Figure 2.16 Meta Diagrams on Energy for a Proposed New Town

Figure 2.16 Meta Diagrams on Energy for a Proposed New Town

Source: Author elaboration (Sebastian Moffatt). Note: This series of energy meta diagrams was used to guide development plans for a proposed new town near Poona, India. The fi rst diagram represents a business-as-usual scenario. It shows how current development practice in southern India encourages greater use of coal-generated electricity. The second meta diagram portrays an advanced system with biomass brought by train and used in a local district energy plant, with the cascading of energy. The third meta diagram includes the transportation energy that was ignored by the designers and is missing from the other meta diagrams. Note that, because residents are expected to commute, transportation-related energy exceeds all other energy uses combined. The third meta diagram suggests that a reduction in the need for commuting and the provision of incentives for the creation of quality transit systems must be a priority in urban design in affl uent new towns.

particular use may be clearly subdivided into off -site potable water, on-site water (the roof catchment), and reclaimed water. Without this type of separation, it is impossible to understand a water consumption indicator. By standardizing the meta diagram format, one may directly compare results from diff erent locations or time periods and create comparable benchmarks for assessing system performance and trend lines. Comparable benchmarks also help in the important process of establishing long-term targets for resource use. For example, authorities in the resort municipality of Whistler, which represents one of Canada’s leading examples of sustainable planning, were unable to agree on long-term performance targets for a set of indicators until they benchmarked their current performance relative to other leading resorts in North America (fi gure 2.17).

Creation of meta diagrams if data are lacking

Creating meta diagrams is easy once the data are properly stored in a database or spreadsheet. In fact, simple software applications may be used to draw the diagrams automatically. The diffi culty arises in collecting baseline data to portray existing conditions or to construct a business-as-usual scenario. Two kinds of baseline information may be used (fi gure 2.18).

1. Top-down data establish how much of any given resource (energy, water, and material) was actually sold, delivered, or imported during the most recent period. If one is dealing with a greenfi eld development, then top-down data may be used from a neighboring site as a proxy for business as usual.

Once the inputs are known, the rest of the database may be constructed using population data and default values for demand by end-use category. For example, we might imagine a situation in which the population is 10,000 and the average person uses 200 liters per day of municipal water, divided into toilets (40 percent), showers (5 percent), surface washing (8 percent), and so on.

2. Bottom-up data aggregate the fl ows of any given resource by beginning with detailed fl ows generated at the scale of various types