This statistic shows a forecast of the top ten most populous megacities in 2030. By 2030, Tokyo will be the most populous city in the world, with a projected 37 million inhabitants.

In 2024, Bangladesh's capital Dhaka had a pollution index score of 93.9, the highest among megacities in the Asia-Pacific region. In contrast, Japan's capital Tokyo had a pollution index score of 42.2 that year. Megacities on course for growth The United Nations defines megacities as cities with over ten million inhabitants. The population living in megacities has doubled in size in the last twenty years and is expected to rise even more until 2035. Today, the Asia-Pacific region is home to the highest number of megacities, with China and India alone accounting for around half of all megacities worldwide. At the same time, only half of the population in Asia is living in cities. This figure is also expected to rise exponentially over the next years, especially with much of the younger population migrating to larger cities. The growth of megacities and their higher population densities bring along several environmental problems. Exposure to pollution in India The most populated cities in APAC are located in Japan, China and India. As seen above, India's capital also falls among the top three most polluted megacities in the region and ranks second among the most polluted capital cities worldwide with an average PM2.5 concentration. As one of the fastest emerging economies in the world, India's rapid urbanization and industrialization have led to high pollution rates in different areas. The volume of emissions from coal-fired power plants has led to electricity and heat accounting for the largest share of greenhouse gas emissions in India. The country is also among the nations with the highest population share exposed to hazardous concentrations of air pollution worldwide.

As of January 2024, Guangzhou had the largest metropolitan population in the Asia-Pacific region, with approximately 70.1 million inhabitants. Tokyo had the second-largest metropolitan population of around 41 million inhabitants. There were a total of 28 megacities with a population of over 10 million inhabitants in the Asia-Pacific region as of January 2024.

This database provides the construction of Large Urban Regions (LUR) in the world. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the areas of economic influence of a core into one statistical unit (see Rozenblat, 2020 or Rogov & Rozenblat, 2020 for Russia). In doing so we use four principal urban concepts (Pumain et al., 1992): local administrative units (Municipality or localities: MUNI), morphological urban area (MUA), functional urban area (FUA), and conurbation that we call Large Urban Region (LUR). The LURs are the spatial extensions of the influence of one or several FUAs or MUAs. MUAs and FUAs are defined by various national or international sources. We implemented LURs using criteria such as the population distribution among one or several MUAs or FUAs, road networks, access to an airport, distance from a core, and presence of multinational firms. FUAs and MUAs perimeters, if they form a part of a LUR, belong to a unique LUR. In this database, we provide the composition of the LURs in terms of local administrative units (MUNI), Morphological Urban Areas (MUA), and Functional Urban Areas (FUA).

This last update provides new LURs for the 54 African Countries (see Rogromel & Rozenblat, 2024) and some corrections for China.

It includes now 1'828 LURs composed of 130'283 localities.

Cities ranking and mega citiesTokyo is the world’s largest city with an agglomeration of 37 million inhabitants, followed by New Delhi with 29 million, Shanghai with 26 million, and Mexico City and São Paulo, each with around 22 million inhabitants. Today, Cairo, Mumbai, Beijing and Dhaka all have close to 20 million inhabitants. By 2020, Tokyo’s population is projected to begin to decline, while Delhi is projected to continue growing and to become the most populous city in the world around 2028.By 2030, the world is projected to have 43 megacities with more than 10 million inhabitants, most of them in developing regions. However, some of the fastest-growing urban agglomerations are cities with fewer than 1 million inhabitants, many of them located in Asia and Africa. While one in eight people live in 33 megacities worldwide, close to half of the world’s urban dwellers reside in much smaller settlements with fewer than 500,000 inhabitants.About the dataThe 2018 Revision of the World Urbanization Prospects is published by the Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). It has been issued regularly since 1988 with revised estimates and projections of the urban and rural populations for all countries of the world, and of their major urban agglomerations. The data set and related materials are available at: https://esa.un.org/unpd/wup/

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONThe Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading environmental science textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards and AP Environmental Science benchmarks. All Advanced Environmental Science GeoInquiries™ can be found at: http://esriurl.com/EnviroGeoInquiries All GeoInquiries™ can be found at: http://www.esri.com/geoinquiries

In a survey conducted in 2022 among respondents from megacities of India, Surat emerged on the top in terms of clean mobility with a score of 0.61, among all megacities of India. It was closely followed by Chennai and Pune-Pimpri-Chinwad. The parameter of clean mobility includes impact of air pollution, clean mobility focused policies, willingness to adopt electric mobility, among others. Megacities are defined as the cities with a population of over four million as per the survey. The Ease of Moving Index is a composite index comprising nine parameters across 41 indicators. The parameters include seamless, inclusive, clean, efficient and shared mobility and investment in the city among others.

BackgroundWorld population growth is projected to be concentrated in megacities, with increases in social inequality and urbanization-associated stress. São Paulo Metropolitan Area (SPMA) provides a forewarning of the burden of mental disorders in urban settings in developing world. The aim of this study is to estimate prevalence, severity, and treatment of recently active DSM-IV mental disorders. We examined socio-demographic correlates, aspects of urban living such as internal migration, exposure to violence, and neighborhood-level social deprivation with 12-month mental disorders. Methods and ResultsA representative cross-sectional household sample of 5,037 adults was interviewed face-to-face using the WHO Composite International Diagnostic Interview (CIDI), to generate diagnoses of DSM-IV mental disorders within 12 months of interview, disorder severity, and treatment. Administrative data on neighborhood social deprivation were gathered. Multiple logistic regression was used to evaluate individual and contextual correlates of disorders, severity, and treatment. Around thirty percent of respondents reported a 12-month disorder, with an even distribution across severity levels. Anxiety disorders were the most common disorders (affecting 19.9%), followed by mood (11%), impulse-control (4.3%), and substance use (3.6%) disorders. Exposure to crime was associated with all four types of disorder. Migrants had low prevalence of all four types compared to stable residents. High urbanicity was associated with impulse-control disorders and high social deprivation with substance use disorders. Vulnerable subgroups were observed: women and migrant men living in most deprived areas. Only one-third of serious cases had received treatment in the previous year. DiscussionAdults living in São Paulo megacity had prevalence of mental disorders at greater levels than similar surveys conducted in other areas of the world. Integration of mental health promotion and care into the rapidly expanding Brazilian primary health system should be strengthened. This strategy might become a model for poorly resourced and highly populated developing countries.

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards. Activity topics include:• Population dynamics • Megacities • Down to the last drop • Dead zones (water pollution) • The Beagle’s Path • Primary productivity • Tropical Deforestation • Marine debris • El Nino (and climate) • Slowing malaria • Altered biomes • Spinning up wind power • Resource consumption and wealthTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

This data is from an internet survey of 4,500 individuals from the cities of Jakarta, Beijing, and Delhi. The surveys were conducted around early-2019. The survey contains questions on basic socioeconomic characteristics, and their responses to contingent valuation questions on willingness to pay for improved air quality. The data were collected using online surveys to carry out a contingent valuation for air quality improvements in three Asian megacities facing severe pollution problems – Beijing, Delhi, and Jakarta. ProbabilityProbability SannolikhetsurvalSannolikhetsurval Web-based interviewWeb-based interview Webbaserad intervjuWebbaserad intervju

These shapefiles contain the data for the GISP model for Los Angeles, New York City, and Manila as described in Meerow (2019) A Green Infrastructure Spatial Planning model for evaluating ecosystem service tradeoffs and synergies across three coastal megacities. https://iopscience.iop.org/article/10.1088/1748-9326/ab502c For each dataset crit01 is criterion 1 (managing stormwater); crit02 is criterion 2 (reducing social vulnerability), crit03 is criterion 3 (increasing access to green space), crit04 is criterion 4 (reducing the urban heat island effect), crit05 is criterion 5 (improving air quality), and crit06 is criterion 6 (increasing landscape connectivity). equal_w is a weighted linear combination of all six criteria using equal weights and pairwise_w is a weighted linear combination of all six criteria using stakeholder pairwise comparison weights.

In 2024, Seoul had the highest grocery index score of all the Asia-Pacific megacities, scoring 92.1 points. Contrastingly, Delhi had a grocery index score of 23.8 in 2024.

As of 2023, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37,8 million people living there. Jakarta ranked second with 34 million, with Delhi in third with 32 million inhabitants.

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

The COVID-19 pandemic perturbed air pollutant emissions as cities shut down worldwide. Peroxyacyl nitrates (PANs) are important tracers of photochemistry that are formed through the oxidation of non-methane volatile organic compounds (NMVOCs) in the presence of nitrogen oxide radicals (NOx = NO + NO2). We use satellite measurements of free tropospheric PANs from the S-NPP Cross-Track Infrared Sounder (CrIS) over eight of the world’s megacities: Mexico City, Beijing, Los Angeles, Tokyo, São Paulo, Delhi, Lagos, and Karachi. We quantify the seasonal cycle of PANs over these megacities and find seasonal maxima in PANs correspond to seasonal peaks in local photochemistry. CrIS is used to explore changes in PANs in response to the COVID-19 lockdowns. Statistically significant changes to PANs occurred over two megacities: Los Angeles (PAN decreased) and Beijing (PAN increased). Our analysis suggests that large perturbations in NOx may not result in significant declines in NOx export poten...

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

This data has been collected to parameterize the Multimedia Urban Model for 19 different mega or major cities. The data collected here can be used with the model, which is available from https://github.com/tfmrodge/FugModel, to estimate the transport and fate of organic contaminants from urban areas.