The most common objection restoration contractors raise to Scope 3 emissions reporting is that it requires tracking data they don’t have. In most cases, the data exists — it’s just not being retained in a form usable for emissions calculation. The RCP 12-point standard formalizes what every job ticket should contain.
Group 1: Transportation Data (Category 4)
Data point 1 — Vehicle log: For each vehicle used (crew vehicles, equipment trailers, pack-out trucks, heavy equipment), record vehicle type, number of round trips to the job site, and round-trip mileage. Source: dispatch records, GPS fleet data, or driver logs.
Data point 2 — Waste transport log: Separately from crew/equipment transportation, record vehicle type, trips, and mileage for all waste hauling — to landfills, transfer stations, hazmat facilities, or wastewater treatment facilities. Often omitted from job documentation when waste hauling is subcontracted, but emissions belong to the job regardless.
Data point 3 — Equipment power source: Document whether drying/filtration/processing equipment operated on building electrical supply or contractor-supplied generators. If generators, record fuel type and quantity consumed. Determines whether equipment energy is Scope 2 (building electricity, property owner) or included in contractor’s Scope 3 calculation.
Group 2: Materials Data (Category 1)
Data point 4 — Chemical treatments log: Volume of each chemical product applied: antimicrobials (liters by product type), biocides, encapsulants, deodorizing compounds, wetting agents. Can be estimated from square footage and application rate if purchase records are not job-specific.
Data point 5 — PPE consumption log: Units of disposable PPE consumed: Tyvek suits, gloves (pairs), N95/P100 respirators, boot covers, eye protection. Can be reconstructed from supply orders or estimated from job duration and crew size using standard consumption rates.
Data point 6 — Containment materials log: Meters of polyethylene sheeting, number of zipper doors installed, HEPA filter media units replaced. Primarily relevant for mold remediation, hazmat abatement, and Category 3 water damage.
Group 3: Waste Data (Category 5)
Data point 7 — Debris volume by waste category: Weight or volume by category: standard C&D debris (tons), regulated hazardous materials (tons by type), contaminated water (liters or gallons). Source: disposal facility receipts, dumpster manifests, or tank/extractor volume logs.
Data point 8 — Disposal method and facility: For each waste category, record the disposal facility used and disposal method (landfill, recycling, hazmat incineration, wastewater treatment). Facility name is sufficient — national average emission factors apply where facility-specific factors are unavailable.
Group 4: Demolished Materials (Category 12) and Context
Data point 9 — Demolished materials log by type: Weight of each building material type removed: drywall (tons), flooring by type, insulation by type (tons), wood framing (tons). Source: demolition scope documentation, dumpster weight receipts.
Data point 10 — Installed replacement materials (reconstruction only): Weight of new building materials installed if reconstruction is within the contractor’s scope. Available from purchase orders or materials delivery receipts.
Data point 11 — Job classification: Job type, damage category/class, affected area in square feet, building construction type (pre/post-1980 for hazmat assumptions).
Data point 12 — Job timeline: Start date, completion date, client property identifier. Assigns emissions to the correct reporting year and property for portfolio-level Scope 3 inventory.
What if some data points are unavailable?
Use RCP’s proxy estimation methodology — standard consumption rates by job type and damage class. Document which data points were estimated and the basis for each estimate. A documented estimate is far more useful to your client than no data.
Who should be responsible for capturing these data points?
Data points 1-3 and 11-12 at the project management level. Data points 4-10 may require field crew input. Designating a data capture owner at job setup and building capture into the close-out checklist is the most reliable approach.
Can existing job management software capture these data points?
Most major restoration platforms (ServiceMonster, Xactimate, Jonas) can accommodate these as custom fields. The RCP will publish integration guidance for common platforms as the standard matures.
What Good vs. Poor Data Capture Looks Like for Each Data Point
The difference between an RCP record that passes third-party verification and one that gets flagged is almost always documentation quality, not calculation complexity. The following examples show what each data point looks like when captured well versus when it is reconstructed or estimated poorly.
Data Point 1 — Vehicle Log
Good: Fleet GPS system exports a trip report showing: Vehicle ID TRK-04, diesel Sprinter, 3 round trips to 1200 Commerce Blvd Sacramento, 47.2 miles per round trip, 141.6 total miles. Timestamps confirm trips align with job dates.
Poor: “We sent two trucks, probably drove about 50 miles each way a few times.” No vehicle types, no trip count, no documentation. Requires complete reconstruction from memory — high uncertainty, won’t survive audit review.
Data Point 2 — Waste Transport Log
Good: Disposal facility receipt showing: Sacramento County Transfer Station, 2026-03-22, 1.8 short tons C&D debris received, facility address 8 miles from job site. Haul vehicle identified as dump truck (diesel).
Poor: Subcontractor handled debris removal, no manifest obtained. Waste weight unknown. RCP proxy required: estimate from affected square footage using 0.75 lbs/sqft standard C&D rate. Flag as proxy in data quality section.
Data Point 3 — Equipment Power Source
Good: Job notes confirm equipment operated on building electrical service, Circuit 14 in mechanical room. Tenant confirmed access in writing. No generator deployed. Equipment energy excluded from contractor’s Category 4 (attributed to building owner’s Scope 2).
Poor: Unknown whether generator was used. If generator use is unconfirmed, RCP default is to assume building power and exclude from contractor calculation, noting the assumption in data quality notes.
Data Point 4 — Chemical Treatments Log
Good: Field technician log: 12 liters Benefect Botanical Disinfectant applied across 2,400 sqft per IICRC protocol. Product lot number recorded. Purchase receipt available.
Poor: “We used some antimicrobial, not sure how much.” Apply RCP proxy: 0.005 liters per sqft for Category 2 commercial job = 12 liters estimated. Flag as proxy. Note product type unknown — use default antimicrobial emission factor.
Data Point 5 — PPE Consumption Log
Good: Supply requisition for this job: 18 Tyvek suits, 36 glove pairs, 24 N95 respirators, 12 pairs boot covers. Matched against job crew size (3 techs × 6 days).
Poor: No PPE tracking by job. Use RCP standard consumption rate: Category 2, Class 3, 3-tech crew × 6 days = 18 Tyvek, 36 gloves, 24 N95 (standard table). Flag as proxy rate.
Data Point 6 — Containment Materials Log
Good: Pre-job setup photo documentation shows poly sheeting perimeter. Close-out notes: 40 linear meters 6-mil poly, 2 zipper doors, 4 HEPA filter replacements during job.
Poor: No containment used — Category 1 water loss, no containment required. Record as zero, not as missing data. Explicitly noting why a field is zero is different from leaving it blank.
Data Point 7 — Debris Volume by Waste Category
Good: Dumpster manifest: 1.5 tons drywall debris + 0.3 tons flooring debris = 1.8 tons total C&D. Weight confirmed by disposal facility ticket.
Poor: No manifest. Estimate from demolition scope: 180 sqft drywall removed (½” = 2.2 lbs/sqft × 180 = 396 lbs = 0.20 tons), 80 sqft carpet removed (carpet weight 0.75 lbs/sqft × 80 = 60 lbs). Total proxy: 0.26 tons. Flag as estimated — significantly lower than manifest weight if heavier debris present.
Data Point 8 — Disposal Method and Facility
Good: All C&D debris → Sacramento County Transfer Station (municipal landfill). Hazmat materials → none (Category 1, no regulated waste). Water extraction discharged to building drain per property manager approval.
Poor: “Trash went to the dump.” Technically usable — national average landfill emission factor applies. But facility name enables verification and future use of facility-specific factors when available.
Data Point 9 — Demolished Materials Log by Type
Good: Demolition scope from job file: 180 sqft drywall (½” standard) = 900 kg, 80 sqft nylon carpet = 180 kg. Source: field measurement records and material weight lookup table.
Poor: Dumpster load size only — “one dumpster full.” Apply proxy: standard 10-yard dumpster ≈ 1.5 tons mixed C&D. No material type breakdown available. Use mixed C&D emission factor, flag as proxy.
Data Point 10 — Installed Replacement Materials
Good: Purchase orders from supplier: 180 sqft drywall delivered (36 sheets ½” × 4×8 = 36 × 26 kg = 936 kg), 80 sqft carpet (1 roll = 200 kg). Reconstruction within contractor scope confirmed in job contract.
Poor: Reconstruction handled by property owner’s GC — outside contractor scope. Record as “reconstruction out of scope” with note. Do not estimate — these are the owner’s Category 1 emissions, not the contractor’s.
Data Point 11 — Job Classification
Good: Job type: water_damage. Damage category: 2. Damage class: 3. Affected area: 2,400 sqft. Building type: commercial office, post-1980 construction (no asbestos assumed per local building records). Classification documented at initial assessment.
Poor: Job type recorded, damage category/class not assessed or not recorded. Without class, equipment calculation defaults to Class 2 proxy — may significantly understate or overstate actual equipment deployment. Always classify at initial assessment.
Data Point 12 — Job Timeline
Good: Job start: 2026-03-14 (initial response). Job completion: 2026-03-22 (final moisture readings, equipment pickup, client sign-off). Emissions attributed to Q1 2026 reporting period for client’s ESG inventory.
Poor: Only month recorded. For portfolio-level ESG reporting, commercial clients need the ability to assign job emissions to specific reporting quarters and fiscal years. Date precision to the day is required.
How Each Data Point Maps to the Emissions Calculation
The following table makes the calculation pipeline explicit. Each data point feeds one or more specific emission factor applications. Software developers implementing RCP should treat this as the calculation dependency map.
|
|
| Data Point |
GHG Protocol Category |
Emission Factor Applied |
Output |
| 1 — Vehicle log |
Category 4 |
10.21 kg CO₂e/gal diesel or 8.89 kg/gal gasoline |
kg CO₂e, transportation |
| 2 — Waste transport log |
Category 4 |
0.186 kg CO₂e/ton-mile (truck freight) |
kg CO₂e, haul transport |
| 3 — Equipment power source |
Category 1 (if building power) or Category 4 (if generator) |
0.3499 kg CO₂e/kWh (grid) or fuel factor (generator) |
kg CO₂e, equipment energy |
| 4 — Chemical treatments |
Category 1 |
2.8 kg CO₂e/liter antimicrobial (default) |
kg CO₂e, materials |
| 5 — PPE consumption |
Category 1 |
Standard rate per unit type (RCP Table 3A) |
kg CO₂e, materials |
| 6 — Containment materials |
Category 1 |
0.22 kg CO₂e/meter poly sheeting |
kg CO₂e, materials |
| 7 — Debris volume by type |
Category 5 |
0.021 tCO₂e/ton mixed C&D (EPA WARM v16) |
tCO₂e, waste disposal |
| 8 — Disposal method/facility |
Category 5 |
Selects landfill vs. recycling vs. incineration factor |
Factor selector, not a numeric input |
| 9 — Demolished materials by type |
Category 12 |
0.12 kg CO₂e/kg drywall; 5.40/kg carpet; etc. |
kg CO₂e, end-of-life materials |
| 10 — Replacement materials |
Category 1 |
Same factors as demolished materials by type |
kg CO₂e, materials (if in scope) |
| 11 — Job classification |
All categories |
Selects job-type proxy rates when primary data is unavailable |
Proxy rate selector |
| 12 — Job timeline |
All categories |
Assigns emissions to reporting period; determines equipment runtime hours |
Period assignment; runtime calculation input |
Building Data Capture Into Your Job Management Workflow
The most reliable RCP implementations don’t ask techs to fill out extra forms — they build data capture into the existing job workflow. Three integration points cover most of the 12 data points without adding steps:
At job setup (Data Points 3, 11, 12): Job classification, power source determination, and start date are all known at mobilization. These should be required fields in the job creation screen of any job management system.
At daily monitoring check-in (Data Points 1, 3): GPS fleet data or odometer entry captures vehicle mileage passively. Equipment runtime hours accumulate between setup and retrieval timestamps already recorded in the system.
At job close-out (Data Points 2, 4, 5, 6, 7, 8, 9, 10, 12): The close-out checklist is the natural capture point for waste manifests, material quantities, PPE counts, and completion date. Adding RCP fields to the close-out checklist is the single highest-impact implementation step.
Platforms that implement close-out checklist capture for RCP data — Encircle, PSA, Dash, and Xcelerate among them — can produce a complete 12-point RCP record as a byproduct of normal job documentation. No additional technician training is required beyond knowing what the fields mean.