Aid to eco-design of neighbourhoods using life cycle assessment
Environmental awareness of local communities has led to develop sustainable urban <br />projects, but without any precise definition of such concepts. Yet the importance of risks, <br />from local to planetary levels, suggests a more rigorous management of these issues. In this context, life cycle assessment (LCA) constitutes a methodological input to help decision makers reducing environmental impacts of projects using an appropriate design approach This project aims at improving existing tools, and taking advantage of these tools to better cope with users needs. Particularly, plus energy neighbourhood concepts are studied considering their implications in terms of urban morphologies, transport and energy networks. Intermittent electricity production and consumption have to be accounted for because of the temporal variation of production techniques and of the related environmental impacts. Energy contributes to a large extent in several effects like climate change, exhaust of natural resources, impacts on human health and biodiversity. But the project also concerns aspects related to water consumption, land use, materials fabrication, end of life treatment and possible recycling.
Some pioneer sustainable neighbourhood projects have been analysed in order to review the questions raised by decision makers, identify the problems that LCA may contribute to solve, the parameters to be accounted for, and the relevant system boundaries according to the objectives of the LCA study. A model has then been elaborated, including buildings, public spaces (streets, green spaces…) and networks (water mains, district heating…). Temporal variation of electricity production and consumption mixes has been integrated.
Data has been collected regarding environmental impacts related to the most common
materials and processes involved in an urban settlement.
In order to study plus energy projects, the energy demand and production is evaluated
hourly using dynamic simulation. The results are transmitted to the building LCA tool. LCA results at building level are then imported by the neighbourhood level tool. Environmental indicators are calculated, constituting a multi-criteria expression of environmental performance. Indicators are normalized on a single scale (equivalent inhabitants) in order to facilitate interpretation. Several alternatives can then be compared, constituting a help in decision making.
Bundled software has been developed and some tools are already distributed by a software
editor. These tools have been applied experimentally in some case studies, for instance to
evaluate concepts corresponding to best practice (quartier Vauban in Freiburg, Germany). A project regarding Cité Descartes (East of Paris) has then been studied.
In this example, appropriate choices of urban morphology and technologies allow the
environmental performance to reach a best practice level. These first case studies show the
feasibility of applying LCA as an aid to eco-design of neighbourhoods.
ACV Quartiers (Neighbourhood LCA) is an industrial research project coordinated by
ARMINES. The other partners are VINCI Construction France, IZUBA Energies and ACT Consultants. The project began in January 2009 and lasted 36 months. The ANR grant has been 377,757 € for a total budget of around 687,000 €.
Four communications in international conferences and an article in a peer reviewed journal have been written on the basis of the developments performed in this project. The
neighbourhood model has been presented during the Sustainable Building Confe
ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS (ARMINES) (Laboratoire public)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS (ARMINES)
Help of the ANR 377,758 euros
Beginning and duration of the scientific project: - 36 Months