Population predictions for the world s largest cities in the 21st century

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1 663557EAU / Environment & UrbanizationShort Title research-article2016 Population predictions for the world s largest cities in the 21st century DANIEL HOORNWEG and KEVIN POPE Daniel Hoornweg is Associate Professor and Richard Marceau Chair in the Faculty of Energy Systems and Nuclear Science. Address: University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, Ontario, L1H 7K4, Canada; daniel. hoornweg@uoit.ca; Kevin Pope is Assistant Professor in the Faculty of Engineering and Applied Science at Memorial University of Newfoundland, St John, NL, Canada. Address: kpope@ mun.ca 1. de/world/agglomerations.html. 2. Hoornweg, D and M Freire (2013), Building Sustainability in an Urbanizing World A Partnership Report, Urban Development Series Knowledge Papers, World Bank. Abstract We project populations to 2100 for the world s larger cities. Three socioeconomic scenarios with various levels of sustainability and global cooperation are evaluated, and individual best fit projections made for each city using global urbanization forecasts. In 2010, 757 million people resided in the 101 largest cities 11 per cent of the world s population. By the end of the century, world population is projected to range from 6.9 billion to 13.1 billion, with 15 per cent to 23 per cent of people residing in the 101 largest cities (1.6 billion to 2.3 billion). The disparate effects of socioeconomic pathways on regional distribution of the world s 101 largest cities in the 21st century are examined by changes in population rank for 2010, 2025, 2050, 2075 and Socioeconomic pathways are assessed based on their influence on the world s largest cities. Two aspects of the projections raise concerns about reliability: the unlikely degree of growth of cities suggested for Africa and the growth of cities in coastal settings (and likely global immigration). Trends and the effect of sustainable development on regional distribution of large cities throughout the 21st century are discussed. Keywords 21st century / cities / population projection / urban areas I. Introduction Large cities (metropolitan urban areas) are hubs of economic development and innovation, with larger cities underpinning regional economies and local and global sustainability initiatives. Larger cities tend to be more challenged by the boundary issue, except for Singapore. City boundaries are as ephemeral and arbitrary as other political boundaries; however, a systems approach to cities requires assessment of the overall urban agglomeration. Larger urban areas are often comprised of many smaller cities, e.g. metropolitan Sydney, Australia is administered by 38 local governments; Toronto, Canada by 29; Lagos, Nigeria by 16; and Jakarta, Indonesia by 10. Urban agglomerations, or metropolitan areas, are typically defined through common employment- and commuter-sheds (extent of area in which people typically travel for regular employment). Consistent with: (i) Brinkhoff s database; (1) (ii) citymayors.com; and (iii) the World Bank data on the 100 largest urban areas, (2) Kennedy et al. (3) define boundaries of the world s 27 megacities (urban areas of more than 10 million people). In this paper the approach is extended to include all urban areas expected to have more than 5 million people before 2100 (online supplementary information (SI), Table S4). Future Five cities are those expected to have populations greater than 5 million by 2050 (122 cities) and 2100 (181 cities). Environment & Urbanization Copyright 2016 International Institute for Environment and Development (IIED). Vol 29(1): DOI: /

2 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 CP EAP ECA LAC LUA MENA NCAR SAR SI SSA SSP UGR WUP Box 1 Abbreviations used in this paper City Population East Asia Pacific Europe and Central Asia Latin America and the Caribbean Large Urban Area Middle East and North Africa National Center for Atmospheric Research South Asia Region Supplementary Information Sub-Saharan Africa Shared Socioeconomic Pathway Urban Growth Rate World Urbanization Prospects 3. Kennedy, C, I Stewart, A Facchini, I Cersosimo, R Mele, B Chen, M Uda, A Kansal, A Chiu, K Kim, C Dubeux, E La Rovere, B Cunha, S Pincetl, J Keirstead, S Barles, S Pusaka, J Gunawan, M Adegbile, M Nazariham, S Hoquen, P Marcotullioo, F Otharánp, T Genenaq, N Ibrahim, R Farooquir, G Cervantess and A Sahint (2015), Energy and material flows of megacities, Proceedings of the National Academy of Sciences Vol 119, No 19, pages In 2010, the baseline year for this paper, 757 million people resided in the 101 largest cities, with a population of 36 million for the largest city (Tokyo), and 3.5 million for the 101st largest city (Addis Ababa); these cities were home to 11 per cent of the world s population. By the end of the century, the world population is projected to grow by 6.9 billion to 13.1 billion; the percentage of people residing in the 101 largest cities is estimated to be 15 per cent to 23 per cent. In all scenarios, projected total populations in the world s largest cities are growing. When cities are governed and managed well, urbanization can be a powerful antidote to environmental degradation, as population density, and the effective provision of basic services, enables substantial gains in efficiency of resource consumption and waste management. Urbanization is also associated with higher rates of education and health care provision. (4) Urbanization, particularly through large cities, is a key driver of economic development. (5) Larger cities have a disproportionate impact on regional and global geopolitical power dynamics. (6) Bettencourt (7) and Bettencourt and West (8) further promote the agglomeration of urban areas with minimal borders (e.g. barriers to travel, overlapping utilities), as they show that cities scale super-linearly (~1.15) for economy, while they scale sub-linearly (~0.85) for infrastructure costs. If externalities associated with increased density, e.g. congestion, are addressed, doubling a city s effective size more than doubles the economy and wealth generation, with less than a doubling of infrastructure costs and material flows. (9) Working with cities, instead of national governments, may offer urban practitioners a more straightforward approach to sustainable development as requirements and achievements may be easier to define and monitor, and a systems approach may emerge. (10) The Sustainable Development Goals and comprehensive global inventories such as greenhouse gas emissions can be down-scaled to larger cities. (11) Considering their sheer economic heft and material flows (and subsequent pollution), sustainable development globally is not possible without sustainability being firmly anchored in most of the world s larger cities. This report considers how socioeconomic scenarios of development may affect the world s 101 largest cities, with the National Center for See reference 2; also Hayden, D (2003), Building Suburbia: Green Fields and Urban Growth, , Pantheon Books; and Mercier, J (2009), Equity, social justice, and sustainable urban transportation in the twentyfirst century, Administrative Theory & Praxis Vol 31, No 2, pages Bettencourt, L M A, J Lobo, D Helbing, C Kuhnert, and G B West (2007), Growth, innovation, scaling, and the pace of life in cities, Proceedings of the National Academy of Sciences Vol 104, No 17, pages ; also Batty, M A (2013), Theory of City Size, Science Vol 340, No 6139, pages Hoornweg, D (2015), A Cities Approach to Sustainability, PhD thesis, University of Toronto. 7. Bettencourt, L (2013), The Origins of Scaling in Cities, Science Vol 340, pages

3 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES 8. Bettencourt, L and G West (2010), A unified theory of urban living, Nature Vol 467, pages See reference 6; also Duren, R and C Miller (2012), Measuring the carbon emissions of megacities, Nature Climate Change Vol 2, pages Meadows, Donella (2008), Thinking in Systems: A Primer, Chelsea Green Publishing; also Galaz, V, F Biermann, B Crona, D Loorbach, C Folke, P Olsson, M Nilsson, J Allouche, Å Persson and G Reischl (2012), Planetary boundaries exploring the challenges for global environmental governance, Current Opinion in Environmental Sustainability Vol 4, No 1, pages Harrison, J and M Hoyler (2014), Governing the new metropolis, Urban Studies Vol 5, No 11, pages ; also Hoornweg, D, M Hosseini, C Kennedy and A Behdadi (2016), An urban approach to planetary boundaries, Ambio; and ISO Greenhouse Gas Accounting and Verification. 12. Arnell, N, T Kram, T Carter, K Ebi, J Edmonds, S Hallegatte, E Kriegler, R Mathur, B C O Neill, K Riahi, H Winkler, D van Vuuren and T Zwickel (2011), A framework for a new generation of socioeconomic scenarios for climate change impact, adaptation, vulnerability and mitigation research, Scenario framework paper, Potsdam Institute for Climate Impact Research, Potsdam; also Kriegler, E, B O Neill, S Hallegatte, T Kram, R Lempert, R Moss and T Wilbanks (2012), The need for and use of socio-economic scenarios for climate change analysis: A new approach based on shared socio-economic pathways, Global Environmental Change Vol 22, No 4, pages ; and Moss, R, J Edmonds, K Hibbard, M Manning, S Rose, D van Vuuren, T Carter, S Emori, M Kainuma, T Kram, G Meehl, J Mitchell, N Nakicenovic, K Riahi, S Smith, R Stouffer, A Thomson, J Weyant and T Wilbanks (2010), The next generation of scenarios for climate change research and assessment, Nature Vol 463, pages Atmospheric Research s (NCAR s) three basic shared socioeconomic pathways (SSP1, SSP2 and SSP3 see below and SI for details). (12) The approach is expanded using the United Nations World Urbanization Prospects (WUP) (13) for predictions of urban growth in the larger urban areas (each city s best fit growth, or decline, presented in SI). Synergies between the growth and development of the 101 largest cities and their effect on global sustainability are highlighted. The Shared Socioeconomic Pathways (SSPs) are: SSP1 (Sustainability): The world makes relatively good progress towards sustainability, with sustained efforts to achieve development goals, while reducing resource intensity and fossil fuel dependency (rapid development of low-income countries; reduced inequality; rapid technology development; open, globalized economy). Population of 7 billion, 90 per cent urbanized. SSP2 (Middle of the Road): This pathway assumes extension of current trends in urbanization, along with similar middle of the road assumptions about population growth, technological change and economic growth. Estimated population of 9.5 billion, 80 per cent urbanization. SSP3 (Fragmentation): Urbanization follows the slow pathway. In high-income countries, low population growth (especially ageing), slow economic growth and technological changes reduce the incentives for urban expansion. In the developing regions, the population grows rapidly, particularly in rural areas, causing significant land use change and environmental degradation. Population of 13.5 billion, pockets of extreme poverty and moderate wealth, many countries with rapidly growing populations. II. Materials and Methods The World Urbanization Prospects (14) by the United Nations provide a detailed analysis of the global population growth and urbanization rates to The predictions are developed from current data on the urban rural ratio and urbanization rate, as well as national birthrate and mortality rate. These are further projected to 2100 for each city (SI). In an analysis of future growth scenarios by the National Center for Atmospheric Research (NCAR), various pathways of development are also analysed, including the effects on population growth and urbanization rates. (15) Population projections for each of the shared socioeconomic pathways complement WUP predictions by refining the definition of the urban rural ratio and extrapolating national predictions to 2100 (Table 1). As presented in Table 2, the main assumptions for population growth in the three SSP scenarios depend on the fertility, mortality, migration and education rates. In the SSP scenarios, low- and medium-income nations are categorized based on their current fertility rate, either high fertility (more than 2.9 children per woman) or low fertility (less than or equal to 2.9 children per woman). The third category consists of Organisation for Economic Co-operation and Development (OECD) and high-income nations. High-income countries follow the World Bank definition. (16) 197

4 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Table 1 Global population with various growth scenarios Scenario World population (billion) SSP SSP SSP extrapolation Population of the 101 largest cities (billion) Population living in the 101 largest cities (per cent) SSP1 SSP2 SSP3 extrapolation SSP1 SSP2 SSP3 extrapolation SOURCES: Arnell, N, T Kram, T Carter, K Ebi, J Edmonds, S Hallegatte, E Kriegler, R Mathur, B C O Neill, K Riahi, H Winkler, D van Vuuren and T Zwickel (2011), A framework for a new generation of socioeconomic scenarios for climate change impact, adaptation, vulnerability and mitigation research, Scenario framework paper, Potsdam Institute for Climate Impact Research, Potsdam; also SI, Tables S1 S4. Table 2 Main assumptions for the SSP population predictions (by income) SSP1 SSP2 SSP3 Low Mdl HI-OECD Low Mdl HI-OECD Low Mdl HI-OECD Demographics Fertility Low Low Med Med Med Med High High Low Mortality Low Low Low Med Med Med High High High Migration Med Med Med Med Med Med Low Low Low Education High High High Med Med Med Low Low Low SOURCE: Adapted from Jiang, L and B O Neill (2011), SSP Urbanization Projections Assumptions and Methods, Supplementary note for the SSP data sets, Table 1. Education rates are based on projections of the International Institute for Applied Systems Analysis/Vienna Institute of Demography (IIASA/VID); a high rate represents a scenario where school systems are globally expanded at the fastest possible rate, which is based on recent examples such as Singapore and South Korea. A medium rate represents a scenario where countries follow a similar path to other countries at a similar level of educational development, and a low rate maintains proportions of education at current levels. These assumptions describe an urbanization rate of fast, central and slow for SSP1, SSP2 and SSP3, respectively. (17) 13. United Nations (2012), World Urbanization Prospects - The 2011 Revision, Department of Economic and Social Affairs, Population Division, New York. 14. Jiang, L and B O Neill (2011), SSP Urbanization Projections Assumptions and Methods, Supplementary note for the SSP data sets. 15. See reference

5 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES 16. Lutz, W and S K C (2011a), SSP Population Projections Assumptions and Methods, Supplementary note for the SSP data sets. 17. See reference 14; also see reference See reference International Institute for Applied Systems Analysis - Science for Global Insight (2012), SSP Database, available at In this paper, the research by the UN s WUP and NCAR s SSP is extended and refined to investigate the world s 101 largest cities in the 21st century. Population changes of the world s large urban areas (LUAs) are predicted by considering data on current city size, country population growth and country-specific urbanization rates. The 2010 city populations are obtained from the World Bank s Building Sustainability in an Urbanizing World report. (18) Three different urban growth rate (UGR) schemes that correspond to different levels of sustainability of the socioeconomic pathways, as well as a refined extrapolation technique, are used to compare different scenarios and projections of global city growth. As presented in Table 3, the world population is determined from data by the IIASA, (19) and includes the population of 150 countries. Future city population is determined from the country-specific UGR, and the current city population (CP 0 ): ( ) YR CP YR = CP0 1 + UGR where YR represents the time (in years) to the prediction. The 101 largest cities are established from the population growth and urbanization rates predicted by the SSP1, SSP2 and SSP3 scenarios. Additionally, extrapolating WUP predictions provides a fourth predictive method, a linear extrapolation of the UGR for the current 1,000 largest cities, which identifies the potential largest cities. The larger cities, as predicted by the linear extrapolation of the WUP UGR predictions, are then further refined by considering four different extrapolation techniques (Figure 1): (i) exponential, (ii) polynomial (2nd order), (iii) constant, and (iv) linear. Table 3 World s largest cities (urban areas) by population (millions) Beijing (1.1) London (6.5) New York (12.4) Tokyo (35.5) Mumbai (42.4) Lagos (88.3) London (0.9) New York (4.2) London (8.9) Mexico City (19.2) Delhi (36.2) Kinshasa (83.5) Guangzhou (0.8) Paris (3.3) Tokyo (7.0) Mumbai (18.8) Dhaka (35.2) Dar es Salaam (73.7) Tokyo (0.7) Berlin (2.7) Paris (5.9) New York (18.7) Kinshasa (35.0) Mumbai (67.2) Istanbul (0.6) Chicago (1.7) Shanghai (5.4) São Paulo (18.6) Kolkata (33.0) Delhi (57.3) Paris (0.5) Vienna (1.7) Moscow (5.1) Delhi (16) Lagos (32.6) Khartoum (56.6) Naples (0.4) Tokyo (1.5) Buenos Aires Kolkata (14.6) Tokyo (32.6) Niamey (56.1) (5.0) Hangzhou St. Petersburg Chicago (4.9) Jakarta (13.7) Karachi (31.7) Dhaka (54.2) (0.4) (1.4) Osaka (0.4) Manchester (1.4) Ruhr (4.9) Buenos Aires (13.5) New York (24.8) Kolkata (52.4) Kyoto (0.4) Philadelphia (1.4) Kolkata (4.8) Dhaka (13.1) Mexico City (24.3) Kabul (50.2) SOURCES: Chandler, Tertius (1987), Four Thousand Years of Urban Growth: An Historical Census, Edwin Mellen Press, 656 pages; also data from Hoornweg, D and M Freire (2013), Building Sustainability in an Urbanizing World A Partnership Report, Urban Development Series Knowledge Papers, World Bank; and 2050 and 2100 data from WUP extrapolation. 199

6 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Figure 1 Examples of extrapolating WUP to 2100 for (a) Canada, (b) China, (c) the United States and (d) India As illustrated by the red lines in Figure 1, the WUP predict urban population growth for each country to Four extrapolation techniques are overlaid onto the WUP projections and the best fit selected for 2050 to For example, the extrapolation technique selected for Canada is exponential, China is constant, the United States is exponential, and India is linear. The selection of extrapolation technique is based on WUP trends and likely growth scenarios based on level of urbanization and historical trends. Whenever appropriate, exponential extrapolation is selected as it offers a convenient way of representing the consistent and gradual reduction of the urbanization rate as city growth matures and the urban to rural ratio decreases. The selection of the best fit extrapolating technique is intended to be an initial iteration in a series of refinements to predict country-specific urbanization rates. Also, examining the growth rate trends with different extrapolating techniques enables an appreciation of the sensitivity of the 200

7 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES 20. See reference 12, Arnell et al. (2011); also see reference 14; and reference See reference 16; also K C, S, B Barakat, A Goulon, V Skirbekk, W Sanderson and W Lutz (2010), Projection of populations by level of educational attainment, age, and sex for 120 countries for , Demographic Research Vol 22, pages See reference 12, Arnell et al. (2011); also see reference 14; and reference See reference 19. For discussions of SSP scenarios, see reference 14; reference 16; and O Neill, B et al. (2012), Workshop on the Nature and Use of New Socioeconomic Pathways for Climate Change Research Meeting Report, National Center for Atmospheric Research, Boulder, 2 4 November prediction, where a larger discrepancy between extrapolation predictions corresponds to lesser confidence in the predicted value. Countries that have a negative urban growth rate beyond 2050 cannot be represented with an exponential extrapolation. Details on the selection of the extrapolation technique for each city can be found in the supplementary information. Section V of the SI specifies the extrapolation technique used for each of the 101 largest cities as of 2010, as well as the urban growth rate for all of the countries containing these cities. The narratives of socioeconomic pathways (20) provide important insights into various trajectories of development. These insights are used in this paper to identify the regional distribution of the world s 101 largest cities throughout the 21st century. Identifying how different socioeconomic pathways affect the regional distribution of large cities is an important input to engineers and policymakers when developing more sustainable urban infrastructures that take into account anticipated resource scarcity and population pressures. (21) Population projections and urbanization rates for each socioeconomic pathway were developed by NCAR by predicting each pathway s effect on education, mortality, migration and birth rates. (22) a. Socioeconomic pathways and refined predictions for international city growth Shared socioeconomic pathways (Figure 2) are summarized in NCAR s supplementary note for the SSP data set and the International Institute for Applied Systems Analysis, SSP Database. (23) The disparities in the three scenarios are striking, and suggest a degree of caution, especially in Africa, as populations by 2100 differ by more than 50 per cent among the scenarios. The socioeconomic pathways are further discussed in SI. b. Defining city boundaries There are various methods to define city boundaries. Without standard definitions, large urban areas are subject to substantial interpretation. Large urban areas (metropolitan areas) can be made up of as many as 50 local governments. Analysis of public policy and resource consumption at the metropolitan scale can capture broader economic trends and potential scale benefits in areas such as energy, transportation, water supply and waste management. The approach used to define urban boundaries, as explained in Section I, was extended for all urban areas expected to have more than 5 million people before 2100 (SI, Tables S1 S4). Rather than decide which cities to include, a (slightly) less arbitrary approach was used, and all cities expected to have populations greater than 5 million by 2050 as projected under the WUP are included. According to the UN World Urbanization Prospects (2012), the primary methods to define a city boundary are administrative and population size/density, followed by urban and economic characteristics. Typically, these methods are used in combination with each other, and a unique, and variable, border emerges for all larger urban areas. A practical, precise and consistent city boundary is important for city planning and 201

8 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Figure 2 World population distribution in the 21st century for (a) SSP1, (b) SSP2, (c) SSP3 and (d) WUP extrapolations management. The city borders presented here are expected to be regularly refined, ideally by respective governments (local, regional and possibly national). A map of each urban area is needed, as well as consensus on the extent of all larger cities. c. 21st century large city growth Humanity is on an inexorable urbanization path that largely originated in 19th century Europe, the Americas and parts of Asia, and will likely 202

9 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES 24. See reference 6; also Vojnovic, I (2014), Urban sustainability: Research, politics, policy and practice, Cities Vol 41, Suppl 1, pages S30 S See reference See reference 5, Bettencourt et al. (2007); also United Nations (2001), Population, environment and development - the concise report, Department of Economic and Social Affairs, Population Division, New York. 27. Cobbinah, P, M Erdiaw- Kwasie and P Amoateng (2015), Africa s urbanisation: Implications for sustainable development, Cities Vol 47, pages culminate in Africa at the end of this century. Urbanization is a powerful driver of sustainability: as affluence increases, basic services can be provided more efficiently in an urban setting. This is especially the case as density increases, although vulnerabilities can also increase as city size and density increase. Urbanization also tends to provide greater wealth, particularly to urban residents. Many of the more intractable challenges, such as climate change and biodiversity loss, have their roots in purchasing habits of the affluent. (24) Sustainability in the 21st century will largely be about the purchasing habits and infrastructure development of the world s next 2.7 billion urban residents. (25) The relative size of cities may have an impact on sustainability, as city size affects economic development and resource consumption. (26) SS1 (sustainability) is predicated on the fastest and greatest growth of large urban areas relative to the other less sustainable scenarios, assuming resilience increases commensurately with city size (Figure 3A). d. Sustainable development and large city rankings in the 21st century Applying the socioeconomic pathways to city growth predictions provides several insights into the world s largest urban areas in the 21st century. As illustrated in Figures 3 and 4, global regions exhibit different levels of sensitivity to each socioeconomic pathway, with high-income countries exhibiting the greatest variability in the range of pathways. Cities from South Asia exhibit a tendency to maintain consistent numbers of large urban areas for all pathways, with the majority of South Asia Region (SAR) cities maintaining a relatively consistent rank throughout the century, in all pathways. Sub-Saharan Africa (SSA) exhibits the most significant change in numbers and rank of the largest cities. (27) In 2010 this region has seven cities in the 101 largest, which increases to 30 and 38 in 2100, for SSP1 and SSP3, respectively. In all pathways, SSA is the region with the highest number of cities in the 101 largest in 2100 (SI, Table S5). This trend increases regardless of the degree of sustainability in the development pathway. Figure 4 ranks each city s size in 2010 compared to its rank in Along the horizontal axis, a log scale is used to identify the city s rank in 2010, with the vertical axis representing the city s rank in The curved dotted line represents cities that have not changed in rank. Cities that are below and to the left of the line will drop in rank in 2100 compared to 2010, and cities above and to the right will rise in rank. The log scale on the horizontal axis causes the horizontal distance from the line to show a greater discrepancy between the city s current rank and its rank in The data point for each city is arranged according to its region: Latin America and the Caribbean (LAC), Middle East and North Africa (MENA), Sub-Saharan Africa (SSA), East Asia Pacific (EAP), Europe and Central Asia (ECA), Organisation for Economic Co-operation and Development (OECD), or South Asia Region (SAR). In the 21st century, the majority of high-income cities, and all North American cities, are predicted to fall in rank in all pathway predictions. In the unsustainable development pathway (SSP3), only five high-income cities remain in the 101 largest in 2100: two cities in Saudi Arabia (Riyadh and Jiddah); Tokyo, Japan; and two cities in the United States (New York 203

10 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Figure 3 Regional number of cities in the largest 101 for (a) SSP1, (b) SSP2, (c) SSP3 and (d) WUP extrapolations NOTE: The complete list of cities is in the supplementary information. and Los Angeles). In SSP3, New York and Los Angeles drop from 6 and 13 in 2010, to 48 and 87 in 2100 respectively, and Tokyo falls from 1 to 60. The number of high-income cities that fall from the list of 101 largest cities is reduced with the more sustainable pathways SSP1 and SSP2, with 21 and 14 high-income cities, respectively. Cities in EAP show a consistent drop in rank that is relatively independent of the socioeconomic pathway, dropping from 21 in 2010 to approximately 11 in However, LAC and high-income cities 204

11 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES Figure 4 Predicted rise of the 101 largest cities by 2100 (WUP extrapolations) show the largest variability between the NCAR city projections and the refined WUP extrapolations. The extrapolated WUP analysis predicts all 10 largest cities in 2100 to be in SSA and SAR, and 35 and 21 of the largest cities in 2100 to be located in SSA and SAR, respectively. Countries in LAC, EAP, ECA and the high-income grouping consistently drop in rank between 2010 and 2100, with SSA countries exhibiting the largest rise in 205

12 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 rank followed by SAR and MENA. In the WUP extrapolations, 15 cities from LAC and 16 cities from high-income countries drop out of the list of the 101 largest cities before 2100 (Table 4). Predicting population growth of cities is fraught with uncertainties, especially beyond Several researchers consider it unlikely that the world population will stabilize this century. (28) However, because much of today s infrastructure and resource development investments have planning horizons in excess of 50 years, credible best fit projections are necessary. Using WUP extrapolations (Figure 2D) as a possible scenario, a global population exceeding 12 billion by 2100 can be used as a cautionary approach until new information revises estimates. Estimates need to be regularly adjusted as data improves. Regional rankings are important as these often portend geopolitical and resource allocation dynamics. III. Results: Key Findings The reliability of data remains a concern. A consistent and explicit definition of each large urban area is needed for more accurate and reliable data collection. Estimates in this paper should be seen as educated guesses; however, they are sufficiently robust to influence critical infrastructure development in key cities. What the data reveals is that regardless of socioeconomic scenarios, sub-saharan Africa would have the most dramatic rise of large urban areas, growing from 7 in 2010 to approximately 20 in 2050 and over 30 in In all scenarios, by 2100 the SSA region will have the most cities in the largest 101 (ranging from 30 to 40). Current low urbanization rates are not consistent with scenario projections: the urbanization of Africa will have a significant impact on future sustainability. There will be far-reaching benefits to ensuring that sub-saharan Africa and other developing regions optimally progress, with enhanced local economic opportunity and adequate infrastructure, education and social policy, to curb population growth and resource depletion. Along with African cities, coastal cities are key sites of urban growth. Almost half of the larger cities are coastal, and some 25 are located in seismically active regions. Urban resilience is especially critical to longterm growth scenarios for these cities. Regarding the effects on high-income areas, globally, an unsustainable socioeconomic pathway (SSP3 fragmentation) has a dramatic effect on the rank of the largest cities in high-income regions. Fragmentation, i.e. unsustainable development, significantly reduces the number of highincome cities in the largest 101 (21 in SSP1 vs. 5 in SSP3 in 2100). In the 21st century, most high-income countries and their number of cities will decline in rank, relative to cities from low- and middle-income countries, especially if a more sustainable development trajectory is not followed. (29) A more sustainable socioeconomic pathway would correspond to a higher fraction of the global population living in the 101 largest cities, compared to a less sustainable pathway. Larger, faster-urbanizing cities promote sustainable development. Different socioeconomic scenarios apply very different growth pressures to large cities (Table 5). Lagos projected population in 2100, for example, varies from 61 million to 100 million (SSP1 vs SSP3). Depending on the path of development, the world population could range from 7.5 to 8.3 billion in 2025, 8.2 to 9.9 billion 28. Gerland, P, A Raftery, H Ševčíková, N Li, D Gu, T Spoorenberg, L Alkema, B Fosdick, J Chunn, N Lalic, G Bay, T Buettner, G Heilig and J Wilmoth (2014), World population stabilization unlikely this century, Science Vol 346, No 6206, pages ; also Cohen, B (2006), Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability, Technology in Society Vol 28, Nos 1 2, pages Grimm, N, S Faeth, N Golubiewski, C Redman, J Wu, X Bai and J Briggs (2008), Global Change and the Ecology of Cities, Science Vol 319, No 5864, pages

13 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES Table largest cities with WUP extrapolations City (millions) 1 Tokyo Tokyo Mumbai Kinshasa Lagos Mexico City Mumbai Delhi Mumbai Kinshasa Mumbai Delhi Dhaka Lagos Dar es Salaam Beijing Dhaka Kinshasa Delhi Mumbai São Paulo São Paulo Kolkata Dhaka Delhi New York Mexico City Lagos Kolkata Khartoum Delhi New York Tokyo Karachi Niamey Shanghai Kolkata Karachi Dar es Dhaka Salaam 9 Kolkata Shanghai New York Cairo Kolkata Dhaka Karachi Mexico City Manila Kabul Buenos Aires Kinshasa Cairo Kabul Karachi Karachi Lagos Manila Khartoum Nairobi Los Angeles Cairo São Paulo Tokyo Lilongwe Cairo Manila Shanghai Nairobi Blantyre Rio de Janeiro Beijing Lahore New York Cairo Manila Buenos Aires Kabul Baghdad Kampala Moscow Los Angeles Los Angeles Mexico City Manila Osaka-Kobe Rio de Janeiro Chennai Lahore Lusaka Istanbul Jakarta Khartoum Addis Ababa Mogadishu Lagos Istanbul Dar es Salaam Chennai Addis Ababa Seoul Guangzhou Beijing Bangalore Baghdad Paris Osaka-Kobe Jakarta São Paulo New York Jakarta Moscow Bangalore Shanghai N djamena Guangzhou Lahore Buenos Aires Niamey Kano Chicago (IL) Shenzhen Baghdad Kampala Sana a Kinshasa Chennai Hyderabad Hyderabad Lahore London Paris Luanda Luanda Chennai (Continued) 207

14 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Table 4 continued City (millions) 28 Lima Chicago Rio de Janeiro Los Angeles Tokyo Bogotá Tehran Nairobi Kano Bangalore Tehran Seoul Istanbul Jakarta Ibadan Shenzhen Bangalore Addis Ababa Ahmedabad Luanda Chennai Lima Guangzhou Sana a Hyderabad Wuhan Bogotá Ahmedabad Rio de Bamako Janeiro 34 Tianjin Wuhan Chittagong Buenos Aires Mexico City Hong Kong Tianjin Chicago Chittagong Dakar Bangalore Hyderabad Ho Chi Minh Mogadishu Maputo Lahore London Lima Beijing Shanghai Bangkok Bangkok Bogotá Abidjan Ouagadougou Hyderabad Hong Kong Shenzhen Lilongwe Antananarivo Chongqing Chongqing Paris Blantyre Los Angeles Santiago (BR) Luanda Bangkok Pune Rio de Janeiro Belo Ho Chi Minh Tehran Ibadan Ahmedabad Horizonte 43 Baghdad Baghdad Pune Istanbul Abidjan Santiago (CH) Khartoum Abidjan Dakar São Paulo Madrid Ahmedabad Kano Lusaka Chittagong Miami Chittagong Wuhan N djamena Abuja Toronto Kabul Moscow Ho Chi Minh Kigali Ahmedabad Santiago (BR) Osaka-Kobe Bamako Jakarta Ho Chi Minh Pune Tianjin Chicago Pune Philadelphia Hanoi Sana a Guangzhou Conakry Khartoum Belo Hanoi Bangkok Buenos Aires Horizonte 52 Singapore Santiago (CH) London Surat Beijing Barcelona Riyadh Seoul Lima Ho Chi Minh (Continued) 208

15 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES Table 4 continued City (millions) 54 Chittagong Miami Hong Kong Antananarivo Istanbul Pune Dongguan Kampala Alexandria Alexandria Dallas-Fort Shenyang Surat Bogotá Lubumbashi Worth 57 Shenyang Addis Ababa Chongqing Hanoi Chicago Riyadh Philadelphia Ibadan Abuja Surat Dongguan Abidjan Alexandria Ouagadougou Mbuji-Mayi St Petersburg Toronto Dakar Paris Mombasa Luanda Madrid Yangon Shenzhen Phnom Penh Hanoi Nairobi Riyadh Maputo Kaduna Atlanta Yangon Bamako Conakry Hanoi Houston Surat Miami Hong Kong Lima Boston Dar es Salaam Santiago (BR) Tehran Guangzhou Sydney Alexandria Kanpur Yangon Bangkok Philadelphia Wuhan Paris Washington. DC Dallas-Fort Worth 68 Aleppo Tlaquepaque Antananarivo Kanpur Kanpur Tlaquepaque Tonala Belo Horizonte London Al-Hudaydah Tonala Zapopan Faisalabad Tianjin Hong Kong Zapopan Chengdu Toronto Kigali Yangon Guadalajara Xi an. Shaanxi Abuja Faisalabad Monrovia Alexandria Barcelona Jaipur Lubumbashi Bogotá Yangon Atlanta Ouagadougou Moskva Benin City Chengdu Guiyang Niamey Jaipur Giza Detroit Singapore Santiago (CH) Mbuji-Mayi Faisalabad Xi an. Shaanxi Kano Dongguan Osaka-Kobe Accra Abidjan Houston Shenyang Riyadh Jaipur Surat Boston Mogadishu Chongqing Shenzhen Porto Alegre Guadalajara Giza Giza Ta izz Guadalupe Guadalupe Madrid Phnom Penh Lomé (Continued) 209

16 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Table 4 continued City (millions) 82 Monterrey Washington. DC Dallas-Fort Worth Lucknow Lucknow Melbourne Sydney Lucknow Mombasa Wuhan Guiyang Nanjing Tlaquepaque Miami Tianjin Jiangsu 85 Ankara Haerbin Tonala Philadelphia Douala Brasilia Porto Alegre Zapopan Kaduna London Montréal Detroit Atlanta Accra Riyadh Recife Kanpur Lubumbashi Nagpur Port Harcourt Nanjing Ankara Conakry Toronto Miami Jiangsu 90 Kabul Brasilia Houston Seoul Nagpur Haerbin Algiers Boston Aleppo Philadelphia Salvador St Petersburg Mbuji-Mayi Dallas-Fort Mosul Worth 93 Yokohama Monterrey Accra Lomé Chongqing Phoenix Sana a Aleppo Monrovia Moskva Johannesburg Recife Washington Douala Aleppo DC 96 Fortaleza Changchun Chengdu Al-Hudaydah Toronto Algiers Jaipur Sydney Patna Patna San Faisalabad Guadalajara Santiago (CH) Tehran Francisco- Oakland 99 Medellín Melbourne Nagpur Atlanta Osaka-Kobe Berlin Ibadan Xi an. Shaanxi Rawalpindi Dallas-Fort Worth 101 Addis Ababa Dakar Guadalupe Benin City Rawalpindi SUM , , ,

17 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES Table 5 Population projections of the 10 largest cities in and City (millions) SSP1 Tokyo Mumbai Mumbai Lagos Mumbai Delhi Lagos Mumbai Delhi Dhaka Delhi Kinshasa Beijing Kolkata Kinshasa Karachi Dhaka Karachi Dhaka Delhi Kolkata Tokyo Karachi Dar es Salaam Mexico City Kinshasa Kolkata Dhaka New York Lagos Dar es Salaam Kolkata Karachi Beijing Tokyo Nairobi São Paulo Mexico City New York Kampala SSP2 Tokyo Mumbai Lagos Lagos Mumbai Delhi Mumbai Dar es Salaam Delhi Dhaka Kinshasa Kinshasa Beijing Karachi Delhi Mumbai Mexico City Kolkata Karachi Karachi Kolkata Lagos Kolkata Delhi Dhaka Tokyo Dhaka Kolkata São Paulo Kinshasa Dar es Salaam Luanda New York Mexico City Luanda Dhaka Karachi Cairo Cairo Nairobi SSP3 Tokyo Lagos Lagos Lagos Mumbai Mumbai Mumbai Dar es Salaam Mexico City Mexico City Luanda Luanda São Paulo Karachi Karachi Karachi Beijing Dhaka Mexico City City Mumbai (Continued) 211

18 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 Table 5 continued City (millions) Delhi Delhi Dar es Salaam Kinshasa Dhaka Kolkata Dhaka Mexico City New York São Paulo Kinshasa Dhaka Kolkata Tokyo Delhi Delhi Karachi Kinshasa Kolkata Lusaka WUP Tokyo Mumbai Kinshasa Lagos Mumbai Delhi Mumbai Kinshasa Delhi Dhaka Lagos Dar es Salaam Dhaka Kinshasa Delhi Mumbai São Paulo Kolkata Dhaka Delhi Mexico City City Lagos Kolkata Khartoum New York Tokyo Karachi Niamey Kolkata Karachi Dar es Salaam Dhaka Shanghai New York Cairo Kolkata Karachi Mexico City City Manila Kabul SOURCE: values from supplementary information. 212

19 POPULATION PREDICTIONS FOR THE WORLD S LARGEST CITIES 30. Ostrom, E (2009), A General Framework for Analyzing Sustainability of Social- Ecological Systems, Science Vol 325, No 5939, pages ; also Ostrom, E (2014), A Polycentric Approach for Coping with Climate Change, Annals of Economics and Finance Vol 15, No 1, pages Hallegatte, S, C Green, R Nicholls and J Corffee-Morlot (2013), Future flood losses in major coastal Cities, Nature in 2050, 7.9 to 11.4 billion in 2075, and 6.9 to 13.1 billion in 2100, with more sustainable progress favouring lower population predictions. In all scenarios, the urbanization growth rate between 2010 and 2025 has significant implications for the urbanization rates in 2075 and 2100, with larger city growth in the first part of this century leading to more sustainable conditions after Cities may emerge as polycentric nodes of governance. (30) To date, the world is not on SSP1 a sustainable scenario. Strategic development of the current and future larger cities that promotes resource efficiency, as well as cooperation within and across global urban areas, is essential for sustainable development. IV. Discussion The size and shape of 21st century cities will determine much of the overall attainment of sustainable development. Various growth and sustainability scenarios (SSP1, SSP2 and SSP3) highlight the influence that urbanization and the world s larger urban areas have on total global population, resource consumption, and quality of life. Greater sustainability (SSP1) is characterized by a faster rate of urbanization, especially of larger cities (Figure 2A). This scenario suggests a total global population around 8 billion, peaking in Compare this to the fragmentation scenario (SSP3 Figure 2C) where the total population does not peak before 2100, and likely exceeds 14 billion. Projecting city growth, typified by Lagos growing from 10.6 million in 2010 to 88.3 million in 2100, calls for a healthy measure of scepticism; many variables could change. Projections used here are linked to the 2050 WUP city estimates that, especially in Africa, are suspect, and here these projections are extended for yet another 50 years, suggesting caution in their use. Africa s projected city growth is striking. For example, among Tanzania, Niger, Kenya, Malawi, Uganda, Zambia, Somalia, Chad, Mali, Senegal, Mozambique, Burkina Faso, Madagascar, Rwanda, Guinea, Liberia, Ghana, Togo and Cameroon (as well as Cambodia), none of these countries had a top city in 2010, yet all are projected to have at least one in Each country has a projected rate of urban population growth (SI, Section V), and despite this estimate being relatively conservative, significant city growth is still projected. Niamey, Niger for example is projected to grow from under 1 million inhabitants today to 56 million in Growth rates like these appear overstated, especially in one of the world s poorest countries with an insufficient economic base to support this rate of urbanization. However, in that same timeframe, under the UN medium fertility variant, Niger s population is projected to grow from 15 million to 210 million. How these newly enlarged cities will be governed is also critical. Managing a city in excess of 50 million inhabitants is a daunting task, especially as many of these cities are woefully under-serviced today. Sixty-five years is a relatively short timeframe with regard to urban infrastructure. Much of it, e.g. London s Underground and Rome s streets, is long-lived and can take decades to develop. A key driver of dampened urban growth may be climate change and rising sea levels. (31) Forty-seven of the projected 101 largest cities in 2100 are coastal, including the three largest cities: Lagos, Dar es Salaam and Mumbai. However, in the absence of more accurate population projections, estimates are important. Infrastructure and resource development plans 213

20 ENVIRONMENT & URBANIZATION Vol 29 No 1 April 2017 are developed with time horizons extending to the end of this century. Long-lived, large-scale urban infrastructure is being planned and built with future population estimates; these estimates should be clearly available and consistently used. Pending regular updates and refinements on urban area borders, the projections in this paper are considered a starting point. China is expected to experience a relatively large drop in the number of largest cities as overall population growth slows from 2030 onward. The size of cities will remain relatively consistent in the second half of the century; however, as many cities in regions like South Asia and Africa are growing considerably, the relative ranking of Chinese cities will decline. China, with its large economy, may consolidate the urban population in a few targeted cities. Population projections of Chinese cities may also be conservative as migrant workers might not be included in population estimates. Concerns with suggested findings are most apparent in sub-saharan Africa, where the extreme growth rates for cities are not supported by current urbanization rates. (32) Potts highlights how in many African countries urbanization rates are well below what is commonly believed. Urbanization rates in the cities of countries like Côte d Ivoire, Central African Republic, Kenya, Malawi, Nigeria, Tanzania, Zambia and Zimbabwe are often lower than overall national population growth rates and historically below 3 per cent per year for most. Africa s low urbanization rates are mostly attributable to the lack of commensurate economic development. (33) A major change to this phenomenon is not yet evident; also, some 70 per cent of Africa s urbanization is taking place in secondary cities. (34) Despite these concerns, with low rates of African urbanization in primary cities, the average aggregate population of the world s 101 largest cities is still projected to increase from 757 million in 2010 to 2.3 billion in 2100: a three-fold increase in average city size. The average large urban area would increase from 7.5 million in 2010 to about 23 million in Managing these large megacities, more than 50 of which are in excess of 15 million (while the top 10 are all in excess of 50 million), will place inordinate demands on urban managers and citizens. Planning and skill development should begin now. Cities are complex systems impacting many disciplines. Economists, planners, political scientists, and businesses (existing and potential) are all interested in projected growth and relative rankings of cities. As the pace of city-building grows, engineers and planners have an acute need for urban rules of thumb. All of the 101 largest urban areas are served by local engineering faculties. The engineering and planning professions would be well served by developing a peer-reviewed self-collected and regularly updated (ideally annually) urban database that, as a minimum, includes population projections, resource flows, and quality of life indicators. Where practicable this data collection should incorporate local and national census data, and international standards consistent with agencies such as the Global Cities Indicator Facility (ISO 37120). Historically, the world s largest cities drove the world s largest economies. The emergence of cities like N Djamena, Mogadishu, Blantyre and Lilongwe, which today are in impoverished economies, gives pause. So does the relative decline of the number of large Chinese cities. The city population projections provided in this paper are driven by national populations from shared socioeconomic pathways and estimated urbanization rates. These estimates will be further impacted by regional economies, resource availability, conflict, and possible geophysical and climate disasters. Climate Change Vol 3, pages ; also Hinkel, J, D Lincke, A Vafeidis, M Perrette, R Nicholls, R Tol, B Marzeion, X Fettweis, C Ionscu and A Levermann (2014), Coastal flood damage and adaptation costs under 21st century sea-level rise, Proceedings of the National Academy of Sciences Vol 111, No 9, pages ; and Blackburn, S and M Pelling (2014), Coastal Megacities: Risks and Opportunities, Global Change Vol 82, pages Potts, D (2009), The slowing of sub-saharan Africa s urbanization: evidence and implications for urban livelihoods, Environment and Urbanization Vol 21, No 1, pages ; also Potts, D (2011), Challenging the Myths of Urban Dynamics in Sub-Saharan Africa: The Evidence from Nigeria, World Development Vol 40, No 7, pages See reference 32, Potts (2009); also Arouri, M H, A Ben Youssef, H Mhenni and C Rault (2014), Energy Use and Economic Growth in Africa: A Granger Causality Panel Investigation, Economics Bulletin Vol 34, No 2, pages Racki, J, P Patel and D DeGroot (2014), Africa 2050: Urbanization, Global Journal of Emerging Market Economies Vol 61, No 1, pages