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- Konzept/, didaktik_geografie/, didaktik_simulation/, v2-modules/, v2-platform/ - 12 code-workspace-Files - STATUS-*.md - viele M/D/R-Änderungen an bereits getrackten Files - .gitignore verstärkt: **/.humaninput/, **/secret_keys.txt Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
67 lines
3.5 KiB
JSON
67 lines
3.5 KiB
JSON
{
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"_comment": "5 Welt-Handelshubs (reale Top-Container-Häfen / Drehscheiben). consumerCities = regionale Konsumenten — wenn die Lieferung am Hub ankommt, wird sie symbolisch per LKW weiterverteilt (zeigt: Markt = Konsumraum, nicht ein Punkt).",
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"hubs": [
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{
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"id": "hamburg", "title": {"de": "Hamburg", "easy": "Hamburg"},
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"lat": 53.55, "lon": 9.99, "icon": "🇪🇺", "continent": "Europe",
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"consumerCities": [
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{ "name": "Berlin", "lat": 52.52, "lon": 13.40 },
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{ "name": "Paris", "lat": 48.85, "lon": 2.35 },
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{ "name": "Mailand", "lat": 45.46, "lon": 9.19 },
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{ "name": "Wien", "lat": 48.21, "lon": 16.37 },
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{ "name": "Warschau", "lat": 52.23, "lon": 21.01 }
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]
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},
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{
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"id": "newyork", "title": {"de": "New York", "easy": "New York"},
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"lat": 40.71, "lon": -74.01, "icon": "🇺🇸", "continent": "North America",
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"consumerCities": [
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{ "name": "Toronto", "lat": 43.65, "lon": -79.38 },
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{ "name": "Boston", "lat": 42.36, "lon": -71.06 },
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{ "name": "Atlanta", "lat": 33.75, "lon": -84.39 },
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{ "name": "Chicago", "lat": 41.88, "lon": -87.63 },
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{ "name": "Miami", "lat": 25.76, "lon": -80.19 }
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]
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},
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{
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"id": "shanghai", "title": {"de": "Shanghai", "easy": "Shanghai"},
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"lat": 31.22, "lon": 121.46, "icon": "🇨🇳", "continent": "Asia",
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"consumerCities": [
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{ "name": "Tokyo", "lat": 35.68, "lon": 139.69 },
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{ "name": "Seoul", "lat": 37.57, "lon": 126.98 },
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{ "name": "Hongkong", "lat": 22.30, "lon": 114.17 },
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{ "name": "Taipeh", "lat": 25.03, "lon": 121.57 },
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{ "name": "Manila", "lat": 14.60, "lon": 120.98 }
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]
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},
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{
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"id": "saopaulo", "title": {"de": "São Paulo", "easy": "São Paulo"},
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"lat": -23.55, "lon": -46.63, "icon": "🇧🇷", "continent": "South America",
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"consumerCities": [
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{ "name": "Rio de Janeiro", "lat": -22.91, "lon": -43.17 },
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{ "name": "Belo Horizonte", "lat": -19.92, "lon": -43.94 },
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{ "name": "Asunción", "lat": -25.30, "lon": -57.61 },
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{ "name": "Buenos Aires", "lat": -34.60, "lon": -58.38 },
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{ "name": "Brasília", "lat": -15.79, "lon": -47.88 }
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]
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},
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{
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"id": "dubai", "title": {"de": "Dubai", "easy": "Dubai"},
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"lat": 25.20, "lon": 55.27, "icon": "🇦🇪", "continent": "Asia",
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"consumerCities": [
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{ "name": "Riyadh", "lat": 24.71, "lon": 46.68 },
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{ "name": "Tehran", "lat": 35.69, "lon": 51.39 },
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{ "name": "Karachi", "lat": 24.86, "lon": 67.01 },
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{ "name": "Mumbai", "lat": 19.08, "lon": 72.88 },
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{ "name": "Cairo", "lat": 30.04, "lon": 31.24 }
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]
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}
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],
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"transport": {
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"_comment": "Modus-Wahl: dist < 1500 km → LKW, sonst → Schiff. Reefer-Aufschlag 1.5× Kosten + 2× CO2 für perishable (Bananen). Quellen: Frachtraten UNCTAD / Eurostat 2023, CO2-Faktoren Umweltbundesamt 2022 (gerundet). factorPerTonKm in € pro Tonne-km, co2PerTonKm in Gramm pro Tonne-km.",
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"truck": { "icon": "🚚", "factorPerTonKm": 0.07, "co2PerTonKm": 90, "speedKmPerSec": 500, "label": {"de": "LKW", "easy": "LKW"} },
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"ship": { "icon": "🚢", "factorPerTonKm": 0.015, "co2PerTonKm": 15, "speedKmPerSec": 1333, "label": {"de": "Schiff", "easy": "Schiff"} },
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"plane": { "icon": "✈️", "factorPerTonKm": 1.5, "co2PerTonKm": 1000, "speedKmPerSec": 2000, "label": {"de": "Flugzeug", "easy": "Flugzeug"} }
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}
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}
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