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EWC-CAT

EWC Hazard Classification

1. Identity

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Depends on module:

Purpose
Classifies waste line items as hazardous or non-hazardous (and optionally assigns hazard class metadata) by resolving an EWC-based mapping dataset (e.g. ewc_all_categories) under ZAR version control.

This engine is the missing governance step that makes hazardous waste reporting auditable:

• the classification rule is explicit,
• dataset version is pinned,
• and every item carries provenance.

Typical usage

• Ingest waste contractor manifests/invoices containing EWC codes
• Enrich line items with: hazardous, hazard_class, canonical ewc_item id, recommended unit
• Feed clean items into MEID_CALC_WASTE_AGGR (which then becomes a pure aggregator)

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2. Contract References (ZAR)

2.1 Input Schema

ZAR Address: schema.compute.waste.haz_classify.inputs.v1_0_0

Required conceptual fields:

• items: list of waste line items to classify
• mapping_ref: ZAR reference to the EWC mapping dataset (defaults allowed)
• jurisdiction: optional (e.g., EU, NO, UK) for regional variations
• alignment: BY_YEAR | BY_INDEX (default BY_YEAR)

Each item conceptually includes:

• period (typically year)
• value
• unit (e.g., kg, tonne)
• one of:
  • ewc_code (preferred, e.g. "01 03 04*" or "010304*")
  • ewc_item (internal key, e.g. "04")
• optional:
  • site_id
  • supplier_id / contractor_id
  • invoice_id / manifest_id
  • description (free text)
  • regional_code (if different from jurisdiction)

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2.2 Options Schema

ZAR Address: schema.compute.waste.haz_classify.options.v1_0_0

Common options:

• match_mode: EWC_CODE | EWC_ITEM | AUTO (default AUTO)
• normalize_ewc_code: boolean (default true)
• asterisk_means_hazardous: boolean (default true)
  (EU convention: * indicates hazardous entry)
• unknown_code_policy: ERROR | FLAG | ASSIGN_NON_HAZARDOUS | ASSIGN_UNKNOWN (default FLAG)
• regional_variations_policy: APPLY_IF_PRESENT | IGNORE (default APPLY_IF_PRESENT)
• unit_normalization: NO_CONVERT | CONVERT_TO_RECOMMENDED (default NO_CONVERT)
• rounding: optional digits

Unit conversion is delegated (as per your architecture rule). This engine only requests conversion if CONVERT_TO_RECOMMENDED.

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2.3 Output Schema

ZAR Address: schema.compute.waste.haz_classify.output.v1_0_0

Outputs include:

• items_classified: same items enriched with classification fields
• summary: counts by classification outcome
• metadata: mapping version/hash, unknown handling stats, jurisdiction used

Enriched fields per item:

• hazardous: boolean or enum
• hazard_class: HAZARDOUS | NON_HAZARDOUS | UNKNOWN
• ewc_item (canonical internal key)
• ewc_code_normalized
• recommended_unit
• reuse_recyclable_flag
• classification_confidence (v1: 1.0 for exact match, lower for heuristic)
• classification_provenance (mapping_ref + row id + rule path)

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3. Mapping Dataset Contract (ewc_all_categories)

The mapping dataset MUST provide at least these columns (your example fits perfectly):

• ewc_item (canonical id)
• ewc_code (string, may include *)
• hazard_class (HAZARDOUS/NON_HAZARDOUS)
• optional:
  • hazardous (boolean/Yes)
  • regional_variations (json/text)
  • recommended_unit
  • reuse_recyclable_flag
  • description

The engine MUST treat the dataset as authoritative and versioned:

• mapping_ref MUST resolve to an immutable ZAR artifact
• the output MUST carry mapping_ref + build_hash (or dataset hash if stored separately)

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4. Classification Semantics (Normative)

Let an input item be $i$.

4.1 EWC code normalization

If normalize_ewc_code = true, transform ewc_code into canonical form:

• remove spaces
• uppercase
• keep trailing * if present

Example:

• "01 03 04*" → "010304*"
• "01 03 04 *" → "010304*"

Call the normalized code $code(i)$.

4.2 Matching strategy

If match_mode:

• EWC_CODE: match only by normalized ewc_code
• EWC_ITEM: match only by ewc_item
• AUTO:
  1. try ewc_code
  2. fallback to ewc_item

Let the matched mapping row be $m(i)$.

If no match:

• apply unknown_code_policy

4.3 Hazard determination (EU star rule)

If asterisk_means_hazardous = true and the matched ewc_code ends with *, then hazard is hazardous even if the dataset row is missing the hazard flag.

Final hazard class:

• If match exists:
  • hazard_class(i) = hazard_class(m(i))
    unless overridden by star rule
• If no match:
  • depends on unknown_code_policy

Star override (if enabled):

$hazard\_class(i) \leftarrow \mathrm{HAZARDOUS} \quad \text{if } code(i) \text{ ends with } *$

4.4 Regional variations

If regional_variations_policy = APPLY_IF_PRESENT and a region key matches the request (jurisdiction or regional_code), apply overrides from regional_variations.

The output MUST record whether a regional override was applied.

4.5 Recommended unit enrichment

If mapping contains recommended_unit, set:

• recommended_unit(i) = recommended_unit(m(i))

If unit_normalization = CONVERT_TO_RECOMMENDED, the engine MUST:

• emit a conversion request (or call the conversion dependency in execution)
• record the conversion provenance

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5. Input/Output Examples

Example A — simple EWC code classification

{
  "mapping_ref": "DATASET.WASTE.EWC_ALL_CATEGORIES.v1",
  "jurisdiction": "EU",
  "items": [
    { "period": 2025, "value": 40, "unit": "tonne", "ewc_code": "01 03 04*" },
    { "period": 2025, "value": 500, "unit": "tonne", "ewc_code": "17 01 07" }
  ]
}

Output (illustrative):

{
  "items_classified": [
    {
      "period": 2025,
      "value": 40,
      "unit": "tonne",
      "ewc_code": "01 03 04*",
      "ewc_code_normalized": "010304*",
      "ewc_item": "04",
      "hazard_class": "HAZARDOUS",
      "hazardous": true,
      "recommended_unit": "tonnes",
      "reuse_recyclable_flag": false,
      "classification_confidence": 1.0,
      "classification_provenance": {
        "mapping_ref": "DATASET.WASTE.EWC_ALL_CATEGORIES.v1",
        "matched_key": "ewc_code",
        "matched_row_ewc_item": "04",
        "rule_path": "dataset_match+asterisk_override"
      }
    },
    {
      "period": 2025,
      "value": 500,
      "unit": "tonne",
      "ewc_code": "17 01 07",
      "ewc_code_normalized": "170107",
      "hazard_class": "NON_HAZARDOUS",
      "hazardous": false,
      "classification_confidence": 1.0,
      "classification_provenance": {
        "mapping_ref": "DATASET.WASTE.EWC_ALL_CATEGORIES.v1",
        "matched_key": "ewc_code",
        "rule_path": "dataset_match"
      }
    }
  ],
  "summary": {
    "total_items": 2,
    "hazardous_items": 1,
    "non_hazardous_items": 1,
    "unknown_items": 0
  }
}

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6. Validation & Error Model

Invariants

• items must be non-empty
• each item must provide either ewc_code or ewc_item
• mapping dataset must resolve and be readable
• normalized codes must be syntactically valid (v1: simple regex)

Error codes (suggested)

• WASTE_HAZ_MAP_NOT_FOUND
• WASTE_HAZ_ITEM_MISSING_EWC_KEY
• WASTE_HAZ_INVALID_EWC_FORMAT
• WASTE_HAZ_UNKNOWN_CODE_ERROR
• WASTE_HAZ_REGIONAL_OVERRIDE_INVALID

Errors MUST include:

• engine cmi_short_code
• item index + any manifest/invoice identifier + offending ewc code

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7. Dependencies

MEID_TRANS_WASTE_HAZ_CLASSIFY depends on:

• schema resolver (ZAR)
• mapping dataset resolver (mapping_ref)
• optional unit conversion capability (delegated; only if unit normalization enabled)

Declared via ZAR dependencies.

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8. Federation & Audit Requirements

To reproduce hazard classification externally, the export MUST include:

• engine identity (cmi or zar_code)
• engine build proof (execution_ref + build_hash)
• mapping dataset reference/version/hash (mapping_ref)
• jurisdiction/regional options used
• unknown handling policy
• per-item provenance (matched row / rule path)

Provenance chain MUST show:

… → MEID_TRANS_WASTE_HAZ_CLASSIFY → MEID_CALC_WASTE_AGGR → …

with cmi_short_code recorded in USO tail arrays.

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9. Performance Notes

• Complexity: $O(n)$ over items with hash-map lookup on ewc_code_normalized
• Memory: $O(n)$ output size
• Dataset should be cached by mapping_ref in-memory per worker

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10. Methods Served (v1)

• Waste.item.classified (enrichment output)
• (optional convenience) hazardous/non-hazardous subtotals if requested

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