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Society faces existential challenges, such as global warming, demographic change and digital innovations. Standards help solving problems and reaping opportunities. They have long been recognised as important, from technological, business, and economic perspectives, but clear evidence about their societal impact is still missing.Against this background, the XXM Partners commissioned this project to get a clearer view of how standards impact society. The project was carried out by researchers from Eindhoven University of Technology and Rotterdam School of Management, Erasmus University between November 2021 and November 2022. We conducted a pre-study of 48 standards, reviewed academic literature on standards’ impact and its measurement. We carried out eight in-depth case studies of particular standards with 86 expert interviews, relevant documents, and other sources. In doing so, we reached all five goals that were agreed in the project contract:Goal 1: Overview over dimensions of standards impactsSocietal impact has many dimensions, which relate, e.g., to public health, education, or the environment. Our literature review identified the 17 United Nations Sustainable Development Goals (SDGs) as the most suitable framework for our project. The SDGs are goals, agreed upon in global consensus, on which society should focus and improve. A growing global movement has formed around them to address societal challenges.In a pre-study, we conducted desk research to explore potential impacts of 48 standards. They cover the breadth of subject areas, and include standards with societal, environmental, technical and/or business purposes. We find that these standards can be linked to all SDGs. Often one standard affects multiple SDGs, going beyond intended impacts.Goal 2: Overview over scientific literature on standards’ impactsStandards are important for society. This is widely recognised in academic literature. However, there is relatively limited research on how they impact society. Most of this limited research focuses on two standards: ISO 9001 (quality management systems) and ISO 14001 (environmental management systems). Our review reveals a research focus on business/economic (both standards) and environmental (ISO 14001) impacts. Some evidence exists on non-environmental societal impacts (e.g., workplace safety), but this remains limited.We extended our review to other fields, especially addressing best practice for impact measurement. We compared multiple approaches, selected the Logic Model for understanding impact, and adapted it to standards. This model helps understand impact by tracing it in five steps: (1) inputs (including standards), (2) activities for standard implementation, (3) outputs (a situation reflecting what a standard prescribes), (4) outcomes (changes for stakeholders), and eventually (5) long-term impact.Goal 3: Evidence of standards’ societal impacts – empirical researchUnder the project team’s guidance, master students carried out eight in-depth studies in Norway (two studies), Sweden (two studies), Finland (two studies), Denmark and Austria. Standards were selected in consultation with the XXM Partners. They cover a broad range of important areas, e.g., greenhouse gas (GHG) emissions reporting (ISO 14064-1), clinical trials for medical devices (ISO 14155), and information security management (ISO 27001).Our studies led to findings about (1) specific societal changes caused by the investigated standards, (2) what drives standards’ impacts in general, and (3) measuring standards’ impact (see Goal 4 below).Findings about standards’ specific societal changesTwo standards in our study are particularly successful in creating positive impact:• EN 16516 (emissions of construction products into indoor air) promotes the availability of low-emission construction products, thereby contributing to healthy indoor air.• ISO 14155 (clinical investigations for medical devices) contributes to safer clinical trials and availability of innovative medical devices for patients.In the other cases, we observe strong potential for positive societal impact. However, this is not achieved, e.g., due to standards not being implemented at large scale, not meeting potential users’ expectations, and/or competing with other standards. In two cases (ISO 14064-1, GHG emissions accounting; ISO 14044, life-cycle assessment), foreseeable abuse of the standard may even provide opportunities for greenwashing.All investigated standards have broader (potential) impacts on the SDGs than identified by ISO. E.g., ISO 14155 does not only contribute to SDG 3 (“Good Health and Wellbeing”), but also to SDG 9 (“Industry, Innovation and Infrastructure”) and the institutional aspect of SDG 16 (“Peace, Justice and Strong Institutions”).Findings about drivers behind standards’ impacts: importance of their ecosystemsAll investigated standards are deeply embedded in their ecosystems. A remarkable finding concerns the large extent, to which (mis)alignment with this context drives their impact. This also makes it challenging to isolate the standard’s impact from that of its entire ecosystem.Where we observed positive impact, this was largely due to a standard serving a clear purpose in its ecosystem (e.g., meeting market needs, supporting certification, alignment with regulatory requirements). In the cases where potentials for positive impact have not yet been realised, our data show how this is driven by misaligned ecosystems and standards. We have recommendations for how to address this (see Goal 5 below)Goal 4: Applied methodology for demonstrating societal impactsIn the course of the project, we developed a methodology for measuring standard’s societal impacts. It consists of a six-step process, which is based on four essential frameworks/tools:1. Stakeholder analysis,2. A checklist for analysing a standard’s ecosystem,3. The logic model for standards,4. The SDGs as a framework for classifying impact.We recommend this methodology for systematically studying further standards’ impacts.Goal 5: Recommendations to National Standard Bodies (NSBs)Our results have clear implications for the XXM Partners, ISO/IEC, CEN/CENELEC, and their members. Based on these implications, we provide recommendations on (1) communicating standards’ impacts to policymakers and other stakeholders, and (2) enhancing standards’ positive impact. Section 9.5 (p.102) specifies these recommendations in detail.Communicating standards’ impact• To policymakers: Emphasise standards’ functions as essential instruments for change in their respective ecosystems.• To other stakeholders: Focus on standards’ contributions to the SDGs, while acknowledging that the full potential is not yet achieved.• Ensure standards’ inclusion in frameworks for measuring societal impact: Engage in dialogue with the impact measurement community. Ensure that increasingly influential approaches to measuring societal impact include standards. This would support clearer communication about standards’ impacts and contribute to frameworks’ accuracy.Enhancing standards’ positive impact• Already address societal impacts during the standardisation process. We provide two tools, which may be used for this.• Improve standards’ relevance and quality in line with their ecosystems’ expectations (positioning standards relative to competing and/or complementary standards, clarity of requirements, quality of translations, withdrawing unused standards).• Need for future research in six directions: (1) Studies at the level of standard families and/or ecosystems. (2) Large-scale replication. (3) Understanding standard competition. (4) Reflecting ongoing developments in impact measurement. (5) Effects of societal change on standards’ role in society. (6) Starting from the “grand- societal challenges”.ConclusionOur work makes a novel contribution to knowledge about standards’ impacts. By doing so, we offer concrete insights, which the XXM Partners can use in communicating the benefits of standards. We also identify key factors affecting standards’ societal impacts, and offer tools and methods that are relevant for practitioners and researchers alike. The XXM Partners can use these insights in their work to further maximise standards’ value to society, and limit any potential negative effects.

This dissertation explores the dependency and relation between land use, temperature, and energy demand in urban systems. There are three main parts of this research: the relation between temperature and land use; the relation between energy demand and land use; and the dynamic relation between urban land use, temperature, and energy demand.In Chapter 3 of this dissertation, a systematic review of urban development modeling, which concerns sustainability, microclimate, and energy, is conducted. The city is facing a rapid transition over the last two decades due to urbanization, immigration, and climate change. To countermeasure with future problems and build a sustainable city, urban development models are broadly discussed. This chapter discusses the three major types of sustainable urban development models for environmental impact assessment: 1) sustainable development model, and 2) urban microclimate model, and 3) urban energy demand model. This chapter reviews these urban models and their research methods in real urban areas. Based on the state-of-art in academic research, the research achievements on three major types of sustainable urban development models are mentioned, and future perspectives are provided.For the land use and urban climate relation, Chapter 4 studies land surface temperature dynamics from a spatial and temporal scale perspective in the city of Eindhoven. Chapter 4 investigates the dependency between land use and summertime land surface temperature (LST) to explore whether optimizing land use planning can mitigate LST, and consequently adapt to the climate change forecast in Eindhoven, the Netherlands. Summertime data between 2000 and 2010 were plotted in a rasterized map of 30-meter cells, using a geographical information system (GIS) and cellular automata model. Subsequently, a set of spatial regression analysis was performed on the impact on LST of the central cells from a collection of circular von Neumann neighborhood-cell rings with five types of land use as neighborhood factors. The analysis indicates that the neighboring built-up area and openly abandoned space increase the LST of the central cell, whereas the neighboring artificial green space, natural green space, and water decrease the central cell’s LST. The impervious surface material has a heating effect on LST, whereas tree canopy has a cooling effect. The surrounding land-use effects on the central cells’ LST decreases after 450m. The LST of a built-up area or natural green area is more sensitive to the neighboring impacts than the water body, artificial green area, and open abandoned space. Implications of this research are spatial planning opportunities for reducing Surface Urban Heat Island (SUHI) effects through allocating different land-use types within certain neighboring rings.To investigate the relation between energy demand and land use, Chapter 5 analyzes urban morphology indicators for urban energy modeling in a spatial context. The reduction of energy consumption in the urban environment has attracted numerous empirical studies in recent decades. However, limited studies have been conducted to investigate the impact of the urban layout on urban energy demand. To analyze the spatial correlation between urban layout and energy demand, Eindhoven is used as a case study in this paper. The urban layout is described by urban morphology indicators (UMIs), which are calculated by Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), building height, plot area and volume of the built environment. The energy demand model includes annual gas and electricity demand. Ordinary least squares regression (OLS) and geographically weighted regression (GWR) models are applied for the regression of energy demand to the UMIs. For the spatial regression, land use is clustered into five types: urban areas (U), open space (O), artificial green areas (G), natural green areas (V), and water body (W). The results revealed that energy demand and UMIs have a significant geographical relation. Among the UMIs, NDVI, building height, and plot area together constitute the most influential indicators for urban energy demand. Finally, the possible usage of the results in sustainable urban design and planning are discussed.The relation between energy consumption, land use, and climate change is broadly discussed. However, there are comparatively little studies that study the effect of climate change and, more specifically, temperature change on energy consumption on an urban scale. Chapter 6 aims to discover the cause-effect relation between land use (L), energy (E), and temperature (T) in the urban system. Furthermore, various indicators combinations for land use (L) and temperature (T) are applied to optimize the urban energy model performance. Besides, the impact from the neighboring land use within the distance 450m is also included as a land-use indicator. The result of Chapter 6 can be applied to sustainable urban planning, targeting energy reduction, and climate adaptation.This dissertation includes empirical spatial and temporal modeling for land use, temperature, and energy demand on an urban scale. Based on an extensive data set, different indicators for describing the urban environment have been analyzed to evaluate their significance and impact on the interaction between these three aspects. This dissertation contributes to the existing body of literature on climate change by providing insight on relevant urban land use indicators for urban system modeling, whereas most studies focus either on local/ building level or the regional/ national level. Additionally, this dissertation investigates the relation between energy consumption and climate change in an urban context, which is hardly covered by scientific literature until now.The results can be applied to cities with similar climate conditions like Eindhoven, the Netherlands. For example, existing neighborhoods suffering from urban heat island effect can be adapted to mitigate these effects, not only focusing on the neighborhood itself but also its surroundings. Newly developed areas can take advantage of the findings when planning an energy and climate sustainable land use mix and urban morphology.

Social activities are responsible for an important portion of trips and they constitute the fastest growing segment of travel. Moreover, social activities and mobility are important aspects of people’s quality of life. Therefore, social activities are important for transport planners to take into account. As social activities involve meeting with other persons at a certain time and location, the spatial-choice behavior for social activities is critical for successful urban design and planning. Over the last decades, researchers have attempted to explain individual (social) travel behavior as a result of socio-demographic and land-use variables. However, recently, it has been acknowledged that other variables that offer opportunities for social mobility have to be added. As social travel demand is derived from a wish or need to perform activities with other people, it is important to incorporate social networks into the study. Moreover, social activities are likely to be influenced by the use of new information and communication technologies (ICT’s), as these ICT’s offer new possibilities for the maintenance of social networks that are becoming more geographically spread. Knowledge about the relationship between ICT’s, social networks and social activity-travel behavior is rather limited. In order to assess future transportation needs for social activities, research is needed. The aim of this dissertation is therefore to study the way in which social activity-travel patterns are influenced by people’s personal characteristics, properties of the built environment, ICT-use and social networks. To that end, a data collection instrument was designed. The instrument consists of a two-day paper-and-pencil social interaction diary a questionnaire on personal characteristics and a follow-up questionnaire on personal social network members. The social interaction diary captured data on ICT-mediated social interactions, as well as face-to-face social activities and travel for these activities. In addition, the social interaction diary was used to collect data on the people with whom the respondents interacted during those two days, including age, gender, social category, distance and frequency of communication with different modes. In addition to the social interaction diary a questionnaire was designed to gather data on the respondents’ personal and residential characteristics. To allow the estimation of the impact of the built environment a requirement for the data collection was to secure sufficient variation in characteristics of the built environment. To this end, the sample was stratified by urban density. The data were collected between January and March 2008 in the region of Eindhoven, among 747 respondents, aged 15 or over. To capture the respondents’ social networks, a follow-up questionnaire was used, which was mailed to a subsample of the respondents. In this social network questionnaire, respondents were asked to record information on all their social network members, including gender, age, social category, how long they have known each other, distance to their homes and the frequency of interaction with each alter by different modes (face-to-face, telephone, SMS, e-mail, IM). The social network questionnaire was completed by 116 respondents. Quantitative analyses were performed on the data. The analyses focus on exploring and testing multivariate relationships in the data. Analyses were carried out to examine the effects of personal characteristics and properties of the built environment on size and composition of social networks; contact frequency and choice between different communication modes, and social activity-travel patterns. The analyses also explored to what extent and how the nature and strength of the relationship between personal characteristics and properties of the built environment and social activity-travel patterns is mediated by ICT-mediated communication and characteristics of social networks. Regression and discrete choice models were used to predict one dependent variable as a function of one or more independent variables. To analyze simultaneously the direct and indirect dependencies between use of communication technology, social networks and activity-travel patterns, a structural equation approach was used. Because the data have a hierarchical structure (individuals(egos) have multiple alters or interactions), multi-level analysis was used. The estimation results of the models allow us to reconstruct the generation of social activities and travel demand for social purposes. The empirical results suggest that the built environment, ICT-use and social networks all play an important role in the generation of social activity-travel and have to be taken into account in transport policy.

Social activities are responsible for an important portion of trips and they constitute the fastest growing segment of travel. Moreover, social activities and mobility are important aspects of people’s quality of life. Therefore, social activities are important for transport planners to take into account. As social activities involve meeting with other persons at a certain time and location, the spatial-choice behavior for social activities is critical for successful urban design and planning. Over the last decades, researchers have attempted to explain individual (social) travel behavior as a result of socio-demographic and land-use variables. However, recently, it has been acknowledged that other variables that offer opportunities for social mobility have to be added. As social travel demand is derived from a wish or need to perform activities with other people, it is important to incorporate social networks into the study. Moreover, social activities are likely to be influenced by the use of new information and communication technologies (ICT’s), as these ICT’s offer new possibilities for the maintenance of social networks that are becoming more geographically spread. Knowledge about the relationship between ICT’s, social networks and social activity-travel behavior is rather limited. In order to assess future transportation needs for social activities, research is needed. The aim of this dissertation is therefore to study the way in which social activity-travel patterns are influenced by people’s personal characteristics, properties of the built environment, ICT-use and social networks. To that end, a data collection instrument was designed. The instrument consists of a two-day paper-and-pencil social interaction diary a questionnaire on personal characteristics and a follow-up questionnaire on personal social network members. The social interaction diary captured data on ICT-mediated social interactions, as well as face-to-face social activities and travel for these activities. In addition, the social interaction diary was used to collect data on the people with whom the respondents interacted during those two days, including age, gender, social category, distance and frequency of communication with different modes. In addition to the social interaction diary a questionnaire was designed to gather data on the respondents’ personal and residential characteristics. To allow the estimation of the impact of the built environment a requirement for the data collection was to secure sufficient variation in characteristics of the built environment. To this end, the sample was stratified by urban density. The data were collected between January and March 2008 in the region of Eindhoven, among 747 respondents, aged 15 or over. To capture the respondents’ social networks, a follow-up questionnaire was used, which was mailed to a subsample of the respondents. In this social network questionnaire, respondents were asked to record information on all their social network members, including gender, age, social category, how long they have known each other, distance to their homes and the frequency of interaction with each alter by different modes (face-to-face, telephone, SMS, e-mail, IM). The social network questionnaire was completed by 116 respondents. Quantitative analyses were performed on the data. The analyses focus on exploring and testing multivariate relationships in the data. Analyses were carried out to examine the effects of personal characteristics and properties of the built environment on size and composition of social networks; contact frequency and choice between different communication modes, and social activity-travel patterns. The analyses also explored to what extent and how the nature and strength of the relationship between personal characteristics and properties of the built environment and social activity-travel patterns is mediated by ICT-mediated communication and characteristics of social networks. Regression and discrete choice models were used to predict one dependent variable as a function of one or more independent variables. To analyze simultaneously the direct and indirect dependencies between use of communication technology, social networks and activity-travel patterns, a structural equation approach was used. Because the data have a hierarchical structure (individuals(egos) have multiple alters or interactions), multi-level analysis was used. The estimation results of the models allow us to reconstruct the generation of social activities and travel demand for social purposes. The empirical results suggest that the built environment, ICT-use and social networks all play an important role in the generation of social activity-travel and have to be taken into account in transport policy.

Office firms represent a large share of economic activities, especially in the sector of professional services. In general, firms will follow an evolutionary cycle comprising the dynamics of starting-up, finding a location to establish their business, growing or declining, relocating and going out of business. The underlying approach taken in this research project relies on the idea that the evolution of office firms is strongly influenced by the urban environment. Traditionally, the specific relationship between transportation and land use has been examined in the framework of aggregate integrated land use-transportation (LUTI) models. However, the field is moving toward a more disaggregate approach, based on concepts of micro simulation and agent-based models. These are built on behaviorally richer concepts for examining firm dynamics, such as firm demography. The aim of this research project is to contribute to this emerging field by developing an agent-based modeling approach to simulate the evolution of office firms in time and space. To this end, a set of statistical/econometric models is used to investigate the relationships between specific firm demographic processes and the urban environment. The research project contributes to the existing literature by focusing on office firm demography and related land use and transportation influences, exploring alternative approaches to model office firm dynamics empirically, and using very detailed nationwide data from The Netherlands.

Office firms represent a large share of economic activities, especially in the sector of professional services. In general, firms will follow an evolutionary cycle comprising the dynamics of starting-up, finding a location to establish their business, growing or declining, relocating and going out of business. The underlying approach taken in this research project relies on the idea that the evolution of office firms is strongly influenced by the urban environment. Traditionally, the specific relationship between transportation and land use has been examined in the framework of aggregate integrated land use-transportation (LUTI) models. However, the field is moving toward a more disaggregate approach, based on concepts of micro simulation and agent-based models. These are built on behaviorally richer concepts for examining firm dynamics, such as firm demography. The aim of this research project is to contribute to this emerging field by developing an agent-based modeling approach to simulate the evolution of office firms in time and space. To this end, a set of statistical/econometric models is used to investigate the relationships between specific firm demographic processes and the urban environment. The research project contributes to the existing literature by focusing on office firm demography and related land use and transportation influences, exploring alternative approaches to model office firm dynamics empirically, and using very detailed nationwide data from The Netherlands.

Activity-based models of transport demand are increasingly used by governments, engineering firms and consultants to predict the impact of various design and planning decisions on travel and consequently on noise emissions, energy consumption, accessibility and other performance indicators. In this context, non-discretionary activities, such as work and school, can be relatively easily explained by the traveller’s sociodemographic characteristics and generalised travel costs. However, participation in, and scheduling of, discretionary and joint activities are not so easily redicted. Understanding the social network that lies on top of the spatial network could lead to better prediction of social activity schedules and better forecasts of travel patterns for joint activities. Existing models of activity-travel behaviour do not consider joint activities in detail, except within households to a limited extent. A recent attempt developed at ETH Zurich to incorporate social networks in a single-day optimisation scheduling model did not model joint activities as such, rather rewarding individuals for scheduling activities at the same location and at the same time as their friends. Realistic social networks were also not incorporated. The aim of this thesis is to contribute to this rapidly expanding field by developing a simulation of activity and travel behaviour incorporating social processes and joint activities to investigate the effects on activity and travel behaviour over a simulated period of weeks. The model developed is intended as a proof-of-concept. In order to achieve this aim, an agent-based simulation was designed, implemented in Java, and calibrated and partly verified with real-world data. The model generates activities on a daily basis, including the time of day and duration of the activity. An interaction protocol has been developed to model the activity decision process. Data collected in Eindhoven on social and joint activities and social networks has been used for calibration and verification. Alongside the model development, several issues are addressed, such as exploring which parameters are useful and their effects, the data required for the validation of agent-based travel behaviour models, and whether the addition of social networks to models of this type makes adifference. Sensitivity testing was undertaken to explore the effects of parameters, which was applied to increasingly more complex versions of the model (starting from one day of outputs with no interactions between individuals and finishing with full interactions over many days). This showed that the model performed as expected when certain parameters were altered. Due to the components included in the model, scenarios of interest to policy makers (such as changes in population, land-use changes, and changes in institutional contexts) can be explored. Altering the structure of the in- put social networks and the interaction protocols showed that these inputs do have a difference on the outputs of the model. As a result, these elements of the model require data collection on the social network structure and the decision processes for each local instantiation. Two more "traditional" transport planning policy scenarios, an increase in free time and an increase in travel cost, showed that the model performs as expected for these scenarios. It is shown that the use of agent-based modelling is useful in permitting the incorporation of social networks. The social network can have a significant impact on model results and therefore the decisions made by planners and stakeholders. The model can be extended further in several different directions as new theories are developed and data sets are collected.

Activity-based models of transport demand are increasingly used by governments, engineering firms and consultants to predict the impact of various design and planning decisions on travel and consequently on noise emissions, energy consumption, accessibility and other performance indicators. In this context, non-discretionary activities, such as work and school, can be relatively easily explained by the traveller’s sociodemographic characteristics and generalised travel costs. However, participation in, and scheduling of, discretionary and joint activities are not so easily redicted. Understanding the social network that lies on top of the spatial network could lead to better prediction of social activity schedules and better forecasts of travel patterns for joint activities. Existing models of activity-travel behaviour do not consider joint activities in detail, except within households to a limited extent. A recent attempt developed at ETH Zurich to incorporate social networks in a single-day optimisation scheduling model did not model joint activities as such, rather rewarding individuals for scheduling activities at the same location and at the same time as their friends. Realistic social networks were also not incorporated. The aim of this thesis is to contribute to this rapidly expanding field by developing a simulation of activity and travel behaviour incorporating social processes and joint activities to investigate the effects on activity and travel behaviour over a simulated period of weeks. The model developed is intended as a proof-of-concept. In order to achieve this aim, an agent-based simulation was designed, implemented in Java, and calibrated and partly verified with real-world data. The model generates activities on a daily basis, including the time of day and duration of the activity. An interaction protocol has been developed to model the activity decision process. Data collected in Eindhoven on social and joint activities and social networks has been used for calibration and verification. Alongside the model development, several issues are addressed, such as exploring which parameters are useful and their effects, the data required for the validation of agent-based travel behaviour models, and whether the addition of social networks to models of this type makes adifference. Sensitivity testing was undertaken to explore the effects of parameters, which was applied to increasingly more complex versions of the model (starting from one day of outputs with no interactions between individuals and finishing with full interactions over many days). This showed that the model performed as expected when certain parameters were altered. Due to the components included in the model, scenarios of interest to policy makers (such as changes in population, land-use changes, and changes in institutional contexts) can be explored. Altering the structure of the in- put social networks and the interaction protocols showed that these inputs do have a difference on the outputs of the model. As a result, these elements of the model require data collection on the social network structure and the decision processes for each local instantiation. Two more "traditional" transport planning policy scenarios, an increase in free time and an increase in travel cost, showed that the model performs as expected for these scenarios. It is shown that the use of agent-based modelling is useful in permitting the incorporation of social networks. The social network can have a significant impact on model results and therefore the decisions made by planners and stakeholders. The model can be extended further in several different directions as new theories are developed and data sets are collected.

Contemporary regional spatial plan-making in the Netherlands is characterized as a complex process wherein multiple actors, with different levels of interests and demands, try to commonly develop a coherent and comprehensive set of future plan scenarios. The construction of the set of spatial plan scenarios is the core activity of each regional spatial planning process and is often unique and tailored to the specific context and policy objectives formulated for a plan area. Modern collaborative scenario construction is complex due to a variety of participating actors, as public planners, domain experts and non-experts as interest groups and landowners. The level of participation of the non-expert group varies from process to process, but for effective spatial scenarios it is important to ergonomically construct, surprising and plausible scenarios with vivid, proximate and concrete content. The last decades, many attempts have been undertaken to support plan scenario development with digital systems, with strong emphasis on the analytical capabilities of computers. Little attention, however is given to the development of intuitive sketch and design tools and methods, that support the interactive process of large-scale collaborative multi-level plan design, by visualizing and modeling comprehensive landscape scenarios down to the level of cadastral lots. Therefore, the main objective of this research is to develop and evaluate a method, that generates plausible landscape configurations by using user-defined landscape typologies, as a digital support tool for participatory spatial plan-making. To enable the effective design and modeling of vivid and plausible future spatial scenarios, there is a need for a method which supports the two main steps of plan scenario construction in Simlandscape. Simlandscape introduces a rich set of instruments and procedures in order to construct a diverse and coherent scenario set that supports communication and social learning and that facilitate a better informed decision-making process. The central notion in Simlandscape is that actual transformation of the landscape takes place at the ownership lot level. Through construction of strategic spatial scenarios down to the level of individual or clustered lots, comprehensive qualitative and quantitative evaluation becomes possible. Design instruments are proposed, that are intuitive in supporting the funneling creative design process from abstract and general sketches to specific and detailed economic function allocation and landscape layout modeling. The latter activity is supported by the definition and allocation of landscape lot typologies with (non-spatial) attributes. The first step in plan scenario construction in Simlandscape consists of the distribution and allocation of landscape lot typologies to lot geometries. This step poses a complex problem, which can be manually as well as automatically be solved, but is not the core of this research. The second step, assumes that a landscape lot typology is allocated to a lot geometry, and contains generation of a plausible landscape configuration, based on the attributes of the landscape lot typology. This step can also be done manually, but is very time-consuming for a total plan area involved. Therefore, automatic generation of a plausible landscape configuration, based on the properties of the allocated landscape lot typology is important and central subject in this research. The automatic generation of landscape configuration is part of the research field called ‘generative modeling’. In chapter 2, the most of the established existing generative approaches in generative landscape modeling are reviewed for their applicability and relevance as the base for the method to generate plausible landscape configurations from landscape lot typologies. In spatial planning literature, four important more or less distinct fields of research are identified which offer directly or indirectly approaches for developing a generative method: 1) procedural modeling, 2) spatial multi-objective optimization modeling, 3) cellular automata and 4) multi-agent systems. The approaches to generate landscape configurations provide several points of departure. Unfortunately, none of the current approaches is directly applicable for the addressed objective in this research. Procedural modeling techniques as shape or landscape grammars are able to produce, or support the creation of detailed, appealing and realistic landscape visualizations. Due to this level of detail of modeling, the process of inference to identify relevant objects and mutual relations in reality, is complex due to the large number of objects and relations to be modeled. Moreover, the ambiguous character of the relations between objects provides large difficulties in identifying objective and generic rules. Spatial multi-objective optimization modeling in spatial planning problems, as linear integer programming, genetic algorithms and simulated annealing, have a strong theoretical base and are applied frequently in spatial planning literature to provide ‘the most favourable’ landscape and plan layout in terms of minimal development costs. More recently, also general spatial shape objectives are included in the multi-objective functions devised. The research objectives in these studies however, are often restricted to a level of layout planning which is less detailed than the objective stated in this research. A direct consequence is that shape objectives are in general terms of compactness and solely defined at the land-use class level. Furthermore, the number of land-uses to be allocated and the site to be modelled is kept relatively small. These features are enough to provide a proof of principle, but not to deal with realistic planning challenges. Cellular automata and multi-agent systems provide robust frameworks to realistically model subject and object interactions in space and time. However, the non-deterministic behavior and outcomes of the model runs make them less suitable to generate plausible landscape configurations as defined in this research. Chapter 3 describes the (development of the) landscape generator, that is compatible with the regional plan scenario development approach identified in Simlandscape. The landscape generator uses landscape types as building blocks of plan scenarios. A landscape typology describes a proposed future spatial development and contains spatial and (non)spatial (descriptive) attributes. A 2D reference image indirectly provides objective compositional and configurational characteristics of the proposed development. In essence, users allocate a landscape typology to a cadastral lot typology and based on this information, the landscape generator produces a comprehensive landscape configuration. The landscape generator is developed as a multi-objective heuristic optimization modeling approach. In this approach a sequentially updated multi-objective function is optimized for a two-dimensional allocation site. It is assumed that the site is homogeneous in physical characteristics (e.g. height, soil etc.). The multi-objective function is compiled from an available library of single spatial attributes. These spatial attributes and their target values are retrieved from the compositional and configurational characteristics present in the reference image of the landscape typology. Examples from the available spatial attributes are the number of landscape component instances, the relative size of each component or each component instance, compactness and shape of component instances and direct adjacency between two different landscape components. In a hypothetical case study, the capabilities and behavior of the landscape generator are demonstrated. In the case study, the landscape generator generates a variety of landscape configurations for a hypothetical allocation site (20x20 cells) and a rural forest estate as allocated landscape typology. The reference image of the rural forest estate provides detailed information for the compilation of the multi-objective function. The landscape generator contains probabilistic elements (e.g. random starting situation, near-random cell swap), which results in different output, each time it is run with identical input settings. The landscape generator is capable of producing a range of landscape configurations for a variety of situations. A unique situation is defined by the allocation of one landscape typology to one allocation site. Theoretically, since the method is based on the objective measurement of spatial characteristics present in a reference image, each user-defined typology can be used for a selected allocation site. The landscape typologies cannot be allocated to every imaginable dimensioned allocation site, but are bounded by the spatial extent which specifies a valid spatial extent. At the heart of the method lies the compilation of the multi-objective function. Ideally, this compilation can be executed completely objectively and without user-interaction, as the reference image of the landscape typology provides the required information. In the current prototype version of the landscape generator, however, the compilation process is partly (and in advance) controlled by the modeler. The modeler needs to specify which of the available spatial attributes to include, in which sequence to optimize them and what attribute target values to specify. Surely, the modeler is informed by statistics calculated for the reference image. An important task is to define consistent guidelines for the compilation of the multi-objective function from each landscape typology, irrespective of the properties of a valid allocation site. In this research, the modeler has been able to define specific guidelines for each landscape typology. In the current state of the method, a continuous assessment, through iterative testing, needs to be made by the modeler, about which compilation is sufficient in producing plausible configurations and which compilation process produces solutions within reasonable computation times. In chapter 4, a method is presented to obtain insight in the usability of the landscape generator. The produced landscape configurations are extensively evaluated in an extensive internet-based validation experiment. For a broad variety of different situations, landscape configurations are generated by the landscape generator for realistically dimensioned and enclosed sites. The configurations are compared with professional hand-drawn configurations, by a large group of planning professionals. The subjects are provided an interactive, user-friendly web-based inquiry, in which they are requested to (graphically) rank order a random selection out of a total set of landscape configurations (hand-made or computer-generated), from ‘most to least plausible’. The population is not informed about the difference in production process of each landscape configuration. In the experiment a distinction is made between subjective and objective plausibility, representing design quality aspects and representativeness of the landscape typology respectively. Eight different situations (three subjective and five objective) are assessed by the group of respondents and analyzed with a modified version of an approved statistical method, known as ‘the law of comparative judgement’. In addition, to indicate points of interest for further improvements of the methodology, implicit and explicit dimensions of evaluation used by the respondents for each of the objective assessments are identified. The implicit dimensions are identified using linear regression analysis, with single spatial metric properties of the configurations as explanatory variables. To identify explicit dimensions of evaluation the respondents are asked for two of the earlier presented situations, to select five pre-defined used dimensions of evaluation. The current experiment setup provides a robust method as well as reliable results about the capability of the landscape generator to produce plausible landscape configurations. With its modern interactive web interface, its well-balanced data scheme (randomness, several situations) and the use of approved statistical methods, the experiment finds a balance between maximum effective information retrieval and an acceptable level of user workload. In chapter 5, the results of the validation experiment are presented and in chapter 6 these results are analyzed. For each of the three assignments of the design quality test, it is concluded that the whole set of computer-generated configurations is not of comparable design quality as the whole set of professional configurations. Several individual computer-generated landscape configurations have comparable design quality as the professional configurations. The landscape generator is able to produce configurations with landscape components which are with respect to its individual area, shape and relative adjacency plausible. The overall structure is, however, often perceived as near-random. In some situations this is regarded plausible, while in other situations it is regarded implausible. The results of the four analyzed assignments of the representativeness test show a more favorable view on the capabilities of the landscape generator. In half of the cases, the whole set of computer-generated configurations are considered comparable in representativeness to professional onfigurations. In the other half, several individual computer-generated are considered of comparable representativeness. The representativeness test is most important in plausibility validation of the landscape generator, as the primary objective of the research implies that each actor (with different levels of design experience) should be able to provide her development idea (described in the landscape typology) as a comprehensive visualization in an integrated plan scenario. In the initial planning phases of application of the landscape generator, it is more important to obtain a first impression of the impacts (visual and analytical) of a plan scenario than a completely well-modeled and calculated landscape design. Possible non-professional design choices in a landscape typology can be reflected in the generated landscape configurations. Analysis to dimensions of evaluation gives insight into possible explanations for the plausibility ordering of the subjects.A distinction is made between explicit and implicit dimensions of evaluation. Explicit dimensions are directly assembled in the experiment and provide perceived dimensions of evaluations. The implicit dimensions, identified with linear regression analysis are however uncertain in its reliability and ideally should be assembled in relation to explicit dimensions. Results of the linear regression analysis can direct future research with different approaches. First, the attribute target values in the current compilation can be re-specified. Second, non-used but available spatial attributes can be added to the multi-objective function. Third, new spatial attributes may be developed to be included in the optimization process. In light of the main objective in this research, it is important to define consistent guidelines for generating landscape typologies for different situations. In this research, a start is made to identify important choices with respect to the minimal selection of spatial attributes, the influence of its sequence and feasible attribute target value specification. The experiment results further provide detailed directions for improvements of the landscape generator. Other recommendations put forward in this research are related to: 1) the modification of the current heuristic approach (for performance improvement and local trapping avoidance purposes) by hybridization with existing heuristic approaches as simulated annealing and evolutionary algorithms, 2) full-automatic translation from the main characteristics of a landscape typology into the compilation of the multi-objective optimization function; this translation should be as generic as possible and the resulting configurations should be thoroughly validated for plausibility for a variety of possible representative situations (i.e. combination of proposed landscape typology with typical influential allocation site characteristics), 3) extending, if possible, the current library of available spatial attributes with functions that describe more overall organizational properties of landscape typologies or investigation of (parallel or sequential) optimization at different scale levels, 4) the inclusion or extension with representative infrastructure generation and 5) the increase in the effectiveness of the validation experiment by standardizing the acquisition of professional configurations (e.g. designing materials, formats and conditions and automation of conversion to images used in the inquiry) and 6) increase in the reliability of the validation experiment by separating the different parts of the experiment according prioritisation of experiment objectives.

Contemporary regional spatial plan-making in the Netherlands is characterized as a complex process wherein multiple actors, with different levels of interests and demands, try to commonly develop a coherent and comprehensive set of future plan scenarios. The construction of the set of spatial plan scenarios is the core activity of each regional spatial planning process and is often unique and tailored to the specific context and policy objectives formulated for a plan area. Modern collaborative scenario construction is complex due to a variety of participating actors, as public planners, domain experts and non-experts as interest groups and landowners. The level of participation of the non-expert group varies from process to process, but for effective spatial scenarios it is important to ergonomically construct, surprising and plausible scenarios with vivid, proximate and concrete content. The last decades, many attempts have been undertaken to support plan scenario development with digital systems, with strong emphasis on the analytical capabilities of computers. Little attention, however is given to the development of intuitive sketch and design tools and methods, that support the interactive process of large-scale collaborative multi-level plan design, by visualizing and modeling comprehensive landscape scenarios down to the level of cadastral lots. Therefore, the main objective of this research is to develop and evaluate a method, that generates plausible landscape configurations by using user-defined landscape typologies, as a digital support tool for participatory spatial plan-making. To enable the effective design and modeling of vivid and plausible future spatial scenarios, there is a need for a method which supports the two main steps of plan scenario construction in Simlandscape. Simlandscape introduces a rich set of instruments and procedures in order to construct a diverse and coherent scenario set that supports communication and social learning and that facilitate a better informed decision-making process. The central notion in Simlandscape is that actual transformation of the landscape takes place at the ownership lot level. Through construction of strategic spatial scenarios down to the level of individual or clustered lots, comprehensive qualitative and quantitative evaluation becomes possible. Design instruments are proposed, that are intuitive in supporting the funneling creative design process from abstract and general sketches to specific and detailed economic function allocation and landscape layout modeling. The latter activity is supported by the definition and allocation of landscape lot typologies with (non-spatial) attributes. The first step in plan scenario construction in Simlandscape consists of the distribution and allocation of landscape lot typologies to lot geometries. This step poses a complex problem, which can be manually as well as automatically be solved, but is not the core of this research. The second step, assumes that a landscape lot typology is allocated to a lot geometry, and contains generation of a plausible landscape configuration, based on the attributes of the landscape lot typology. This step can also be done manually, but is very time-consuming for a total plan area involved. Therefore, automatic generation of a plausible landscape configuration, based on the properties of the allocated landscape lot typology is important and central subject in this research. The automatic generation of landscape configuration is part of the research field called ‘generative modeling’. In chapter 2, the most of the established existing generative approaches in generative landscape modeling are reviewed for their applicability and relevance as the base for the method to generate plausible landscape configurations from landscape lot typologies. In spatial planning literature, four important more or less distinct fields of research are identified which offer directly or indirectly approaches for developing a generative method: 1) procedural modeling, 2) spatial multi-objective optimization modeling, 3) cellular automata and 4) multi-agent systems. The approaches to generate landscape configurations provide several points of departure. Unfortunately, none of the current approaches is directly applicable for the addressed objective in this research. Procedural modeling techniques as shape or landscape grammars are able to produce, or support the creation of detailed, appealing and realistic landscape visualizations. Due to this level of detail of modeling, the process of inference to identify relevant objects and mutual relations in reality, is complex due to the large number of objects and relations to be modeled. Moreover, the ambiguous character of the relations between objects provides large difficulties in identifying objective and generic rules. Spatial multi-objective optimization modeling in spatial planning problems, as linear integer programming, genetic algorithms and simulated annealing, have a strong theoretical base and are applied frequently in spatial planning literature to provide ‘the most favourable’ landscape and plan layout in terms of minimal development costs. More recently, also general spatial shape objectives are included in the multi-objective functions devised. The research objectives in these studies however, are often restricted to a level of layout planning which is less detailed than the objective stated in this research. A direct consequence is that shape objectives are in general terms of compactness and solely defined at the land-use class level. Furthermore, the number of land-uses to be allocated and the site to be modelled is kept relatively small. These features are enough to provide a proof of principle, but not to deal with realistic planning challenges. Cellular automata and multi-agent systems provide robust frameworks to realistically model subject and object interactions in space and time. However, the non-deterministic behavior and outcomes of the model runs make them less suitable to generate plausible landscape configurations as defined in this research. Chapter 3 describes the (development of the) landscape generator, that is compatible with the regional plan scenario development approach identified in Simlandscape. The landscape generator uses landscape types as building blocks of plan scenarios. A landscape typology describes a proposed future spatial development and contains spatial and (non)spatial (descriptive) attributes. A 2D reference image indirectly provides objective compositional and configurational characteristics of the proposed development. In essence, users allocate a landscape typology to a cadastral lot typology and based on this information, the landscape generator produces a comprehensive landscape configuration. The landscape generator is developed as a multi-objective heuristic optimization modeling approach. In this approach a sequentially updated multi-objective function is optimized for a two-dimensional allocation site. It is assumed that the site is homogeneous in physical characteristics (e.g. height, soil etc.). The multi-objective function is compiled from an available library of single spatial attributes. These spatial attributes and their target values are retrieved from the compositional and configurational characteristics present in the reference image of the landscape typology. Examples from the available spatial attributes are the number of landscape component instances, the relative size of each component or each component instance, compactness and shape of component instances and direct adjacency between two different landscape components. In a hypothetical case study, the capabilities and behavior of the landscape generator are demonstrated. In the case study, the landscape generator generates a variety of landscape configurations for a hypothetical allocation site (20x20 cells) and a rural forest estate as allocated landscape typology. The reference image of the rural forest estate provides detailed information for the compilation of the multi-objective function. The landscape generator contains probabilistic elements (e.g. random starting situation, near-random cell swap), which results in different output, each time it is run with identical input settings. The landscape generator is capable of producing a range of landscape configurations for a variety of situations. A unique situation is defined by the allocation of one landscape typology to one allocation site. Theoretically, since the method is based on the objective measurement of spatial characteristics present in a reference image, each user-defined typology can be used for a selected allocation site. The landscape typologies cannot be allocated to every imaginable dimensioned allocation site, but are bounded by the spatial extent which specifies a valid spatial extent. At the heart of the method lies the compilation of the multi-objective function. Ideally, this compilation can be executed completely objectively and without user-interaction, as the reference image of the landscape typology provides the required information. In the current prototype version of the landscape generator, however, the compilation process is partly (and in advance) controlled by the modeler. The modeler needs to specify which of the available spatial attributes to include, in which sequence to optimize them and what attribute target values to specify. Surely, the modeler is informed by statistics calculated for the reference image. An important task is to define consistent guidelines for the compilation of the multi-objective function from each landscape typology, irrespective of the properties of a valid allocation site. In this research, the modeler has been able to define specific guidelines for each landscape typology. In the current state of the method, a continuous assessment, through iterative testing, needs to be made by the modeler, about which compilation is sufficient in producing plausible configurations and which compilation process produces solutions within reasonable computation times. In chapter 4, a method is presented to obtain insight in the usability of the landscape generator. The produced landscape configurations are extensively evaluated in an extensive internet-based validation experiment. For a broad variety of different situations, landscape configurations are generated by the landscape generator for realistically dimensioned and enclosed sites. The configurations are compared with professional hand-drawn configurations, by a large group of planning professionals. The subjects are provided an interactive, user-friendly web-based inquiry, in which they are requested to (graphically) rank order a random selection out of a total set of landscape configurations (hand-made or computer-generated), from ‘most to least plausible’. The population is not informed about the difference in production process of each landscape configuration. In the experiment a distinction is made between subjective and objective plausibility, representing design quality aspects and representativeness of the landscape typology respectively. Eight different situations (three subjective and five objective) are assessed by the group of respondents and analyzed with a modified version of an approved statistical method, known as ‘the law of comparative judgement’. In addition, to indicate points of interest for further improvements of the methodology, implicit and explicit dimensions of evaluation used by the respondents for each of the objective assessments are identified. The implicit dimensions are identified using linear regression analysis, with single spatial metric properties of the configurations as explanatory variables. To identify explicit dimensions of evaluation the respondents are asked for two of the earlier presented situations, to select five pre-defined used dimensions of evaluation. The current experiment setup provides a robust method as well as reliable results about the capability of the landscape generator to produce plausible landscape configurations. With its modern interactive web interface, its well-balanced data scheme (randomness, several situations) and the use of approved statistical methods, the experiment finds a balance between maximum effective information retrieval and an acceptable level of user workload. In chapter 5, the results of the validation experiment are presented and in chapter 6 these results are analyzed. For each of the three assignments of the design quality test, it is concluded that the whole set of computer-generated configurations is not of comparable design quality as the whole set of professional configurations. Several individual computer-generated landscape configurations have comparable design quality as the professional configurations. The landscape generator is able to produce configurations with landscape components which are with respect to its individual area, shape and relative adjacency plausible. The overall structure is, however, often perceived as near-random. In some situations this is regarded plausible, while in other situations it is regarded implausible. The results of the four analyzed assignments of the representativeness test show a more favorable view on the capabilities of the landscape generator. In half of the cases, the whole set of computer-generated configurations are considered comparable in representativeness to professional onfigurations. In the other half, several individual computer-generated are considered of comparable representativeness. The representativeness test is most important in plausibility validation of the landscape generator, as the primary objective of the research implies that each actor (with different levels of design experience) should be able to provide her development idea (described in the landscape typology) as a comprehensive visualization in an integrated plan scenario. In the initial planning phases of application of the landscape generator, it is more important to obtain a first impression of the impacts (visual and analytical) of a plan scenario than a completely well-modeled and calculated landscape design. Possible non-professional design choices in a landscape typology can be reflected in the generated landscape configurations. Analysis to dimensions of evaluation gives insight into possible explanations for the plausibility ordering of the subjects.A distinction is made between explicit and implicit dimensions of evaluation. Explicit dimensions are directly assembled in the experiment and provide perceived dimensions of evaluations. The implicit dimensions, identified with linear regression analysis are however uncertain in its reliability and ideally should be assembled in relation to explicit dimensions. Results of the linear regression analysis can direct future research with different approaches. First, the attribute target values in the current compilation can be re-specified. Second, non-used but available spatial attributes can be added to the multi-objective function. Third, new spatial attributes may be developed to be included in the optimization process. In light of the main objective in this research, it is important to define consistent guidelines for generating landscape typologies for different situations. In this research, a start is made to identify important choices with respect to the minimal selection of spatial attributes, the influence of its sequence and feasible attribute target value specification. The experiment results further provide detailed directions for improvements of the landscape generator. Other recommendations put forward in this research are related to: 1) the modification of the current heuristic approach (for performance improvement and local trapping avoidance purposes) by hybridization with existing heuristic approaches as simulated annealing and evolutionary algorithms, 2) full-automatic translation from the main characteristics of a landscape typology into the compilation of the multi-objective optimization function; this translation should be as generic as possible and the resulting configurations should be thoroughly validated for plausibility for a variety of possible representative situations (i.e. combination of proposed landscape typology with typical influential allocation site characteristics), 3) extending, if possible, the current library of available spatial attributes with functions that describe more overall organizational properties of landscape typologies or investigation of (parallel or sequential) optimization at different scale levels, 4) the inclusion or extension with representative infrastructure generation and 5) the increase in the effectiveness of the validation experiment by standardizing the acquisition of professional configurations (e.g. designing materials, formats and conditions and automation of conversion to images used in the inquiry) and 6) increase in the reliability of the validation experiment by separating the different parts of the experiment according prioritisation of experiment objectives.

Jatropha is emerging as an important biofuel crop throughout developing countries in the tropics. Initially lauded as an environmentally-benign ‘wonder crop’ suitable for arid wasteland cultivation that would avoid competition with scarce livelihood resources, it has recently begun to attract mounting criticisms related to competition with food production, biodiversity impacts, insecurity of land access by local populations, exploitative employment conditions, and disappointing effects on greenhouse gas emission reduction. In this paper we analyse the nature of the local developments that have given rise to these criticisms, and the underlying innovation processes and global forces that are driving the sector in the direction of these contested outcomes. We focus on Tanzania, an important forerunner in Jatropha biofuels production whose experiences have informed the international biofuel debate more broadly. Two surveys among biofuel actors in Tanzania held in 2005 and 2008/9 are the primary data sources. An extended innovation systems perspective is adopted, which is instrumental in studying patterns of global and local institutional embeddedness from a long-term perspective. These patterns are found to be key drivers behind the emergence and evolution of three distinct organizational models in the sector: local energy production and use for rural communities; decentralised subcontracting for centralised oil processors; and large centralised plantations. Socio-economic interactions in these models seem to be regulated by institutions put in place by colonial and early post-colonial governance of agri-commodity production and exchange. Each is also closely associated with different social (network) relations, organizational choices, economic viability, and environmental sustainability effects.

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed method

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed method