vulnerable households, the country has an established social protection system, including a Social Cash Transfer Program (SCTP), which contains shock-sensitive social protection mechanisms to increase the coping capacity of beneficiaries to climate shocks. The purpose of this research is to investigate how the social protection system performs during climate shocks from the perspective of beneficiaries and what changes beneficiaries would like within these structures. This research builds on primary data collected through semi-structured interviews with beneficiaries of the SCTP in Phalombe and Blantyre Districts and district- and national-level government officials. This study’s results reveal gaps within the existing structures, including deficiency in transfer consistency, transfer amounts, support coverage, and poor info dissemination regarding SCTP and impending climate shocks. Beneficiaries’ desired changes to the structures relate to transfer consistency, shorter transfer intervals, increased transfer amounts, and increased program support to both have resources and information available regarding impending climate shocks. Further research is needed on transfer timeliness, transfer consistency, program messaging, and program sufficiency, to enable SCTP to become shock-sensitive by anticipating shocks and provide timely support., As climate change get more severe, households in southern Malawi are dealing with impacts of weather-related events in their daily lives. Cash support from a social protection program provides support to households dealing with climate change impacts. But how well does the social protection program cover the needs of the households dealing directly with climate impacts? The purpose of this research was to talk to households receiving support from the social protection program, hear their perspectives and experiences, compare this to accounts from government officials, and understand how well the current social protection program covered the needs of households facing climate impacts. This research was based on semi-structured interviews with individuals from households receiving cash transfers from the social protection program in two districts in southern Malawi, and interviews with government officials. The social protection program was a critical factor for households to meet their daily needs. However, challenges with the timing and amount of transfers, and communication related to the cash program and climate impacts made it hard for households to act before weather-related events. This resulted in households struggling to cover their needs in between cash transfers, making them more vulnerable to climate impacts. Overall, this research found that the main challenges with the social protection program is related to: • Coverage of the cash transfers and the needs of beneficiaries. • The intervals between and the timing of the cash transfers. • Communication about and understanding of the social protection program and climate impacts. • The cash transfer amounts and payments. The existing structures of the social protection program were not designed or used to provide support before climate impacts, but to provide regular support and additional support after climate impacts. Prolonged intervals between cash transfers and the low amount of cash transfers resulted

Artificial Intelligence (AI) is rapidly evolving and demonstrating potential for climate change adaptation in urban planning, including urban stormwater management. Through the case study of InflowGo, an AI-based stormwater model, this research identifies and appraises potential opportunities and challenges that such a tool can provide for decision-making in urban stormwater management. By the means of semi-structured interviews with urban water professionals, it was revealed that conventional decision-making, i.e. without AI application, is complex due to technical and organisational challenges, as well as insufficient speed, flexibility, and collaboration. AI has the potential to address these challenges and fill these gaps as it can accelerate decision-making, both technically and by facilitating the selection of different alternatives earlier in the process. It can also foster interdisciplinary collaboration and participation of stakeholders in decision-making by running the models during meetings, helping to break silos, and supporting educational purposes. To do this, the user-friendliness and web-based nature of the tool were identified as two contributing success factors. Although appearing as potentially relevant, AI was found not capable of overcoming the complexity and uncertainty of the field, the world, and climate change. Moreover, it can bring new challenges and shortcomings related to the ethical responsibility of making decisions, resistance to change and fear of the unknown, as well as legal and cybersecurity aspects. Further research is encouraged to investigate the application of AI-based tools in different contexts and with fully developed products, and to explore the potential educational added value of AI in decision-making., Artificial Intelligence has the potential to revolutionise urban stormwater management decision-making to make cities ready for challenges like climate change, urbanisation, and ageing infrastructure. Using the case study of the AI-based stormwater model InflowGo, the study describes the shortcomings of the current decision-making process, and suggests potential benefits of using AI to fill these gaps. Furthermore, it discusses AI’s potential limitations and arising challenges that come with its application. The research is based on the case study of the InflowGo tool, still in development, and 16 semi-structured interviews conducted with urban water management professionals from Germany, Denmark, and Sweden. Decision-making in urban stormwater management is a complex process that involves politics, teamwork, and technical know-how. It requires experts to use conventional tools for modelling and simulation, making it a time-consuming and repetitive process. Moreover, this process involves extensive data analysis and coordination among many professionals from different departments, which is found to be lacking flexibility and in fact non-inclusive. The research highlights several potential benefits of integrating AI into stormwater management. AI's ability to rapidly analyse large datasets can significantly reduce the time required to develop and implement effective stormwater strategies. By simulating various stormwater scenarios in real-time during meetings, an AI-based tool can allow urban stormwater managers to visualise potential impacts, compare different solutions, and make informed decisions more quickly and efficiently than before. This not only speeds up the decision-making process but also encourages participation and collaboration among stakeholders from different fields. Furthermore, InflowGo’s user-friendliness and web-based design make it accessible to various stakeholders without the need for specialised training or powerful computing resources, and a

Impacts of disasters are felt acutely at community level, as a consequence communities in the Philippines are among the most affected by the increase in disaster risks. This realization led to an increase of community-based approaches, such as community-based disaster risk management (CBDRM). However, literature acknowledges a recurring failure of projects to be sustainable long-term, attributed to a lack of trust in implementers, lowering the motivation of communities to commit. Therefore, this research explores the role of trust in achieving sustainable CBDRM for the case of four communities in Pangasinan, Philippines. Based on the literature, a conceptual framework was created and adapted according to findings through two focus group discussions and 15 key informant interviews with community members, CBDRM implementers, and duty-bearers. The role of trust was identified by analyzing the data following Creswell (2013) and relating it to other relevant factors for the CBDRM sustainability in terms of horizontal trust and vertical trust. Interviewees identified the importance of awareness, linked to knowledge on vulnerabilities and disasters, which they also related to perceived source trustworthiness. Furthermore, an interactive relationship with trust and meaningful, inclusive, and accessible participation was highlighted and considered to significantly contribute to CBDRM sustainability. Political complexities that impact trust levels show the need for an enabling environment and a stricter policy implementation to enhance sustainability. While the role of trust in achieving sustainable CBDRM in this research is considered substantial, more research on different aspects of trust and especially within other contexts is needed., Because of disasters, rural communities in the Philippines experience a lot of losses. Since the communities know best about their own needs and resources, approaches like ‘community-based disaster risk management’ (CBDRM) aim to include the communities in all steps of developing disaster risk management plans. You can imagine it like this: a CBDRM implementing organization visits a community to analyze the risks and resources with them and write a disaster risk management plan together. This sounds nice – but even though projects often work well while the organization is in the community they often fail once organizations leave. Experts believe that this is due to a lack of trust in the implementing organization, leading to a lack of commitment. This research asked community members, people working in CBDRM organizations, and local government officials in four rural communities in the Philippines about their perspectives on what role trust plays in the outcome of CBDRM projects through interviews and focus group discussions. Trust is a critical factor in influencing the sustainability of CBDRM projects, but more factors that influence the CBDRM sustainability and connections between all of these were found. Overall, this research found that the sustainability of CBDRM is related to: 1) Information, knowledge, and awareness of the disasters 2) Meaningful participation in terms of it being accessible and contextually adapted 3) Frameworks, and policies to create an enabling environment for CBDRM 4) Trust in terms of inter-community trust and vice versa trust between implementers and the community. A close connection between information, knowledge, and awareness of the risks and how this influences both participation and trust was found since if community members do not know about the activities or risks, they would not participate. It became obvious that the inclusiveness, accessibility, and contextual adaptation of activities were crucial for the participation since

När en himlakropp med hyperhastighet kolliderar med jorden skapas nedslagskratrar. Nedslags- kratrar ger oss en inblick i hur jordens geologi har blivit påverkad av dessa storskaliga event. När nedslag sker om- vandlas projektilens rörelseenergi till chockvågor som rör sig genom berggrunden och deformerar mineral. Detta fenomen har kommit att kallas för chockmetamorfos. Chockvågen skapar chockmetamorfa strukturer hos mängder av mineral. Dessa strukturer fungerar som verktyg för att identifiera nedslagskratrar. Konventionellt har chockme- tamorfa strukturer i till exempel kvarts och zirkoner används för att identifiera nedslagskratrar. Denna rapport foku- serar på mineral som inte förekommer lika ofta i litteratur om chockmetamorfos och därav inte lika välstuderade som identifikationsmineral för nedslagskratrar. Genom litteraturstudier har nio okonventionella chockmetamorfa mineral identifierats som lämpliga för att användas som identifikations mineral för nedslagstrukturer. Dessa mineral finns i en rad olika bergarter och uppvisar tillsammans chockmetamorfa strukturer från både låga och höga tryck. Några av strukturerna som uppvisas i mineralerna är PDFs, PFs, PDBs och tvillingar. Genom att titta på för- och nackdelarna av dessa mineral jämfört med de konventionella mineralen drogs slutsatsen att många, om inte alla, av de undersökta okonventionella mineralen kan vara användbara som identifikationsmineral för nedslagskratrar.

Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. Consequently, several methodologies have been developed to efficiently determine land cover using remote sensing imagery according to the spectral characteristics of each land cover category. The objective of this thesis is to classify an area located in the Ionian region of Greece, identifying ‘Artificial’, ‘Bare Soil’, ‘Cropland’, ‘Dense Forest’, ‘Grassland’, ‘Low-density Urban’, ‘Low/Sparse Vegetation, and ‘Water’ classes. To do so, the study investigates the performance of different techniques for processing and integrating remote sensing data obtained from various sensors. Multi-spectral and thermal imagery are employed, as well as topographic data from the area of interest. Landsat 8 and Landsat 9 images were specifically chosen for this project, as they include both multi-spectral and thermal information in a single acquisition. Additionally, ASTER GDEM data was used for elevation information and the generation of two elevation derivatives, the aspect and the slope of the study area. These factors, along with their temporal variability, are considered crucial as the spectral properties of certain key classes (specifically those related to vegetation and agricultural activities) are influenced by the phenological cycle. The study addresses several research questions, including the impact of thermal information, elevation, and topography on the classification accuracy, as well as the utilization of time series data to enhance the results compared to using only the multispectral information as input. The findings indicate that combining multi-spectral data with either terrain information, thermal infrared bands, or both, significantly improves the class, Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. In this study, satellite imagery, alongside elevation data and time series are utilized with the goal to categorize diverse land cover types with precision. The primary goal is to classify an area located in the Ionian region of Greece using Machine Learning techniques into specific categories such as ‘Artificial,’ ‘Bare Soil,’ ‘Cropland,’ ‘Dense Forest,’ ‘Grassland,’ ‘Low-density Urban,’ ‘Low/Sparse Vegetation,’ and ‘Water.’ This classification is achieved through the analysis of multispectral and thermal imagery, as well as topographic data from the area of interest. Landsat 8 and Landsat 9 images were specifically chosen for this project, as they include both multispectral and thermal information in a single acquisition. Additionally, ASTER GDEM data was used for elevation information and the generation of two elevation derivatives, the aspect and the slope of the study area. These factors, along with their temporal variability, are considered crucial as the spectral properties of certain key classes (specifically those related to vegetation and agricultural activities) are influenced by the phenological cycle. The study addresses several research questions, exploring the influence of thermal information, elevation, and topography on classification accuracy. Additionally, it investigates the synergy of time series data with multispectral information to enhance classification results. The findings indicated that combining multispectral data with either terrain information, thermal infrared bands, or both, significantly improves the classification. The highest performance in classification accuracy was achieved when incorporating the time series informatio

The effects of climate change are resulting in harmful impacts — known as loss and damage — hitting the most vulnerable countries the hardest. At COP27 in Sharm el- Sheikh, a new “loss and damage fund” was agreed upon, creating history within the international climate change policy arena. However, the question of who may benefit from this fund, remains. The fund is to address the countries that are most vulnerable to climate change, but the concept of vulnerability is in its nature vague, and its implications are many. Through a qualitative analysis of interviews with Nordic and African climate strategy experts, this study sets out to investigate whether the ambiguity of perceptions behind vulnerability may influence the effectiveness and operationalization of the new loss and damage fund. The study examines (i) how the perception of vulnerability differs between the two groups, (ii) how this difference relates to the larger political debate between developed and developing countries, and (iii) what implications these results may have for the future process of the fund. The study takes a constructionist stance, arguing that it is not possible to separate actors from the world in which they are embedded, resulting in different perceptions of core concepts. Concepts are therefore assigned a large degree of linguistic uncertainty, which may hamper the effectiveness of negotiations and operationalization of institutions tasked with applying climate strategies. The study finds that the world view of different political actors is dependent on their positionality in the international arena. These positionalities result in diverging perceptions of the vulnerability concept and the concept of particularly vulnerable, which in turn have large implications for countries’ eligibility to access the loss and damage fund. This study further finds that the linguistic uncertainty of core concepts may have large implications for the future effectiveness of the new fund. Lastly, the s, Under många decennier har världen påverkats av klimatförändringar, och problematiken fortsätter öka alltmer. Effekterna av människoskapade klimatförändringar leder till förödande konsekvenser i form av skador och förluster för människor världen över. Det finns en tendens till att skador och förluster drabbar utsatta människor i utvecklingsländer värst. Förutom att historisk ha bidragit minst till de globala klimatförändringarna är dessa folkgrupper också ofta minst kapabla att hantera dessa skador och förluster på grund av ekonomiska, sociala och strukturella utmaningar. För att hantera den stora problematiken kring skador och förluster behövs det ny klimatfinansiering på området. Vid det årliga internationella klimattoppmötet 2022 (COP27) enades världens länder om en ny klimatfond med syfte att hantera skador och förluster som har uppkommit i världens mest sårbara länder som följd av klimatförändringarna. Operationaliseringen och strukturerna av denna fond klubbades igenom vid klimattoppmötet 2023 (COP28). Genom tiden har det dock varit stor skillnad på hur sårbarhet definieras och vem som anses vara särskilt sårbara, vilket inte heller har specificerats i beslutet bakom den nya fonden. Denna studie undersöker hur synen på vad sårbarhet är och vem som anses vara särskilt sårbara kan skilja sig åt och vilka konsekvenser dessa skillnader kan tänkas ha för effektiviteten av den nya fonden. Detta görs genom intervjuer med insatta aktörer i nordiska och afrikanska länder. Det undersöks därutöver vad bakgrunden till dessa skillnader kan tänkas vara. Studien visar att det finns tydliga skillnader på hur företrädare för nordiska och afrikanska länder förstår sårbarhet och vem de identifierar som särskilt sårbara. Dessa olikheter grundas till stor del på de två gruppernas position i den internationella ordningen och den historiska debatten mellan utvecklingsländer och utvecklade länder. Studien visar dessutom på att sådana osäkerheter kring språkbruk kan leda till en sämre

The presence of organic micropollutants (OMPs) in wastewater effluents is concerning, as they pose a threat to human and aquatic health. Biodegradation via methane-oxidizing bacteria (MOB) is an attractive option, as the method is cheap and effective. MOB can co-metabolize a variety of substrates, there among organic micropollutants. Methane-oxidizing microbiomes (MOMs) were cultivated with different SRT, methane loading rate, O2:CH4 ratio and nitrogen sources. The MOMs were spiked with OMPs for adaptation. Most of the MOMs generated similar results with specific growth rates of 0,40-0,66 d-1 and biomass yields on methane of 0,32-0,64 g CDW∙g CH4-1. The MOMs with higher methane loading had the highest methane uptake rates, as well as the highest yields on nitrogen. The MOMs grown on nitrate instead of ammonia had higher methane and nitrogen uptake rates. The MOMs with 15 days SRT, high methane loading, 3:2 O2:CH4 ratio and nitrate as the nitrogen source generated the highest biokinetic values overall. The MOMs degraded sulfamethoxazole (SMX) between 81-85%, reaching removal rates of 4,5-5,3 L∙g-1∙d-1. Metoprolol, diclofenac and dimethyl sulfide were moderately degraded between 22-50%. The degradation of SMX generated higher removal rates than some previous studies, there among degradation via activated sludge and membrane bioreactors. The MOMs that had not been adapted to OMPs had poor removal efficiencies in general, highlighting the importance of adaptation. The MOMs with low methane loading generated the highest removal efficiencies. A microbial community analysis is needed to further conclude how the communities differ. Further research is needed to grasp why the high methane loading bacteria had lower removal efficiencies while simultaneously oxidizing methane to a higher extent., Uppreningsförsök av organiska mikroföroreningar i avloppsvatten Dagens extensiva användning av olika organiska kemikalier såsom läkemedel och smink, lämnar restprodukter i avloppsvatten som till viss del hamnar i dricksvatten och i naturen. Dessa restprodukter antas kunna skada både mänsklig och vattenlevande hälsa, till exempel genom att förhindra tillväxt och endokrina funktioner. Därför är det viktigt att rena vattnet ordentligt. Dagens befintliga tekniker är kostsamma och tidskrävande och behovet av ett billigare och effektivare alternativ efterfrågas. Detta projekt har undersökt nedbrytningen av organiska mikroföreningar i avloppsvatten med hjälp av mikroorganismer. Mikroorganismer som konsumerar metan, så kallade metanoxiderande bakterier, kan bryta ner vissa mikroföreningar via en process som kallas co-metabolism. Co-metabolism innebär att mikroorganismer bryter ner och omvandlar ett ämne, utan att ta del av deras näringsinnehåll. De behöver med andra ord näring i annan form, i detta fall metan. Under en fyramånadersperiod, odlades mikroorganismer i förslutna bägare. Mikroorganismerna odlades med variationer i deras tillväxtförutsättningar, med b.la. tillförsel av olika mängder metan samt olika kvävekällor. Till bakterierna tillsattes även en uppsättning mikroföreningar för att undersöka eventuell påverkan på tillväxt. Nedbrytningen mättes sedan under 48 timmar för att undersöka hur mycket av varje ämne som bröts ner samt för att generera hastighetskonstanten kbio för varje ämne, för att kunna jämföra med litteraturvärden för tidigare försök. Resultaten visade bland annat att bakterierna gynnades av högre metantillförsel och nitrat istället för ammoniak som kvävekälla. Bland de olika mikroföroreningarna var det endast ett, sulfamethoxazole, som bröts ner signifikant (81–85%). Bland resten av mikroföroreningarna, bröts tre ner mellan 22–50%, metoprolol, diclofenac och dimethylsulfid. Resultaten påvisar att vissa mikroföreningar kan brytas ner till viss del av

Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. This study aims to address these challenges by predicting the station-level demand in public bicycle-sharing systems through the application of machine learning and deep learning methods. This has been done by outlining the influencing urban built environment factors of bike-sharing systems and comparing the machine and deep learning models’ performance prediction results. The Spatial Regression Graph Convolutional Neural Network (SRGCNN) and SRGCNN-Geographically Weighted methods are employed and compared with traditional machine learning methods, namely Multiple Linear Regression, Multilayer Perceptron Regressor, Support Vector Machine, and Random Forest Regressor. For the SRGCNN method, a graph has been constructed based on the number of trips between the stations. Additionally, factors related to the urban environment have been considered for the prediction task. Also, evaluation metrics have been utilized to assess and facilitate the comparison of the machine and deep learning models’ performance. Concluding this case study in Zurich, the deep learning models and Random Forest Regressor were found to outperform other machine learning methods, showcasing better accuracy in terms of several evaluation metrics. Despite recognizing limitations such as the relatively low number of stations, this study highlights future research opportunities to enhance model accuracy and deepen our understanding of micro-mobility demand dynamics, especially in the context of PBS station planning., The field of artificial intelligence has drawn much attention in the scientific community. Its integration into the field of Geographic Information Systems has given a new perspective on solving spatial-related problems. Micro-mobility planning can be pretty challenging since it comes alongside lots of data and requires computational power, sufficient storage space, and data processing. This is where Geographic Artificial Intelligence facilitates geospatial data analysis, processing, and making predictions to assist policymakers and urban and transport planners in the case of this study. Public-Bicycle Sharing systems have been developing in many cities around the world. It is an efficient and convenient means of transport in the citizens' daily lives. However, many questions arise regarding station placement, public bike availability across cities, and more. This thesis aims to tackle those issues by predicting the station-level demand in the bike-sharing system in Zurich. Publicly available data have been used to calculate the number of shared bikes at each station for approximately one month. Additionally, other factors, such as healthcare centers, sports facilities, the closest distance from each station to public transport stops, and more, have been taken into consideration since they can significantly impact the usage of shared bikes. Subsequently, machine and deep learning models have been developed to predict the station-level demand for the bike-sharing system in Zurich. After developing the models, evaluation metrics have been utilized to compare the models’ performance results. Concluding the case study in Zurich, Geographic Artificial Intelligence proved to be useful in predicting the station-level demand for bike-sharing systems. Despite acknowledging limitations, such as the relatively low number of stations, this study highlights the capabilities of such models and their potential application in addressing micro-mobility problems, particularly in stat

This study investigates concentrations of eight metals (Cu, Zn, Cd, Pb, Hg, Cr, Ni, As) in the freshwater resource Lake Vomb, located in the south of Sweden (Scania), and explores the potential use of deformed Chironomidae larvae as bioindicator. Sediment samples from six locations were analysed against threshold values from the Swedish Agency for Marine and Water Management and background values from the Swedish Environmental Protection Agency. Nickel (Ni) exhibited a significant departure, indicating contamination. Uncertainties regarding the risks associated with metal concentrations arise due to sediment properties. The literature review suggests that deformed larvae are unsuitable bioindicators, given the unknown causes of deformations and the potential influence of other environmental pollutants. Results indicate that the larvae may serve as general bioindicators for pollution, lacking specificity regarding the contaminant nature. This research emphasizes the importance of thoroughly assessing metal concentrations in Lake Vomb and questions the utility of deformed Chironomidae larvae as singular indicators of heavy metal pollution. Further research is needed to better understand the relationships between metal concentrations, sediment properties, and bioavailability. Ultimately, the study underscores the complexity of assessing the environmental impact of metals and highlights the need to refrain from hasty conclusions or recommendations based on limited information., Metaller förekommer naturligt i jordskorpan men på grund av industrialiseringen har spridningen av metaller i miljön ökat vilket har resulterat i att många av världens sjöar är förorenade. För att övervaka metallkoncentrationerna i sjöar kan bioindikatorer användas, vilket är en organism som reagerar på en miljöförändring. Sydvatten är ett företag som producerar dricksvatten ur Vombsjön som ligger i Skåne. År 2021 utförde Medins Havs och Vattenkonsulter en inventering av Vombsjöns bottenfauna åt Sydvatten. De fann ett högt antal deformerade mygglarver, det tros bero på att larverna har varit i kontakt med metaller eller bekämpningsmedel. Tidigare forskning tyder på att det finns potential att använda dessa deformerade mygglarver som en bioindikator för metaller. Denna studie undersöker åtta metallkoncentrationer (Cu, Zn, Cd, Pb, Hg, Cr, Ni, As) i dricksvattentäkten Vombsjön. Studien utforskar potentiella risker som metallkoncentrationerna kan medföra samt potentialen av att använda deformerade larver ur familjen Chironomidae som bioindikator för att övervaka dessa metaller. Sedimentprover togs på sex olika platser i Vombsjön med en Ekmanhämtare som skickades in till laboratoriet SGS Analytics Sweden för metallanalys. Metallkoncentrationerna jämfördes med gränsvärden från Havs- och vattenmyndighetens föreskrifter om klassificering och miljökvalitetsnormer avseende ytvatten (HVMFS 2019:25) samt jämförvärden från Naturvårdsverkets rapport 4913. En litteraturstudie utfördes för att ta reda på om mygglarver kan användas som bioindikator. Resultatet visade att metallkoncentrationerna avvek generellt lite för samtliga metaller med undantag från Ni som avvek tydligt vilket kan innebära att sjön är förorenad. Det uppmättes måttligt höga koncentrationer av Ni och Cu vilket kan bidra till biologiska effekter. Slutligen anses mygglarver som bioindikator inte lämplig då det inte är känt vilka metaller som ger upphov till deformationerna samt att deformationerna kan orsakas av an

Perennial agriculture systems are gaining ground as a more sustainable alternative to conventional annual agriculture, partly for their potential to increase the soil organic carbon (SOC) content. Carbon farming is another hot topic for SOC sequestration, as it creates economic incentives for farmers. The main purpose of this study was to measure the baseline SOC stock for a larger research project, where the SOC balance of a field with the perennial grain Kernza™ will be compared to conventional annual crops grown on a control field during five years. The SOC stock of the test and a control plot in Alnarp, south Sweden has been determined to 136.76 Mg SOC ha-1 for Kernza™ and 150.06 Mg SOC ha-1 for the control, through extensive field sampling and laboratory analysis. When evaluating different sampling protocols regarding stratification and sample size, it was found that in order to accurately detect relevant changes in SOC over a short time frame, a large number of samples was required. In this study, stratification was not effective to reduce the required number of samples. This study implies that there is a need for robust SOC sampling designs for research and the carbon farming market alike., Perennial agriculture is gaining traction as a more sustainable option compared to traditional annual farming methods. One reason for this shift is its potential to boost soil health by increasing soil organic carbon (SOC) content. Carbon farming, which focuses on sequestering carbon in soils as a way to mitigate climate change, is also becoming increasingly popular due to the economic incentives it offers to farmers. This MSc study aimed to develop and execute a sampling protocol for establishing a baseline for SOC levels, as part of a larger research project comparing the SOC balance of fields planted with perennial grain Kernza™ versus fields growing conventional annual crops over a five-year period. It also looked at the the efficiency of different sampling protocols for accurately detecting changes in SOC over a short timeframe, by comparing the sampling protocol developed for this study to the sampling protocol proposed by the Swedish carbon farming initiative Svensk Kolinlagring (Swedish Carbon Sequestration). This study, conducted in Alnarp, south Sweden, found that the SOC stock of the Kernza™ field was measured at 136.76 Mg SOC per hectare, while the control fields with conventional crops had 150.06 Mg SOC per hectare. This data was gathered through extensive field sampling and laboratory analysis. The difference between the two research fields was mostly due to the presence of a single outlier in the control field with unusually high SOC levels, especially at depth. Upon further investigation, it was found that the high levels at this location could possibly be explained by hydrology and land management. When comparing the different sampling protocols, it was discovered that a large number of samples were necessary to be able to accurately detect relevant levels of SOC sequestration over a short time frame. It was also found that stratification—dividing the soil into subareas with similar characteristics —did not significantly reduce the required sample s

Wetlands are vital for biodiversity, socio-ecological systems, and carbon sequestration, but they present a complex challenge in crafting effective conservation policies. This study investigates a successful case of wetland conservation policy, focusing on the notable achievements of Kristianstad Vattenrike. Utilizing a comprehensive research approach, encompassing semi-structured interviews, surveys, and document analysis, the study explores the multifaceted factors influencing and fostering the participation of private actors in wetland restoration efforts. Emphasizing the significance of policy attributes and social norms as facilitators for collective action, the research delves into the intricacies of stakeholder attitudes. Furthermore, the study seeks to explore the role of agenda-setting and coalition magnets in the creation of wetland policy instruments. In doing so, this study seeks to understand the contextual adaptation of policy instruments, recognizing the unique characteristics of wetland restoration, offering insights into the development of wetland policies. By unraveling the success of Kristianstad Vattenrike with the unique approach of policy emergence and policy development, this research contributes valuable knowledge to the interplay of ecological, economic, and social factors in wetland conservation, offering a foundation for future studies on the design of policies that not only protect but also enhance the resilience of these vital ecosystems., Våtmarker är en egen kategori av naturens egna superhjältar. Våtmarker av olika slag erbjuder ökad biologisk mångfald, naturnära besöksplatser med unik flora och fauna samt möjligheter att lagra koldioxid i jorden. Men att hantera och skydda dessa områden är en utmaning, framförallt när det gäller att skapa en smart naturvårdspolitik. Denna studie ger oss en närmare titt på ett framgångsrikt exempel där man har anlagt, vårdat och återställt våtmarker – Kristianstad Vattenrike. Studien tillämpar en blandad metod där intervjuer, enkäter och dokumentanalys används för att förstå vad som får privata markägare att vara med och återställa våtmarker. Studien gör en djupdykning i olika teoretiska ramverk, så som agendasetting, policy design och sociala normer för att se hur man kan få folk att samarbeta och dra åt samma håll. Studien kastar också ljus på hur man medvetet kan sätta agendan och bygga upp stöd för olika åtgärder för att främja våtmarker. Målet är att förstå vad som gör styrmedel och politiska verktyg effektiva. Genom att titta närmare på framgången i Kristianstad Vattenrike, där man inte bara har skyddat utan även stärkt dessa viktiga ekosystem, erbjuder studien en nyckel till att förstå hur ekologiska, ekonomiska och sociala faktorer samverkar inom våtmarksbevarande. Det öppnar dörren för framtida studier om hur vi kan skapa politiska verktyg som inte bara värnar om dessa områden utan också ökar deras motståndskraft mot förändringar.

Increasing demand for incorporating renewable energy projects into the national energy mix, is associated with international and European efforts to tackle the negative effects of climate change and strengthen energy resilience. Greece, as a member country of the European Union, has acknowledged that necessity, by implementing a national program aiming to significantly reduce Green House Gas Emissions and upscale Renewable Energy Sources (RES) project development in upcoming years. Wind farms are considered a major contributor to Renewable Energy Sources deployment due to their technological maturity and know-how, as well as to their ability to support a more sustainable and environmentally oriented energy production model. Nevertheless, their rapid growth has urged developers to look for new areas of installation, as an endeavor facing spatial planning limitations and public opposition. In Greece, such areas include, among others, by mountainous regions. The aim of this study is to investigate and assess the wind power suitability of a mountainous municipality in Western Greece. This is possible by incorporating a comprehensive fuzzy GIS-Multi Criteria Decision Analysis (MCDA) approach that aims at minimizing environmental impacts, while incorporating the input provided by local stakeholders and decision-makers. The proposed methodology forms a set of constraint criteria, which identify exclusion zones. The spatial dimension of local stakeholders’ input was recorded through interviews, and then, utilized as a filter in this exclusion analysis. It was indicated that the exclusion character of the inputs gathered, was connected to the type of their activity. Six evaluation criteria were identified, which assessed the remaining availability areas based on weights derived from fuzzy Analytical Hierarchy Process (AHP). Results of this analysis, indicate that only a very small portion of the municipality is suitable for wind farm development. This research suggests that, Wind energy is considered amongst the most mature RES technologies with the ability to support a more sustainable and environmentally oriented energy production model. Nevertheless, one has to consider that the growing development of wind power projects comes with certain spatial and planning limitations, as well as public opposition. As a result, developers are searching for new territories, facing less developmental challenges, including, among others, mountainous regions. The aim of this study is to investigate and assess the wind power suitability of a mountainous municipality in Western Greece. The analysis includes the incorporation of a GIS-based analysis where multiple criteria are incorporated in a methodology aiming at minimizing environmental impacts, while incorporating the input provided by local stakeholders and decision-makers. The methodology is based on the formation of a set of constraint and evaluation criteria in order to, firstly, define areas where the development of wind farms is excluded, and secondly to evaluate the remaining areas on their suitability. An important element of the applied approach was the incorporation of local stakeholders’ input that was utilized as a filter in the exclusion analysis. Results of this analysis indicate that only a very small portion of the municipality (0.7 %) is available for wind farm development, while these areas were assessed as of medium suitability. This research suggests that the proposed framework and its outcomes could be utilized as a consultation tool by decision-makers in the future.

The dataset encompassed the observation of bud phenology, height growth performances, assessment of frost damage, and the timing of first reproduction for five provenances of black spruce. This investigation spanned the years 2017 to 2022, focusing on spruce varieties originating from natural stands distributed along a latitudinal gradient between the 48th and 53rd parallels within the boreal coniferous forest of Quebec, Canada.

This study presents the results from the first detailed structural analysis of glaciotectonic structures of the northern cliff exposures on Ven alongside the first coherent interpretation of the glaciotectonic evolution of the island. Additionally, the study presents the findings of the first geomorphological mapping of surface features on Ven. The primary objective of this study was to fill gaps in our knowledge regarding the influence of successive advancements of the SIS in the area and address previous claims regarding the surface geomorphology of the island. This was accomplished using a standard sedimentological and geomorphological approach along with detailed structural investigations of glaciotectonic structures. Fifteen distinct lithofacies where identified throughout the northern cliff exposure, which can be summarized as three subglacial till beds connected to the two last glacial advances of the SIS during the late Weichselian, separated by discontinuous layers of deformed outwash and glaciolacustrine deposits. Overall, the interpreted sedimentary succession is interpreted to represent the upper sedimentary succession of the Alnarp Valley fill, one of Scania's most valuable groundwater resources. Measurements of deformational structures alongside the sedimentological revealed a substantial glaciotectonic influence from the last two glacial advances on island`s stratigraphic succession. The findings show that our preexisting knowledge pertaining to the glaciotectonic evolution of the island only show a simplistic overview. This study presents two conceptual models to explain the evolution of the glaciotectonic structures and the sedimentological findings seen in the northern cliff exposures. Furthermore, previous claims of Ven being a prime example of a cupola hill complex could not be entirely dismissed but are shown to be an unlikely interpretation based on the evidence from the geomorphological analysis of the island. Additionally, 10 subtle long-stre, Denna studie presenterar resultaten från den första detaljerade strukturanalysen av glaciotektoniska strukturer på de norra klippexponeringarna på Ven tillsammans med den första sammanhängande tolkningen av öns glaciotektoniska utveckling. Dessutom presenterar studien resultaten av den första geomorfologiska kartläggningen av land former på Ven. Det primära syftet med denna studie var att fylla kunskapsluckor gällande påverkan av successiva framstötningar av SIS i området och adressera tidigare påståenden angående öns morfologi. Detta uppnåddes med hjälp av en standard sedimentologisk och geomorfologisk metodik tillsammans med detaljerade strukturella undersökningar av glaciotektoniska strukturer. Femton distinkta litofacies identifierades genom hela de norra klippexponeringarna, vilket kan sammanfattas som tre subglaciala tillsängar som är kopplade till de två senaste glaciala framstegen av SIS under sena Weichsel, åtskilda av diskontinuerliga lager av deformerade avrinnings- och glaciolakustrina avlagringar. Övergripande tolkas den sedimentära successionen som den övre sedimentära successionen av Alnarp dalen, en av Skånes mest värdefulla grundvattenresurser. Mätningar av deformerande strukturer tillsammans med sedimentologin avslöjade en betydande glaciotektonisk påverkan från de två senaste glaciala framstegen på öns stratigrafiska succession. Resultaten visar att vår befintliga kunskap om öns glaciotektoniska utveckling endast ger en förenklad översikt. Denna studie presenterar två konceptuella modeller för att förklara utvecklingen av glaciotektoniska strukturer och de sedimentologiska fynden i de norra klippexponeringarna. Vidare kunde tidigare påståenden om att Ven skulle vara ett utmärkt exempel på en cupola hill inte helt avfärdas, men visar sig vara en osannolik tolkning baserat på bevis från den geomorfologiska analysen av ön. Dessutom finns det 10 subtila långsträckta åsar som finns genom öns annars platta yta. Ursprunget till dessa åsar kunde inte fast

This study focuses on the estimation of lake water volume fluctuations using open-source remote sensing data and evaluates its accuracy. The research follows a three-step methodology, starting with water area estimation from Sentinel-2 imagery, followed by water level estimation using ICESat-2 satellite data, and concluding with the calculation of lake water volume differences, testing the regression modeling and Triangular Irregular Networks (TINs). For the water extent estimation, three different methods are being compared – Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Random Forest machine learning algorithm - against manual digitization. All three methods yield accurate results on the quantitative comparison, with performance metrics consistently exceeding 0.95, indicating the absence of a clear preference among these approaches. During the qualitative comparison, misclassified areas were revealed, indicating the problems caused by clouds, shadows and leaves upon the lake which sometime makes the process of accurately map the water extent difficult even for the human eye. For the water level estimation, ICESat-2 satellite observations were found to be accurate in lake water level monitoring, with a standard deviation of approximately 5 cm, surpassing the nominal accuracy of 6.1 cm. However, limitations are noted in terms of temporal resolution, impacting their use in combination with Sentinel-2 acquisitions. Finally, for the estimation of water volume fluctuations, the research explores two distinct approaches for calculating water volumes within open water surfaces. The first approach employs regression modeling, deriving a regression equation to estimate water volumes based on area computations. The second approach involves Triangular Irregular Networks (TINs). However, the research discerns that the latter method is not applicable in cases where a significant difference in scale between vertical and horizon, Understanding changes in lake water levels is crucial for managing water resources. Our project uses advanced space technology to tackle this task. We aimed to develop a simple, reliable method to monitor changes in lake water volume over time, offering valuable insights for decision-makers. We utilized satellite imagery from Sentinel-2 satellite to assess the extent of water coverage in lakes. Additionally, we also used data from ICESat-2 satellite to measure water height. Our research explored various techniques for calculating water volume changes, including mathematical models and also geometrical 3D approaches. Water extend data have been analyzed with various remote sensing methods. All of them provided accurate results which suggests no clear preference among them. However, several challenges have been identified such as the presence of clouds, shadows and leaves over the lake, that were visible in the satellite images. Water level data proved to be applicable for this task, since their precision was found to exceed our initial expectations. However, their limited frequency posed certain challenges, when it comes to availability of this data source. For the water level changes estimation, our mathematical approach was found to be effective and provided the expected results. On the other hand, the geometrical method faced certain limitations. Due to the specific lake’s individualities, when it comes to the actual level changes compared to the extent changes, the latter wasn’t able to provide comparable results. Our research offers a promising approach for water resource management and decision-making. By leveraging freely available data and tools, we can enhance our ability to monitor and understand changes in lake water levels. Future endeavors may involve more advanced methodologies and data from other sources too, to further refine our analysis.

Urban green space (UGS) refers to open spaces within an urban context that are filled with greenery and nature. These can range from very small vegetation to expansive park areas. The common denominator is that they have proven to be beneficial for human health and well-being. Access to green spaces is also important for children. Research suggests that time spent in green spaces supports the behavioral, intellectual, and physical development of children. When cities are growing, it is often associated with a loss of UGS due to the current concept of densification which is achieved by infill, repurposing land, and adding height to existing buildings. The loss of UGS can negatively affect access to green spaces for the inhabitants of an urbanized city. It is supported by previous research that access is not equal, and oftentimes those with lower socio-economic standing are negatively affected by the loss of UGS. Given the above, this study set out to examine how changes to a city influences UGS and access to green space in urban areas using the city of Malmö as a case study. A rapidly growing urban area, it is the fastest growing city in Sweden. While the city reports diminishing UGS within the urban context, the municipality has aimed to expand Malmö through densification - mostly through the refurbishing of industrial areas according to official documents regarding city development. This study uses the official greenery guidelines for Malmö, to assess how access to UGS corresponds to official aims. It focuses on the relation to children’s daytime access to UGS by examining the accessibility from school environment, using pre- and compulsory schools as the base for analysis. This study also examines how this varied depending on socio-economic background. To assess the extent of UGS access, GIS is used to develop a methodology using open access satellite-, demographic- and socioeconomic data. By creating a landcover map of Malmö. using a satellite image and maximum-l, Urban green space (UGS) refers to open spaces within an urban context which consists of greenery and nature. These can take many forms, from just being a small patch of grass to an urban forest. These UGS have proven to be beneficial for human health and well-being. While it is said that green spaces are good for everyone, they are also very important for children’s development according to a multitude of studies – supporting the behavioral, intellectual, and physical development of children. When cities grow, the extent of UGS often gets smaller. Research shows that the current concept of densification, which is achieved by infill, land repurposing, and adding height to existing buildings, are often to blame for this development. The access to UGS is not equal, and oftentimes those with lower socio-economic status are negatively affected by a loss of UGS. Given the above, this study set out to examine how changes to a city influences UGS and access to green space in urban areas using the city of Malmö as a case study. It also sets out to examine if there is a socio-economic context to UGS access. A rapidly growing urban area, Malmö is the fastest growing city in Sweden. The municipality has aimed to expand Malmö through densification - mostly through the refurbishing of industrial areas according to official documents regarding city development. At the same time, Malmö city reports diminishing UGS within the urban context. To assess the extent of UGS access, GIS was used to develop a methodology using open access satellite-, demographic- and socioeconomic data. By creating a landcover map of Malmö, using á satellite image and maximum-likelihood classification, the UGS was mapped for the studied year. This study uses the official greenery guidelines for Malmö to assess how access to UGS corresponds to official aims. Statistical analysis using SPSS was used to examine correlations to socioeconomic variables, making it possible to analyze how access to green space var

The integration of Geographic Information Systems (GIS) into real estate analysis has long been considered an interesting interdisciplinary pursuit, but has yet to become mainstream. Despite the increasing academic focus over the last twenty years, this endeavour has mostly been approached from the scientific side of Geography. Inversely, such focus from the real estate sector remains marginal. Notably, there is an expanding theoretical and empirical basis supporting the importance of further exploring the GIS and Real Estate integration potential. Besides, the real estate sector is being increasingly scrutinised regarding the transparency and validity of decision-making practises. GIS-based analysis can help meet such requirements. The present research looked into the role of GIS in real estate analysis. The aim was to apply multicriteria evaluation techniques for real estate land-use suitability analysis in the Greek coastal city of Volos. The multicriteria evaluation of land-use suitability was examined based on selected spatial criteria related to real estate values in the study area, using the non-fuzzy and fuzzy method of the Analytical Hierarchy Process (AHP). The analysis focused on the Commercial, Office and Residential land-uses. Research findings showed that fuzzy AHP should always be considered in terms of providing more accurate spatial weights compared to the non-fuzzy AHP, but whether the one will be selected over the other is dependent on context and the resources needed. The AHP analysis provided clear classification of suitability for the land-uses examined. Validity of the AHP output was assessed by using correlation analysis. The research also focused on the spatial criteria weight extraction methods, which are not often detailed in relevant studies. Based on the findings, attention is needed when using pairwise comparison matrices (PCMs) for weighting spatial criteria, if the participants have no prior experience with such processes. Also, fuzzi, Theoretically, the discussion on the integration of Geographic Information Systems (GIS) into real estate analysis goes back to the early 90s. Empirical research was late to follow, but there is an increasing academic focus in the last twenty years. This trend has mostly been driven by geographers, while contribution by the real estate sector still remains marginal. Despite the importance of location to real estate, GIS spatial analysis has yet to enter the mainstream real estate research. Notably, there is an expanding theoretical and empirical basis supporting the utility of integrating GIS science and tools into real estate analysis. Moreover, the real estate sector has increasingly been scrutinised on the validity and transparency of its decision-making practices. GIS methods and tools can help improve real estate analysis. This research looked into the utility of GIS in real estate analysis, by applying multicriteria evaluation for real estate land-use suitability analysis in the Greek coastal city of Volos. Main aim was to model the varying suitability of the Volos city urban area for commercial, office and residential land-uses, using and comparing the output of different methods. To that end, various spatial criteria i.e. distances from open spaces, bus stops, waterfront etc. were set. The expert opinion of real estate professionals was sought, and then used to identify the varying importance (weights) of the spatial criteria for each real estate land-use. Multicriteria evaluation methods used for this research provided clear and reliable suitability patterns for the real estate land-uses examined. The approach of this research provided findings useful both to local planning authorities and real estate professionals. Multicriteria evaluation may help spatial planning decision makers develop targeted policies related to optimising land-use parameters. Also, real estate professionals will be able to operate in a more spatially informed manner, thus reducing th

In the Mekong region, sustainable water resource management is a significant challenge for all countries involved. In Cambodia, where rice production is crucial for household food security and export, groundwater is increasingly used for irrigation during the dry season, leading to higher rice yields. However, this unplanned and unregulated use of groundwater is causing depleting groundwater levels in the region. Economic challenges and pandemic restrictions have likely changed irrigation patterns, affecting groundwater storage. To investigate the impact of changing irrigation patterns on groundwater levels during the pandemic a groundwater model using GMS MODFLOW was established, initially creating a steady-state model and then transitioning to a transient-state model, where evapotranspiration (ET) should be used as an indicator of groundwater irrigation. Furthermore, input data to the model were collected during field visits in Cambodia. The calibrated models performed well, but automated parameter estimation faced computational issues. Analysis showed increased groundwater decline during the pandemic. Data limitations and simplifications were acknowledged, suggesting a need for better data and model enhancements for accurate groundwater modelling and sustainable water management., In the Mekong region, managing water resources sustainably is a big challenge. In Cambodia, where rice farming is vital for food security and exports, groundwater is now a source for irrigation, especially during the dry season, increasing rice yields. However, this unregulated use is causing groundwater levels to drop. Economic challenges and pandemic measures likely changed irrigation patterns, affecting groundwater storage. To understand these changes, GMS MODFLOW was used to create a groundwater model, and field visits in Cambodia were conducted, to collect the relevant input data to the model. Despite challenges with automated parameter estimation, the model performed well. Analysis showed increased groundwater decline during the pandemic. Data limitations and simplifications suggest a need for better data and model enhancements for accurate groundwater modelling and sustainable water management.

The Atlantic Multidecadal Variability (AMV) is a variation in sea surface temperature (SST) in the North Atlantic with a period of about 60-90 years. The drivers of this mode of variability are largely unknown as observational data only go back 150 years. Global climate models can help us better understand the AMV and its drivers and this thesis investigates how the AMV behaves in the Earth system model EC-Earth3. The thesis examines a 1000-year-long pre-industrial run and evaluates potential driving variables for the AMV. Specifically, the Atlantic Meridional Overturning Circulation (AMOC), which supplies the North Atlantic with warm, salty waters of tropical origin, as well as total cloud cover that affects the incoming solar radiation to the sea surface. The thesis finds that the AMOC is well correlated with the AMV with a lead of 4 years, suggesting that the AMOC is a key factor in modulating the AMV. It also finds that the AMV in the model experiences a period of around 128 years, longer than in observations, and that the subtropical arm of the AMV is weaker than in observations. Finally, the thesis finds positive cloud feedback in the subtropical arm of the AMV that enhance and propagate the changes in SSTs southward. Since the subtropical AMV arm is not as strong as in observations, the feedbacks are either not strong enough, or there are missing feedbacks needed to fully form the subtropical arm of the AMV in EC-Earth3., The ocean affects our climate to a great extent. Here in Scandinavia we have the Gulf Stream to thank for our warm climate as it transports warm water from the south up to the western coast of Scandinavia. The warm surface water heats up the atmosphere and brings us our pleasant Swedish summers, and relatively mild winters. If something were to happen to the Gulf Stream our climate would drastically change. The ocean is a massive interconnected web of different processes that all intertwine with each other. Pull one string and it can have unforeseen consequences in other parts of the ocean. One such string is the Atlantic Multidecadal Variability (AMV). The AMV is a variation in sea surface temperature (SST) in the North Atlantic. It changes between a warm period and a cold period on a time-scale of around 60-90 years. While it is not a very large variation it still packs enough power to affect the climate of the entire Northern Hemisphere by a significant amount. The AMV moved into its warm phase in the 1990s, resulting in warming and a change in weather patterns across the entire Northern Hemisphere. If we do not take the AMV into account in our global climate models the observed climate change will be larger than our predictions, as models underestimate the warming. It is thus important to know how the AMV functions and how it interacts with the rest of the North Atlantic. Scientists argue over what the main power source of the AMV is, and part of the reason why it is hard to fully understand the dynamics of the AMV is because of its long period. We only have observational data going back around 150 years, which is only enough to maybe cover one full cycle of the AMV. We therefore have to turn to climate models to investigate it properly. One such model is the relatively new global climate model, EC-Earth3. This thesis investigates the AMV through a model run of EC-Earth3 and finds that in the model, the AMV is in part caused by variations in oceanic circulation

Northern peatlands, spanning across vast regions of the northern hemisphere, are critical carbon reservoirs essential for global carbon cycling and climate regulation. Their dual role as long-term atmospheric carbon dioxide (CO2) sinks and the largest natural source of methane (CH4) in the northern hemisphere allows them to accumulate more carbon than they emit, helping to mitigate the rise in atmospheric CO2 levels. However, they face significant threats from ongoing climate change, while the local response to climate change is divided. The potential impacts of increasing temperatures, altered precipitation patterns and shifts in hydrology have the capacity to accelerate decomposition rates and release stored carbon into the atmosphere, thereby exacerbating global warming. Conversely, the net productivity of peatland ecosystems also increases due to CO2 fertilization and prolonged growing seasons in northern latitudes. This study employs the dynamic global vegetation model LPJ-GUESS to analyse historical and future carbon dynamics of northern peatlands, aiming to reduce uncertainty surrounding peatland carbon stocks by evaluating the historical model results and assessing the fate of four northern peatlands under CMIP5 projections (RCP2.6 and RCP8.5). The project does not only identify the temporal and spatial patterns of the peatland carbon stocks and greenhouse gas emissions at these sites but also quantify how these patterns are in response to climatic drivers. Evaluation against available datasets and literature reveals underestimations in modelled annual carbon sink capacities) and overestimated CH4 emissions, introducing uncertainties in future carbon balance assessments. Despite limitations, the trend in future carbon stocks suggests a potential reduction across Canadian sites under RCP8.5, while the sites demonstrate resilience under RCP2.6. The high emissions scenario (RCP8.5) projects Stordalen and Mer Bleue to potentially transition into carbon sources b

This dataset contains the codes for machine learning and Shapley value analysis over global land and two single spots (Amazona and Southern New South Wales). We have customized the Shapley Value visualization tools based on the original package, so please update the _beeswarm.py and _scatter.py codes in the package when running our codes. (2024-03-14)

This dataset contains the calculation codes of FFDI and FWI. (2024)

The dataset includes sediment oxygen uptake, sediment oxygen profiles, sediment oxygen penetration depth, water column CTD profiles (temperature, salinity, sigma density, oxygen, and chlorophyll a), and buoyance frequency (N2) from the Pearl River Estuary and adjacent coastal shelf. Data in the literature are also included for comparison. (2023-03-09)

Aerosol Nitrogen and Carbon Observation Data at 12 sites of China (2024-03-01)

We develop and evaluate a method for quantifying polyP in environmental planktonic samples. This dataset includes two data files. The first file (table) includes the responses of polyP-JC-D7 fluorescence signal (excitation 405 nm, emission 535 nm) under a range of polyP concentrations, tested for a number of experimental variabilities, including the compositions of the cell lysing buffer, the concentration of the fluorescence dye JC-D7, and the chain lengths of polyP. The second file (table) includes data for comparisons of polyP estimated using different extraction and quantification methods, from algae, bacteria, and environmental samples.

Data description This data collection includes the minimal datasets necessary to ensure the replicability of the results presented in the above-mentioned manuscript. Specifically: • Xylogenesis, GPPfluxsat, and FluxNet fitting parameters report the parameters of each fitted curve and the point of maximum for each site, year, and species. • An example R code is also available (Rcode_parametric_fitting_and_random_forest.txt) to demonstrate how the fitting was effectively carried out. • The dataset includes fitting parameters for cambial activity and wood formation phenophases, as well as monthly averages for phenological observations on xylogenesis and raw data for xylogenesis. • A file titled "Xylogenesis_site_info" provides a description of the wood formation sites, along with monthly averages of the number of cambial, enlarging, wall thickening, lignifying, and mature cells. • Raw xylogenesis data are available under restricted access. Please consult the data policy for further information. Data policy The present data are available under the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International - CC BY 4.0; https://creativecommons.org/licenses/by/4.0/). Users of the data should adhere to the following attribution guidelines for CC-BY-4.0: • Cite the original paper that assembled and utilized this data, citing Silvestro et al. 2024. • Provide the DOI of this data collection in the paper (DOI: …). For access to the xylogenesis raw data, interested parties should first contact one of the following individuals: • Roberto Silvestro, robertosilvestro91@gmail.com • Sergio Rossi, srossi@uqac.ca

This dataset contain the raw data used in the realization of the analysis linked to the following article: Mr. William Fortin, Prof. Olivier Morissette, Dr. Serge Lavoie, Dr. Marc Mingelbier, and Dr. Pascal Sirois. Matching the elemental fingerprints of fish otoliths with water masses of the St. Lawrence River and its tributaries, Canada. Canadian Journal of Fisheries and Aquatic Sciences. https://doi.org/10.1139/cjfas-2023-0097