International attention on issues related to the environmental impact of cities, both in research and in the media, is directed towards reducing building energy use and optimizing human mobility. On one hand, data regarding mobility is increasingly available due to the use of mobile phone data and smart grid technology. Using the resource of Big Data, the complex network theory models, predicts, and optimizes human mobility. On the other hand, the data available on the energy and environmental impact of a building is less, as it can be a random, building by building analysis derived from privately owned software, or can originate from a statistical-engineering evaluation method. The real-real time data of building energy use is very difficult to obtain from private companies. Traditionally only energy analysis (First Law of Thermodynamic) is used in the design of buildings and urban systems: its efficiency is associated to a smaller environmental footprint, green construction, sustainability, the use of renewable resources, etc.. The Second Law of Thermodynamics is always used in the thermodynamic system analysis (industrial ecology, ecological and energy economics, engineering design process, etc.) because as energy is used, its quality deteriorates and becomes less useful. The model developed in this thesis integrates both of these requirements, and both the First and Second Law analysis, energy use and energy consume. Modelling a black box approach, it uses with flexibility the available data of energy and material utilization in an urban space, and immediately and comprehensively defines the environmental impact of energy use. The results show that while the quality of energy necessary in an urban system is low, energy of high quality is used resulting in significant deterioration (exergy consumption). The results claim that the urban system is a destroyer of quality of energy: reducing the share of input vectors is a necessity to reduce the environmental impact. The numerical results of the model can be useful to compare different retrofitting energy efficiency scenarios.
Therefore with the increasing emergence of data analysis at large scale, together with the increased need to rationalize the energy use, an efficient way to reduce the deterioration of environmental resources becomes both more necessary and possible. The model is useful for using the information system of city in order to manage and optimize the energy use of an urban system.
624 Civil engineering 006 Special computer methods