Conference Agenda

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Session Overview
Monday, 04/July/2022:
11:30am - 1:00pm

Session Chair: Maria BALOUKTSI
Location: Hall A

Tools for urban development

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11:30am - 11:45am

Proof Of Concept - Using Prospective Hybrid MFA-LCA To Evaluate The Environmental Implications Of Circular Economy Using A Case Study Of Wood

Nikolaos EMMANOUIL1, Sarah Cecilie ANDERSEN1,2, Morten BIRKVED1

1The University of Southern Denmark, SDU Life Cycle Engineering, Department of Green Technology (IGT), Campusvej 55, DK-5230 Odense M, Denmark; 2Danish Technological Institute, Buildings & Environment, Gregersensvej, DK-2630 Taastrup, Denmark

Consistent evaluations of impacts induced by implementation of Circular Economy (CE) design processes and solutions within the built environment, necessitates decision-support tool development/advancement, as CE does not allow for business-as-usual assessments only. A preliminary test of concept that seeks to quantify the environmental implications of CE on a case study of wood, is presented here,

The core methodology is based on coupling of the Shared Socioeconomic Pathways (SSPs) with Material Flow Analysis (MFA) and consequential Life Cycle Assessment (cLCA). Applying this novel approach, a prospective consequential hybrid MFA-LCA analysis was initiated, to evaluate the mitigation challenges of CE design processes, through different formalized and generally accepted (i.e. consensus) scenarios.

The case study is Danish reference buildings, meeting the current building regulations, designed to replace conventional building materials with wood. This ‘wood-approach’ for test of concept case study, is chosen due to the increasing interest in wood construction.

The development and calibration of a prospective model for different building material consumptions will further illuminate the connection between the to-be generated emissions and the marginal productions of the materials in question, under specific sets of societal development scenarios.

11:45am - 12:00pm

Digitalising Cities: A Methodology To Map Evaluation Requirements Into Robust And Feasible Data Collection Approaches


1CARTIF, Spain; 2Cerema, France; 3VTT, Finland

The sustainable development of cities relies on the implementation of multi-sectoral actions towards carbon neutrality, reducing the air pollutants emissions. The actions’ decision-making process for cities transformation should be supported by lessons learnt from previous interventions and KPIs (Key Performance Indicators). To do so, gathering real data becomes pivotal, complementing simulation tools (currently used), solving the inherent uncertainties due to assumptions. Data collection methodologies are then necessary, being the main driver for digital cities and providing better mechanisms for informed decision-making. Most of the cities still operate in silos and do not always implement the strategic plans supported with a digitalization of the municipal processes. Within this perspective, this paper presents a methodology to support cities in the preparation of monitoring programmes to collect real data in a robust and feasible manner. Taking the KPIs and the Smart Cities urban strategies into account, this paper concludes with some lessons learnt within cities to deploy monitoring approaches. From the city challenges to the review of the plans, all the process is driven by real data and KPIs. The methodology has been applied in the mySMARTLife project (Grant Agreement #731297) and deployed into the cities of Nantes (France), Hamburg (Germany) and Helsinki (Finland).

12:00pm - 12:15pm

A Theoretical Assessment Of Transport Emissions from Institutional Buildings in Norwegian Municipality

Oskar Fredrik FAHLSTEDT, Rolf André BOHNE

Norwegian University of Science and Technology,

Municipalities are key actors for reaching the sustainable development goals 9, 11, 12, 13 set by the United Nations. This paper aims to develop a theoretical framework that will aid municipalities in managing their building stock more sustainability. The framework focuses on reducing embodied and operational emissions, including travel-induced emissions. The focal point in this paper is institutional buildings governed by a Norwegian municipality as they are the daily destination for many inhabitants. An existing framework in the municipality value the building stock based on quality and the cost of refurbishing them. No framework is currently including travel-induced emissions in the evaluation.

The intention is to provide a holistic framework that includes this aspect when deciding if a building should be refurbished or demolished. The omission of transport emissions can lead to truncation errors in assessments. The transport to and from the school generates higher emissions in certain scenarios. Based on the knowledge in the assessment a theoretical framework that assesses this is developed.

12:15pm - 12:30pm

Holistic Assessment Methodology For Positive Energy Districts


Czech Techical University in Prague, Faculty of Civil Engineering, Czech Republic

Globally, cities are responsible for most of the world's energy consumption and most of the carbon dioxide emissions. Therefore, the efficient transformation of urban energy systems is becoming a crucial step towards carbon neutrality and more effective climate protection. The Positive Energy District (PED) concept has been pointed out as one of the key principles of this path. The Positive Energy District concept leads towards an integrated and sustainable urban development with an emphasis on the use of renewable energy sources and attention shifting from energy performance at the level of individual buildings to the level of the entire district. However, PEDs represent a relatively new and still not sufficiently explored area in the field of sustainable development.

The aim of this paper is to describe a new holistic assessment and innovative process of stakeholder engagement to identify Positive Energy Districts in the early development phase that arises within the PED-ID project. The early development phase is crucial since the structure of the urban area is being decided along with its sustainability and climate protection levels.

The assessment methodology is based on the creation and optimization of energy balance scenarios.

Case studies of existing urban areas have been developed in order to verify the methodology.

It is concluded that this innovative methodology devised for PED evaluation, together with strengthening of knowledge‐based and decision-making framework, will help to accelerate the process of transforming the current urban energy systems into more efficient and renewable systems.

12:30pm - 12:45pm

Exploring Machine Learning-based Archetypes For Urban Life Cycle Modeling (UBiM)

Giseli Mary COLLETO, Vanessa GOMES

University of Campinas, School of Civil Engineering, Architecture and Urbanism, Brazil

Urban analyses demand simplifications that balance modelling level of detail and scope broadness. Thus, classification by archetypes is a promising methodological approach. Such an approach is common for energy studies but rarely applied for Life Cycle Assessment (LCA) purposes. When archetypes are used in urban LCA, they generally result from previous studies for classification and characterization according to parameters that directly affect the operational energy performance of buildings. This paper tackles two research questions: i) Is it appropriate to aggregate building stocks based on operational energy (OE) variables when life cycle impacts are investigated? ii) When integrated LCA (OE + embodied impacts) is pursued, would variables describing both interests simultaneously result in better representation than using operational energy-based clustering to predict embodied impacts and vice versa? Thus, we aim to confirm that, combining variables that govern OE and embodied impacts offers a better result than using OE to predict materials groupings, even if some adherence is lost relatively to single-objective clustering. Clustering experiments were carried out for the campus of the University of Campinas, Brazil. After unsupervised k-medoid (PAM) grouping, the data were submitted to a supervised learning (neural networks) classification method. Generated confusion matrices demonstrate how adherent the clustering is when considering one interest to predict the other in three situations. Results indicate that an operational energy-driven archetype fails to represent buildings from the embodied impacts viewpoint, and that merging operational energy and embodied impact variables would better support integrated life cycle impact predictions.

12:45pm - 12:52pm

Supporting sustainable policies through Urban Energy Environmental Model and Multi Criteria Analysis: a case study in an Italian province


ITC-CNR, Italy

Public Authorities (PAs) need to define cross-cutting strategies for urban planning including policies for sustainable and energy-efficient buildings and innovative urban solutions. The article presents a decision support tool that combines an Urban Energy Environmental Model (UEEM) and a Multi-Criteria Analysis (MCA) to support the development of sustainable local policies. The UEEM, developed with a bottom-up approach incorporating energy and environmental items, provides a representation of the performance of local urban areas and quantifies the impact of new interventions in expansion areas. The UEEM is based on the definition of virtual archetypes built on the characteristics of the area under consideration. 92 building archetypes and 40 urban archetypes are developed. The energy performance of each building archetype is calculated with a dynamic simulation tool. The environmental performance of urban areas (overheating risk and outdoor thermal comfort) is analysed through a Grasshopper-based parametric model. In addition, soil permeability is calculated. The UEEM results are aggregated into a single index using the MCA, providing a Municipal Rating Index (MRI). The weights of the MCA are estimated through the Analytical Hierarchy Process (AHP) based on a survey submitted to local stakeholders (municipalities, environmental associations, experts). The model is applied to the province of Monza and Brianza in northern Italy.

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