The statistic shows the ten largest cities in Australia in 2021. In 2021, around 5.26 million people lived in Sydney and the surrounding area, making it the most populous city in Australia.

Australia Population in Largest City: as % of Urban Population data was reported at 22.673 % in 2023. This records a decrease from the previous number of 22.893 % for 2022. Australia Population in Largest City: as % of Urban Population data is updated yearly, averaging 24.973 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 27.701 % in 1971 and a record low of 22.181 % in 2013. Australia 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 Australia – Table AU.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;

The statistic shows the total population of Australia from 1980 to 2021, with projections up until 2029. In 2021, Australia had a total population of about 25.77 million people. Population of Australia Australia is among the ten largest countries in the world, in terms of area size, although its total population is low in relation to this. Much of Australia’s interior remains uninhabited, as the majority of Australians live in coastal metropolises and cities. Most of the population is of European descent (predominantly British), although there is a growing share of the population with Asian heritage; only a small percentage belongs to the indigenous Aboriginal population. Australia's year-on-year population growth is fairly high compared to most other economically and demographically advanced nations, due to comparatively high rates of natural increase and immigration. Living standards Standard of living is fairly high in Australia, which can be seen when looking at the Human Development Index, which ranks countries by their level of human development and living standards, such as their unemployment rate, literacy rate, or life expectancy at birth. Life expectancy of Australia’s population is quite high in international comparison, for example, Australia is also among the leading countries when it comes to this key factor.

Economically speaking, Australia is also among the leading nations, with a steadily rising employment rate, an increasing gross domestic product (GDP) with a steady growth rate, and a relatively stable share in the global GDP.

Australia Population in Largest City data was reported at 5,235,407.000 Person in 2023. This records an increase from the previous number of 5,150,766.000 Person for 2022. Australia Population in Largest City data is updated yearly, averaging 3,691,137.500 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 5,235,407.000 Person in 2023 and a record low of 2,134,673.000 Person in 1960. Australia Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.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 June 2022, it was estimated that around 7.3 percent of Australians were aged between 25 and 29, and the same applied to people aged between 30 and 34. All in all, about 55 percent of Australia’s population was aged 35 years or older as of June 2022. At the same time, the age distribution of the country also shows that the share of children under 14 years old was still higher than that of people over 65 years old. A breakdown of Australia’s population growth Australia is the sixth-largest country in the world, yet with a population of around 26 million inhabitants, it is only sparsely populated. Since the 1970s, the population growth of Australia has remained fairly constant. While there was a slight rise in the Australian death rate in 2022, the birth rate of the country decreased after a slight rise in the previous year. The fact that the birth rate is almost double the size of its death rate gives the country one of the highest natural population growth rates of any high-income country.
National distribution of the population Australia’s population is expected to surpass 28 million people by 2028. The majority of its inhabitants live in the major cities. The most populated states are New South Wales, Victoria, and Queensland. Together, they account for over 75 percent of the population in Australia.

In 2023, approximately 988,943 people lived in Stockholm, making it not only the capital, but also the biggest city in Sweden. The second biggest city, Gothenburg (Göteborg) had about half as many inhabitants, with about 596,840 people. Move to the citySweden is a country with a very high urbanization rate, the likes of which is usually only seen in countries with large uninhabitable areas, such as Australia, or in nations with very little rural landscape and agrarian structures, like Cuba. So why do so few Swedes live in rural areas, even though based on total area, the country is one of the largest in Europe? The total population figures are the answer to this question, as Sweden has only about 10.3 million inhabitants as of 2018 – that’s only 25 inhabitants per square kilometer. Rural exodus or just par for the course?It is no mystery why most Swedes flock to the cities: Jobs, of course. Over 65 percent of Sweden’s gross domestic product is generated by the services sector, and agriculture only contributes about one percent to the GDP. Employment mirrors this, with 80 percent of the workforce being deployed in services, namely in foreign trade, telecommunications, and manufacturing, among other industries.

Australia Population Density: People per Square Km data was reported at 3.382 Person/sq km in 2022. This records an increase from the previous number of 3.339 Person/sq km for 2021. Australia Population Density: People per Square Km data is updated yearly, averaging 2.263 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 3.382 Person/sq km in 2022 and a record low of 1.365 Person/sq km in 1961. Australia Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Made possible by the Digital Atlas of Australia The Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.

Contact the Australian Bureau of Statistics If you have questions or feedback about this web service, please email geography@abs.gov.au. To subscribe to updates about ABS web services and geospatial products, please complete this form. For information about how the ABS manages any personal information you provide view the ABS privacy policy.

Data and geography references Source data publication: Population Projections, Australia, 2022 (base)

This web maps looks at the breakdown of who is renting, who is paying off the mortgage, and who owns their place outright. Using data from ABS Census 2021 General Community Profile release. This map shows the percentage of the population that is married. Data is available for Country, Greater Capital City Statistical Area (GCCSA), Local Government Area (LGA), Statistical Area Level 1 (SA1) and 2 (SA2), and State Suburb (SSC) boundaries.This map contains layers that contain some of the more commonly used variables from the General Community Profile information from the Australian Bureau of Statistics 2021 census. Data is available for Country, Greater Capital City Statistical Area (GCCSA), Local Government Area (LGA), Statistical Area Level 1 (SA1) and 2 (SA2), and Suburb and Localities (SAL) boundaries.The General Community Profile contains a series of tables showing the characteristics of persons, families and dwellings in a selected geographic area. The data is based on place of usual residence (that is, where people usually live, rather than where they were counted on Census night). Community Profiles are excellent tools for researching, planning and analysing geographic areas for a number of social, economic and demographic characteristics.Download the data here.Data and Geography notes:View the Readme files located in the DataPacks and GeoPackages zip files.To access the 2021 DataPacks, visit https://www.abs.gov.au/census/find-census-data/datapacksGlossary terms and definitions of classifications can be found in the 2021 Census DictionaryMore information about Census data products is available at https://www.abs.gov.au/census/guide-census-data/about-census-tools/datapacksDetailed geography information: https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/main-structure-and-greater-capital-city-statistical-areas: 2021 Statistical Area Level 1 (SA1), 2021 Statistical Area Level 2 (SA2), 2021 Greater Capital City Statistical Areas (GCCSA), 2021 Australia (AUS)https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/non-abs-structures: 2021 Suburbs and Localities (SAL), 2021 Local Government Areas (LGA)Please note that there are data assumptions that should be considered when analysing the ABS Census data. These are detailed within the Census documents referenced above. These include:Registered Marital StatusIn December 2017, amendments to the Marriage Act 1961 came into effect enabling marriage equality for all couples. For 2021, registered marriages include all couples.Core Activity Need for AssistanceMeasures the number of people with a profound or severe core activity limitation. People with a profound or severe core activity limitation are those needing assistance in their day to day lives in one or more of the three core activity areas of self-care, mobility and communication because of a long-term health condition (lasting six months or more), a disability (lasting six months or more), or old age. Number of Motor VehiclesExcludes motorbikes, motor scooters and heavy vehicles.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.Source: Australian Bureau of Statistics

This dataset contains time series for monthly precipitation over six sites (Blackheath, Braidwood, Darkes Forest, Goulburn, Lithgow and Moss Vale) in the Sydney Catchment Area (SCA) and monthly mean maximum and mean minimum temperature for three sites (Goulburn, Lithgow, and Moss Vale) in the SCA. This data was used in the study Attribution and Prediction of Precipitation and Temperature Trends within the Sydney Catchment Using Machine Learning. The data was originally from the Australian Bureau of Meteorology Climate Data Online (http://www.bom.gov.au/climate/data/index.shtml), but has been updated to have missing values (8% of data) filled using a moving average centred on the year for which the data is missing.

Below is the abstract for the paper:

Droughts in southeastern Australia can profoundly affect the water supply to Sydney, Australia's largest city. Increasing population, a warming climate, land surface changes, and expanded agricultural use increase water demand and reduce catchment runoff. Studying Sydney's water supply is necessary to manage water resources and lower the risk of severe water shortages. This study aims at understanding Sydney water supply by analysing precipitation and temperature trends across the catchment. A decreasing trend in annual precipitation was found across the Sydney catchment area. Annual precipitation also is significantly less variable, due to fewer years above the 80th percentile. These trends result from significant reductions in precipitation during spring and autumn, especially over the last 20 years. Wavelet analysis is applied to assess how the influence of climate drivers has changed over time. Attribute selection was carried out using linear regression and machine learning techniques including random forests and support vector regression. Drivers of annual precipitation included Niño3.4, SAM, DMI and measures of global warming such as the Tasman Sea Sea Surface temperature anomalies. The support vector regression model with a polynomial kernel achieved correlations of 0.921 and a skill score compared to climatology of 0.721. The linear regression model also performed well with a correlation of 0.815 and skill score of 0.567, highlighting the importance of considering both linear and non-linear methods when developing statistical models. Models were also developed on autumn and winter precipitation but performed worse than annual precipitation on prediction. For example, the best performing model on autumn precipitation, which accounts for approximately one quarter of annual precipitation, achieved an RMSE of 418.036 mm² on the testing data while annual precipitation achieved an RMSE of 613.704 mm². However, the seasonal models provided valuable insight into whether the season would be wet or dry compared to the climatology.

It should be noted that this data is now somwhat dated!

Human population density is a surrogate indicator of the extent of human pressures on the surrounding landscapes.

Areas with high population density are associated with higher levels of stream pollution and water diversion through sewers and drains. City and urban environments are substantially changed from their pre-European condition but a changed condition is not of itself necessarily poor by societal standards. It is the impacts such as polluted run-off to waterways, air pollution, sewage disposal, household water use and predation of wildlife by pets that confer impacts on catchment condition. Human population centres have an impact well beyond the built environment.

The impact of major population centres is well expressed in the AWRC map, but is best displayed in the 500 map. The main areas of impact are the major coastal and capital cities and suburbs, including popular beachside tourist destinations. Elsewhere, the impact of population density appears to be confined to the Murray and other major river valleys.

The Australian Bureau of Statistics compiles population statistics by sampling statistical local areas (SLAas) through the national census. These data can be converted to a per catchment basis.

Interpretation of the indicator is largely unequivocal, although there are land-uses/activities (e.g. mining) where population density is not a good indicator of the degree of habitat decline. This indicator has not been validated relative to habitat decline. This indicator is easy to understand.

Data are available as:

• continental maps at 5km (0.05 deg) cell resolution for the ILZ;
• spatial averages over CRES defined catchments (CRES, 2000) in the ILZ;
• spatial averages over the AWRC river basins in the ILZ.

See further metadata for more detail.

Since the 1960s, Australia's urbanization rate has consistently been above 80 percent, and in 2023 it has reached its highest ever rate at 86.62 percent. Historically, Australia has been one of the most urbanized countries in the world, due to high rates of immigration since the 20th century, which were generally to coastal, urban areas. However, despite its high urbanization rate, Australia is among the largest countries in the world; therefore its population density is among the lowest in the world.

In 2021, the proportion of Aboriginal and/or Torres Strait Islander people living in major cities in Australia amounted to 41.1 percent of the Aboriginal and/or Torres Strait Islander population. By comparison, 73.7 percent of the non-Indigenous population lived in major cities. Although the majority of the Aboriginal and/or Torres Strait Islander population lived in major cities and inner regional areas, almost one in ten lived in very remote communities.

This data set includes 1) customised geographies for 3047 settlements in Australia and their associated sociodemographic data as calculated from ABS data, and 2) detailed codes reflecting the legal protections for residential electricity customers across 12 selected indicators, which applied in each settlement in Australia on 1 July 2022. This data is best interpreted with the associated codebook, and the associated manuscript provides further details on the coding process.Geography identificationThe Australian Bureau of Statistics (ABS) Urban Centres and Localities (UCL) dataset identifies all settlements in Australia with populations of 200 or more people. There are also many smaller towns and settlements in Australia. To capture both large and small settlements, we developed a detailed settlement classification based on ABS’s smallest geographical units, Mesh Blocks (MBs), which cover the whole country without gaps or overlaps and which are intended to contain between 30 and 60 dwellings. Settlements have latitude and longitude of centre point included. We identified settlements using several steps:Estimated Residential Populations (ERP) at 30 June 2021 are imputed for every MB for the total population and the Indigenous population by progressively downscaling state/territory ERPs using Census counts tabulated at the SA4, SA3, SA2, SA1 and MB level.All MBs within a UCLs are allocated to that UCL.All remaining MBs classified by the ABS as being primarily used for residential purposes are grouped into clusters based on spatial contiguity.Clusters of MBs that are contiguous with a UCL are allocated to that UCL.Unallocated MB clusters are classified based on OpenStreetMap data. Specifically, a place name is allocated to a cluster of MBs if the MBs intersect an OpenStreetMap node with a “place” tag containing any of the values “city”, “town”, “village”, “hamlet” or “isolated_dwelling” and with a “name” tag.Unallocated MB clusters with a total ERP of 20 or less are excluded.Unallocated MB clusters that are within 10 km of a UCL are allocated to that UCL.Unallocated MB clusters that are within 10 km of a named OpenStreetMap place node (as above) are allocated to that place.Some outliers (e.g., prisons, a fracking field) were manually removed.Extensive manual checking against satellite photographs and other gazetteers was undertaken, especially of those MBs allocated to a settlement on the basis of distance to the closest named place. We manually added a number of named place nodes in OpenStreetMap based on a visual inspection of interim results.The exclusions column reflects 42 settlements (additional to the mapped 3047) for which names were identified but for which there is incomplete sociodemographic and policy data; we do not recommend using these settlements for analytical purposes.Sociodemographic data mapped to this settlement levelSEIFA indicators for the customised geographies, calculated as a population-weighted average of its constituent MBs. IRSAD, IRSD, IER, and IEO are included. See ABS for descriptions of these indicators.Remoteness as a dichotomous indicator (0 = 'Remote' or 'Very Remote'; 1 = ‘Major Cities’, ‘Inner Regional’, ‘Outer Regional’). Remoteness is determined from the ABS 2021 Remoteness Areas (see associated manuscript for further details).Estimated Resident Population (ERP).Percent of population that is Aboriginal or Torres Strait Islander People.Coding of legal protectionsData collection was completed during October 2021 to February 2023 and included review of 284 legal documents to identify protections in each settlement (reflected in respective "Agency, document" columns). Regulatory environment at the settlement level was cross-checked with review of over 800 further documents to ensure no exceptions were overlooked. Settlements were coded based on their legal protections up to and including 1 July 2022. Regulation undergoes frequent iteration, and there were many pending changes variously proposed, in draft form or in the process of introduction during our review. For example, one major change not captured by review is the transfer for responsibility for electricity services for 141 remote Aboriginal communities in WA (Remote Essential and Municipal Services communities) from the Department of Communities to the licensed utility Horizon Power (effective 1 April 2023). Document review focused on consumer focused electricity retail regulation (such as the National Energy Retail Law, NERL). Where categories of interest for electricity services fell within distributor remit as opposed to retailer remit (such as solar connections), we reviewed the appropriate documents associated with that level of electricity regulation (such as the National Electricity Rules (NER) made by the Australian Energy Market Commission (AEMC) under the NEL). Further details on the regulatory review process are included in the associated manuscript.We mapped twelve categories, separately recording prepay and post-pay customer protections where applicable. Separate coding of prepay and post-pay was undertaken due to the different types of legal protections afforded to customers for each of these payment types. The coding questions are as follows:Is the use of prepayment meters expressly prohibited by act, regulation, code, or licence condition?Are protections from disconnection due to non-payment required for life support customers pursuant to act, regulation, code or licence condition? (pre and post)Is the retailer required to have a family violence policy pursuant to act, regulation, code or licence condition? (pre and post)Is the retailer required to provide protections from disconnection/self-disconnection during an extreme weather event pursuant to act, regulation, code, or licence condition? (pre and post)Does an act, regulation, code or licence condition establish a guaranteed service level scheme which the distributor must adhere to regarding unplanned interruptions in the customer's electricity supply? (pre and post)What type of discretion does the regulation establish for customer right to connect residential solar?In the contract (such as a model standing offer) that a customer would refer to when connecting solar to a distribution network, are there clear eligibility criteria laid out under which the consumer could reasonably expect the distributor to approve a connection request for solar? (pre and post)Is the retailer required to report total numbers of customer disconnections for non‐payment (i.e., disconnections in the case of post-pay or so-called ‘self‐disconnections’ in the case of prepay) pursuant to act, regulation, code, or licence condition? (pre and post)Does an act, regulation, code, or licence condition require the retailer to have and publish customer complaints / dispute resolution procedures? (pre and post)Does an act, regulation, code, or licence condition require the retailer to be subject to an independent investigation and resolution process e.g., ombudsman scheme in relation to customer complaints / disputes? (pre and post)Does an act, regulation, code, or licence condition require the distributor to have and publish customer complaint / dispute resolution procedures? (pre and post)Does legislation, regulation, code, or licence condition require the distributor to be subject to an independent investigation and resolution process e.g., ombudsman scheme in relation to customer complaints / disputes? (pre and post)In addition to recording these protections, we also assessed:Do individual residential customers have a direct contractual relationship (e.g., a retail contract) with the utility?Is the settlement located within the National Electricity Market (NEM) (i.e., part of the interconnected network)?What category of NEM and consumer protections regime does the location belong to? (where the category is descriptive of the type of network (e.g., interconnected, isolated) and regulatory framework (e.g., NERL, local code) which applies for residential customers in each case).The Stata do file is included for ease of aggregating (changing) indicator assignment.

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]

Four of Australia's largest five population centres are topographically constrained by prominent escarpments (i.e. Sydney, Melbourne, Perth, Adelaide). These escarpments are underlain by faults or fault complexes capable of hosting damaging earthquakes. Paleoseismological investigations over the last decade indicate that the seismogenic character (e.g. recurrence and magnitude) of these structures varies markedly. Uplift rates on range bounding faults in the Mount Lofty Ranges suggest average recurrence times on individual faults for Mmax earthquakes (MW 7.1-7.4) in the order of 10-20 ka. A high density of faults with demonstrated Late Quaternary surface rupture occurring proximally to Adelaide suggests recurrence times for damaging ground shaking at a given location from earthquakes on these faults in the hundreds to low thousands of years. Uplift rates on faults proximal to Melbourne (and the Latrobe Valley, where much of Melbourne's power is generated) in some cases exceed those of the Mount Lofty Ranges. However, a lower relative density of seismogenic faults proximal to the conurbation of Melbourne is suggestive of a lesser hazard than for Adelaide. In contrast to Melbourne and Adelaide, paleoseismological investigations on the Darling Fault near Perth, and the Lapstone Structural Complex near Sydney, indicate average recurrence for Mmax events in the hundreds of thousands to millions of years. Of course, distal larger events and proximal sub-Mmax events have been demonstrated to be damaging in these areas (e.g. 1968 Ms6.8 Meckering, 1989 ML5.6 Newcastle). The same is true for Adelaide and Melbourne (e.g. 1954 ML5.4 Adelaide, 2012 ML 5.4 Moe). Further research is required to demonstrate that earthquakes of sub-morphogenic and morphogenic magnitude might be modelled on the same Guttenberg-Richter distribution curve.

With 109.9 men per one hundred women in the city, the greater Darwin area in Australia has the highest sex ratio. This is in stark contrast to the demographics of the other major cities in Australia which have more women than men. This is consistent with the fact that more than two thirds of all women between 25 and 64 participating in the workforce.Despite this fact, there is still some disparity between men and women in high level position as women are multiple times more likely to be sexually assaulted while men are much more likely to be victims of murder.The perpetrators of crimes are also much more likely to be men as there are

最大城市人口占城市总人口的百分比在12-01-2023达22.673%，相较于12-01-2022的22.893%有所下降。最大城市人口占城市总人口的百分比数据按年更新，12-01-1960至12-01-2023期间平均值为24.973%，共64份观测结果。该数据的历史最高值出现于12-01-1971，达27.701%，而历史最低值则出现于12-01-2013，为22.181%。CEIC提供的最大城市人口占城市总人口的百分比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澳大利亚 – Table AU.World Bank.WDI: Population and Urbanization Statistics。

At the 2021 Australian census, 278,043 people in New South Wales were Aboriginal or Torres Strait Islander. New South Wales is Australia’s most populated state, also housing Australia’s largest city, Sydney. By comparison, Australia’s second largest state, Victoria, was home to around 66 thousand Aboriginal and Torres Strait Islander people.

Aboriginal and Torres Strait Islander peoples

There are around 800,000 Aboriginal and Torres Strait Islander people in Australia, which represents just over three percent of the Australian population. Indigenous people are often referred to as Australia's first people or the traditional custodians of the land in recognition of their ancestors inhabiting Australia more than 60,000 years ago. Australia's Indigenous peoples are represented by two distinct groups. Aboriginal people come from the Australian mainland. Torres Strait Islander people inhabit the group of Islands between the northern tip of Queensland and Papua New Guinea and represent less than 40,000 people.

Closing the gap

Aboriginal and Torres Strait Islander peoples experience significantly poorer health and wellbeing outcomes when compared to their non-Indigenous Australian counterparts. The average life expectancy of Indigenous Australians is around eight years shorter than that of the non-Indigenous population. In education, Indigenous Australians are also underrepresented, but attendance rates are improving and in 2019, full-time Aboriginal and Torres Strait Islander students numbered well over 200,000 people.

(Note: Excludes cases for whom sex, age and organism were unknown. Population sizes are the ABS mid-year estimated residential populations for 2019).