NXS-GRX-ARG · South America · Regions

Buenos Aires

First-level unit, Argentina: people, area, the units inside and neighbours, with risk values when released.

Page GRX-ARG-REdition Baseline Edition 2026Evidence close 2026-09-30ISO ARG / ARStatus UN member stateValues not yet publishedMethod v1.0.0-draft

12,320,230

people (GHSL 2025)

382,902 km²

area

28.8%

of Argentina

140

units inside

01Map

Inside Buenos Aires

The 140 ADM2 units of Buenos Aires.

FIG 1 · 140 units inside Buenos Aires

Loading the map

Colour by

Units rise with people per km² · GHSL 2025 raster · terrain · ADM1 ADM2Risk values when released

Lowest fifthLow fifthMiddle fifthHigh fifthHighest fifthNo data

Column height and colour show people per km² by unit, in quantile fifths among the units shown (the key on the map gives the breaks); units with no people on the grid are grey, not the lowest class; the raster beneath is the GHSL 2025 population grid. Source observations, not index values. Choose a humanitarian figure from the list to colour and raise the units by it; each figure shows its source on the unit page. Select a unit to drill into the units inside it; the path above the map climbs back.

02Figures

People, area and density

Source observations from open grids summed inside the boundary; not index values.

People · GHSL 2025

12,320,230

28.8% of Argentina.

People · WorldPop 2025

12,304,337

0% against GHSL; the two grids differ in method.

Area

382,902 km²

32 people per km².

Code

AR-B

Subdivision code as carried by the boundary source.

Low coastal zone

1,776,133

people on land at or below 10 m, 14.4% of the unit (GEBCO 2024 and GHSL 2025).

03Humanitarian data

Buenos Aires in humanitarian data

Source observations from the Humanitarian Data Exchange, matched to this unit by name, each with its reference date, provider and licence. They are not index values.

Population · 2021-12-31

17,709,598

people. UNFPA · Creative Commons Attribution for Intergovernmental Organisations (CC BY-IGO).

04Units

140 units inside Buenos Aires

Each unit has its own page.

Boundary licences: Creative Commons Attribution 2.5 Generic · Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO)

Filter units

Unit	Code	People (GHSL)	People (WorldPop)	Area km²	Per km²	Share	Coast ≤ 10 m
25 de Mayo	–	41,604	34,095	4,781.11	9	0.3%	0
9 de Julio	–	53,779	50,656	4,288.2	13	0.4%	0
Adolfo Alsina	–	20,257	16,392	5,858.07	3	0.2%	0
Adolfo Gonzáles Chaves	–	13,871	12,771	3,786.84	4	0.1%	0
Alberti	–	12,265	12,419	1,115.63	11	0.1%	0
Almirante Brown	–	685,645	669,687	129.53	5,293	5.4%	70,014
Arrecifes	–	34,136	31,515	1,240.5	28	0.3%	0
Ayacucho	–	23,454	21,803	6,749.81	3	0.2%	0
Azul	–	76,253	74,873	6,531.98	12	0.6%	0
Bahía Blanca	–	326,632	327,070	2,249.01	145	2.6%	69,337
Balcarce	–	52,140	51,334	4,119.8	13	0.4%	0
Baradero	–	33,612	35,574	1,530.16	22	0.3%	3,003
Benito Juárez	–	24,024	21,468	5,347.87	4	0.2%	0
Berazategui	–	382,719	380,997	220.12	1,739	3%	73,197
Berisso	–	93,692	89,402	144.57	648	0.7%	89,823
Bolívar	–	40,381	36,571	4,928.59	8	0.3%	0
Bragado	–	48,985	44,516	2,201.08	22	0.4%	0
Brandsen	–	30,696	32,453	1,117.81	27	0.2%	270
Campana	–	101,320	100,453	988.81	102	0.8%	54,527
Cañuelas	–	69,669	88,161	1,190.29	59	0.6%	0
Capitán Sarmiento	–	17,862	15,878	549.54	33	0.1%	0
Carlos Casares	–	26,551	22,870	2,522.18	11	0.2%	0
Carlos Tejedor	–	13,436	12,908	3,910.06	3	0.1%	0
Carmen de Areco	–	17,250	17,264	1,061.4	16	0.1%	0
Castelli	–	9,615	10,854	2,114.7	5	0.1%	4,770
Chacabuco	–	56,650	51,394	2,296.12	25	0.4%	0
Chascomús	–	42,664	42,455	3,164.69	13	0.3%	19,475
Chivilcoy	–	76,180	70,733	2,055.18	37	0.6%	0
Colón	–	29,101	26,725	998.65	29	0.2%	0
Colón	–	58,313	62,358	2,762.7	21	0.5%	11,994
Concordia	–	167,116	177,142	3,279.66	51	1.3%	6,306
Coronel de Marina L. Rosales	–	68,396	62,845	1,291.34	53	0.5%	34,206
Coronel Dorrego	–	18,104	14,891	5,836.15	3	0.1%	349
Coronel Pringles	–	26,149	23,761	5,258.33	5	0.2%	0
Coronel Suárez	–	46,216	43,748	5,969.01	8	0.4%	0
Daireaux	–	20,157	18,983	3,820.17	5	0.2%	0
Diamante	–	50,850	51,958	2,680.27	19	0.4%	351
Dolores	–	31,445	30,512	1,971.5	16	0.2%	24,780
Ensenada	–	66,771	63,117	113.4	589	0.5%	60,519
Escobar	–	265,480	277,838	302	879	2.1%	71,734
Esteban Echeverría	–	310,288	296,785	121.76	2,548	2.5%	65,629
Exaltación de la Cruz	–	38,858	47,215	635.6	61	0.3%	262
Ezeiza	–	222,881	222,240	237.45	939	1.8%	6,156
Federación	–	77,118	78,847	3,775.52	20	0.6%	0
Federal	–	28,106	29,497	5,217.53	5	0.2%	0
Feliciano	–	16,502	16,423	3,174.98	5	0.1%	0
Florencio Varela	–	510,975	547,759	190.33	2,685	4.1%	26,458
Florentino Ameghino	–	10,097	9,062	1,808.32	6	0.1%	0
General Alvarado	–	21,321	21,844	1,629.41	13	0.2%	1,885
General Alvear	–	13,189	9,178	3,367.23	4	0.1%	0
General Arenales	–	17,110	15,624	1,485.09	12	0.1%	0
General Belgrano	–	20,667	21,306	1,849.28	11	0.2%	0
General Guido	–	3,416	3,400	2,325.28	1	0%	1,422
General Juan Madariaga	–	31,177	31,446	2,983.6	10	0.2%	29,036
General La Madrid	–	12,360	11,498	4,811.53	3	0.1%	0
General Las Heras	–	16,118	16,612	752.23	21	0.1%	0
General Lavalle	–	18,440	24,921	2,692.31	7	0.1%	17,964
General Paz	–	13,398	14,662	1,197.65	11	0.1%	0
General Pinto	–	13,161	12,085	2,553.63	5	0.1%	0
General Pueyrredón	–	586,216	562,398	1,462.05	401	4.7%	3,018
General Rodríguez	–	75,002	116,730	364.55	206	0.6%	0
General Viamonte	–	19,018	18,100	2,144.52	9	0.2%	0
General Villegas	–	37,298	34,136	7,250.84	5	0.3%	0
Gualeguay	–	67,604	65,872	6,613.06	10	0.5%	17,821
Gualeguaychú	–	121,470	124,481	7,536.75	16	1%	53,552
Guaminí	–	13,304	10,250	4,822.64	3	0.1%	0
Hipólito Yrigoyen	–	11,488	10,408	1,647.38	7	0.1%	0
Islas del Ibicuy	–	12,881	13,948	4,931.37	3	0.1%	12,137
José C. Paz	–	177,838	194,646	50.34	3,533	1.4%	0
Junín	–	107,040	99,975	2,253.23	48	0.8%	0
La Costa	–	28,974	35,984	247.86	117	0.2%	10,641
La Paz	–	69,171	71,626	6,642.85	10	0.5%	0
La Plata	–	778,159	773,325	890.41	874	6.2%	164,567
Laprida	–	12,063	11,570	3,446.17	4	0.1%	0
Las Flores	–	27,812	26,539	3,340.32	8	0.2%	0
Leandro N. Alem	–	19,281	17,029	1,604.68	12	0.2%	0
Lezama	–	8,030	6,180	1,042.86	8	0.1%	1,599
Lincoln	–	51,140	46,196	5,784.31	9	0.4%	0
Lobería	–	20,413	17,065	4,722.94	4	0.2%	14
Lobos	–	42,862	41,576	1,725.85	25	0.3%	0
Luján	–	118,333	105,281	772.83	153	0.9%	37
Magdalena	–	23,796	23,140	1,850.14	13	0.2%	15,710
Maipú	–	11,711	11,274	2,602.82	4	0.1%	895
Malvinas Argentinas	–	231,120	226,099	63.22	3,656	1.8%	0
Mar Chiquita	–	25,241	32,977	3,090.77	8	0.2%	6,913
Marcos Paz	–	54,107	58,580	424.49	127	0.4%	0
Mercedes	–	68,480	71,491	1,050.28	65	0.5%	0
Merlo	–	520,968	515,109	174.11	2,992	4.1%	0
Monte	–	25,977	23,892	1,887.31	14	0.2%	0
Monte Hermoso	–	7,934	9,029	205.55	39	0.1%	2,085
Moreno	–	605,918	682,678	186.27	3,253	4.8%	775
Navarro	–	20,379	20,438	1,619.16	13	0.2%	0
Necochea	–	106,030	97,565	4,559.15	23	0.8%	20,099
Nogoya	–	42,198	41,877	4,381.74	10	0.3%	0
Olavarría	–	131,678	121,587	7,655.82	17	1%	0
Paraná	–	375,151	389,559	5,111.28	73	3%	8,401
Patagones	–	32,404	33,116	13,548.35	2	0.3%	2,431
Pehuajó	–	46,589	41,906	4,524.62	10	0.4%	0
Pellegrini	–	6,980	7,149	1,812.2	4	0.1%	0
Pergamino	–	124,461	112,584	3,005.92	41	1%	0
Pila	–	4,368	4,723	3,452.65	1	0%	173
Pilar	–	351,828	402,521	384.06	916	2.8%	28,995
Pinamar	–	26,584	35,156	66.3	401	0.2%	5,012
Presidente Perón	–	92,123	103,196	120.98	761	0.7%	0
Puán	–	17,930	15,421	6,348.15	3	0.1%	10
Punta Indio	–	11,155	11,927	1,608.73	7	0.1%	2,377
Quilmes	–	541,099	511,196	91.46	5,916	4.3%	284,509
Ramallo	–	34,894	37,275	1,047.99	33	0.3%	5,648
Rauch	–	17,713	16,976	4,307.85	4	0.1%	0
Rivadavia	–	20,707	20,446	3,948.34	5	0.2%	0
Rojas	–	27,675	25,902	2,061.68	13	0.2%	0
Roque Pérez	–	15,429	13,966	1,547.72	10	0.1%	0
Saavedra	–	25,036	21,875	3,533.61	7	0.2%	0
Saladillo	–	38,831	35,647	2,710.19	14	0.3%	0
Salliqueló	–	9,868	9,825	790.06	12	0.1%	0
Salto	–	37,972	39,955	1,613.46	24	0.3%	0
San Andrés de Giles	–	25,282	26,069	1,127.5	22	0.2%	0
San Antonio de Areco	–	24,938	25,907	864.97	29	0.2%	9
San Cayetano	–	9,862	9,525	3,004.3	3	0.1%	9
San Fernando	–	1,923	2,752	990.31	2	0%	92,630
San Nicolás	–	165,580	155,359	681.55	243	1.3%	29,843
San Pedro	–	70,050	68,734	1,356.59	52	0.6%	19,235
San Salvador	–	18,760	20,839	1,332.84	14	0.1%	0
San Vicente	–	71,416	106,427	655.25	109	0.6%	0
Suipacha	–	12,491	12,303	942.09	13	0.1%	0
Tala	–	27,580	30,952	2,645.21	10	0.2%	0
Tandil	–	151,459	150,670	4,844.33	31	1.2%	0
Tapalqué	–	11,049	10,828	4,168.83	3	0.1%	0
Tigre	–	552,615	537,279	394.1	1,402	4.4%	326,594
Tordillo	–	1,959	2,728	1,332.85	1	0%	1,944
Tornquist	–	13,935	12,633	4,175.08	3	0.1%	0
Trenque Lauquen	–	50,643	47,339	5,501.59	9	0.4%	0
Tres Arroyos	–	60,374	56,247	5,924.03	10	0.5%	393
Tres Lomas	–	11,326	8,743	1,255.25	9	0.1%	0
Uruguay	–	110,746	114,400	5,150.37	22	0.9%	22,026
Victoria	–	157,049	112,701	6,643.1	24	1.2%	99,319
Villa Gesell	–	7,202	9,219	165	44	0.1%	3,092
Villaguay	–	52,622	55,019	6,582.53	8	0.4%	0
Villarino	–	38,440	33,012	10,392.4	4	0.3%	1,036
Zárate	–	143,095	133,657	1,182.89	121	1.1%	46,658

05Exposure

Open exposure layers

Count of H3 resolution-3 cells whose centre falls in the unit and that carry each Natural Earth layer.

Urban areas: 3,252 H3 cells
Ports: 6 H3 cells
Airports: 4 H3 cells
Major roads: 9,025.6 H3 cells
Railways: 10,139.5 H3 cells
Rivers and lakes: 1,672.5 H3 cells

06Risk

Risk values

Values when released. Subnational risk values for Buenos Aires publish with the edition from The Global Risks Index. Until then, run a scenario on open data for Argentina.

Run a scenario Hazards Domain indices

07Neighbours

Neighbouring units

08Sources

Sources, credits and licences

ADM1 boundaries: geoBoundaries (William & Mary geoLab), gbOpen ARG ADM1, source: geoBoundaries, Wikimedia, licence: Creative Commons Attribution 2.5 Generic · source · represents 2006
ADM2 boundaries: geoBoundaries (William & Mary geoLab), gbOpen ARG ADM2, source: Instituto Geografico Nacional and UNHCR, OCHA ROLAC, licence: Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO) · source · represents 2020
Basemap: OpenFreeMap © OpenMapTiles (CC BY 4.0) · data © OpenStreetMap contributors (ODbL 1.0). Vector tiles requested by the reader’s browser, unmodified; the map falls back to plain land and sea when the host does not answer.
Terrain: Terrain Tiles (Mapzen, AWS Open Data), compiled from SRTM and other public elevation sources (NASA, USGS, ETOPO1, GMTED, EU-DEM under the Copernicus programme, Geoscience Australia, Kartverket, INEGI, LINZ, data.gov.uk). Display relief, not survey data.
People: GHSL 2025 population grid, European Commission Joint Research Centre (CC BY 4.0), shown at 0.05° and summed per unit; WorldPop 2025 (CC BY 4.0) as a second estimate. Units smaller than a grid cell take the density of the cell under them.
Countries: Natural Earth (public domain).
Elevation: GEBCO Compilation Group (2024) GEBCO 2024 Grid (public domain), reduced to 0.05°: the share of each cell’s land at or below 10 m, weighted by GHSL 2025 people for the low coastal zone.
Position: Boundaries are shown for location only and take no position on any boundary, name or status.

Status

The methodology, structure and definitions of The Global Risks Index are a preparatory working draft (2026), circulated for review and comment and not for implementation. No value appears until an edition is released from a governed evidence cut; values then carry intervals, classes, sources and their correction pathway. Simulators run the published methods on numbers you choose and never show a NXS-GRX value.

A country profile reads public evidence about a place. It is not a statement by or about the policy of any government, takes no position on the status of any territory, and does not imply a national programme or participation. Names follow UN M49.

What NXS-GRX is not

NXS-GRX is research and risk-analytics information. It is not a credit or ESG rating and uses no rating scale, not a benchmark for financial instruments, not official statistics, not an emergency warning or official classification, and not advice. It must not be used to evaluate natural persons. Risk classes are bands on a published scale, never rankings of countries or people.

Pulse signals and outlook probabilities are information for review by competent authorities, never public warnings; official warnings come only from mandated authorities.

Institutions and sources

The Nexus Consortium is stewarded by three independent not-for-profit institutions: The Global Centre for Risk and Innovation (GCRI), through GCRI US in Washington, DC and GCRI Canada in Ontario, with GCRI Canada as Lead Institution, Consortium Secretariat and lead contracting organisation; The Global Risks Forum (GRF); and The Global Risks Alliance (GRA). Technology, infrastructure and service providers work with the Consortium at arm’s length under written agreements, like every other external party in the public-private-planet model, and hold no role in its stewardship.

Every value carries the attribution of its sources, which keep their own licences. External names are cited for interoperability only. Nexus-authored text is intended for CC BY 4.0 on release.

Avis en français

La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.

Buenos Aires

Inside Buenos Aires

People, area and density

12,320,230

12,304,337

382,902 km²

AR-B

1,776,133

Buenos Aires in humanitarian data

17,709,598

140 units inside Buenos Aires

Open exposure layers

Risk values

Neighbouring units

Sources, credits and licences

Status

What NXS-GRX is not

Institutions and sources

Not for profit

Who funds us

Independence

Licence