In 2023, Prague was the most populous city in Czechia with nearly 1.38 million inhabitants. Brno was the second largest city in population with over 400 thousand inhabitants, followed by Ostrava with a population of 317.5 thousand.

Czech Republic CZ: Population in Largest City data was reported at 1,323,339.000 Person in 2023. This records an increase from the previous number of 1,318,085.000 Person for 2022. Czech Republic CZ: Population in Largest City data is updated yearly, averaging 1,191,039.000 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 1,323,339.000 Person in 2023 and a record low of 1,000,830.000 Person in 1960. Czech Republic CZ: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Czech Republic – Table CZ.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

In 2023, the largest city in Czechia was its capital, Prague, with a population of more than 1.3 million. Together with Brno and Ostrava, these were the only three cities with more than 200,000 people.

Czech Republic CZ: Population in Largest City: as % of Urban Population data was reported at 16.339 % in 2023. This records a decrease from the previous number of 16.606 % for 2022. Czech Republic CZ: Population in Largest City: as % of Urban Population data is updated yearly, averaging 16.010 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 17.504 % in 1960 and a record low of 15.216 % in 1980. Czech Republic CZ: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Czech Republic – Table CZ.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

Prague had the highest population of any city in Czechia and also had the highest number of companies with a cryptocurrency ATM or in-store payment method in 2021. According to open-source information, the Czech capital city even had a relatively high amount of these firms, especially when compared against the second-largest city of Brno - a city with roughly one-third of the population of Prague but approximately 25 percent the amount of businesses.

最大城市人口在12-01-2023达1,323,339.000人，相较于12-01-2022的1,318,085.000人有所增长。最大城市人口数据按年更新，12-01-1960至12-01-2023期间平均值为1,191,039.000人，共64份观测结果。该数据的历史最高值出现于12-01-2023，达1,323,339.000人，而历史最低值则出现于12-01-1960，为1,000,830.000人。CEIC提供的最大城市人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的捷克共和国 – Table CZ.World Bank.WDI: Population and Urbanization Statistics。

The smart city platforms market analysis report by Future Market Insights reveals that global sales of the smart city platforms market in 2022 were held at US$ 157.6 billion. The projected market growth from 2023 to 2033 is expected to be 11%.

Attributes	Details
Global Smart City Platforms Market Size (2023)	US$ 175 billion
Global Smart City Platforms Market Size (2033)	US$ 496.9 billion
Global Smart City Platforms Market CAGR (2023 to 2033)	11%

Scope of Report

Report Attributes	Details
Growth Rate	CAGR of 11% from 2023 to 2033
Base Year for Estimation	2023
Historical Data	2018 to 2022
Forecast Period	2023 to 2033
Global Smart City Platforms Market Size (2023)	US$ 175 billion
Global Smart City Platforms Market Size (2033)	US$ 496.9 billion
Quantitative Units	Revenue in US$ million and CAGR from 2023 to 2033
Report Coverage	Revenue Forecast, Volume Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends, and Pricing Analysis
Segments Covered	Offering Delivery Model Application Region
Regions Covered	North America Latin America Western Europe Eastern Europe Asia Pacific excluding Japan Japan The Middle East and Africa
Key Countries Profiled	The United States Canada Brazil Mexico Germany The United Kingdom France Spain Italy Poland Russia Czech Republic India Bangladesh Australia New Zealand China Japan South Korea GCC Countries South Africa Israel
Customization	Available Upon Request

Abstract

Polluted air is a major health hazard in developing countries. Improvements in pollution monitoring and statistical techniques during the last several decades have steadily enhanced the ability to measure the health effects of air pollution. Current methods can detect significant increases in the incidence of cardiopulmonary and respiratory diseases, coughing, bronchitis, and lung cancer, as well as premature deaths from these diseases resulting from elevated concentrations of ambient Particulate Matter (Holgate 1999).

Scarce public resources have limited the monitoring of atmospheric particulate matter (PM) concentrations in developing countries, despite their large potential health effects. As a result, policymakers in many developing countries remain uncertain about the exposure of their residents to PM air pollution. The Global Model of Ambient Particulates (GMAPS) is an attempt to bridge this information gap through an econometrically estimated model for predicting PM levels in world cities (Pandey et al. forthcoming).

The estimation model is based on the latest available monitored PM pollution data from the World Health Organization, supplemented by data from other reliable sources. The current model can be used to estimate PM levels in urban residential areas and non-residential pollution hotspots. The results of the model are used to project annual average ambient PM concentrations for residential and non-residential areas in 3,226 world cities with populations larger than 100,000, as well as national capitals.

The study finds wide, systematic variations in ambient PM concentrations, both across world cities and over time. PM concentrations have risen at a slower rate than total emissions. Overall emission levels have been rising, especially for poorer countries, at nearly 6 percent per year. PM concentrations have not increased by as much, due to improvements in technology and structural shifts in the world economy. Additionally, within-country variations in PM levels can diverge greatly (by a factor of 5 in some cases), because of the direct and indirect effects of geo-climatic factors.

The primary determinants of PM concentrations are the scale and composition of economic activity, population, the energy mix, the strength of local pollution regulation, and geographic and atmospheric conditions that affect pollutant dispersion in the atmosphere.

Geographic coverage

The database covers the following countries: Afghanistan Albania Algeria Andorra Angola
Antigua and Barbuda Argentina
Armenia Australia
Austria Azerbaijan
Bahamas, The
Bahrain Bangladesh
Barbados
Belarus Belgium Belize
Benin
Bhutan
Bolivia Bosnia and Herzegovina
Brazil
Brunei
Bulgaria
Burkina Faso
Burundi Cambodia
Cameroon
Canada
Cayman Islands
Central African Republic
Chad
Chile
China
Colombia
Comoros Congo, Dem. Rep.
Congo, Rep. Costa Rica
Cote d'Ivoire
Croatia Cuba
Cyprus
Czech Republic
Denmark Dominica
Dominican Republic
Ecuador Egypt, Arab Rep.
El Salvador Eritrea Estonia Ethiopia
Faeroe Islands
Fiji
Finland France
Gabon
Gambia, The Georgia Germany Ghana
Greece
Grenada Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hong Kong, China
Hungary Iceland India
Indonesia
Iran, Islamic Rep.
Iraq
Ireland Israel
Italy
Jamaica Japan
Jordan
Kazakhstan
Kenya
Korea, Dem. Rep.
Korea, Rep. Kuwait
Kyrgyz Republic Lao PDR Latvia
Lebanon Lesotho Liberia Liechtenstein
Lithuania
Luxembourg
Macao, China
Macedonia, FYR
Madagascar
Malawi
Malaysia
Maldives
Mali
Mauritania
Mexico
Moldova Mongolia
Morocco Mozambique
Myanmar Namibia Nepal
Netherlands Netherlands Antilles
New Caledonia
New Zealand Nicaragua
Niger
Nigeria Norway
Oman
Pakistan
Panama
Papua New Guinea
Paraguay
Peru
Philippines Poland
Portugal
Puerto Rico Qatar
Romania Russian Federation
Rwanda
Sao Tome and Principe
Saudi Arabia
Senegal Sierra Leone
Singapore
Slovak Republic Slovenia
Solomon Islands Somalia South Africa
Spain
Sri Lanka
St. Kitts and Nevis St. Lucia
St. Vincent and the Grenadines
Sudan
Suriname
Swaziland
Sweden
Switzerland Syrian Arab Republic
Tajikistan
Tanzania
Thailand
Togo
Trinidad and Tobago Tunisia Turkey
Turkmenistan
Uganda
Ukraine United Arab Emirates
United Kingdom
United States
Uruguay Uzbekistan
Vanuatu Venezuela, RB
Vietnam Virgin Islands (U.S.)
Yemen, Rep. Yugoslavia, FR (Serbia/Montenegro)
Zambia
Zimbabwe

Kind of data

Observation data/ratings [obs]

Mode of data collection

Other [oth]