Urban Metabolism of Six Asian Cities - adb.org

URBAN METABOLISMOF SIX ASIAN CITIES

ASIAN DEVELOPMENT BANK

© 2014 Asian Development Bank

All rights reserved. Published in 2014.Printed in the Philippines.

ISBN 978-92-9254-659-5 (Print), 978-92-9254-660-1 (e-ISBN)Publication Stock No. RPT146817-2

Cataloging-In-Publication Data

Asian Development Bank. Urban Metabolism of Six Asian Cities.Mandaluyong City, Philippines: Asian Development Bank, 2014.

1. Urbanization. 2. Urban Metabolism. I. Asian Development Bank.

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iii

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2 The Urban Metabolism Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3 Measuring Urban Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.1 Available Statistical Data . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.2 A New Streamlined Urban Metabolism Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.3 Urban Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

4 Urban Metabolism of the Six Asian Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.1 Bangalore . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.2 Bangkok . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.3 Ho Chi Minh City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.4 Metro Manila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.5 Seoul Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

4.6 Shanghai Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

5 Comparative Assessment of the Metropolitan Metabolisms . . . . . . . . . . . . . . . . . . . . . . . . 47

5.1 Urban Spatial Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.2 Assessing Urban Material Dependency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

5.3 Material Intensity of the Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.4 Typifying Urban Typologie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

6 Contributions from Urban Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

9 Appendix. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

10 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

iv

List of Figures

Figure 1 Schematic Representation of Urban Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 2 Domestic Material Consumption per Capita of India and Bangalore, 2000 . . . . . . . . . . . . . .Figure 3 Direct Material Input of Bangalore, Disaggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 4 Waste Production in Bangalore (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . . . . . Figure 5 Direct Material Input per capita of India and Bangalore, by End use, 2000 . . . . . . . . . . . . . .Figure 6 Urban Metabolism of Bangalore, Aggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 7 Complete Urban metabolism of Bangalore, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 8 Bangalore Metropolitan Area Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 9 Main Transport Networks in Bangalore Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 10 Domestic Material Consumption per Capita of Thailand and Bangkok, 2000 . . . . . . . . . . . Figure 11 Direct Material Input of Bangkok, Disaggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 12 Waste Production in Bangkok (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . . . . Figure 13 Direct Material Input per capita of Thailand and Bangkok, by End use, 2000 . . . . . . . . . . . . Figure 14 Urban Metabolism of Bangkok, Aggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 15 Complete Urban metabolism of Bangkok, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 16 Bangkok Metropolitan Area Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 17 Main Transport Networks in Bangkok Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 18 Domestic Material Consumption per Capita of Viet Nam and Ho Chi Minh City, 2000 . . .Figure 19 Direct Material Input of Ho Chi Minh City, Disaggregated, 2000 . . . . . . . . . . . . . . . . . . . . . .Figure 20 Waste Production in Ho Chi Minh City (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . Figure 21 Direct Material Input per capita of Viet Nam and Ho Chi Minh City, by End use, 2000 . . . .Figure 22 Urban Metabolism of Ho Chi Minh City, Aggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 23 Complete Urban metabolism of Ho Chi Minh City, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 24 Ho Chi Minh City Area Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 25 Main Transport Networks in Ho Chi Minh City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 26 Domestic Material Consumption per Capita of the Philippines and Metro Manila, 2000. . .Figure 27 Direct Material Input of Metro Manila, Disaggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . Figure 28 Waste Production in Metro Manila (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . . . .Figure 29 Direct Material Input per capita of the Philippines and Metro Manila, by End use, 2000. . Figure 30 Urban Metabolism of Metro Manila, Aggregated, 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 31 Complete Urban metabolism of Metro Manila, 2000. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . Figure 32 Manila Metropolitan Area Land Use. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 33 Main Transport Networks in Manila Metropolitan Area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 34 Domestic Material Consumption per Capita of the Republic of Korea and Seoul, 2000. . . .Figure 35 Direct Material Input of Seoul, Disaggregated, 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

41112

1212131415151718

1818192021212324

2424252627273030

3030323333353536

v

363637383939

4141

42

424344454547

49

4950

51

5253545557

Figure 36 Waste Production in Seoul (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . . . . .Figure 37 Direct Material Input per capita of the Republic of Korea and Seoul, by End use, 2000 . . .Figure 38 Urban Metabolism of Seoul, Aggregated, 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 39 Complete Urban metabolism of Seoul, 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 40 Seoul Metropolitan Area Land Use. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 41 Main Transport Networks in Seoul Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Figure 42 Domestic Material Consumption per Capita of the People’s Republic of China and Shanghai, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 43 Direct Material Input of Shanghai, Disaggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 44 Waste Production in Shanghai (a) by Waste Type in 2000; and (b) in the Following 50 years, Stemming from the Materials Consumed in 2000 . . . . . . . . . . . . . . . . . .Figure 45 Direct Material Input per Capita of the People’s Republic of China and Shanghai, by End use, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 46 Urban Metabolism of Shanghai, Aggregated, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 47 Complete Urban metabolism of Shanghai, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 48 Shanghai Metropolitan Area Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 49 Main Transport Networks in Shanghai Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 50 Water and Built-Up area (Impervious Surface) of the Six Metropolitan Areas . . . . . . . . . . Figure 51 Direct Material Input per Capita of the Eight Metropolitan Areas, by Material Category, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 52 Cumulative share of the 28 Material Subcategories in the Eight Metropolitan Areas, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 53 Share of Metropolitan Direct Material Input by End Use, 2000 . . . . . . . . . . . . . . . . . . . . . . . Figure 54 Share of the Direct Material Input of the Manufacturing Sector, by Industry Type, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 55 Material Use per Capita versus Product per Capita in the Eight Metropolitan Areas, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure 56 Material and Economic Structure of Selected Metropolitan Areas, 2000 . . . . . . . . . . . . . . . Figure 57 Material use Typologies of the Eight Metropolitan Areas, 2000 . . . . . . . . . . . . . . . . . . . . . . . Figure 58 Material Consumption Typologies of the Eight Metropolitan Areas, 2000 . . . . . . . . . . . . . .Figure 59 Urban Metabolism Framework for Green Cities Parameters . . . . . . . . . . . . . . . . . . . . . . . . . .

vi

List of Tables

Table 1 Economic Sectors and Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Table 2 Nomenclature for Material Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Table 3 Definition of Spatial Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Table 4 Spatial Characterization of the Bangalore Metropolitan Region . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Table 5 Spatial Characterization of the Bangkok Metropolitan Region . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Table 6 Spatial Characterization of the Ho Chi Minh City Metropolitan Area . . . . . . . . . . . . . . . . . . . . 28

Table 7 Spatial Characterization of the Manila Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Table 8 Spatial Characterization of the Seoul Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Table 9 Spatial Characterization of the Shanghai Metropolitan Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Table 10 Spatial Metrics of the Six Metropolitan Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Table A1 Characterization of the Six Urban Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Table A2 Regional Gross Domestic Product per Economic Activity, 2000 ($). . . . . . . . . . . . . . . . . . . . . . . 64

Table A3 Employment Structure of the Urban Areas (number). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

vii

Abbreviations

DMC domestic material consumption

DMI direct material input

EU European Union

EUROSTAT Statistical Office of the European Union

GDP gross domestic product

GFCF gross fixed capital formation

HCMC Ho Chi Minh City

ISIC International Standard Industrial Classification

IT information technology

km2 square kilometer

MATCAT classification of categories of materials

MMDA Metropolitan Manila Development Authority

OECD Organisation for Economic Co-operation and Development

PRC People’s Republic of China

UN Comtrade United Nations Commodity Trade Statistics

viii

Acknowledgments

This report was made possible with the help and collaboration of many individuals from various institutions.

This report was prepared by a team from the In+ Center for Innovation, Technology and Policy Research, Instituto Superior Técnico, University of Lisbon, Portugal, comprising Paulo Ferrao, João Fumega, Nuno Gomes, Samuel Niza, André Pina and Luis Santos.

The direction and guidance provided by the former Chief Economist Changyong Rhee and Assistant Chief Economist Douglas Brooks of the Asian Development Bank (ADB) was instrumental in ensuring that the report is geared toward operational relevance in serving the knowledge interest of ADB’s client countries.

Representatives from ADB members participated in the inception workshop in Manila to share their perspectives and ensure that topics covered in the report reflect their most immediate needs and concerns: B. Mahendra from the Bangalore Metropolitan Region Development Authority, Maria Josefina Faulan and Shiela Gail Satura from the Metropolitan Manila Development Authority, Qiu Aijun from the China Center for Urban Development, Sang-Il Kim from the Urban Information Center of Seoul Institute, Saranat Kanjanavanit of the Green World Foundation based in Bangkok, and Nguyen Trong Hoa and Du Phuoc Tan from the Ho Chi Minh Institute for Development Studies. Toby Melissa Monsod and Rachel Racelis from the University of the Philippines contributed the perspectives of an urban economist and an urban planner.

Caroline Ahmad was the manuscript editor, and Jo-Marie Guillermo designed the report cover. Eugenia Go and Rhommel Rico coordinated and oversaw the production of this publication.

We thank Matthew Howells of the Department of External Relations and the Office of Administrative Services for ensuring the timely and smooth production of this report.

ix

Urbanization has been a potent force of growth and development across the world. The process has been slower to unfold in Asia, but has taken off rapidly since the 1980s. The urbanization rate in the region doubled from around 20% to 40% from 1980 to 2010, and is projected to reach over 60% by 2050 (ADB 2012).

The literature on agglomeration suggests that urbanization will bring about productivity increases and spur further growth and development badly needed to lift yet more people out of poverty. But the process of urbanization, especially when unplanned, which is often the case, brings its own sets of challenges that can be a drag on the productivity that cities supposedly promise. Cities across the developing world, especially in the hyper dense metropolises of Asia, face problems in the forms of congestion, pollution, slums, and environmental degradation. Aside from retarding growth, these problems have real costs to public safety, biodiversity and general well-being of city-dwellers.

In this context, the big question is: how can societies reap the benefits of urbanization while at the same time minimizing associated costs to the economy, the people, and the environment?

The urban metabolism framework is a useful tool as a starting point for answering the big question. It maps the activities of cities from their consumption of materials, the different activities associated with those processes, and the wastes produced. Information generated provides a diagnostic tool for identifying high waste generating or inefficient activities and identifying potential points of policy intervention. The tool also yields useful information for tapping potential for industrial symbioses, where the refuse of one sector can be used by another.

In this report, a streamlined urban metabolism approach based on material flow analyses was applied to six Asian cities—Bangalore, Bangkok, Ho Chi Minh City, Manila, Seoul and Shanghai. The streamlined approach surmounts the lack of city level data, which is often cited as the most significant limitation preventing material flow analysis at the city level. The results provide a glimpse of material flows across sectors, and find that emergent patterns are highly dependent on income levels of cities. Further extension of the methodology could confirm these initial observations and create benchmarks for city typologies.

Foreword

1

The size and speed of the urbanization processes occurring throughout the world have raised valid

regions. Urban areas now account for more than 80% of the region’s GDP. Many of the cities have become centers of international trade and commerce and hubs for regional and international connectivity. As economies mature and become more knowledge-centered, Asian cities are also becoming globally important centers of education, culture, and innovation. They are also the key drivers for stronger and more relevant global environment–economy interactions.

During their development stages, cities encourage or discourage the development of particular economic activities within their boundaries. At each stage, this defines their signature (typology), including jobs; economic output; dependence on material resources from elsewhere; and, depending on how they process the resources, impact on the environment. Sustainable development depends on a better understanding of how natural resource use correlates with urban economic activities. Providing a quantitative assessment of these correlations is the role and ambition of the emerging field of urban metabolism.

Assessing the metabolism of urban areas provides important clues about their direct and indirect environmental impacts as a result of their use of natural resources. Deepening the research on urban metabolism can also help identify the most effective infrastructure design and technology choices for diverse cities in different development contexts, such as those for waste management, as well as the potential for establishing a circular economy.2

The growing importance of urban areas1 can be illustrated by the fact that the largest 200 metropolitan economies account for 14% of world population and employment but generate more than 48% of global gross domestic product (GDP) (BI 2012). Metropolitan areas function as locations for high-value economic activity in their nations and world regions. Almost four in five boast average incomes (as proxied by per capita gross value-added) that exceed averages for their nations. This is particularly true in rapidly emerging areas of Asia and Eastern Europe, where the average incomes of major metropolitan areas exceed those of the national by margins of at least 90% (BI and LSE 2010).

During 1993–2007, roughly half of the metropolitan areas that achieved the strongest growth in gross value-added per capita and employment were located in rising nations of Asia, Latin America, and the Middle East, benefiting from new heights of global economic integration (BI and LSE 2010).

The spectacular economic momentum of the past 2 decades has turned Asia into one of the main engines of global prosperity and Asian cities into prominent symbols of this success. In a closely related development, more than half the world’s urban population now lives in cities in Asia and the Pacific—cities that are also home to most of the world’s slum dwellers, despite the fact that the region has managed to improve the lives of an estimated 172 million slum dwellers during 2000–2010 (UN-Habitat 2010).

As urban expansion and new patterns of economic activity interact, novel configurations have emerged, such as mega urban regions, urban corridors, and city

1 In this report, an urban area refers to the metropolitan area, according to the administrative boundaries defined by each government.

1. Introduction

2 A circular economy pertains to a system wherein wastes are eliminated or minimized by reusing or upgrading end-of-life products for other applications and through as many cycles as possible.

2 Urban Metabolism of Six Asian Cities

concerns about the overall sustainability of urban systems. As the number of people living in densely populated areas grows, the threats and opportunities for promoting more healthy and sustainable ways of living also increase. In Asia, while economic growth has enabled poverty levels to be reduced, the environmental costs induced are already being felt by the urban population (Lindfield and Steinberg 2012).

Moreover, the impacts of urban areas stretch far beyond their administrative boundaries, contributing directly or indirectly to more intensive land use and greater resource extraction, waste generation, and greenhouse gas emissions. Understanding the relationship between the consumption of materials, water, and energy in urban areas, and the locations where these resources are extracted or produced, can provide relative measures of the ecological footprint of different cities and help assess the real impact of those cities (Lindfield and Steinberg 2012).

Not only are the environmental impacts dictated by how economic activities in urban areas, but the concept of promoting a transition to sustainable urban systems depends to a large degree on the structural transformations that urban areas undergo over time. Identifying the main environmental, social, and economic development issues within each urban area can support the design of sustainable urban development plans (Lindfield and Steinberg 2012), and this constitutes another major contribution of the urban metabolism approach developed in this document.

Designing policies that promote green urbanization is not an easy task. Each city must be able to diagnose its current levels of consumption, identify its own targets, and implement its own sustainability plan (Lindfield and Steinberg 2012). Designing optimal water, energy, waste, and mobility infrastructure; pursuing opportunities for promoting a circular economy; and identifying best practices for the critical activities of each city are important steps in the path towards green urbanization. The urban

metabolism concept is intended to support the crafting and implementation of sustainable policy design through three distinct contributions:

1. Benchmarking quantitative data on resource use and waste generation. This can facilitate the identification of best practices by enabling clear comparisons of quantitative indicators of diverse urban areas (e.g., Siemens 2011).

2. Enhancing clustering techniques3 for the development of city typologies that may consider the specificities of urban areas, such as climate, demographics, governance, urban morphology, and economic structures, together with the characterization of the key urban economic sectors and their resource use intensity.

3. Providing a basis for the assessment of alternative policy scenarios, i.e., how different policy measures, through their impact on the economic structure, change the mix, type, and volume of natural resources on which the urban systems depend, and the nature and volume of waste products (PwC 2012).

The material dimension of urban metabolism is one of the most relevant in assessing the sustainability of urban areas. However, a major challenge in assessing urban sustainability is the lack of standardized criteria for data collection at the city level. In particular, there is little understanding of the correlation between resource use and urban economic activities. This is partly due to the lack of a standardized methodology based on publicly available data to quantify the urban metabolism of the major world cities.

The report develops and demonstrates the application of a simplified urban metabolism methodology to six Asian metropolitan areas: Bangalore, Bangkok, Ho Chi Minh City, Metro Manila, Seoul, and Shanghai. These cities were chosen as case studies because of their importance, economic structure, and data availability.

3 Cluster analysis is a statistical tool used to determine natural groupings from observed data.

3

Urban metabolism provides a framework for analyzing the technical and socioeconomic processes that occur in cities. This includes assessing the inputs, outputs, and stores of energy, water, and materials of an urban area (Kennedy et al. 2011).

The concept is grounded on the analogy with the metabolism of living organisms, as cities can transform raw materials into infrastructure, human biomass, and waste (Wolman 1965, Bai 2007, Kennedy et al. 2007). They can also be analyzed as an ecosystem to incorporate relationships between and among cities (Kennedy et al. 2011). Indeed, approximating the dynamics of natural ecosystems is often presented as an objective when developing sustainable cities, as natural ecosystems are considered to be the most sustainable systems on earth.

Ideally, the study of urban system metabolism should capture the complex cross-scale relationships among the natural environment, the transboundary implications of engineered infrastructure, and the social agents and institutions that shape interactions in the city systems (Ramaswami et al. 2012). The lack of data and systematic metrics for engineered infrastructure and social agents and institutions, however, prevents such an ideal from being realized.

The material aspect of the interaction in cities presents an opportunity for analysis, nonetheless. While the material dimension is only one component of understanding the metabolism of cities, it allows the development of reliable metrics for the assessment of urban material flows and stocks. The consumption and production of materials is crucial for assessing the sustainability of a city in terms of efficient functioning, resource availability, and environmental protection (Brunner 2007).

2. The Urban Metabolism Framework

Material flow accounting allows the consumption of a system to be visualized for a particular base year, corresponding to a static analysis of flows; but it also permits an evaluation of the consumption trends of an economic system through a time series. In addition, data computation methodologies allow flows to be broken down into urban activities (Rosado et al. 2013)—intermediate consumption (economic activities) and final consumption (households, services, and state).

The material flows of an urban area are illustrated in Figure 1. They include

• inputs:domesticextractionofresources,andimports of raw materials and products;

• outputs:emissionsandwastes,andexportsofraw materials and products;

• internalprocesses:intermediateandfinalconsumption; and

• additiontostock:shareoftheconsumptionthatis accumulated in the system.

Imports to an urban area may come from the rest of the country or from abroad. Together with locally extracted materials, imports are used by the urban economic activities to produce goods and services that will be consumed within the city by other economic activities and by the citizens, or exported (to the rest of the country and to the rest of the world). A portion of the materials consumed is accumulated in the material stock of the local economy (as buildings, infrastructure, and durable goods). The rest leaves the economy as valuable products, waste, and emissions (to the local environment or beyond). In addition, a large fraction of materials is


imported and largely reexported. These materials are termed transit or crossing flows. This fraction does not become part of the urban economy because the

Figure 1: Schematic Representation of Urban Metabolism

Source: Authors

urban area (through its harbors, train stations, and airports) functions essentially as a gateway to other regions.

5

3.1 Available Statistical Data

3.2 A New Streamlined Urban Metabolism Methodology

The development of the proposed methodology for accounting for the material flows of urban areas was based on datasets that are widely available to the public. The most relevant international datasets used for the analysis of urban metabolism are as follows:

• TheUnitedNationsCommodityTradeStatistics(UN Comtrade) database describes the imports and exports of all countries in the world. It reports the weight and value exchanged between one country and another for all product types, using the Standard International Trade Classification (1- to 5-digit level) or Harmonized Commodity Description and Coding System.

• Modelling Opportunities and Limits forRestructuring Europe towards Sustainability (MOSUS) compiled domestic extraction data for all countries. This database, managed by the Sustainable Europe Research Institute, reports the domestic extraction of materials divided into several materials using the economy-wide material flow accounts classification (EUROSTAT 2001) for 1980–2002 and in 12 material subgroups for 2003–2009.

• The Organisation for Economic Co-operationand Development (OECD) compiles input–output tables for all OECD members and 15 non-OECD member economies, which report the monetary exchanges between producers and consumers in an economy. The tables have been compiled for three periods—mid-1990s, early 2000s, and mid-2000s—although not all countries have all periods. For each country, the input–output total table, domestic table, and import table are available using the International Standard Industrial Classification (ISIC) (Revision 3).

The study undertook an assessment of the six metropolitan areas using metrics such as demographics, and economic and physical structure. The physical structure of an urban economy is described by the material throughput of that economy. To measure these flows, the following elements need to be considered: inputs—domestic extraction of resources, and imports of raw materials and products; internal processes—intermediate and final consumption; addition to stock—accumulation of materials in the system; and outputs—emissions and wastes, and exports of raw materials and products.

The material inputs of an urban area derive from locally extracted materials, imports from the rest of the country, and/or imports from abroad. The raw materials and intermediate goods imported are used by economic activities to produce final goods that will eventually be used for final consumption, either by the economic activities themselves or by the citizens and the government, or exported. To describe the production structure of the urban area in mass units, it is necessary to allocate materials to economic activities.

Few countries maintain accounts at the regional level, much less distinguish between urban and rural attributions. Niza et al. (2009) and Rosado et al. (2013) developed a method to account for

3. Measuring Urban Metabolism

• Specific regional data from national andmetropolitan governments were compiled based on the distribution of employment, population, and local extraction of raw materials.


and disaggregate urban flows based on economy-wide material flow accounting of the Statistical Office of the European Union (EUROSTAT 2001) but requiring detailed statistics, particularly at the urban area level, such as statistics on international trade; transport (within the urban area and between it and the other regions of the country); industrial production; mineral extraction; agricultural, forest, and fishery production; and industrial and municipal wastes and emissions. The streamlined urban metabolism method applied in their work involves estimating the metabolism of an urban area using national statistical data and scaling it down to an urban level, overcoming several data gaps, albeit with some costs to precision.

The structure of an economy is described by input–output tables, which are used to estimate the use of materials by economic activities in a country considering the volume content per monetary unit. These tables map the sales from each economic sector to the others; the consumption of households; the consumption of the government; the acquisition of buildings and machinery by companies, households, and the government (gross fixed capital formation [GFCF]); and the exports.

Resource flows were allocated from the national scale to different dimensions using proxies, such as the number of workers per economic activity. For instance, material consumption per economic activity at a regional level (e.g., urban) was considered as a fraction of the national figure. This fraction is equivalent to the ratio between the local (urban) number of workers per economic activity and the total (national) number of workers in that activity.

Following the first law of thermodynamics (conservation of mass), the total of inputs must, by definition, equal the total of the outputs plus the net accumulation of materials in the system:

Input = Output + Stock increases – Stock decreases

This material balance principle is as true for the whole economy as for any of its subsystems (economic sectors, firms, households, etc.).

EUROSTAT (2001) defined direct material input (DMI) and domestic material consumption (DMC) as the main input material flow indicators. The main output indicators are the domestic processed outputs and exports. Stock changes are accounted for as net additions to stock.

DMI measures the direct input of materials for use in the economy, i.e., all materials that have an economic value and are used in production and consumption activities. In practice, DMI equals domestic extraction plus imports.4

DMC measures the total amount of material directly used in an economy for own consumption. DMC equals DMI minus exports, and is defined in the same way as other key physical indicators such as gross inland energy consumption.

The domestic processed output measures the total weight of materials—whether extracted from the domestic environment or imported—that have been used in the domestic economy, before flowing to the environment. These flows occur at the processing, manufacturing, use, and final disposal stages of the production–consumption chain.

Once this has been accomplished at the national level, the metropolitan DMI can be derived by scaling down from the national data. In this context, the following is observed:

1. The DMI of the metropolitan area is smaller than

4 DMI is not to be added across economies, because it includes the fraction of materials that are imported by other econo-mies. For example, to calculate the DMI of the European Union (EU), intra-EU foreign trade flows must be netted out from the DMIs of member states because exports from one country would also be accounted for as imports to another country, and thus some materials in the resulting EU DMI would be double-counted.

7Measuring Urban Metabolism

the sum of the DMIs of the economic sectors present in the metropolitan area:

DMIMetro < ∑ DMISector

2. The DMI of the metropolitan area is equal to the sum of the DMCs of the economic sectors plus the exports of the metropolitan area:

DMIMetro = ∑ DMCSector + ExpMetro

3. The DMI of each sector equals the DMC of the sector plus the exports of that sector:

DMISector = DMCSector + ExpSector

Usually, the description of data in international trade statistics provides a way of mapping material categories of imports of raw materials and intermediate goods to economic activities. Assuming that the domestic extraction categories are distributed among the same activities as imports, it is possible, through the input–output table, to estimate the use of goods for each activity.

The calculation of the input of materials to the country was based on domestic extraction and trade statistics (Food and Agriculture Organization of the United Nations, and UN Comtrade, among others). To distribute the input of materials by the multiple economic sectors, each material and product entering the economy is first allocated to the economic sectors that process it. This is performed using correspondence tables linking commodities (expressed in the Standard International Trade Classification, Economy-Wide Material Flow Accounts, Harmonized Commodity Description and Coding System, or combined nomenclatures) to economic activities (expressed in nomenclatures such as ISIC and the Statistical Classification of Economic Activities in the European Community [NACE]), and conversion tables for nomenclatures of materials and of economic activities. The economic activities considered in this work are consistent with the ISIC nomenclature (Table 1).

Table 1: Economic Sectors and ActivitiesEconomic Sector Economic Activities

Agriculture and mining

Agriculture, hunting, forestry, and fishingMining and quarrying

Biomass-related products

Food products, beverages, and tobaccoTextiles, textile products, leather, and footwearWood and products of wood and corkPulp, paper, paper products, printing, and publishing

Chemicals and fuel products

Coke, refined petroleum products, and nuclear fuelChemicals and chemical productsRubber and plastics products

Construction products Other nonmetallic mineral products

Metallic productsBasic metalsFabricated metal products except machinery and equipment

Machinery and equipment

Machinery and equipment not elsewhere classifiedOffice, accounting, and computing machineryElectrical machinery and apparatus not elsewhere classifiedRadio, television, and communication equipmentMedical, precision, and optical instrumentsMotor vehicles, trailers, and semitrailersOther transport equipmentManufacturing not elsewhere classified; recycling

Utilities Electricity, gas, and water supplyConstruction Construction

Services

Wholesale and retail trade; repairsHotels and restaurantsTransport and storagePost and telecommunicationsFinance and insuranceReal estate activitiesRenting of machinery and equipmentComputer and related activitiesResearch and developmentOther business activitiesPublic administration and defense; compulsory social securityEducationHealth and social workOther community, social, and personal services

Source: Authors based on ISIC


Table 2: Nomenclature for Material CategoriesMaterial Category

Material Code Description of Material

Fossil Fuels (FF)

FF1 Low-ash fuelsFF2 High-ash fuelsFF3 Lubricants, oils, and solventsFF4 Plastics and rubbers

Metals (MM)

MM1 Iron, steel alloying metals, and ferrous metals

MM2 Light metalsMM3 Nonferrous heavy metalsMM4 Special metalsMM5 Nuclear fuelsMM6 Precious metals

Nonmetallic minerals

(NM)

NM1 SandNM2 CementNM3 ClayNM4 StoneNM5 Other (fibers, salt, inorganic

parts of animals)

Biomass (forestry, crops

and animal products)

(BM)

BM1 Agricultural biomassBM2 Animal biomassBM3 Textile biomassBM4 Oils and fatsBM5 SugarsBM6 Wood BM7 Paper and boardBM8 Unspecified biomass

Chemicals and Fertilizers

(CF)

CF1 AlcoholsCF2 Chemicals and pharmaceuticalsCF3 Fertilizers and pesticides

Others (O)

O1 UnspecifiedO2 Liquids

The distribution of materials throughout the economy is made by allocating them across all economic sectors, final consumption, and exports according to the purchases made from each sector based on the sales registered. These calculations enable the estimation of how materials are distributed within a country’s economy. The analysis of a large variety of materials and products that enter an economy has been facilitated by converting them into a structured nomenclature of categories of materials, or MATCAT, as coined by Rosado et al. (2013).

The MATCAT establishes a correspondence between products listed in the combined nomenclature and the materials that constitute them (Table 2). MATCAT considers 6 categories of materials (fossil fuels, metallic minerals, nonmetallic minerals, biomass, chemical, and others) and 28 subcategories. This enables a systematic analysis of the types of materials on which an economy is most dependent. In addition to the material composition of products, the database includes the average lifetime of each product.

Source: Rosado, L., S. Niza, and P. Ferrão. (2014)

The proportion of workers employed in a sector is used to estimate the amount of materials consumed by each economic sector, as well as the amount of materials and products produced by each economic sector for national and international export at the metropolitan level.5 The final consumption by households and government was estimated using their share in the total population.

Using this method, the material input to an urban economy comprises of (i) inputs that enter the urban area to be transformed by its productive sectors and (ii) the materials that are locally consumed by the

economic sectors (households, government, and firms):

material input = products for transformation + local consumption

For each sector, the products for transformation are described as the products that enter an economic sector and leave it to be consumed elsewhere. Local consumption includes the consumption by households, the government, and firms (materials

5 The authors recognize that such an approach does not ac-count for the productivity effects of economies of agglom-eration.

9Measuring Urban Metabolism

3.3 Characterizing Urban Patterns

Remote sensing data, such as satellite images and aerial photographs, play an important role in the study of urban footprint evolution because they allow the identification of recurring patterns in land use changes. Recent research uses remote sensing images to quantitatively describe the spatial structure of urban environments and thus characterize patterns of urban morphology. The three different methods for obtaining data for mapping land cover in urban areas are field data collection, aerial photography, and satellite imaging.

The extraction of information from digital aerial photographs and satellite imagery can be performed using digital image processing and/or visual image

analysis. This analysis used visual image analysis. In this method, different objects in the image are recognized and classified based on visual variables (shape, texture, size, color, and location), and the data are transformed into geographic information.

The procedure allows the identification of three distinct classes of area: impervious surfaces, pervious surfaces, and water. All elements in the images were identified at a scale of 1:30,000 through aerial imagery from Bing Maps (Painho and Caetano 2006).

Impervious surfaces (built-up areas) are a notable feature of urban areas. They include the following structural elements: continuous urban fabric, discontinuous urban fabric, other (impervious) areas outside the urban fabric, industrial or commercial units, road and rail networks and associated land, and ports and airports.

Permeable surfaces are areas without impermeable ground or floor constructions, thus allowing infiltration of water. Examples include arable land, permanent crops, pastures, heterogeneous agricultural areas, forests, scrub and herbaceous vegetation, and open spaces with little or no vegetation.

Areas classified as water include inland waters (water courses and water bodies) and marine waters (coastal lagoons and estuaries).

Recent advances in spatial analysis, particularly in the development of spatial metrics, have made it possible to compare urban form, urban growth, and changes through time (Taubenbock et al. 2008). They also capture the spatial heterogeneity of each fragment among the fragments of the same class and among classes (Herold et al. 2003). A fragment (or patch) is a fairly discrete area of relatively homogeneous conditions at a particular scale (McGarigal and McComb 1995). A class is a group of patches that share the same characteristics (e.g., the urban area class).

that enter the economic sectors and only leave it as waste). The international exports originating from the urban area are estimated based on the international exports estimated at the national level for each economic activity. Domestic exports are then calculated as follows:

domestic exports = material input – local consumption – international exports

The material input to an urban area, as calculated by this method, is equal to the direct material input (DMI) (domestic extraction + imports), with the local consumption being equal to the domestic material consumption (DMC) (DMI – exports).

The methodology described in this work does not calculate the flows of materials that cross an urban area. However, this is not an issue, as the total material input to an urban area is determined by the total final consumption and the exports; therefore the materials that cross the urban area are not accounted in the inputs, thus leading to a correct material balance.


Table 3: Definition of Spatial MetricsSpatial Metric

(class) Range Unit Detail Measure

PLAND (Area) 0 < PLAND ≤ 100 Percent Percentage of the metropolitan area comprised of impervious surface Area

PD (Aggregation) PD > 0 Number per 100 hectares

Number of patches of impervious surface per total impervious area

(number of continuous urban areas)Fragmentation

ENN (Aggregation) ENN > 0 Meters Distance between patches, allowing estimating the

isolation of urban areas Dispersion

CIRCLE (Shape) 0 < CIRCLE < 1 Mean patch size

Measure of the circularity of the patches (low values represent circular patches) Geometry

SHAPE (Shape) 1 ≤ SHAPE ≤ ∞ Mean patch size

Shape irregularity of the urban area (low values represent low complexity) Shape Irregularity

Source: Based on McGarigal, K., Cushman, S.A., Neel, M.C.; Ene, E., 2002. FRAGSTATS: Spatial pattern analysis program for categorical maps, version 3.0. University of Massachusetts, Amherst, Massachusetts

Spatial metrics describe area, aggregation, and shape. The metrics characterizing the area quantify the landscape composition, those describing aggregation refer to the tendency of patch types to be spatially

aggregated or disaggregated, while those referring to shape describe the morphology of the patch. The metrics in this analysis are based on McGarigal et al. (2002) and are described in Table 3.

11

4. Urban Metabolism of the Six Asian Cities

4.1 Bangalore

The Bangalore Metropolitan Region is part of Karnataka State in India and is the state’s main hub for administration, culture, commerce, industry, and knowledge. The Bangalore Metropolitan Region Development Authority is an autonomous parastatal agency created by the state government to plan, coordinate, and supervise the development of the areas within the Bangalore Metropolitan Region. The most important administrative area within the metropolitan region is the Greater Bangalore area, which comprises the city of Bangalore, the industrial hub of electronics city, seven city municipal councils, one town municipal council, and 111 villages around the city.

The state of Karnataka has created numerous other organizations to manage services such as the Bangalore Water Supply and Sewerage Board, Bangalore City Police, Bangalore Metropolitan Transport Corporation (bus-based), Bangalore Metro Rail Corporation (rail-based), Regional Transport Office (vehicle licenses and taxes), Bangalore Electricity Supply Company (power distribution), and the Lake Development Authority (regeneration and conservation of lakes in Bangalore urban district).

The reference year for this study was 2001, and at that time, the Bangalore Metropolitan Region had a population of 8.4 million, representing 0.8% of the total population of India, and a density of 1,000 inhabitants per square kilometer (km2) (Appendix). The metropolis had 3.4 million workers and a gross domestic product (GDP) per capita of $2,300 measured at purchasing power parity. Bangalore’s GDP represented 1.4% of national GDP. The sectors that contributed most to regional GDP in the assessment year were services (57%) and manufacturing (27%). The bulk of employment in Bangalore was in the service sector (63%), biomass products industries (20%), and machinery and

equipment sector (9%).

Bangalore is well known for its achievements in the information technology (IT) sector. According to Software Technology Parks of India, Bangalore’s IT exports rose from about $1 billion in 2001 to more than $10 billion in 2006.

The city has also benefited from employment generated by spin-offs of the IT industry. The other main sectors of industry are textiles, automobile, machines, aviation, space, defense, and biotechnology. These activities are scattered across 20 industrial areas.

Despite having above-average per capita incomes, the high price of the land and amenities in Bangalore Metropolitan Region—a result of the exponential development of the city—have created areas of poverty that account for 220,000 households, housing approximately 1.1 million people (Sudhira et al. 2007). Slums are therefore a significant feature of the Bangalore urban landscape.

In 2000, the DMI of the Bangalore Metropolitan Area was 60.4 million tons. DMC was estimated at about 54.6 million tons, or approximately 1.4% of India’s DMC. This corresponds to a per capita figure of 6.5 tons for Bangalore, compared to 3.9 tons per capita for India as a whole in the same year (Figure 2).

Figure 2: Domestic Material Consumption per Capita of India and Bangalore, 2000

DMC = domestic material consumption, t/cap = tons per capita.Source: Authors.

DMC

per c

apita

(t/c

ap)

India Bangalore

DMI = direct material input, GFCF = gross fixed capital formation, t/cap = tons per capita.Source: Authors.


The DMI of the Bangalore Metropolitan Region was composed mainly of biomass (30.7 million tons, or 51%), nonmetallic minerals (18.9 million tons, 31%) and fossil fuels (7.6 million tons, 13%) (Figure 3). The main subcategories of biomass entering Bangalore were unspecified biomass (BM8), which includes pasture, representing 47% of the total biomass; agricultural biomass (BM1), representing 38%; and wood (BM6), representing 11%. For fossil fuels, the main subcategory was low-ash fuels (FF1) with 73%; while for nonmetallic minerals, stone (NM4) accounted for 96% of the materials in this category. Together, these five subcategories of materials accounted for 88% of the DMI of the Bangalore Metropolitan Region.

Figure 3: Direct Material Input of Bangalore, Disaggregated, 2000

FF = fossil fuels, MM = metallic minerals, NM = nonmetallic minerals, BM = biomass, CF = chemicals and fertilizers, O=others, DMI = direct material input, kt = thousand tons.Source: Authors.

Almost all of the materials were imported, either from outside the country or from other areas of the country. Only 6.8% of the DMI was extracted in the metropolitan area, and this consisted mainly of biomass (79%) and nonmetallic minerals (15%).

Excluding fossil fuels, 71% of the materials that were consumed within the urban area in 2000 were estimated to have been disposed of as wastes in the same year, while 28% are expected to be converted to residues after 35 years. Figure 4 shows the waste production by waste type in 2000 (Figure 4a) and in the following 50 years (Figure 4b) stemming from the

Figure 4: Waste Production in Bangalore (a) by Waste Type in 2000; and (b) in the Following 50 Years, Stemming

from the Materials Consumed in 2000

kt = thousand tons. Source: Authors.

6 The waste estimation by year was obtained by considering the average lifetime of the products entering the urban area. For example, an apple is transformed to waste in the year it enters the urban area, while a car will stay in the urban area for more than a decade before becoming waste. In the case of construction, materials used normally turn into waste after 30 years or more.

The use of materials by the economic sectors of Bangalore is significantly different from that of India as a whole (Figure 5). Of the materials that pass through the urban area, 10% (5.9 million tons) are not consumed there, but are exported to the rest of the country or to other countries. By comparison, India only exported about 2% of its DMI. The main end uses of the materials consumed in the urban area are the manufacture of biomass-related products (26%

Figure 5: Direct Material Input per Capita of Bangalore and India, by End Use, 2000

DMI (

kt)

FF MM NM BM CF O

materials consumed in 2000.6

Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

DMC

per c

apita

(t/c

ap)

8

7

6

5

4

3

2

1

0

India Bangalore

(a) (b)

13Bangalore

BangaloreDirect Material Input 60.4 million tons

BM – BiomassCF – Chemicals and fertilizersFF – Fossil fuelsMM – Metallic mineralsNM – Nonmetallic mineralsO - Others

Figure 6: Urban Metabolism of Bangalore, Aggregated, 2000

Source: Authors.

of DMI). The final consumption of households and government is responsible for 23% of DMI, while the service sector accounts for 15%. Bangalore’s large textile industry (particularly the silk industry), which is one of the largest in the country, is responsible for the significant consumption of biomass products by the manufacturing sector.

The urban metabolism of Bangalore, illustrated in Figure 6, shows that biomass is the main type of material used, accounting for 79% of the production of biomass-related products and 86% of the final

consumption of households and government. Nonmetallic minerals account for 45% of the materials used by services, while biomass accounts for 34%. The use of fossil fuels is spread out through the economy, with 26% consumed in the production of biomass products, 23% going to the final consumption of households and government, and 15% used by services. Figure 7 provides a more detailed picture of the urban metabolism of Bangalore, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, gross fixed capital formation (GFCF), and exports.

S01 – Agriculture and miningS02 – Biomass-related productsS03 – Chemicals and fuel productsS04 – Contruction productsS05 – Metallic productsS06 – Machinery and equipmentS07 – UtilitiesS08 – ConstructionS09 – ServicesSEXP – ExportsSFC – Final consumptionSGFCF – Gross fixed capital formation

14

Figu

re 7

: Com

plet

e U

rban

Met

abol

ism

of B

anga

lore

, 200

0

Bang

alor

eD

irect

Mat

eria

l Inp

ut

60.4

mill

ion

tons

Sour

ce: A

utho

rs.

BM1

– A

gric

ultu

ral b

iom

ass

BM2

– A

nim

al b

iom

ass

BM3

– T

extil

e bi

omas

sBM

4 –

Oils

and

fats

BM5

– S

ugar

sBM

6 –

Woo

dsBM

7 –

Pap

er a

nd b

oard

BM8

– U

nspe

cifie

d bi

omas

sCF

1 –

Alc

ohol

sCF

2

– Ch

emic

als a

nd

ph

arm

aceu

tical

sCF

3

– Fe

rtiliz

ers a

nd p

estic

ides

FF1

–

Low

ash

fuel

sFF

2

– H

igh

ash

fuel

sFF

3

– Lu

brifi

cant

s, o

ils

an

d so

lven

tsFF

4

– Pl

astic

s and

rubb

ers

MM

1 –

Iron

, ste

el a

lloyi

ng

an

d fe

rrous

met

als

MM

2 –

Lig

ht m

etal

sM

M3

– N

onfe

rrous

hea

vy m

etal

sM

M4

– S

peci

al m

etal

sM

M5

– N

ucle

ar fu

els

MM

6 –

Pre

ciou

s met

als

NM

1 –

Sand

NM

2 –

Cem

ent

NM

3 –

Cla

yN

M4

– S

tone

NM

5 -

Oth

ers

O1

–

Non

spec

ified

O2

–

Liqu

ids

S01

– A

gric

ultu

re, h

untin

g, fo

rest

ry a

nd fi

shin

gS0

2 –

Min

ing a

nd q

uarry

ing

S03

– F

ood

prod

ucts

, bev

erag

es a

nd to

bacc

oS0

4 –

Tex

tiles

, tex

tile

prod

ucts

, lea

ther

an

d fo

otw

ear

S05

– W

ood

and

prod

ucts

of w

ood

and

cork

S06

– P

ulp,

pap

er, p

aper

pro

duct

s, p

rintin

g

an

d pu

blish

ing

S07

– C

oke,

refin

ed p

etro

leum

pro

duct

s

an

d nu

clea

r fue

lS0

8 –

Che

mic

als a

nd c

hem

ical

pro

duct

sS0

9 –

Rub

ber a

nd p

last

ics p

rodu

cts

S10

– O

ther

non

met

allic

min

eral

pro

duct

sS1

1 –

Bas

ic m

etal

sS1

2 –

Fabr

icat

ed m

etal

pro

duct

s

ex

cept

mac

hine

ry a

nd e

quip

men

tS1

3 –

Mac

hine

ry a

nd e

quip

men

t n.e

.c

S14

– O

ffice

, acc

ount

ing a

nd

com

putin

g mac

hine

ryS1

5 –

Ele

ctric

al m

achi

nery

and

app

arat

us n

.e.c

S16

– R

adio

, tel

evisi

on a

nd c

omm

unic

atio

n

eq

uipm

ent

S17

– M

edic

al, p

reci

sion

and

optic

al in

stru

men

tsS1

8 –

Mot

or ve

hicl

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raile

rs a

nd s

emitr

aile

rsS1

9 –

Oth

er tr

ansp

ort e

quip

men

tS2

0 –

Man

ufac

turin

g n.e

.c; r

ecyc

ling

S21

– E

lect

ricity

, gas

and

wat

er su

pply

S22

– C

onst

ruct

ion

S23

– W

hole

sale

and

reta

il tra

de; r

epai

rsS2

4 –

Hot

els a

nd re

stau

rant

sS2

5 –

Tra

nspo

rt an

d st

orag

eS2

6 –

Pos

t and

tele

com

mun

icat

ions

S27

– F

inan

ce a

nd in

sura

nce

S28

– R

eal e

stat

e ac

tiviti

esS2

9 –

Ren

ting o

f mac

hine

ry a

nd e

quip

men

tS3

0 –

Com

pute

r and

rela

ted

activ

ities

S31

– R

esea

rch

and

deve

lopm

ent

S32

– O

ther

Bus

ines

s Act

iviti

esS3

3 –

Pub

lic a

dmin

. and

def

ence

;

co

mpu

lsory

soci

al se

curit

yS3

4 –

Edu

catio

nS3

5 –

Hea

lth a

nd so

cial

wor

kS3

6 –

Oth

er c

omm

unity

, soc

ial

and

pers

onal

serv

ices

SEX

P –

Expo

rtsSF

C –

Fin

al c

onsu

mpt

ion

SGFC

F –

Gro

ss fi

xed

capi

tal f

orm

atio

n

15Bangalore

The low level of consumption for GFCF can be linked to the significant proportion of the population living in slums. The prevalence of slum dwellers also explains the importance of biomass consumption. Nonetheless, the increasing spatial distribution of households and employment clusters, coupled with economic growth due to the increase of IT services, suggests that the metropolitan area will require significant amounts of nonmetallic minerals in the future to build the housing, transport networks, and waste collection systems needed to support this development.

The urban development of Bangalore is concentrated along the transport networks, with residential areas outside the city center and cores of industrial parks in the periphery. Figure 8 presents the spatial distribution of three classes of land use in the Bangalore Metropolitan Area: industrial area, built-up area, and water.

Corroboration with ground data reveals that the IT industry and other large companies cluster around the industrial parks, while small and medium-sized enterprises are dispersed in residential and commercial areas and along the main roads.

Figure 8: Bangalore Metropolitan Area Land Use

The dispersive growth pattern, which was accelerated by the creation of employment clusters around the periphery of the city, has accelerated the fragmentation of the urban form, weakening the connection between residential and employment areas. This has an impact on the distribution of infrastructure including transport network, with the more peripheral areas that are appearing within the Bangalore Metropolitan Area becoming more isolated and having much lower road densities. Figure 9 shows the main transport networks in the Bangalore Metropolitan Area.

Source: Authors.

Figure 9: Main Transport Networks in Bangalore Metropolitan Area

Source: OpenStreetMap. http://www.openstreetmap.org

The results of the analysis of spatial metrics in the Bangalore Metropolitan Area are in Table 4. Urban areas (impervious surfaces) occupy only 8.6% of the total area of the metropolitan region, indicating that most of the territory is composed of pervious surfaces (such as vacant space, natural areas, and agricultural areas).

The results of analysis of shape complexity (irregularity and geometry) vary. The metropolitan area is classified as low for shape irregularity (SHAPE). This means that the urban areas in Figure 8 have linear and simple forms, indicating a tendency


Table 4: Spatial Characterization of the Bangalore Metropolitan RegionDescription Unit Range Measure Value Classification

Metropolitan Area Square kilometers 8,010

Percentage of class (PLAND) Percent 0 < PLAND ≦ 100 Area 8.6 Low

Shape index distribution (SHAPE) 1 ≤ SHAPE ≤ ∞ Shape Irregularity 1.5 Low

Related circumscribing circle (CIRCLE) 0 < CIRCLE < 1 Geometry 0.6 Medium

Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 0.8 High

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 872 Medium-high

Spat

ial m

etric

Source: Authors.

toward a coherent urban form. The geometry of the urban areas (CIRCLE) is classified as medium, which indicates that despite being somewhat coherent, the urban areas tend to be elongated. The fragmentation of the urban form (PD) is classified as high, which means that the Bangalore Metropolitan Area includes a large number of small urban areas, in addition to central Bangalore. This can be the result

of the geography of the area, such as the numerous lakes that characterize the metropolitan area, but it may also be due to of fragmentation of the landscape by strong zoning policies. Finally, the nearest neighbor distance (ENN) metric was classified medium-high, showing that the urban form of Bangalore tends to be dispersed.

17Bangkok

4.2 Bangkok

The Bangkok Metropolitan Administration is responsible for area-wide functions, such as urban and regional planning, water and sewerage, transport and traffic, drainage and flood control, and environmental protection, because its area-wide nature, size, and scale demand regional cooperative action (Laquian 2005). Mayoralties have autonomy over functions such as waste collection, cleaning and maintenance of local roads, running of day care centers, nurseries and preschool facilities, tax collection, and levying of service fees and charges. Metropolitan mayors are elected, increasing their power and influence.

Bangkok—Thailand’s capital—is situated along the banks of the Chao Phraya River, and is one of Asia’s commercial and transport hubs (Siemens 2011). It is one of the world’s most popular tourist destinations and home to all of Thailand’s major financial institutions. The city also serves as the regional headquarters of numerous multinational companies.

In 2000, Bangkok Metropolitan Region had a population of 9.4 million, representing 15% of the population of Thailand, and a density of 1,200 inhabitants per km2 (Appendix). The metropolis had 6.4 million workers and a gross domestic product (GDP) per capita of $17,000 measured at purchasing power parity. Bangkok’s GDP represented half of national GDP. The sectors that contributed most to regional GDP in the assessment year were services (64%) and manufacturing (29%).

Most of Bangkok’s population was employed in the service sector (36%), agriculture and mining (34%), the biomass products industries (12%), and the machinery and equipment sector (8%). The employment structure varies according to the city area. Commercial, financial, and service sectors are highly concentrated in central Bangkok. Middle

Bangkok (the consolidated urban area) hosts production, commercial, and service activities; while manufacturing dominates the peripheral areas of the metropolis. Despite the spatial dominance of manufacturing in the suburbs and parts of the consolidated urban area, the proportion of workers employed in manufacturing decreased from 67% in 1990 to 49% in 2000, while the share of the service sector increased in both areas.

The rapid increase in Bangkok’s population—from 9.4 million in 2000 to 14.6 million in 2010—contributed to a decrease in the quality of infrastructure and services provision. It also increased the city’s poverty index because most immigrants from the rural areas had low levels of education and income, and poor housing conditions. In 2000, slums accounted for about 1.0 million residents, and were located mainly in the center and consolidated urban area of Bangkok (Choiejit et al. 2005).

The direct material input (DMI) of the Bangkok Metropolitan Area was 211.9 million tons in 2000. The city’s domestic material consumption (DMC) was estimated at 170.6 million tons—about 37.2% of Thailand’s DMC. This corresponds to a per capita figure of 18.1 tons for Bangkok, compared to an average of 7.5 tons per capita for Thailand as a whole in the same year (Figure 10).

Figure 10: Domestic Material Consumption per Capita of Thailand and Bangkok, 2000


DMC

per c

apita

(t/c

ap)

Thailand Bangkok


The DMI of Bangkok Metropolitan Area was composed mainly of nonmetallic minerals, totaling 85.8 million tons (40% of the DMI); biomass, totaling 64.0 million tons (30%); and fossil fuels, totaling 46.7 million tons (22%) (Figure 11).

The main subcategory of nonmetallic minerals that entered in Bangkok was stone (NM4), representing 88% of total nonmetallic minerals. The most significant biomass categories were agricultural biomass (BM1) (63%), wood (BM6) (12%), and unspecified biomass (BM8) (11%). Low-ash fuels (FF1), accounted for 60% of all fossil fuels. Together, these five subcategories of materials accounted for 75% of the DMI of the Bangkok Metropolitan Area.

Almost all of the materials were imported either from outside the country or from other areas of Thailand. Only 0.9% of the DMI was extracted from the Bangkok Metropolitan Area, and this consisted exclusively of biomass.

Figure 11: Direct Material Input of Bangkok, Disaggregated, 2000


DMI (

kt)

Excluding fossil fuels, 48% of the materials consumed within the urban area in 2000 are estimated to have been disposed of as wastes in the same year, while 48% are expected to be converted to wastes after 35 years. Figure 12 shows the waste production by type in 2000 (Figure 12a) and in the following 50 years

(Figure 12b stemming from the materials consumed in 2000 (footnote 6). The materials accumulated within the urban area are nonmetallic minerals, mainly used for construction.


Figure 12: Waste Production in Bangkok (a) by Waste Type in 2000; and (b) in the Following 50 Years, Stemming from

the Materials Consumed in 2000


Figure 13: Direct Material Input per Capita of Thailand and Bangkok, by End Use, 2000

Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

DMC

per c

apita

(t/c

ap)

Thailand Bangkok

The consumption of materials by the economic sectors of Bangkok is significantly different from that of the country as a whole (Figure 13). Of the materials that pass through the urban area, 19% (41.3 million tons) are not consumed there, but are exported to the rest of the country or to other countries. By comparison, Thailand only exports about 14% of its DMI. The main end uses of the materials consumed in the urban area are gross fixed capital formation (GFCF) (25% of DMI), the manufacture of biomass products (12%), and utilities (9%).

(a) (b)

Low-ashFuels

Stone

NonspecifiedBiomass

Wood

AgriculturalBiomass

FF MM NM BM CF O

19Bangkok

The urban metabolism of Bangkok, illustrated in Figure 15, shows that biomass is the main type of material used for the production of biomass-related products (87%), the final consumption of households and government (74%), and services (49%). For utilities, fossil fuels account for 71% of the materials used. Nonmetallic minerals are mainly used for GFCF, with 58% of all nonmetallic minerals

and accounting for 95% of all materials used for this purpose. The exports of Bangkok consist mainly of fossil fuels (41%), biomass (28%), and nonmetallic minerals (20%). Figure 15 provides a more detailed picture of the urban metabolism of Bangkok, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, GFCF, and exports.

BangkokDirect Material Input 211.9 million tons

Figure 14: Urban Metabolism of Bangkok, Aggregated, 2000

Source: Authors.



20

Figu

re 1

5: C

ompl

ete

Urb

an M

etab

olis

m o

f Ban

gkok

, 200

0

Bang

kok

Dire

ct M

ater

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21

1.9

mill

ion

tons

Sour

ce: A

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rs.

BM1

– A

gric

ultu

ral b

iom

ass

BM2

– A

nim

al b

iom

ass

BM3

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extil

e bi

omas

sBM

4 –

Oils

and

fats

BM5

– S

ugar

sBM

6 –

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dsBM

7 –

Pap

er a

nd b

oard

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– U

nspe

cifie

d bi

omas

sCF

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Alc

ohol

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2

– Ch

emic

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ph

arm

aceu

tical

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3

– Fe

rtiliz

ers a

nd p

estic

ides

FF1

–

Low

ash

fuel

sFF

2

– H

igh

ash

fuel

sFF

3

– Lu

brifi

cant

s, o

ils

an

d so

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tsFF

4

– Pl

astic

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rubb

ers

MM

1 –

Iron

, ste

el a

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ng

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rrous

met

als

MM

2 –

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ht m

etal

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M3

– N

onfe

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vy m

etal

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M4

– S

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etal

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M5

– N

ucle

ar fu

els

MM

6 –

Pre

ciou

s met

als

NM

1 –

Sand

NM

2 –

Cem

ent

NM

3 –

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yN

M4

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tone

NM

5 -

Oth

ers

O1

–

Non

spec

ified

O2

–

Liqu

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S01

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nd fi

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Min

ing a

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S03

– F

ood

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ucts

, bev

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nd to

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4 –

Tex

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, tex

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S05

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S06

– P

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g

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s

an

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Che

mic

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hem

ical

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duct

sS0

9 –

Rub

ber a

nd p

last

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cts

S10

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ther

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min

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pro

duct

sS1

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Bas

ic m

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Fabr

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ex

cept

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S23

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and

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ss fi

xed

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tal f

orm

atio

n

21Bangkok

Figure 16: Bangkok Metropolitan Area Land Use

Source: Authors.

Figure 17: Main Transport Networks in Bangkok Metropolitan Area


The high level of consumption for GFCF can be attributed to the economic growth and spatial expansion that Bangkok has been experiencing. Examples include the construction of the Bangkok Metropolitan Rapid Transit and the beginning of the construction of the Bangkok Art and Culture Centre in 2000, due to the increase in tourism and financial services, and the significant size of the city’s manufacturing activities. The consumption of materials by the manufacturing sector mainly supports the transformation of products for export. Good transport networks are required to move the materials from one industry to the other and also from the metropolitan area to other parts in the country.

Bangkok experienced rapid expansion and dispersion during 1994–2002 (Angel 2007). The urban core area grew substantially along axes of transport and development, increasing the density along those axes and filling the vacant areas between them. The built area has grown more through densification than by expansion, as seen by the reduction in open space in the urban area. Figure 16 illustrates the spatial distribution of land use in the Bangkok Metropolitan Area. Current trends suggest that future development could lead to the dispersion of the urban area of Bangkok.

Urban growth is traditionally driven by economic growth and the accompanying opportunities for employment and investment. Most cities in developing countries tend to discover the challenges resulting from urbanization rather than planning and preparing for the process. Choiejit et al. (2005) identify some of the problems that arise from unplanned urban development. These include degradation of agricultural areas (and thus of the ecological structure of the metropolitan area); high intensity of land use on the edge of both sides of land transport routes, creating super-blocks with low accessibility; low interconnection between the main networks and urban areas; mobility issues, especially for those living in outer Bangkok; congestion; and lack of public transport. Figure 17 shows the main transport networks in Bangkok Metropolitan Area.

The spatial metrics of the Bangkok Metropolitan Area are in Table 5. The proportion of the urban area (impervious surface) within the total area of the metropolitan region (PLAND) is 18.8%, corresponding to a classification of low. This implies that most of the territory is composed of pervious surfaces, such as vacant space, natural areas, and agricultural areas.


The metropolitan area is classified as medium-high for shape irregularity (SHAPE). This means that the urban areas have complex forms, indicating a continuous dispersion of the urban form through the creation of new branches at a distance from the main urban areas. The geometry of the urban areas (CIRCLE) is classified as medium-high, showing that the urban form is elongated, tending toward sprawl. The fragmentation of the urban form (PD) is classified as medium-low, implying a medium

number of urban areas with a significant continuous area. In the case of Bangkok, this may be the result of having one main urban center and four medium-sized cities (Khlong Luang, Nakhon Pathom, Nonthaburi, and Samut Prakan). Finally, the nearest neighbor distance (ENN) metric was classified as medium, a result that reinforces the suggestion that Bangkok is tending toward dispersion, and reflects the existing connection between different urban areas.

Table 5: Spatial Characterization of the Bangkok Metropolitan RegionDescription Unit Range Measure Value Classification



Shape index distribution (SHAPE) 1 ≤ SHAPE ≤ ∞ Shape Irregularity 2.2 Medium-high

Related circumscribing circle (CIRCLE) 0 < CIRCLE < 1 Geometry 0.7 Medium-high

Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 0.2 Medium-low

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 637 Medium

Spat

ial m

etric

Source: Authors.

23Ho Chi Minh City

4.3 Ho Chi Minh City

The hierarchic levels of the political–administrative system in Viet Nam are determined according to the principles of democratic centralization, with each level in principle being subordinated to the higher one. Ho Chi Minh City (HCMC) is the top level, followed by the urban districts, the subdistricts, and finally neighborhood groups and cells (Wust et al. 2002).

Public planning and administration in Viet Nam are dominated by hierarchical and formalistic elements of the “end-of-pipe” type—end result centered planning rather than process and context oriented. Current master planning methods tend to be rigid and nonparticipatory, and generally discourage formal nonstate contributions in urban planning (Waibel et al. 2007).

HCMC Metropolitan Area had a population of 13.5 million in 2000, representing 17% of the population of Viet Nam, and a density of 440 inhabitants per km2 (Appendix)—the lowest of the six Asian metropolitan areas being studied. The metropolis had 6.1 million workers and a gross domestic product (GDP) per capita of $3,400 measured at purchasing power parity. HCMC’s GDP represented almost 40% of national GDP. The sectors that contributed most to regional GDP in the assessment year were services (34%), agriculture and mining (34%), and manufacturing (24%). Most of the population of HCMC was employed in services (45%), agriculture and mining (26%), and the biomass products industries (16%).

HCMC is one of Viet Nam’s largest hubs for trade, services, science, technology, and culture (UN-Habitat 2010). The city’s economy has grown steadily, with an average annual rate of 5.2% during 1986–1990—the initial phase of doi moi (renewal). The metropolitan area contributes to 30% of national manufacturing output, 40% of its export value, 30% of national tax revenues, and 25% of retail and service

Figure 18: Domestic Material Consumption per Capita of Viet Nam and Ho Chi Minh City, 2000


DMC

per c

apita

(t/c

ap)

Viet Nam Ho Chi Minh City

trade volume (UN-Habitat 2010). The state-owned sector retains a major role in the city’s economy, but private enterprises have also been thriving since 2000, with more than 50,000 new businesses being established. These businesses contribute 30% of HCMC’s total industrial output and 78% of retail sales, and have created hundreds of thousands of jobs. An additional 1,600 enterprises are backed by foreign investment, contributing 19% of HCMC’s production of goods and services.

Factory compounds and industrial zones were built in the periphery of the city, and have triggered migration from rural to urban areas and from the core of the city to its periphery. A total of 15 industrial parks were established in suburban areas, which attracted migrants mainly to the suburbs (Tan et al. 2010). This has resulted in increasing construction of households in these areas, which is being accompanied by the growth of new residential areas for the middle- and upper-class citizens between the city core and the urban periphery.

In 2000, the direct material input (DMI) of HCMC Metropolitan Area was 52.1 million tons. Domestic material consumption (DMC) was estimated at about 48.4 million tons, or 17.2% of Viet Nam’s DMC. This corresponds to a per capita figure of 3.6 tons for HCMC, which is the same as the national figure in the same year (Figure 18).

24 Urban Metabolism of Six Asian Cities 24 Urban Metabolism of Six Asian Cities

The DMI of the HCMC metropolitan area was composed mainly of biomass, totaling 22.6 million tons (43% of the DMI); nonmetallic minerals, totaling 22.1 million tons (42%); and fossil fuels, totaling 5.2 million tons (10%) (Figure 19). The main subcategories of biomass entering HCMC were agricultural biomass (BM1) (55%), wood (BM6) (23%), and unspecified biomass (BM8) (18%). The most significant nonmetallic minerals were stone (NM4), representing 77% of the total nonmetallic minerals; and sand (NM1), representing 22%. Fossil fuels were mainly of the low-ash type (FF1), accounting for 55% of all fossil fuels. Together, these six subcategories of materials accounted for 89% of the DMI of HCMC.

Most of the materials were imported either from outside the country or from other areas of the country. About 23% of the DMI was extracted from the HCMC Metropolitan Area, and this consisted exclusively of biomass.

Figure 19: Direct Material Input of Ho Chi Minh City, Disaggregated, 2000


DMI (

kt)

Excluding fossil fuels, 62% of the materials consumed within the urban area in 2000 are estimated to have been disposed of as wastes in the same year, while 36% are expected to be converted to residues after 35 years. Figure 20 shows the waste production by waste type in 2000 (Figure 20a) and in the following 50 years (Figure 20b) stemming from the materials consumed since 2000 (footnote 6).


Figure 20: Waste Production in Ho Chi Minh City (a) by Waste Type in 2000; and (b) in the Following 50 Years,

Stemming from the Materials Consumed in 2000


Figure 21: Direct Material Input per Capita of Viet Nam and Ho Chi Minh City, by End Use, 2000

Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

DMC

per c

apita

(t/c

ap)

Viet Nam Ho Chi Minh City

The consumption of materials within the HCMC economy is similar to that of Viet Nam as a whole (Figure 21). Of the materials that pass through HCMC, 7% (11.8 million tons) are exported to the rest of the country or to other countries, compared to 9% of DMI for Viet Nam. The main end uses of the materials consumed in the urban area are the final consumption of households and government (25%), gross fixed capital formation (GFCF) (20%), and agriculture and mining (16%). The large consumption for GFCF suggests that HCMC was experiencing substantial infrastructure growth at the time, possibly due to significant population increase and economic growth.

(a) (b)

Low-ashFuels

StoneNonspecifiedBiomass

Wood

AgriculturalBiomass

Sand

FF MM NM BM CF O

25Ho Chi Minh City

The urban metabolism of HCMC, illustrated in Figure 22, shows that biomass accounts for 91% of material used for the final consumption of households and government. For services, however, biomass only accounts for 14% of final consumption, nonmetallic minerals account for 66%, and fossil fuels account for 14% of the materials used in this sector. Nonmetallic

minerals account for 91% of all materials used for used for GFCF, and 43% of all nonmetallic minerals are used for this purpose. Figure 23 provides a more detailed picture of the urban metabolism of HCMC, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, GFCF, and exports.

Ho Chi Minh CityDirect Material Input 52.1 million tons

Figure 22: Urban Metabolism of Ho Chi Minh City, Aggregated, 2000

Source: Authors.



26 26

Figu

re 2

3: C

ompl

ete

Urb

an M

etab

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m o

f Ho

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, 200

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Ho

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Sour

ce: A

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– A

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ral b

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BM2

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ass

BM3

– T

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omas

sBM

4 –

Oils

and

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BM5

– S

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sBM

6 –

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–

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cant

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astic

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6 –

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NM

1 –

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NM

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tone

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5 -

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–

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–

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– A

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– F

ood

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ucts

, bev

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4 –

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, tex

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, lea

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tsS1

8 –

Mot

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raile

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nd s

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9 –

Oth

er tr

ansp

ort e

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men

tS2

0 –

Man

ufac

turin

g n.e

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ecyc

ling

S21

– E

lect

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, gas

and

wat

er su

pply

S22

– C

onst

ruct

ion

S23

– W

hole

sale

and

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il tra

de; r

epai

rsS2

4 –

Hot

els a

nd re

stau

rant

sS2

5 –

Tra

nspo

rt an

d st

orag

eS2

6 –

Pos

t and

tele

com

mun

icat

ions

S27

– F

inan

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nd in

sura

nce

S28

– R

eal e

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e ac

tiviti

esS2

9 –

Ren

ting o

f mac

hine

ry a

nd e

quip

men

tS3

0 –

Com

pute

r and

rela

ted

activ

ities

S31

– R

esea

rch

and

deve

lopm

ent

S32

– O

ther

Bus

ines

s Act

iviti

esS3

3 –

Pub

lic a

dmin

. and

def

ence

;

co

mpu

lsory

soci

al se

curit

yS3

4 –

Edu

catio

nS3

5 –

Hea

lth a

nd so

cial

wor

kS3

6 –

Oth

er c

omm

unity

, soc

ial

and

pers

onal

serv

ices

SEX

P –

Expo

rtsSF

C –

Fin

al c

onsu

mpt

ion

SGFC

F –

Gro

ss fi

xed

capi

tal f

orm

atio

n

27Ho Chi Minh City

Figure 24: Ho Chi Minh City Metropolitan Area Land Use

Source: Authors.

Figure 25: Main Transport Networks in Ho Chi Minh City Metropolitan Area


The high level of material consumption for GFCF can be attributed to the economic growth and spatial expansion that have accompanied HCMC’s development as an economic and cultural hub in Viet Nam. The large metropolitan area includes significant agricultural development, which supports the important biomass-related production activities that take place in the city. The increasing spatial distribution, coupled with the economic growth due to the increase in IT services and exports, suggests that the metropolitan area will continue to require significant amounts of nonmetallic minerals to build the transport networks and waste collection systems that will support this development.

HCMC has a fragmented urban form, as can be seen in Figure 24. The mega-urban region has an extensive land footprint and contains more than 10 million inhabitants, many of whom live in precarious conditions on illegally occupied land. Nonetheless, the core city has been experiencing de-densification, not only because of population migration from the inner city areas to the periphery, but also due to the functional reconfiguration of the urban core into a business district with the construction of businesses, services, and leisure activities. This restructuring has been led by both the state and local companies, but also multinational corporations, to foster economic development.

Figure 25 illustrates the main transport networks in HCMC Metropolitan Area.

The spatial distribution of the HCMC Metropolitan Area suggests a need to promote urban concentration and modify the planning approach for the hinterland and city periphery. A revised approach would involve developing residential areas and services near the industrial parks and promoting a public transport network to complement the existing one, preferably with an ecological corridor to prevent further sprawl.

The spatial metrics of the HCMC Metropolitan Area are in Table 6. A value of 8.2% was obtained for the proportion of the urban area (impervious surface) within the total area of the metropolitan region (PLAND). This corresponds to a classification of low, implying that most of the territory is composed of pervious surface, such as vacant space, and natural and agricultural areas.

The metropolitan area is classified as high for irregularity of the shape (SHAPE). This means that the urban areas have complex forms, indicating a continuous dispersion of the urban form through the creation of new branches of urban areas at some distance from the main urban areas. The geometry of the urban areas (CIRCLE) is classified as medium-

28 Urban Metabolism of Six Asian Cities 28 Urban Metabolism of Six Asian Cities

Table 6: Spatial Characterization of the Ho Chi Minh City Metropolitan Area Description Unit Range Measure Value Classification

Metropolitan Area Square kilometers 8.2 Low

Percentage of class (PLAND) Percent 0 < PLAND ≦ 100 Area 2.8 High


Related circumscribing circle (CIRCLE) 0 < CIRCLE < 1 Geometry 0.1 Low

Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 1,849 High

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 1,849 High

Spat

ial m

etric

Source: Authors.

high, showing that the urban form is elongated and tends toward sprawl. The low classification for fragmentation of the urban form (PD) indicates that there are a few urban areas with high average surface areas. In the case of HCMC, this may be because there is one main urban center with a large

continuous surface area, and numerous small urban centers. Finally, the nearest neighbor distance (ENN) metric was classified as high, demonstrating that the urban form of HCMC Metropolitan Area is highly dispersed and tends toward sprawl.

29Metro Manila

4.4 Metro Manila

There are five levels of governance in Metro Manila (Ruble et al. 2001). At the highest level is the central government, which exercises considerable authority and power because Metro Manila is the national capital. All local officials are under the supervision of the President of the Philippines through the Department of the Interior and Local Government. Statutes, including the issuance of city charters, are the prerogatives of the House of Representatives and the Senate. Most development activities in the National Capital Region are carried out by central government departments. National roads and bridges, for example, are built and maintained by the Department of Public Works and Highways. The financing of major infrastructure projects is under the authority of the Presidential Adviser on Flagship Programs and Projects. The Philippine National Police is in charge of all police forces. The central government controls the financial purse strings as budgets of all local government units are reviewed by the Department of Budget and Management.

At the metropolitan level, governance is exercised by the Metropolitan Manila Development Authority (MMDA). The MMDA in its present form was established in 1995 and is charged with comprehensive planning, land use control, urban renewal, traffic and transport management, solid waste disposal, flood control and drainage, engineering, and public safety. Policy making in the MMDA is vested in a council made up of all the 17 mayors of the local government units. The executive functions of planning and management are under specific departments reporting to the MMDA chair. The MMDA is a “special development and administrative” unit under the direct supervision of the President of the Philippines and engages in “planning, monitoring, and coordinating activities subject to the proviso that it does not infringe on the autonomy of local government units on issues that are purely local in nature” (Ruble et al. 2001, p. 78).

The lowest level of governance in Metro Manila is the barangay (neighborhood unit). A barangay may

be made up of 100–1,000 households residing within a specified territory.

Metro Manila had a population of about 10 million in 2000, representing 13% of the national population, and a density of 16,000 inhabitants per km2 (Appendix)—the highest of the six metropolitan areas in the country. The metropolis had 3.6 million workers in 2000 and a gross domestic product (GDP) per capita of $6,300 measured at purchasing power parity. Metro Manila’s GDP represented 35% of national GDP. The sectors that contributed most to regional GDP in the assessment year were services (67%) and manufacturing (27%). The service sector employed 74% of the population of Metro Manila, while the machinery and equipment sector accounted for 8% and the construction sector absorbed 7%.

Metro Manila is the major manufacturing location in the Philippines, which is the second-largest employer after the wholesale and retail rectors (Lambino 2010). Food and tobacco processing also employ a substantial portion of the work force. With its excellent protected harbor, Metro Manila also serves as the nation’s principal port. It is also the financial and business center of the Philippines. The widespread use of English gives the city an advantage in international trade not shared by many Asian cities. Metro Manila exhibits the problems of many large cities, however. It is overpopulated, and municipal agencies struggle to keep up with the demand for services.

The central areas of the metropolis have high levels of poverty. The Philippine Institute for Development Studies estimates that 4.0 million of the 11.5 million residents in the National Capital Region live in slums (Cox 2011).

In 2000, the direct material input (DMI) of Metro Manila was 73.6 million tons. Domestic material consumption (DMC) was estimated at about 68.2 million tons, or 19.4% of national DMC. This corresponds to a per capita figure of 6.9 tons in Metro

30 Urban Metabolism of Six Asian Cities 30 Urban Metabolism of Six Asian Cities 30 Urban Metabolism of Six Asian Cities

Figure 27: Direct Material Input of Metro Manila, Disaggregated, 2000


DMI (

kt)

Low-ashFuels

Stone

NonspecifiedBiomass

Wood

AgriculturalBiomass


Figure 29: Direct Material Input per Capita of the Philippines and Metro Manila, by End Use, 2000

DMC

per c

apita

(t/c

ap)

Figure 28: Waste Production in Metro Manila (a) by Waste Type in 2000; and (b) in the Following 50 Years,



Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

(a) (b)

Figure 26: Domestic Material Consumption per Capita of the Philippines and Metro Manila, 2000


DMC

per c

apita

(t/c

ap)

Philippines Metro Manila

Manila and 4.6 tons per capita for the Philippines overall (Figure 26).

The DMI of Metro Manila was composed mainly of nonmetallic minerals, totaling 34.4 million tons (47%), and biomass amounting to 28.4 million tons (39%) (Figure 27). The main subcategories of nonmetallic minerals entering the metropolis were sand (NM1), representing 55% of nonmetallic minerals; and stone (NM4), accounting for 42%. The principal categories of biomass were agricultural biomass (BM1), representing 48%; wood (BM6), accounting for 24%; and unspecified biomass (BM8), representing 16%. Together, these five subcategories of materials accounted for 79% of the DMI of Metro Manila.

Almost all of the materials were imported from either outside the country or from other areas of the

The consumption of materials within Metro Manila is slightly different from that of the Philippines as a whole (Figure 29). About 7% (5.4 million tons) of the materials that pass through the urban area are not

country. Only 0.2% of DMI was extracted from Metro Manila, and this consisted exclusively of biomass.

Excluding fossil fuels, 80% of the materials consumed within the urban area in 2000 are estimated to have been disposed of as wastes within the same year, while 18% are expected to be converted to wastes after 35 years. Figure 28 shows the waste production by waste type in 2000 (Figure 28a) and in the following 50 years (Figure 28b) stemming from the materials consumed in 2000 (footnote 6).

Sand

Philippines Metro ManilaFF MM NM BM CF O

31Metro Manila

The urban metabolism of Metro Manila, illustrated in Figure 30, shows that the use of nonmetallic minerals is mainly concentrated in the chemicals and fuel products industry (41% of nonmetallic minerals), gross fixed capital formation (GFCF) (14%), and services, (10%). Nonmetallic minerals account for 84% of all materials used in the chemicals and fuel products industry. Biomass is the main type of material used for the production of biomass-related

Metro ManilaDirect Material Input 73.6 Million tons

Figure 30: Urban Metabolism of Metro Manila, Aggregated, 2000

Source: Authors.

consumed there, but are exported to the rest of the country or to other countries. The Philippines as a whole exports only about 5% of its DMI. The main end uses of the materials consumed in the urban area are in the biomass products industry (28%), the chemicals and fuel products industry (23%), and the final consumption of households and government (11%). Consumption in the biomass products industry was mainly for food processing.



32 32 32

Figu

re 3

1: C

ompl

ete

Urb

an M

etab

olis

m o

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, 200

0

Met

ro M

anila

Dire

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ial I

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73

.6 m

illio

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Sour

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utho

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BM1

– A

gric

ultu

ral b

iom

ass

BM2

– A

nim

al b

iom

ass

BM3

– T

extil

e bi

omas

sBM

4 –

Oils

and

fats

BM5

– S

ugar

sBM

6 –

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7 –

Pap

er a

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BM8

– U

nspe

cifie

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sCF

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2

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FF1

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Low

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2

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igh

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3

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an

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4

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astic

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MM

1 –

Iron

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als

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2 –

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M3

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M4

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MM

6 –

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NM

1 –

Sand

NM

2 –

Cem

ent

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3 –

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tone

NM

5 -

Oth

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S01

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– P

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mic

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pro

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s

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S21

– E

lect

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and

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S22

– C

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ion

S23

– W

hole

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de; r

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4 –

Hot

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rant

sS2

5 –

Tra

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Pos

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S27

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S28

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Ren

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0 –

Com

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S31

– R

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S32

– O

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;

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4 –

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5 –

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6 –

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omm

unity

, soc

ial

and

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onal

serv

ices

SEX

P –

Expo

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C –

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ion

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F –

Gro

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capi

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orm

atio

n

33Metro Manila

Figure 32: Manila Metropolitan Area Land Use

Source: Authors.

Figure 33: Main Transport Networks in Manila Metropolitan Area


The moderate level of consumption for GFCF can be attributed to the fact that the metropolitan area is already saturated and continued growth is being directed to the areas surrounding Metro Manila. The urban metabolism analysis shows the importance of commerce and services, which account for a significant share of final material consumption. Furthermore, the high share of exports and consumption in the production of biomass-related products are in line with the manufacturing that occurs in Metro Manila and its role as a major port.

Metro Manila is one of the largest urban areas in the world. Due to an intense suburbanization process, the suburban population quickly exceeded the population of the core city. However, despite this tendency, the core of Metro Manila has one of the highest population densities in the world, with an average of 45,000 inhabitants per km2, and densities of up to 70,000 inhabitants per km2. In the inner suburbs, the density is 18,000 inhabitants per km2, while the outer suburbs average 11,000 inhabitants per km2 (Cox 2011).

Figure 32 identifies three land use classes in Metro Manila: industrial area, built-up area, and water. The development of Metro Manila shows that the metropolitan area is undergoing polycentric development, due to investment in centers of agglomeration of employment (particularly in the service sector) in the outer areas, together with the dispersion of residential neighborhoods through a complex transport network of roads and railways, as shown in Figure 33. The transport infrastructure

The spatial metrics of Metro Manila are in Table 7. A value of 81.6% was obtained for the proportion of the urban area (impervious surface) within the total area of the metropolitan region (PLAND). This corresponds to a classification of high, implying that most of the territory is composed of impervious surface, including continuous or discontinuous urban fabric, industrial or commercial units, roads, port areas, and airports.

products (86%), and in the final consumption of households and government (83%). For services, however, biomass only accounts for 22%, while nonmetallic minerals account for 53% and fossil fuels constitute 17%. Figure 31 provides a more detailed picture of the urban metabolism of Metro Manila, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, GFCF, and exports.

is struggling to address these rapid changes in the urban landscape, and traffic congestion tends to worsen as the population in Metro Manila continues to increase.


Table 7: Spatial Characterization of the Manila Metropolitan Area Description Unit Range Measure Value Classification

Metropolitan Area Square kilometers 620

Percentage of class (PLAND) Percent 0 < PLAND ≦ 100 Area 81.6 High

Shape index distribution (SHAPE) 1 ≤ SHAPE ≤ ∞ Shape Irregularity 2.0 Medium


Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 0.1 Low

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 298 Low

Spat

ial m

etric

Source: Authors.

The metropolitan area is classified as medium for shape irregularity (SHAPE). This means that the urban areas in Figure 32 have forms of medium complexity, indicating that some branches are far from the main urban areas. The geometry of the urban areas (CIRCLE) is classified as medium-high, showing that the urban form is elongated and tends to expand beyond the limits of the metropolitan area. The fragmentation of the urban form (PD) is low,

suggesting that there is a small number of urban areas with a high average surface area. In the case of Metro Manila, this may reflect the dominance of urban or impervious surfaces in the metropolitan area. Finally, the nearest neighbor distance (ENN) metric is also classified as low, which demonstrates that the urban form of Metro Manila inside its boundaries is highly concentrated.

35 Seoul Metropolitan Area

4.5 Seoul Metropolitan Area

The Republic of Korea has a two-tier system of local government. There are nine provinces (do); six metropolitan cities; and Seoul, which is considered a special city, managed by the Seoul Metropolitan Government. Seoul’s administrative tiers are subdivided into units (gu), which are further subdivided into neighborhoods (dong). The next level is subdivided into villages (tong). There are 522 dong and 13,787 tong (Seoul Metropolitan Government 2011). Seoul is the county’s political, economic, intellectual, and cultural center (Siemens 2011). The city is home to most of the country’s big corporations, major financial institutions, top universities, and the national media. The overall makeup of the metropolitan government is hierarchal, with the mayor overseeing many lower organizations under its control.

The Seoul Metropolitan Area had a population of 21 million in 2000, representing 46% of the country’s population, and a density of about 1,800 inhabitants per km2 (Appendix). The metropolis had almost 10 million workers and a gross domestic product (GDP) per capita of $17,700 measured at purchasing power parity. Seoul’s GDP represented almost 50% of national GDP. The sectors that contribute most to regional GDP are services (67%) and manufacturing (24%). The majority of the employment in Seoul is in services (67%), the machinery and equipment sector (11%), and construction (8%).

While service industries account for a significant share of Seoul’s economic output, Gyeonggi-do—the province surrounding Seoul—has a high concentration of manufacturing industries, including electronics and textiles.

In 2000, the direct material input (DMI) of the Seoul Metropolitan Area was 413.1 million tons. Domestic material consumption (DMC) was estimated at

Figure 34: Domestic Material Consumption per Capita of the Republic of Korea and Seoul, 2000


DMC

per c

apita

(t/c

ap)

about 365.9 million tons, or 46.1% of the national figure. This corresponds to a per capita figure of 17.2 tons for Seoul, which was the same as the average for the country as a whole (Figure 34).

The DMI of the Seoul Metropolitan Area was composed mainly of nonmetallic minerals, totaling 210.9 million tons (51% of DMI); fossil fuels, totaling 123.3 million tons (30%); and metallic minerals, amounting to 36.8 million tons (10%) (Figure 35). The main subcategory of nonmetallic minerals entering Seoul was stone (NM4), representing 96% of the total nonmetallic minerals. The most significant fossil fuels were low-ash fuels (FF1) (48%), lubricants and oils and solvents (FF3) (19%), and plastics and rubbers (FF4) (19%). Most of the metallic minerals used were iron, steel alloying metals, and ferrous metals (MM1) (81%). Together, these five subcategories of materials accounted for 83% of the DMI of the Seoul Metropolitan Area.

Almost all of the materials were imported either from outside of the country or from other areas of the country. Only 1.3% of DMI was extracted from the Seoul Metropolitan Area, and this consisted mainly of biomass (84%), nonmetallic minerals (7%), and chemicals and fertilizers (6%).

Republic of Korea Seoul


Excluding fossil fuels, 29% of the materials consumed within the urban area in 2000 are estimated to have been disposed of as wastes in the same year, while 67% are expected to be converted to residues after 35 years. Figure 36 shows the waste production by waste type in 2000 (Figure 36a) and in the following 50 years (Figure 36b) stemming from the materials consumed in 2000 (footnote 6).

Figure 35: Direct Material Input of Seoul, Disaggregated, 2000


DMI (

kt)

Plastics and Rubbers

Lubricants,Oils and Solvents

The consumption of materials within Seoul’s economy is almost the same as that of the country as a whole (Figure 37). Of the materials that pass


Figure 37: Direct Material Input per Capita of the Republic of Korea and Seoul, by End Use, 2000

DMC

per c

apita

(t/c

ap)

The urban metabolism of Seoul, illustrated in Figure 38, shows that nonmetallic minerals are the main type of material used for construction (97%), GFCF (92%), and machinery and equipment (79%). The main types of materials exported are fossil fuels (60%) and metallic minerals (20%).

In the service sector, nonmetallic minerals account for 48% of the materials used in this sector, while fossil fuels account for 36%, and metallic minerals 10%. The use of fossil fuels is relatively evenly spread across the economy, with 26% for the final consumption of households and government, 23% going for exports, and 20% for services. Figure 39 provides a more detailed picture of the urban metabolism of Seoul, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, GFCF, and exports.

Figure 36: Waste Production in Seoul (a) by Waste Type in 2000; and (b) in the Following 50 Years,



Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

(a) (b)

through the urban area, 11% (47.2 million tons) are not consumed there, but are exported to the rest of the country or to other countries, while the Republic of Korea in general exports about 12% of its DMI. The main end uses of the materials consumed in the urban area are gross fixed capital formation (GFCF) (21%), services (16%), and final consumption of households and government (16%).

Low-ashFuels

Ferrousmetals

Stone

FF MM NM BM CF O

Republic of Korea Seoul


SeoulDirect Material Input 413.1 million tons

Figure 38: Urban Metabolism of Seoul, Aggregated, 2000

Source: Authors.



38

Figu

re 3

9: C

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an M

etab

olis

m o

f Seo

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Mat

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n to

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– A

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ultu

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BM2

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BM3

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extil

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4 –

Oils

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BM5

– S

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6 –

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7 –

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–

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2

– H

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3

– Lu

brifi

cant

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an

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4

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astic

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MM

1 –

Iron

, ste

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als

MM

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etal

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M4

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– N

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MM

6 –

Pre

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s met

als

NM

1 –

Sand

NM

2 –

Cem

ent

NM

3 –

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M4

– S

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NM

5 -

Oth

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O1

–

Non

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ified

O2

–

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ids

S01

– A

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ultu

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nd fi

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gS0

2 –

Min

ing a

nd q

uarry

ing

S03

– F

ood

prod

ucts

, bev

erag

es a

nd to

bacc

oS0

4 –

Tex

tiles

, tex

tile

prod

ucts

, lea

ther

an

d fo

otw

ear

S05

– W

ood

and

prod

ucts

of w

ood

and

cork

S06

– P

ulp,

pap

er, p

aper

pro

duct

s, p

rintin

g

an

d pu

blish

ing

S07

– C

oke,

refin

ed p

etro

leum

pro

duct

s

an

d nu

clea

r fue

lS0

8 –

Che

mic

als a

nd c

hem

ical

pro

duct

sS0

9 –

Rub

ber a

nd p

last

ics p

rodu

cts

S10

– O

ther

non

met

allic

min

eral

pro

duct

sS1

1 –

Bas

ic m

etal

sS1

2 –

Fabr

icat

ed m

etal

pro

duct

s

ex

cept

mac

hine

ry a

nd e

quip

men

tS1

3 –

Mac

hine

ry a

nd e

quip

men

t n.e

.c

S14

– O

ffice

, acc

ount

ing a

nd

com

putin

g mac

hine

ryS1

5 –

Ele

ctric

al m

achi

nery

and

app

arat

us n

.e.c

S16

– R

adio

, tel

evisi

on a

nd c

omm

unic

atio

n

eq

uipm

ent

S17

– M

edic

al, p

reci

sion

and

optic

al in

stru

men

tsS1

8 –

Mot

or ve

hicl

es, t

raile

rs a

nd s

emitr

aile

rsS1

9 –

Oth

er tr

ansp

ort e

quip

men

tS2

0 –

Man

ufac

turin

g n.e

.c; r

ecyc

ling

S21

– E

lect

ricity

, gas

and

wat

er su

pply

S22

– C

onst

ruct

ion

S23

– W

hole

sale

and

reta

il tra

de; r

epai

rsS2

4 –

Hot

els a

nd re

stau

rant

sS2

5 –

Tra

nspo

rt an

d st

orag

eS2

6 –

Pos

t and

tele

com

mun

icat

ions

S27

– F

inan

ce a

nd in

sura

nce

S28

– R

eal e

stat

e ac

tiviti

esS2

9 –

Ren

ting o

f mac

hine

ry a

nd e

quip

men

tS3

0 –

Com

pute

r and

rela

ted

activ

ities

S31

– R

esea

rch

and

deve

lopm

ent

S32

– O

ther

Bus

ines

s Act

iviti

esS3

3 –

Pub

lic a

dmin

. and

def

ence

;

co

mpu

lsory

soci

al se

curit

yS3

4 –

Edu

catio

nS3

5 –

Hea

lth a

nd so

cial

wor

kS3

6 –

Oth

er c

omm

unity

, soc

ial

and

pers

onal

serv

ices

SEX

P –

Expo

rtsSF

C –

Fin

al c

onsu

mpt

ion

SGFC

F –

Gro

ss fi

xed

capi

tal f

orm

atio

n


Figure 40: Seoul Metropolitan Area Land Use

Source: Authors.

Figure 41: Main Road Networks in Seoul Metropolitan Area


The high level of consumption associated with GFCF can be attributed to the creation of new satellite towns and the growth of transport networks, such as works on the Seoul Metropolitan Subway and the construction of Incheon International Airport, which were ongoing in 2000.

The importance of commerce and services can be seen in the urban metabolism analysis, with this sector accounting for a significant share of final material consumption. The considerable size of the biomass products and machinery and equipment sectors is also in line with the importance of manufacturing in the Seoul Metropolitan Area.

The extreme density of the city center and local government initiatives to promote the development of new areas for expansion have progressively stopped population increase in the core city and begun a process of dispersion of the urban form toward suburban centers in the periphery. Most heavy manufacturing has located along the southeast coast of the Korean Peninsula because of the easy access to deep-water ports. Other factories and plants in Seoul have expanded into the surrounding area because of land scarcity and the high price of industrial property in the city (Kim and Han et al. 2012). Figure 40 identifies three land use classes in Seoul Metropolitan Area: industrial area, built-up area, and water.

The creation of new satellite towns has resulted in a polycentric urban form, supported by the growth of transport networks (Figure 41). These developments enable the population to commute from the outer areas to the industrial areas close to the water.

The spatial metrics of the Seoul Metropolitan Area are in Table 8. A value of 16.5% was obtained for the proportion of urban area (impervious surface) within the total area of the metropolitan region (PLAND). This corresponds to a classification of low, implying most of the territory is composed of pervious surfaces, such as arable land, permanent crops, forest, and open spaces with little or no vegetation.

The metropolitan area is classified as medium for shape irregularity (SHAPE). This means that the urban areas in Figure 40 have forms of medium complexity, indicating that some of the branches are far from the main urban areas. The geometry of the urban areas (CIRCLE) is classified as medium-high, showing that the urban form is elongated and tending toward dispersion, particularly in the province of Gyeonggi-do. The fragmentation of the urban form (PD) is classified as high, reflecting the large number of urban areas distributed across the territory. Finally, the nearest neighbor distance (ENN) metric is classified as medium-low, demonstrating


Table 8: Spatial Characterization of the Seoul Metropolitan AreaDescription Unit Range Measure Value Classification



Shape index distribution (SHAPE) 1 ≤ SHAPE ≤ ∞ Shape Irregularity 2.0 Medium


Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 0.8 High

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 495 Medium-low

Spat

ial m

etric

Source: Authors.

that the urban form of the metropolitan area is not very dispersed in the provinces of Incheon and

Seoul relative to the dispersion of the urban form in Gyeonggi-do.

41Shanghai Metropolitan Area

4.6 Shanghai Metropolitan Area

Shanghai is one of the four municipalities in the People’s Republic of China (PRC) that have an administrative status similar to that of a province (Kam Ng and Hills 2003). Unlike other big cities in the world, Shanghai, under the leadership of the Communist Party of the PRC, has parallel national party and government administrative apparatuses. The central government created single unitary governments headed by appointed mayors (Laquian 2005). Shanghai has a party secretary and a mayor, both of which are appointed by the standing committee of the Community Party. Economic planning is often influenced by political (state) considerations. The Shanghai Municipal People’s Congress with its standing committee is the policy making authority, and the Shanghai Municipal People’s Government is its executive arm.

Shanghai has unified governance structures with jurisdictions over city regions. The physical boundaries of these urban agglomerations have been expanded to absorb towns, cities, and villages on the urban periphery (Laquian 2005). Area-wide services, such as water and sewerage, transport, and solid waste disposal, were placed under a single metropolitan government.

Districts in the metropolitan area have limited powers, but the metropolitan governments have greater authority and larger financial resources.

The Shanghai Metropolitan Area had a population of 16.4 million in 2000, representing 1% of the PRC population, and a density of about 2,600 inhabitants per km2 (Appendix). The metropolis had 6.7 million workers in 2000 and a gross domestic product (GDP) per capita of $8,830 measured at purchasing power parity. Shanghai’s GDP represented 5% of national GDP. The sectors that contribute most to regional GDP are services (52%) and manufacturing (37%). Most of the population of Shanghai was employed in services (54%), the machinery and equipment sector

(15%), the biomass products industries (9%), and agriculture and mining (8%).

In 2005, Shanghai became the world’s largest cargo port (UN-Habitat 2010). By 2010, the city accounted for 17% of the country’s port cargo handling volume, 25% of its total exports, and 13% of financial revenues. On top of port facilities, Shanghai has expanded its role in finance and banking, and as a location for corporate headquarters. These developments are fuelling demand for a highly educated, forward-looking workforce. Manufacturing, Shanghai’s largest economic sector, accounts for 36% of the output of the metropolitan area. Business and financial services are Shanghai’s second-largest sector (17%), and account for 13% of the PRC’s total output in the sector. Local nonmarket services (education, health care, administrative services, and government) contributed 40% to employment growth in Shanghai (BI 2011).

In 2000, the direct material input (DMI) of the Shanghai Metropolitan Area was 228.6 million tons. Direct material consumption (DMC) was estimated at about 221.5 million tons, or 2.5% of that of the PRC. This corresponds to a per capita figure of 13.5 tons for Shanghai, compared to an average of 7.2 tons per capita for the PRC as a whole in the same year (Figure 42).

Figure 42: Domestic Material Consumption per Capita of the People’s Republic of China and Shanghai, 2000


DMC

per c

apita

(t/c

ap)

PRC Shanghai


The DMI of the Shanghai Metropolitan Area was composed mainly of nonmetallic minerals, totaling 128.7 million tons (56%); biomass, totaling 65.0 million tons (28%), fossil fuels, totaling 20.7 million tons (9%); and metallic minerals, totaling 13.6 million tons (6%) (Figure 43). Stone (NM4) accounted for 99% of nonmetallic minerals entering Shanghai. The most significant biomass categories were unspecified biomass (BM8) (60%) and agricultural biomass (BM1), (30%). Low-ash fuels (FF1) comprised 79% of fossil fuels used; while 75% of metallic minerals used consisted of Iron, steel alloying metals, and ferrous metals (MM1). Together, these five subcategories of materials accounted for 93% of the DMI of the Shanghai Metropolitan Area.

Almost all of the materials were imported either from outside of the country or from other areas of the country. Only 3.7% of the DMI was extracted from the Shanghai Metropolitan Area, and this consisted exclusively of biomass.

Figure 43: Direct Material Input of Shanghai, Disaggregated, 2000


DMI (

kt)

Low-ashFuels Ferrous

metals

Stone

NonspecifiedBiomass

AgriculturalBiomass

Excluding fossil fuels, 39% of the materials that were consumed within the urban area in 2000 are estimated to have been disposed of as residues within the same year, while 57% are expected to be converted to residues after 35 years. Figure 44 shows the waste production by waste type in 2000 (Figure 44a) and in the following 50 years (Figure 44b) stemming from the materials consumed in 2000 (footnote 6).


Figure 44: Waste Production in Shanghai (a) by Waste Type in 2000; and (b) in the Following 50 Years,



Figure 45: Direct Material Input per Capita of the People’s Republic of China and Shanghai,

by End Use, 2000

Was

te p

rodu

ction

(kt)

Was

te p

rodu

ction

(kt)

DMC

per c

apita

(t/c

ap)

PRC Shanghai

The consumption of materials within the economic sector of Shanghai is significantly different from that of the PRC as a whole (Figure 45). Only 3% (7.1 million tons) the materials that pass through the urban area are not consumed there, and are exported to the rest of the country or to other countries. The PRC also exports about 3% of its DMI. The main end uses of the materials consumed in the urban area are gross fixed capital formation (GFCF) (51%), final consumption of households and government (15%), and consumption for services (9%). The large consumption for GFCF suggests that Shanghai was experiencing infrastructure growth at that time, possibly due to its high rate of population increase, which averaged 3% per year.

(a) (b)

FF MM NM BM CF O


The urban metabolism of Shanghai, illustrated in Figure 46, shows that nonmetallic minerals are mainly used for GFCF, and make up 89% of the materials used for this purpose. Biomass (71%) and fossil fuels (16%) are the main types of materials used for the final consumption of households and government.

In the service sector, biomass accounts for 53% of materials consumed, nonmetallic minerals account

for 27%, fossil fuels 15%, and metallic minerals 5%. The use of biomass is spread across the economy, with 38% for the final consumption of households and government, 22% for the production of biomass products, and 17% for services. Figure 47 provides a more detailed picture of the urban metabolism of Shanghai, matching the 28 subcategories of materials with the 36 economic sectors, final consumption, GFCF, and exports.

ShanghaiDirect Material Input 228.6 million tons

Figure 46: Urban Metabolism of Shanghai, Aggregated, 2000

Source: Authors.



44

Figu

re 4

7: C

ompl

ete

Urb

an M

etab

olis

m o

f Sha

ngha

i, 20

00

Shan

ghai

Dire

ct M

ater

ial I

nput

22

8.6

mill

ion

tons

Sour

ce: A

utho

rs.

BM1

– A

gric

ultu

ral b

iom

ass

BM2

– A

nim

al b

iom

ass

BM3

– T

extil

e bi

omas

sBM

4 –

Oils

and

fats

BM5

– S

ugar

sBM

6 –

Woo

dsBM

7 –

Pap

er a

nd b

oard

BM8

– U

nspe

cifie

d bi

omas

sCF

1 –

Alc

ohol

sCF

2

– Ch

emic

als a

nd

ph

arm

aceu

tical

sCF

3

– Fe

rtiliz

ers a

nd p

estic

ides

FF1

–

Low

ash

fuel

sFF

2

– H

igh

ash

fuel

sFF

3

– Lu

brifi

cant

s, o

ils

an

d so

lven

tsFF

4

– Pl

astic

s and

rubb

ers

MM

1 –

Iron

, ste

el a

lloyi

ng

an

d fe

rrous

met

als

MM

2 –

Lig

ht m

etal

sM

M3

– N

onfe

rrous

hea

vy m

etal

sM

M4

– S

peci

al m

etal

sM

M5

– N

ucle

ar fu

els

MM

6 –

Pre

ciou

s met

als

NM

1 –

Sand

NM

2 –

Cem

ent

NM

3 –

Cla

yN

M4

– S

tone

NM

5 -

Oth

ers

O1

–

Non

spec

ified

O2

–

Liqu

ids

S01

– A

gric

ultu

re, h

untin

g, fo

rest

ry a

nd fi

shin

gS0

2 –

Min

ing a

nd q

uarry

ing

S03

– F

ood

prod

ucts

, bev

erag

es a

nd to

bacc

oS0

4 –

Tex

tiles

, tex

tile

prod

ucts

, lea

ther

an

d fo

otw

ear

S05

– W

ood

and

prod

ucts

of w

ood

and

cork

S06

– P

ulp,

pap

er, p

aper

pro

duct

s, p

rintin

g

an

d pu

blish

ing

S07

– C

oke,

refin

ed p

etro

leum

pro

duct

s

an

d nu

clea

r fue

lS0

8 –

Che

mic

als a

nd c

hem

ical

pro

duct

sS0

9 –

Rub

ber a

nd p

last

ics p

rodu

cts

S10

– O

ther

non

met

allic

min

eral

pro

duct

sS1

1 –

Bas

ic m

etal

sS1

2 –

Fabr

icat

ed m

etal

pro

duct

s

ex

cept

mac

hine

ry a

nd e

quip

men

tS1

3 –

Mac

hine

ry a

nd e

quip

men

t n.e

.c

S14

– O

ffice

, acc

ount

ing a

nd

com

putin

g mac

hine

ryS1

5 –

Ele

ctric

al m

achi

nery

and

app

arat

us n

.e.c

S16

– R

adio

, tel

evisi

on a

nd c

omm

unic

atio

n

eq

uipm

ent

S17

– M

edic

al, p

reci

sion

and

optic

al in

stru

men

tsS1

8 –

Mot

or ve

hicl

es, t

raile

rs a

nd s

emitr

aile

rsS1

9 –

Oth

er tr

ansp

ort e

quip

men

tS2

0 –

Man

ufac

turin

g n.e

.c; r

ecyc

ling

S21

– E

lect

ricity

, gas

and

wat

er su

pply

S22

– C

onst

ruct

ion

S23

– W

hole

sale

and

reta

il tra

de; r

epai

rsS2

4 –

Hot

els a

nd re

stau

rant

sS2

5 –

Tra

nspo

rt an

d st

orag

eS2

6 –

Pos

t and

tele

com

mun

icat

ions

S27

– F

inan

ce a

nd in

sura

nce

S28

– R

eal e

stat

e ac

tiviti

esS2

9 –

Ren

ting o

f mac

hine

ry a

nd e

quip

men

tS3

0 –

Com

pute

r and

rela

ted

activ

ities

S31

– R

esea

rch

and

deve

lopm

ent

S32

– O

ther

Bus

ines

s Act

iviti

esS3

3 –

Pub

lic a

dmin

. and

def

ence

;

co

mpu

lsory

soci

al se

curit

yS3

4 –

Edu

catio

nS3

5 –

Hea

lth a

nd so

cial

wor

kS3

6 –

Oth

er c

omm

unity

, soc

ial

and

pers

onal

serv

ices

SEX

P –

Expo

rtsSF

C –

Fin

al c

onsu

mpt

ion

SGFC

F –

Gro

ss fi

xed

capi

tal f

orm

atio

n


Figure 48: Shanghai Metropolitan Area Land Use

Source: Authors.

Figure 49: Main Transport Networks in Shanghai Metropolitan Area


The high level of consumption for GFCF can be attributed to Shanghai’s urban policy of renovating the core city while relocating employment to the suburbs, mainly through the creation of new satellite towns and industrial parks, and the huge parallel investment in infrastructure.

The importance of services can be seen in the urban metabolism analysis, with this sector accounting for a significant share of final material consumption. Despite being one of the world’s most important ports, Shanghai’s share of exports is small, suggesting that the port is mainly used for crossing flows. As such, the port is mainly a gateway for entry and exit of products to and from the PRC in general and not for Shanghai in particular.

Shanghai has experienced a tremendous transformation in land use from a rural to urban, while the urban fringe has steadily advanced outward into the surrounding agricultural land (Yin et al. 2011). Recently, the urban policy of Shanghai has shifted to urban renewal of the core city and relocation of employment to the suburbs in order to foster a higher quality of life in the center. The development of satellite towns, industrial parks, and infrastructure has been accompanied by a large influx of migrants from the rural areas. Figure 48 identifies three land use classes in the Shanghai Metropolitan Area: industrial area, built-up area, and water.

The urban area has grown at the expense of farmland, green land, water bodies, and bare land; and farmland has, in turn, expanded at the expense of green land in order to meet the huge food needs of the growing population (Yin et al. 2011). Future urban expansion is expected to take place along the main traffic routes between the center and the surrounding towns. This extension of the urban area in the center and subcenters of the metropolitan area is creating a progressively greater distance between the city center and its surroundings. Figure 49 shows the main transport networks in the Shanghai Metropolitan Area.

The spatial metrics of the Shanghai Metropolitan Area are in Table 9. A value of 33.0% was obtained for the proportion of the urban area (impervious surface) within the total area of the metropolitan region (PLAND). This corresponds to a classification of medium-low, implying that most of the territory is composed of pervious surfaces, such as arable land, permanent crops, forest, and open spaces with little or no vegetation.

The metropolitan area is classified as medium for shape irregularity (SHAPE). This means that the urban areas in Figure 48 have forms of medium complexity, indicating that some of the branches are

46 Urban Metabolism of Six Asian Cities 46 Urban Metabolism of Six Asian Cities 46 Urban Metabolism of Six Asian Cities 46 Urban Metabolism of Six Asian Cities

Table 9: Spatial Characterization of the Shanghai Metropolitan Area Description Unit Range Measure Value Classification

Metropolitan Area Square kilometers 33.0 Medium-low

Percentage of class (PLAND) Percent 0 < PLAND ≦ 100 Area 2.1 Medium


Related circumscribing circle (CIRCLE) 0 < CIRCLE < 1 Geometry 0.2 Medium-low

Patch density (PD) Number per 100 hectares PD > 0 Fragmentation 434 Medium-low

Euclidean nearest neighbor distance (ENN) Meters ENN > 0 Dispersion 434 Medium-low

Spat

ial m

etric

Source: Authors.

far from the main urban areas. The geometry of the urban areas (CIRCLE) is classified as high, implying an elongated urban form and a tendency toward dispersion, mainly in provinces with low proportions of pervious surface.

The fragmentation of the urban form (PD) is classified as medium-low. This means that there are a medium number of urban areas with an average

surface area, reflecting the duality between the less fragmented urban core and the developing urban areas in the periphery of the urban area. Finally, the nearest neighbor distance (ENN) metric is classified as medium-low, demonstrating that while the urban form of the Shanghai Metropolitan Area is not very dispersed in the provinces of Baoshan, Jiading, Minhang, Pudong, and Shanghai, the remaining provinces tend to have low levels of compactness.

47

Table 10: Spatial Metrics of the Six Metropolitan Regions Metropolitan Region Area Shape Irregularity Geometry Fragmentation Dispersion

Bangalore Low Low Medium High Medium-highBangkok Low Medium-high Medium-high Medium-low MediumHCMC Low High Medium-high Low High

Metro Manila High Medium Medium-high Low LowSeoul Low Medium Medium-high High Medium-low

Shanghai Medium-low Medium Medium-high Medium-low Medium-low

5. Comparative Assessment of the Metropolitan Metabolisms

5.1 Urban Spatial Metrics

The six metropolitan regions differ significantly in area and form (Figure 50 and Table 10). The spatial metrics of the urban areas indicate similar overall

Figure 50: Water and Built-Up Area of the Six Metropolitan Areas

Scale: 1:1700000. Source: Authors.

HCMC = Ho Chi Minh City.Source: Authors.

tendencies in urban form. Historical trends suggest they all start to spread with a greater or lesser intensity toward their administrative boundaries, and, in the case of Metro Manila, even exceed such limits.


Four of the six metropolitan areas are characterized by the presence of a significant central urban core that continues to attract the majority of activities and population. This means that most of the metropolitan area consists of pervious surface, such as vacant space, and natural and agricultural areas. Two exceptions are Metro Manila, which is already exceeding the limits of its administrative area, resulting in a high proportion of built-up area; and Shanghai, where the rate of expansion of the urban area is very high (indicating a tendency for dispersion).

The metropolitan area of Ho Chi Minh City (HCMC) stands out because of its more irregular pattern of urban areas that comprise each metropolitan area (shape irregularity). This is the result of an urban core that spreads out through the road and rail networks in a great distance from the urban core. Bangkok also presents considerable shape irregularity, indicating a tendency toward a less formal planning policy. By contrast, Bangalore has a low level of shape irregularity, which signifies great coherence in urban design.

All six metropolitan areas tend to be elongated rather than concentrated, which means that that they all present a significant tendency toward dispersion.

The metropolitan areas are varied in terms of fragmentation of their urban form. HCMC and Metro Manila present low levels of fragmentation. In the case of HCMC, this is because the urban centers remain well demarcated; while for Metro Manila, the very dense concentration of population has led to the merging of various urban areas. Bangalore and Seoul are highly fragmented. In Bangalore, this is because of the large number of small urban areas that are spread across the rural areas of the metropolitan area. In Seoul it is the result of natural constraints7 and the growth of other central business districts to the south and west of the city (such as Ansan, Anyang,

Goyang, Incheon, Puchon, Seongnam, Shihung, and Suwon).

Four of the six cities are classified as medium for dispersion, which can be explained by the small or medium-sized urban areas dispersed across their territory. Only Metro Manila is classified as low, because of the large concentration of impervious surfaces throughout its administrative territory. The urban form of HCMC is highly dispersed, containing many small urban areas spread over a great distance via the rail and road networks. This pattern accords with the linear development urban typology, with average densities adjacent to the networks, low densities between the networks, and high densities at network intersections.

The following sections compare the six Asian metropolitan areas with two European ones: Lisbon and Paris. The material flow accounting of these two additional metropolitan areas used the methodology described in this document.

The analysis confirms that metropolitan areas tend to be highly dependent on imported materials to support their economic activities and final consumption. In five of the metropolitan areas more than 90% of the materials used are imported (Bangkok and Metro Manila depend almost exclusively on imports). Only in the case of HCMC is a significant amount of the materials used (23%) extracted locally.

This means these areas are heavily dependent on sources they cannot control or manage directly—a situation that may threaten their resilience. The dependency affects the various economic sectors of the urban economy differently and varies according to the type of material.

Figure 51 provides a breakdown of the direct material input (DMI) per capita for production and consumption in the eight metropolitan areas. The

5.2 Assessing Urban Material Dependency

7 Of the total built-up area of 605 km2, 237 km2 cannot be used for development due to geographical features (Kim et al. 2012).

49

Others

Chemicals and fertilizers

Biomass

Nonmetallic minerals

Metallic minerals

Fossil fuels

Bang

alor

e

25

20

15

10

5

0

Bang

kok

Ho

Chi M

inh

Met

ro M

anila

Seou

l

Shan

ghai

Lisb

on

Paris

Comparative Assessment of the Metropolitan Metabolisms

DMI per capita ranges from 3.8 tons in HCMC to 23.8 tons in Paris, with an average of 13.9 tons for the eight cities. In most of the cities, nonmetallic materials are the largest category of material inputs, followed by biomass. Bangkok’s DMI is noticeably higher than other cities of similar income levels. This is attributable to the city’s predominance in national manufacturing capacity, which results in a very high share of materials being exported. Manufacturing has been observed to be a much more material-

Figure 51: Direct Material Input per Capita of the Eight Metropolitan Areas, by Material Category, 2000

Figure 52: Cumulative Share of the 28 Material Subcategories in the Eight Metropolitan Areas, 2000

DMI = direct material input, t/cap = tons per capita.Source: Authors.

DMI = direct material input.Source: Authors.

Bangalore

Bangkok

Ho Chi Minh City

Metro Manila

Seoul

Shanghai

Lisbon

Paris

intensive sector than services, which dominate in the urban areas in this study.

To better assess the diversity of material dependency in the eight urban areas, Figure 52 illustrates the cumulative share of total material input by number of material subcategories. For each urban area, the subcategories are ordered from highest to lowest by their share of total material input.

100%

90%

80%

70%

60%

50%

40%

30%

20%

10

0%1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28


The results show that a few subcategories account for a significant share of total material input in all urban areas. Bangkok and Lisbon have the most diverse set of material input subcategories, while Shanghai has the least diverse set. This can be observed from the number of subcategories that make up 90% of the material input:

• Lisbon: 11 subcategories—4 fossil fuels, 1metallic minerals, 3 nonmetallic minerals, and 3 biomass

• Bangkok: 11 subcategories—4 fossil fuels, 2metallic minerals, 2 nonmetallic minerals, and 3 biomass

• Paris:9subcategories—3fossilfuels,1metallicminerals, 3 nonmetallic minerals, and 2 biomass

• Metro Manila: 9 subcategories—1 fossil fuels,2 metallic minerals, 2 nonmetallic minerals, and 4 biomass

• Seoul:7subcategories—4fossilfuels,1metallicminerals, 1 nonmetallic minerals, and 1 biomass

• HCMC: 7 subcategories—2 fossil fuels, 2nonmetallic minerals, and 3 biomass

• Bangalore: 6 subcategories—1 fossil fuels, 1metallic minerals, 1 nonmetallic minerals, and 3 biomass

• Shanghai: 5 subcategories—1 fossil fuels, 1nonmetallic mineral, 1 metallic minerals, and 2 biomass

While a larger range of material inputs may indicate a diversified economy, the results may also indicate that some urban areas lack material-intensive industries, which may explain why no type of material is dominant. An assessment of the share of material input by economic sector supports this analysis (Figure 53).

Lisbon and Paris present very similar shares of material use by economic sector, with manufacturing sector accounting for 24%–27% and services making up 15%–18%. Final consumption is 19% and gross fixed capital formation (GFCF) is 17%–22%. These metropolitan areas also have the second- and fourth-highest shares of materials for export (12% in Lisbon and 10% in Paris).

Figure 53: Share of Metropolitan Direct Material Input by End Use, 2000


Construction and utilities

Exports

Final consumption

GFCF

Manufacturing

Services

Paris

Lisbon

Shanghai

Seoul

Metro Manila

Ho Chi Minh City

Bangkok

Bangalore

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Source: Authors.

51Comparative Assessment of the Metropolitan Metabolisms

Figure 54: Share of the Direct Material Input of the Manufacturing Sector, by Industry Type, 2000

Biomass products

Chemicals and fuel products

Construction products

Machinery and equipment

Metallic products

Paris

Lisbon

Shanghai

Seoul

Metro Manila

Ho Chi Minh City

Bangkok

Bangalore

Source: Authors.

In Shanghai, exports represent only 3% of the total material use in the metropolitan area, while GFCF accounts for 51%—the largest share of all the areas. GFCF absorbs 25% of materials in Bangkok and 21% in Seoul. Furthermore, Bangkok, Lisbon, Paris, and Seoul have the highest share of materials used in the construction and utilities sectors, ranging from 5% in Lisbon to 11% in Bangkok.

The high share of material use for GFCF and construction in these four metropolitan areas may have significant impacts on their future management of end-of-life materials (particularly in the case of Shanghai), because it mainly includes materials with long life spans that stay with the city for several years (as material stock), being converted into waste progressively.

The areas with the highest share of material use by the manufacturing sector are Metro Manila (61%), Bangalore (43%), and Bangkok (30%). With the exception of Bangkok, these are also the economies that have the lowest share of materials consumed by GFCF.

The share of material use by agriculture and mining is low, accounting for 16% in HCMC, and varying from a low of 0.1% in Metro Manila to a high of 3.7% in Lisbon in the remaining areas. This is not surprising as the areas under analysis are much more densely populated than the rest of country, with little space available for sourcing raw materials such as biomass or minerals.

The results show that two-thirds of the Asian metropolitan economies assessed—Bangalore, Bangkok, HCMC, and Metro Manila—were focused on producing tradable products; while Seoul, Shanghai, and the Western European metropolitan areas were more centered on services and nontradable products.

The use of materials by the different industries is a proxy for their importance in the overall material use of the regions assessed. Figure 54 shows the gross share (inclusive of materials that flow through a sector, but are ultimately consumed in another sector or exported) of each industrial sector.

0% 20% 40% 60% 80% 100%


Generally, the construction products industry is very significant in the urban areas under analysis, being responsible for more than 30% of the products used by manufactures in all the metropolitan areas and as much as 72% in Shanghai and 62% in HCMC. Metro Manila is an exception, with a share of only 23%.

The next most material-intensive industries are biomass products (e.g., 39% in Bangalore, 33% in Metro Manila, and 31% in HCMC) and chemicals and fuels (e.g., 32% in Seoul, 30% in Metro Manila, and 22% in Paris). The metallic products and machinery and equipment industries are less material-intensive, with shares 2%–9%.

As can be seen from Figure 54, HCMC and Shanghai had the least diversified manufacturing sectors because of the high concentration of materials use in one industry (construction products); while Metro Manila had the most diversified economy in terms of the relative importance of different industries.

The material intensity of an economy is measured by the amount of materials (e.g., tons) that an economy uses to produce one unit of monetary output (e.g., $). Figure 55 compares the level of output (gross domestic product [GDP] per capita) and material use (DMI per capita) of the metropolitan areas, classifying the cities into four quadrants. Clockwise, the second and third quadrants represent the most affluent economies (Bangkok, Seoul, Lisbon, and Paris) and the first and the fourth quadrants contain the less affluent economies (Bangalore, HCMC, Metro Manila, and Shanghai).

Figure 55 shows an apparent trend of higher material usage being associated with higher outputs. This observation needs to be confirmed with a larger sample of cities. However, material intensities vary considerably, as the following examples illustrate:

Figure 55: Material Use per Capita versus Product per Capita in the Eight Metropolitan Areas, 2000

DMI = direct material input, GDP = gross domestic product, t/cap = tons per capita.Source: Authors.

5.3 Material Intensity of the Economy

DM

I per

cap

ita (t

/cap

)

GDP per capita (thousand international US$ / cap)

Shanghai

25

20

15

10

5

0

0 5 10 15 20 25 30 35 40

Manila

Bangkok

SeoulParis

Lisbonavg median

Ho Chi Minh

Bangalore


• to achieve 40% more output per capita thanMetro Manila, Shanghai has to use almost 100% more materials per capita;

• with almost the same material use per capita,Lisbon achieves almost triple the output of Shanghai;

• foralmostthesameoutputs,Bangaloreusesanadditional 3 tons of materials per capita than HCMC, and Bangkok uses an additional 3 tons per capita than Seoul;

• with almost the same use of materials percapita, Paris produces $19,000 per capita more than Bangkok at purchasing power parity; and

• consumingonly0.2tonsofmaterialspercapitamore than Bangalore, Metro Manila produces almost triple Bangkok’s output.

Lisbon, Paris, and Seoul are more productive, in material terms, than the others. An understanding

Figure 56: Material and Economic Structure of Selected Metropolitan Areas, 2000

Source: Authors.


Construction

Manufacturing

Utilities

Services

GDP DMI GDP DMI GDP DMI

Ho Chi Minh CIty Seoul Singapore

700000

600000

500000

400000

300000

200000

100000

0

of the evolution of these parameters over 2001–2010 would be very helpful in assessing the degree of materialization or dematerialization of these economies.

The comparison of the material and monetary structures of these metropolitan economies may provide some clues about their material productivity. The examples of HCMC, Seoul, and Shanghai are shown in Figure 56.

Seoul, the most affluent of the three metropolitan areas, has the highest share of material use by the manufacturing (62%) and services (12%) sectors. However, 67% of its GDP is produced by services, compared with 52% in Shanghai and 34% in HCMC. Seoul also has the most productive service sector in material terms. In HCMC, the least affluent, the share of the primary sector is higher in material and monetary terms. In the case of Shanghai, the material productivity of the construction sector is very low and is often designated a nonproductive investment.


The metropolitan areas assessed may be categorized into different typologies based on their use of materials (Figure 57) and the material consumption of the economic sectors (Figure 58).

In terms of the typologies based on the categories of materials used:

• type1(Bangalore)hasaveryhighshareofbiomassconsumption, and low shares of nonmetallic and fossil fuel consumption;

5.4 Typifying Urban Typologies

Figure 57: Material Use Typologies of the Eight Metropolitan Areas, 2000

Source: Authors.

• type2areas(Lisbon,Paris,andShanghai)presenthigh shares of nonmetallic minerals, medium shares of biomass, and low shares of fossil fuel consumption;

• type3areas(Bangkok,HCMC,andMetroManila)present medium-to-high shares of biomass and nonmetallic minerals, and low shares of fossil fuels; and

• type 4 (Seoul) has a high share of nonmetallicminerals, medium-to-high share of fossil fuels, and low share of biomass.


Figure 58: Material Consumption Typologies of the Eight Metropolitan Areas, 2000

Source: Authors.

In terms of the typologies based on the consumption of materials by economic sector:

• type1areas(BangaloreandMetroManila)haveahigh share of materials consumed by manufacturing, and low shares of materials for final consumption and GFCF;

• type 2 areas (Lisbon, Paris, and Seoul) present moderate shares of materials going to final consumption and GFCF, with services and manufacturing having nontrivial shares of consumption;

• type 3 (Bangkok) presents significant materialshares for both exports and manufacturing, and a low share for services; and

As can be seen from the analysis of the typologies by material type and consumption by sector, while some urban areas remain in the same typology in both assessments, others do not. Lisbon and Paris are in the same typologies, while the six Asian metropolitan areas are in different groups in both analyses. This suggests that more typologies might exist. However, they can only be identified by analyzing and comparing many more urban areas.

• type 4 areas (HCMC and Shanghai) have highshares of materials going for final consumption and GFCF, and low shares for services and manufacturing.

56

6. Contributions from Urban Metabolism

The streamlined urban metabolism method is a means of overcoming the lack of city-level data on material consumption and waste generation by using national input–output data and other available information such as national and regional extraction of raw materials.

This report demonstrates the potential of urban metabolism studies by providing a rigorous quantitative analysis of urbanization patterns. The main achievement of the preliminary results of this ongoing work is a better understanding of how the use of natural resources correlates with urban economic activities.

The assessment of the metabolism of economies provides important clues about their direct and indirect environmental impacts as a result of their use of natural resources. These include:

• thedirectimpactsofextraction(e.g.,impactsonthe natural environment of opencast mining); and

• the disruption of materials cycles associatedwith the introduction of compounds in unsurpassed volumes into the biosphere (e.g., carbon, phosphate, and heavy metals), or major movements of materials through the biosphere (e.g., nitrogen and phosphorus), or the loss of natural areas as a result of deforestation and erosion.

Other environmental impacts are associated with the use of natural resources, such as pesticides used in the production of food, and acidification caused by the combustion of fossil fuels.

The results of the method developed and described in this report support sustainable urbanization by providing information relevant to addressing key issues such as environmental quality, global warming, resilience, and environment–economy interactions.

A city’s size, urban form, and demand for resources determine the area required to provide water and nutrients to its inhabitants, and manage the city’s wastes to ensure the sustainability of the materials cycle (Cuchí et al. 2010).

The characterization of the spatial distribution of urban metabolism, its main drivers, and how it is related to critical urban infrastructures and technologies helps identify zones where the supporting infrastructure systems (energy supply, water supply, sanitation, and waste management) are heavily loaded, and possible synergies for improving these systems. In addition, it allows areas that should be the target of policy measures to be specified, and suggests how planning efforts can be coordinated to be more efficient, particularly to support urban strategies.

The information generated can be useful to urban planners for drawing general plans and making initial assessments. It can also assist in planning appropriate waste management facilities, understanding the use and allocation of scarce resources, and identifying economic activities that contribute most to greenhouse gas emissions and other pollution problems.

Moreover, while the models are useful for determining present material stocks and flows, they can also be used to simulate future changes in urban metabolism as a result of technological interventions or new policies. The models are particularly useful for identifying solutions to environmental issues beyond end-of-pipe approaches. A good example of this approach is the work performed by the Asian Development Bank in Kazakhstan and Uzbekistan under the Preparation of Sector Road Maps for Central and West Asia Project, where investment needs for technological solutions to urban waste management were thoroughly identified and

57Contributions from Urban Metabolism

accounted for in monetary terms with the objective of achieving an urban sustainable management in the next 40 years.

The application of the method can be extended to cover more urban areas. Combined with computations of material flow with other complementary data, and extending the analysis across time periods, it provides a systematic way of:

• calculating environmental pressure indicators,such as the ecological footprint or greenhouse gas emissions;

• measuringtheintensityandefficiencyofmaterialuse of economic activities, and the urban area’s dependence on externally sourced materials;

• uncovering the infrastructure needs for wastemanagement and the potential for establishing a circular economy; and

• benchmarking urban areas and defining urbantypologies.

Thus the urban metabolism framework allows a holistic assessment of critical parameters for sustainable urbanization (Figure 59).

Figure 59: Urban Metabolism Framework for Green Cities Parameters

GAV = gross added value, GDP = gross domestic product, IO = input–output.Source: Authors.


Environmental pressure indicators. The Ecological footprint of an urban area is calculated by computing the yield factors of the materials used in the urban economy. Greenhouse gas emissions are calculated by computing the carbon dioxide emission factors of the fossil fuels consumed and the incinerated wastes.

Material use intensity and resource efficiency. The total materials used by each economic activity represent its material intensity. This is a measure of the natural resource productivity of the activity when compared for different regions. Another measure of productivity is obtained by computing economic data with the material intensity (e.g., $/ton). The inverse of this ratio represents the resource efficiency of an urban economy or economic activity (ton/$).

Urban metabolism reveals the comparative resource intensity of urban areas in order to provide the most effective pathways toward resource efficiency and security of access for a diverse range of cities.

Waste management. Developing an urban circular economy requires investments in waste recovery and material exchanges between companies (industrial symbiosis). The potential for such strategies can be determined through material flow accounting and modeling with waste input–output tables.

The dynamics and type of investment in waste and product end-of-life processing infrastructures depend on waste production forecasts. An understanding of the dynamics of the material flows in an urban system is particularly relevant for predicting the need for waste management infrastructures, as their capacity over the coming decades will be based on stock models that represent inflows and outflows of different types of products and substances, considering the evolution and obsolescence of products displaced in the market (e.g., construction materials, metals from machinery and appliances, and plastics).

Benchmarking urban typologies. Replicating this work to cover a larger group of cities would allow the characterization of different urbanization patterns and their performance in key sustainability metrics. When evaluated against economic, climate, demographic, urban morphology, and governance data, urban metabolism indicators can characterize urban typologies and benchmark each city to the relative resource intensity of the economic sectors. This would be a valuable tool in learning how different development options can be taken as a reference to be adopted in the rapidly urbanizing context of Asia.

As shown through the analysis performed, metropolitan areas with different urban forms may present similar material use structures. However, further research is needed to identify which parameters are to be used for identifying different urban typologies. In addition, assessing the structure of resource consumption over time allows development models to be defined and enables forcasting of potential resource needs of transitional urban economies.

More in-depth research on urban metabolism can also ascertain the most effective design and technology choices for basic infrastructure for cities in diverse development contexts.8 Some investments are however necessary to complete such a study. First, cities need to begin the task of collecting and organizing urban resource data for use in short-, medium-, and long-term operation and planning. Second, urban metabolism can provide insight into alternative planning strategies that take greatest advantage of industrial symbiosis and colocating firms, substituting physical products and goods for urban services, and promoting the enhancement

8 Again, a good example of this approach is the work performed by the Asian Development Bank concerning Kazakhstan and Uzbekistan under the Preparation of Sector Road Maps for Central and West Asia Project, which involved members of the team that developed the current report.

59Contributions from Urban Metabolism

of recycling and “downcycling” 9 networks toward a comprehensive closing of urban material cycles.

In summary, urban metabolism as presented in this report may provide:

1. overall direction to planners, engineers, designers, and policy makers in the general assessment of the resource consumption behavior of urban areas;

2. an overall understanding of the interaction between urban socioeconomic and biogeochemical processes;

3. an accessible and agile tool for the assessment of a diverse range of urban resource issues;

9 Downcycling refers to the creation of new products from waste materials.

4. an accessible and agile tool to quantify the impact of green city initiatives in their early development stages;

5. insights into aspects of the fundamental resource consumption behavior of urban areas;

6. an approach for developing generalizing principles upon which a wide variety of cities can be modeled and assessed; and

7. an approach for developing a general typological scheme of cities based on distinct resource consumption profiles.

60

7. Conclusions

Urbanization has been a result and also a potent force of economic growth and development. By concentrating resources, information, and talent, agglomeration effects made cities engines of productivity.

The process of urbanization is projected to intensify as incomes grow across the developing world (ADB 2012). Urban areas will continue to expand and the number of people residing in urban centers will also grow. With this comes increasing awareness and concern about the negative externalities of urbanization that accompany the process—pollution, congestion, environmental degradation, and the sustainability of the process itself. How can societies reap the benefits of urbanization while minimizing the costs to the well-being of people and the environment?

Answering this question requires an understanding of the dynamics between the economy, resource consumption, and waste generation of urban areas. Examining these relationships requires a new set of tools that correlate the use of natural resources, economic activities, and consumption patterns.

This study responds to this challenge by developing a unique urban metabolism approach and applying it to six urban areas in Asia and two in Europe. The streamlined urban metabolism methodology allows the metabolism of an urban area to be quantified using publicly available national statistical data and scaling them down to an urban level, thereby overcoming previously insurmountable data limitations.

The application of the method to the six Asian cities provides a rigorous examination and quantitative analysis of urbanization patterns. The

main achievement of the preliminary results of this ongoing work is to provide a unique understanding of how natural resource uses correlate with urban economic activities. The results demonstrate the potential of urban metabolism to characterize urban typologies and, for each of them, to benchmark the relative resource intensity of the economic sectors. It can also be a valuable tool in assessing different development options in the context of rapid urbanization.

The material intensity of the economy is measured by the amount of materials it uses to produce one unit of monetary output. There is an apparent trend of higher material uses being associated with higher outputs, but material intensities vary considerably. For example, the economic output of Lisbon is almost triple that of Shanghai with approximately the same material use per capita; while for almost the same outputs, Bangalore uses an additional 3 tons of materials per capita than HCMC, and Bangkok uses an additional 3 tons of materials per capita than Seoul. Charting these parameters over 2001–2010 would be very helpful to gauge the degree of materialization or dematerialization of these economies.

This report points to a remarkable opportunity to cross the boundaries between economy and environment, and to establish strong and quantitative links between these dimensions at an urban level. This has the potential to make a major contribution to the design of sustainable urban systems and infrastructure that have been observed in this report.

The extension of this analysis to a wider set of urban areas across Asia, covering multiple urban typologies, has great potential to contribute to the development of sustainable urban areas around the world.

61

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9. Appendix

Tabl

e A

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of th

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Are

as

Are

a (k

m2 )

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Table A2: Regional Gross Domestic Product per Economic Activity, 2000 ($)

Sector Bangalore Bangkok HCMC Metro Manila Seoul ShanghaiAgriculture and

Mining 1,194 2,077 15,285 0 7,168 2,925

Manufacturing 5,125 47,129 11,026 17,028 91,530 53,769

Utilities 1,342 3,743 1,511 1,433 1,632 6,345

Construction 655 3,931 1,919 2,558 24,556 6,337

Commerce and services 11,017 103,301 15,393 41,756 251,862 75,528

Table A3: Employment Structure of the Urban Areas (number)

SectorBangalore* Bangkok HCMC Metro Manila Seoul Shanghai

2011 2011 2005 2001 2005 2005

Agriculture and mining 4,337 2,633,951 2,025,040 41,000 203,000 670,391

Biomass products 203,154 927,680 1,295,401 146,000 486,932 755,231

Chemicals and fuel products 28,948 270,870 153,180 109,500 257,641 380,399

Construction products 7,124 42,400 63,506 36,500 52,246 104,018

Metallic products 21,909 219,271 99,321 73,000 194,556 305,685

Machinery and equipment 92,959 593,670 417,700 292,000 1,232,625 1,323,239

Utilities 7,199 43,887 417,700 16,000 290,750 46,360

Construction 6,780 175,374 454,860 261,000 917,000 404,991

Commerce and services 644,231 2,759,911 3,667,707 2,820,500 7,498,250 4,642,886

Note: GDP data are based on purchasing power parity.HCMC = Ho Chi Minh City.Sources: See list at the end of the Appendix.

HCMC = Ho Chi Minh City.Sources: See list at the end of the Appendix.

65

Area Bangalore Metropolitan Region Ministry of Home Affairs—Directorate of Census Operations, Karnataka, Census 2011 http://censuskarnataka.gov.in/census%20data.htm

Bangkok Metropolitan Region Thailand Statistical Yearbook 2012 http://service.nso.go.th/nso/nsopublish/pubs/e-book/syb55/index.html#/52/

Ho Chi Minh Metropolitan Area Vietnam Statistical Yearbook 2012 http://www.gso.gov.vn/default.aspx?tabid=512&idmid=5&ItemID=13699

Metro Manila National Statistics Office—National Capital Region (Special release on 2010 Census of

Population and Housing) http://nso-ncr.ph/special%20releases.html

Seoul Capital Area Ministry of Land, Transport and Maritime Affairs—Cadastral Statistical Annual Report http://www.ngii.go.kr/kor/board/view.do?rbsIdx=103&page=1&idx=31

Shanghai Municipality Shanghai Statistical Yearbooks http://www.stats-sh.gov.cn/data/release.xhtml

Population Bangalore Metropolitan Region Ministry of Statistics and Programme Implementation - India Statistical Yearbook 2013 Ministry of Home Affairs, Office of the Registrar General and Census Commissioner—Provi-

sional Population for the state of Karnataka http://mospi.nic.in/mospi_new/upload/SYB2013/index1.html http://censusindia.gov.in/2011-prov-results/prov_data_products_karnatka.html

Bangkok Metropolitan Region Ministry of Interior, Department of Provincial Administration National Statistics Office—Population statistics http://stat.bora.dopa.go.th/xstat/popyear.html http://service.nso.go.th/nso/nsopublish/BaseStat/basestat.html

Ho Chi Minh City Metropolitan Area General Statistics Office—Statistical Data, Population and Employment http://www.gso.gov.vn/default_en.aspx?tabid=467&idmid=3

Metro Manila National Statistics Office—Statistics, Population National Statistics Office—National Capital Region (Special release on 2010 Census of

Population and Housing) http://www.nscb.gov.ph/secstat/d_popn.asp http://nso-ncr.ph/special%20releases.html

10. Data Sources


Seoul Capital Area Korean Statistical Information Service—Population/Household http://kosis.kr/eng/database/database_001000.jsp?listid=Z

Shanghai Municipality Shanghai Statistical Yearbooks [People’s Republic of] China Statistical Yearbooks http://www.stats-sh.gov.cn/data/release.xhtml http://www.stats.gov.cn/english/statisticaldata/yearlydata/ Gross domestic product Bangalore Metropolitan Region Planning Commission, Government of India—Strengthening State Plan for Human Development Directorate of Economics and Statistics, Government of Karnataka—State Income + Statis-

tical Abstract of Karnataka Reserve Bank of India—Database on Indian Economy Ministry of Statistics and Programme Implementation—National Accounts http://planningcommission.gov.in/plans/stateplan/index.php?state=ssphdbody.htm http://des.kar.nic.in/node/140/index.html http://des.kar.nic.in/node/188/index.html http://dbie.rbi.org.in/DBIE/dbie.rbi?site=statistics http://mospi.nic.in/Mospi_New/site/inner.aspx?status=3&menu_id=82

Bangkok Metropolitan Region National Statistics Office—National GDP and Provincial GDP http://service.nso.go.th/nso/nsopublish/BaseStat/basestat.html

Ho Chi Minh City Metropolitan Area Vietnam’s Provincial Statistical Yearbooks 2007 General Statistics Office—Statistical Data, National Accounts http://www.gso.gov.vn/default_en.aspx?tabid=468&idmid=3

Metro Manila Philippines Statistical Yearbook 2007 Philippine Institute for Development Studies, Economic and Social Database - Economic

Statistics, Gross Regional Domestic Product http://econdb.pids.gov.ph/tablecategories/index/38

Seoul Capital Area Korean Statistical Information Service—Regional Accounts http://kosis.kr/eng/database/database_001000.jsp?listid=Z

Shanghai Municipality Shanghai Statistical Yearbooks China Statistical Yearbooks http://www.stats-sh.gov.cn/data/release.xhtml http://www.stats.gov.cn/english/statisticaldata/yearlydata/

Main reference International Monetary Fund, World Economic Outlook Database http://www.imf.org/external/pubs/ft/weo/2010/01/weodata/index.aspx

67Data Sources

Employment Bangalore Metropolitan Region Ministry of Home Affairs, Office of the Registrar General and Census Commissioner—

Census 2001, District Profile; Primary Census 2011 Abstract http://www.censusindia.gov.in/Tables_Published/Basic_Data_Sheet.aspx http://www.censusindia.gov.in/2011census/hlo/pca_highlights/pe_data.html

Bangkok Metropolitan Region National Statistics Office—Social Census, Labour Force Survey National Statistics Office—Employment statistics http://service.nso.go.th/nso/nsopublish/pubs/ http://service.nso.go.th/nso/search/ http://service.nso.go.th/nso/nsopublish/BaseStat/basestat.html

Ho Chi Minh Metropolitan Area General Statistics Office—Statistical Data, Population and Employment http://www.gso.gov.vn/default_en.aspx?tabid=467&idmid=3

Metro Manila Department of Labor and Employment, Bureau of Labor Statistics - Yearbook of Labor Statistics http://www.bles.dole.gov.ph/ARCHIVES/YLS/2005YLS/CHAP3.html http://www.bles.dole.gov.ph/ARCHIVES/YLS/YLS2006/STAT_TABLES.html#chap3 http://www.bles.dole.gov.ph/ARCHIVES/YLS/2007YLS/chap3_Employment.html http://www.bles.dole.gov.ph/ARCHIVES/YLS/2008_YLS/HTML%20FILES/CHAP3.html http://www.bles.dole.gov.ph/ARCHIVES/YLS/2009%20YLS/html/chapter_3.html http://www.bles.dole.gov.ph/ARCHIVES/YLS/2010%20YLS/chap3.html http://www.bles.dole.gov.ph/ARCHIVES/YLS/2011%20YLS/chap3.html

Seoul Capital Area Seoul Statistical Yearbooks—Labor Incheon Statistical Database—Statistical Yearbook; Labor Gyeonggi-Do Statistical Yearbooks—Labor Korean Statistical Information Service—Employment/Labor/Wage http://stat.seoul.go.kr/jsp2/WWS8/WWSDS8115.jsp?cot=009 http://stat.kosis.kr/nsieu/main.do;jsessionid=A6src13cODROQ2i0ICJc1StdqIGMHDT40asM

g0btBK9OXI5WNy8XUu5xKQt72O8f.0000000.STAT_WAS1_servlet_engine3?task=view&mode=1&db=&hOrg=204

http://stat.gg.go.kr/publication/publication01_01.jsp?pub_sosok=006&htxt_code=12536969080002842417291754407236

http://kosis.kr/eng/database/database_001000.jsp?listid=Z

Shanghai Municipality Shanghai Statistical Yearbooks [People’s Republic of] China Statistical Yearbooks http://www.stats-sh.gov.cn/data/release.xhtml http://www.stats.gov.cn/english/statisticaldata/yearlydata/

Urban Metabolism of Six Asian Cities

The urban metabolism framework maps the activities of cities from their consumption of materials, the different activities associated with those processes, and the wastes produced. Information generated provides a diagnostic tool for identifying high waste generating or inefficient activities and identifying potential points of policy intervention.

A streamlined urban metabolism approach based on material flow analyses was applied to six Asian cities—Bangalore, Bangkok, Ho Chi Minh City, Manila, Seoul and Shanghai. The streamlined approach surmounts the lack of city level data, which is often cited as the most significant limitation preventing material flow analysis at the city level. Extension of the methodology to cover more cities can contribute towards creating benchmarks for city typologies.

About the Asian Development Bank

ADB’s vision is an Asia and Pacific region free of poverty. Its mission is to help its developing member countries reduce poverty and improve the quality of life of their people. Despite the region’s many successes, it remains home to approximately two-thirds of the world’s poor: 1.6 billion people who live on less than $2 a day, with 733 million struggling on less than $1.25 a day. ADB is committed to reducing poverty through inclusive economic growth, environmentally sustainable growth, and regional integration.

Based in Manila, ADB is owned by 67 members, including 48 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance.

ASIAN DEVELOPMENT BANK6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippines www.adb.org

Urban Metabolism of Six Asian Cities - adb.org

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