An open environmental-justice method for prioritising protection of schoolchildren from air pollution in Central Asia — data and code

Compact derived datasets and the complete analysis pipeline for an open, transferable environmental-justice method that prioritises school-level air-pollution protection in data-scarce cities, demonstrated across six Central Asian capitals (Tashkent, Almaty, Astana, Bishkek, Dushanbe, Ashgabat) and transferred out-of-region (Accra, Kathmandu, Lima).Contents (see ZENODO_MANIFEST.md and CLAIM_INDEX.md): per-school exposure surfaces, building-age, wealth (Meta RWI), under-20 child-density and NO2 layers; the injustice/retrofit-priority index and its robustness runs (random weightings, VIIRS and GRDI deprivation cross-checks, surface-parameter sweep, indoor/outdoor invariance); measured on-school validation; reference and municipal-network PM2.5; health (GBD 2021) inputs; global-applicability and OpenAQ reference-coverage tables; and all Python code. Raw third-party rasters (ACAG, GRDI, WSF, WorldPop) are NOT redistributed; each script fetches them from their public source, so the pipeline is fully reproducible from open data.Data CC-BY-4.0; code MIT. Associated manuscript submitted to npj Urban Sustainability.