Research Methods

Methodology

Summary of how the platform classifies, aggregates, and displays environmental information.

Research DashboardMethodology

Document details

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Last updated: [Effective Date]
Bivariate classes
3 × 3 matrix
Missing data rule
Missing is a data-quality state, not a measurement
Aggregation examples
Nearest station, regional mean, regional median, maximum pollution
Research note
Correlation does not imply causation

Observations and joins

The dashboard may combine air-quality observations, pollutant concentrations, weather context, regional boundaries, and analytical overlays from multiple sources. Spatial assignment can depend on station coordinates, boundary polygons, provider metadata, or normalized identifiers.

Coverage states

  • Valid: both selected dimensions available within freshness thresholds.
  • Partial: only one selected dimension available.
  • Stale: one or more observations older than the configured threshold.
  • No station: no matching monitoring station available for the region.
  • Provider gap: provider coverage does not currently include the region.
  • API error: a provider request or enrichment step failed.

Classification and aggregation

Bivariate maps use a 3 × 3 classification matrix. Only valid observations participate in quantile or equal-range calculations. Missing, stale, or invalid regions must not influence thresholds, ranks, AQI distributions, or research summaries.

Historical and comparative limitations

Historical series may be derived from provider retention windows, sampling frequencies, and AQI conversion logic. Comparative research views may involve heterogeneous data sources and should be interpreted cautiously.

Legal review

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