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By zoning geared to strategic planning for facilities and public services pro- the city into smaller subdivisions based on type of activity, de- visions, cohort-component methods are acceptable and reliable, mographics and economic drivers, the modeling structure can be since they allow grouping of the population based on characteris- underpinned by several levels of resolution, demanding a certain tics that impact the resources use intensity, without addition of type of method assigned at different scales.

In discrete zone unnecessary details. The movement tion of a population. How the population is distributed into of phenomena within any of these zones or regions, or the spatial households and how those households can be grouped based on interactions between collections of regions are modeled.

This re- size and age composition can become important as well. Economic factors 4. Demographic factors The environmental impact of a set of economic variables e. IUMAT's approach to simulation in larger scales implicitly forces income, employment, energy pricing, and taxing regulations is a collecting and collating statistical information on population dy- key part of the IUMAT framework. The U. Census Bureau keeps track of alterations in economic variables are modeled.

Overall processes of census count and publishes a public report every decade that economic transformation, patterns of growth or decline in regional summarizes demographic data at both state, county and town economy, or if the economy is export or import oriented are beyond levels. These reports are helpful in understanding urban population the scope of this framework. Both demographic e.

Urban Metabolism, Prof Herbert Giradet, Co-Founder, World Future Council on Urban Metabolism

To illustrate, the buying use [30]. Moreover, the aggre- [31]. Sustainable land use planning is predicated on minimizing gated income of families directly impacts household energy con- transformation of green-sites into brown-sites with simultaneous sumption. Replacing represented as functions of household level of wealth, gross in- permeable land with impervious surfaces increases the risk of come, or perceived economic security. Intense use of air conditioning units and dark paving IUMAT simulates economic indicators related to energy con- materials trigger the heat island effect in urban areas [34].

New sumption and environmental conservation. Contamination of soil or groundwater may occur if toxic mental impacts. Variables such as population size, average age, materials permeate. GIS land use mapping uses discrete zones The economic theory applied to a region depends on scale of the versus continuous space representation that treat borders of study and size of the economy being analyzed as well as availability properties as geographic boundaries between zones.

Discrete of data at various geographic levels. Determining the economic conceptualization of the space enables mathematical formulation borders of the study needs to be carried out coherently to enable and use of computational techniques. Using GIS features for import services and goods exogenously or endogenously from local Use type indicator businesses [28]. Input-output analysis is another economic ac- planar conceptualization of space allocation of activities in build- counting analysis method to investigate inter-industry transactions ings and other spatial units enables appending non-spatial data to [29].

The accurate mapping of land use location is goods and services within the industrial and producer division of necessary for the integration of transportation and resource con- the economy. Analyses based on households or industrial trans- sumption patterns. In forms the unit structure of urban economy. And, certain types of land use necessitate alterations to the existing For modeling objectives, a different system is required.

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Changes land cover. Changes to land use and cover are also governed and in land cover may occur naturally due to climate conditions as well limited by rules and regulations enacted by public or private as human induced alterations. Anderson et al. Since multiple elements that shape the way a parcel of land is used. Every TAZ is assigned a centroid that is an from new construction or change of use projects, this system optimal distance from buildings.

The path taken from the centroid of a zone origin cultural, rangeland, forest land, water, wetland, barren land, tundra, to one's destination is called a trip. After 7. Urban trans- growth and alternative types of human activity. The most common portation planning is aimed at creating the most viable alternative travel demand modeling process, commonly known as Four Step systems of transportation based on the type and volume of activity Travel Demand prediction incorporates four separate key parts and compactness of settlement.

The transportation simulation [42]. Trip distribution in which mental consequences of change in land use, and characterizes the generated trips are distributed between the TAZs, mode choice mobility within the urban region. In this framework based on the land and privacy [41].

The TAZs are buildings grouped as before assigning them to the TAZ centroids compared to conven- neighborhoods with relatively uniform distribution of activity tional transportation modeling software. Within every building, Fig. At the characterizing the trips as home based work, home base non-work scale of the zone, parameters such as density of development and or any other type. However, it distribution of land use type are effective as they specify overall has advantages over conventional transportation modeling struc- characteristics of the zones. Trip distribution is carried out using tures that may assume transportation demand is only generated at the well-known gravity model based on number of produced and residential TAZs.

IUMAT accounts for commercial and industrial attracted travels and impeding factors between the zones such as transportation as well as public transportation.

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The demand for public transportation produced by residents where Tij is the number of trips generated at zone i and destined at of individual buildings is estimated by modeling the public trans- zone j; Pi is total number of trips generated at zone i; Aj is the total portation schedules of different modes. Route 8. Energy, water and materials choice modeling focuses on using a minimum time route algorithm.

In this method trips that cross the boundary of the study area are Creating environmentally sound policies requires the ability to ignored.


Dynamics of Urban Metabolism

These four steps are not necessarily followed in a analyze and project impacts and implications of different growth sequential chain. For instance, availability of transportation modes and development scenarios. Detailed information on buildings and The travel demand produced by buildings is assigned to a TAZ neighborhood characteristics extend the accuracy of the model to centroid, and the origin-destination matrices show the number of higher levels.

Initial examination of cover. Generic EWM templates based on loads, gross area, window- the data and the interpretation of the expected patterns provide to-wall ratio, year of construction, activity types etc. In addition, a complete understanding of the physical use and year of construction.

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For example, having a constant Depending on the technology used for energy generation, number of residents, energy and water usage of the household different amounts of water may be consumed. Supplying the should increase with the living space area. But this increase is required water is itself associated with energy use. Dividing a household of four into two portation, energy, water, materials using calculative algorithms. To collect primary template energy data, end use energy use versus living area which is likely to follow a power consumption surveys provided by the U. Coordinators that are responsible for data distribution between measurements and process unmeasurable randomness in the the modules.

The prob- connector, metabolism modules, and data exporter. Raw data and ability distribution can be regarded as a mechanism for data gen- user inputs are introduced at the input entry, while topography, eration in simulation cases that generates data points in a random land use and socio-economic elements are spatially compiled and fashion that are expected to occur in real case examples.

Selected Publications

Since the disaggregated. The data generator takes advantage of compiled desired outcome of simulation processes by IUMAT is basically data to generate large samples. This for describing the stochastic component of the models. With respect to local reg- ulations and policies, users are able to actively manage modeling 9.

Urban metabolism: Measuring the city's contribution to sustainable development.

Based on statistical results, this Module also provides suggestions for calibration of the a. The Result Aggregator Module compiles and through setting, translating, coding, and exporting data. Spatial storage unit that holds the Spatial Compiled simulation Finally, user is able to create different comparative maps or spatial results.

This unit keeps record of socio-economic attributes as well. Modules that are the main simulation engines for capturing the Exporter and Visualizer Tool. For some time now we have been offered up a seemingly endless series of positivist images of the urban future, whether we find their origins from large international architecture and engineering consulting firms or from the fevered speculation of tenure track professors picking up the sci-fi wave of high-tech green as new paradigm, or alibi. The overwhelming tone of these images is their generic quality, their strong similarity to one another whether it be future Singapore or New York City, Hamburg, Masdar, or numerous eco-cities proposed and labeled around the world.

A picture is worth a thousand words, but the imagery of green cities is the same generic thousand-word message over and over again. Consider that today one would not think of sustainable, resource-efficient buildings in a generic sense. Anyone associated with efforts to move toward net zero energy and serious materials reuse and recycling understands the significant differences between buildings that accommodate vastly different types of human activities.

In fact, today we know that it is extremely important to distinguish between the many types of buildings and their accompanying energy and material requirements; laboratories, hospitals, retail malls, warehouses, car garages, and the like, when considering design, technology and other strategies for a sustainable built environment.

Caption: Singapore and Mumbai. When considering urban sustainability is it reasonable to think that Singapore and Mumbai can be considered in the same, or even in a remotely similar way? These thoughts spawned the motivation behind research to uncover useful differences among many thousands of cities; a search for distinctions and possible classifications that forms the core of this article. Closely associated with the motivation to discover species and subspecies of urban resource consumption among the range of agglomeration economies is the idea that city types as they exist today may be telling us more about the evolution of cities than we currently appreciate.

Caption: Two graphic representations of city resource consumption types showing an energy-intensive city on the left and a material-intensive city on the right Bio, biomass; FF, fossil fuels; TE, total energy; EL, electricity; CO2, carbon dioxide emissions; Ind, industrial minerals; TM, total materials; Con, construction minerals. The Urban Metabolism Group at MIT has analyzed hundreds of cities for the purpose of deriving the above-mentioned city typology. This typology is based on urban resource consumption UNEP Caption: City typology using the graphing technique explained in Figure 2.

Starting at the upper left-hand corner and moving to the right in Figure 3, then proceeding to the next row, each city type is briefly described and a few representative cities are listed. Type 3, a combination of low and medium resource intensity; low consumption of total energy, electricity, fossil fuels, and industrial minerals. Emission of carbon dioxide is also low; cities in South America, Asia, and Africa. Type 4 shows total energy, fossil fuel, and electricity consumption are low as is carbon dioxide emissions.