Research On Low - Carbon Eco - City Industry Planning From The Perspective Of Self - Organization Theory

The urban system is a complex, open and giant system with self-organizing characteristics. As a subsystem of the urban system, industrial system is also a self-organizing system. Based on self-organizing theories, this dissertation aims to study underlying self-organizing mechanism of the industrial system and apply the results to industrial planning.Recently, low-carbon eco-city has become one of the hot spots in urban planning and construction. Especially, as more and more eco-cities have been built, the methodologies of urban planning and construction low-carbon eco-city have been well established, which include mix-land use, transit oriented development(TOD), green building and so on. However, because of an incomplete and inaccurate industrial plan, as well as a lack of economic development, low-carbon eco cities have little attraction for people or firms to move in,urban infrastructures have a low utilization. Different from the traditional industrial planning, this dissertation provides innovative industrial analysis methods and industrial planning of low-carbon eco-city based on self-organizing theories combined with economy and urban planning, from the sustainable development’s point of view.The dissertation, firstly, comparing characteristics of self-organization with hetero organization for analysis of low-carbon eco-cities in China and abroad about urban construction, summed up the sustainable developing way and methods for low-carbon eco-city from the perspective of self-organizing theory. Secondly, this paper uses methodology of time series, which belongs to self-organizing theory, to modeling low carbon and ecological target analysis, and constructs composite target model of green index model, which are analyzed in view of certainty and uncertainty from the perspective of self-organization. Finally, based on synergetic theory of self-organization, the dissertation points out that industrial development should coordinates with development of urban economy, environment, ecology and society, which is the industrial developing way to achieve the goal of sustainable development.Combined with methodologies to construct low-carbon eco- city, this dissertation synthesizes multidisciplinary results from complexity science, system science, ecology, economy, urban planning. Low-carbon eco-city’s goals are decomposed into three targets including low-carbon target, ecological target and economic target. At first, to analyze the low-carbon target, economic, social and environmental data from 35 major cities of China are chosen. Four factors including carbon emission factor, economic factor, environment factor and social factor are concluded to be the key factors in meeting the low-carbon target. Furthermore, in order to achieve the aim of ecology in low-carbon eco-city, data from112 cities of China are acquired and analyzed, and key factors have been obtained, which have high impacts on the sustainable development, especially on urban ecological development. Additionally, Based on conclusions of low-carbon target and eco target, Green target index is defined as a comprehensive index to evaluate low-carbon eco-city, which has been analyzed in factor analysis and correlation analysis between the nine factors of low– carbon and ecological goals. It is concluded that three factors influence the green target index, which are strong correlation. In other words, the three variables can well explain the green target index. At last, the green index model is built up, which deals with the issue that cities’ industrial development could be compatible with society and environment.In the next, there is industry analysis. Firstly, applying the green index calculation model, the time series data of the green target indexes is estimate with the statistics of three independent variables from Tianjin Bandai New Area. Secondly, Tianjin Banhai New Area of statistical data is selected to do correlation analysis with Green target index on two levels of industry analysis. On the first level, the correlation coefficient index between green target index and the first, second, third industry is generated by regression analysis of data from the index of green target and the first, second, third industry of the Binhai New Area. On the second level, the more detailed industrial time series data is used to do correlation analysis with green target index that includes seven industrial departments, agriculture, industry, construction, transportation, warehousing and postal service, wholesale and retail and hotel catering industry, finance, real estate industry. Having been carried on the analysis, correlation coefficient index between green index and the subdivision industry is calculated. Based on the quantitative model and the analysis of the industry, the results would be helpful for low-carbon ecological industrial planning.With data and model analyzing results, the dissertation gives developing ways of industrial economy setting targets for improving environment, which concretely includes low-carbon and eco objective function. That industrial developing way is following principles of self-organization to realize that economic growth is compatible with improving environment. At last, dissertation states and analyzes position and role of industrial planning of low-carbon eco-city in urban planning system, and concludes the methods of industrial analysis and planning in low-carbon eco-cities’ urban planning system, especially in urban system plan, urban master plan and urban detailed plan.