Epd Parser

/epd-parser — EPD PDF Parser

Extract structured environmental impact data from EPD (Environmental Product Declaration) PDF files. Uses PyMuPDF for text extraction and Claude's reasoning to parse varying EPD formats into a standardized 42-column schema.

EPDs follow ISO 14025 / ISO 21930 / EN 15804 and report life cycle environmental impacts of building products. This skill reads those PDFs and structures the data for comparison, specification, and LEED documentation.

Input

The user provides EPD PDFs in one of these ways:

1. File paths — one or more PDF file paths
2. Folder path — a directory containing PDFs (will process all .pdf files)
3. Just invoked — ask the user for file paths or a folder

Also ask (or use defaults):

• Output destination — Google Sheet, local CSV, or markdown (default: ask)

Output Schema

EPD data uses a 42-column schema — separate from the 33-column FF&E product schema. When writing to CSV, use the same column order.

Product Identity (columns A-H)

EPD Metadata (columns I-P)

Impact Indicators — Product Stage A1-A3 (columns Q-V)

Impact Indicators — Other Stages (columns W-AB)

Resource Use (columns AC-AH)

Tracking (columns AI-AP)

Material Category Vocabulary

Use ONE normalized term: Concrete, Steel, Aluminum, Wood/Timber, Insulation, Gypsum, Glass, Ceramic/Tile, Carpet, Resilient Flooring, Roofing Membrane, Sealant, Paint/Coating, Masonry, Stone, Composite Panel, Acoustic, Cladding, Rebar, Cement, Aggregate, Furniture, Other.

EPD-specific data in Notes (col AO)

EPDs contain fields that don't have dedicated columns. Append these to Notes:

• EPD Type: Type: Product-specific or Type: Industry-average or Type: Sector
• Verification: Verified by: [verifier name]
• EN version: EN 15804+A1 or EN 15804+A2 (important for comparability)
• Source File: Source: holcim-readymix-epd.pdf
• LCA Software: LCA: GaBi or LCA: SimaPro or LCA: openLCA
• Biogenic carbon note: If the EPD reports biogenic carbon storage separately

Example Notes cell: Type: Product-specific | Verified by: Underwriters Laboratories | EN 15804+A2 | LCA: GaBi | Source: holcim-readymix-epd.pdf

LEED Eligibility Logic (col AI)

• Yes: Product-specific, third-party verified EPD conforming to ISO 14025
• Partial: Industry-average or sector EPD (counts for LEED Option 1 but not Option 2)
• No: Self-declared, unverified, or non-conforming

Workflow

Step 1: Get input

Parse the user's input to identify PDF file(s) and output preferences.

• If given a folder, list all .pdf files and report count
• If no PDFs found or path is invalid, ask the user
• Report: "Found N EPD PDF(s) to process."

Step 2: Extract text from PDF

Use PyMuPDF (fitz) to extract text from each PDF. Run this Python script via Bash:

import fitz
import sys
import json

pdf_path = sys.argv[1]
doc = fitz.open(pdf_path)
pages = []
for i, page in enumerate(doc):
    text = page.get_text()
    pages.append({"page": i + 1, "text": text})
doc.close()

print(json.dumps({"filename": pdf_path.split("/")[-1], "total_pages": len(pages), "pages": pages}))

For each PDF, extract all pages and save the JSON output.

Step 3: Parse EPD data

Read the extracted text and identify all environmental impact data. This is the core intelligence step.

For small EPDs (<=30 pages): Process all pages at once.

For large EPDs (>30 pages): Process in chunks of 15 pages. Carry forward context between chunks.

Parsing instructions:

1. Identify the EPD structure — EPDs typically have these sections:

   • General information (pages 1-2): manufacturer, product, declared unit, program operator, validity
   • Product description (pages 2-3): materials, manufacturing process, application
   • LCA information: system boundary, data sources, allocation rules
   • Impact indicator tables: the core data — usually 1-3 pages of tables
   • Resource use and waste tables
   • Additional information: scenarios, biogenic carbon, recycled content

2. Extract product identity first — manufacturer, product name, declared unit, functional unit. These are always on page 1-2.

3. Extract EPD metadata — registration number, program operator, PCR, standard, dates, system boundary. Usually on page 1 or in a header/sidebar.

4. Find and parse impact indicator tables — This is the most critical step:

   • Look for tables with life cycle stage columns (A1, A2, A3 or A1-A3 combined, A4, A5, B1-B7, C1-C4, D)
   • Impact categories are rows: GWP, ODP, AP, EP, POCP, ADP (or ADPE/ADPF)
   • EN 15804+A2 EPDs split GWP into: GWP-total, GWP-fossil, GWP-biogenic, GWP-luluc. Capture all that exist.
   • EN 15804+A1 EPDs report a single GWP row. Put this value in GWP-total (A1-A3).
   • If A1, A2, A3 are reported separately (not combined), sum them for the A1-A3 total.
   • Units are standardized: GWP = kg CO2e, ODP = kg CFC-11e, AP = kg SO2e (or mol H+ eq for +A2), EP = kg PO4e (or mol N eq / kg P eq for +A2), POCP = kg C2H4e (or kg NMVOC eq for +A2).

5. Extract resource use — PERE, PENRE, fresh water, waste. Usually in a separate table following the impact indicators.

6. Extract additional data — recycled content %, manufacturing plant, country of origin, LCA software, verifier name.

7. Determine LEED eligibility — based on EPD type and verification status.

8. Leave fields blank rather than guessing — if a field isn't in the EPD, leave it empty.

Multi-product EPDs

Some EPDs declare impacts for multiple products, product groups, or concrete mix designs. Create one row per product/variant:

• If the EPD covers "Product A" and "Product B" with separate impact tables, create two rows
• If the EPD covers multiple concrete mixes (e.g., 3000 PSI, 4000 PSI, 5000 PSI), create one row per mix
• The product name should distinguish variants: "ReadyMix Concrete — 4000 PSI"

Step 4: Present results

Show a summary table for each parsed EPD:

## EPD Parse Results

### holcim-readymix-epd.pdf
| Field | Value |
|-------|-------|
| Product | ReadyMix Concrete — 4000 PSI |
| Manufacturer | Holcim |
| Declared Unit | 1 m3 |
| GWP (A1-A3) | 312 kg CO2e |
| System Boundary | Cradle-to-gate |
| Program Operator | NSF |
| Valid | 2024-01-15 to 2029-01-15 |
| LEED Eligible | Yes |

Products extracted: 3 (3000 PSI, 4000 PSI, 5000 PSI)

Ask: "Does this look correct? Should I adjust anything before saving?"

Step 5: Write output

Ask the user (if not already specified): "Where should I save this?"

Options:

• EPD Google Sheet — append rows to a dedicated EPD spreadsheet (separate from the FF&E product library). Ask for spreadsheet ID if not already known.
• Local CSV — save to a specified path (default: ~/Documents/Alpaca Labs/{client}/Working/epd-data-YYYY-MM-DD.csv)
• Just the table — leave as markdown in the conversation

CSV Format

When saving to CSV, use the 42-column header:

EPD Link,Manufacturer,Product Name,Description,Declared Unit,Functional Unit,CSI Division,Material Category,EPD Registration No.,Program Operator,PCR Reference,PCR Expiry,Standard,System Boundary,Valid From,Valid To,GWP-total (A1-A3),GWP-fossil (A1-A3),GWP-biogenic (A1-A3),ODP (A1-A3),AP (A1-A3),EP (A1-A3),GWP (A4-A5),GWP (B1-B7),GWP (C1-C4),GWP (D),GWP-total (all stages),POCP (A1-A3),PERE (A1-A3),PENRE (A1-A3),Total Energy (A1-A3),FW (A1-A3),Recycled Content,Waste (A1-A3),LEED Eligible,EC3 ID,Plant/Facility,Country,Parsed At,Tags,Notes,Source

Edge Cases

• Scanned PDFs (image-only): PyMuPDF will return empty or garbage text. Detect this (very short text relative to page count) and tell the user: "This PDF appears to be scanned/image-based. Text extraction won't work — consider using an OCR tool first."
• Non-English EPDs: Common for European manufacturers (German, French, Spanish, Swedish). Impact indicator abbreviations (GWP, ODP, AP, EP, POCP) are the same internationally. Extract numeric data regardless; note the language in Notes.
• EN 15804+A1 vs +A2: Older EPDs use +A1 (single GWP row, different EP/AP units). Newer use +A2 (split GWP, different units for AP/EP/POCP). Always note which version in Notes. Map to schema as closely as possible.
• Multi-product EPDs: One row per product/variant. See Multi-product EPDs section above.
• Expired EPDs: Flag in Notes: EXPIRED — valid to YYYY-MM-DD. Still parse the data.
• Password-protected PDFs: PyMuPDF will fail to open. Catch the error and tell the user.
• Very large PDFs (50+ pages): Process in 15-page chunks. Give progress updates.
• EPDs with impact tables as images: Detect missing numeric data in what should be table sections. Flag: "Impact tables may be embedded as images — manual extraction needed."

Error Reporting

After processing, always report:

Parsed: X products from Y EPD PDF(s)
- filename.pdf: N products extracted
- filename2.pdf: M products extracted
Issues: [list any problems — expired, scanned, missing tables, etc.]