Southeast Asia is experiencing fast and strong economic growth. ASEAN-5 countries are among the most dynamic areas in the world in economics terms. Evidence shows that ASEAN-5 countries had an average annual population growth rate in cities of 2.3% (vs. the OECD average of 1.3%). The continued rapid urbanisation of ASEAN-5 countries puts pressure on land use and land resources, leading to higher GHG emissions, air pollutions, and increased vulnerability to climate risks such as floods or heatwaves. This chapter presents an overview of the status of sustainable urban development in ASEAN-5 countries and the key challenges they face.
Financing Sustainable Cities in Southeast Asia
Diversifying Instruments and Leveraging Private investment
Abstract
2.1.1. A highly dynamic economic region
Southeast Asia is experiencing fast and strong economic growth. ASEAN-5 countries are among the most dynamic areas in the world in economics terms. Between 1990 and 2019, before the start of the COVID-19 pandemic, the GDP in ASEAN-5 countries increased on average by 4.9% annually, as opposed to the 2.1% average in OECD countries (World Bank, 2022[1]). The GDP per capita in ASEAN-5 countries remains lower than in the OECD countries but is increasing steadily. In 1990, the average GDP per capita in ASEAN-5 countries was USD PPP 3 029 (18% of the OECD average), while in 2019, the GDP per capita was USD PPP 13 645 (29% of the OECD average). Malaysia has experienced the highest growth rates. In 2019, the national GDP per capita in Malaysia (USD PPP 29 621) was 64% of the OECD average (USD PPP 45 977) (Figure 2.1).
% share compared with OECD average
Source: Author’s elaboration based on data from the (World Bank, 2022[2]) World Development Indicators.
Although the COVID-19 pandemic and related containment measures hit the region hard, and the share of GDP per capita in ASEAN-5 countries compared with the OECD average reduced from 29% to 28% (OECD, 2022[3]). The economies of ASEAN-5 countries began to recover in 2021. Their GDP grew substantially in 2022, particularly due to post-pandemic recovery, and remained positive, albeit with slower growth in 2023 (Figure 2.2).
Annual % change
Note: Data are as of 7 March 2022. The projection for Indonesia is based on data from the OECD (2021a), OECD Economic Outlook No. 110.
Source: (OECD, 2022[3]). Economic Outlook for Southeast Asia, China and India 2022: Financing Sustainable Recovery from COVID-19. Large metropolitan areas in ASEAN-5 countries drive national economic growth
However, their challenges vary by country (Box 2.1). Moreover, the ASEAN-5 countries currently face some risks such as rising inflation—especially in energy-related products and commodities—disruptions in the international supply chains, depreciation of domestic currencies, financial market volatility, capital outflows due to rising interest rates in developed countries, tightening of global credit conditions, and the rise of public debt (OECD, 2022[3]).
Cities in ASEAN-5 countries have been experiencing significant growth. Between 2000 and 2015, GDP in cities in ASEAN-5 countries increased by an average of 5.5% in real terms compared to 1.8% within OECD countries (Table 2.1). In 2015, the GDP per capita in cities in ASEAN-5 countries was 42% of the OECD average, while in 2000, the share was 27%.
Among the 731 cities in the ASEAN-5 countries, large metropolitan areas are demonstrating particularly strong economic performances. For example, cities in Malaysia and Thailand show per capita values of GDP higher than the OECD average, thanks to Kuala Lumpur and Bangkok, which produce 60% and 83% of the urban GDP of their respective countries.
USD PPP
Source: Author’s elaboration based on data from the European Commission – Joint Research Centre (Centre, 2019[4]).
2.1.2. ASEAN-5 cities grew by more than 154 million inhabitants between 1975 and 2015
Economic growth in ASEAN-5 countries has been coupled with strong urbanisation trends. Evidence shows that ASEAN-5 countries had an average annual population growth rate in cities of 2.3% (vs. the OECD average of 1.3%). Cities also led national population growth, contributing to more than half of the total aggregate growth of ASEAN-5 population: this means that for every 100 additional people, 57 were in cities (Figure 2.3).
Cities grew by 150% between 1975 and 2015, faster than other types of settlements under the Degree of Urbanisation in all ASEAN-5 countries, except for the Philippines, where ‘towns’ demonstrated the fastest growth. Suburban and peri-urban areas also experienced a notable growth increase of 122%, particularly between 1990 and 2000. The population in villages and rural areas grew at a slower pace by 60% (Figure 2.3).
Source: Author’s elaboration based on data from European Commission - Joint Research Centre (2019[5]).
2.1.3. The urbanisation level of ASEAN-5 countries is similar to the OECD average, with Indonesia and Malaysia being more highly urbanised
The level of urbanisation in ASEAN-5 countries are very close to the OECD average. In 2015, 257.5 million people lived in cities in ASEAN-5 countries, accounting for 48% of the total population (compared to 49% in OECD countries); 56.4 million people lived in suburban or peri-urban areas, accounting for 11% of the total population (compared to 12% in OECD countries); and 87.4 million lived in towns, accounting for 16% of the total population (compared to 14% in OECD countries).
Indonesia and Malaysia show higher shares of the population living in cities (58% and 51%, respectively) than the OECD average (49%) (Figure 2.4).
The Philippines and Thailand have relatively lower shares of population living in cities (40% and 31%, respectively) and higher shares of the population living in rural areas and villages (40% and 41%, respectively).
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5])
2.1.4. Large metropolitan areas in ASEAN-5 countries lead to urban population growth
Cities and their surrounding commuting zones form functional urban areas (FUAs). Among the numerous methodologies to identify FUAs, the OECD and the European Commission have developed a global definition that provides a better understanding of urban agglomerations in an internationally comparable way (Box 2.1). Within ASEAN-5 countries, 468 FUAs are identified (Table 2.2).
The concept of FUA considers the ‘functional’ and ‘economic’ linkages across space that characterise urban areas. Those linkages can be proxied by the local labour markets, which are usually integrated in urban areas, where densely inhabited cities – that concentrate jobs – are usually surrounded by less densely populated commuting zones: therefore, FUAs comprise cities and their surrounding areas, which approximate the extent of a city’s labour market (‘commuting zone’). Several methodologies have been proposed to define FUAs, such as identifying one-hour travel time boundaries (Marchetti, 1994[6]). While the identification of commuting zones is subject to the availability of actual commuting or travel-time data at a granular spatial scale, such data is not always available, which prevents the international application of FUAs.
To address such challenges, the OECD and the European Commission have developed a method to identify FUAs across the world that does not require information on commuting flows. The method draws on a global statistical grid of population and a probabilistic model. It assigns a grid cell to an FUA according to a probability function which considers the (estimated) population of the cell, the population of the nearest urban centre, the travel time between the cell and the nearest urban centre (which is an intermediate notion used to define cities), the country’s economic activity level, and the vehicle stock. Cities are identified by using the methodology provided by the Degree of Urbanisation and GHSL data, i.e., densely populated areas with 50 000 inhabitants and a minimum density of 1 500 inhabitants per square kilometre.
Source: (Marchetti, 1994[6]). Anthropological invariants in travel behavior. Technological Forecasting and Social Change, 47(1), 75-88; (OECD/European Commission, 2020[7]). Cities in the World: A New Perspective on Urbanisation. OECD Publishing, Paris. (Moreno-Monroy, Schiavina and Veneri, 2021[8]). Metropolitan areas in the world. Delineation and population trends. Journal of Urban Economics, 125.
The demographic analysis for FUAs confirms that the urban population trend continues in ASEAN-5 countries. From 1975 to 2015, 95% of FUAs (444) experienced population growth, and from 2000 to 2015, the figure dropped to 81% (380), but nevertheless remains high. For reference, in OECD countries, the population grew in 86% of FUAs between 1975 and 2015 and in 81% of FUAs between 2000 and 2015.
Source: Author’s elaboration based on data from European Commission – Joint Research Centre (European Commission - Joint Research Centre, 2019[5]).
The FUAs with more than 5 million inhabitants grew fastest among different sizes of FUAs (Figure 2.5). In particular, the largest cities within each of the five countries grew much faster than other parts of their countries (Figure 2.6).Currently, 17% of the total national population in ASEAN-5 countries resides in the FUAs belonging to each country’s largest city (Jakarta, Kuala Lumpur, Manila, Bangkok, Ho Chi Minh City), which has grown by 8% since 1975. The rise of megacities is also evidenced by the fact that 9 out of 94 FUAs with more than 5 million inhabitants were found in ASEAN-5 countries in 2015.
Annual growth rate of population
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
Index numbers (1975=100)
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
2.2.1. Urbanisation generates strong needs for investment in urban infrastructure and the urban built environment for citizen wellbeing
The continued rapid urbanisation of ASEAN-5 countries puts pressure on land use and land resources, calling for policy responses on the effective use of land resources. In parallel with the population growth, the built-up areas, i.e., the areas covered by buildings and other physical structures (JRC, 2022[9]) in ASEAN-5 cities grew much faster than the average of OECD countries. Between 1975 and 2015, they grew by 164%, which is almost double the growth rate in built-up areas in OECD countries (Figure 2.7). This means that every year, on average, 426 square kilometres of land have been newly used in ASEAN-5 cities.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5])
Despite growth in the urban built-up area, ASEAN-5 cities are still much denser than OECD cities. Net-density, defined as the ratio between population and built-up area, is 12 773 inhabitants per square km in ASEAN-5 cities, 2.7 times higher than in OECD cities (4 751 inhabitants per built square km). While net-density is higher in all cities of ASEAN-5 countries than the OECD average, ASEAN-5 countries also show a high level of differentiation: average net density in the Philippines is 3.82 times higher than the average net-density in Malaysia. ASEAN-5 countries also differ in trends: while net-density in cities grew in all ASEAN-5 countries between 1975 and 2015, it grew fastest in the Philippines, showing the highest net-density (31 655.7 inhabitants per urbanised square km) among the five countries (Figure 2.3).
Dense cities are often linked with better public transport and better accessibility to services and jobs, which in turn can promote environmental, economic, and social benefits (OECD, 2012[10]); (OECD, 2020[11]). Furthermore, density can reduce infrastructure costs per user, making public services more economically viable. For instance, Transit-Oriented Developments, meaning the expansion of urban areas along (public) transport corridors, can maximise ridership, and therefore the returns of infrastructure investments (OECD, 2020[11]); (ASEAN, 2020[12]). On the other hand, investment in the provision of infrastructure can be less cost-effective in densely built-up areas compared to underdeveloped land since it may involve greater physical and normative constraints, as well as higher transaction costs (OECD, 2015[13]). Furthermore, in the context of rapid urbanisation, ASEAN-5 countries face challenges in maintaining their investment in urban infrastructure and services to match the rapid population growth in cities. Failing to do so will lead to reduced urban attractiveness and citizen well-being. The variation in urban net-density that characterises ASEAN-5 countries necessitates place-based approaches to urban management and development. This approach integrates city growth with quality urban development. For instance, in densely populated urban areas, promoting a healthy environment includes enhancing accessibility to open public spaces for urban dwellers.
Population per built square km
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
Data from the Urban Centre Database indicates that, in comparison to OECD cities, ASEAN-5 cities generally exhibit better access to green and open spaces (measured by the proportion of the population residing in areas with such amenities) (European Commission - Joint Research Centre, 2019[5]) (Figure 2.8). For instance, regarding green spaces, approximately 34% of the population in ASEAN-5 cities enjoys proximity to green areas, with Indonesia showing the highest percentage at 41%, in contrast to 24% in OECD cities. However, the shares in Thailand (17%), Malaysia (19%), and Viet Nam (22%) are below the OECD average (Table 2.4). It should be noted that being close to a green area does not necessarily mean that the area is accessible and available for public use (Figure 2.8). Furthermore, green areas might not qualify as “quality” open spaces usable by citizens. For instance, this definition could encompass residual areas from building development and areas that are vulnerable to floods.
Year 2015
Note: Weighted average of city values (weighted by population). The potential access to green areas is measured as a share of the (estimated) population living in areas where “high green” (i.e., areas with dense vegetation) is found. The potential access to open spaces is measured as a share of the (estimated) population living in areas where non-built areas are found.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
Looking at the data by city size, the largest cities (with a population higher than 5 million inhabitants) have lower levels of potential access to green areas and open spaces, calling for action, especially in large metropolises (Table 2.4).
Year 2014
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
2.2.2. GHG emissions are high and rising necessitating mitigation strategies and actions
In 2015, urban areas (comprising cities, towns, suburban and peri-urban areas) generated between 70% and 80% of global anthropogenic greenhouse gases and the majority of air pollutants (Crippa et al., 2021[15]) In aggregate, urban areas were the source of almost two-thirds of total CO2 emissions in ASEAN-5 countries (vs. 53% in OECD countries) (Figure 2.9).
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
CO2 emissions increased across all settlement types in both in ASEAN-5 and OECD countries between 1990 and 2015. However, the increase in ASEAN-5 countries (134%) is notably higher compared to OECD countries (9%). Specifically, CO2 emissions in cities increased by 236% (in contrast to the OECD average of 37%), equating to an average annual increase of 5%. Suburban and peri-urban areas also experienced substantial growth (178%), followed by towns and rural areas (Figure 2.10).
A closer look by country reveals that cities show the highest growth in emissions in four countries except for the Philippines, where CO2 emissions grew fastest in suburban and peri-urban areas. In Viet Nam, CO2 emissions grew by almost 400% in cities. In Malaysia, CO2 emissions grew in all types of settlements (Figure 2.11).
Average annual growth rates (%)
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
The energy and industrial processes (from here onwards the energy-industry sector) is the largest CO2 emitting sector in cities, responsible for 59.5% of emissions (compared to 57% in OECD cities), followed by the transport sector (16%). The share of the energy-industry sector is particularly high in cities in Thailand (70.5%), while the transport sector has higher shares in cities in Malaysia (29.1%), and the Philippines (20%). The share of the residential sector is relatively high in cities in Indonesia (13.8%) and in Viet Nam (12.4%) (Figure 2.12).
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
Regarding the growth rate of emissions by sector, it is the transport sector that grew the fastest. Between 1990 and 2015 the transport sector’s emissions grew by 375.2% in ASEAN-5 countries (in contrast to the OECD average of 61.9%) (Table 2.5). This is due to rapid motorisation and high levels of traffic congestion that characterise ASEAN-5 cities (OECD, 2019[16]); (OECD, 2018[17]).
Note: Sectors are ordered according to the growth rate between 1990 and 2015 in ASEAN-5 countries. Contribution to growth of CO2 emissions is measured as the product between the sectoral share on total emissions in 1990 and the growth rate of sectoral emissions between 1990 and 2015.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2021[14]).
2.2.3. Air pollution and congestion are compromising the quality of the urban environment
Air pollution is one of the most urgent challenges for ASEAN-5 cities to tackle. At present, air pollution is the largest environmental threat to health, having caused 2.4 million premature deaths in Southeast Asia in 2016 (World Health Organization, 2022[18]). The impacts are particularly strong on the most vulnerable populations, such as children (Luong et al., 2019[19]). In terms of the concentration of PM2.5 (fine suspended particles of less than 2.5 microns in diameter), Viet Nam ranks 22 out of 240 countries worldwide in 2022. Thailand ranks 24, Indonesia ranks 52, the Philippines ranks 58, and Malaysia ranks 87 (EPIC- University of Chicago, 2022[20]). Beyond national averages, urban areas are more intensely affected by air pollution. In 2014, 86% of the urban population experienced living in a city with an average mean concentration of PM2.5 exceeding the maximum value proposed by the WHO for safety at the time (10 μg/m3) (compared to 83% in the OECD). Exceeding the WHO guideline for pollution is expected to reduce life expectancy by 1.5 years (EPIC- University of Chicago, 2022[20]). In 2014, all cities in Thailand had estimated concentration levels above 10 μg/m3. The share of the population with estimated concentration levels above 10 μg/m3 in 2014 was 96% in Viet Nam, 89% in Malaysia, 83% in Indonesia, and 82% in the Philippines, compared with 83% in OECD countries (Figure 2.13).
Micrograms per cubic metre
Note: Country averages are weighted by population. A red line shows WHO’s safety standard.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5])
Rising temperatures and heatwaves in cities call for adaptation efforts
From 1990 to 2015, the average temperature of cities in ASEAN-5 countries increased from 26.2 to 26.6 degrees Celsius (Table 2.6). This increase presents a serious challenge for cities, with extreme heat events posing a danger to public health, well-being, and national economies. The real impacts to urban citizens may be even stronger, as the data may not consider micro-climates in urban areas (European Commission - Joint Research Centre, 2019[21]). Urban areas are more affected by heatwaves than rural areas, because “urban heat islands” amplify extreme heat events (Rodas, Lombardi and Ledesma, 2022[22]). Most importantly, heatwaves are most strongly affecting the poorest urban neighbourhoods in ASEAN-5 cities, as reported in Bangkok, Thailand (Arifwidodo and Chandrasiri, 2020[23]), and the Philippines (Zander et al., 2018[24]). Rising temperatures and heat waves in cities also affect energy consumption in cities, putting strong pressures on electricity and greenhouse gas emission, as most of the adaptation strategies to heat events rely on installing air conditioning units in buildings.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
The heat wave magnitude index (HWMI), which sums up the excess temperatures beyond a normalised threshold and synthesises duration and temperature anomalies in a single number, shows that ASEAN-5 cities are more severely affected by heatwaves than OECD cities (Figure 2.14). An analysis conducted in Southeast Asia for the period of 1983-2016 found that heat waves have become more frequent, longer lasting, more intense, and have affected larger land areas across most parts of the region (Li, Yuan and Hang, 2022[25]). Furthermore, global warming is expected to increase the frequency of extreme heatwaves, making events that typically occur only once every 50 years more common (Dong et al., 2021[26]). This underscores the need for proper planning to enhance preparedness and adaptation, ensuring that cities in ASEAN-5 countries become heatwave resilient (Sharma, Andhikaputra and Wang, 2022[27]).
Average 1980-2010
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[5]).
ASEAN-5 cities are increasingly exposed to floods, storm surges, and sea level rise
ASEAN-5 cities are heavily affected by floods, storm surges, and sea level rise. Urbanisation patterns in cities in Southeast Asia, which often occurred in river deltas (e.g., Thailand, Viet Nam) and floodplains, have amplified flood risks (Tierolf, de Moel and van Vliet, 2021[28]). About one-fifth of the built-up area in cities (22%) and population in cities (20%) was faced flood risks (measured as the built-up area and population exposed to a 100-year flood in ASEAN-5 countries) in 2015, which is double the OECD average. In Thailand, 81% of the urban population (53 million) and 72% of the urban built environment are at risk of floods. In Bangkok, the exposure reaches 99% of the population, while in Viet Nam, over half of the population faces flood risks (Table 2.7), with Hanoi’s exposure at 85%. Significantly, data also shows that such risks are increasing over time. Further urban expansion, coupled with climate change, is likely to increase flood risks in the region (Winsemius et al., 2015[29]),illustrating the need for better and more effective urban planning and greater investment in flood protection infrastructure.
Source: Author’s elaboration based on data from the (European Commission - Joint Research Centre, 2019[21])).
Storm surges are another key challenge for ASEAN-5 cities. In 2015, 19% of built-up areas and 22% of inhabitants in cities across ASEAN-5 countries were exposed to the risk of storms, which is higher than the average of OECD cities (16% and 15%, respectively). The share of built-up areas exposed to storm surges has slowly declined between 1975 and 2015 in ASEAN-5 cities while the share of population has remained stable. The Philippines is particularly vulnerable, where 68% of its built-up areas and 69% of population are exposed to risks of storm surges (Table 2.8).
These data underscore the urgency for ASEAN-5 cities to enhance urban development resilience to climate impacts. This involves integrating strategies to address climate risks (adaptation) and measures to reduce greenhouse gas emissions (mitigation), while at the same time preserving natural resources and enhancing community well-being.
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