Eco-Design of Buildings and Infrastructure

Developments in the Period 2016–2020

Bruno Peuportier, Fabien Leurent, Jean Roger-Estrade, Bruno Peuportier, Fabien Leurent, Jean Roger-Estrade

• Publisher: CRC Press
• Year: 2020
• ISBN:
  9781000260847
• Edition: 1
• Topic: Technologie et ingénierie
• Subtopic: Ingénierie de la construction et de l'architecture

The Chair Eco-design of buildings and infrastructure, a partnership between three engineering colleges (MINES ParisTech, Ecole des Ponts ParisTech and AgroParisTech) and the VINCI group, aims to create measurement and simulation tools which integrate all the dimensions of eco-design (greenhouse gas emissions, impact on biodiversity and resource levies, etc.) to become real decision-making tools, based on a scientific approach, for all actors in the city (designers, builders and users).

This book reviews the second five-year sequence of the Chair, first presenting methodological advances in eco-design: life cycle assessment and quantification of uncertainties; local environmental impacts of transport and biodiversity. The interdisciplinary partnership, also associating the human sciences, shows its interest in taking into account the human factor in the modelling of urban systems. This modelling is based on several numerical simulation tools, presented in the third part. This theoretical set results in more substantial proposals for the renewal of techniques and systems, in terms of energy management strategies in buildings, urban agriculture, participatory data collection and digital transformation in transport.

This book is intended for urban planners, local authorities, building owners, architects, design offices, companies, building managers, teacher-researchers and anyone interested in the environmental quality of our living spaces.

Part 1

New Developments in the Methods for Eco-design

Chapter 1

Consequential Life Cycle Assessment Applied to Buildings

Charlotte Roux

Mines ParisTech, CES - PSL

1.1 Introduction

Today, new environmental assessment methods and approaches are being developed in connection with the central concept of the life cycle. They make it possible to improve the accuracy of the inventory by taking into account dynamic phenomena (DLCA, dynamic life cycle assessment) and economic sectors that are usually neglected (EIOLCA, environmental input–output-based LCA), and to extend the method to the economic field (LCC, life cycle cost) or the social sphere (SLCA, social life cycle assessment), etc. These new developments aim to fill the current gaps and limitations of LCAs (Finnveden et al. 2009, Guinée et al. 2010, Reap et al. 2008).

In parallel with these developments, LCA studies are generally classified into two large families in the scientific literature: the “attributional” approach (ALCA) and the “consequential” approach (CLCA), which serve to meet different objectives (Halvgaard et al.2012). The attributional approach seeks to allocate part of a responsibility to a given system, while the consequential approach seeks to model the environmental consequences of a decision (Finnveden et al. 2009). When using life cycle assessment in the design phase, the project is by definition not yet realised. The addition of a new district, or the rehabilitation action on an existing district, is therefore a decision and impacts the existing one, which corresponds to a consequential approach. This framework can be opposed to the normative framework of building certification, whereby the building evaluated is already completed.

For Suh and Yang (2014), there are no well-defined boundaries between ALCA and CLCA, but rather, LCA studies introduce complementary approaches (data or economic models, scenarios, land-use change, system dynamics, etc.) to improve the realism of the environmental analysis. They also stress that no “complete” CLCA exists since it is impossible to model all the consequences of a decision exhaustively.

It is therefore important to determine whether the objective of the study imposes a “consequential” point of view. Then, in practice, an “attributional” model can be seen as a first approximation of a consequential question. For example, according to some researchers, it is possible to rely on an attributional “base” to carry out a consequential study (Yang 2016).

The application of the “consequential” philosophy is a paradigm shift that displaces the focus of the study: it is not “the building/district” that is evaluated, but rather “the decision to build or renovate the building/district”. The implementation of this proposed new approach for the eco-design of buildings is based on the identification of marginal technologies and processes, and the expansion of the system, which integrates the substitution effects and the impacts avoided (see Table 1.1).

Table 1.1 Main Features of the Consequential Project Approach Compared to the Classic Attributional Approach

Modelling Hypotheses	Attributional	Consequential Project
Manufacture of materials/processes	Average technology(ies)	Marginal technology(ies)
Biogenic carbon	Neutral balance sheet	Differentiated balance sheet
Use of recycled materials – integrated benefit	Inventory method 100%	Consideration of market constraints: between 0% and 100%^a
Recycling/recovery at the end-of-life of materials – integrated benefit	Inventory method 0%	Consideration of market constraints: between 0% and 100%^b
Energy export/co-production	Co-product method: allocation of production infrastructure	Avoided burden method: substitution of marginal technologies
Database modelling system for the background	Cut-off	Allocation at the point of substitution (APOS)**

^a 50-50 by default.

^b This would currently require more transparency in database inventories.

The “consequential project” approach proposed here justifies neglecting the market effects (use of economic equilibrium models, rebound effects, elasticities, experience curve) generally associated with consequential studies, given the limited size of the project compared to the size of the national economic system. The analysis of market effects is more suited to the study of an economic sector than to the study of a project.

The introduction of new mechanisms (economic, techno-economic) by the consequential approach requires more information on the system studied and its environment, and information that can be obtained in part thanks to a dynamic LCA.¹

In particular, the issue of electricity and energy mix is complex and requires an additional modelling effort. On the one hand, more than two-thirds of electricity in France is consumed in buildings (SOeS 2016). On the other hand, electricity consumption can be one of the main contributors in the environmental assessment of buildings. It is then necessary to finely model this component of the system studied. The long lifespan of buildings also requires the introduction of a prospective approach. Finally, a reflection on the neighbourhood level must integrate the issues of transport and waste management.

The consequential project approach was applied to the development project of a new district, Cité Descartes.

The following sections of this chapter take up these different hypotheses, which were developed characterising the consequential project approach: electrical system modelling, transport and waste problems. Their impact on design aid is analysed through the example of Cité Descartes. The interest of a prospective approach is discussed in Chapter 12.

1 For a definition and a comprehensive conceptual framework of dynamic LCA, see Collinge et al. (2013).

1.2 Modelling the Electrical System

1.2.1 Model Overview

The study of the existing models of electrical system simulation has shown the need for the development of a new model, which is specifically created for the study of buildings and neighbourhoods. In particular, one of the main obstacles to the use of the existing models was the impossibility of ensuring consistency between the data repository used for the study of the electrical mix and that used for the study of buildings (weather, reference consumption, etc.).

The model presented here represents the current French situation (e.g. French meteorological data, installed capacities, plant characteristics) but can potentially be calibrated for other national contexts. It is an explicit model that allows a production mix to be associated at each hour of the year, according to a demand that depends significantly on the meteorological conditions. The model generates mixes that are consistent with the data used in building energy efficiency, independent of climatic or economic hazards inherent in real years (e.g. cold wave, heat wave, strikes, other hazards).

Three large submodels are considered (Figure 1.1):

Figure 1.1 Principle of simplified modelling of the electricity generation system.

• Electricity demand, the sum of national consumption, exports and consumption of pumping stations;
• Incidental productions, independent of electricity demand, but dependent on meteorological factors (e.g. wind) or unknown local economic variables (e.g. household waste incinerator);
• Modular production, which covers the residual demand once the incidental productions are subtracted.

Incidental productions, independent of the level of demand, are first entered in the model and subtracted from the national consumption. The demand to be met is then adjusted with border exchanges (addition of exports, subtraction of imports) and increased by consumption due to pumped energy transfer stations (PETS). Modular production units must then meet the residual demand according to their cost and technological constraints.

The model was calibrated on the actual years 2012 and 2013, then validated on 2014.² In a second stage, as well as when real weather data are used to construct typical meteorological data like TRYs (test reference years) (Lund 1985), a model is constructed for determining electricity production and its hourly variations in a “type” frame. For example, a representative demand for typical data used in dynamic thermal simulation (DTS) is used, as well as average historical availability of production units, average hydraulic productibility, etc.

This allows the model to be used for assisting building and neighbourhood design: consistency is ensured between the input data used (meteorological data in particular) and the average model of the incidents for actual years (availability of water resources for hydraulic production, decrease in availability due to a disruption at a nuclear power station, cold wave or heat wave …).

The final model gives an electrical production for each hour representative of the current functioning of the system with respect to a given request. It is po...