THÔNG TIN TÀI LIỆU
Carbon Footprint of Vietnam’s Small Urban Areas (A Case Study of Ha Dong District, Hanoi) Nguyen An Thinh(1)* (1) VNU University of Economics and Business, Vietnam National University, Hanoi, Vietnam Correspondence: anthinhhus@gmail.com Abstract: Increasing urbanization advocates the compact city This study classifies small urban areas in the Ha Dong district (Hanoi, Vietnam) based on indicators for a compact city, and calculates the carbon footprint of urban clusters based on data household of lifestyle surveys A step use approach combining exploratory factor analysis, hierarchy cluster analysis, and carbon footprint is used The results sort out four main factors characterizing the compact city as “quality of infrastructure”, “density of open space”, “transportation pattern”, and “public transportation and urban green space” Small urban areas in Ha Dong are grouped into urban clusters based on the factor “quality of infrastructure” The carbon footprint (CF) of the Ha Dong district is 6.66 ton.year-1.person-1, which is higher than this of the average world, about times over the GHGs target, and nearly times than that of GHGs in Vietnam The urban cluster C3 shows the highest carbon footprint, whereas the C4 has the lowest one Recommendations based on the study result include: have been raised for study area as increase the number of high-density cities (compact city); develop the urban green spaces and public transport system; and improve tools for urban planning based on the criteria of sustainable development and green growth Keywords: Urban small area; urban clusters; compact city; carbon footprint; factor analysis; Hanoi city Introduction Sustainable cities offer a considerable challenge for contemporary land use planning During recent years, Vietnam urbanized at a rate of approximately 3.4 percent per year (WB, 2012); by 2013 about 33.47 percent of the land was urban (MOC Vietnam, 2013) Urban planning until now contributed to environmental pollution, which hampered the economic growth and the sustainable development of the country The urban population is predicted to double in the next ten years, which necessitates agriculture land transformed to urban land by four times (WB, 2012) Urban areas developed without planning could lead to the decrease of infrastructure qualities, impacting on environment and urban landscape During the United Nations Conference on Sustainable Development (Rio 20+) in 2012, decision makers committed to promote an integrated approach to planning and building sustainable cities and urban settlements It would not create liveable habitats for urban people but deal with other ecological and environmental problems Climate change, population growth and urbanization are considered significant issues that need to be considering in the process of land use planning and urban planning ensuring sustainable development Vietnam has witnessed urban sprawling faster and faster during different periods of socioeconomic development (WB, 2012) Consequences of unplanned urban are inefficient land use as well as environmental pollution Sustainable urban planning requires both improving the land quality and decreasing the emission of green house gases (GHGs) In European country, compact cities have been showed as good examples of sustainable urban planning and climate change responses in terms of creating liveable habitats for urban people, and promoting relatively high residential density with mixed land uses and based on an efficient public transport system (Dantzig and Saaty, 1973) In the international literature, there were many urban areas developed from 1950 to 1970, resulting from the increased housing demand after wars As a result, different problems arising from the process of urbanization: the irrational land use, the overuse and exploitation of natural resources, environment pollution, traffic jam, and green house gas emission In 1973, the term “compact city” was invented and defined as a way to efficient urban planning, which allowed to limit the process of urban sprawl and to reduce energy consumption (Dantzig and Saaty, 1973) Brundtland commitment in 1987 first introduced the term “sustainable development” and stated that “transforming the old urban architecture into the compact city was considered as a good practice to archive sustainable development Compact city was the structure of urban planning which enabled citizens to cycle and walk easily as well as use public transportation effectively (Elkin, 1991) Compact city was regarded as the more sustained urban architecture in compared with urban sprawl because its structure helped to reduce using private cars and to increase the effect of infrastructure (Williams, 2000) While urban sprawl became ineffective and lead to inequality society (Bourne, 1992), compact cities offered good conditions for society development (Garcia and Riera, 2003) Different research on the relationship between the compact city and sustainable development showed that the compactness and the sustainability had interactive effects (Neuman, 2005) Transportation was one of major resources of carbon dioxide emission One solution that could be implemented was to adjust land use planning (Baron, 1990) Through efficiency urban planning and effective land use, the amount of fossil fuel decreased by 1015 percent, which means the amount of CO2 released also dropped by 10-15 percent through the changes in using transportation (Rickaby, 1992) Compact cities were developed by mixing land use in a reasonable scale for the purpose of effective energy consumption (Owen, 1992) because the effect is higher in high density cities (WB, 2010) Obviously, the urban structure and energy consumption have close linkage This study deals with classifying small urban areas and calculating carbon footprint in a case study of Ha Dong district (Hanoi city) Ha Dong district is selected as a case study area It is located along two sides of the National Road no 6, is 13 kilometer away from city center, and covers 4,833.66 square kilometers Ha Dong is an urban district which contiguous to rural districts (Thanh Oai district in the south, to Thanh Tri district in the east, and Hoai Duc district in the west) Thus, it becomes the west gate to the suburb of Hanoi In the history of development, Ha Dong became a district of Hanoi because of the urban sprawl In addition, the speed of urbanization accelerates, which results in more and more effect showing clearly in the urban landscape of Ha Dong Meanwhile, Ha Dong affected by population growth and urban resettlement In general, Ha Dong’s infrastructure is not synchronous The center areas have good infrastructure, in contrast to the suburb areas Therefore, practical solutions need to be considered to solve problems related to urban planning The rest of paper consists of four parts: the part shows an introduction and literature review; the part introduces material and methodology of factor analysis and carbon footprint calculation; the part focuses on the results of small urban area classification and calculating carbon footprint for these areas; lastly, conclusion and discussion are pointed out in the part Methodology 2.1 Conceptual study model Figure indicates flow-chart of steps for studying carbon footprint of urban small areas Once land use map in the year 2010 had been used to conduct an urban small area map, the factor analysis and hierarchy cluster analysis was applied to group small urban areas into a reduced number of urban clusters The analysis is based on data collected by an urban architecture questionnaire Then responses of citizens’ lifestyle questionnaire were used to create input data for carbon footprint estimation for different small urban areas Lastly, an urban planning recommendation was conducted based on analyzed results Figure Flow-chart of steps for studying carbon footprint of urban small areas 2.2 Questionnaire Two questionnaires were conducted for survey as follow: (i) Urban architecture questionnaire: as shown in the Table and Table 2, this questionnaire was designed based on 30 indicators belonging to criteria of compact city The 3-point-Likert scale is used to quantify and standardized the properties of small urban areas Data conducted from this questionnaire then to be used in factor analysis and hierarchy cluster analysis (ii) Carbon footprint questionnaire: enables to collects data from sectors for carbon footprint estimation (as shown in Table 3) Table 1: Criteria of a compact city Criteria Definition Mixed land use (C1) Density of open spaces; the number of commercial zones/ services places Take advantage of compact building design (C2) Housing architecture Provide a variety of transportation choices (C3) The quality of transportation Preserve open space, farmland, natural beauty, and critical The quality of public places (parks, environmental areas (C4) schools, hospitals, playgrounds) Strengthen and direct development toward existing The environmental quality communities (C5) Make development decisions predictable, fair, and cost The effect of infrastructure planning effective and create a range of housing opportunities and choices (C6) Develop ground space (C7) The number of ground spaces Table 2: The interpretation of criteria and indicators for urban architecture questionnaire Criteria Indicators (Variable) I1 Open space density I2 Water body density C1 Likert scale low (1), average (2), high (3) I3 Number of commercial sites (markets, shopping malls, etc.) I4 Number of service sites (restaurants, cinemas, poor (1), average (2), good (3) etc.) C2 C3 I5 Housing architectural style houses (1), houses and high buildings (2), high building (3) I6 Number of public transport none (1), small (2), reasonable (3) I7 Quality of roads low (1), average (2), good (3) I8 Wide of roads narrow (1), average (2), wide (3) I9 Wide of footpaths none (1), narrow (2), wide (3) I10 The number of over bridge none (1), small (2), reasonable (3) I11 Bus lane I12 Vehicle lane I13 Type of road network I14 Number of lighting I15 Number of traffic sign I16 Number of lanes (in main roads) none (1), small (2), reasonable (3) radial road network (1), ring road network (3), both (2) none (1), little (2), reasonable (3) lanes (1), 3-4 lanes (2), >4 lanes (3) I17 The quality of public space C4 I18 The quality of schools low quality (1), average quality (2), high I19 The quality of hospitals quality (3) I20 The quality of playgrounds C5 I21 Density of green spaces along main roads low (1), average (2), high (3) I22 The waste treatment process I23 The water waste treatment process I24 Water quality (in rives, lakes) C7 heavy polluted (1), slight polluted (2), good quality (3) polluted (1), only polluted in rush hours (2), I25 Air quality C6 none (1), average (2), good (3) good I26 Electric capable network disordered (1), reasonable (2), ground capable I27 Internet capable network (3) I28 Water consumption rain water (1), tap water (3), both (2) I29 Energy consumption coal (1), green energy (3), both (2) I30 Number of round space none (1), low (2), high (3) 2.3 Factor analysis Factor analysis is a method of multi-criteria analysis, which allows reducing from a large number of variances to a smaller number of factors that account for the most of variance among the original data Factors are nominated by applying principal component analysis to a standardized correlation matrix A table of factor loadings shows which variables are grouped together on which common factors, and the degree of correlation between individual variables and the factors The factors are interpreted as axes in state spaces, and the meanings of the axes are inferred from the variables which are most correlated with them * Factor matrix: k xi ij fi e j (1) i 1 Where: xi are observed variables; fi are the common factors; αij are factor loading of factor xi; and ej is measurement error for xi For factor analysis, to calculate the covariance of any two observable variables: rjk j1 k1 j 2 k jm km (2) * Principal components analysis was used to determine eigenvalue and eigenvector of correlation matrix Eigenvalue i show the proportion of the variance of xj Eigenvector show the attribute of component i m x j wij x j (3) i 1 Where: xj are observed variables; zj are matrix components; wij are variables j loading of component i * Varimax Rotation: Once principal components analysis had been completed, a variable in the n dimensional space specified by the factors involved, factor loadings are the cosine of the angle formed by a vector from the origin to that coordinate and the factor axis Varimax rotation function is as follow (γ = 1): RVAR k p k 2 agr max r AR ij AR ij j 1 k 1 p j 1 2.4 Hierarchical cluster analysis A hierarchical cluster analysis based on the Euclidean nearest-neighbor distance attempted at identifying relatively homogeneous groups of small urban areas in Ha Dong district based on factor scores Euclidean nearest-neighbor distance is defined using simple Euclidean geometry as the shortest straight-line distance between a commune and its nearest neighbor Theoretically, an algorithm that starts with each of small urban area in a separate cluster and combines clusters until only one is left was used for this analysis Hierarchical clustering, consequently, created a hierarchy of clusters, which may be represented in a tree structure called a dendrogram This analysis is based on Euclidean distance metrics as following: ab a bi i i mind a, b : a A, b B Where: a and b belongs to two sets of observations A and B; and d is the chosen metric Results of a hierarchical cluster analysis showed that there are four groups of the small urban areas as urban clusters 2.5 Carbon footprint (CF) calculation Carbon footprint is a measurement of total cumulated GHGs emitted direct and indirect over times resulting from different human activities There are different methods of GHGs estimation depending on the object (individuals, residents, nations or companies, factories, economic sectors) The result of carbon footprint estimation becomes the foundation of implementing policies and strategies for the purpose of GHG reduction To quantify the impact of human activities and lifestyle of residents, the study use the method of GHG estimation (with particular Vietnamese CO2e index) presented by Carbon Footprint Ltd., US (retrieved from http://www.carbonfootprint.com in 2015): CF = CFH + CFT + CFS (5) Table 3: The interpretation of sectors and variables in the carbon footprint questionnaire for households Sectors CFH Definition Variable Total amount of electricity consumption (kWh/person/month) CFT Total amount of GHGs released Total amount of natural gas consumption from household energy (kWh/person/month) consumption Total amount of coal consumption (ton/person/month) Total amount of GHGs released Private transportation: from transportation - The average distance driven per month - Type of private transportation: US car, EU car, average car/van, motorbike, others - Type of fossil fuel consumed: petrol, diesel, others - Capacity: + Car: Large, average, small + Motorbike: 150cc Private Transportation: - The average distance driven per month CFs Total amount of secondary GHG Food and drink products: from residential lifestyle - Vegetarian - Mainly consume fishes - Mainly consume red meats - Mainly consume white meats - Consume both red and white meats Consume organic products: often/sometimes/never Consume seasonal products: only/try/never consume Consume imported products: - Not consume imported products - Only using traditional products - Most product are made in Vietnam - Focus on the quality of product - Not concern the origin of products Fashion: follow latest trend/only buy if necessary/only buy old clothes Plastic bags: none use plastic bags/limit use plastic bags/hardly use plastic bags/ only buy if products are wrapped by plastic bags Furniture and electric divides: - Using latest products - Bought new product and have used more than years - Only buy or change if necessary - Only use old products Recycle products: All/Almost/Some/None products made from recycled materials Recreation: - Take part in activities which are none- GHG emission (e.g cycling, walking, etc.) - Sometime/often go shopping malls, restaurants, cinemas, etc - Take part in high GHG emission activities Total number of private transportation Using baking and finance services: Yes/No (Source: http://www.carbonfootprint.com) Results 3.1 Classifying urban small areas As shown in the table 4, once factor analysis had completed, 19 out of 30 compact city variables were selected and quantified into factors as follows: Factor 1: “the quality of infrastructure” includes 15 variables correlating and showing the synchronization between infrastructure and urban landscape of individual residential areas Factor 2: “the density of open space” describes the appearance of open spaces inside urban Factor 3: “transportation pattern” shows the distribution of two main road types inside urban Factor 4: “public transportation and urban green space” is a dipole factor showing the inverse correlation of two variables It indicates that public traffic spaces and urban green spaces are not planned logically Table 4: Varimax rotated component matrix Indicator Factor Factor Factor Factor I4 0.833 0.030 0.054 0.185 I8 0.828 0.270 0.256 0.006 I9 0.816 0.260 -0.018 -0.164 I16 0.801 0.276 0.141 -0.075 I24 0.799 -0.108 -0.363 -0.016 I3 0.796 0.185 0.185 -0.029 I30 0.778 0.168 0.012 0.067 I29 0.763 0.267 0.261 -0.053 I20 0.732 0.404 0.176 -0.099 I26 0.723 0.297 0.319 -0.088 I15 0.713 0.340 0.282 -0.112 I7 0.701 0.444 0.251 0.072 I5 0.682 0.186 0.320 0.188 I16 0.643 0.490 0.210 -0.184 I23 0.634 0.486 0.131 -0.066 I2 0.218 0.844 -0.125 0.132 I13 0.185 -0.057 0.890 0.079 I11 0.307 -0.006 0.108 0.858 I21 0.339 -0.067 0.019 -0.670 Table Total Variance Explained Factors Initial Eigenvalues Rotation Sums of Squared Loadings Total Percentage Cumulative Total of variance Percentage Cumulative of variance 10.373 54.592 54.592 8.774 46.177 46.177 1.441 7.583 62.176 2.158 11.358 65.858 1.119 5.890 68.065 1.581 8.323 65.858 974 5.124 73.189 1.393 7.331 73.189 Based on the mathematical relationship between factors and the 2010 land use map, four urban classification maps were created (as shown in figures 2, 3, 4, and 5) Dancu by Fac1 1.23 0.12 -0.55 -1 to to to to 2.23 1.23 0.12 -0.55 (10) (16) (22) (17) Figure 2: Map of the quality of infrastructure (Factor 1) Dancu by Fac2 0.7 -0.16 -0.72 -1 to to to to 2.23 0.7 -0.16 -0.72 (16) (20) (16) (13) Figure 3: Map of the density of open space (Factor 2) Dancu by Fac3 2.62 -0.02 -0.49 -1 to to to to 3.5 (5) 2.62 (18) -0.02 (22) -0.49 (20) Figure 4: Map of transportation pattern (Factor 3) Dancu by Fac4 1.27 -0.01 -0.57 -1 to to to to 2.54 (8) 1.27 (22) -0.01 (10) -0.57 (25) Figure 5: Maps of public transportation and urban green space (Factor 4) The total percentage of variability of factor accounts for 75 percent Moreover, factor describles a direct correlation Thus, small urban areas in Ha Dong are grouped into urban clusters based on the quality of infrastructures (As shown in figure 6) Urban cluster C1 includes new small urban areas having similar properties in complex building each of them is a combination of housings, commercial zones, schools, hospitals, sport centers, playground, and etc In addition, there are several urban green spaces and underground spaces in cluster C1 Overall, these areas have good quality infrastructures, creating livable environment for residents as well as promoting socioeconomic development Urban cluster C2 includes old small urban areas with the high diversity in its pattern: complex buildings, containing housings, commercial zones, schools, hospitals, playgrounds, and etc However, the area of green spaces and ground spaces is limited Overall, cluster C2 offers reasonable infrastructure quality for residents Urban cluster C3 includes residential areas which have been developed along two side of the National Road number Thanks to special location, the number of population accelerates which results in the highest population density in Ha Dong district There are many main offices of Ha Dong’s Government in the cluster C3 In these areas, the development of urban areas is spontaneous because of a scarcity of planning Urban areas chopped into many blocks Otherwise, the public transport system is developed, whereas urban areas are shot of green spaces Urban cluster C4 includes suburbs of Ha Dong district In the part, some of them were part of Ha Dong district because of the urban sprawl, whereas others were urban areas when Ha Dong became urban district Urban areas are chopped into many blocks Most of houses are built for a long time, which makes them have bad quality In the cluster C4, many people using charcoal stoves instead of gas cookers and electric cookers Both the infrastructure system and the potential of socioeconomic are limited The impact of urbanization cannot promote the development of these areas It may lead to many environmental and social problems Phan khu thi C1 C2 C3 C4 Figure 6: Map of urban clusters in Ha Dong district The results of study show the differences of energy using, transportation, and lifestyle Hence, the relationship between urban pattern and lifestyle is close 3.2 Carbon footprint Among three indexes of CF, CFH has the lowest value, accounting only for 13 percent (equivalent to 0.91 ton/year/person) It is followed by that of CFT is 1.18 ton/year/person (about 18 percent) The highest value belongs to CFS, with the index being 4.57 ton/year/person (equivalent to 69 percent) In total, that of CF of Ha Dong district is 6.66 ton/year/person, which is higher than that of average CF in the world (4 ton/year/person), is times more than that of GHGs target (2 ton/year/person); is nearly times than that of GHGs in Vietnam (1.18 ton/year/person) Urban clusters C1 and C2 are high density urban areas among four clusters They offer certain benefits from effective urban architecture, providing a variety of choices As a result, the demand for transportation decreases However, the figure of CFH is showed quite high, resulting from high electricity divided consumption The figure of CFS also is considerable due to consuming high GHGs emission products as imported products, plastic bags, joining high GHG emission activities, and high number of transportation means Urban cluster C3 witnesses different negative impacts of urbanization such as rapid population growth The number and the density of population in C3 is highest, which lead to great demand for transportation Thus, the figure of CFT of C3 is highest and the difference between that figure of C3 and three other clusters is considerable In addition, the figure of CFS of C3 is biggest, resulting from high GHGs emission lifestyle as using many imported products, buy many furniture and electric divides, and using plastic bags for shopping Cluster C4 is not affected by urbanization Most of residents in C4 are rural villages, being located separated and mixed with agriculture land They remains old habitats such as using charcoal stove instead of gas cookers or electric cooker, which results in the highest figure of CFH However, their demand for transportation is low, which bring about the lowest figure of CFT In addition, the citizens in C4 have healthy lifestyle such as enjoying organic and seasonal products (they grow by themselves), joining none-GHGs emission activities, only using furniture and electric divides if necessary Table 6: Carbon footprint of Ha Dong urban (unit: ton/year/person) Sectors N Min Max Mean Std Deviation CFH 56 0.12 5.40 0.91 0.84 CFT 56 0.12 7.08 1.18 1.23 CFS 56 2.11 8.21 4.57 1.20 CF 56 2.83 15.40 6.66 2.14 Table 7: Carbon footprint of urban cluster C1 (unit: ton/year/person) Sectors N Min Max Mean Std Deviation CFH 10 0.36 1.68 0.93 0.45 CFT 10 0.36 1.44 0.81 0.46 CFS 10 2.72 5.66 4.19 0.83 CF 10 4.62 8.18 5.94 1.01 Table 8: Carbon footprint of urban cluster C2 (unit: ton/year/person) Sectors N Min Max Mean Std Deviation CFH 13 0.36 1.08 0.55 0.19 CFT 13 0.36 1.56 0.84 0.36 CFS 13 2.50 6.44 4.70 1.19 13 3.34 8.48 6.09 1.36 CF Table 9: Carbon footprint of urban cluster C3 (unit: ton/year/person) Sectors N Min Max Mean Std Deviation CFH 24 0.12 5.40 1.01 1.06 CFT 24 0.36 7.08 1.70 1.70 CFS 24 3.13 8.21 4.88 1.27 CF 24 4.47 15.40 7.59 2.64 Table 10: Carbon footprint of urban cluster C4 (unit: ton/year/person) N Min Max Mean Std Deviation CFH 10 0.24 3.60 1.05 0.97 CFT 10 0.12 1.20 0.71 0.34 CFS 10 2.11 5.85 4.04 1.18 CF 10 2.83 7.48 5.80 1.60 3.3 Conclusion and discussion The compact city is recognised a good lesson for urban planning in developed countries Urban analysis and classification based the criteria of compact city therefore is a useful tool for planning Urban architecture helps to change the way to consume energy inside cities The results show the relationship between urban landscape and lifestyle of human inside urban landscape In 2010, World Bank presents report, namely “Cities and climate change: An Urgent Agenda”, and shows results as: increased density can reduce energy consumption; urban design and mobility are crucial in CO2 emissions; encouraged denser cities and greater reliance on public transportation; change in urban landscape architecture (compact cities are more sustainable than sprawling cities); and change in using energy, toward using alternative resources This support the favourable solutions for analyse the relationship between urban pattern and resident’s lifestyle in urban planning Increasing the number of high-density cities (compact city): Density may concerns in term of building density, population density or infrastructure density as the ratio of urban green space From sustainable development viewpoint, high-density cities emit CO2 lower than low-density cities For instance, Japan’s urban areas are five times denser than Canada’s The consumption of energy per capita in Japan is 40 percent lower than in Canada In Madrid, city density is 10 times higher than Atlanta, and Madrid’s CO2e emissions per capita are four times lower than in Atlanta (WB, 2010) Obviously, the compact city becomes a model of sustainable city which applied widely over the world Cities may have high density for several measures such as mixing land use in planning and developing the public transport system It not only reduces using energy and natural recourses, but also save the environment and improve the land use effect For study area, urban clusters C1 and C2 need apply density cities model because these areas have good quality infrastructures and high building density Developing the urban green spaces and public transport system: Developing urban green space means design in individual spaces making small parks inside the city A good example is the green spaces of Singapore, calling “garden of the world” Otherwise, Government need implement more policies about transportation such as restricting private cars, improving the public transport system In many high-density country in European, people travel by public transportation for a long journey and ride bikes in a short distance This solution brings about many benefits such as saving energy, reducing green house gas emission, management transportation more effectively Another good example is transportation in Copenhagen (Denmark), 55 percent of population travel by bicycles which result in reducing 90,000 ton CO2 per year For study area, cluster C3 need apply this solution because this zone has good quality public transportation but lack of urban green spaces Improving tools for urban planning based on the criteria of sustainable development and green growth: Urbanization and population growth bring many difficulties such as the shortage of land, environment pollution, and traffic congestion Yokohama also dealt with these challenges from 1960s to 1980s Government changed in urban planning policies which helped Yokohama escape from these difficulties For instance, Government spent more money on improving transport system such as building underground highways which may decrease air pollution Not only that, but also Government considered about traffic planning the most when they planned the city As a result, Yokohama is one of eleven most livable cities in the word, becoming an Ecological Economic City (Eco2 Cities) in the world It brings many benefits to improving living-standard and economical competitive advantages Yokohama becomes a model of urban planning toward sustainable development and green growth In Vietnam, urbanization causes different changes in urban land use, which results in many new challenges and opportunities Dealing with these problems, urban planning plays a significant role Not only that, but also it is the orientation and determination factors toward sustainable development Decision-makers should seek scientific indicators system which becomes the framework for assessing the effect of urban planning and the extent of sustainability in urban management: - Carbon footprint is the indicator of green urban city; - The compactness is a quantified indicator for assessing “the sustainability”; and - The relationship between the carbon footprint and the compactness should be used for assessing the sustainable development of urban areas References Banister, D (1992) Energy Use, Transport and Settlement Patterns In: “Sustainable Development and Urban Form”, edited by Breheny, M., 160–181 Barton, H (1990) Local global planning The Planner 76(42), 12-15 BC (Brundtland Commission) (1987) Our common future: Brundtland Report Bourne, L (1992) Self-fulfilling prophecies? Decentralization, inner city decline, and the quality of urban life American Planning 58(4), 509-513 Breheny, M (1992) Sustainable development and urban form (London, UK: Pion Limited) Dantzig, G., Saaty, T.L (1973) Compact City: A Plan for a Livable Urban Environment (San Francisco, US: W.H Freeman) Elkin, T., McLaren, D., Hillman, M (1991) Reviving the City: towards sustainable urban development (London, UK: Friends of the Earth Trust) Garcia, D., Riera, P (2003) Expansion versus density in Barcelona: A valuation exercise Urban Studies 40(10), 1925-1936 Neuman, M (2005) The Compact City Fallacy Planning Education and Research 25(1), 11-26 Owen, S (1992) Energy, Environmental Sustainability and Land-use Planning In: Sustainable Development and Urban Form, edited by Breheny, M 79-105 Rickaby, C.A., Steadman, P., Barrett, M (1992) Patterns of Land Use in English Towns: Implications for Energy Use and Carbon Dioxide Emissions In: Sustainable Development and Urban Form, edited by Breheny, M., 182-196 WB (World Bank) (2010) “Cities and climate change: An Urgent Agenda” Washington, US: The World Bank Williams, K., Burton, E., Jenks, M (2000) Achieving Sustainable Urban Form London, UK: Taylor & Francis ... classifying small urban areas and calculating carbon footprint in a case study of Ha Dong district (Hanoi city) Ha Dong district is selected as a case study area It is located along two sides of the... Conceptual study model Figure indicates flow-chart of steps for studying carbon footprint of urban small areas Once land use map in the year 2010 had been used to conduct an urban small area... developed, whereas urban areas are shot of green spaces Urban cluster C4 includes suburbs of Ha Dong district In the part, some of them were part of Ha Dong district because of the urban sprawl, whereas
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