{ "schema_version": "1.0.0", "api_version": "v1", "snapshot_id": "bctl-7eb7c1c7524bb525d233", "edition": { "name": "Civometra Index", "label": "2026 Q4", "status": "research", "methodology_version": "1.0.0", "official_city_results_released": false }, "as_of": "2026-10-27", "as_of_meaning": "Last complete source check recorded in the research snapshot; not a common observation period or a new editorial review. A separately validated source may have a later retrieved_at date; inspect each observation.", "dates": { "source_checked_at": "2026-10-27", "last_complete_source_check_at": "2026-10-27", "latest_observation_retrieved_at": "2026-10-27", "observations_changed_at": "2026-10-21", "editorial_review_earliest": "2026-10-11", "editorial_review_latest": "2026-10-27", "urban_context_retrieved_at": "2026-10-26", "index_evidence_evaluated_at": "2026-10-27", "air_quality_retrieved_at": "2026-10-26", "geography_candidates_evaluated_at": "2026-10-26", "protocols_prepared_at": "2026-10-26", "scoring_geographies_reviewed_at": "2026-10-26", "pm25_evidence_reviewed_at": "2026-10-26", "heat_evidence_reviewed_at": "2026-10-26", "rental_vacancy_evidence_reviewed_at": "2026-10-26", "housing_supply_evidence_reviewed_at": "2026-10-26", "life_expectancy_evidence_reviewed_at": "2026-10-26", "road_deaths_evidence_reviewed_at": "2026-10-27" }, "publisher": { "name": "BestCityToLive Intelligence", "initiative": "AINT.app", "url": "https://aint.app" }, "notice": "Civometra is a research edition, with no official quarterly city results. Current engine-accepted index inputs are explicitly separated from editorial guides, contextual observations and inherited legacy scores. An accepted indicator does not establish an eligible city score or ranking. National context never measures a city.", "rights": "No new licence is granted by this API. BestCityToLive editorial material retains its existing rights. Third-party observations and sources retain their own licences and attribution requirements; consult each primary publisher before reuse. Source catalog links do not imply permission to reproduce full source content.", "kind": "city-observatory", "id": "observatory:tokyo", "self": "https://bestcitytolive.com/api/v1/observatory/tokyo.json", "canonical_url": "https://bestcitytolive.com/observatory", "slug": "tokyo", "name": "Tokyo", "country": { "id": "country:JPN", "name": "Japan", "iso_2": "JP", "iso_3": "JPN", "continent": "Asia" }, "canonical_city_url": "https://bestcitytolive.com/city/tokyo", "editorial_reviewed_at": "2026-10-13", "editorial_source_count": 3, "context_coverage": { "agency_records": 0, "agency_measurements": 0, "derived_agency_changes": 0, "national_records": 4, "urban_source_fields": 2, "urban_derived_measures": 1, "air_context_records": 0, "air_monitor_records": 0, "modelled_air_context_records": 0, "notice": "Destination counts are not counts of independent physical urban areas. Population is projected; area is a source field; density is derived. 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"higher_better": true, "anchors": [ 10, 250 ], "max_age_days": 365, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "road-deaths", "pillar": "infrastructure", "label": "Traffic deaths per 100,000 residents", "unit": "per 100000", "higher_better": false, "anchors": [ 0, 20 ], "max_age_days": 730, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "daily-access", "pillar": "infrastructure", "label": "Residents within a 15-minute walk of everyday services", "unit": "%", "higher_better": true, "anchors": [ 0, 100 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "service-reliability", "pillar": "infrastructure", "label": "Reliable water and electricity access", "unit": "%", "higher_better": true, "anchors": [ 80, 100 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "homicide", "pillar": "trust", "label": "Intentional homicide rate", "unit": "per 100000", "higher_better": false, "anchors": [ 0, 20 ], "max_age_days": 730, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "unmet-healthcare", "pillar": "trust", "label": "Residents with unmet medical needs", "unit": "%", "higher_better": false, "anchors": [ 0, 20 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "avoidable-mortality", "pillar": "trust", "label": "Age-standardized avoidable mortality", "unit": "per 100000", "higher_better": false, "anchors": [ 50, 400 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "life-expectancy", "pillar": "trust", "label": "Urban-area life expectancy at birth", "unit": "years", "higher_better": true, "anchors": [ 65, 85 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "school-access", "pillar": "trust", "label": "Children with access to a school place", "unit": "%", "higher_better": true, "anchors": [ 70, 100 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "social-support", "pillar": "trust", "label": "Residents reporting someone to rely on", "unit": "%", "higher_better": true, "anchors": [ 40, 100 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "pm25", "pillar": "environment", "label": "Population-weighted annual PM2.5", "unit": "micrograms/m3", "higher_better": false, "anchors": [ 5, 50 ], "max_age_days": 730, "status": "accepted", "reason": "A reviewed observation passes the configured admission checks.", "observation": { "city_slug": "tokyo", "metric": "pm25", "value": 12.907995602808032, "unit": "micrograms/m3", "period_start": "2024-01-01", "period_end": "2024-12-31", "source_url": "https://www.satpm.org/v6-gl-03", "geography_type": "harmonized-urban-area", "geography_ref": "efua-2015-v1-0:tokyo", "protocol_ref": "civometra.pm25.measurement@1.0.0", "source_frame_ref": "pm25-2024-efua-5129", "source_frame_url": "/data/source-frames/pm25-2024-efua-5129.npz", "source_frame_sha256": "4f0d6280620ab857695c96370145c4f70bc5241ae13c8c577326097db9f60083", "source_record_ref": "pm25-2024-efua-5129.npz; population_2020 and pm_fine arrays; source estimated area 5129", "universe": "Residents modelled in the GHS-POP R2023A 2020 count grid inside the frozen 2015 JRC/OECD estimated functional urban area; annual ambient outdoor concentration represented at residential grid cells, with source coverage explicitly reported.", "denominator": 36697548.9260917, "publisher": "BestCityToLive Research Desk / AINT.app; derived from SatPM and European Commission/JRC", "source_label": "Population-weighted annual PM2.5: reviewed research input", "geography": "2015 estimated functional urban area: Tokyo (5129)", "definition_version": "1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "boundary_reference_year": 2015, "population_reference_year": 2020, "concentration_year": 2024, "source_model": { "name": "SatPM CNNPM25", "version": "V6.GL.03", "source_url": "https://satpmdata.s3.us-east-1.amazonaws.com/V6GL03/CNNPM25/Annual/GL/V6GL03.CNNPM25.GL.202401-202412.nc", "sha256": "9f1059f6a7d675a53f987e8b6ccc6981c3c29a867cc3a2324043a4eff2c19928" }, "calculation_method": "sum(known 2020 population_cell * valid nearest native 0.01-degree annual 2024 PM2.5 at that population-cell centre) / sum(covered known 2020 population_cell). The reviewed 2015 source boundaries align exactly with whole 1 km population cells; no fractional edge allocation is needed. Concentration is represented as constant within each population cell. Missing values are never zero; known zero is retained.", "coverage": { "population_grid_area_coverage": 0.9971598028569042, "pm_population_coverage": 1, "cell_count": 11971, "population_grid_valid_cells": 11937, "population_grid_missing_cells": 34, "population_grid_zero_cells": 934, "total_known_modelled_population": 36697548.9260917, "pm_covered_population": 36697548.9260917, "weighted_concentration_sum": 473691800.17182434, "population_in_zero_pm_cells": 0 }, "sensitivity": { "bilinear_estimate": 12.907096731928107, "bilinear_population_coverage": 1, "coarse_estimate": 12.889587420219799, "coarse_population_coverage": 1, "notice": "Method-sampling diagnostics with their own coverage; not statistical uncertainty or confidence intervals. Neither fills missing primary values." }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "No city-specific statistical interval supplied by this global product; sampling sensitivity is not a confidence interval." }, "scope_notice": "Annual 2024 modelled ambient PM2.5 weighted by 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Historical modelled geography; source country labels and area identities are retained.", "source_attribution": [ { "publisher": "Atmospheric Composition Analysis Group / Washington University in St. Louis / SatPM", "title": "Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., and Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. doi:10.1021/acsestair.3c00054. SatPM V6.GL.03, annual 2024; accessed 26 October 2026.", "url": "https://www.satpm.org/v6-gl-03", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre", "title": "GHS-POP R2023A V1-0, 2020 modelled residential-population counts", "url": "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre, in collaboration with OECD", "title": "GHS-FUA R2019A V1_0, estimated functional urban areas, 2015", "url": "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95", "licence": "CC BY 4.0" } ], "reviewed": true, "reviewed_at": "2026-10-26", "evidence_id": "pm25-2024-efua2015-tokyo", "source_ref": "source-e473b5267fc79730", "source_frame_absolute_url": "https://bestcitytolive.com/data/source-frames/pm25-2024-efua-5129.npz", "attribution_source_refs": [ "source-e473b5267fc79730", "source-f3189a9194a27e72", "source-ef5611a3b029db1b" ] }, "observation_identity": { "evidence_id": "pm25-2024-efua2015-tokyo", "observation_sha256": "3b7623d8554029122a478a3faab4a4ec134a4eef516290a7b550f134f440e120", "evidence_review_sha256": "efd55759f001ea80d978d0628a016f0d1e8e1d1c8a22d99ca80f4327192d63aa", "reviewed_at": "2026-10-26", "protocol_ref": "civometra.pm25.measurement@1.0.0", "protocol_sha256": "05e35da782e171155969f3129d6002a26efff73c77ca18abfe0430ac93eedfc5", "protocol_reviewed_at": "2026-10-26", "geography_ref": "efua-2015-v1-0:tokyo", "geography_sha256": "22c523a3aaf1eae919e058aba2f1d5b6d8e75a526c2861ecfd36474daab61331", "geography_reviewed_at": "2026-10-26", "source_frame_ref": "pm25-2024-efua-5129", "source_frame_registry_sha256": "78f81d90943e6387459465c3fc1af9e3fc240076dc936107248d73474242644e", "source_frame": { "id": "pm25-2024-efua-5129", "archive_url": "/data/source-frames/pm25-2024-efua-5129.npz", "sha256": "4f0d6280620ab857695c96370145c4f70bc5241ae13c8c577326097db9f60083", "source_urls": [ "https://www.satpm.org/v6-gl-03", "https://satpmdata.s3.us-east-1.amazonaws.com/V6GL03/CNNPM25/Annual/GL/V6GL03.CNNPM25.GL.202401-202412.nc", "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., and Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. doi:10.1021/acsestair.3c00054. SatPM V6.GL.03, annual 2024; accessed 26 October 2026. Population weighting and extraction by BestCityToLive / AINT.app; JRC population and boundary sources credited separately." }, "geography_source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." } ] }, "scoring_boundary": { "id": "efua-2015-v1-0:tokyo", "city_slug": "tokyo", "status": "reviewed", "scope": "functional-urban-area", "boundary_kind": "estimated-functional-urban-area", "authority": "European Commission Joint Research Centre, in collaboration with OECD", "source_geography_id": "5129", "source_name": "Tokyo", "boundary_vintage": "2015", "geography_edition": "GHS-FUA R2019A, 2015, V1_0", "version": "efua2015-cohort-v1.0.0", "source_frame_ref": "ghs-efua-2015-cohort-validity-adapter-v1", "original_source_frame_ref": "ghs-efua-2015-r2019a-v1-0-original", "crosswalk_method": "Inherited WGS84 destination point transformed to ESRI:54009 and uniquely intersected with original source polygon; original country labels retained. OECD IDs/overlap diagnostics are separate, non-equivalence crosswalks.", "crosswalk": { "city_slug": "tokyo", "estimated_area_id": 5129, "oecd_crosswalk": [ { "oecd_id": "JPN01F", "oecd_name": "Tokyo", "status": "spatial-overlap-diagnostic-only", "boundary_vintage": null, "estimated_area_km2": 11971, "oecd_projected_area_km2": 11329.412471922402, "intersection_km2": 9681.531908892248, "fraction_of_estimated_area_in_oecd": 0.8087488020125511, "fraction_of_oecd_area_in_estimated": 0.8545484536718843, "intersection_over_union": 0.7108904336215238, "oecd_reprojected_validity_adapter_applied": false, "notice": "Approximate area diagnostic after reprojection to common equal-area CRS; not boundary equivalence, current boundary vintage, population coverage or outcome conversion weights." } ], "oecd_status": "matched-different-edition", "reference_point": { "longitude": 139.6503, "latitude": 35.6762, "provenance": "Inherited destination registry: spatial lookup aid only; not evidence of a scored boundary." }, "destination_country_iso3": "JPN", "source_country_iso3": "JPN", "source_country_name": "Japan" }, "reviewed_at": "2026-10-26", "scoring_approved": true, "policy_decision_ref": "civometra-pm25-initial-research-admission-2026-10-26", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "shared_with": [], "source_record_ref": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0; eFUA_ID=5129; fid=5886", "exact_geometry": { "archive_file": "efua-2015-cohort-exact.gpkg", "archive_sha256": "12ae143651080d64458da3ce2603bb58ee4cd3d9357e624a383128f41f0bebc9", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "source_fid": 5886, "source_geometry_wkb_sha256": "48a22203c281dea4beaec496ad4f3aacf5dda2a5e0a9bd7ddcf5d5935c24165e", "source_geometry_blob_sha256": "bb6dc57064eb417d3e0597746809b4a88d7618f936f67a74058c1a2490fc3ecc", "crs": "ESRI:54009", "simplified": false, "reprojected": false, "clipped": false }, "extraction_geometry": { "archive_file": "efua-2015-cohort-validity-adapter.gpkg", "archive_sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "record_id": 5129, "geometry_wkb_sha256": "d0e2bd09cc85c912684eae1641fef5e1aad86bdd6bb26124d3662b772fd76ce7", "adapter": "make-valid-linework-v1", "source_1km_mask_sha256": "ec8276a792adc0e402d1f1ed047d1141ed2811a07e3670ac85ff92b6b17fa520" }, "geometry_review": { "completed": true, "reviewed_at": "2026-10-26", "original_valid": false, "validity_adapter_applied": true, "native_area_and_grid_footprint_unchanged": true }, "interpretation": "Fixed 2015 globally estimated functional area. Current-year annual exposure may be extracted within this historical analytical footprint using separately reviewed population and concentration grids. This is not a claim about observed/current commuting flows or present-day city-proper boundaries.", "approved_protocol_refs": [ "civometra.pm25.measurement@1.0.0" ], "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "review_scope": "Reviewed research geography for this PM protocol only; not an observed current commuting zone or blanket approval for other indicators.", "geography_ref": "efua-2015-v1-0:tokyo", "geography_type_required": "harmonized-urban-area", "notice": "Scoped protocol permissions can repeat one unchanged physical boundary. Counts distinguish reviewed entries from unique destinations and analytical areas. Frozen 2015 estimated areas are not current observed commuting zones or 2025 urban centres.", "registry_url": "https://bestcitytolive.com/api/v1/scoring-geographies.json", "source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "copyright_notice_sha256": "f20723519a580fb35b3499870f0b1baea54f483195105416e547f0014f1610d2", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "original_source_frame_ref": "ghs-efua-2015-r2019a-v1-0-original", "original_source_archive_sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "adaptation": "Exact selected original features, with documented make_valid linework decomposition only where invalid. No coordinate, boundary-linework, area or 1 km cell-footprint change; source originals separately retained.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "source_ref": "source-0a2031537592e1ba" }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "copyright_notice_sha256": "f20723519a580fb35b3499870f0b1baea54f483195105416e547f0014f1610d2", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "source_ref": "source-0a2031537592e1ba" } ] } }, { "id": "green-access", "pillar": "environment", "label": "Residents within 300m of public green space", "unit": "%", "higher_better": true, "anchors": [ 0, 100 ], "max_age_days": 1095, "status": "missing", "reason": "No index observation has been submitted for this indicator." }, { "id": "heat-exposure", "pillar": "environment", "label": "Annual dangerous heat exposure", "unit": "person-days/person", "higher_better": false, "anchors": [ 0, 90 ], "max_age_days": 730, "status": "accepted", "reason": "A reviewed observation passes the configured admission checks.", "observation": { "city_slug": "tokyo", "metric": "heat-exposure", "value": 29.44000849449062, "unit": "person-days/person", "period_start": "2025-01-01", "period_end": "2025-12-31", "source_url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "geography_type": "harmonized-urban-area", "geography_ref": "efua-2015-heat-v1-0:tokyo", "protocol_ref": "civometra.heat-exposure.measurement@1.0.0", "source_frame_ref": "heat-2025-efua-5129", "source_frame_url": "/data/source-frames/heat-2025-efua-5129.npz", "source_frame_sha256": "d64332f7607272912a095070a090e36047f1c95ce75a0af74d82d7d8db41d1d3", "source_record_ref": "heat-2025-efua-5129.npz; heat_days_2025/monthly_heat_days_2025 and exact population operands; estimated source area 5129", "universe": "Residents modelled in the GHS-POP R2023A 2020 native 1 km count grid inside the frozen 2015 JRC/OECD estimated functional urban area; historical annual outdoor UTCI maximum heat days represented at residential grid cells. This is not an individual clinical-risk measure.", "denominator": 36697548.9260917, "publisher": "BestCityToLive Research Desk / AINT.app; derived from C3S/ECMWF and European Commission/JRC", "source_label": "Population-weighted annual extreme-heat exposure: reviewed research input", "geography": "2015 estimated functional urban area: Tokyo (5129)", "definition_version": "1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "boundary_reference_year": 2015, "population_reference_year": 2020, "source_model": { "name": "ERA5-HEAT via Thermal Trace (archived chart-data snapshot)", "version": null, "source_url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "sha256": "42401d35af69b247923a891cde93a7f9893bc420dff5034fea864dda8a53c8d0" }, "calculation_method": "For each complete UTC day in 2025, count maximum outdoor UTCI >=38 degrees Celsius at the nearest actual native 0.25-degree Thermal Trace grid point for each population-cell centre. Annual exposure = sum(known 2020 population_cell * exposed UTC days) / sum(known population with complete 365-day weather); monthly values use the same denominator. Exact whole 1 km 2015 source-cell masks are retained. Weather is constant within a population cell; no interpolation, neighbour gap-fill, invented zero population or city-specific thresholds. Primary exposure counts exported daily maximum Celsius UTCI >=38. Publisher annual hot counts were empirically compared with strict > recounts at 26/32/38/46 on those same exact exported Celsius operands; inclusive-minus-reference equals the exact equality count. No epsilon, rounded operands or verified backend cause is asserted. The difference is threshold-definition sensitivity, not a confidence interval, physical accuracy estimate, separate scored indicator or replacement primary value.", "coverage": { "cell_count": 11971, "population_grid_valid_cells": 11937, "missing_cells": 34, "zero_cells": 934, "population_grid_area_coverage": 0.9971598028569042, "total_known_modelled_population": 36697548.9260917, "weather_covered_population": 36697548.9260917, "weather_population_coverage": 1, "weighted_exposed_person_days": 1080376152.1111248, "native_weather_points": 33, "expected_days": 365 }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "The source supplies no city-specific statistical confidence interval. Regional reanalysis does not resolve shade, indoor conditions, neighbourhood microclimate or individual physiological exposure." }, "scope_notice": "Annual 2025 modelled outdoor heat exposure using 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Native weather resolution is 0.25 degrees. This historical modelled analytical footprint is not a current municipality or observed commuting boundary.", "source_attribution": [ { "publisher": "Copernicus Climate Change Service (C3S), implemented by ECMWF", "title": "ERA5-HEAT via Thermal Trace, archived 2025 daily maximum/minimum outdoor UTCI chart facts", "url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "licence": "CC BY 4.0", "attribution": { "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "basis": "Pinned official frontend chart/CSV export metadata; the JSON response itself omits licence and units.", "attribution": "Contains modified Copernicus Climate Change Service (C3S) information 2025, implemented by ECMWF. Source: ERA5-HEAT via Thermal Trace and the Climate Data Store, DOI 10.24381/cds.553b7518; chart facts licensed CC BY 4.0.", "modifications": "Modified by BestCityToLive / AINT.app: daily maxima counted >=38 degrees Celsius on exact exported daily operands, native 0.25-degree sampling with the disclosed higher-coordinate tie rule, GHS-POP 2020 population weighting on reviewed estimated-FUA 2015 masks, and annual/monthly calculations with strict-threshold definition sensitivity. These derivatives are not source-produced city estimates.", "responsibility_notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data in this publication.", "no_endorsement": "The original publishers have not endorsed BestCityToLive, AINT.app, Civometra, the historical estimated-area compatibility review, or these derived city-area values." } }, { "publisher": "European Commission Joint Research Centre", "title": "GHS-POP R2023A V1-0, 2020 modelled residential population counts", "url": "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre, in collaboration with OECD", "title": "GHS-FUA R2019A V1_0, estimated functional urban areas, 2015", "url": "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95", "licence": "CC BY 4.0" } ], "weather_reference_year": 2025, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "value": 0.25519059874306943, "weighted_exposed_person_days": 9364869.482852425 }, { "month": "2025-07", "calendar_days": 31, "value": 8.804585907445192, "weighted_exposed_person_days": 323106722.11244744 }, { "month": "2025-08", "calendar_days": 31, "value": 15.854601605423266, "weighted_exposed_person_days": 581825018.1187123 }, { "month": "2025-09", "calendar_days": 30, "value": 4.52563038287909, "weighted_exposed_person_days": 166079542.39711252 }, { "month": "2025-10", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 } ], "definition_sensitivity": { "label": "threshold-definition sensitivity", "threshold_c": 38, "primary_comparison": ">=", "reference_comparison": ">", "denominator": 36697548.9260917, "strict_value": 29.44000849449062, "strict_weighted_exposed_person_days": 1080376152.1111248, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "strict_value": 0.25519059874306943, "strict_weighted_exposed_person_days": 9364869.482852425, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-07", "calendar_days": 31, "strict_value": 8.804585907445192, "strict_weighted_exposed_person_days": 323106722.11244744, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-08", "calendar_days": 31, "strict_value": 15.854601605423266, "strict_weighted_exposed_person_days": 581825018.1187123, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-09", "calendar_days": 30, "strict_value": 4.52563038287909, "strict_weighted_exposed_person_days": 166079542.39711252, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-10", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 } ], "notice": "Exact published-Celsius comparison sensitivity; not a confidence interval, physical accuracy estimate, new scored indicator or replacement primary value. The provider backend comparison/conversion order is not established." }, "reviewed": true, "reviewed_at": "2026-10-26", "evidence_id": "heat-2025-efua2015-tokyo", "source_ref": "source-82ac6f7a3f0687eb", "source_frame_absolute_url": "https://bestcitytolive.com/data/source-frames/heat-2025-efua-5129.npz", "attribution_source_refs": [ "source-82ac6f7a3f0687eb", "source-f3189a9194a27e72", "source-ef5611a3b029db1b" ] }, "observation_identity": { "evidence_id": "heat-2025-efua2015-tokyo", "observation_sha256": "6611bef8ec41b24329c0bed030ea05a5d9a093a9c91e21ef972739dd76c9a54f", "evidence_review_sha256": "f4bcf9c1a793f52de6859dd0ed8809177a0916a5de9a59f97cc0bc98d6cc8002", "reviewed_at": "2026-10-26", "protocol_ref": "civometra.heat-exposure.measurement@1.0.0", "protocol_sha256": "67b31ac71f805f7807a86472a0b7a27857d242ac001d41d89a49a6a421b68659", "protocol_reviewed_at": "2026-10-26", "geography_ref": "efua-2015-heat-v1-0:tokyo", "geography_sha256": "3b108ca9810246a055e8bc537f8d8f115c75b5d48e672faa1a413d655e30844d", "geography_reviewed_at": "2026-10-26", "source_frame_ref": "heat-2025-efua-5129", "source_frame_registry_sha256": "60a04b4614d3a0223e6b680de1b69596d92e435c839f2d6d827d80a91ffcbaa8", "source_frame": { "id": "heat-2025-efua-5129", "archive_url": "/data/source-frames/heat-2025-efua-5129.npz", "sha256": "d64332f7607272912a095070a090e36047f1c95ce75a0af74d82d7d8db41d1d3", "source_urls": [ "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "https://thermaltrace.climate.copernicus.eu/", "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "Contains modified Copernicus Climate Change Service (C3S) information 2025, implemented by ECMWF. Source: ERA5-HEAT via Thermal Trace and the Climate Data Store, DOI 10.24381/cds.553b7518; chart facts licensed CC BY 4.0. Modified by BestCityToLive / AINT.app: daily maxima counted >=38 degrees Celsius on exact exported daily operands, native 0.25-degree sampling with the disclosed higher-coordinate tie rule, GHS-POP 2020 population weighting on reviewed estimated-FUA 2015 masks, and annual/monthly calculations with strict-threshold definition sensitivity. These derivatives are not source-produced city estimates. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data in this publication." }, "geography_source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." } ] }, "scoring_boundary": { "id": "efua-2015-heat-v1-0:tokyo", "city_slug": "tokyo", "status": "reviewed", "scope": "functional-urban-area", "boundary_kind": "estimated-functional-urban-area", "authority": "European Commission Joint Research Centre, in collaboration with OECD", "source_geography_id": "5129", "source_name": "Tokyo", "boundary_vintage": "2015", "geography_edition": "GHS-FUA R2019A, 2015, V1_0", "version": "efua2015-cohort-v1.0.0", "source_frame_ref": "ghs-efua-2015-cohort-validity-adapter-v1", "original_source_frame_ref": "ghs-efua-2015-r2019a-v1-0-original", "crosswalk_method": "Inherited WGS84 destination point transformed to ESRI:54009 and uniquely intersected with original source polygon; original country labels retained. OECD IDs/overlap diagnostics are separate, non-equivalence crosswalks.", "crosswalk": { "city_slug": "tokyo", "estimated_area_id": 5129, "oecd_crosswalk": [ { "oecd_id": "JPN01F", "oecd_name": "Tokyo", "status": "spatial-overlap-diagnostic-only", "boundary_vintage": null, "estimated_area_km2": 11971, "oecd_projected_area_km2": 11329.412471922402, "intersection_km2": 9681.531908892248, "fraction_of_estimated_area_in_oecd": 0.8087488020125511, "fraction_of_oecd_area_in_estimated": 0.8545484536718843, "intersection_over_union": 0.7108904336215238, "oecd_reprojected_validity_adapter_applied": false, "notice": "Approximate area diagnostic after reprojection to common equal-area CRS; not boundary equivalence, current boundary vintage, population coverage or outcome conversion weights." } ], "oecd_status": "matched-different-edition", "reference_point": { "longitude": 139.6503, "latitude": 35.6762, "provenance": "Inherited destination registry: spatial lookup aid only; not evidence of a scored boundary." }, "destination_country_iso3": "JPN", "source_country_iso3": "JPN", "source_country_name": "Japan" }, "reviewed_at": "2026-10-26", "scoring_approved": true, "policy_decision_ref": "civometra.heat2025.complete-source-and-scoped-review@1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "shared_with": [], "source_record_ref": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0; eFUA_ID=5129; fid=5886", "exact_geometry": { "archive_file": "efua-2015-cohort-exact.gpkg", "archive_sha256": "12ae143651080d64458da3ce2603bb58ee4cd3d9357e624a383128f41f0bebc9", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "source_fid": 5886, "source_geometry_wkb_sha256": "48a22203c281dea4beaec496ad4f3aacf5dda2a5e0a9bd7ddcf5d5935c24165e", "source_geometry_blob_sha256": "bb6dc57064eb417d3e0597746809b4a88d7618f936f67a74058c1a2490fc3ecc", "crs": "ESRI:54009", "simplified": false, "reprojected": false, "clipped": false }, "extraction_geometry": { "archive_file": "efua-2015-cohort-validity-adapter.gpkg", "archive_sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "record_id": 5129, "geometry_wkb_sha256": "d0e2bd09cc85c912684eae1641fef5e1aad86bdd6bb26124d3662b772fd76ce7", "adapter": "make-valid-linework-v1", "source_1km_mask_sha256": "ec8276a792adc0e402d1f1ed047d1141ed2811a07e3670ac85ff92b6b17fa520" }, "geometry_review": { "completed": true, "reviewed_at": "2026-10-26", "original_valid": false, "validity_adapter_applied": true, "native_area_and_grid_footprint_unchanged": true }, "interpretation": "Fixed 2015 globally estimated functional area. Current-year annual exposure may be extracted within this historical analytical footprint using separately reviewed population and concentration grids. This is not a claim about observed/current commuting flows or present-day city-proper boundaries.", "approved_protocol_refs": [ "civometra.heat-exposure.measurement@1.0.0" ], "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "review_scope": "Same exact 2015 source geometry, separately reviewed for the frozen heat protocol only. Historical estimated area; not an observed current commuting zone or blanket approval.", "derived_from_geography_ref": "efua-2015-v1-0:tokyo", "geography_ref": "efua-2015-heat-v1-0:tokyo", "geography_type_required": "harmonized-urban-area", "notice": "Scoped protocol permissions can repeat one unchanged physical boundary. Counts distinguish reviewed entries from unique destinations and analytical areas. Frozen 2015 estimated areas are not current observed commuting zones or 2025 urban centres.", "registry_url": "https://bestcitytolive.com/api/v1/scoring-geographies.json", "source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "copyright_notice_sha256": "f20723519a580fb35b3499870f0b1baea54f483195105416e547f0014f1610d2", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "original_source_frame_ref": "ghs-efua-2015-r2019a-v1-0-original", "original_source_archive_sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "adaptation": "Exact selected original features, with documented make_valid linework decomposition only where invalid. No coordinate, boundary-linework, area or 1 km cell-footprint change; source originals separately retained.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "source_ref": "source-0a2031537592e1ba" }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "copyright_notice_sha256": "f20723519a580fb35b3499870f0b1baea54f483195105416e547f0014f1610d2", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. 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GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "source_ref": "source-0a2031537592e1ba" } ] } ], "notice": "Per-indicator admission checks are research metadata, not an official results release. Contextual observations remain separate. Comparable definitions, documented boundaries and editorial quarterly review are required before publication." }, "index_history": { "slug": "tokyo", "name": "Tokyo", "evaluated_at": "2026-10-27", "status": "research", "official_results_released": false, "metrics": [ { "id": "rent-burden", "label": "Median rent / disposable household income", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "residual-income", "label": "Income remaining after housing and essentials", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "essentials-burden", "label": "Essentials / disposable household income", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, 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null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "commute", "label": "Median one-way commute", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "broadband", "label": "Median fixed download speed", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "road-deaths", "label": "Traffic deaths per 100,000 residents", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "daily-access", "label": "Residents within a 15-minute walk of everyday services", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "service-reliability", "label": "Reliable water and electricity access", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "homicide", "label": "Intentional homicide rate", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "unmet-healthcare", "label": "Residents with unmet medical needs", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "avoidable-mortality", "label": 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"geography_reviewed_at": "2026-10-26", "source_frame_ref": "pm25-2024-efua-5129", "source_frame_registry_sha256": "78f81d90943e6387459465c3fc1af9e3fc240076dc936107248d73474242644e", "source_frame": { "id": "pm25-2024-efua-5129", "archive_url": "/data/source-frames/pm25-2024-efua-5129.npz", "sha256": "4f0d6280620ab857695c96370145c4f70bc5241ae13c8c577326097db9f60083", "source_urls": [ "https://www.satpm.org/v6-gl-03", "https://satpmdata.s3.us-east-1.amazonaws.com/V6GL03/CNNPM25/Annual/GL/V6GL03.CNNPM25.GL.202401-202412.nc", "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., and Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. doi:10.1021/acsestair.3c00054. SatPM V6.GL.03, annual 2024; accessed 26 October 2026. Population weighting and extraction by BestCityToLive / AINT.app; JRC population and boundary sources credited separately." }, "geography_source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." } ] }, "observation": { "city_slug": "tokyo", "metric": "pm25", "value": 12.907995602808032, "unit": "micrograms/m3", "period_start": "2024-01-01", "period_end": "2024-12-31", "source_url": "https://www.satpm.org/v6-gl-03", "geography_type": "harmonized-urban-area", "geography_ref": "efua-2015-v1-0:tokyo", "protocol_ref": "civometra.pm25.measurement@1.0.0", "source_frame_ref": "pm25-2024-efua-5129", "source_frame_url": "/data/source-frames/pm25-2024-efua-5129.npz", "source_frame_sha256": "4f0d6280620ab857695c96370145c4f70bc5241ae13c8c577326097db9f60083", "source_record_ref": "pm25-2024-efua-5129.npz; population_2020 and pm_fine arrays; source estimated area 5129", "universe": "Residents modelled in the GHS-POP R2023A 2020 count grid inside the frozen 2015 JRC/OECD estimated functional urban area; annual ambient outdoor concentration represented at residential grid cells, with source coverage explicitly reported.", "denominator": 36697548.9260917, "publisher": "BestCityToLive Research Desk / AINT.app; derived from SatPM and European Commission/JRC", "source_label": "Population-weighted annual PM2.5: reviewed research input", "geography": "2015 estimated functional urban area: Tokyo (5129)", "definition_version": "1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "boundary_reference_year": 2015, "population_reference_year": 2020, "concentration_year": 2024, "source_model": { "name": "SatPM CNNPM25", "version": "V6.GL.03", "source_url": "https://satpmdata.s3.us-east-1.amazonaws.com/V6GL03/CNNPM25/Annual/GL/V6GL03.CNNPM25.GL.202401-202412.nc", "sha256": "9f1059f6a7d675a53f987e8b6ccc6981c3c29a867cc3a2324043a4eff2c19928" }, "calculation_method": "sum(known 2020 population_cell * valid nearest native 0.01-degree annual 2024 PM2.5 at that population-cell centre) / sum(covered known 2020 population_cell). The reviewed 2015 source boundaries align exactly with whole 1 km population cells; no fractional edge allocation is needed. Concentration is represented as constant within each population cell. Missing values are never zero; known zero is retained.", "coverage": { "population_grid_area_coverage": 0.9971598028569042, "pm_population_coverage": 1, "cell_count": 11971, "population_grid_valid_cells": 11937, "population_grid_missing_cells": 34, "population_grid_zero_cells": 934, "total_known_modelled_population": 36697548.9260917, "pm_covered_population": 36697548.9260917, "weighted_concentration_sum": 473691800.17182434, "population_in_zero_pm_cells": 0 }, "sensitivity": { "bilinear_estimate": 12.907096731928107, "bilinear_population_coverage": 1, "coarse_estimate": 12.889587420219799, "coarse_population_coverage": 1, "notice": "Method-sampling diagnostics with their own coverage; not statistical uncertainty or confidence intervals. Neither fills missing primary values." }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "No city-specific statistical interval supplied by this global product; sampling sensitivity is not a confidence interval." }, "scope_notice": "Annual 2024 modelled ambient PM2.5 weighted by 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Historical modelled geography; source country labels and area identities are retained.", "source_attribution": [ { "publisher": "Atmospheric Composition Analysis Group / Washington University in St. Louis / SatPM", "title": "Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., and Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. doi:10.1021/acsestair.3c00054. 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Source: ERA5-HEAT via Thermal Trace and the Climate Data Store, DOI 10.24381/cds.553b7518; chart facts licensed CC BY 4.0. Modified by BestCityToLive / AINT.app: daily maxima counted >=38 degrees Celsius on exact exported daily operands, native 0.25-degree sampling with the disclosed higher-coordinate tie rule, GHS-POP 2020 population weighting on reviewed estimated-FUA 2015 masks, and annual/monthly calculations with strict-threshold definition sensitivity. These derivatives are not source-produced city estimates. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data in this publication." }, "geography_source_frames": [ { "id": "ghs-efua-2015-cohort-validity-adapter-v1", "archive_url": "/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement." } ] }, "observation": { "city_slug": "tokyo", "metric": "heat-exposure", "value": 29.44000849449062, "unit": "person-days/person", "period_start": "2025-01-01", "period_end": "2025-12-31", "source_url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "geography_type": "harmonized-urban-area", "geography_ref": "efua-2015-heat-v1-0:tokyo", "protocol_ref": "civometra.heat-exposure.measurement@1.0.0", "source_frame_ref": "heat-2025-efua-5129", "source_frame_url": "/data/source-frames/heat-2025-efua-5129.npz", "source_frame_sha256": "d64332f7607272912a095070a090e36047f1c95ce75a0af74d82d7d8db41d1d3", "source_record_ref": "heat-2025-efua-5129.npz; heat_days_2025/monthly_heat_days_2025 and exact population operands; estimated source area 5129", "universe": "Residents modelled in the GHS-POP R2023A 2020 native 1 km count grid inside the frozen 2015 JRC/OECD estimated functional urban area; historical annual outdoor UTCI maximum heat days represented at residential grid cells. This is not an individual clinical-risk measure.", "denominator": 36697548.9260917, "publisher": "BestCityToLive Research Desk / AINT.app; derived from C3S/ECMWF and European Commission/JRC", "source_label": "Population-weighted annual extreme-heat exposure: reviewed research input", "geography": "2015 estimated functional urban area: Tokyo (5129)", "definition_version": "1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "boundary_label": "2015 estimated functional urban area: Tokyo (5129)", "boundary_reference_year": 2015, "population_reference_year": 2020, "source_model": { "name": "ERA5-HEAT via Thermal Trace (archived chart-data snapshot)", "version": null, "source_url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "sha256": "42401d35af69b247923a891cde93a7f9893bc420dff5034fea864dda8a53c8d0" }, "calculation_method": "For each complete UTC day in 2025, count maximum outdoor UTCI >=38 degrees Celsius at the nearest actual native 0.25-degree Thermal Trace grid point for each population-cell centre. Annual exposure = sum(known 2020 population_cell * exposed UTC days) / sum(known population with complete 365-day weather); monthly values use the same denominator. Exact whole 1 km 2015 source-cell masks are retained. Weather is constant within a population cell; no interpolation, neighbour gap-fill, invented zero population or city-specific thresholds. Primary exposure counts exported daily maximum Celsius UTCI >=38. Publisher annual hot counts were empirically compared with strict > recounts at 26/32/38/46 on those same exact exported Celsius operands; inclusive-minus-reference equals the exact equality count. No epsilon, rounded operands or verified backend cause is asserted. The difference is threshold-definition sensitivity, not a confidence interval, physical accuracy estimate, separate scored indicator or replacement primary value.", "coverage": { "cell_count": 11971, "population_grid_valid_cells": 11937, "missing_cells": 34, "zero_cells": 934, "population_grid_area_coverage": 0.9971598028569042, "total_known_modelled_population": 36697548.9260917, "weather_covered_population": 36697548.9260917, "weather_population_coverage": 1, "weighted_exposed_person_days": 1080376152.1111248, "native_weather_points": 33, "expected_days": 365 }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "The source supplies no city-specific statistical confidence interval. Regional reanalysis does not resolve shade, indoor conditions, neighbourhood microclimate or individual physiological exposure." }, "scope_notice": "Annual 2025 modelled outdoor heat exposure using 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Native weather resolution is 0.25 degrees. This historical modelled analytical footprint is not a current municipality or observed commuting boundary.", "source_attribution": [ { "publisher": "Copernicus Climate Change Service (C3S), implemented by ECMWF", "title": "ERA5-HEAT via Thermal Trace, archived 2025 daily maximum/minimum outdoor UTCI chart facts", "url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "licence": "CC BY 4.0", "attribution": { "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "basis": "Pinned official frontend chart/CSV export metadata; the JSON response itself omits licence and units.", "attribution": "Contains modified Copernicus Climate Change Service (C3S) information 2025, implemented by ECMWF. Source: ERA5-HEAT via Thermal Trace and the Climate Data Store, DOI 10.24381/cds.553b7518; chart facts licensed CC BY 4.0.", "modifications": "Modified by BestCityToLive / AINT.app: daily maxima counted >=38 degrees Celsius on exact exported daily operands, native 0.25-degree sampling with the disclosed higher-coordinate tie rule, GHS-POP 2020 population weighting on reviewed estimated-FUA 2015 masks, and annual/monthly calculations with strict-threshold definition sensitivity. These derivatives are not source-produced city estimates.", "responsibility_notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data in this publication.", "no_endorsement": "The original publishers have not endorsed BestCityToLive, AINT.app, Civometra, the historical estimated-area compatibility review, or these derived city-area values." } }, { "publisher": "European Commission Joint Research Centre", "title": "GHS-POP R2023A V1-0, 2020 modelled residential population counts", "url": "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre, in collaboration with OECD", "title": "GHS-FUA R2019A V1_0, estimated functional urban areas, 2015", "url": "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95", "licence": "CC BY 4.0" } ], "weather_reference_year": 2025, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "value": 0.25519059874306943, "weighted_exposed_person_days": 9364869.482852425 }, { "month": "2025-07", "calendar_days": 31, "value": 8.804585907445192, "weighted_exposed_person_days": 323106722.11244744 }, { "month": "2025-08", "calendar_days": 31, "value": 15.854601605423266, "weighted_exposed_person_days": 581825018.1187123 }, { "month": "2025-09", "calendar_days": 30, "value": 4.52563038287909, "weighted_exposed_person_days": 166079542.39711252 }, { "month": "2025-10", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 } ], "definition_sensitivity": { "label": "threshold-definition sensitivity", "threshold_c": 38, "primary_comparison": ">=", "reference_comparison": ">", "denominator": 36697548.9260917, "strict_value": 29.44000849449062, "strict_weighted_exposed_person_days": 1080376152.1111248, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "strict_value": 0.25519059874306943, "strict_weighted_exposed_person_days": 9364869.482852425, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-07", "calendar_days": 31, "strict_value": 8.804585907445192, "strict_weighted_exposed_person_days": 323106722.11244744, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-08", "calendar_days": 31, "strict_value": 15.854601605423266, "strict_weighted_exposed_person_days": 581825018.1187123, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-09", "calendar_days": 30, "strict_value": 4.52563038287909, "strict_weighted_exposed_person_days": 166079542.39711252, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-10", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 } ], "notice": "Exact published-Celsius comparison sensitivity; not a confidence interval, physical accuracy estimate, new scored indicator or replacement primary value. The provider backend comparison/conversion order is not established." }, "reviewed": true, "reviewed_at": "2026-10-26", "evidence_id": "heat-2025-efua2015-tokyo", "source_ref": "source-82ac6f7a3f0687eb", "source_frame_absolute_url": "https://bestcitytolive.com/data/source-frames/heat-2025-efua-5129.npz", "attribution_source_refs": [ "source-82ac6f7a3f0687eb", "source-f3189a9194a27e72", "source-ef5611a3b029db1b" ] }, "source_age": { "reference_date": "2025-12-31", "reference_kind": "period-end", "maximum_age_days": 730, "age_days": 300, "last_age_eligible_date": "2027-12-31", "first_age_rejected_date": "2028-01-01", "notice": "These UTC dates describe the unchanged age gate only; source, identity, review and selection checks still apply." }, "duplicate_submissions": 1, "state": "selected", "selected": true, "age_eligible": true, "reasons": [] } ], "selection_decisions": [] }, { "id": "flood-exposure", "label": "Residents in high-risk flood areas", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "thermal-comfort", "label": "Annual hours with moderate outdoor thermal conditions", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "emissions", "label": "Territorial greenhouse gas emissions per capita", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "employment", "label": "Employment rate, working age", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "job-growth", "label": "Three-year annualized employment growth", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "skills", "label": "Adults with postsecondary qualifications", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "business-formation", "label": "New employer firms per 1,000 working-age residents", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "culture-access", "label": "Residents near a library or cultural venue", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] }, { "id": "housing-supply", "label": "Housing completions per 1,000 residents", "status": "missing", "selected_history_id": null, "selected_evidence_id": null, "submitted_rows": 0, "withheld_rows": 0, "withheld_states": {}, "records": [], "selection_decisions": [] } ], "notice": "Only exact completed approved evidence identities expose observations. Expiry and current selection do not rewrite historical source values, source dates or approvals. Rejected/unreviewed/future raw rows are withheld; their fixed diagnostic counts are not observations. Age dates describe the unchanged UTC age gate only. No official score or quarterly result is released." }, "air_monitor_context": { "status": "context-only", "record_count": 0, "index_eligible": false, "ranking_eligible": false, "evidence_types": [], "source_retrievals": [], "coverage": [], "records": [], "notice": "EPA monitoring-site summaries only; zero rows means no matching monitor context in this snapshot. Separate contextual evidence classes: EPA annual monitor/site summaries and EEA two-year modelled city/greater-city exposure. Monitor rows are not city averages, independent urban areas or population-weighted FUA exposure. EEA values are 2024–2025 modelled city-boundary averages, not annual monitor statistics. Do not pool, average, rank or convert these classes into index inputs. Missing destinations are not assigned a substitute value." }, "air_quality_context": { "status": "context-only", "record_count": 0, "index_eligible": false, "ranking_eligible": false, "evidence_types": [], "source_retrievals": [], "coverage": [], "records": [], "notice": "Separate contextual evidence classes: EPA annual monitor/site summaries and EEA two-year modelled city/greater-city exposure. Monitor rows are not city averages, independent urban areas or population-weighted FUA exposure. EEA values are 2024–2025 modelled city-boundary averages, not annual monitor statistics. Do not pool, average, rank or convert these classes into index inputs. Missing destinations are not assigned a substitute value." }, "geography_candidates": { "city_slug": "tokyo", "city_name": "Tokyo", "destination_country_iso3": "JPN", "status": "matched", "scoring_approved": false, "reference_point": { "longitude": 139.6503, "latitude": 35.6762, "provenance": "Inherited destination registry: spatial lookup aid only; not evidence of a scored boundary." }, "oecd_fua_candidates": [ { "id": "JPN01F", "country_iso3": "JPN", "source_name": "Tokyo", "source_label": "OECD functional urban area", "identity_source_frame": "oecd-codelist", "boundary_vintage": null, "boundary_vintage_status": "unknown: the retrieved package does not establish the national boundary/commuting reference year", "boundary_match": "point_intersects", "boundary_source_frame": "oecd-boundaries", "boundary_archive_generation": "2025-03-06T14:50:34.695Z", "member_count": 228, "member_ids": [ "JPN08204", "JPN08208", "JPN08217", "JPN08219", "JPN08224", "JPN08235", "JPN08542", "JPN08564", "JPN09364", "JPN11101", "JPN11102", "JPN11103", "JPN11104", "JPN11105", "JPN11106", "JPN11107", "JPN11108", "JPN11109", "JPN11110", "JPN11201", "JPN11202", "JPN11203", "JPN11206", "JPN11208", "JPN11209", "JPN11210", "JPN11212", "JPN11214", "JPN11215", "JPN11216", "JPN11217", "JPN11218", "JPN11219", "JPN11221", "JPN11222", "JPN11223", "JPN11224", "JPN11225", "JPN11227", "JPN11228", "JPN11229", "JPN11230", "JPN11231", "JPN11232", "JPN11233", "JPN11234", "JPN11235", "JPN11237", "JPN11238", "JPN11239", "JPN11240", "JPN11241", "JPN11242", "JPN11243", "JPN11245", "JPN11246", "JPN11301", "JPN11324", "JPN11326", "JPN11327", "JPN11341", "JPN11342", "JPN11343", "JPN11346", "JPN11347", "JPN11348", "JPN11349", "JPN11369", "JPN11408", "JPN11442", "JPN11464", "JPN11465", "JPN12101", "JPN12102", "JPN12103", "JPN12104", "JPN12105", "JPN12106", "JPN12203", "JPN12204", "JPN12206", "JPN12207", "JPN12208", "JPN12210", "JPN12211", "JPN12212", "JPN12213", "JPN12216", "JPN12217", "JPN12219", "JPN12220", "JPN12221", "JPN12222", "JPN12224", "JPN12225", "JPN12226", "JPN12227", "JPN12228", "JPN12229", "JPN12230", "JPN12231", "JPN12232", "JPN12233", "JPN12237", "JPN12239", "JPN12322", "JPN12329", "JPN12403", "JPN12421", "JPN12422", "JPN12423", "JPN12424", "JPN12426", "JPN12427", "JPN12441", "JPN12463", "JPN13101", "JPN13102", "JPN13103", "JPN13104", "JPN13105", "JPN13106", "JPN13107", "JPN13108", "JPN13109", "JPN13110", "JPN13111", "JPN13112", "JPN13113", "JPN13114", "JPN13115", "JPN13116", "JPN13117", "JPN13118", "JPN13119", "JPN13120", "JPN13121", "JPN13122", "JPN13123", "JPN13201", "JPN13202", "JPN13203", "JPN13204", "JPN13205", "JPN13206", "JPN13207", "JPN13208", "JPN13209", "JPN13210", "JPN13211", "JPN13212", "JPN13213", "JPN13214", "JPN13215", "JPN13218", "JPN13219", "JPN13220", "JPN13221", "JPN13222", "JPN13223", "JPN13224", "JPN13225", "JPN13227", "JPN13228", "JPN13229", "JPN13303", "JPN13305", "JPN13307", "JPN13308", "JPN14101", "JPN14102", "JPN14103", "JPN14104", "JPN14105", "JPN14106", "JPN14107", "JPN14108", "JPN14109", "JPN14110", "JPN14111", "JPN14112", "JPN14113", "JPN14114", "JPN14115", "JPN14116", "JPN14117", "JPN14118", "JPN14131", "JPN14132", "JPN14133", "JPN14134", "JPN14135", "JPN14136", "JPN14137", "JPN14151", "JPN14152", "JPN14153", "JPN14201", "JPN14203", "JPN14204", "JPN14205", "JPN14206", "JPN14207", "JPN14208", "JPN14210", "JPN14211", "JPN14212", "JPN14213", "JPN14214", "JPN14215", "JPN14216", "JPN14217", "JPN14218", "JPN14301", "JPN14321", "JPN14341", "JPN14342", "JPN14361", "JPN14362", "JPN14363", "JPN14364", "JPN14366", "JPN14383", "JPN14384", "JPN14401", "JPN14402", "JPN19206", "JPN19212" ], "member_geography_levels": [ "Municipalities (市区町村)" ], "member_count_by_geography_level": { "Municipalities (市区町村)": 228 }, "membership_interpretation": "Counts of source correspondence units. Multiple geographic levels may overlap; do not sum their populations or treat these rows as disjoint boundary components.", "membership_source_frame": "oecd-membership", "membership_boundary_alignment": "not audited; separate source snapshots must not be assumed contemporaneous", "scoring_approved": false, "source_geometry_wkb_sha256": "b5ca1cdd69d0966e8f48bba7a8d64cbe01f0cde5680d1472337a10e02a06c3f9", "shared_with": [] } ], "estimated_fua_2015": { "status": "matched", "source_frame": "jrc-efua", "boundary_vintage": "2015", "type": "JRC/OECD globally estimated functional urban area; modelled commuting influence", "scoring_approved": false, "candidates": [ { "eFUA_ID": 5129, "eFUA_name": "Tokyo", "Cntry_ISO": "JPN", "Cntry_name": "Japan", "UC_IDs": "12962;12964;12966;12989;12995", "UC_num": 5, "source_geometry_wkb_sha256": "48a22203c281dea4beaec496ad4f3aacf5dda2a5e0a9bd7ddcf5d5935c24165e", "shared_with": [] } ], "notice": "Historical estimated area of influence, not observed current commuting data. Not interchangeable with OECD administrative FUAs or 2025 GHSL urban centres." }, "eurostat_2024_research_crosscheck": { "status": "unresolved", "source_frame": "gisco-2024", "boundary_vintage": "2024-01-01", "geometry_redistribution_cleared": false, "licence_notice": "Retrieved GISCO metadata states source acknowledgement and non-commercial use; Administrative boundaries: © EuroGeographics. Do not assume commercial API boundary reuse is cleared.", "candidates": [] }, "scope_notice": "Municipal/city-proper, national metropolitan, police-service and GHSL urban-centre records describe their own populations and boundaries. They do not become FUA observations through matching city names or shared points. Indicator-specific aggregation and a reviewed vintage crosswalk are required.", "evaluated_at": "2026-10-26", "registry_url": "https://bestcitytolive.com/api/v1/geography-candidates.json", "notice": "An evidence-backed geography intake, not the scoring approval registry. Matches establish candidate identities, not comparable indicator coverage. 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OECD IDs/overlap diagnostics are separate, non-equivalence crosswalks.", "crosswalk": { "city_slug": "tokyo", "estimated_area_id": 5129, "oecd_crosswalk": [ { "oecd_id": "JPN01F", "oecd_name": "Tokyo", "status": "spatial-overlap-diagnostic-only", "boundary_vintage": null, "estimated_area_km2": 11971, "oecd_projected_area_km2": 11329.412471922402, "intersection_km2": 9681.531908892248, "fraction_of_estimated_area_in_oecd": 0.8087488020125511, "fraction_of_oecd_area_in_estimated": 0.8545484536718843, "intersection_over_union": 0.7108904336215238, "oecd_reprojected_validity_adapter_applied": false, "notice": "Approximate area diagnostic after reprojection to common equal-area CRS; not boundary equivalence, current boundary vintage, population coverage or outcome conversion weights." } ], "oecd_status": "matched-different-edition", "reference_point": { "longitude": 139.6503, "latitude": 35.6762, "provenance": "Inherited destination registry: spatial lookup aid only; not evidence of a scored boundary." }, "destination_country_iso3": "JPN", "source_country_iso3": "JPN", "source_country_name": "Japan" }, "reviewed_at": "2026-10-26", "scoring_approved": true, "policy_decision_ref": "civometra.heat2025.complete-source-and-scoped-review@1.0.0", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "shared_with": [], "source_record_ref": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0; eFUA_ID=5129; fid=5886", "exact_geometry": { "archive_file": "efua-2015-cohort-exact.gpkg", "archive_sha256": "12ae143651080d64458da3ce2603bb58ee4cd3d9357e624a383128f41f0bebc9", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "source_fid": 5886, "source_geometry_wkb_sha256": "48a22203c281dea4beaec496ad4f3aacf5dda2a5e0a9bd7ddcf5d5935c24165e", "source_geometry_blob_sha256": "bb6dc57064eb417d3e0597746809b4a88d7618f936f67a74058c1a2490fc3ecc", "crs": "ESRI:54009", "simplified": false, "reprojected": false, "clipped": false }, "extraction_geometry": { "archive_file": "efua-2015-cohort-validity-adapter.gpkg", "archive_sha256": "514cc4071511d149ff4f37b533404954e5e785913cbafce1294428848bc0a9fb", "table": "GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0", "record_id": 5129, "geometry_wkb_sha256": "d0e2bd09cc85c912684eae1641fef5e1aad86bdd6bb26124d3662b772fd76ce7", "adapter": "make-valid-linework-v1", "source_1km_mask_sha256": "ec8276a792adc0e402d1f1ed047d1141ed2811a07e3670ac85ff92b6b17fa520" }, "geometry_review": { "completed": true, "reviewed_at": "2026-10-26", "original_valid": false, "validity_adapter_applied": true, "native_area_and_grid_footprint_unchanged": true }, "interpretation": "Fixed 2015 globally estimated functional area. 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GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "original_source_frame_ref": "ghs-efua-2015-r2019a-v1-0-original", "original_source_archive_sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "adaptation": "Exact selected original features, with documented make_valid linework decomposition only where invalid. No coordinate, boundary-linework, area or 1 km cell-footprint change; source originals separately retained.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-efua-2015-cohort-validity-adapter-514cc4071511.gpkg", "source_ref": "source-0a2031537592e1ba" }, { "id": "ghs-efua-2015-r2019a-v1-0-original", "archive_url": "/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "sha256": "d54de59b82b8c4d64a710f90ccd554975a3be92233f14115ac154094c3549979", "source_urls": [ "https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_FUA_UCDB2015_GLOBE_R2019A/V1-0/GHS_FUA_UCDB2015_GLOBE_R2019A_54009_1K_V1_0.zip", "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95" ], "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "reuse_review": "permitted-with-attribution", "reuse_reviewed_at": "2026-10-26", "copyright_notice_sha256": "f20723519a580fb35b3499870f0b1baea54f483195105416e547f0014f1610d2", "attribution": "European Commission, Joint Research Centre, developed in collaboration with OECD. GHS-FUA R2019A (2015), V1_0. Source DOI 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95. Selection and geometry validity adaptation by BestCityToLive / AINT.app; no publisher endorsement.", "archive_absolute_url": "https://bestcitytolive.com/data/source-frames/ghs-fua-2015-r2019a-d54de59b82b8.zip", "source_ref": "source-0a2031537592e1ba" } ] } ], "reviewed_pm25_history": { "city_slug": "tokyo", "city_name": "Tokyo", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "source_area_id": "5129", "source_area_name": "Tokyo", "value": 12.907995602808032, "unit": "micrograms/m3", "period_start": "2024-01-01", "period_end": "2024-12-31", "population_reference_year": 2020, "boundary_reference_year": 2015, "concentration_year": 2024, "source_model": { "name": "SatPM CNNPM25", "version": "V6.GL.03", "source_url": "https://satpmdata.s3.us-east-1.amazonaws.com/V6GL03/CNNPM25/Annual/GL/V6GL03.CNNPM25.GL.202401-202412.nc", "sha256": "9f1059f6a7d675a53f987e8b6ccc6981c3c29a867cc3a2324043a4eff2c19928" }, "protocol_ref": "civometra.pm25.measurement@1.0.0", "shared_with": [], "coverage": { "population_grid_area_coverage": 0.9971598028569042, "pm_population_coverage": 1, "cell_count": 11971, "population_grid_valid_cells": 11937, "population_grid_missing_cells": 34, "population_grid_zero_cells": 934, "total_known_modelled_population": 36697548.9260917, "pm_covered_population": 36697548.9260917, "weighted_concentration_sum": 473691800.17182434, "population_in_zero_pm_cells": 0 }, "denominator": 36697548.9260917, "sensitivity": { "bilinear_estimate": 12.907096731928107, "bilinear_population_coverage": 1, "coarse_estimate": 12.889587420219799, "coarse_population_coverage": 1, "notice": "Method-sampling diagnostics with their own coverage; not statistical uncertainty or confidence intervals. Neither fills missing primary values." }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "No city-specific statistical interval supplied by this global product; sampling sensitivity is not a confidence interval." }, "frame": { "url": "/data/source-frames/pm25-2024-efua-5129.npz", "sha256": "4f0d6280620ab857695c96370145c4f70bc5241ae13c8c577326097db9f60083" }, "geography_ref": "efua-2015-v1-0:tokyo", "evidence_id": "pm25-2024-efua2015-tokyo", "review_status": "accepted", "scope_notice": "Annual 2024 modelled ambient PM2.5 weighted by 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Historical modelled geography; source country labels and area identities are retained.", "source_attribution": [ { "publisher": "Atmospheric Composition Analysis Group / Washington University in St. Louis / SatPM", "title": "Shen, S., Li, C., van Donkelaar, A., Jacobs, N., Wang, C., and Martin, R. V. (2024). Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. ACS ES&T Air. doi:10.1021/acsestair.3c00054. SatPM V6.GL.03, annual 2024; accessed 26 October 2026.", "url": "https://www.satpm.org/v6-gl-03", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre", "title": "GHS-POP R2023A V1-0, 2020 modelled residential-population counts", "url": "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre, in collaboration with OECD", "title": "GHS-FUA R2019A V1_0, estimated functional urban areas, 2015", "url": "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95", "licence": "CC BY 4.0" } ], "reviewed_at": "2026-10-26", "current": { "admitted": true, "as_of": "2026-10-27" }, "current_engine_state": "accepted", "current_engine_evaluated_at": "2026-10-27", "review_status_meaning": "Historical review approval, not a guarantee of current admission. The current engine state separately applies age and all other checks." }, "reviewed_heat_history": { "city_slug": "tokyo", "city_name": "Tokyo", "analytical_area_id": "ghs-efua-2015-r2019a:5129", "source_area_id": "5129", "source_area_name": "Tokyo", "value": 29.44000849449062, "unit": "person-days/person", "period_start": "2025-01-01", "period_end": "2025-12-31", "weather_reference_year": 2025, "population_reference_year": 2020, "boundary_reference_year": 2015, "protocol_ref": "civometra.heat-exposure.measurement@1.0.0", "geography_ref": "efua-2015-heat-v1-0:tokyo", "evidence_id": "heat-2025-efua2015-tokyo", "shared_with": [], "review_status": "accepted", "scope_notice": "Annual 2025 modelled outdoor heat exposure using 2020 modelled population in the fixed 2015 estimated area Tokyo (source ID 5129). Native weather resolution is 0.25 degrees. This historical modelled analytical footprint is not a current municipality or observed commuting boundary.", "coverage": { "cell_count": 11971, "population_grid_valid_cells": 11937, "missing_cells": 34, "zero_cells": 934, "population_grid_area_coverage": 0.9971598028569042, "total_known_modelled_population": 36697548.9260917, "weather_covered_population": 36697548.9260917, "weather_population_coverage": 1, "weighted_exposed_person_days": 1080376152.1111248, "native_weather_points": 33, "expected_days": 365 }, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "value": 0.25519059874306943, "weighted_exposed_person_days": 9364869.482852425 }, { "month": "2025-07", "calendar_days": 31, "value": 8.804585907445192, "weighted_exposed_person_days": 323106722.11244744 }, { "month": "2025-08", "calendar_days": 31, "value": 15.854601605423266, "weighted_exposed_person_days": 581825018.1187123 }, { "month": "2025-09", "calendar_days": 30, "value": 4.52563038287909, "weighted_exposed_person_days": 166079542.39711252 }, { "month": "2025-10", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "value": 0, "weighted_exposed_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "value": 0, "weighted_exposed_person_days": 0 } ], "definition_sensitivity": { "label": "threshold-definition sensitivity", "threshold_c": 38, "primary_comparison": ">=", "reference_comparison": ">", "denominator": 36697548.9260917, "strict_value": 29.44000849449062, "strict_weighted_exposed_person_days": 1080376152.1111248, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0, "monthly_exposure_days": [ { "month": "2025-01", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-02", "calendar_days": 28, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-03", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-04", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-05", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-06", "calendar_days": 30, "strict_value": 0.25519059874306943, "strict_weighted_exposed_person_days": 9364869.482852425, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-07", "calendar_days": 31, "strict_value": 8.804585907445192, "strict_weighted_exposed_person_days": 323106722.11244744, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-08", "calendar_days": 31, "strict_value": 15.854601605423266, "strict_weighted_exposed_person_days": 581825018.1187123, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-09", "calendar_days": 30, "strict_value": 4.52563038287909, "strict_weighted_exposed_person_days": 166079542.39711252, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-10", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-11", "calendar_days": 30, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 }, { "month": "2025-12", "calendar_days": 31, "strict_value": 0, "strict_weighted_exposed_person_days": 0, "inclusive_minus_strict_value": 0, "equality_weighted_person_days": 0 } ], "notice": "Exact published-Celsius comparison sensitivity; not a confidence interval, physical accuracy estimate, new scored indicator or replacement primary value. The provider backend comparison/conversion order is not established." }, "uncertainty": { "status": "not-reported-for-this-derived-area", "note": "The source supplies no city-specific statistical confidence interval. Regional reanalysis does not resolve shade, indoor conditions, neighbourhood microclimate or individual physiological exposure." }, "frame": { "url": "/data/source-frames/heat-2025-efua-5129.npz", "sha256": "d64332f7607272912a095070a090e36047f1c95ce75a0af74d82d7d8db41d1d3" }, "source_attribution": [ { "publisher": "Copernicus Climate Change Service (C3S), implemented by ECMWF", "title": "ERA5-HEAT via Thermal Trace, archived 2025 daily maximum/minimum outdoor UTCI chart facts", "url": "https://cds.climate.copernicus.eu/datasets/derived-utci-historical?tab=overview", "licence": "CC BY 4.0", "attribution": { "licence": "CC BY 4.0", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "basis": "Pinned official frontend chart/CSV export metadata; the JSON response itself omits licence and units.", "attribution": "Contains modified Copernicus Climate Change Service (C3S) information 2025, implemented by ECMWF. Source: ERA5-HEAT via Thermal Trace and the Climate Data Store, DOI 10.24381/cds.553b7518; chart facts licensed CC BY 4.0.", "modifications": "Modified by BestCityToLive / AINT.app: daily maxima counted >=38 degrees Celsius on exact exported daily operands, native 0.25-degree sampling with the disclosed higher-coordinate tie rule, GHS-POP 2020 population weighting on reviewed estimated-FUA 2015 masks, and annual/monthly calculations with strict-threshold definition sensitivity. These derivatives are not source-produced city estimates.", "responsibility_notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data in this publication.", "no_endorsement": "The original publishers have not endorsed BestCityToLive, AINT.app, Civometra, the historical estimated-area compatibility review, or these derived city-area values." } }, { "publisher": "European Commission Joint Research Centre", "title": "GHS-POP R2023A V1-0, 2020 modelled residential population counts", "url": "https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe", "licence": "CC BY 4.0" }, { "publisher": "European Commission Joint Research Centre, in collaboration with OECD", "title": "GHS-FUA R2019A V1_0, estimated functional urban areas, 2015", "url": "https://data.jrc.ec.europa.eu/dataset/347f0337-f2da-4592-87b3-e25975ec2c95", "licence": "CC BY 4.0" } ], "reviewed_at": "2026-10-26", "current_engine_state": "accepted", "current_engine_evaluated_at": "2026-10-27", "current": { "admitted": true, "status": "accepted", "as_of": "2026-10-27", "reason": "A reviewed observation passes the configured admission checks." }, "review_status_meaning": "Historical review approval; current admission separately applies age and other engine checks.", "source_refs": { "weather_source_ref": "source-82ac6f7a3f0687eb", "app_source_ref": "source-46745581000ebca4", "population_source_ref": "source-f3189a9194a27e72" }, "attribution_source_refs": [ "source-82ac6f7a3f0687eb", "source-f3189a9194a27e72", "source-ef5611a3b029db1b" ], "monthly_status": "dependent-annual-contributions-not-independent-indicators", "notice": "Dated modelled annual heat research, using historical population and estimated boundaries. A counted UTC day reaches the daily-maximum UTCI threshold; it does not mean 24 hours at that threshold or individual measured exposure. Monthly rows are dependent contributions to one annual indicator, not independent admitted metrics, forecasts or climate normals. Current admission comes only from the engine; no composite score or official ranking is established." }, "reviewed_rental_vacancy_history": null, "reviewed_housing_supply_history": null, "reviewed_life_expectancy_history": null, "reviewed_road_deaths_history": null, "links": { "city": "https://bestcitytolive.com/api/v1/cities/tokyo.json", "markdown": "https://bestcitytolive.com/api/v1/cities/tokyo.md", "index_metrics": "https://bestcitytolive.com/api/v1/index-metrics.json", "urban_centres": "https://bestcitytolive.com/api/v1/urban-centres.json" } }