Neighbourhood context and its contribution to urban health inequalities

The neighbourhood environment in which people live has gained increasing attention in epidemiological research. This dissertation investigated relationships between contextual neighbourhood factors and individual health with a focus on the built environment and its contribution to health inequalities on the neighbourhood level. Furthermore, this dissertation developed new approaches and applied new statistical methods to analyse environmental inequalities in an urban context with a particular focus on public green space and its distribution by socioeconomic neighbourhood characteristics. Firstly, in a systematic review multilevel studies which considered both neighbourhood socioeconomic position (SEP) and objectively measured factors of the built environment were assessed in order to disentangle their independent and interactive effects on individual health outcomes and health behaviours. Secondly, two multilevel analyses of cross-sectional data in the city of Munich investigated whether neighbourhood SEP, public playground and park space, and parentally perceived environmental exposures were independently associated with overweight in preschool aged children while simultaneously considering individual child and family factors. Thirdly, two ecological neighbourhood studies in the city of Dortmund and Munich were conducted to assess whether air and noise pollution and public green space were disproportionately distributed by the degree of neighbourhood deprivation. The systematic review identified a great heterogeneity of definitions applied and metrics being used for measuring built and socioeconomic neighbourhood variables. Mostly mixed results across multilevel studies on how built and socioeconomic neighbourhood environments were associated with health and health-related behaviours were found. Furthermore, the review identified several interactions between contextual neighbourhood factors and individual factors, mostly concerning sex or individual SEP. The two multilevel studies showed that in the case of childhood overweight individual factors, such as parental education or parental overweight, were the most important determinants. However, perceived and objective built environmental factors additionally explained overweight variance between neighbourhoods. The two ecological case studies found out that deprived neighbourhoods were more exposed to air pollution and low public green space availability than more affluent neighbourhoods. This dissertation recommends that apart from individual determinants policies and interventions targeting health promotion should consider the neighbourhood environment additionally. Moreover, a socioeconomic unequal distribution of environmental burdens and resources may result in amplifications of health inequalities within cities. There is a need for further studies considering multiple neighbourhood dimensions in order to analyse interactive and mediating pathways between contextual factors and individual health. The development of new approaches and methods for analysing and assessing environmental health inequalities will contribute to the reconnection of urban planning and public health

Developing a 3D City Digital Twin: Enhancing Walkability through a Green Pedestrian Network (GPN) in the City of Imola, Italy

Predominantly, dense historical cities face insufficient pedestrian-level greenery in the urban spaces. The lack of greenery impacts the human thermal comfort on the walking paths, which contributes to a considerable reduction in pedestrian flow rate. This study aims at developing a model to assess pedestrian-level thermal comfort in city environments and then evaluate the feasibility of creating a green pedestrian network (GPN). Imola, as a historical city in Italy with a compact urban pattern, is selected as the case study of this paper. To accomplish this, a three-dimensional digital twin at city scale is developed for the recognition of real-time shade patterns and for designing a GPN in this city. The 3D model of the proposed digital twin is developed in the Rhinoceros platform, and the physiological equivalence temperature (PET) is simulated through EnergyPlus, Honeybee, and Ladybug components in grasshopper. This study provides the city with a digital twin that is capable of examining pedestrian-level thermal comfort for designing a GPN based on real-time PET in the compact urban morphology of Imola. The PET model indicates that during the hottest hour of the 25th of June, pedestrians in open spaces can experience 3  C more than on narrow shaded streets. The results are validated based on in situ datasets that prove the reliability of the developed digital twin for the GPN. It provides urban planners and policy makers with a precise and useful methodology for simulating the effects of pedestrian-level urban greenery on human thermal comfort and also guarantees the functionality of policies in different urban settings

A novel framework for assessing multi-hazard risk and resilience in a changing world

The world’s changing climate and rapidly evolving societies are exacerbating the risk posed by natural hazards (such as earthquakes) to infrastructure and communities in general. The dynamic interdependencies of built, natural, and social systems and the potential hazard interactions amplified by climate change also add important challenges to evaluating built-naturalsocial system resilience. Yet, there is a lack of tools available in the literature for comprehensively assessing (and supporting related decision-making on) the performance of the built environment under multi-hazard conditions, considering climate change impacts and the cascading effects caused by system interdependencies. This paper aims to fill this gap by proposing a novel dynamic multi-hazard risk modelling framework to support decision-making under deep uncertainty, accounting for climate change effects in hazard interactions (including earthquakes), cascading consequences of system disruptions, and the multidimensional impacts of naturalhazard-related disasters. The paper describes the framework’s main modules and emphasises the key aspects to consider when implementing it in different contexts. Overall, the proposed framework advances the state-of-the-art in multi-hazard risk and resilience assessment and climate-aware decision-making to support the development of robust mitigation plans and policies under different climate and societal development scenarios

Mapping and modelling multifunctional landscapes

De maatschappij profiteert van een grote verscheidenheid van diensten die door het landschap geleverd worden. Deze zogenaamde ‘landschapsdiensten’ omvatten onder andere de productie van voedsel en hout, de levering van drinkwater, klimaatregulatie, landschapsbeleving en recreatiemogelijkheden. Landschapsdiensten zijn ongelijk verdeeld over het landschap, sommige plekken leveren meer of andere diensten dan andere plekken. Om het landschap zo goed mogelijk te gebruiken is het voor beleidsmakers belangrijk te weten waar en hoeveel landschapsdiensten geleverd worden. Het probleem is dat er op dit moment geen kaarten zijn die deze informatie voor volledige regio’s laten zien. Daarbij is ook de kennis beperkt over in hoeverre landschapsdiensten veranderen als hun omgeving verandert. Met name op multifunctionele locaties waar mensen het landschap veranderen om de levering van één specifieke landschapsdienst te versterken, spelen keuzes in landschapsmanagement een belangrijke rol, aangezien veranderingen in het landschap elke aanwezige landschapsdienst op een andere wijze zal beïnvloeden. Om deze twee problemen aan te pakken richt dit proefschrift zich op het ontwikkelen van methoden om de huidige en toekomstige staat van een aantal landschapsdiensten van Gelderse Vallei regio te kunnen kwantificeren en karteren. In proefschrift focussen we ons voornamelijk op methoden die ruimtelijke patronen en processen die deze ontwikkelingen in de tijd en ruimte kunnen beschrijven. De kaarten en het verbeterde begrip van landschapsdynamieken, die resulteren uit dit proefschrift, kunnen helpen om in de toekomst het ruimtelijk beleid voor multifunctionele gebieden beter te ontwerpen en te evalueren

Mapping and assessment of ecosystems and their services. Urban ecosystems

Action 5 of the EU Biodiversity Strategy to 2020 requires member states to Map and Assess the state of Ecosystems and their Services (MAES). This report provides guidance for mapping and assessment of urban ecosystems. The MAES urban pilot is a collaboration between the European Commission, the European Environment Agency, volunteering Member States and cities, and stakeholders. Its ultimate goal is to deliver a knowledge base for policy and management of urban ecosystems by analysing urban green infrastructure, condition of urban ecosystems and ecosystem services. This report presents guidance for mapping urban ecosystems and includes an indicator framework to assess the condition of urban ecosystems and urban ecosystem services. The scientific framework of mapping and assessment is designed to support in particular urban planning policy and policy on green infrastructure at urban, metropolitan and regional scales. The results are based on the following different sources of information: a literature survey of 54 scientific articles, an online-survey (on urban ecosystems, related policies and planning instruments and with participation of 42 cities), ten case studies (Portugal: Cascais, Oeiras, Lisbon; Italy: Padua, Trento, Rome; The Netherlands: Utrecht; Poland: Poznań; Spain: Barcelona; Norway: Oslo), and a two-day expert workshop. The case studies constituted the core of the MAES urban pilot. They provided real examples and applications of how mapping and assessment can be organized to support policy; on top, they provided the necessary expertise to select a set of final indicators for condition and ecosystem services. Urban ecosystems or cities are defined here as socio-ecological systems which are composed of green infrastructure and built infrastructure. Urban green infrastructure (GI) is understood in this report as the multi-functional network of urban green spaces situated within the boundary of the urban ecosystem. Urban green spaces are the structural components of urban GI. This study has shown that there is a large scope for urban ecosystem assessments. Firstly, urban policies increasingly use urban green infrastructure and nature-based solutions in their planning process. Secondly, an increasing amount of data at multiple spatial scales is becoming available to support these policies, to provide a baseline, and to compare or benchmark cities with respect to the extent and management of the urban ecosystem. Concrete examples are given on how to delineate urban ecosystems, how to choose an appropriate spatial scale, and how to map urban ecosystems based on a combination of national or European datasets (including Urban Atlas) and locally collected information (e.g., location of trees). Also examples of typologies for urban green spaces are presented. This report presents an indicator framework which is composed of indicators to assess for urban ecosystem condition and for urban ecosystem services. These are the result of a rigorous selection process and ensure consistent mapping and assessment across Europe. The MAES urban pilot will continue with work on the interface between research and policy. The framework presented in this report needs to be tested and validated across Europe, e.g. on its applicability at city scale, on how far the methodology for measuring ecosystem condition and ecosystem service delivery in urban areas can be used to assess urban green infrastructure and nature-based solutions

The ecomics of ecosystems and biodiversity: scoping the scale

The G8 decided in March 2007 to initiate a “Review on the economics of biodiversity loss”, in the so called Potsdam Initiative: 'In a global study we will initiate the process of analysing the global economic benefit of biological diversity, the costs of the loss of biodiversity and the failure to take protective measures versus the costs of effective conservation. The study is being supported by the European Commission (together with the European Environmental Agency and in cooperation with the German Government. “The objective of the current study is to provide a coherent overview of existing scientific knowledge upon which to base the economics of the Review, and to propose a coherent global programme of scientific work, both for Phase 2 (consolidation) and to enable more robust future iterations of the Review beyond 2010.

Stratifying and predicting patterns of neighbourhood change and gentrification ‐ an urban analytics approach

While recent debates have widely acknowledged gentrification’s varied manifestations, success in enumerating and disentangling the process and its defining features from other forms of neighbourhood change at-scale and across entire cities, has remained largely elusive. This paper addresses this gap and employs a novel, open and reproducible urban analytics approach to systematically examine the past and future trajectories of neighbourhood change using London, England, as a case-study example. Using suites of datasets relating to population, house prices and built environment development, the nature of gentrification’s mutations and its spatial patterns are extracted through a multi-stage data dimensionality reduction and classification methodology. Machine Learning is subsequently adopted to model gentrification’s observed trends and predict its future frontiers with interactive visualisation methods offering new insights into gentrification’s projected dynamics and geographies

Incorporating fine-scale environmental heterogeneity into broad-extent models

A key aim of ecology is to understand the drivers of ecological patterns, so that we can accurately predict the effects of global environmental change. However, in many cases, predictors are measured at a finer resolution than the ecological response. We therefore require data aggregation methods that avoid loss of information on fine-grain heterogeneity. We present a data aggregation method that, unlike current approaches, reduces the loss of information on fine-grain spatial structure in environmental heterogeneity for use with coarse-grain ecological datasets. Our method contains three steps: (a) define analysis scales (predictor grain, response grain, scale-of-effect); (b) use a moving window to calculate a measure of variability in environment (predictor grain) at the process-relevant scale (scale-of-effect); and (c) aggregate the moving window calculations to the coarsest resolution (response grain). We show the theoretical basis for our method using simulated landscapes and the practical utility with a case study. Our method is available as the grainchanger r package. The simulations show that information about spatial structure is captured that would have been lost using a direct aggregation approach, and that our method is particularly useful in landscapes with spatial autocorrelation in the environmental predictor variable (e.g. fragmented landscapes) and when the scale-of-effect is small relative to the response grain. We use our data aggregation method to find the appropriate scale-of-effect of land cover diversity on Eurasian jay Garrulus glandarius abundance in the UK. We then model the interactive effect of land cover heterogeneity and temperature on G. glandarius abundance. Our method enables us quantify this interaction despite the different scales at which these factors influence G. glandarius abundance. Our data aggregation method allows us to integrate variables that act at varying scales into one model with limited loss of information, which has wide applicability for spatial analyses beyond the specific ecological context considered here. Key ecological applications include being able to estimate the interactive effect of drivers that vary at different scales (such as climate and land cover), and to systematically examine the scale dependence of the effects of environmental heterogeneity in combination with the effects of climate change on biodiversity