|The BRIDGE approach|
One of the best approaches to evaluate the environmental dimension of a city’s sustainability consists in analysing the city as an organism, characterizing its metabolism. Urban metabolism considers a city as a system and distinguishes between energy and material flows. “Meta-bolic” studies are usually top-down approaches that assess the inputs and outputs of food, water, energy, etc. from a city (Ngo and Pataki 20081), or that compare the metabolic process of several cities (Kennedy et al. 20072). In contrast, bottom-up approaches are based on quantitative estimates of urban metabolism components at local scale, considering the urban metabolism as the 3D exchange and transformation of energy and matter between a city and its environment. Recent advances in bio-physical sciences have led to new methods to estimate energy, water, carbon and pollutants fluxes. However, there is poor communication of new knowledge to end-users, such as planners, architects and engineers.
The European Thematic Strategy on the urban environment is based on the principles of sustainable urban development, such as decentralised concentration (polycentric structure) and a balanced mix of different land uses (residential, working, shopping, leisure, etc.) in a compact structure implying short distances. The utilization and flow of material resources (solid, liquid and gaseous) underpins economic and social development, but the ways in which they are used can create waste, emissions, effluents and resource shortages. One of the biggest challenges to sustainable development in Europe is a more responsible management of natural resources. Breaking the link between the economic growth, and the use of resources has been determined as a headline objective.
Multidisciplinary research will address urban metabolism and resource optimisation in the urban fabric. Recent advances in bio-physical sciences have led to new methods and models to estimate local scale energy, water, carbon and pollutants fluxes. Energy, water and carbon fluxes in urban areas are investigated in contemporary studies by three main approaches of science: micrometeorological site studies, remote sensing measurements and numerical modelling approaches. The energy and water fluxes are measured and modelled in order to define the spatio-temporal distribution of the energy and water balance at local scale (Offerle et al. 20063, Masson 20064, Mitchell et al. 20075). The fluxes of carbon and pollutants are modelled and their spatio-temporal distributions are estimated (Borrego et al. 20066). The uptake by trees and onward transport or storage of various pollutants in the urban environment are measured by a range of techniques (Freer-Smith and Taylor 20017). These fluxes are simulated in a three dimensional context and also dynamically by using state-of-the-art numerical models, which normally simulate the complexity of the urban dynamical process exploiting the power and capabilities of modern computer platforms (San Jose et al. 20088).
The BRIDGE DSS integrates the data and the models’ outputs that lead to indicators which define the state of the urban environment. A Multi-criteria Decision Making approach based on cost-benefit analysis has been adopted to cope with the complexity of urban metabolism issues and objectives which measure the intensity of the interactions among the different elements in the system and its environment.
The end-users decide on the objectives that correspond to their needs and determine objectives’ relative importance (weighting). The objectives’ weights reflect the central priorities of the project. Once the objectives have been determined, a set of associated criteria is developed to link the objectives with the indicators. BRIDGE integrates key environmental and socio-economic considerations into urban planning through Strategic Environmental Assessment (Donnelly et al. 20069).
Five European cities have been selected as BRIDGE case studies: a high latitude with rapid urbanization city that requires a substantial amount of energy for heating (Helsinki, Finland); a low latitude Mediterranean city that requires a substantial amount of energy for cooling (Athens, Greece); a representative European megacity (London, United Kingdom); a representative European old city with substantial cultural heritage (Firenze, Italy) and a representative Eastern European city with dynamic planning process reflecting the economical, social, and political changes held within last two decades (Gliwice, Poland).
There is if often poor communication of new knowledge and its implications to end-users, such as planners, architects, engineers and local stakeholders. The BRIDGE project uses Communities of Practice (CoP) as an approach to organize the interaction between end-users and urban research scientists by creating a learning environment in the field of city planning. CoPs have been organized in each of the five case study cities and the intension is to create an “umbrella” CoP across the participating cities to exchange ideas and experience of the BRIDGE products on a European level.
The end-users are:
· The Helsinki City Planning Office (Finnish case study).
· Prefecture of Athens (Greek case study).
· The Greater London Authority (UK case study).
· The Direzione Urbanistica, Comune di Firenze (Italian case study).
· The Department of Architecture and Town-planning of Gliwice (Polish case study).
1 Ngo, N. S. and Pataki, D. E., 2008: The energy and mass balance of Los Angeles County. Urban Ecosyst, 11, 21–139.
2 Kennedy C., Cuddihy J., Engel-Yan J., 2007: The Changing Metabolism of Cities. J. Industrial Ecology, 22, 43-59.
3 Offerle B., Grimmond, C. S. B., Fortuniak, K. and Pawlak, W. (2006): Intra-urban differences of surface energy fluxes in a central European city. J. Appl. Meteorol., 45: 125 - 136.
4 Masson, V. (2006): Urban surface modelling and the meso-scale impact of cities. Theor. Appl. Climatol, 84: 35 - 45.
5 Mitchell, V. G., Cleugh, H. A., Grimmond, C. S. B. and Xu, J. (2007): Linking urban water balance and energy balance models to analyse urban design options. Hydrol. Process., DOI: 10.1002/hyp.6868.
6 Borrego, C., Martins, H., Tchepel, O., Salmim, L., Monteiro, A. and Miranda, A.I. (2006): How urban structure can affect city sustainability from an air quality perspective. Environ. Modell. Softw., 21, 461 - 467.
7 Freer-Smith, P. H. and Taylor, G. (2001): Trees as Environmental Sinks. “Trees 2000 – Challenges for the Future” DETR Research for Amenity Trees Series).
8 San Jose, R., Perez, J.L., Morant, J.L. and Gonzalez, R.M. (2008): CFD and Mesoscale Air Quality Modelling Integration: Web Application for Las Palmas (Canary Islands, Spain). In: Air Pollution Modeling and Its Application XIX, Springer Netherlands: 37-45.
9 Donnelly, A., Jones, M., O’Mahony, T. and Byrne, G. (2006): Decision-support Framework for Establishing Objectives, Targets and Indicators for Use in Strategic Environmental Assessment. Impact Assessment and Project Appraisal, 24: 151- 157.